METHODS AND COMPOSITIONS FOR DIAGNOSIS, MONITORING AND DEVELOPMENT OF THERAPEUTICS FOR TREATMENT OF ATHEROSCLEROTIC DISEASE

FIELD OF THE INVENTION

This application is in the field of atherosclerotic disease. In particular, this invention relates to methods and compositions for diagnosing, monitoring, and development of therapeutics for atherosclerotic disease.

BACKGROUND OF THE INVENTION

Atherosclerosis is the primary cause of heart disease and stroke (Kannel and Belanger (1991) Am. Heart J. 121:951-57), and is the most common cause of morbidity and mortality in the United States (NHLBI Morbidity and Mortality Chartbook, National Heart, Lung, and Blood Institute, Bethesda, Md., May, 2002; NHLBI Fact Book, Fiscal Year 2003, pp. 35-53, National Heart, Lung, and Blood Institute, Bethesda, Md., February, 2004). Atherosclerosis is currently conceptualized as a chronic inflammatory disease of the arterial vessel wall that develops due to complex interactions between the environment and the genetic makeup of an individual (Ross (1999) N Engl J Med 340:115-26). Development of an atherosclerotic plaque occurs in stages, beginning with simple fatty streak formation and culminating in complex calcified lesions containing abnormal accumulation of smooth muscle cells, inflammatory cells, lipids, and necrotic debris. It is likely that the various stages of atherosclerotic disease are governed by a set of genes that are expressed by a variety of cell types present in the vessel wall.

The propensity for developing atherosclerosis is dependent on underlying genetic risk, and varies as a function of age and exposure to environmental risk factors. However, despite the chronic nature of atherosclerotic disease, knowledge regarding temporal gene expression during the course of disease progression is very limited. The prolonged, chronic, and unpredictable nature of the disease in humans, by virtue of heterogeneous genetic and environment factors, has limited systematic temporal gene expression studies in humans.

The roles of a limited number of genes that are differentially expressed in vascular disease have been identified, and a few of these genes linked through mechanistic studies to disease processes (Glass and Witztum (2001) Cell 104:503-16; Breslow (1996) Science 272:685-88; Lusis (2000) Nature 407:233-41). Recent efforts to identify disease related gene expression patterns have employed transcriptional profiling with DNA microarrays. However, these studies have included relatively small arrays (Wuttge et al. (2001) Mol Med 7:383-392) as well as limited time points, with the primary comparison between normal and late stage diseased tissue (Archacki et al. (2003) Physiol Genomics 15:65-74; Faber et al. (2002) Curr Opin Lipidol 13:545-552; McCaffrey et al. (2000) J Clin Invest 105:653-662; Randi et al. (2003) J Throm Haemost 1:829-835; Seo et al. (2004) Arterioscler Thromb Vasc Biol 24:1922-1927; Zohlnhofer et al. (2001) Mol Cell 7:1059-1069. Utilizing microarrays in animal models, where a disease process can be studied over time, the impact of individual risk factors and perturbations on the expression of individual genes during disease development can be studied systematically without a priori knowledge of gene identity. The temporal expression patterns of the genes can then be correlated with the well-described disease stages.

There is a need for a comprehensive list of atherosclerosis-related genes that are predictive of atherosclerotic disease conditions, for use as diagnostic markers and for discovery of biochemical pathways involved in development of atherosclerotic disease and discovery and/or testing of new therapeutics.

BRIEF SUMMARY OF THE INVENTION

This invention provides compositions, methods, and kits for detection of gene expression, diagnosis, monitoring, and development of therapeutics with respect to atherosclerotic disease.

In one aspect, the invention provides a system for detecting gene expression, comprising at least two isolated polynucleotide molecules, wherein each isolated polynucleotide molecule detects an expressed gene product from a gene that is differentially expressed in atherosclerotic disease in a mammal. In one embodiment, the differentially expressed gene is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the differentially expressed gene is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 1-927. In various embodiments, a system for detecting gene expression comprises any of at least 3, 5, 10, 15, 20, 25, 30, 35, 40, 50, 60, 70, 80, 90, or 100 of the isolated polynucleotide molecules described herein or their polynucleotide complements, or human homologs or orthologs thereof. In one embodiment, the gene expression system comprises at least two isolated polynucleotide molecules, wherein each isolated polynucleotide molecule detects an expressed gene product, wherein the gene is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 1-927, wherein the gene is differentially expressed in atherosclerotic disease in a mammal, and wherein the gene expression system comprises at least 1, 3, 5, 10, 15, 20, 25, or 30 isolated polynucleotide molecules that detect genes corresponding to the polynucleotide sequences selected from the group consisting of SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927.

In some embodiments, the isolated polynucleotide molecules are immobilized on an array, which may be selected from the group consisting of a chip array, a plate array, a bead array, a pin array, a membrane array, a solid surface array, a liquid array, an oligonucleotide array, a polynucleotide array, a cDNA array, a microtiter plate, a membrane, and a chip. The isolated polynucleotide molecules may be selected from the group consisting of synthetic DNA, genomic DNA, cDNA, RNA, or PNA. A gene corresponding to an isolated polynucleotide molecules described herein may be differentially expressed in any blood vessel or portion thereof which has developed an atherosclerotic or inflammatory disease, for example, the aorta, a coronary artery, the carotid artery, or a blood vessel of the peripheral vasculature.

In another aspect, the invention provides a kit comprising a system for detecting gene expression as described above. In one embodiment, the kit comprises an array comprising a system for detecting gene expression as described above.

In another aspect, the invention provides a method of detecting gene expression, comprising contacting products of gene expression with the system for detecting gene expression as described above. In one embodiment, the method comprises isolating mRNA, for example from a sample from individual who has or who is suspected of having an atherosclerotic disease, and hybridizing the RNA to the polynucleotide molecules from the system for detecting gene expression. In another embodiment, the method comprises isolating mRNA, converting the RNA to nucleic acid derived from the RNA, e.g., cDNA, and hybridizing the nucleic acid derived from the RNA to the polynucleotide molecules of the system for detecting gene expression. Optionally, the RNA may be amplified prior to hybridization to the system for gene expression. Optionally, the RNA is detectably labeled, and determination of presence, absence, or amount of an RNA molecule corresponding to a gene detected by a polynucleotide molecule of the system for detecting gene expression comprises detection of the label.

In another embodiment, the method for detecting gene expression comprises isolating proteins from an individual who has or who is suspected of having an atherosclerotic disease, and detecting the presence, absence, or amount of one or more proteins corresponding to the gene expression product of a gene that is differentially expressed in atherosclerotic disease and corresponds to a polynucleotide molecule of the system for detecting gene expression as described above. Detection may be via an antibody that recognizes the protein, for example, by contacting the isolated proteins with an antibody array.

In another aspect, the invention provides a method for diagnosing an atherosclerotic disease in an individual, comprising contacting polynucleotides derived from a sample from the individual with a system for detecting gene expression as described above. In one embodiment, the method comprises detecting hybridization complexes formed, if any, wherein presence, absence or amount of hybridization complexes formed from at least one of the polynucleotides from the individual is indicative of presence or absence of the atherosclerotic disease. In another embodiment, the method comprises comparing levels of expression of the genes with a molecular signature indicative of the presence or absence of the atherosclerotic disease.

In another aspect, the invention provides a method for assessing extent of progression of atherosclerotic disease in an individual, comprising contacting polynucleotides derived from a sample from the individual with a system for detecting gene expression as described above. In one embodiment, the method comprises detecting hybridization complexes formed, if any, wherein presence, absence or amount of hybridization complexes formed from at least one of the polynucleotides from the individual is indicative of extent of progression of the atherosclerotic disease. In another embodiment, the method comprises detecting hybridization complexes formed, if any, and comparing levels of expression of the genes with a molecular signature indicative of extent of progression of the atherosclerotic disease.

In another aspect, the invention provides a method of assessing efficacy of treatment of atherosclerotic disease in an individual, comprising contacting polynucleotides derived from a sample from the individual with a system for detecting gene expression as described above. In one embodiment, the method comprises detecting hybridization complexes formed, if any, wherein presence, absence or amount of hybridization complexes formed from at least one of the polynucleotides from the individual is indicative of extent of progression of the atherosclerotic disease. In another embodiment, the method comprises comparing levels of expression of the genes with a molecular signature indicative of extent of progression of the atherosclerotic disease.

In another aspect, the invention provides a method for determining prognosis of atherosclerotic disease in an individual, comprising contacting polynucleotides derived from a sample from the individual with a system for detecting gene expression as described above. In one embodiment, the method comprises detecting hybridization complexes formed, if any, wherein presence, absence or amount of hybridization complexes formed from at least one of the polynucleotides from the individual is indicative of prognosis of the atherosclerotic disease. In another embodiment, the method comprises comparing levels of expression of the genes with a molecular signature indicative of prognosis of the atherosclerotic disease.

In another aspect, the invention provides a method for identifying a compound effective to treat an atherosclerotic disease, comprising administering a test compound to a mammal with an atherosclerotic disease condition and contacting polynucleotides derived from a sample from the mammal with a system for detecting gene expression as described above. In one embodiment, the method comprises detecting hybridization complexes formed, if any, wherein presence, absence or amount of hybridization complexes formed from at least one of the polynucleotides from the individual is indicative of treatment of the disease. In another embodiment, the invention comprises detecting hybridization complexes formed, if any, and comparing levels of expression of the genes with a molecular signature indicative of treatment of the disease.

In another aspect, the invention provides a method of monitoring atherosclerotic disease in a mammal, comprising detecting the expression level of at least one, at least two, at least ten, at least one hundred, or more genes selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 1-927. In some embodiments, at least one of the genes for which expression level is detected is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In one embodiment, the atherosclerotic disease comprises coronary artery disease. In one embodiment, the atherosclerotic disease comprises carotid atherosclerosis. In one embodiment, the atherosclerotic disease comprises peripheral vascular disease. In some embodiments, the expression level of said gene(s) is detected by measuring the RNA expression level. In one embodiment, RNA is isolated from the individual prior to detection of the RNA expression level. Measurement of RNA expression level may comprise amplifying RNA from an individual, for example, by polymerase chain reaction (PCR), using a primer that is complementary to a polynucleotide sequence corresponding to a gene to be detected, wherein the gene corresponds to a polynucleotide sequence selected from the group of genes depicted in SEQ ID NOs: 1-927. In some embodiments, a primer is used that is complementary to a polynucleotide sequence corresponding to a gene to be detected, wherein the gene corresponds to a polynucleotide sequence selected from the group of genes depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. Measurement of RNA expression level may comprise hybridization of RNA from the individual to a polynucleotide corresponding to a gene to be detected, wherein the gene corresponds to a polynucleotide sequence selected from the group of genes depicted in SEQ ID NOs: 1-927. In some embodiments, RNA from the individual is hybridized to a polynucleotide corresponding to a gene to be detected, wherein the gene to be detected is selected from the group of genes depicted in 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In some embodiments, gene expression level is detected by measuring the expressed protein level. In some embodiments, the method further comprises selecting an appropriate therapy for treatment or prevention of the atherosclerotic disease. In some embodiments, gene expression level, for example, RNA or protein level, is detected in serum from an individual.

In another aspect, the invention provides a method of monitoring atherosclerotic disease in an individual, comprising detecting RNA expressed from at least one gene selected from the group of genes corresponding to at least one polynucleotide sequence depicted in SEQ ID NOs:1-927. In one embodiment, the at least one gene is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In one embodiment, the method comprises measuring the expressed RNA in serum from the individual.

In another aspect, the invention provides a method of monitoring atherosclerotic disease in an individual, comprising detecting protein expressed from at least one gene selected from the group of genes corresponding to at least one polynucleotide sequence depicted in SEQ ID NOs:1-927. In one embodiment, the at least one gene is selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In one embodiment, the method comprises measuring the expressed protein in serum from the individual.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 depicts the experimental design of the experiments described in Example 1. ApoE deficient mice (C57BL/6J-Apoe^5m1Unc), were fed non-cholate-containing high-fat diet from 4 weeks of age for a maximum period of 40 weeks. Aortas were obtained for transcriptional profiling at pre-determined time intervals corresponding to various stages of atherosclerotic plaque formation. For each time point, aortas from 15 mice were combined into 3 pools for microarray replicate studies. To eliminate gene expression differences due to aging, diet, and genetic differences, a number of control groups were also used at each time point, including apoE deficient mice on normal chow, aw well as C57B1/6 and C3H/HeJ wild type mice on both normal and atherogenic diets.

FIG. 2 depicts quantification of atherosclerotic disease in the experiments described in Example 1. Percent lesion area was determined by calculating the ratio of atherosclerotic area versus total surface area of the aorta. ApoE-deficient mice (n=7) on high-fat diet were compared to other control mice (n=5-7 for each mouse/diet combination). Representative time intervals were used for analysis, including baseline (TOO) measurements in mice prior to initiation of diet at 4 weeks of age and end point measurements corresponding to 40 weeks (T40) on either high-fat or normal diet. At TOO, three were no statistically significant differences in lesion area among the various conditions. At 40 weeks on high-fat diet, the controls did not develop any lesions. In contrast to the control mice, the ApoE-deficient mice on normal chow and on high-fat diet had significantly larger atherosclerotic area (14.00%+/−3.92%, p<0.0001, and 37.98%+/−6.3%, p<0.0001, respectively.)

FIG. 3 depicts atherosclerosis genes identified in the experiments described in Example 1. Employing a newly-developed statistical algorithm which relies on permutation analysis and generalized regression, atherosclerosis-related genes were identified. Selecting the genes on the basis of their false detection rate (FDR <0.05) and depicting their expression with a heatmap (ordered by hierarchical clustering), demonstrates profiles which closely correlate with disease progression. The heatmap is a graphic representation of expression patterns of 6 parallel time course studies with time progressing from left to right for each of the 6 sets of strain-diet combination. Each set of the strain-diet combination therefore contains 15 columns (3 for each of 5 time points). Each row represents the row normalized expression pattern of a single gene. The dominant temporal pattern of expression is one that increases linearly with time (667 genes). Fewer genes (64) reveal an opposite pattern. HF: high-fat diet; NC: normal chow.

FIG. 4 depicts time-related patterns of gene expression in atherosclerosis observed in the experiments described in Example 1. Using AUC analysis, a number of distinct time-related patterns of gene expression in ApoE-deficient mice on high-fat diet were observed. Eight different time-related patterns are depicted, with the y-axis representing normalized gene expression values and the x-axis representing 6 different time points from time 0 to 40 weeks. The genes in each pattern were clustered based on positive correlation values. The mean distance of genes from the center of each cluster is noted in parentheses for each pattern. Using enrichment analysis for each cluster of genes, specific pathways were found to be associated with these patterns that reflect particular biological processes.

FIG. 5 depicts the identification and validation of mouse atherosclerotic disease classifier genes as determined in the experiments described in Example 1. FIG. 5A depicts identification of the classification gene set. The SVM algorithm described in Example 1 was employed to rank genes based on their abilities to accurately discriminate between 5 time points in ApoE-deficient mice on high-fat diet. An optimal set of 38 genes was identified to classify the experiments at a minimal error rate of 15%. The optimal 15% error rate was determined with a 1000 step cross-validation method with 25% of the experiments employed as the test group and the rest as the training group. FIG. 5B depicts classification of an independent mouse atherosclerosis data set. Aortas of ApoE-deficient mice aged 16 weeks were used for gene expression profiling utilizing a different microarray and labeling protocol than in the experiment depicted in FIG. 5A. Using the SVM algorithm, where known experiments were the five time points in the original experimental design and the independent set of experiments was the test set, these mice most closely classified with the 24 week time point. SVM scores for each experiment based on one-versus-all comparisons are represented graphically in a heatmap.

FIG. 6 depicts expression of atherosclerosis-related genes in human coronary artery disease, as described in Example 1. To investigate the expression profile of differently regulated mouse genes in human coronary artery atherosclerosis, 40 coronary artery samples with and without atherosclerotic lesions were used for transcriptional profiling. Atherosclerosis-associated mouse genes were matched to human orthologs/homologs by gene symbol and by known homology, and their expression was compared in human atherosclerotic plaques classified as lesion versus no lesion (SAM FDR<0.025). The expression of the top genes is represented graphically as a heatmap, where rows represent row normalized expression of each gene and the columns represent coronary artery samples. Calculated SAM FDR<0.009 for d-score 4.25-2.45, FDR<0.015 for d-score 2.41-2.357, FDR<0.025 for d-score 2.33-2.05.

FIG. 7 depicts the experimental design of the experiments described in Example 2. FIG. 7A: Four-week-old female C3H/HeJ (C3H) and C57B16 (C57) mice were fed normal chow vs. high-fat diet for the maximum period of 40 weeks. Triplicate microarray experiments were performed for each time point using 3 pools of 5 aortas at 0, 4, 10, 24, and 40 weeks on either diet (total of 15 mice per time point). FIG. 7B: Data analysis overview. Of the 20,283 genes present on the array, 311 genes were found to be significantly differentially expressed between C3H and C57 mice at baseline (SAM FDR 10% and >1.5-fold change). Differential gene expression during aging was determined by comparing C57 vs. C3H time-course differences on normal and atherogenic high-fat diets using AUC analysis.

FIG. 8 depicts differential gene expression between C3H and C57 mice at baseline. The SAM analysis shown was associated with an FDR of 10%, and a total of 311 probes were identified as differentially regulated at this level of confidence. Lists represent a select group of genes (expressed sequence tags excluded) with higher expression in C3H (top 20 ranking genes) and C57 (top 45 ranking genes). The heatmap reflects normalized gene expression ratios and is organized with individual hybridizations for each of the 3 replicates for each mouse strain arranged along the x axis.

FIG. 9 depicts differential gene expression between C3H and C57 mice in response to normal aging. FIG. 9A: Response to aging was determined by comparing C57 vs. C3H time-course differences on normal diet (AUC analysis F statistic>10). FIG. 9B: Functional annotation of the 413 differentially expressed genes reveals differences in various biological processes, including growth and differentiation. The probability rates provided area based on Fisher exact test (P<0.02). FIG. 9C: K-means clustering of the 413 genes reveals several profiles of gene expression. Clusters 1, 4, and 9 reveal increased gene expression in C3H vs. C57 mice, whereas clusters 2, 6, and 14 reveal the opposite pattern.

FIG. 10 depicts differential gene expression between C3H and C57 mice in response to high-fat diet. FIG. 10A: Response to atherogenic stimulus was determined by comparing C57 vs. C3H time-course differences on high-fat diet (AUC analysis F statistic>10). FIG. 10B: Functional annotation of the 509 differentially expressed genes reveals differences in various biological processes and cellular components. The probability rates provided are based on Fisher exact test (P<0.02). FIG. 10C: K-means clustering of the 509 differentially expressed genes revealed several patterns of gene expression with clusters 3 and 9 exhibiting increased gene expression in C3H vs. C57 mice and clusters 8 and 10 with the opposite pattern.

FIG. 11 shows the results of evaluation in the apoE knockout model of genes identified as differentially expressed between C3H and C57 strains. FIG. 11A: ApoE knockout mice (C57BL/6J-Apoe^tmlUnc) were fed normal chow versus high-fat diet for the maximum period of 40 weeks. Triplicate microarray experiments were preformed for each time point using 3 pools of 5 aortas at 0, 4, 10, 24, and 40 weeks for regular and high-fat diet groups (total of 15 mice per time point). SOMs were used to visualize patterns of expression of genes of interest. Genes which were differentially regulated by aging (FIG. 9, K-means clusters 1, 4, and 9 with higher expression in C3H and clusters 4, 6, and 14 with higher expression in C57) and genes identified with atherogenic stimuli (FIG. 10, K-means clusters 3 and 9 with higher expression in C3H and clusters 8 and 10 with opposite pattern) as well as genes which were differentially expressed at the baseline time point (FIG. 8), were grouped and their expression was studied using SOM analysis. SOM analysis reveals diverse patterns of expression of these genes throughout the development of atherosclerosis in apoE knockout mice. Cluster 8 contains genes that are consistently increasing in expression with progression of atherosclerosis. Pie charts reflect the analysis group from which the genes populating each cluster were derived. The relative size of sectors of the pie chart indicates the relative number of genes that are derived from the various staging groups. FIG. 11B lists genes with higher expression in C57 mice at baseline and in C3H mice at baseline or on a high fat diet.

DETAILED DESCRIPTION OF THE INVENTION

The invention provides polynucleotide sequences that correspond to genes that are differentially expressed in atherosclerotic disease conditions, and methods for using these sequences to detect gene expression and/or for transcriptional profiling in mammals. The polynucleotide sequences provided herein may be used, for example, to diagnose, assess extent of progression, assess efficacy of treatment of, to determine prognosis of, and/or to identify compounds effective to treat an atherosclerotic disease condition. The polynucleotide sequences herein may also be used in methods for elucidation of biochemical pathways that are involved in development and/or maintenance of atherosclerotic disease conditions.

General Techniques

The practice of the present invention will employ, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, and biochemistry, which are within the skill of the art. Such techniques are explained fully in the literature, such as: Molecular Cloning: A Laboratory Manual, vol. 1-3, third edition (Sambrook et al., 2001); Oligonucleotide Synthesis (M. J. Gait, ed., 1984); Methods in Enzymology (Academic Press, Inc.); Current Protocols in Molecular Biology (F. M. Ausubel et al., eds., 1987); PCR Cloning Protocols, (Yuan and Janes, eds., 2002, Humana Press).

In addition to the above references, protocols for in vitro amplification techniques, such as the polymerase chain reaction (PCR), the ligase chain reaction (LCR), Qβ-replicase amplification, and other RNA polymerase mediated techniques (e.g., NASBA), useful, e.g., for amplifying oligonucleotide probes of the invention, are found in Mullis et al., U.S. Pat. No. (1987) 4,683,202; PCR Protocols: A Guide to Methods and Applications (Innis et al., eds.) Academic Press, Inc., San Diego, Calif. (1990); Arnheim and Levinson (1990) C&EN 36; The Journal of NIH Research (1991) 3:81; Kwoh et al. (1989) Proc Natl Acad Sci USA 86:1173; Guatelli et al. (1990) Proc Natl Acad Sci USA 87:1874; Lomell et al. (1989) J Clin Chem 35:1826; Landegren et al. (1988) Science 241:1077; Van Brunt (1990) Biotechnology 8:291; Wu and Wallace (1989) Gene 4:560; Barringer et al. (1990) Gene 89:117; Sooknanan and Malek (1995) Biotechnology 13:563. Additional methods, useful for cloning nucleic acids, include Wallace et al., U.S. Pat. No. 5,426,039. Improved methods of amplifying large nucleic acids by PCR are summarized in Cheng et al. (1994) Nature 369:684, and the references therein.

DEFINITIONS

Unless defined otherwise, all scientific and technical terms are understood to have the same meaning as commonly used in the art to which they pertain. For the purpose of the present invention, the following terms are defined below.

As used herein, the term “gene expression system” or “system for detecting gene expression” refers to any system, device or means to detect gene expression and includes candidate libraries, oligonucleotide sets or probe sets.

The term “diagnostic oligonucleotide set” generally refers to a set of two or more oligonucleotides that, when evaluated for differential expression of their products, collectively yields predictive data. Such predictive data typically relates to diagnosis, prognosis, monitoring of therapeutic outcomes, and the like. In general, the components of a diagnostic oligonucleotide set are distinguished from nucleotide sequences that are evaluated by analysis of the DNA to directly determine the genotype of an individual as it correlates with a specified trait or phenotype, such as a disease, in that it is the pattern of expression of the components of the diagnostic nucleotide set, rather than mutation or polymorphism of the DNA sequence that provides predictive value. It will be understood that a particular component (or member) of a diagnostic nucleotide set can, in some cases, also present one or more mutations, or polymorphisms that are amenable to direct genotyping by any of a variety of well known analysis methods, e.g., Southern blotting, RFLP, AFLP, SSCP, SNP, and the like.

A “disease specific target oligonucleotide sequence” is a gene or other oligonucleotide that encodes a polypeptide, most typically a protein, or a subunit of a multi-subunit protein, that is a therapeutic target for a disease, or group of diseases.

A “candidate library” or a “candidate oligonucleotide library” refers to a collection of oligonucleotide sequences (or gene sequences) that by one or more criteria have an increased probability of being associated with a particular disease or group of diseases. The criteria can be, for example, a differential expression pattern in a disease state, tissue specific expression as reported in a sequence database, differential expression in a tissue or cell type of interest, or the like. Typically, a candidate library has at least 2 members or components; more typically, the library has in excess of about 10, or about 100, or about 500, or even more, members or components.

The term “disease criterion” is used herein to designate an indicator of a disease, such as a diagnostic factor, a prognostic factor, a factor indicated by a medical or family history, a genetic factor, or a symptom, as well as an overt or confirmed diagnosis of a disease associated with several indicators. A disease criterion includes data describing a patient's health status, including retrospective or prospective health data, e.g., in the form of the patient's medical history, laboratory test results, diagnostic test results, clinical events, medications, lists, response(s) to treatment and risk factors, etc.

The terms “molecular signature” or “expression profile” refers to the collection of expression values for a plurality (e.g., at least 2, but frequently at least about 10, about 30, about 100, about 500, or more) of members of a candidate library. In many cases, the molecular signature represents the expression pattern for all of the nucleotide sequences in a library or array of candidate or diagnostic nucleotide sequences or genes. Alternatively, the molecular signature represents the expression pattern for one or more subsets of the candidate library.

The terms “oligonucleotide” and “polynucleotide” and “nucleic acid,” used interchangeably herein, refer to a polymeric form of two or more nucleotides of any length and any three-dimensional structure (e.g., single-stranded, double-stranded, triple-helical, etc.), which contain deoxyribonucleotides, ribonucleotides, and/or analogs or modified forms of deoxyribonucleotides or ribonucleotides. Nucleotides may be DNA or RNA, and may be naturally occurring, or synthetic, or non-naturally occurring. A nucleic acid of the present invention may contain phosphodiester bonds or an alternate backbone, comprising, for example, phosphoramide, phosphorothioate, phosphorodithioate, O-methylphosphoroamidite linkages, and peptide nucleic acid backbones and linkages. The term polynucleotide includes peptide nucleic acids (PNA).

The terms “polypeptide,” “peptide,” and “protein” are used interchangeably herein to refer to a polymer of amino acid residues. The terms apply to amino acid polymers in which one or more amino acid residue is an analogue of a corresponding naturally occurring amino acid, as well as to naturally occurring amino acid polymers. The term also includes variants on the traditional peptide linkage joining the amino acids making up the polypeptide.

An “isolated” or “purified” polynucleotide or polypeptide is one that is substantially free of the materials with which it is associated in nature. By substantially free is meant at least 50%, preferably at least 70%, more preferably at least 80%, and even more preferably at least 90% free of the materials with which it is associated in nature.

As used herein, “individual” refers to a vertebrate, typically a mammal, such as a human, a nonhuman primate, an experimental animal, such as a mouse or rat, a pet animal, such as a cat or dog, or a farm animal, such as a horse, sheep, cow, or pig.

The term “healthy individual,” as used herein, is relative to a specified disease or disease criterion, e.g., the individual does not exhibit the specified disease criterion or is not diagnosed with the specified disease. It will be understood that the individual in question can exhibit symptoms, or possess various indicator factors, for another disease.

Similarly, an “individual diagnosed with a disease” refers to an individual diagnosed with a specified disease (or disease criterion). Such an individual may, or may not, also exhibit a disease criterion associated with, or be diagnosed with another (related or unrelated) disease.

An “array” is a spatially or logically organized collection, e.g., of oligonucleotide sequences or nucleotide sequence products such as RNA or proteins encoded by an oligonucleotide sequence. In some embodiments, an array includes antibodies or other binding reagents specific for products of a candidate library.

When referring to a pattern of expression, a “qualitative” difference in gene expression refers to a difference that is not assigned a relative value. That is, such a difference is designated by an “all or nothing” valuation. Such an all or nothing variation can be, for example, expression above or below a threshold of detection (an on/off pattern of expression). Alternatively, a qualitative difference can refer to expression of different types of expression products, e.g., different alleles (e.g., a mutant or polymorphic allele), variants (including sequence variants as well as post-translationally modified variants), etc.

In contrast, a “quantitative” difference, when referring to a pattern of gene expression, refers to a difference in expression that can be assigned a numerical value, such as a value on a graduated scale, (e.g., a 0-5 or 1-10 scale, a +−+++scale, a grade 1-grade 5 scale, or the like; it will be understood that the numbers selected for illustration are entirely arbitrary and in no-way are meant to be interpreted to limit the invention).

The term “monitoring” is used herein to describe the use of gene sets to provide useful information about an individual or an individual's health or disease status. “Monitoring” can include, for example, determination of prognosis, risk-stratification, selection of drug therapy, assessment of ongoing drug therapy, determination of effectiveness of treatment, prediction of outcomes, determination of response to therapy, diagnosis of a disease or disease complication, following of progression of a disease or providing any information relating to a patient's health status over time, selecting patients most likely to benefit from experimental therapies with known molecular mechanisms of action, selecting patients most likely to benefit from approved drugs with known molecular mechanisms where that mechanism may be important in a small subset of a disease for which the medication may not have a label, screening a patient population to help decide on a more invasive/expensive test, for example, a cascade of tests from a non-invasive blood test to a more invasive option such as biopsy, or testing to assess side effects of drugs used to treat another indication.

System for Detecting Gene Expression

The invention provides a system for detecting expression of genes that are differentially expressed in atherosclerotic disease. In one embodiment, the system for detecting gene expression detects at least two expressed gene products of genes selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the system for detecting gene expression detects at least two expressed gene products of genes selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 1-927. The term “corresponding” as used herein in the context of a gene corresponding to a polynucleotide sequence depicted in the Sequence Listing refers to a gene that is detectable by interaction of a product of expression of the gene (e.g., mRNA, protein) or a product derived from a product of expression of the gene (e.g., cDNA) with the system for detecting gene expression. The polynucleotide sequences represented by Sequence Identification Nos. 1-927 and accompanying identifying information are depicted in Table 1 below. These sequences have been shown to be differentially expressed in atherosclerosis in mice (see Example 1). The 60mer sequences represented in Table 1 are encompassed within the genes indicated therein. The gene sequences are obtainable from publicly available databases such as GenBank, and at http://www.ncbi.nlm.nih.gov or http://source.stanford.edu/cgi-bin/source/sourceSearch, using the identifying information provided in Table 1.

In one embodiment, the system for detecting gene expression includes at least two isolated polynucleotide molecules, each of which detects an expressed gene product of a gene that is differentially expressed in atherosclerotic disease in a mammal. The gene expression system includes at least two isolated polynucleotides that each comprise at least a portion of a sequence depicted in the Sequence Listing or its complement (i.e., a polynucleotide sequence capable of hybridizing to a sequence depicted in the sequence listing). A system for detecting gene expression in accordance with the invention may include any of at least 2, 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 polynucleotides each comprising at least a portion of a polynucleotide depicted in the Sequence Listing or a polynucleotide complement thereof.

It is understood that the polynucleotides of the invention may have slightly different sequences than those identified herein. Such sequence variations are understood to those of ordinary skill in the art to be variations in the sequence that do not significantly affect the ability of the sequences to detect gene expression. For example, homologs and variants of the polynucleotides disclosed herein may be used in the present invention. Homologs and variants of these polynucleotide molecules possess a relatively high degree of sequence identity when aligned using standard methods. Polynucleotide sequences encompassed by the invention have at least 40-50, 50-60, 70-80, 80-85, 85-90, 90-95 or 95-100% sequence identity to the sequences disclosed herein.

It is understood that for expression profiling, variations in the disclosed polynucleotide sequences will still permit detection of gene expression. The degree of sequence identity required to detect gene expression varies depending on the length of an oligonucleotide. For example, for a 60mer (i.e., an oligonucleotide with 60 nucleotides), 6-8 random mutations or 6-8 random deletions do not affect gene expression detection. Hughes, T. R., et al. (2001) Nature Biotechnology 19:343-347. As the length of the polynucleotide sequence is increased, the number of mutations or deletions permitted while still allowing gene expression detection is increased.

As will be appreciated by those skilled in the art, the sequences of the present invention may contain sequencing errors. For example, there may be incorrect nucleotides, frameshifts, unknown nucleotides, or other types of sequencing errors in any of the sequences; however, the correct sequences will fall within the homology and stringency definitions herein.

In some embodiments, polynucleotide molecules are less than about any of the following lengths (in bases or base pairs): 10,000; 5000; 2500; 2000; 1500; 1250; 1000; 750; 500; 300; 250; 200; 175; 150; 125; 100; 75; 50; 25; 10. In some embodiments, polynucleotide molecules are greater than about any of the following lengths (in bases or base pairs): 10; 15; 20; 25; 30; 40; 50; 60; 75; 100; 125; 150; 175; 200; 250; 300; 350; 400; 500; 750; 1000; 2000; 5000; 7500; 10,000; 20,000; 50,000. Alternately, a polynucleotide molecule can be any of a range of sizes having an upper limit of 10,000; 5000; 2500; 2000; 1500; 1250; 1000; 750; 500; 300; 250; 200; 175; 150; 125; 100; 75; 50; 25; or 10 and an independently selected lower limit of 10; 15; 20; 25; 30; 40; 50; 60; 75; 100; 125; 150; 175; 200; 250; 300; 350; 400; 500; 750; 1000; 2000; 5000; or 7500, wherein the lower limit is less than the upper limit.

The isolated polynucleotides of the system for detecting gene expression may include DNA or RNA or a combination thereof, and/or modified forms thereof, and/or may also include a modified polynucleotide backbone. In some embodiments, the isolated polynucleotides are selected from the group consisting of synthetic oligonucleotides, genomic DNA, cDNA, RNA, or PNA.

In one embodiment, the system for detecting gene expression comprises two antibody molecules or antigen binding fragments thereof, each of which detects an expressed gene product (e.g., a polypeptide) of a gene that is differentially expressed in atherosclerotic disease in a mammal.

As used herein, “atherosclerotic disease” refers to a vascular inflammatory disease characterized by the deposition of atheromatous plaques containing cholesterol, lipids, and inflammatory cells within the walls of large and medium-sized blood vessels, which can lead to hardening of blood vessels, stenosis, and thrombotic and embolic events. Atherosclerosis includes coronary vascular disease, cerebral vascular disease, and peripheral vascular disease. The term “atherosclerotic disease” as used herein includes any condition associated with atherosclerosis in a mammal in which differential gene expression may be detected by a system for detecting gene expression as described herein. Examples of such atherosclerotic disease conditions include, but are not limited to, coronary artery disease (e.g., stable angina, unstable angina, exertional angina, myocardial infarction, congestive heart failure, sudden cardiac death, atrial fibrillation), cerebral vascular disease (e.g., stroke, cerebrovascular accident (CVA), transient ischemic attack (TIA), cerebral infarction, cerebral intermittent claudication), peripheral vascular disease (e.g., claudications), extracranial carotid disease, carotid plaque, and carotid bruit.

Arrays

In some embodiments, a system for detecting gene expression in accordance with the invention is in the form of an array. “Microarray” and “array,” as used interchangeably herein, comprise a surface with an array, preferably ordered array, of putative binding (e.g., by hybridization) sites for a biochemical sample (target) which often has undetermined characteristics. In one embodiment, a microarray refers to an assembly of distinct polynucleotide or oligonucleotide probes immobilized at defined positions on a substrate. Arrays may be formed on substrates fabricated with materials such as paper, glass, plastic (e.g., polypropylene, nylon, polystyrene), polyacrylamide, nitrocellulose, silicon, optical fiber or any other suitable solid or semi-solid support, and configured in a planar (e.g., glass plates, silicon chips) or three-dimensional (e.g., pins, fibers, beads, particles, microtiter wells, capillaries) configuration. Probes forming the arrays may be attached to the substrate by any number of ways including (i) in situ synthesis (e.g., high-density oligonucleotide arrays) using photolithographic techniques (see, Fodor et al., Science (1991), 251:767-773; Pease et al., Proc. Natl. Acad. Sci. U.S.A. (1994), 91:5022-5026; Lockhart et al., Nature Biotechnology (1996), 14:1675; U.S. Pat. Nos. 5,578,832; 5,556,752; and 5,510,270); (ii) spotting/printing at medium to low-density (e.g., cDNA probes) on glass, nylon or nitrocellulose (Schena et al, Science (1995), 270:467-470, DeRisi et al, Nature Genetics (1996), 14:457-460; Shalon et al., Genome Res. (1996), 6:639-645; and Schena et al., Proc. Natl. Acad. Sci. U.S.A. (1995), 93:10539-11286); (iii) by masking (Maskos and Southern, Nuc. Acids. Res. (1992), 20:1679-1684) and (iv) by dot-blotting on a nylon or nitrocellulose hybridization membrane (see, e.g., Sambrook et al., Eds., 1989, Molecular Cloning: A Laboratory Manual, 2nd ed., Vol. 1-3, Cold Spring Harbor Laboratory (Cold Spring Harbor, N.Y.)). Probes may also be noncovalently immobilized on the substrate by hybridization to anchors, by means of magnetic beads, or in a fluid phase such as in microtiter wells or capillaries. The probe molecules are generally nucleic acids such as DNA, RNA, PNA, and cDNA but may also include proteins, polypeptides, oligosaccharides, cells, tissues and any permutations thereof which can specifically bind the target molecules.

For example, microarrays, in which either defined cDNAs or oligonucleotides are immobilized at discrete locations on, for example, solid or semi-solid substrates, or on defined particles, enable the detection and/or quantification of the expression of a multitude of genes in a given specimen.

Several techniques are well-known in the art for attaching nucleic acids to a solid substrate such as a glass slide. One method is to incorporate modified bases or analogs that contain a moiety that is capable of attachment to a solid substrate, such as an amine group, a derivative of an amine group or another group with a positive charge, into the amplified nucleic acids. The amplified product is then contacted with a solid substrate, such as a glass slide, which is coated with an aldehyde or another reactive group which will form a covalent link with the reactive group that is on the amplified product and become covalently attached to the glass slide. Microarrays comprising the amplified products can be fabricated using a Biodot (BioDot, Inc. Irvine, Calif.) spotting apparatus and aldehyde-coated glass slides (CEL Associates, Houston, Tex.). Amplification products can be spotted onto the aldehyde-coated slides, and processed according to published procedures (Schena et al., Proc. Natl. Acad. Sci. U.S.A. (1995) 93:10614-10619). Arrays can also be printed by robotics onto glass, nylon (Ramsay, G., Nature Biotechnol. (1998), 16:40-44), polypropylene (Matson, et al., Anal Biochem. (1995), 224(1):110-6), and silicone slides (Marshall, A. and Hodgson, J., Nature Biotechnol. (1998), 16:27-31). Other approaches to array assembly include fine micropipetting within electric fields (Marshall and Hodgson, supra), and spotting the polynucleotides directly onto positively coated plates. Methods such as those using amino propyl silicon surface chemistry are also known in the art, as disclosed at www.cmt.corning.com and http://cmgm.stanford.edu/pbrown/.

One method for making microarrays is by making high-density polynucleotide arrays. Techniques are known for rapid deposition of polynucleotides (Blanchard et al., Biosensors & Bioelectronics, 11:687-690). Other methods for making microarrays, e.g., by masking (Maskos and Southern, Nuc. Acids. Res. (1992), 20:1679-1684), may also be used. In principle, and as noted above, any type of array, for example, dot blots on a nylon hybridization membrane, could be used. However, as will be recognized by those skilled in the art, very small arrays will frequently be preferred because hybridization volumes will be smaller.

In one embodiment, the invention provides an array comprising at least two isolated polynucleotide molecules, wherein each isolated polynucleotide molecule detects an expressed gene product of a gene selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927, and wherein the gene is differentially expressed in atherosclerotic disease in a mammal. In one embodiment, the invention provides an array comprising at least two isolated polynucleotide molecules, wherein each isolated polynucleotide molecule detects an expressed gene product of a gene selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs:1-927, and wherein the gene is differentially expressed in atherosclerotic disease in a mammal. In various embodiments, an array in accordance with the invention comprises any of at least 2, 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 polynucleotides each comprising at least a portion of a polynucleotide depicted in the Sequence Listing or a polynucleotide complement thereof.

In another embodiment, the invention provides an array comprising at least two antibody molecules or antigen binding fragments thereof, wherein each antibody molecule or antigen binding fragment thereof detects an expressed gene product of a gene selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927, and wherein the gene is differentially expressed in atherosclerotic disease in a mammal. In another embodiment, the invention provides an array comprising at least two antibody molecules or antigen binding fragments thereof, wherein each antibody molecule or antigen binding fragment thereof detects an expressed gene product of a gene selected from the group of genes corresponding to the polynucleotide sequences depicted in SEQ ID NOs:1-927, and wherein the gene is differentially expressed in atherosclerotic disease in a mammal. In various embodiments, an antibody array in accordance with the invention comprises any of at least 2, 3, 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 antibodies or antigen binding fragments thereof each recognizing an expression product (e.g., a polypeptide) of a gene corresponding to a polynucleotide sequence depicted in the Sequence Listing.

Methods of the Invention
Methods for Detecting Gene Expression

The invention provides methods for detecting gene expression, comprising contacting products of gene expression (e.g., mRNA, protein) in a sample with a system for detecting gene expression as described above, and detecting interaction between the products of gene expression in the sample and the system for detecting gene expression. The methods for detecting gene expression described herein may be used to detect or quantify differential expression and/or for expression profiling of a sample. As used herein, “differential expression” refers to increased (upregulated) or decreased (downregulated) production of an expressed product of a gene (e.g., mRNA, protein). Differential expression may be assessed qualitatively (presence or absence of a gene product) and/or quantitatively (change in relative amount, i.e., increase or decrease, of a gene product).

In one embodiment, mRNA from a sample is contacted with a system for detecting gene expression comprising isolated polynucleotide molecules as described above, and hybridization complexes formed, if any, between the mRNA in the sample and the polynucleotide sequences of the system for detecting gene expression, are detected. In other embodiments, the mRNA is converted to nucleic acid derived from the mRNA, for example, cDNA, and/or amplified, prior to contact with the system for detecting gene expression.

In another embodiment, polypeptides from a sample are contacted with a system for detecting gene expression comprising antibodies or antigen fragments thereof that bind to polypeptide expression products of genes corresponding to the polynucleotide sequences described herein, and binding between the antibodies and polypeptides in the sample, if any, is detected.

Methods for Expression Profiling

An “expression profile” or “molecular signature” is a representation of gene expression in a sample, for example, evaluation of presence, absence, or amount of a plurality of gene expression products, such as mRNA transcripts, or polypeptide translation products of mRNA transcripts. Expression patterns constitute a set of relative or absolute expression values for a number of RNA or protein products corresponding to the plurality of genes evaluated, referred to as the subject's “expression profile” for those nucleotide sequences. In various embodiments, expression patterns corresponding to at least about 2, 5, 10, 20, 30, 50, 100, 200, or 500, or more nucleotide sequences are obtained. The expression pattern for each differentially expressed component member of the expression profile may provide a specificity and sensitivity with respect to predictive value, e.g., for diagnosis, prognosis, monitoring treatment, etc. In some embodiments, a molecular signature is determined by a statistical algorithm that determines the optimal relation between patterns of expression for various genes.

In some embodiments, an expression profile from an individual is compared with a reference expression profile to determine, for example, presence or absence of a disease condition, symptom, or criterion, extent of progression of disease, effectiveness of treatment of disease, or prognosis for prophylaxis, therapy, or cure of disease.

As used herein, the term “subject” refers to an individual regardless of health and/or disease status. For example, a subject may be a patient, a study participant, a control subject, a screening subject, or any other class of individual from whom a sample is obtained and assessed in the context of the invention. Accordingly, a subject may be diagnosed with a disease, can present with one or more symptom of a disease, or may have a predisposing factor, such as a genetic or medical history factor, for a disease. Alternatively, a subject may be healthy with respect to any of the aforementioned disease factors or criteria. It will be appreciated that the term “healthy” as used herein, is relative to a specified disease condition, factor, or criterion. Thus, an individual described as healthy with reference to any specified disease or disease criterion, can be diagnosed with any other one or more disease, or may exhibit any other one or more disease criterion.

Methods for Obtaining Expression Data

Numerous methods for obtaining expression data are known, and any one or more of these techniques, singly or in combination, are suitable for determining expression profiles in the context of the present invention. For example, expression patterns can be evaluated by northern analysis, PCR, RT-PCR, Taq Man analysis, FRET detection, monitoring one or more molecular beacon, hybridization to an oligonucleotide array, hybridization to a cDNA array, hybridization to a polynucleotide array, hybridization to a liquid microarray, hybridization to a microelectric array, molecular beacons, cDNA sequencing, clone hybridization, cDNA fragment fingerprinting, serial analysis of gene expression (SAGE), subtractive hybridization, differential display and/or differential screening (see, e.g., Lockhart and Winzeler (2000) Nature 405:827-836, and references cited therein).

For example, specific PCR primers are designed to a member(s) of a candidate nucleotide library (e.g., a polynucleotide member of a system for detecting gene expression). cDNA is prepared from subject sample RNA by reverse transcription from a poly-dT oligonucleotide primer, and subjected to PCR. Double stranded cDNA may be prepared using primers suitable for reverse transcription of the PCR product, followed by amplification of the cDNA using in vitro transcription. The product of in vitro transcription is a sense-RNA corresponding to the original member(s) of the candidate library. PCR product may be also be evaluated in a number of ways known in the art, including real-time assessment using detection of labeled primers, e.g. TaqMan or molecular beacon probes. Technology platforms suitable for analysis of PCR products include the ABI 7700, 5700, or 7000 Sequence Detection Systems (Applied Biosystems, Foster City, Calif.), the MJ Research Opticon (MJ Research, Waltham, Mass.), the Roche Light Cycler (Roche Diagnostics, Indianapolis, Ind.), the Stratagene MX4000 (Stratagene, La Jolla, Calif.), and the Bio-Rad iCycler (Bio-Rad Laboratories, Hercules, Calif.). Alternatively, molecular beacons are used to detect presence of a nucleic acid sequence in an unamplified RNA or cDNA sample, or following amplification of the sequence using any method, e.g., IVT (in vitro transcription) or NASBA (nucleic acid sequence based amplification). Molecular beacons are designed with sequences complementary to member(s) of a candidate nucleotide library, and are linked to fluorescent labels. Each probe has a different fluorescent label with non-overlapping emission wavelengths. For example, expression of ten genes may be assessed using ten different sequence-specific molecular beacons.

Alternatively, or in addition, molecular beacons are used to assess expression of multiple nucleotide sequences simultaneously. Molecular beacons with sequences complimentary to the members of a diagnostic nucleotide set are designed and linked to fluorescent labels. Each fluorescent label used must have a non-overlapping emission wavelength. For example, 10 nucleotide sequences can be assessed by hybridizing 10 sequence specific molecular beacons (each labeled with a different fluorescent molecule) to an amplified or non-amplified RNA or cDNA sample. Such an assay bypasses the need for sample labeling procedures.

Alternatively, or in addition, bead arrays can be used to assess expression of multiple sequences simultaneously (see, e.g., LabMAP 100, Luminex Corp, Austin, Tex.). Alternatively, or in addition, electric arrays can be used to assess expression of multiple sequences, as exemplified by the e-Sensor technology of Motorola (Chicago, Ill.) or Nanochip technology of Nanogen (San Diego, Calif.).

Of course, the particular method elected will be dependent on such factors as quantity of RNA recovered, practitioner preference, available reagents and equipment, detectors, and the like. Typically, however, the elected method(s) will be appropriate for processing the number of samples and probes of interest. Methods for high-throughput expression analysis are discussed below.

Alternatively, expression at the level of protein products of gene expression is performed. For example, protein expression in a sample can be evaluated by one or more method selected from among: western analysis, two-dimensional gel analysis, chromatographic separation, mass spectrometric detection, protein-fusion reporter constructs, calorimetric assays, binding to a protein array (e.g., antibody array), and characterization of polysomal mRNA. One particularly favorable approach involves binding of labeled protein expression products to an array of antibodies specific for members of the candidate library. Methods for producing and evaluating antibodies are well known in the art, see, e.g., Coligan, supra; and Harlow and Lane (1989) Antibodies: A Laboratory Manual, Cold Spring Harbor Press, NY (“Harlow and Lane”). Additional details regarding a variety of immunological and immunoassay procedures adaptable to the present invention by selection of antibody reagents specific for the products of candidate nucleotide sequences can be found in, e.g., Stites and Terr (eds.) (1991) Basic and Clinical Immunology, 7th ed. Another approach uses systems for performing desorption spectrometry. Commercially available systems, e.g., from Ciphergen Biosystems, Inc. (Fremont, Calif.) are particularly well suited to quantitative analysis of protein expression. Protein Chip® arrays (see, e.g., the website, ciphergen.com) used in desorption spectrometry approaches provide arrays for detection of protein expression. Alternatively, affinity reagents, (e.g., antibodies, small molecules, etc.) may be developed that recognize epitopes of one or more protein products. Affinity assays are used in protein array assays, e.g., to detect the presence or absence of particular proteins. Alternatively, affinity reagents are used to detect expression using the methods described above. In the case of a protein that is expressed on a cell surface, labeled affinity reagents are bound to a sample, and cells expressing the protein are identified and counted using fluorescent activated cell sorting (FACS).

High Throughput Expression Assays

A number of suitable high throughput formats exist for evaluating gene expression. Typically, the term high throughput refers to a format that performs at least about 100 assays, or at least about 500 assays, or at least about 1000 assays, or at least about 5000 assays, or at least about 10,000 assays, or more per day. When enumerating assays, either the number of samples or the number of candidate nucleotide sequences evaluated can be considered. For example, a northern analysis of, e.g., about 100 samples performed in a gridded array, e.g., a dot blot, using a single probe corresponding to a polynucleotide sequence as described herein can be considered a high throughput assay. More typically, however, such an assay is performed as a series of duplicate blots, each evaluated with a distinct probe corresponding to a different polynucleotide sequence of a system for detecting gene expression. Alternatively, methods that simultaneously evaluate expression of about 100 or more polynucleotide sequences in one or more samples, or in multiple samples, are considered high throughput.

Numerous technological platforms for performing high throughput expression analysis are known. Generally, such methods involve a logical or physical array of either the subject samples, or the candidate library, or both. Common array formats include both liquid and solid phase arrays. For example, assays employing liquid phase arrays, e.g., for hybridization of nucleic acids, binding of antibodies or other receptors to ligand, etc., can be performed in multiwell, or microtiter, plates. Microtiter plates with 96, 384 or 1536 wells are widely available, and even higher numbers of wells, e.g., 3456 and 9600 can be used. In general, the choice of microtiter plates is determined by the methods and equipment, e.g., robotic handling and loading systems, used for sample preparation and analysis. Exemplary systems include, e.g., the ORCA™ system from Beckman-Coulter, Inc. (Fullerton, Calif.) and the Zymate systems from Zymark Corporation (Hopkinton, Mass.).

Alternatively, a variety of solid phase arrays can favorably be employed to determine expression patterns in the context of the invention. Exemplary formats include membrane or filter arrays (e.g., nitrocellulose, nylon), pin arrays, and bead arrays (e.g., in a liquid “slurry”). Typically, probes corresponding to nucleic acid or protein reagents that specifically interact with (e.g., hybridize to or bind to) an expression product corresponding to a member of the candidate library, are immobilized, for example by direct or indirect cross-linking, to the solid support. Essentially any solid support capable of withstanding the reagents and conditions necessary for performing the particular expression assay can be utilized. For example, functionalized glass, silicon, silicon dioxide, modified silicon, any of a variety of polymers, such as (poly)tetrafluoroethylene, (poly)vinylidenedifluoride, polystyrene, polycarbonate, or combinations thereof can all serve as the substrate for a solid phase array.

In one embodiment, the array is a “chip” composed, e.g., of one of the above-specified materials. Polynucleotide probes, e.g., RNA or DNA, such as cDNA, synthetic oligonucleotides, and the like, or binding proteins such as antibodies or antigen-binding fragments or derivatives thereof, that specifically interact with expression products of individual components of the candidate library are affixed to the chip in a logically ordered manner, i.e., in an array. In addition, any molecule with a specific affinity for either the sense or anti-sense sequence of the marker nucleotide sequence (depending on the design of the sample labeling), can be fixed to the array surface without loss of specific affinity for the marker and can be obtained and produced for array production, for example, proteins that specifically recognize the specific nucleic acid sequence of the marker, ribozymes, peptide nucleic acids (PNA), or other chemicals or molecules with specific affinity.

Detailed discussion of methods for linking nucleic acids and proteins to a chip substrate, are found in, e.g., U.S. Pat. No. 5,143,854, “Large Scale Photolithographic Solid Phase Synthesis Of Polypeptides And Receptor Binding Screening Thereof,” to Pirrung et al., issued, Sep. 1, 1992; U.S. Pat. No. 5,837,832, “Arrays Of Nucleic Acid Probes On Biological Chips,” to Chee et al., issued Nov. 17, 1998; U.S. Pat. No. 6,087,112, “Arrays With Modified Oligonucleotide And Polynucleotide Compositions,” to Dale, issued Jul. 11, 2000; U.S. Pat. No. 5,215,882, “Method Of Immobilizing Nucleic Acid On A Solid Substrate For Use In Nucleic Acid Hybridization Assays,” to Bahl et al., issued Jun. 1, 1993; U.S. Pat. No. 5,707,807, “Molecular Indexing For Expressed Gene Analysis,” to Kato, issued Jan. 13, 1998; U.S. Pat. No. 5,807,522, “Methods For Fabricating Microarrays Of Biological Samples,” to Brown et al., issued Sep. 15, 1998; U.S. Pat. No. 5,958,342, “Jet Droplet Device,” to Gamble et al., issued Sep. 28, 1999; U.S. Pat. No. 5,994,076, “Methods Of Assaying Differential Expression,” to Chenchik et al., issued Nov. 30, 1999; U.S. Pat. No. 6,004,755, “Quantitative Microarray Hybridization Assays,” to Wang, issued Dec. 21, 1999; U.S. Pat. No. 6,048,695, “Chemically Modified Nucleic Acids And Method For Coupling Nucleic Acids To Solid Support,” to Bradley et al., issued Apr. 11, 2000; U.S. Pat. No. 6,060,240, “Methods For Measuring Relative Amounts Of Nucleic Acids In A Complex Mixture And Retrieval Of Specific Sequences Therefrom,” to Kamb et al., issued May 9, 2000; U.S. Pat. No. 6,090,556, “Method For Quantitatively Determining The Expression Of A Gene,” to Kato, issued Jul. 18, 2000; and U.S. Pat. No. 6,040,138, “Expression Monitoring By Hybridization To High Density Oligonucleotide Arrays,” to Lockhart et al., issued Mar. 21, 2000.

For example, cDNA inserts corresponding to candidate nucleotide sequences, in a standard TA cloning vector, are amplified by a polymerase chain reaction for approximately 30-40 cycles. The amplified PCR products are then arrayed onto a glass support by any of a variety of well-known techniques, e.g., the VSLIPS™ technology described in U.S. Pat. No. 5,143,854. RNA, or cDNA corresponding to RNA, isolated from a subject sample, is labeled, e.g., with a fluorescent tag, and a solution containing the RNA (or cDNA) is incubated under conditions favorable for hybridization, with the “probe” chip. Following incubation, and washing to eliminate non-specific hybridization, the labeled nucleic acid bound to the chip is detected qualitatively or quantitatively, and the resulting expression profile for the corresponding candidate nucleotide sequences is recorded. Multiple cDNAs from a nucleotide sequence that are non-overlapping or partially overlapping may also be used.

In another approach, oligonucleotides corresponding to members of a candidate nucleotide library are synthesized and spotted onto an array. Alternatively, oligonucleotides are synthesized onto the array using methods known in the art, e.g. Hughes, et al. supra. The oligonucleotide is designed to be complementary to any portion of the candidate nucleotide sequence. In addition, in the context of expression analysis for, e.g. diagnostic use of diagnostic nucleotide sets, an oligonucleotide can be designed to exhibit particular hybridization characteristics, or to exhibit a particular specificity and/or sensitivity, as further described below.

Oligonucleotide probes may be designed on a contract basis by various companies (for example, Compugen, Mergen, Affymetrix, Telechem), or designed from the candidate sequences using a variety of parameters and algorithms as indicated at the website genome.wi.mit.edu/cgi-bin/prtm-er/primer3.cgi. Briefly, the length of the oligonucleotide to be synthesized is determined, preferably at least 16 nucleotides, generally 18-24 nucleotides, 24-70 nucleotides and, in some circumstances, more than 70 nucleotides. The sequence analysis algorithms and tools described above are applied to the sequences to mask repetitive elements, vector sequences and low complexity sequences. Oligonucleotides are selected that are specific to the candidate nucleotide sequence (based on a Blast n search of the oligonucleotide sequence in question against gene sequences databases, such as the Human Genome Sequence, UniGene, dbEST or the non-redundant database at NCBI), and have <50% G content and 25-70% G+C content. Desired oligonucleotides are synthesized using well-known methods and apparatus, or ordered from a commercial supplier.

A hybridization signal may be amplified using methods known in the art, and as described herein, for example use of the Clontech kit (Glass Fluorescent Labeling Kit), Stratagene kit (Fairplay Microarray Labeling Kit), the Micromax kit (New England Nuclear, Inc.), the Genisphere kit (3DNA Submicro), linear amplification, e.g., as described in U.S. Pat. No. 6,132,997 or described in Hughes, T R, et al. (2001) Nature Biotechnology 19:343-347 (2001) and/or Westin et al. (2000) Nat Biotech. 18:199-204. In some cases, amplification techniques do not increase signal intensity, but allow assays to be done with small amounts of RNA.

Alternatively, fluorescently labeled cDNA are hybridized directly to the microarray using methods known in the art. For example, labeled cDNA are generated by reverse transcription using Cy3- and Cy5-conjugated deoxynucleotides, and the reaction products purified using standard methods. It is appreciated that the methods for signal amplification of expression data useful for identifying diagnostic nucleotide sets are also useful for amplification of expression data for diagnostic purposes.

Microarray expression may be detected by scanning the microarray with a variety of laser or CCD-based scanners, and extracting features with numerous software packages, for example, Imagene (Biodiscovery), Feature Extraction Software (Agilent), Scanalyze (Eisen, M. 1999. SCANALYZE User Manual; Stanford Univ., Stanford, Calif. Ver 2.32.), GenePix (Axon Instruments).

In another approach, hybridization to microelectric arrays is performed, e.g., as described in Umek et al (2001) J Mol Diagn. 3:74-84. An affinity probe, e.g., DNA, is deposited on a metal surface. The metal surface underlying each probe is connected to a metal wire and electrical signal detection system. Unlabelled RNA or cDNA is hybridized to the array, or alternatively, RNA or cDNA sample is amplified before hybridization, e.g., by PCR. Specific hybridization of sample RNA or cDNA results in generation of an electrical signal, which is transmitted to a detector. See Westin (2000) Nat Biotech. 18:199-204 (describing anchored multiplex amplification of a microelectronic chip array); Edman (1997) NAR 25:4907-14; Vignali (2000) J Immunol Methods 243:243-55.

Evaluation of Expression Patterns

Expression patterns can be evaluated by qualitative and/or quantitative measures. Certain of the above described techniques for evaluating gene expression (e.g., as RNA or protein products) yield data that are predominantly qualitative in nature, i.e., the methods detect differences in expression that classify expression into distinct modes without providing significant information regarding quantitative aspects of expression. For example, a technique can be described as a qualitative technique if it detects the presence or absence of expression of a candidate nucleotide sequence, i.e., an on/off pattern of expression. Alternatively, a qualitative technique measures the presence (and/or absence) of different alleles, or variants, of a gene product.

In contrast, some methods provide data that characterize expression in a quantitative manner. That is, the methods relate expression on a numerical scale, e.g., a scale of 0-5, a scale of 1-10, a scale of +−+++, from grade 1 to grade 5, a grade from a to z, or the like. It will be understood that the numerical, and symbolic examples provided are arbitrary, and that any graduated scale (or any symbolic representation of a graduated scale) can be employed in the context of the present invention to describe quantitative differences in nucleotide sequence expression. Typically, such methods yield information corresponding to a relative increase or decrease in expression.

Any method that yields either quantitative or qualitative expression data is suitable for evaluating expression of candidate nucleotide sequences in a subject sample. In some cases, e.g., when multiple methods are employed to determine expression patterns for a plurality of candidate nucleotide sequences, the recovered data, e.g., the expression profile, for the nucleotide sequences is a combination of quantitative and qualitative data.

In some embodiments, qualitative and/or quantitative expression data from a sample is compared with a reference molecular signature that is indicative of, for example, presence or absence of a disease condition, symptom, or criterion, extent of progression of disease, effectiveness of treatment of disease, or prognosis for prophylaxis, therapy, or cure of disease. The reference molecular signature may be from a reference healthy individual (e.g., an individual who does not exhibit symptoms of the disease condition to be evaluated) or an individual with a disease condition for comparison with the sample (e.g., an individual with the same or different stage of disease for comparison with the individual being evaluated, or with a genotype or phenotype that indicates, for example, prognosis for successful treatment), or the reference molecular signature may be established from a compilation of data from multiple individuals

In some applications, expression of a plurality of candidate polynucleotide sequences is evaluated sequentially. This is typically the case for methods that can be characterized as low-to moderate throughput. In contrast, as the throughput of the elected assay increases, expression for the plurality of candidate polynucleotide sequences in a sample or multiple samples is typically assayed simultaneously. Again, the methods (and throughput) are largely determined by the individual practitioner, although, typically, it is preferable to employ methods that permit rapid, e.g. automated or partially automated, preparation and detection, on a scale that is time-efficient and cost-effective.

Genotyping

In addition to, or in conjunction with, the correlation of expression profiles and clinical data, it is often desirable to correlate expression patterns with a subject's genotype at one or more genetic loci or to correlate both expression profiles and genetic loci data with clinical data. The selected loci can be, for example, chromosomal loci corresponding to one or more member of the candidate library, polymorphic alleles for marker loci, or alternative disease related loci (not contributing to the candidate library) known to be, or putatively associated with, a disease (or disease criterion). Indeed, it will be appreciated that where a (polymorphic) allele at a locus is linked to a disease (or to a predisposition to a disease), the presence of the allele can itself be a disease criterion.

Numerous well known methods exist for evaluating the genotype of an individual, including southern analysis, restriction fragment length polymorphism (RFLP) analysis, polymerase chain reaction (PCR), amplification length polymorphism (AFLP) analysis, single stranded conformation polymorphism (SSCP) analysis, single nucleotide polymorphism (SNP) analysis (e.g., via PCR, Taqman or molecular beacons), among many other useful methods. Many such procedures are readily adaptable to high throughput and/or automated (or semi-automated) sample preparation and analysis methods. Often, these methods can be performed on nucleic acid samples recovered via simple procedures from the same sample as yielded the material for expression profiling. Exemplary techniques are described in, e.g., Sambrook, and Ausubel, supra.

Samples

Samples which may be evaluated for differential expression of the polynucleotide sequences described herein include any blood vessel or portion thereof with atherosclerotic and/or inflammatory disease. Such blood vessels include, but are not limited to, the aorta, a coronary artery, the carotid artery, and peripheral blood vessels such as, for example, iliac or femoral arteries. In one embodiment, the sample is derived from an arterial biopsy. In another embodiment, the sample is derived from an atherectomy. Samples may also be derived from peripheral blood cells or serum.

Samples may be stabilized for storage by addition of reagents such as Trizol. Total RNA and/or protein may be isolated using standard techniques known in the art for expression profiling experiments.

Methods for RNA isolation include those described in standard molecular biology textbooks. Commercially available kits such as those provided by Qiagen (RNeasy Kits) may also be used for RNA isolation.

Methods for Diagnosing Atherosclerotic Disease

The invention provides methods for diagnosing an atherosclerotic disease condition in an individual. Diagnosis includes, for example, determining presence or absence of a disease condition or a symptom of a disease condition in an individual who has, who is suspected of having, or who may be suspected of being predisposed to an atherosclerotic disease. In accordance with methods of the invention for diagnosing atherosclerotic disease, gene expression products (e.g., RNA or proteins) from a sample from an individual are contacted with a system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a test sample are compared with levels of expression in a molecular signature that is indicative of presence or absence of an atherosclerotic disease condition for which diagnosis is desired. To obtain a diagnosis, the levels of gene expression in a sample may be compared to one or more than one molecular signature, each of which may be indicative of presence or absence one or more than one atherosclerotic disease condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of presence or absence of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of presence or absence of a disease condition, criterion, or symptom for which diagnosis is desired.

In some embodiments, polypeptides derived from a sample from an individual are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of presence or absence of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of presence or absence of a disease condition, criterion, or symptom for which diagnosis is desired.

Methods for Assessing Extent of Progression of Atherosclerotic Disease

The invention provides methods for assessing extent of progression of an atherosclerotic disease condition in an individual. For example, a stage to which a disease condition or particular symptom has progressed may be assessed. In accordance with methods of the invention for assessing extent of progression of atherosclerotic disease, gene expression products (e.g., RNA or proteins) from a sample from an individual are contacted with a system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a test sample are compared with levels of expression in a molecular signature that is indicative of extent of progression of an atherosclerotic disease condition for which assessment is desired. The levels of gene expression may be compared to one or more than one molecular signature, each of which may be indicative of extent of progression of one or more than one atherosclerotic disease condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of extent of progression of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of extent of progression of a disease condition for which diagnosis is desired.

In some embodiments, polypeptides derived from a sample from an individual are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of extent of progression of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of extent of progression of a disease condition for which diagnosis is desired.

Methods for Assessing Efficacy of Treatment of Atherosclerotic Disease

The invention provides methods for assessing extent of progression of an atherosclerotic disease condition in an individual. For example, a stage to which a disease condition or particular symptom has progressed may be assessed by the methods of the invention. In accordance with methods of the invention for assessing extent of progression of atherosclerotic disease, gene expression products (e.g., RNA or proteins) from a sample from an individual are contacted with the system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a test sample are compared with levels of expression in a molecular signature that is indicative of extent of progression of an atherosclerotic disease condition for which assessment is desired. The levels of gene expression may be compared to one or more than one molecular signature, each of which may be indicative of extent of progression of one or more than one atherosclerotic disease condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of extent of progression of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of extent of progression of a disease condition for which assessment is desired.

In some embodiments, polypeptides derived from a sample from an individual are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of extent of progression of an atherosclerotic disease in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of extent of progression of a disease condition for which assessment is desired.

Methods for Assessing Efficacy of Treatment

The invention provides methods for assessing efficacy of treatment of an atherosclerotic disease symptom or condition in an individual. As used herein, “efficacy of treatment” refers to achievement of a desired therapeutic outcome (e.g., reduction or elimination of one or more symptoms of atherosclerotic disease). “Treatment” as used herein may refer to prophylaxis, therapy, or cure with respect to one or more symptoms of an atherosclerotic disease or condition. Treatment includes administration of one or more compounds or biological substances with potential therapeutic benefit and/or alterations in environmental factors, such as, for example, diet and/or exercise. In one embodiment, administration of the one or more compounds or biological substances comprises administration via a medical device such as, for example, a drug eluting stent. In other embodiments, treatment may include gene therapy or any other method that alters expression of the polynucleotide sequences described herein. In accordance with methods of the invention for assessing efficacy of treatment of atherosclerotic disease, gene expression products (e.g., RNA or proteins) from a sample from an individual are contacted with a system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a test sample are compared with levels of expression in a molecular signature that is indicative of efficacy of treatment of an atherosclerotic disease symptom or condition for which assessment is desired. The levels of gene expression may be compared to one or more than one molecular signature, each of which may be indicative of extent of effectiveness of treatment of one or more than one atherosclerotic disease symptom or condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of efficacy of treatment of an atherosclerotic disease symptom or condition in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of efficacy of treatment of a disease symptom or condition for which assessment is desired.

In some embodiments, polypeptides derived from a sample from an individual are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of efficacy of treatment of an atherosclerotic disease condition in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of efficacy of treatment of a disease condition for which assessment is desired.

Methods for Identifying Compounds Effective for Treatment of Atherosclerotic Disease

The invention provides methods for identifying compounds effective for treatment of an atherosclerotic disease symptom or condition in an individual. In accordance with methods of the invention for identifying compounds effective for treatment of atherosclerotic disease, at least one test compound (i.e., one or more than one test compound) is administered, for example as a pharmaceutical composition comprising the at least one test compound and a pharmaceutically acceptable excipient, to an individual with an atherosclerotic disease symptom or condition or suspected of having an atherosclerotic disease symptom or condition, or to an individual who is predisposed to or suspected of being predisposed to development of an atherosclerotic disease symptom or condition. Gene expression products (e.g., RNA or proteins) from a sample from the individual are contacted with a system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a test sample from the individual to whom the at least one test compound has been administered are compared with levels of expression in a molecular signature that is indicative of efficacy of treatment of the atherosclerotic disease symptom or condition for which assessment is desired. The levels of gene expression may be compared to one or more than one molecular signature, each of which may be indicative of extent of effectiveness of treatment of one or more than one atherosclerotic disease symptom or condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) to whom at least one test compound has been administered are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of efficacy of treatment of an atherosclerotic disease symptom or condition in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of efficacy of treatment of a disease symptom or condition for which assessment is desired.

In some embodiments, polypeptides derived from a sample from an individual to whom at least one test compound has been administered are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of efficacy of treatment of an atherosclerotic disease condition in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of efficacy of treatment of a disease condition for which assessment is desired.

Methods For Determining Prognosis of Atherosclerotic Disease

The invention provides methods for determining prognosis of atherosclerotic disease in an individual, comprising contacting polynucleotides derived from a sample from the individual with a system for detecting gene expression as described above. “Prognosis” as used herein refers to the probability that an individual will develop an atherosclerotic disease symptom or condition, or that atherosclerotic disease will progress in an individual who has an atherosclerotic disease. Prognosis is a determination or prediction of probable course and/or outcome of a disease condition, i.e., whether an individual will exhibit or develop symptoms of the disease, i.e., a clinical event. In cardiovascular medicine, a common measure of prognosis is (but is not limited to) MACE (major adverse cardiac event). MACE includes mortality as well as morbidity measures, such as myocardial infarction, angina, stroke, rate of revascularization, hospitalization, etc.

For determination of prognosis of atherosclerotic disease, gene expression products (e.g., RNA or proteins) from a sample from an individual are contacted with the system for detecting gene expression as described above. In one embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 8, 14, 26, 32, 50, 64, 83, 99, 142, 154, 159, 161, 177, 181, 200, 390, 430, 434, 439, 440, 476, 491, 508, 530, 534, 565, 567, 572, 624, 647, 657, 690, 733, 745, 806, 824, 886, 882, 901, 905, 913, and 927. In another embodiment, the genes for which expression is detected are selected from the group of genes corresponding to SEQ ID NOs: 1-927.

In some embodiments, qualitative and/or quantitative levels of gene expression in a sample from the individual are compared with levels of expression in a molecular signature that is indicative of prognosis of the atherosclerotic disease symptom or condition for which assessment is desired. The levels of gene expression may be compared to one or more than one molecular signature, each of which may be indicative of prognosis for one or more than one atherosclerotic disease symptom or condition.

In some embodiments, polynucleotides derived from a sample from an individual (e.g., mRNA or polynucleotides derived from mRNA, for example cDNA) are contacted with isolated polynucleotide molecules in a system for detecting gene expression as described above, wherein each isolated polynucleotide molecule detects an expressed product of a gene that is differentially expressed in atherosclerotic disease in a mammal, and hybridization complexes formed, if any, are detected, wherein presence, absence, or amount of hybridization complexes formed from at least one of the isolated polynucleotides is indicative of prognosis for development or progression an atherosclerotic disease symptom or condition in the individual. In some embodiments, presence, absence, or amount of the polynucleotides derived from the sample is compared with presence, absence, or amount of polynucleotides in a molecular signature indicative of prognosis for development or progression of a disease symptom or condition for which assessment is desired.

In some embodiments, polypeptides derived from a sample from an individual are contacted with a system for detecting gene expression as described above which comprises molecules capable of detectably binding to polypeptides that are differentially expressed in atherosclerotic disease, for example, antibodies or antigen binding fragments thereof, that detect expressed polypeptide products of genes corresponding to polynucleotide sequences depicted in the Sequence Listing, wherein presence, absence, or amount of bound polypeptide is indicative of prognosis for development or progression of an atherosclerotic disease symptom or condition in the individual. In some embodiments, presence, absence, or amount of the polypeptides derived from the sample is compared with presence, absence, or amount of polypeptides in a molecular signature indicative of prognosis for development or progression of an atherosclerotic disease symptom or condition for which assessment is desired.

Novel Polynucleotide Sequences

The invention provides novel polynucleotide sequences that are differentially expressed in atherosclerotic disease. We have identified unnamed (not previously described as corresponding to a gene or an expressed gene, and/or for which no function has previously been assigned) polynucleotide sequences herein. The novel differentially expressed nucleotide sequences of the invention are useful in a system for detecting gene expression, such as a diagnostic oligonucleotide set, and are also useful as probes in a diagnostic oligonucleotide set immobilized on an array. The novel polynucleotide sequences may be useful as disease target polynucleotide sequences and/or as imaging reagents as described herein.

As used herein, “novel polynucleotide sequence” refers to (a) a polynucleotide sequence containing at least one of the polynucleotide sequences disclosed herein (as depicted in the Sequence Listing); (b) a polynucleotide sequence that encodes the amino acid sequence encoded by a polynucleotide sequence disclosed herein; (c) a polynucleotide sequence that hybridizes to the complement of a coding sequence disclosed herein under highly stringent conditions, e.g., hybridization to filter-bound DNA in 0.5 M NaHPO₄, 7% sodium dodecyl sulfate (SDS), 1 mM EDTA at 65° C., and washing in 0.1×SSC/0.1% SDS at 68° C. (Ausubel, F. M. et al., eds. (1989) Current Protocols in Molecular Biology, Vol. 1, Green Publishing Associates, Inc., and John Wiley & Sons, Inc., New York, at p. 2.01.3); (d) a polynucleotide sequence that hybridizes to the complement of a coding sequence disclosed herein under less stringent conditions, such as moderately stringent conditions, e.g., washing in 0.2×SSC/0.1% SDS at 42° C. (Ausubel et al. (1989), supra), yet which still encodes a functionally equivalent gene product; and/or (e) a polynucleotide sequence that is at least 90% identical, at least 80% identical, or at least 70% identical to the coding sequences disclosed herein, wherein % identity is determined using standard algorithms known in the art.

The invention also includes polynucleotide molecules that hybridize to, and are therefore the complements of, novel polynucleotide molecules as described in (a) through (c) in the preceding paragraph. Such hybridization conditions may be highly stringent or less highly stringent, as described above. In instances wherein the polynucleotide molecules are deoxyoligonucleotides, highly stringent conditions may refer to, e.g., washing in 6×SSC/0.05% sodium pyrophosphate at 37° C. (for 14-base oligonucleotides), 48° C. (for 17-base oligonucleotides), 55° C. (for 20-base oligonucleotides, and 60° C. (for 23-base oligonucleotides). These polynucleotide molecules may act as target nucleotide sequence antisense molecules, useful, for example, in target nucleotide sequence regulation and/or as antisense primers in amplification reactions of target nucleic acid sequences. Further, such sequences may be used as part of ribozyme and/or triple helix sequences, also useful for target nucleotide sequence regulation. Such molecules may also be used as components of diagnostic methods whereby the presence of a disease-causing allele may be detected.

The invention also encompasses nucleic acid molecules contained in full-length gene sequences that are related to or derived from novel polynucleotide sequences as described above and as depicted in the Sequence Listing. One sequence may map to more than one full-length gene.

The invention also encompasses (a) polynucleotide vectors that contain any of the foregoing novel polynucleotide sequences and/or their complements; (b) polynucleotide expression vectors that contain any of the foregoing novel polynucleotide sequences and/or their complements; and (c) genetically engineered host cells that contain any of the foregoing novel polynucleotide sequences operatively associated with a regulatory element that directs expression of the polynucleotide in the host cell. As used herein, regulatory elements include, but are not limited to, inducible and non-inducible promoters, enhancers, operators, and other elements known to those skilled in the art that drive and regulate gene expression.

The invention includes fragments of the novel polynucleotide sequences described above. Fragments may be any of at least 5, 10, 15, 20, 25, 50, 100, 200, or 500 nucleotides, or larger.

Novel Polypeptide Products

The invention includes novel polypeptide products, encoded by genes corresponding to the novel polynucleotide sequences described above, or functionally equivalent polypeptide gene products thereof. “Functionally equivalent,” as used herein, refers to a protein capable of exhibiting a substantially similar in vivo function, e.g., activity, as a novel polypeptide gene product encoded by a novel polynucleotide of the invention.

Equivalent novel polypeptide products may include deletions, additions, and/or substitutions of amino acid residues within the amino acid sequence encoded by a gene corresponding to a novel polynucleotide sequence of the invention as described above, but which results in a “silent” change (i.e., a change which does not substantially change the functional properties of the polypeptide). Amino acid substitutions may be made on the basis of similarity in polarity, charge, solubility, hydrophobicity, hydrophilicity, and/or the amphipathic nature of the residues involved.

Novel polypeptide products of genes corresponding to novel polynucleotide sequences described herein may be produced by recombinant nucleic acid technology using techniques that are well known in the art. For example, methods that are well known to those skilled in the art may be used to construct expression vectors containing novel polynucleotide coding sequences and appropriate transcriptional/translational control signals. These methods include, for example, in vitro recombinant DNA techniques, synthetic techniques and in vivo recombination/genetic recombination. See, for example, the techniques described in Sambrook et al., 1989, supra, and Ausubel et al., 1989, supra. Alternatively, RNA capable of encoding novel nucleotide sequence protein sequences may be chemically synthesized using, for example, synthesizers. See, for example, the techniques described in “Oligonucleotide Synthesis” (1984) Gait, M. J. ed., IRL Press, Oxford. A variety of host-expression vector systems may be utilized to express the novel nucleotide sequence coding sequences of the invention. Ruther et al. (1983) EMBO J. 2:1791; Inouye & Inouye (1985) Nucleic Acids Res. 13:3101-3109; Van Heeke & Schuster (1989) J. Biol. Chem. 264:5503; Smith et al. (1983) J. Virol. 46: 584; Smith, U.S. Pat. No. 4,215,051; Logan & Shenk (1984) Proc. Natl. Acad. Sci. USA 81:3655-3659; Bittner et al. (1987) Methods in Enzymol. 153:516-544; Wigler, et al. (1977) Cell 11:223; Szybalska & Szybalski (1962) Proc. Natl. Acad. Sci. USA 48:2026; Lowy, et al. (1980) Cell 22:817; Wigler, et al. (1980) Proc. Natl. Acad. Sci. USA 77:3567; O'Hare, et al. (1981) Proc. Natl. Acad. Sci. USA 78:1527; Mulligan & Berg (1981) Proc. Natl. Acad. Sci. USA 78:2072; Colberre-Garapin, et al. (1981) J. Mol. Biol. 150:1; Santerre, et al. (1984) Gene 30:147; Janknecht, et al. (1991) Proc. Natl. Acad. Sci. USA 88: 8972-8976. When recombinant DNA technology is used to produce the protein encoded by a gene corresponding to the novel polynucleotide sequence, it may be advantageous to engineer fusion proteins that can facilitate labeling, immobilization and/or detection.

Antibodies

The invention also provides antibodies or antigen binding fragments thereof that specifically bind to novel polypeptide products encoded by genes that correspond to novel polynucleotide sequences as described above. Antibodies capable of specifically recognizing one or more novel nucleotide sequence epitopes may be prepared by methods that are well known in the art. Such antibodies include, but are not limited to, polyclonal antibodies, monoclonal antibodies (mAbs), humanized or chimeric antibodies, single chain antibodies, Fab fragments, F(ab′)₂fragments, fragments produced by a Fab expression library, anti-idiotypic (anti-Id) antibodies, and epitope-binding fragments of any of the above. Such antibodies may be used, for example, in the detection of a novel polynucleotide sequence in a biological sample, or, alternatively, as a method for the inhibition of abnormal gene activity, for example, the inhibition of a disease target nucleotide sequence, as further described below. Thus, such antibodies may be utilized as part of a disease treatment method, and/or may be used as part of diagnostic techniques whereby patients may be tested for abnormal levels of novel nucleotide sequence encoded proteins, or for the presence of abnormal forms of the such proteins.

For the production of antibodies that bind to a polypeptide encoded by a novel nucleotide sequence, various host animals may be immunized by injection with a novel protein encoded by the novel nucleotide sequence, or a portion thereof. Such host animals may include, but are not limited to rabbits, mice, and rats. Various adjuvants may be used to increase the immunological response, depending on the host species, including but not limited to, Freund's (complete and incomplete), mineral gels such as aluminum hydroxide, surface active substances such as lysolecithin, pluronic polyols, polyanions, peptides, oil emulsions, keyhole limpet hemocyanin, dinitrophenol, and potentially useful human adjuvants such as BCG (bacille Calmette-Guerin) and Corynebacterium parvum.

Polyclonal antibodies are heterogeneous populations of antibody molecules derived from the sera of animals immunized with an antigen, such as novel polypeptide gene product, or an antigenic functional derivative thereof. For the production of polyclonal antibodies, host animals such as those described above, may be immunized by injection with novel polypeptide gene product supplemented with adjuvants as also described above.

Monoclonal antibodies, which are homogeneous populations of antibodies to a particular antigen, may be obtained by any technique which provides for the production of antibody molecules by continuous cell lines in culture. These include, but are not limited to, the hybridoma technique of Kohler and Milstein (1975) Nature 256:495-497; and U.S. Pat. No. 4,376,110, the human B-cell hybridoma technique (Kosbor et al. (1983) Immunology Today 4:72; and Cole et al. (1983) Proc. Natl. Acad. Sci. USA 80:2026-2030), and the EBV-hybridoma technique (Cole et al. (1985) Monoclonal Antibodies And Cancer Therapy, Alan R. Liss, Inc., pp. 77-96). Such antibodies may be of any immunoglobulin class including IgG, IgM, IgE, IgA, IgD and any subclass thereof. A hybridoma producing a mAb may be cultivated in vitro or in vivo.

In addition, techniques developed for the production of “chimeric antibodies” by splicing the genes from a mouse antibody molecule of appropriate antigen specificity together with genes from a human antibody molecule of appropriate biological activity can be used. Morrison et al. (1984) Proc. Natl. Acad. Sci. 81:6851-6855; Neuberger et al. (1984) Nature 312:604-608; Takeda et al. (1985) Nature 314:452-454. A chimeric antibody is a molecule in which different portions are derived from different animal species, such as those having a variable region derived from a murine mAb and a human immunoglobulin constant region.

Alternatively, techniques described for the production of single chain antibodies can be adapted to produce novel nucleotide sequence-single chain antibodies. (U.S. Pat. No. 4,946,778; Bird (1988) Science 242:423-426; Huston et al. (1988) Proc. Natl. Acad. Sci. USA 85:5879-5883; and Ward et al. (1989) Nature 334:544-546) Single chain antibodies are formed by linking the heavy and light chain fragments of the Fv region via an amino acid bridge, resulting in a single chain polypeptide.

Antibody fragments which recognize specific epitopes may be generated by known techniques. For example, such fragments include but are not limited to: the F(ab′)₂fragments which can be produced by pepsin digestion of the antibody molecule and the Fab fragments which can be generated by reducing the disulfide bridges of the F(ab′)₂fragments. Alternatively, Fab expression libraries may be constructed (Huse et al. (1989) Science 246:1275-1281) to allow rapid and easy identification of monoclonal Fab fragments with a desired specificity.

Disease Specific Target Polynucleotide Sequences

The invention also provides disease specific target polynucleotide sequences, and sets of disease specific target polynucleotide sequences. The diagnostic oligonucleotide sets, individual members of the diagnostic oligonucleotide sets and subsets thereof, and novel polynucleotide sequences, as described above, may also serve as disease specific target polynucleotide sequences. In particular, individual polynucleotide sequences that are differentially regulated or have predictive value that is strongly correlated with an atherosclerotic disease or disease criterion are especially favorable as atherosclerotic disease specific target polynucleotide sequences. Sets of genes that are co-regulated may also be identified as disease specific target polynucleotide sets. Such polynucleotide sequences and/or their complements and/or the expression products of genes corresponding to such polynucleotide sequences (e.g., mRNA, proteins) are targets for modulation by a variety of agents and techniques. For example, disease specific target polynucleotide sequences (or the expression products of genes corresponding to such polynucleotide sequences, or sets of disease specific target polynucleotide sequences) can be inhibited or activated by, e.g., target specific monoclonal antibodies or small molecule inhibitors, or delivery of the polynucleotide sequence or an expression product of a gene corresponding to the polynucleotide sequence to patients. Also, sets of genes can be inhibited or activated by a variety of agents and techniques. The specific usefulness of the target polynucleotide sequence(s) depends on the subject groups from which they were discovered, and the disease or disease criterion with which they correlate.

Kits

The invention provides kits containing a system for detecting gene expression, a diagnostic nucleotide set, candidate nucleotide library, one or novel polynucleotide sequence, one or more polypeptide products of the novel polynucleotide sequences, and/or one or more antibodies that recognize polypeptide expression products of the differentially regulated polynucleotide sequences described herein. A kit may contain a diagnostic nucleotide probe set, or other subset of a candidate library (e.g., as a cDNA, oligonucleotide or antibody microarray or reagents for performing an assay on a diagnostic gene set using any expression profiling technology), packaged in a suitable container. The kit may further comprise one or more additional reagents, e.g., substrates, labels, primers, reagents for labeling expression products, tubes and/or other accessories, reagents for collecting tissue or blood samples, buffers, hybridization chambers, cover slips, etc., and may also contain a software package, e.g., for analyzing differential expression using statistical methods as described herein, and optionally a password and/or account number for accessing the compiled database. The kit optionally further comprises an instruction set or user manual detailing preferred methods of performing the methods of the invention, and/or a reference to a site on the Internet where such instructions may be obtained.

TABLE 1

Polynucleotide sequences which detect differentially

expressed genes in atherosclerotic disease

SEQ

ID

GENE
GENE
CLONE

NO:
CLONE ID
SYMBOL
NAME
NAME

1.
C0267B04-3

C0267B04-5N
C0267B04

NIA Mouse

7.5-dpc Whole

Embryo cDNA

Library (Long)

Mus musculus

cDNA clone

NIA: C0267B04

IMAGE: 30017007

5′, MRNA

sequence

2.
M29697.1
Il7r
interleukin 7
M29697

receptor

3.
L0304D03-3
Wnt4
wingless-
L0304D03

related MMTV

integration site 4

4.
L0237D12-3
Ctsd
cathepsin D
L0237D12

5.
C0266B08-3
BM204200
ESTs
C0266B08

BM204200

6.
J0537C05-3
Pfdn2
prefoldin 2
J0537C05

7.
L0216F02-3
C430008C19Rik
RIKEN cDNA
L0216F02

C430008C19

gene

8.
NM_017372.1
Lyzs
lysozyme
NM_017372

9.
C0271B02-3
4732437J24Rik
RIKEN cDNA
C0271B02

4732437J24

gene

10.
H3022C10-3
AA408868
expreexpressed
H3022C10

sequence

AA408868

11.
L0806E05-3
Gtl2
GTL2,
L0806E05

imprinted

maternally

expressed

untranslated

mRNA

12.
H3111E06-5
Acas2l
acetyl-
H3111E06

Coenzyme A

synthetase 2

(AMP

forming)-like

13.
H3091H05-3
Hras1
Harvey rat
H3091H05

sarcoma virus

oncogene 1

14.
K0324B10-3
Timp1
tissue inhibitor
K0324B10

of

metalloproteinase 1

15.
K0508B06-3

transcribed
K0508B06

sequence with

moderate

similarity to

protein

ref: NP_077285.1

(H. sapiens)

A20-binding

inhibitor of NF-

kappaB

activation 2;

LKB1-

interacting

protein [Homo

sapiens]

16.
C0176A01-3
Syngr1
synaptogyrin 1
C0176A01

17.
J0748G02-3

AU018093
J0748G02

Mouse two-cell

stage embryo

cDNA Mus

musculus

cDNA clone

J0748G02 3′,

MRNA

sequence

18.
J0035G10-3
C77672
ESTs C77672
J0035G10

19.
C0630C02-3
Cxcl16
chemokine
C0630C02

(C—X—C motif)

ligand 16

20.
K0313A10-3
5430435G22Rik
RIKEN cDNA
K0313A10

5430435G22

gene

21.
L0070E11-3
Cbfa2t1h
CBFA2T1
L0070E11

identified gene

homolog

(human)

22.
H3072E02-3
BG069076
ESTs
H3072E02

BG069076

23.
H3079B06-3

Mus musculus

H3079B06

unknown

mRNA

24.
H3002D08-3
4833412N02Rik
RIKEN cDNA
H3002D08

4833412N02

gene

25.
H3159A08-3
Gp49b
glycoprotein 49 B
H3159A08

26.
C0612F12-3
BM207436
ESTs
C0612F12

BM207436

27.
H3108A03-3
Apobec1
apolipoprotein
H3108A03

B editing

complex 1

28.
C0180G01-3
BI076556
ESTs BI076556
C0180G01

29.
C0938A03-3
Sf3a1
splicing factor
C0938A03

3a, subunit 1

30.
J0703E02-3
Ogdh
oxoglutarate
J0703E02

dehydrogenase

(lipoamide)

31.
C0274D12-3

transcribed
C0274D12

sequence with

moderate

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

32.
H3097H03-3
Expi
extracellular
H3097H03

proteinase

inhibitor

33.
H3074D10-3

transcribed
H3074D10

sequence with

weak similarity

to protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

34.
M14222.1
Ctsb
cathepsin B
M14222

35.
C0176G01-3
2400006H24Rik
RIKEN cDNA
C0176G01

2400006H24

gene

36.
H3092F08-5

UNKNOWN:
H3092F08

Similar to Mus

musculus

immediate-

early antigen

(E-beta) gene,

partial intron 2

sequence

37.
H3054F02-3
1200003C15Rik
RIKEN cDNA
H3054F02

1200003C15

gene

38.
C0012F07-3
3010021M21Rik
RIKEN cDNA
C0012F07

3010021M21

gene

39.
L0955A10-3
9030409G11Rik
RIKEN cDNA
L0955A10

9030409G11

gene

40.
L0045B05-3

transcribed
L0045B05

sequence with

moderate

similarity to

protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

41.
H3049A10-3
BG066966
ESTs
H3049A10

BG066966

42.
X70298.1
Sox4
SRY-box
X70298

containing gene 4

43.
L0001C09-3

transcribed
L0001C09

sequence with

weak similarity

to protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

44.
H3010D12-5

UNKNOWN:
H3010D12

Similar to Mus

musculus

RIKEN cDNA

8430421I07

gene

(8430421I07Rik),

mRNA

45.
C0923E12-3
Ptpns1
protein tyrosine
C0923E12

phosphatase,

non-receptor

type substrate 1

46.
C0941E09-3
D330001F17Rik
RIKEN cDNA
C0941E09

D330001F17

gene

47.
K0534C04-3
Tce1
T-complex
K0534C04

expressed gene 1

48.
H3064E11-3
BG068354
ESTs
H3064E11

BG068354

49.
L0957C02-3
E130319B15Rik
RIKEN cDNA
L0957C02

E130319B15

gene

50.
L0240C12-3
C1qa
complement
L0240C12

component 1, q

subcomponent,

alpha

polypeptide

51.
J0018H07-3
Rnf149
ring finger
J0018H07

protein 149

52.
K0508E12-3
Rin3
Ras and Rab
K0508E12

interactor 3

53.
L0208A01-3
4933437K13Rik
RIKEN cDNA
L0208A01

4933437K13

gene

54.
C0239G03-3
BM202478
EST
C0239G03

BM202478

55.
L0518C11-3
1700016K05Rik
RIKEN cDNA
L0518C11

1700016K05

gene

56.
H3054C09-3
Oas1c
2′-5′
H3054C09

oligoadenylate

synthetase 1C

57.
L0811E07-3
3110057O12Rik
RIKEN cDNA
L0811E07

3110057O12

gene

58.
J0948A06-3

Mus musculus

J0948A06

mRNA similar

to RIKEN

cDNA

4930503E14

gene (cDNA

clone

MGC: 58418

IMAGE: 6708114),

complete

cds

59.
C0931B05-3

transcribed
C0931B05

sequence with

weak similarity

to protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

60.
H3022A09-3
Eps8l2
EPS8-like 2
H3022A09

61.
G0118B03-3
Usf2
upstream
G0118B03

transcription

factor 2

62.
H3156C12-3
Ms4a6d
membrane-
H3156C12

spanning 4-

domains,

subfamily A,

member 6D

63.
H3074G06-3
9530020G05Rik
RIKEN cDNA
H3074G06

9530020G05

gene

64.
NM_003254.1
TIMP1
tissue inhibitor
NM_003254

of

metalloproteinase

1 (erythroid

potentiating

activity,

collagenase

inhibitor)

65.
K0647H07-3
Il7r
interleukin 7
K0647H07

receptor

66.
J0257F12-3
Rnf25
ring finger
J0257F12

protein 25

67.
H3083G02-3
Lcn2
lipocalin 2
H3083G02

68.
M64086.1
Serpina3n
serine (or
M64086

cysteine)

proteinase

inhibitor, clade

A, member 3N

69.
C0906B05-3
Cenpc
centromere
C0906B05

autoantigen C

70.
H3094B08-3
BG071051
ESTs
H3094B08

BG071051

71.
K0110F02-3
Pstpip1
proline-serine-
K0110F02

threonine

phosphatase-

interacting

protein 1

72.
L0072G08-3
Renbp
renin binding
L0072G08

protein

73.
J0088G06-3
4930472G13Rik
RIKEN cDNA
J0088G06

4930472G13

gene

74.
K0121F05-3
Fcgr2b
Fc receptor,
K0121F05

IgG, low

affinity IIb

75.
K0124E12-3
Wbscr5
Williams-
K0124E12

Beuren

syndrome

chromosome

region 5

homolog

(human)

76.
K0649H05-3
F730038I15Rik
RIKEN cDNA
K0649H05

F730038I15

gene

77.
K0154C05-3
D230024O04
hypothetical
K0154C05

protein

D230024O04

78.
C0182E05-3
Hmox1
heme
C0182E05

oxygenase

(decycling) 1

79.
L0823E04-3

transcribed
L0823E04

sequence with

weak similarity

to protein

pir: T26134

(C. elegans)

T26134

hypothetical

protein

W04A4.5 -

Caenorhabditis

elegans

80.
K0130E05-3
9830126M18
hypothetical
K0130E05

protein

9830126M18

81.
C0908B11-3
P2ry6
pyrimidinergic
C0908B11

receptor P2Y,

G-protein

coupled, 6

82.
K0438A08-3
Ccl2
chemokine (C-
K0438A08

C motif) ligand 2

83.
H3082C12-3
Spp1
secreted
H3082C12

phosphoprotein 1

84.
H3014A12-3
Capg
capping protein
H3014A12

(actin filament),

85.
H3089C11-3
BG070621
ESTs
H3089C11

BG070621

86.
X67783.1
Vcam1
vascular cell
X67783

adhesion

molecule 1

87.
J0509D03-3

AU018874
J0509D03

Mouse eight-

cell stage

embryo cDNA

Mus musculus

cDNA clone

J0509D03 3′,

MRNA

sequence

88.
H3055A11-5

UNKNOWN:
H3055A11

Similar to

Homo sapiens

KIAA1363

protein

(KIAA1363),

mRNA

89.
C0455A05-3
AW413625
expressed
C0455A05

sequence

AW413625

90.
NM_019732.1
Runx3
runt related
NM_019732

transcription

factor 3

91.
L0008A03-3
AW546412
ESTs
L0008A03

AW546412

92.
K0329C10-3
Thbs1
thrombospondin 1
K0329C10

93.
H3115H03-3
BC019206
cDNA sequence
H3115H03

BC019206

94.
C0643F09-3
Usp18
ubiquitin
C0643F09

specific

protease 18

95.
X84046.1
Hgf
hepatocyte
X84046

growth factor

96.
L0236C05-3
Aldh1b1
aldehyde
L0236C05

dehydrogenase

1 family,

member B1

97.
H3055E08-3
Mcoln2
mucolipin 2
H3055E08

98.
H3009F12-3
BG063639
ESTs
H3009F12

BG063639

99.
J0208G12-3
Cxcl1
chemokine
J0208G12

(C—X—C motif)

ligand 1

100.
K0300C11-3
9130025P16Rik
RIKEN cDNA
K0300C11

9130025P16

gene

101.
H3104F03-5
Krt1-18
keratin complex
H3104F03

1, acidic, gene

18

102.
L0858D08-3
Trim2
tripartite motif
L0858D08

protein 2

103.
L0508H09-3
BY564994
EST BY564994
L0508H09

104.
L0701G07-3
BM194833
ESTs
L0701G07

BM194833

105.
K0102A10-3
E430025L02Rik
RIKEN cDNA
K0102A10

E430025L02

gene

106.
C0190H11-3
Spn
sialophorin
C0190H11

107.
L0514A11-3
2810457I06Rik
RIKEN cDNA
L0514A11

2810457I06

gene

108.
J0911E11-3
Nefl
neurofilament,
J0911E11

light

polypeptide

109.
K0647E02-3
Def6
differentially
K0647E02

expressed in

FDCP 6

110.
H3091E09-3
Eif1a
eukaryotic
H3091E09

translation

initiation factor

1A

111.
AF286725.1
Pdgfc
platelet-derived
AF286725

growth factor,

C polypeptide

112.
D31942.1
Osm
oncostatin M
D31942

113.
L0046B04-3
Alcam
activated
L0046B04

leukocyte cell

adhesion

molecule

114.
K0131D09-3
LOC217304
similar to
K0131D09

triggering

receptor

expressed on

myeloid cells 5

(LOC217304),

mRNA

115.
H3024C07-3
Hexa
hexosaminidase A
H3024C07

116.
L0251A07-3
B4galt1
UDP-
L0251A07

Gal:betaGlcNAc

beta 1,4-

galactosyltransferase,

polypeptide 1

117.
C0612G04-3
Grip1
glutamate
C0612G04

receptor

interacting

protein 1

118.
C0357B04-3

C0357B04-3
C0357B04

NIA Mouse

Undifferentiated

ES Cell

cDNA Library

(Short) Mus

musculus

cDNA clone

C0357B04 3′,

MRNA

sequence

119.
L0529E02-3
Egfl3
EGF-like-
L0529E02

domain,

multiple 3

120.
L0218E05-3
Dnase2a
deoxyribonuclease
L0218E05

II alpha

121.
H3074C12-3
Dutp
deoxyuridine
H3074C12

triphosphatase

122.
H3072F09-3
Icsbp1
interferon
H3072F09

consensus

sequence

binding protein 1

123.
C0829F05-3
4632404H22Rik
RIKEN cDNA
C0829F05

4632404H22

gene

124.
L0063A12-3

similar to
L0063A12

ubiquitin-

conjugating

enzyme UBCi

(LOC245350),

mRNA

125.
C0143E09-3
6330548O06Rik
RIKEN cDNA
C0143E09

6330548O06

gene

126.
K0127G03-3

transcribed
K0127G03

sequence with

weak similarity

to protein

ref: NP_000072.1

(H. sapiens)

beige protein

homolog;

Lysosomal

trafficking

regulator

[Homo sapiens]

127.
H3109D03-3
Lamp2
lysosomal
H3109D03

membrane

glycoprotein 2

128.
J0034B02-3
Dhx16
DEAH (Asp-
J0034B02

Glu-Ala-His)

box polypeptide

16

129.
K0428C07-3
Plcb3
phospholipase
K0428C07

C, beta 3

130.
K0119F10-3
Ccl9
chemokine (C-
K0119F10

C motif) ligand 9

131.
J0046B07-3
Tuba4
tubulin, alpha 4
J0046B07

132.
C0117E11-3
Neu1
neuraminidase 1
C0117E11

133.
C0101C01-3
Sdc1
syndecan 1
C0101C01

134.
K0245A03-3
9130012B15Rik
RIKEN cDNA
K0245A03

9130012B15

gene

135.
H3109A02-3
Fcer1g
Fc receptor,
H3109A02

IgE, high

affinity I,

gamma

polypeptide

136.
L0819C05-3
Mapk8ip
mitogen
L0819C05

activated

protein kinase 8

interacting

protein

137.
U77083.1
Anpep
alanyl
U77083

(membrane)

aminopeptidase

138.
C0164B01-3
Tnfaip2
tumor necrosis
C0164B01

factor, alpha-

induced protein 2

139.
H3085G03-3
Cyba
cytochrome b-
H3085G03

245, alpha

polypeptide

140.
H3074F04-3
Abcc3
ATP-binding
H3074F04

cassette, sub-

family C

(CFTR/MRP),

member 3

141.
H3145E02-3
Wbp1
WW domain
H3145E02

binding protein 1

142.
K0609F07-3
Cd53
CD53 antigen
K0609F07

143.
K0205H04-3
9830148O20Rik
RIKEN cDNA
K0205H04

9830148O20

gene

144.
H3095H04-3
2410002I16Rik
RIKEN cDNA
H3095H04

2410002I16

gene

145.
C0623H08-3
Tm7sf1
transmembrane
C0623H08

7 superfamily

member 1

146.
L0242F05-3
2700088M22Rik
RIKEN cDNA
L0242F05

2700088M22

gene

147.
C0177F02-3
Sdc3
syndecan 3
C0177F02

148.
L0803B02-3
Ppp1r9a
protein
L0803B02

phosphatase 1,

regulatory

(inhibitor)

subunit 9A

149.
H3061D01-3
BB172728
ESTs
H3061D01

BB172728

150.
L0259D11-3
C1qb
complement
L0259D11

component 1, q

subcomponent,

beta

polypeptide

151.
H3011D10-3
Lcp1
lymphocyte
H3011D10

cytosolic

protein 1

152.
H3052B11-3
Pctk3
PCTAIRE-
H3052B11

motif protein

kinase 3

153.
K0413H04-3
Anxa8
annexin A8
K0413H04

154.
H3054F05-3
Lyzs
lysozyme
H3054F05

155.
H3060F11-3
Cybb
cytochrome b-
H3060F11

245, beta

polypeptide

156.
H3012F08-3
9430068N19Rik
RIKEN cDNA
H3012F08

9430068N19

gene

157.
G0106B08-3
Abr
active BCR-
G0106B08

related gene

158.
L0287A12-3
Tdrkh
tudor and KH
L0287A12

domain

containing

protein

159.
H3083D01-3
AY007814
hypothetical
H3083D01

protein,

12H19.01.T7

160.
H3131F02-3
BG074151
ESTs
H3131F02

BG074151

161.
C0172H02-3
Lgals3
lectin, galactose
C0172H02

binding, soluble 3

162.
K0542E07-3
Cd44
CD44 antigen
K0542E07

163.
C0450H11-3
E430019N21Rik
RIKEN cDNA
C0450H11

E430019N21

gene

164.
K0216A08-3
Orc51
origin
K0216A08

recognition

complex,

subunit 5-like

(S. cerevisiae)

165.
H3122D03-3
Pdgfc
platelet-derived
H3122D03

growth factor,

C polypeptide

166.
C0037H07-3
Il13ra1
interleukin 13
C0037H07

receptor, alpha 1

167.
H3054F04-3
2610318I15Rik
RIKEN cDNA
H3054F04

2610318I15

gene

168.
L0908A12-3
Blnk
B-cell linker
L0908A12

169.
G0111E06-3
Car7
carbonic
G0111E06

anhydrase 7

170.
L0284B06-3
Ngfrap1
nerve growth
L0284B06

factor receptor

(TNFRSF16)

associated

protein 1

171.
K0145G06-3
Tcfec
transcription
K0145G06

factor EC

172.
H3001B08-3
Lyn
Yamaguchi
H3001B08

sarcoma viral

(v-yes-1)

oncogene

homolog

173.
G0117F12-3
Prkcsh
protein kinase
G0117F12

C substrate

80K-H

174.
C0903A11-3
2510004L01Rik
RIKEN cDNA
C0903A11

2510004L01

gene

175.
L0062C10-3
Rasa3
RAS p21
L0062C10

protein

activator 3

176.
L0939G09-3
Cd38
CD38 antigen
L0939G09

177.
H3115B07-3
S100a9
S100 calcium
H3115B07

binding protein

A9 (calgranulin

B)

178.
K0608H07-3
Fyb
FYN binding
K0608H07

protein

179.
C0104E07-3
Tcirg1
T-cell, immune
C0104E07

regulator 1

180.
K0431D02-3
Wisp1
WNT1
K0431D02

inducible

signaling

pathway protein 1

181.
L0837H10-3
Igfbp2
insulin-like
L0837H10

growth factor

binding protein 2

182.
C0159A08-3
Mta3
metastasis
C0159A08

associated 3

183.
K0649D06-3
Ms4a6b
membrane-
K0649D06

spanning 4-

domains,

subfamily A,

member 6B

184.
K0609D11-3
Man1a
mannosidase 1,
K0609D11

alpha

185.
C0907B04-3
Mcoln3
mucolipin 3
C0907B04

186.
H3020D08-3
Edem1
ER degradation
H3020D08

enhancer,

mannosidase

alpha-like 1

187.
J0039F05-3
Gdf3
growth
J0039F05

differentiation

factor 3

188.
C0906C11-3
BM218094
ESTs
C0906C11

BM218094

189.
L0266E10-3
B930060C03
hypothetical
L0266E10

protein

B930060C03

190.
H3060D11-3
Mll5
myeloid/lymphoid
H3060D11

or mixed-

lineage

leukemia 5

191.
L0062E01-3
Tnc
tenascin C
L0062E01

192.
K0132G08-3
AI662270
expressed
K0132G08

sequence

AI662270

193.
H3114D08-3
Arpc3
actin related
H3114D08

protein 2/3

complex,

subunit 3

194.
C0649E02-3
Unc93b
unc-93
C0649E02

homolog B (C. elegans)

195.
L0293H10-3
2510048K03Rik
RIKEN cDNA
L0293H10

2510048K03

gene

196.
H3024C03-3
1110008B24Rik
RIKEN cDNA
H3024C03

1110008B24

gene

197.
H3055G02-3
Ctsc
cathepsin C
H3055G02

198.
K0518A04-3
BM238476
ESTs
K0518A04

BM238476

199.
K0128H01-3
Parvg
parvin, gamma
K0128H01

200.
K0649F04-3
Ccr2
chemokine (C-
K0649F04

C) receptor 2

201.
K0603E03-3
Vav1
vav 1 oncogene
K0603E03

202.
K0649A02-3
Stat1
signal
K0649A02

transducer and

activator of

transcription 1

203.
H3013D11-3
Mt2
metallothionein 2
H3013D11

204.
H3013B02-3
Atp6v1b2
ATPase, H+
H3013B02

transporting,

V1 subunit B,

isoform 2

205.
L0541H09-3

transcribed
L0541H09

sequence with

weak similarity

to protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

206.
K0516E03-3

Mus musculus

K0516E03

12 days embryo

embryonic

body between

diaphragm

region and neck

cDNA, RIKEN

full-length

enriched

library,

clone: 9430012B12

product: unknown

EST, full

insert sequence.

207.
H3034A10-3
Plaur
urokinase
H3034A10

plasminogen

activator

receptor

208.
C0910G05-3
BM218419
ESTs
C0910G05

BM218419

209.
C0262H12-3
Msh2
mutS homolog
C0262H12

2 (E. coli)

210.
H3078C11-3
BG069620
ESTs
H3078C11

BG069620

211.
L0926H09-3
6030440G05Rik
RIKEN cDNA
L0926H09

6030440G05

gene

212.
J0076H03-3

C80125 Mouse
J0076H03

3.5-dpc

blastocyst

cDNA Mus

musculus

cDNA clone

J0076H03 3′,

MRNA

sequence

213.
L0817B08-3

transcribed
L0817B08

sequence with

strong

similarity to

protein

sp: P00722 (E. coli)

BGAL_ECOLI

Beta-

galactosidase

(Lactase)

214.
H3065D11-3
Crnkl1
Crn, crooked
H3065D11

neck-like 1

(Drosophila)

215.
H3157E02-3
5630401J11Rik
RIKEN cDNA
H3157E02

5630401J11

gene

216.
H3007C11-3
BG063444
ESTs
H3007C11

BG063444

217.
K0517E07-3
C530050H10Rik
RIKEN cDNA
K0517E07

C530050H10

gene

218.
H3150B11-5
Ptpn2
protein tyrosine
H3150B11

phosphatase,

non-receptor

type 2

219.
C0199C01-3
9930104E21Rik
RIKEN cDNA
C0199C01

9930104E21

gene

220.
H3063A09-3
Rassf5
Ras association
H3063A09

(RalGDS/AF-6)

domain family 5

221.
K0445A07-3
Hfe
hemochromatosis
K0445A07

222.
H3123G07-3
C630007C17Rik
RIKEN cDNA
H3123G07

C630007C17

gene

223.
H3094C03-3
Baz1a
bromodomain
H3094C03

adjacent to zinc

finger domain

1A

224.
L0845H04-3
BM117070
ESTs
L0845H04

BM117070

225.
C0161F01-3
BC010311
cDNA sequence
C0161F01

BC010311

226.
H3034E07-3
BG065726
ESTs
H3034E07

BG065726

227.
J0419G11-3
Cldn8
claudin 8
J0419G11

228.
C0040C08-3
Cxcr4
chemokine
C0040C08

(C—X—C motif)

receptor 4

229.
K0612H02-3
BM241159
ESTs
K0612H02

BM241159

230.
J0460B09-3

AU024759
J0460B09

Mouse

unfertilized egg

cDNA Mus

musculus

cDNA clone

J0460B09 3′,

MRNA

sequence

231.
H3103F07-3

Mus musculus

H3103F07

transcribed

sequence with

weak similarity

to protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

232.
H3079H09-3
BG069769
ESTs
H3079H09

BG069769

233.
H3130D06-3
BG074061
ESTs
H3130D06

BG074061

234.
H3071D08-3
Lcp2
lymphocyte
H3071D08

cytosolic

protein 2

235.
K0218E07-3

Mus musculus

K0218E07

10 days neonate

olfactory brain

cDNA, RIKEN

full-length

enriched

library,

clone: E530016P10

product: weakly

similar to

ONCOGENE

TLM [Mus

musculus], full

insert sequence.

236.
C0907H07-3
BM218221
ESTs
C0907H07

BM218221

237.
K0605B09-3
BM240642
ESTs
K0605B09

BM240642

238.
C0322F05-3
Eya3
eyes absent 3
C0322F05

homolog

(Drosophila)

239.
J0004A01-3
C76123
ESTs C76123
J0004A01

240.
K0139H06-3
BM223668
ESTs
K0139H06

BM223668

241.
L0941F06-3
BM120591
ESTs
L0941F06

BM120591

242.
C0300G03-3
3021401C12Rik
RIKEN cDNA
C0300G03

3021401C12

gene

243.
C0925E03-3

transcribed
C0925E03

sequence with

moderate

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

244.
H3083B07-5
BG082983
ESTs
H3083B07

BG082983

245.
H3056F01-3
Gdf9
growth
H3056F01

differentiation

factor 9

246.
J0259A06-3
C88243
EST C88243
J0259A06

247.
C0124B09-3
BC042513
cDNA sequence
C0124B09

BC042513

248.
L0933E02-3

L0933E02-3
L0933E02

NIA Mouse

Newborn

Kidney cDNA

Library (Long)

Mus musculus

cDNA clone

L0933E02 3′,

MRNA

sequence

249.
H3072B12-3
BG069052
ESTs
H3072B12

BG069052

250.
L0266C03-3
D930020B18Rik
RIKEN cDNA
L0266C03

D930020B18

gene

251.
K0423B04-3
Zfp91
zinc finger
K0423B04

protein 91

252.
J0403C04-3

AU021859
J0403C04

Mouse

unfertilized egg

cDNA Mus

musculus

cDNA clone

J0403C04 3′,

MRNA

sequence

253.
J0248E12-3
1700011I03Rik
RIKEN cDNA
J0248E12

1700011I03

gene

254.
J0908H04-3
Rpl24
ribosomal
J0908H04

protein L24

255.
K0205H10-3
Madd
MAP-kinase
K0205H10

activating death

domain

256.
C0507E09-3
Gpr22
G protein-
C0507E09

coupled

receptor 22

257.
J0005B11-3

Mus musculus

J0005B11

transcribed

sequence with

weak similarity

to protein

ref: NP_083358.1

(M. musculus)

RIKEN cDNA

5830411J07

[Mus musculus]

258.
L0201E08-3
AW551705
ESTs
L0201E08

AW551705

259.
J0426H03-3
AU023164
ESTs
J0426H03

AU023164

260.
C0649D06-3
Cdkn2b
cyclin-
C0649D06

dependent

kinase inhibitor

2B (p15,

inhibits CDK4)

261.
J0421D03-3
Rpl24
ribosomal
J0421D03

protein L24

262.
K0643F07-3

ESTs
K0643F07

BQ563001

263.
H3103C12-3
Slamf1
signaling
H3103C12

lymphocytic

activation

molecule

family member 1

264.
J0416H11-3
Pscdbp
pleckstrin
J0416H11

homology, Sec7

and coiled-coil

domains,

binding protein

265.
AF015770.1
Rfng
radical fringe
AF015770

gene homolog

(Drosophila)

266.
C0933C05-3

ESTs
C0933C05

BQ551952

267.
C0931A05-3
E130304F04Rik
RIKEN cDNA
C0931A05

E130304F04

gene

268.
J0030C02-3
C77383
ESTs C77383
J0030C02

269.
H3061A07-3
Srpk2
serine/arginine-
H3061A07

rich protein

specific kinase 2

270.
J0823B08-3

AU041035
J0823B08

Mouse four-

cell-embryo

cDNA Mus

musculus

cDNA clone

J0823B08 3′,

MRNA

sequence

271.
L0942H08-3

Mus musculus

L0942H08

transcribed

sequence with

moderate

similarity to

protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

272.
C0280H06-3
Mrp150
mitochondrial
C0280H06

ribosomal

protein L50

273.
L0534E07-3
4632417D23
hypothetical
L0534E07

protein

4632417D23

274.
U22339.1
Il15ra
interleukin 15
U22339

receptor, alpha

chain

275.
L0533C12-3

L0533C12-3
L0533C12

NIA Mouse

Newborn Heart

cDNA Library

Mus musculus

cDNA clone

L0533C12 3′,

MRNA

sequence

276.
C0909E04-3
Mvk
mevalonate
C0909E04

kinase

277.
J0093B09-3
Bhmt2
betaine-
J0093B09

homocysteine

methyltransferase 2

278.
H3066D09-3
BG068517
ESTs
H3066D09

BG068517

279.
C0346F01-3
BM197260
ESTs
C0346F01

BM197260

280.
K0125A06-3
Hdac7a
histone
K0125A06

deacetylase 7A

281.
J0214H07-3

C85807 Mouse
J0214H07

fertilized one-

cell-embryo

cDNA Mus

musculus

cDNA clone

J0214H07 3′,

MRNA

sequence

282.
C0309H10-3
5930412E23Rik
RIKEN cDNA
C0309H10

5930412E23

gene

283.
C0351C04-3
2610034E13Rik
RIKEN cDNA
C0351C04

2610034E13

gene

284.
K0204G07-3
Arf3
ADP-
K0204G07

ribosylation

factor 3

285.
L0928B09-3

transcribed
L0928B09

sequence with

strong

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

286.
H3059A09-3
C430004E15Rik
RIKEN cDNA
H3059A09

C430004E15

gene

287.
C0949D03-3

UNKNOWN
C0949D03

C0949D03

288.
K0118A04-3
Rgs1
regulator of G-
K0118A04

protein

signaling 1

289.
H3123F11-3

transcribed
H3123F11

sequence with

moderate

similarity to

protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

290.
H3154A06-3
Gng13
guanine
H3154A06

nucleotide

binding protein

13, gamma

291.
L0534E01-3

L0534E01-3
L0534E01

NIA Mouse

Newborn Heart

cDNA Library

Mus musculus

cDNA clone

L0534E01 3′,

MRNA

sequence

292.
L0250B10-3
Ap4m1
adaptor-related
L0250B10

protein

complex AP-4,

mu 1

293.
L0518G04-3
BM123045
ESTs
L0518G04

BM123045

294.
J1020E03-3

transcribed
J1020E03

sequence with

moderate

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

295.
X12616.1
Fes
feline sarcoma
X12616

oncogene

296.
J0026H02-3
C77164
expressed
J0026H02

sequence

C77164

297.
H3154D11-5
Taf7l
TAF7-like
H3154D11

RNA

polymerase II,

TATA box

binding protein

(TBP)-

associated

factor

298.
H3054H04-3
Kcnn4
potassium
H3054H04

intermediate/small

conductance

calcium-

activated

channel,

subfamily N,

member 4

299.
J0425B03-3
R75183
expressed
J0425B03

sequence

R75183

300.
C0930C02-3
0610037D15Rik
RIKEN cDNA
C0930C02

0610037D15

gene

301.
L0812A11-3

ESTs BI793430
L0812A11

302.
J0243F04-3
9530020D24Rik
RIKEN cDNA
J0243F04

9530020D24

gene

303.
C0335A03-3
1110035O14Rik
RIKEN cDNA
C0335A03

1110035O14

gene

304.
H3003B10-3
BG063111
ESTs
H3003B10

BG063111

305.
U97073.1
Prtn3
proteinase 3
U97073

306.
K0300D08-3
Afmid
arylformamidase
K0300D08

307.
H3029H06-3
Sf3b2
splicing factor
H3029H06

3b, subunit 2

308.
H3074D09-3
Drg2
developmentally
H3074D09

regulated

GTP binding

protein 2

309.
K0647G12-3
Plek
pleckstrin
K0647G12

310.
H3137A08-3

Mus musculus

H3137A08

transcribed

sequence with

moderate

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

311.
C0166D06-3
Slc38a3
solute carrier
C0166D06

family 38,

member 3

312.
K0406B07-3
Sirt7
sirtuin 7 (silent
K0406B07

mating type

information

regulation 2,

homolog) 7 (S. cerevisiae)

313.
H3085D10-3
Gda
guanine
H3085D10

deaminase

314.
H3099C09-3
Igf1
insulin-like
H3099C09

growth factor 1

315.
H3099B07-5
2610028H24Rik
RIKEN cDNA
H3099B07

2610028H24

gene

316.
H3114H10-3
Rec8L1
REC8-like 1
H3114H10

(yeast)

317.
L0703E03-3
Lipc
lipase, hepatic
L0703E03

318.
H3074H08-3
BG069302
ESTs
H3074H08

BG069302

319.
K0443D01-3
Baz1b
bromodomain
K0443D01

adjacent to zinc

finger domain,

1B

320.
J0409E10-3
AU022163
ESTs
J0409E10

AU022163

321.
L0528E01-3
BM123655
EST
L0528E01

BM123655

322.
L0031B11-3
Alcam
activated
L0031B11

leukocyte cell

adhesion

molecule

323.
G0115A06-3
Fem1a
feminization 1
G0115A06

homolog a (C. elegans)

324.
L0947C07-3
Mal
myelin and
L0947C07

lymphocyte

protein, T-cell

differentiation

protein

325.
H3101A05-3
AU040576
expressed
H3101A05

sequence

AU040576

326.
H3064E10-3
BG068353
ESTs
H3064E10

BG068353

327.
K0505H05-3
Ian6
immune
K0505H05

associated

nucleotide 6

328.
H3082E12-3
Ptpre
protein tyrosine
H3082E12

phosphatase,

receptor type, E

329.
H3088A06-3
2310047N01Rik
RIKEN cDNA
H3088A06

2310047N01

gene

330.
K0635B07-3
Ccr5
chemokine (C-
K0635B07

C motif)

receptor 5

331.
C0153A12-3
1110025F24Rik
RIKEN cDNA
C0153A12

1110025F24

gene

332.
C0143E02-3
BC022145
cDNA sequence
C0143E02

BC022145

333.
L0863F12-3
Nr2c2
nuclear receptor
L0863F12

subfamily 2,

group C,

member 2

334.
H3045F02-3
LOC214424
hypothetical
H3045F02

protein

LOC214424

335.
H3035G05-3
BG065832
ESTs
H3035G05

BG065832

336.
H3137D02-3
Hnrpl
heterogeneous
H3137D02

nuclear

ribonucleoprotein L

337.
H3097F07-3
AU040829
expressed
H3097F07

sequence

AU040829

338.
J0029C02-3
Frag1-pending
FGF receptor
J0029C02

activating

protein 1

339.
BB416014.1

Mus musculus

BB416014

B6-derived

CD11 +ve

dendritic cells

cDNA, RIKEN

full-length

enriched

library,

clone: F730035A01

product: similar

to SWI/SNF

COMPLEX

170 KDA

SUBUNIT

[Homo

sapiens], full

insert sequence.

340.
H3087E01-3
Anxa4
annexin A4
H3087E01

341.
H3088E08-3
BG070548
ESTs
H3088E08

BG070548

342.
AF179424.1

Mus musculus

AF179424

13 days embryo

male testis

cDNA, RIKEN

full-length

enriched

library,

clone: 6030408M17

product: GATA

binding protein

4, full insert

sequence

343.
J0258C01-3

Mus musculus

J0258C01

mRNA for

mKIAA1335

protein

344.
K0507B09-3

ESTs
K0507B09

BM238095

345.
L0846F07-3
BM117131
ESTs
L0846F07

BM117131

346.
U48866.1
CEBPE
CCAAT/enhancer
U48866

binding

protein

(C/EBP),

epsilon

347.
K0301B06-3
Fech
ferrochelatase
K0301B06

348.
NM_009756.1
Bmp10
bone
NM_009756

morphogenetic

protein 10

349.
NM_010100.1
Edar
ectodysplasin-A
NM_010100

receptor

350.
G0115E06-3
C430014D17Rik
RIKEN cDNA
G0115E06

C430014D17

gene

351.
L0266D11-3
Ppp3ca
protein
L0266D11

phosphatase 3,

catalytic

subunit, alpha

isoform

352.
L0526F10-3

Mus musculus

L0526F10

10 days neonate

cortex cDNA,

RIKEN full-

length enriched

library,

clone: A830020C21

product: unknown

EST, full

insert sequence.

353.
H3047C10-3
Slc6a6
solute carrier
H3047C10

family 6

(neurotransmitter

transporter,

taurine),

member 6

354.
K0322G06-3
BC042620
cDNA sequence
K0322G06

BC042620

355.
NM_009580.1
Zp1
zona pellucida
NM_009580

glycoprotein 1

356.
H3150E08-3
Map4k5
mitogen-
H3150E08

activated

protein kinase

kinase kinase

kinase 5

357.
J0059G03-3
C79059
ESTs C79059
J0059G03

358.
U93191.1
Hdac2
histone
U93191

deacetylase 2

359.
H3033C04-5

H3033C04-5
H3033C04

NIA Mouse

15K cDNA

Clone Set Mus

musculus

cDNA clone

H3033C04 5′,

MRNA

sequence

360.
H3085C01-3
2700038N03Rik
RIKEN cDNA
H3085C01

2700038N03

gene

361.
J0412G02-3
BB336629
ESTs
J0412G02

BB336629

362.
K0527H09-3
BM239048
ESTs
K0527H09

BM239048

363.
H3009C10-3
Serpinb9b
serine (or
H3009C10

cysteine)

proteinase

inhibitor, clade

B, member 9b

364.
H3142D11-3

Mus musculus

H3142D11

mRNA similar

to hypothetical

protein

FLJ20811

(cDNA clone

MGC: 27863

IMAGE: 3492516),

complete

cds

365.
H3094B07-3

Mus musculus

H3094B07

transcribed

sequence with

weak similarity

to protein

sp: P11369

(M. musculus)

POL2_MOUSE

Retrovirus-

related POL

polyprotein

[Contains:

Reverse

transcriptase;

Endonuclease]

366.
J0068F09-3
C79588
ESTs C79588
J0068F09

367.
H3039B03-5
E030024M05Rik
RIKEN cDNA
H3039B03

E030024M05

gene

368.
H3068B03-3
BG068673
ESTs
H3068B03

BG068673

369.
C0250F05-3
BM203195
ESTs
C0250F05

BM203195

370.
H3110C11-3
Mlph
melanophilin
H3110C11

371.
H3121F01-3
Wnt4
wingless-
H3121F01

related MMTV

integration site 4

372.
J1012G09-3
Brd3
bromodomain
J1012G09

containing 3

373.
L0952B09-3
Usp49
ubiquitin
L0952B09

specific

protease 49

374.
K0131B12-3
Il4ra
interleukin 4
K0131B12

receptor, alpha

375.
H3046E09-3
Nfatc2ip
nuclear factor
H3046E09

of activated T-

cells,

cytoplasmic 2

interacting

protein

376.
K0520B05-3

transcribed
K0520B05

sequence with

weak similarity

to protein

pir: I58401

(M. musculus)

I58401 protein-

tyrosine kinase

(EC 2.7.1.112)

JAK3 - mouse

377.
K0315G05-3
Stat5a
signal
K0315G05

transducer and

activator of

transcription

5A

378.
H3086F07-3
BC003332
cDNA sequence
H3086F07

BC003332

379.
H3156A10-5
Ctsd
cathepsin D
H3156A10

380.
C0890D02-3

C0890D02-3
C0890D02

NIA Mouse

Blastocyst

cDNA Library

(Long) Mus

musculus

cDNA clone

C0890D02 3′,

MRNA

sequence

381.
L0245G03-3
6430519N07Rik
RIKEN cDNA
L0245G03

6430519N07

gene

382.
J0447A10-3

Mus musculus

J0447A10

cDNA clone

IMAGE: 12820

81, partial cds

383.
J1031A09-3

Mus musculus

J1031A09

transcribed

sequence with

weak similarity

to protein

pir: I58401

(M. musculus)

I58401 protein-

tyrosine kinase

(EC 2.7.1.112)

JAK3 - mouse

384.
L0072H04-3
A630084M22Rik
RIKEN cDNA
L0072H04

A630084M22

gene

385.
J0050E03-3

transcribed
J0050E03

sequence with

weak similarity

to protein

ref: NP_081764.

1 (M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

386.
H3039C11-3
Tyro3
TYRO3 protein
H3039C11

tyrosine kinase 3

387.
C0324F11-3
6720458F09Rik
RIKEN cDNA
C0324F11

6720458F09

gene

388.
L0018F11-3
AW547199
ESTs
L0018F11

AW547199

389.
X69902.1
Itga6
integrin alpha 6
X69902

390.
H3105A09-3

transcribed
H3105A09

sequence with

weak similarity

to protein

ref: NP_416488.

1 (E. coli)

putative

transport

protein,

shikimate

[Escherichia

coli K12]

391.
H3159F01-5

UNKNOWN
H3159F01

H3159F01

392.
K0522B04-3
F5
coagulation
K0522B04

factor V

393.
C0123F08-3
AI843918
expressed
C0123F08

sequence

AI843918

394.
H3067G08-3
BG068642
ESTs
H3067G08

BG068642

395.
K0349B03-3
Stam2
signal
K0349B03

transducing

adaptor

molecule (SH3

domain and

ITAM motif) 2

396.
C0620D11-3
Bid
BH3 interacting
C0620D11

domain death

agonist

397.
C0189H10-3
4930486L24Rik
RIKEN cDNA
C0189H10

4930486L24

gene

398.
H3140A02-3
Slc9a1
solute carrier
H3140A02

family 9

(sodium/hydrogen

exchanger),

member 1

399.
K0645B04-3
Smc4l1
SMC4
K0645B04

structural

maintenance of

chromosomes

4-like 1 (yeast)

400.
C0300G08-3
6720460I06Rik
RIKEN cDNA
C0300G08

6720460I06

gene

401.
M59378.1
Tnfrsf1b
tumor necrosis
M59378

factor receptor

superfamily,

member 1b

402.
NM_009399.1
Tnfrsf11a
tumor necrosis
NM_009399

factor receptor

superfamily,

member 11a

403.
C0168E12-3
2810442I22Rik
RIKEN cDNA
C0168E12

2810442I22

gene

404.
L0228H10-3
C1r
complement
L0228H10

component 1, r

subcomponent

405.
H3088B10-3
BG070515
ESTs
H3088B10

BG070515

406.
K0409D10-3
Lrrc5
leucine-rich
K0409D10

repeat-

containing 5

407.
H3056D02-3

transcribed
H3056D02

sequence with

moderate

similarity to

protein

ref: NP_079108.1

(H. sapiens)

hypothetical

protein

FLJ22439

[Homo sapiens]

408.
J0430F08-3
AU023357
ESTs
J0430F08

AU023357

409.
H3158C06-3
2810457I06Rik
RIKEN cDNA
H3158C06

2810457I06

gene

410.
M85078.1
Csf2ra
colony
M85078

stimulating

factor 2

receptor, alpha,

low-affinity

(granulocyte-

macrophage)

411.
C0145E06-3
Satb1
special AT-rich
C0145E06

sequence

binding protein 1

412.
H3015B08-3
BG064069
ESTs
H3015B08

BG064069

413.
C0842H05-3
Fbln1
fibulin 1
C0842H05

414.
G0117D07-3
Otx2
orthodenticle
G0117D07

homolog 2

(Drosophila)

415.
L0806E03-3
Stmn4
stathmin-like 4
L0806E03

416.
H3073B06-3
BG069137
ESTs
H3073B06

BG069137

417.
H3082G08-3
Myo10
myosin X
H3082G08

418.
C0141F07-3
C3ar1
complement
C0141F07

component 3a

receptor 1

419.
K0525G09-3
5830411I20
hypothetical
K0525G09

protein

5830411I20

420.
H3064D01-3

transcribed
H3064D01

sequence with

weak similarity

to protein

ref: NP_001362.1

(H. sapiens)

dynein,

axonemal,

heavy

polypeptide 8

[Homo sapiens]

421.
C0120F08-3
6330406L22Rik
RIKEN cDNA
C0120F08

6330406L22

gene

422.
H3105G04-3
Map4k4
mitogen-
H3105G04

activated

protein kinase

kinase kinase

kinase 4

423.
J0800D09-3
2310004L02Rik
RIKEN cDNA
J0800D09

2310004L02

gene

424.
L0226H02-3
5830411I20
hypothetical
L0226H02

protein

5830411I20

425.
L0529D10-3
BM123730
ESTs
L0529D10

BM123730

426.
H3088E05-3
Gla
galactosidase,
H3088E05

alpha

427.
K0621H11-3

K0621H11-3
K0621H11

NIA Mouse

Hematopoietic

Stem Cell (Lin-/

c-Kit-/Sca-1+)

cDNA Library

(Long) Mus

musculus

cDNA clone

NIA: K0621H11

IMAGE: 30070846

3′, MRNA

sequence

428.
C0846H03-3
D330025I23Rik
RIKEN cDNA
C0846H03

D330025I23

gene

429.
J0058E06-3
C78984
ESTs C78984
J0058E06

430.
K0325E09-3
Ibsp
integrin binding
K0325E09

sialoprotein

431.
K0336F07-3
Pycs
pyrroline-5-
K0336F07

carboxylate

synthetase

(glutamate

gamma-

semialdehyde

synthetase)

432.
H3013B04-3
B230106I24Rik
RIKEN cDNA
H3013B04

B230106I24

gene

433.
L0238A07-3
Midn
midnolin
L0238A07

434.
L0929C04-3
Tnfrsf11b
tumor necrosis
L0929C04

factor receptor

superfamily,

member 11b

(osteoprotegerin)

435.
L0020F05-3
6330583M11Rik
RIKEN cDNA
L0020F05

6330583M11

gene

436.
H3012H07-3
Cd44
CD44 antigen
H3012H07

437.
K0240E11-3
Myo5a
myosin Va
K0240E11

438.
K0401C06-3
Col8a1
procollagen,
K0401C06

type VIII, alpha 1

439.
C0917F02-3
Frzb
frizzled-related
C0917F02

protein

440.
H3104C03-3
1500015O10Rik
RIKEN cDNA
H3104C03

1500015O10

gene

441.
K0438D09-3
Col8a1
procollagen,
K0438D09

type VIII, alpha 1

442.
H3152C04-3
Usp16
ubiquitin
H3152C04

specific

protease 16

443.
H3079D12-3
Pld3
phospholipase
H3079D12

D3

444.
L0020E08-3
C1qg
complement
L0020E08

component 1, q

subcomponent,

gamma

polypeptide

445.
J0025G01-3
Yars
tyrosyl-tRNA
J0025G01

synthetase

446.
L0832H09-3
Mafb
v-maf
L0832H09

musculoaponeurotic

fibrosarcoma

oncogene

family, protein

B (avian)

447.
C0451C02-3
2700094L05Rik
RIKEN cDNA
C0451C02

2700094L05

gene

448.
H3063A08-3
Lgmn
legumain
H3063A08

449.
K0629D05-3
Evi2a
ecotropic viral
K0629D05

integration site

2a

450.
G0111D11-3
Ctsl
cathepsin L
G0111D11

451.
H3077D05-3
Npc2
Niemann Pick
H3077D05

type C2

452.
G0104C04-3
Dab2
disabled
G0104C04

homolog 2

(Drosophila)

453.
L0502D10-3
Pla1a
phospholipase
L0502D10

A1 member A

454.
H3126B08-3
Pla2g7
phospholipase
H3126B08

A2, group VII

(platelet-

activating factor

acetylhydrolase,

plasma)

455.
J0034A07-3
Creg
cellular
J0034A07

repressor of

E1A-stimulated

genes

456.
H3114B07-3
Slc12a4
solute carrier
H3114B07

family 12,

member 4

457.
K0339H12-3
Thbs1
thrombospondin 1
K0339H12

458.
H3028C09-3
Adk
adenosine
H3028C09

kinase

459.
L0277B06-3
Psap
prosaposin
L0277B06

460.
H3013F05-3
Sdc1
syndecan 1
H3013F05

461.
H3084A06-3
Spin
spindlin
H3084A06

462.
H3077F04-3
Osbpl8
oxysterol
H3077F04

binding protein-

like 8

463.
K0324A06-3
Itga11
integrin, alpha
K0324A06

11

464.
C0115E05-3
2010110K16Rik
RIKEN cDNA
C0115E05

2010110K16

gene

465.
C0668G11-3
Fabp5
fatty acid
C0668G11

binding protein

5, epidermal

466.
L0030A03-3
Alox5ap
arachidonate 5-
L0030A03

lipoxygenase

activating

protein

467.
H3009E11-3
Socs3
suppressor of
H3009E11

cytokine

signaling 3

468.
L0010B01-3
Abca1
ATP-binding
L0010B01

cassette, sub-

family A

(ABC1),

member 1

469.
G0116C07-3
Ctsb
cathepsin B
G0116C07

470.
K0426E09-3
Eps8
epidermal
K0426E09

growth factor

receptor

pathway

substrate 8

471.
H3102F08-3
Asah1
N-
H3102F08

acylsphingosine

amidohydrolase 1

472.
L0825G08-3
Dcamkl1
double cortin
L0825G08

and

calcium/calmodulin-

dependent

protein kinase-

like 1

473.
K0306B10-3
Fgf7
fibroblast
K0306B10

growth factor 7

474.
H3127F04-3
Chst11
carbohydrate
H3127F04

sulfotransferase

11

475.
L0208A08-3
1200013B22Rik
RIKEN cDNA
L0208A08

1200013B22

gene

476.
H3026G09-3
Col2a1
procollagen,
H3026G09

type II, alpha 1

477.
C0218D02-3
Madh1
MAD homolog
C0218D02

1 (Drosophila)

478.
J1031F04-3
Dfna5h
deafness,
J1031F04

autosomal

dominant 5

homolog

(human)

479.
L0276A08-3
Rai14
retinoic acid
L0276A08

induced 14

480.
C0508H08-3
Sptlc2
serine
C0508H08

palmitoyltransferase,

long

chain base

subunit 2

481.
J0042D09-3
C78076
ESTs C78076
J0042D09

482.
J0013B06-3
Akr1b8
aldo-keto
J0013B06

reductase

family 1,

member B8

483.
H3158D11-3
Mmp2
matrix
H3158D11

metalloproteinase 2

484.
H3001D04-3
Hist2h3c2
histone 2, H3c2
H3001D04

485.
C0664G04-3
Ppicap
peptidylprolyl
C0664G04

isomerase C-

associated

protein

486.
H3091E10-3
Nupr1
nuclear protein 1
H3091E10

487.
X98792.1
Ptgs2
prostaglandin-
X98792

endoperoxide

synthase 2

488.
L0908B12-3
Ptpn1
protein tyrosine
L0908B12

phosphatase,

non-receptor

type 1

489.
H3081D02-3
Bok
Bcl-2-related
H3081D02

ovarian killer

protein

490.
C0127E12-3
Cln5
ceroid-
C0127E12

lipofuscinosis,

neuronal 5

491.
K0310G10-3
Col5a2
procollagen,
K0310G10

type V, alpha 2

492.
H3023H09-3
Ftl1
ferritin light
H3023H09

chain 1

493.
G0104B11-3
Slc7a7
solute carrier
G0104B11

family 7

(cationic amino

acid transporter,

y+ system),

member 7

494.
C0123F05-3
B4galt5
UDP-
C0123F05

Gal:betaGlcNAc

beta 1,4-

galactosyltransferase,

polypeptide 5

495.
H3082D01-3
1810015C04Rik
RIKEN cDNA
H3082D01

1810015C04

gene

496.
C0121E07-3
AW539579
EST
C0121E07

AW539579

497.
H3153H08-3
Hs6st2
heparan sulfate
H3153H08

6-O-

sulfotransferase 2

498.
J0238C08-3
4930579A11Rik
RIKEN cDNA
J0238C08

4930579A11

gene

499.
L0942B10-3
Msr2
macrophage
L0942B10

scavenger

receptor 2

500.
J0915B05-3
Cdca1
cell division
J0915B05

cycle associated 1

501.
H3058B09-3
Lypla3
lysophospholipase 3
H3058B09

502.
C0197E01-3
D630023B12
hypothetical
C0197E01

protein

D630023B12

503.
J0802G04-3
0610011I04Rik
RIKEN cDNA
J0802G04

0610011I04

gene

504.
H3039E08-3
Sh3d3
SH3 domain
H3039E08

protein 3

505.
L0210A08-3
B130023O14Rik
RIKEN cDNA
L0210A08

B130023O14

gene

506.
H3114C10-3
Ppgb
protective
H3114C10

protein for beta-

galactosidase

507.
C0322A01-3
2810441C07Rik
RIKEN cDNA
C0322A01

2810441C07

gene

508.
L0256F11-3
Adfp
adipose
L0256F11

differentiation

related protein

509.
L0939H06-3
Mgat5
mannoside
L0939H06

acetylglucosaminyltransferase 5

510.
C0503B05-3
Dcamkl1
double cortin
C0503B05

and

calcium/calmodulin-

dependent

protein kinase-

like 1

511.
H3136H11-3
Map4k5
mitogen-
H3136H11

activated

protein kinase

kinase kinase

kinase 5

512.
K0349A04-3
Fn1
fibronectin 1
K0349A04

513.
C0177C04-3
Ctsz
cathepsin Z
C0177C04

514.
C0668D08-3
Grn
granulin
C0668D08

515.
C0106D12-3
Anxa1
annexin A1
C0106D12

516.
H3078E09-3
Hexb
hexosaminidase B
H3078E09

517.
L0033F05-3
2810442I22Rik
RIKEN cDNA
L0033F05

2810442I22

gene

518.
K0144G04-3
Ifi203
interferon
K0144G04

activated gene

203

519.
H3144E05-3
4933426M11Rik
RIKEN cDNA
H3144E05

4933426M11

gene

520.
K0336D02-3
Ifi16
interferon,
K0336D02

gamma-

inducible

protein 16

521.
H3004B12-3
Hpn
hepsin
H3004B12

522.
K0617G07-3
Atp6v1b2
ATPase, H+
K0617G07

transporting,

V1 subunit B,

isoform 2

523.
L0849B10-3
Pltp
phospholipid
L0849B10

transfer protein

524.
L0019H03-3
Fn1
fibronectin 1
L0019H03

525.
J0099E12-3
Slc6a6
solute carrier
J0099E12

family 6

(neurotransmitter

transporter,

taurine),

member 6

526.
J0023G04-3
BC004044
cDNA sequence
J0023G04

BC004044

527.
C0913D04-3
4933433D23Rik
RIKEN cDNA
C0913D04

4933433D23

gene

528.
H3020C02-3
Mt1
metallothionein 1
H3020C02

529.
C0217B11-3
Sema4d
sema domain,
C0217B11

immunoglobulin

domain (Ig),

transmembrane

domain (TM)

and short

cytoplasmic

domain,

(semaphorin)

4D

530.
C0917E01-3
Bhlhb2
basic helix-
C0917E01

loop-helix

domain

containing,

class B2

531.
H3132B12-5
Deaf1
deformed
H3132B12

epidermal

autoregulatory

factor 1

(Drosophila)

532.
L0270C04-3
Mpp1
membrane
L0270C04

protein,

palmitoylated

533.
J0709H10-3

transcribed
J0709H10

sequence with

moderate

similarity to

protein

pir: A38712

(H. sapiens)

A38712

fibrillarin

[validated] -

human

534.
C0166A10-3
Car2
carbonic
C0166A10

anhydrase 2

535.
L0511A03-3
BM122519
ESTs
L0511A03

BM122519

536.
H3029F09-3
Atp6v1e1
ATPase, H+
H3029F09

transporting,

V1 subunit E

isoform 1

537.
J0716H11-3
Kdt1
kidney cell line
J0716H11

derived

transcript 1

538.
C0102C01-3
Acp5
acid
C0102C01

phosphatase 5,

tartrate resistant

539.
C0641C07-3
Pdgfb
platelet derived
C0641C07

growth factor,

B polypeptide

540.
C0147C09-3
Ttc7
tetratricopeptide
C0147C09

repeat domain 7

541.
K0301G02-3
9430025M21Rik
RIKEN cDNA
K0301G02

9430025M21

gene

542.
H3022D05-3
Tpbpb
trophoblast
H3022D05

specific protein

beta

543.
H3007C09-3
Sh3bgrl3
SH3 domain
H3007C09

binding

glutamic acid-

rich protein-like 3

544.
L0820G02-3
Igsf4
immunoglobulin
L0820G02

superfamily,

member 4

545.
C0120H11-3
4933433D23Rik
RIKEN cDNA
C0120H11

4933433D23

gene

546.
J1016E08-3
1810046J19Rik
RIKEN cDNA
J1016E08

1810046J19

gene

547.
L0822D10-3
Prkcb
protein kinase
L0822D10

C, beta

548.
H3050H09-3
Ppp2r5c
protein
H3050H09

phosphatase 2,

regulatory

subunit B

(B56), gamma

isoform

549.
J0442H09-3

Mus musculus

J0442H09

hypothetical

LOC237436

(LOC237436),

mRNA

550.
H3141E06-3
Sra1
steroid receptor
H3141E06

RNA activator 1

551.
C0170H06-3
Adss2
adenylosuccinate
C0170H06

synthetase 2,

non muscle

552.
K0344C08-3
Emp1
epithelial
K0344C08

membrane

protein 1

553.
J0907F03-3
Npl
N-
J0907F03

acetylneuraminate

pyruvate

lyase

554.
J1008C10-3
Ptpn1
protein tyrosine
J1008C10

phosphatase,

non-receptor

type 1

555.
K0103F09-3
2500002K03Rik
RIKEN cDNA
K0103F09

2500002K03

gene

556.
C0837H01-3
Adam9
a disintegrin
C0837H01

and

metalloproteinase

domain 9

(meltrin

gamma)

557.
J0207H07-3
Runx2
runt related
J0207H07

transcription

factor 2

558.
J0246C10-3
Tpd52
tumor protein
J0246C10

D52

559.
H3158E12-3
BC003324
cDNA sequence
H3158E12

BC003324

560.
H3094A04-3
Dnajc3
DnaJ (Hsp40)
H3094A04

homolog,

subfamily C,

member 3

561.
L0231F01-3
Evl
Ena-vasodilator
L0231F01

stimulated

phosphoprotein

562.
K0512E10-3
Myo5a
myosin Va
K0512E10

563.
K0608H09-3
Ptprc
protein tyrosine
K0608H09

phosphatase,

receptor type, C

564.
L0842E04-3
Prkcb
protein kinase
L0842E04

C, beta

565.
H3121G01-3
BG073361
ESTs
H3121G01

BG073361

566.
C0947F04-3
5830411K21Rik
RIKEN cDNA
C0947F04

5830411K21

gene

567.
H3009D03-5
Plac8
placenta-
H3009D03

specific 8

568.
H3132E07-3
Lxn
latexin
H3132E07

569.
H3054C01-3
Nr2e3
nuclear receptor
H3054C01

subfamily 2,

group E,

member 3

570.
H3013H03-3
Man1a
mannosidase 1,
H3013H03

alpha

571.
J0058F02-3
ank
progressive
J0058F02

ankylosis

572.
L0829D10-3
Snca
synuclein, alpha
L0829D10

573.
H3037H02-3
1110018O12Rik
RIKEN cDNA
H3037H02

1110018O12

gene

574.
K0105H12-3
Cdk6
cyclin-
K0105H12

dependent

kinase 6

575.
C0105D10-3

C0105D10-3
C0105D10

NIA Mouse

E7.5

Extraembryonic

Portion cDNA

Library Mus

musculus

cDNA clone

C0105D10 3′,

MRNA

sequence

576.
L0229E05-3
Prkx
putative
L0229E05

serine/threonine

kinase

577.
L0931H07-3

ESTs
L0931H07

BQ557106

578.
K0138B11-3
Trim25
tripartite motif
K0138B11

protein 25

579.
H3019H03-3
Lass6
longevity
H3019H03

assurance

homolog 6 (S. cerevisiae)

580.
J0051F04-3
Ifi30
interferon
J0051F04

gamma

inducible

protein 30

581.
H3106G04-3
Cacna1d
calcium
H3106G04

channel,

voltage-

dependent, L

type, alpha 1D

subunit

582.
L0701D10-3
Arhgdib
Rho, GDP
L0701D10

dissociation

inhibitor (GDI)

beta

583.
H3137A02-3

Mus musculus

H3137A02

10 days neonate

cerebellum

cDNA, RIKEN

full-length

enriched

library,

clone: B930053

B19

product: unknown

EST, full

insert sequence.

584.
L0043D10-3
A530090O15Rik
RIKEN cDNA
L0043D10

A530090O15

gene

585.
H3087D06-3
Etf1
eukaryotic
H3087D06

translation

termination

factor 1

586.
C0827E01-3

Mus musculus

C0827E01

15 days embryo

head cDNA,

RIKEN full-

length enriched

library,

clone: D930031H08

product: unknown

EST, full

insert sequence.

587.
H3053E01-3
B130024B19Rik
RIKEN cDNA
H3053E01

B130024B19

gene

588.
K0117C08-3
BM222243
ESTs
K0117C08

BM222243

589.
H3056D11-3
Ptgfrn
prostaglandin
H3056D11

F2 receptor

negative

regulator

590.
C0228C02-3
2510004L01Rik
RIKEN cDNA
C0228C02

2510004L01

gene

591.
H3144F09-3
Rab7l1
RAB7, member
H3144F09

RAS oncogene

family-like 1

592.
H3052B06-3
Abcb1b
ATP-binding
H3052B06

cassette, sub-

family B

(MDR/TAP),

member 1B

593.
L0273B08-3
Tgif
TG interacting
L0273B08

factor

594.
K0406A08-3
Siat4c
sialyltransferase
K0406A08

4C (beta-

galactoside

alpha-2,3-

sialytransferase)

595.
AF075136.1
Sap30
sin3 associated
AF075136

polypeptide

596.
K0644H12-3
Prkch
protein kinase
K0644H12

C, eta

597.
H3108A04-3
Clu
clusterin
H3108A04

598.
H3020F06-3
Snx10
sorting nexin 10
H3020F06

599.
L0066C05-3
Uxs1
UDP-
L0066C05

glucuronate

decarboxylase 1

600.
L0025F08-3
Rgs19
regulator of G-
L0025F08

protein

signaling 19

601.
H3076F06-3
Siat4a
sialyltransferase
H3076F06

4A (beta-

galactoside

alpha-2,3-

sialytransferase)

602.
C0354G01-3

Mus musculus,
C0354G01

Similar to IQ

motif

containing

GTPase

activating

protein 2, clone

IMAGE: 3596508,

mRNA,

partial cds

603.
C0191H09-3
Atp6v1a1
ATPase, H+
C0191H09

transporting,

V1 subunit A,

isoform 1

604.
H3050G04-3
Dpp7
dipeptidylpeptidase 7
H3050G04

605.
L0219A09-3
Gatm
glycine
L0219A09

amidinotransferase

(L-

arginine:glycine

amidinotransferase)

606.
J0821E02-3
AU040950
expressed
J0821E02

sequence

AU040950

607.
H3080A02-3
Cbfb
core binding
H3080A02

factor beta

608.
C0276B08-3
Plscr1
phospholipid
C0276B08

scramblase 1

609.
C0279E04-3
Srd5a2l
steroid 5 alpha-
C0279E04

reductase 2-like

610.
K0434D04-3
Pgd
phosphogluconate
K0434D04

dehydrogenase

611.
C0174H01-3
Ddx21
DEAD (Asp-
C0174H01

Glu-Ala-Asp)

box polypeptide

21

612.
H3085A07-3
BG070224
ESTs
H3085A07

BG070224

613.
K0208E10-3
Mmab
methylmalonic
K0208E10

aciduria

(cobalamin

deficiency) type

B homolog

(human)

614.
H3006F10-3
Cops2
COP9
H3006F10

(constitutive

photomorphogenic)

homolog,

subunit 2

(Arabidopsis

thaliana)

615.
C0108A10-3
Nek6
NIMA (never in
C0108A10

mitosis gene a)-

related

expressed

kinase 6

616.
H3028H10-3
Ppic
peptidylprolyl
H3028H10

isomerase C

617.
H3121E08-3
Ralgds
ral guanine
H3121E08

nucleotide

dissociation

stimulator

618.
L0266H12-3
Opa1
optic atrophy 1
L0266H12

homolog

(human)

619.
K0635G02-3
2310046K10Rik
RIKEN cDNA
K0635G02

2310046K10

gene

620.
L0704C05-3
2610318G18Rik
RIKEN cDNA
L0704C05

2610318G18

gene

621.
C0303D10-3

UNKNOWN
C0303D10

C0303D10

622.
K0605C04-3
BM240648
ESTs
K0605C04

BM240648

623.
H3071G06-3
BG069012
ESTs
H3071G06

BG069012

624.
C0600A01-3
Coro2a
coronin, actin
C0600A01

binding protein

2A

625.
NM_007679.1
Cebpd
CCAAT/enhancer
NM_007679

binding

protein

(C/EBP), delta

626.
H3048A01-3
Kras2
Kirsten rat
H3048A01

sarcoma

oncogene 2,

expressed

627.
C0267D12-3
Tpp2
tripeptidyl
C0267D12

peptidase II

628.
J1012C06-3
AU041997
ESTs
J1012C06

AU041997

629.
L0072F04-3
Vav2
Vav2 oncogene
L0072F04

630.
L0836H04-3
C030038J10Rik
RIKEN cDNA
L0836H04

C030038J10

gene

631.
K0614A10-3
Sh3kbp1
SH3-domain
K0614A10

kinase binding

protein 1

632.
H3156B08-3
6620401D04Rik
RIKEN cDNA
H3156B08

6620401D04

gene

633.
C0334C11-3
B230339H12Rik
RIKEN cDNA
C0334C11

B230339H12

gene

634.
H3103G05-3
BG071839
ESTs
H3103G05

BG071839

635.
C0205H05-3
1600010D10Rik
RIKEN cDNA
C0205H05

1600010D10

gene

636.
L0513G12-3
Qk
quaking
L0513G12

637.
C0100E08-3
Pdap1
PDGFA
C0100E08

associated

protein 1

638.
J0055B04-3

transcribed
J0055B04

sequence with

strong

similarity to

protein

pir: S12207

(M. musculus)

S12207

hypothetical

protein (B2

element) -

mouse

639.
J0008D10-3
Mbp
myelin basic
J0008D10

protein

640.
K0319D09-3
Mtml
X-linked
K0319D09

myotubular

myopathy gene 1

641.
C0243H05-3
Galnt7
UDP-N-acetyl-
C0243H05

alpha-D-

galactosamine:

polypeptide N-

acetylgalactosaminyltransferase 7

642.
L0841H10-3
BM116846
ESTs
L0841H10

BM116846

643.
K0334D05-3
Ccnd1
cyclin D1
K0334D05

644.
L0209B01-3

L0209B01-3
L0209B01

NIA Mouse

Newborn Ovary

cDNA Library

Mus musculus

cDNA clone

L0209B01 3′,

MRNA

sequence

645.
K0151H10-3
BB129550
EST BB129550
K0151H10

646.
L0505B11-3
Ammecr1
Alport
L0505B11

syndrome,

mental

retardation,

midface

hypoplasia and

elliptocytosis

chromosomal

region gene 1

homolog

(human)

647.
L0944C06-3
BM120800
ESTs
L0944C06

BM120800

648.
J0027C07-3
Mrps25
mitochondrial
J0027C07

ribosomal

protein S25

649.
L0855B04-3
Wdr26
WD repeat
L0855B04

domain 26

650.
H3060H05-3

Mus musculus

H3060H05

cDNA clone

MGC: 28609

IMAGE: 42185

51, complete

cds

651.
K0330G09-3
5830461H18Rik
RIKEN cDNA
K0330G09

5830461H18

gene

652.
L0803E07-3
Dpysl4
dihydropyrimidinase-
L0803E07

like 4

653.
L0283B01-3
Ivnslabp
influenza virus
L0283B01

NS1A binding

protein

654.
L0065G02-3
6530401D17Rik
RIKEN cDNA
L0065G02

6530401D17

gene

655.
C0949A06-3

Mus musculus

C0949A06

0 day neonate

skin cDNA,

RIKEN full-

length enriched

library,

clone: 4632424N07

product: unknown

EST, full

insert sequence.

656.
H3100C11-3
BG071548
ESTs
H3100C11

BG071548

657.
C0142H08-3
3110020O18Rik
RIKEN cDNA
C0142H08

3110020O18

gene

658.
L0945G09-3
Bcl2l11
BCL2-like 11
L0945G09

(apoptosis

facilitator)

659.
L0848H06-3
E130318E12Rik
RIKEN cDNA
L0848H06

E130318E12

gene

660.
K0617B02-3
Bmp2k
BMP2
K0617B02

inducible

kinase

661.
C0203D07-3
Pftk1
PFTAIRE
C0203D07

protein kinase 1

662.
L0267A02-3
2210409B22Rik
RIKEN cDNA
L0267A02

2210409B22

gene

663.
J0086F05-3

transcribed
J0086F05

sequence with

moderate

similarity to

protein

sp: P00722 (E. coli)

BGAL_ECOLI

Beta-

galactosidase

(Lactase)

664.
C0606A03-3
Rps23
ribosomal
C0606A03

protein S23

665.
L0902D02-3
Ncoa6ip
nuclear receptor
L0902D02

coactivator 6

interacting

protein

666.
H3060C12-3
BG067974
ESTs
H3060C12

BG067974

667.
C0611E01-3
Tor3a
torsin family 3,
C0611E01

member A

668.
U54984.1
Mmp14
matrix
U54984

metalloproteinase

14

(membrane-

inserted)

669.
H3089F08-3
0610013E23Rik
RIKEN cDNA
H3089F08

0610013E23

gene

670.
K0633C04-3
Ebi2
Epstein-Barr
K0633C04

virus induced

gene 2

671.
J0943E09-3
Nup62
nucleoporin 62
J0943E09

672.
L0267D03-3
Dcn
decorin
L0267D03

673.
L0250B09-3
1110031E24Rik
RIKEN cDNA
L0250B09

1110031E24

gene

674.
L0915B12-3
Etv3
ets variant gene 3
L0915B12

675.
NM_009403.1
Tnfsf8
tumor necrosis
NM_009403

factor (ligand)

superfamily,

member 8

676.
C0308F04-3
2700064H14Rik
RIKEN cDNA
C0308F04

2700064H14

gene

677.
C0288G12-3
6030400A10Rik
RIKEN cDNA
C0288G12

6030400A10

gene

678.
H3005A11-3
Fancd2
Fanconi
H3005A11

anemia,

complementation

group D2

679.
H3121H07-3
2810405I11Rik
RIKEN cDNA
H3121H07

2810405I11

gene

680.
K0124A06-3
BM222608
ESTs
K0124A06

BM222608

681.
NM_010835.1
Msx1
homeo box,
NM_010835

msh-like 1

682.
K0134C07-3
Falz
fetal Alzheimer
K0134C07

antigen

683.
K0424H02-3
Pfkp
phosphofructokinase,
K0424H02

platelet

684.
H3153G06-3
8030446C20Rik
RIKEN cDNA
H3153G06

8030446C20

gene

685.
H3071C09-3
BG068971
ESTs
H3071C09

BG068971

686.
L0243B07-3

Possibly
L0243B07

intronic in

U008124-

L0243B07

687.
C0143D11-3
Ii
Ia-associated
C0143D11

invariant chain

688.
L0512A02-3
Snx5
sorting nexin 5
L0512A02

689.
K0112C06-3
Atp8a1
ATPase,
K0112C06

aminophospholipid

transporter

(APLT), class I,

type 8A,

member 1

690.
H3053A01-3
Tnfsf13b
tumor necrosis
H3053A01

factor (ligand)

superfamily,

member 13b

691.
C0668F08-3
Atp6ap2
ATPase, H+
C0668F08

transporting,

lysosomal

accessory

protein 2

692.
K0417E05-3
Osmr
oncostatin M
K0417E05

receptor

693.
NM_010872.1
Birc1b
baculoviral IAP
NM_010872

repeat-

containing 1b

694.
L0262G06-3
Cfh
complement
L0262G06

component

factor h

695.
J0249F06-3
2210023K21Rik
RIKEN cDNA
J0249F06

2210023K21

gene

696.
C0170A02-3
Serpinb9
serine (or
C0170A02

cysteine)

proteinase

inhibitor, clade

B, member 9

697.
H3076C12-3
Facl4
fatty acid-
H3076C12

Coenzyme A

ligase, long

chain 4

698.
H3155C07-3
1810036L03Rik
RIKEN cDNA
H3155C07

1810036L03

gene

699.
K0331C04-3
Sdccag8
serologically
K0331C04

defined colon

cancer antigen 8

700.
J0538B04-3
Laptm5
lysosomal-
J0538B04

associated

protein

transmembrane 5

701.
H3014E07-3
1810029G24Rik
RIKEN cDNA
H3014E07

1810029G24

gene

702.
K0515H12-3
2900064A13Rik
RIKEN cDNA
K0515H12

2900064A13

gene

703.
H3159D10-3
BG076403
ESTs
H3159D10

BG076403

704.
K0127F02-3
Prg
proteoglycan,
K0127F02

secretory

granule

705.
L0919B08-3
Bnip3l
BCL2/adenovirus
L0919B08

E1B 19 kDa-

interacting

protein 3-like

706.
J0904A09-3
1110060F11Rik
RIKEN cDNA
J0904A09

1110060F11

gene

707.
L0270B06-3
D11Ertd759e
DNA segment,
L0270B06

Chr 11,

ERATO Doi

759, expressed

708.
K0230D06-3
Eaf1
ELL associated
K0230D06

factor 1

709.
K0611A03-3
AI447904
expressed
K0611A03

sequence

AI447904

710.
H3155A07-3
BG076050
ESTs
H3155A07

BG076050

711.
H3028H11-3
Ctsh
cathepsin H
H3028H11

712.
L0001D12-3
4833422F06Rik
RIKEN cDNA
L0001D12

4833422F06

gene

713.
L0951G01-3
BG061831
ESTs
L0951G01

BG061831

714.
H3035G02-3
AI314180
expressed
H3035G02

sequence

AI314180

715.
C0925G02-3
Fer1l3
fer-1-like 3,
C0925G02

myoferlin (C. elegans)

716.
C0103H10-3
Il17r
interleukin 17
C0103H10

receptor

717.
H3129F05-3
Mrpl16
mitochondrial
H3129F05

ribosomal

protein L16

718.
L0942B12-3

Mus musculus

L0942B12

12 days embryo

spinal ganglion

cDNA, RIKEN

full-length

enriched

library,

clone: D130046C24

product: unknown

EST, full

insert sequence.

719.
L0009B09-3
Plcg2
phospholipase
L0009B09

C, gamma 2

720.
C0665B08-3
Sh3bp1
SH3-domain
C0665B08

binding protein 1

721.
H3102F04-3
Rgs10
regulator of G-
H3102F04

protein

signalling 10

722.
K0547F06-3

transcribed
K0547F06

sequence with

moderate

similarity to

protein

sp: P00722 (E. coli)

BGAL_ECOLI

Beta-

galactosidase

(Lactase)

723.
H3087C07-3
Glb1
galactosidase,
H3087C07

beta 1

724.
J0437D05-3
AU023716
ESTs
J0437D05

AU023716

725.
H3156A09-3
Pex12
peroxisomal
H3156A09

biogenesis

factor 12

726.
G0108H12-3
Ly6e
lymphocyte
G0108H12

antigen 6

complex, locus E

727.
H3098D12-5
Map2k1
mitogen
H3098D12

activated

protein kinase

kinase 1

728.
C0637C02-3
Zmpste24
zinc
C0637C02

metalloproteinase,

STE24

homolog (S. cerevisiae)

729.
H3119B06-3
Atp1b3
ATPase,
H3119B06

Na+/K+

transporting,

beta 3

polypeptide

730.
C0176B06-3
Ubl1
ubiquitin-like 1
C0176B06

731.
C0626D04-3
9130404D14Rik
RIKEN cDNA
C0626D04

9130404D14

gene

732.
H3155E07-3
Dock4
dedicator of
H3155E07

cytokinesis 4

733.
C0106A05-3
H2-Eb1
histocompatibility
C0106A05

2, class II

antigen E beta

734.
H3037B09-3

Mus musculus

H3037B09

12 days embryo

spinal cord

cDNA, RIKEN

full-length

enriched

library,

clone: C530028D16

product: 231000

8H09RIK

PROTEIN

homolog [Mus

musculus], full

insert sequence.

735.
H3003B09-3
F730017H24Rik
RIKEN cDNA
H3003B09

F730017H24

gene

736.
C0909E10-3
Pign
phosphatidylinositol
C0909E10

glycan,

class N

737.
H3045G01-3
BG066588
ESTs
H3045G01

BG066588

738.
H3006E10-3

transcribed
H3006E10

sequence with

weak similarity

to protein

sp: Q9H321

(H. sapiens)

VCXC_HUMAN

VCX-C

protein

(Variably

charged protein

X-C)

739.
H3098H09-3
2310016E02Rik
RIKEN cDNA
H3098H09

2310016E02

gene

740.
J0540D09-3
Adam9
a disintegrin
J0540D09

and

metalloproteinase

domain 9

(meltrin

gamma)

741.
L0208C06-3
Pknox1
Pbx/knotted 1
L0208C06

homeobox

742.
H3154G05-3
Napg
N-
H3154G05

ethylmaleimide

sensitive fusion

protein

attachment

protein gamma

743.
L0854E11-3
1500032M01Rik
RIKEN cDNA
L0854E11

1500032M01

gene

744.
H3014C06-3
B2m
beta-2
H3014C06

microglobulin

745.
K0538G12-3
Ccr2
chemokine (C-
K0538G12

C) receptor 2

746.
J0819C09-3
C030002B11Rik
RIKEN cDNA
J0819C09

C030002B11

gene

747.
C0175B11-3
Hist1h2bc
histone 1, H2bc
C0175B11

748.
H3009B11-3
Nufip1
nuclear fragile
H3009B11

X mental

retardation

protein

interacting

protein

749.
H3135D02-3
Lamp2
lysosomal
H3135D02

membrane

glycoprotein 2

750.
K0540G08-3
1200013B08Rik
RIKEN cDNA
K0540G08

1200013B08

gene

751.
H3089H05-3
Lnx2
ligand of numb-
H3089H05

protein X 2

752.
J0203A08-3
C85149
ESTs C85149
J0203A08

753.
H3119F01-3
Mcfd2
multiple
H3119F01

coagulation

factor

deficiency 2

754.
H3134C05-3
Mglap
matrix gamma-
H3134C05

carboxyglutamate

(gla) protein

755.
C0147D11-3
B230215M10Rik
RIKEN cDNA
C0147D11

B230215M10

gene

756.
C0949H10-3
Sulf1
sulfatase 1
C0949H10

757.
K0114E04-3
BM222075
ESTs
K0114E04

BM222075

758.
H3012C03-3
Cappa1
capping protein
H3012C03

alpha 1

759.
C0507E11-3
BE824970
ESTs
C0507E11

BE824970

760.
H3158D06-3
Lnk
linker of T-cell
H3158D06

receptor

pathways

761.
C0174C02-3
Pold3
polymerase
C0174C02

(DNA-

directed), delta

3, accessory

subunit

762.
C0130G10-3
Cklfsf7
chemokine-like
C0130G10

factor super

family 7

763.
C0137F07-3
Pik3cb
phosphatidylinositol
C0137F07

3-kinase,

catalytic, beta

polypeptide

764.
H3115F01-3
2610027O18Rik
RIKEN cDNA
H3115F01

2610027O18

gene

765.
H3097F03-3

Mus musculus,
H3097F03

clone

IMAGE: 53723

38, mRNA

766.
H3059A05-3
Mad2l1
MAD2 (mitotic
H3059A05

arrest deficient,

homolog)-like 1

(yeast)

767.
L0935E02-3
Syk
spleen tyrosine
L0935E02

kinase

768.
C0946F08-3
1110014L17Rik
RIKEN cDNA
C0946F08

1110014L17

gene

769.
H3079F02-5

Possibly
H3079F02

intronic in

U011488-

H3079F02

770.
H3137E07-3
Il10ra
interleukin 10
H3137E07

receptor, alpha

771.
C0143H12-3
Galns
galactosamine
C0143H12

(N-acetyl)-6-

sulfate sulfatase

772.
H3114D03-3
Man2a1
mannosidase 2,
H3114D03

alpha 1

773.
H3041H09-3
BG066348
ESTs
H3041H09

BG066348

774.
C0628H04-3
Slc2a12
solute carrier
C0628H04

family 2,

member 12

775.
K0125E07-3
Ifngr
interferon
K0125E07

gamma receptor

776.
G0115E02-3
Sdcbp
syndecan
G0115E02

binding protein

777.
C0032B05-3
Rap2b
RAP2B,
C0032B05

member of

RAS oncogene

family

778.
H3141C08-3
Ofd1
oral-facial-
H3141C08

digital

syndrome 1

gene homolog

(human)

779.
H3157C05-3
BG076236
ESTs
H3157C05

BG076236

780.
H3076A01-3
5031439G07Rik
RIKEN cDNA
H3076A01

5031439G07

gene

781.
H3080D06-3
BC018507
cDNA sequence
H3080D06

BC018507

782.
L0518D04-3
Uap1
UDP-N-
L0518D04

acetylglucosamine

pyrophosphorylase 1

783.
K0542B11-3
BM239901
ESTs
K0542B11

BM239901

784.
L0959D03-3
Tnfrsf1a
tumor necrosis
L0959D03

factor receptor

superfamily,

member 1a

785.
H3035C07-3
BG065787
ESTs
H3035C07

BG065787

786.
M29855.1
Csf2rb2
colony
M29855

stimulating

factor 2

receptor, beta 2,

low-affinity

(granulocyte-

macrophage)

787.
C0352C11-3
BM197981
ESTs
C0352C11

BM197981

788.
L0846B10-3
BM117093
ESTs
L0846B10

BM117093

789.
L0227C06-3
Serpinb6a
serine (or
L0227C06

cysteine)

proteinase

inhibitor, clade

B, member 6a

790.
J0214H09-3
Serpina3g
serine (or
J0214H09

cysteine)

proteinase

inhibitor, clade

A, member 3G

791.
H3077F12-3
Arhh
ras homolog
H3077F12

gene family,

member H

792.
C0341D05-3
BM196992
ESTs
C0341D05

BM196992

793.
H3043H11-3
BG066522
ESTs
H3043H11

BG066522

794.
K0507D06-3

Mus musculus,
K0507D06

clone

IMAGE: 1263252,

mRNA

795.
J0535D11-3
AU020606
ESTs
J0535D11

AU020606

796.
H3152F04-3
Sepp1
selenoprotein P,
H3152F04

plasma, 1

797.
L0701F07-3
H2-Ab1
histocompatibility
L0701F07

2, class II

antigen A, beta 1

798.
L0227H07-3
Clca1
chloride
L0227H07

channel calcium

activated 1

799.
J1014C11-3
2900036G02Rik
RIKEN cDNA
J1014C11

2900036G02

gene

800.
H3134H09-3
BG074421
ESTs
H3134H09

BG074421

801.
G0116A07-3
Atp6v1c1
ATPase, H+
G0116A07

transporting,

V1 subunit C,

isoform 1

802.
L0942F05-3
Ostm1
osteopetrosis
L0942F05

associated

transmembrane

protein 1

803.
C0912H10-3
0610041E09Rik
RIKEN cDNA
C0912H10

0610041E09

gene

804.
C0304E12-3
Pde1b
phosphodiesterase
C0304E12

1B, Ca2+-

calmodulin

dependent

805.
L0605C12-3
4930579K19Rik
RIKEN cDNA
L0605C12

4930579K19

gene

806.
K0539A07-3
Cd53
CD53 antigen
K0539A07

807.
L0228H12-3
6430628I05Rik
RIKEN cDNA
L0228H12

6430628I05

gene

808.
L0855B10-3
BM117713
ESTs
L0855B10

BM117713

809.
H3075B10-3
2810404F18Rik
RIKEN cDNA
H3075B10

2810404F18

gene

810.
L0022G07-3

L0022G07-3
L0022G07

NIA Mouse

E12.5 Female

Mesonephros

and Gonads

cDNA Library

Mus musculus

cDNA clone

L0022G07 3′,

MRNA

sequence

811.
H3107C11-3
Efemp2
epidermal
H3107C11

growth factor-

containing

fibulin-like

extracellular

matrix protein 2

812.
H3025H12-3
1200003O06Rik
RIKEN cDNA
H3025H12

1200003O06

gene

813.
J0040E05-3
Stx3
syntaxin 3
J0040E05

814.
H3075F03-3
C1s
complement
H3075F03

component 1, s

subcomponent

815.
L0600G09-3
BM125147
ESTs
L0600G09

BM125147

816.
K0115H01-3
KLHL6
kelch-like 6
K0115H01

817.
H3015B10-3
Gus
beta-
H3015B10

glucuronidase

818.
H3108A12-3
0910001A06Rik
RIKEN cDNA
H3108A12

0910001A06

gene

819.
H3108H09-5

UNKNOWN:
H3108H09

Similar to

Homo sapiens

KIAA1577

protein

(KIAA1577),

mRNA

820.
K0645H01-3
Fyb
FYN binding
K0645H01

protein

821.
H3029A02-3
Shyc
selective
H3029A02

hybridizing

clone

822.
K0410D10-3
Cxcl12
chemokine
K0410D10

(C—X—C motif)

ligand 12

823.
H3118H11-3
Snrpg
small nuclear
H3118H11

ribonucleoprote

in polypeptide G

824.
K0517D08-3
BM238427
ESTs
K0517D08

BM238427

825.
L0227G11-3
Sh3d1B
SH3 domain
L0227G11

protein 1B

826.
H3134B10-3
6530409L22Rik
RIKEN cDNA
H3134B10

6530409L22

gene

827.
H3115A08-3
Ly6a
lymphocyte
H3115A08

antigen 6

complex, locus A

828.
C0120G03-3
Csk
c-src tyrosine
C0120G03

kinase

829.
H3094G08-3
Tigd2
tigger
H3094G08

transposable

element derived 2

830.
NM_008362.1
Il1r1
interleukin 1
NM_008362

receptor, type I

831.
C0300E10-3
Trps1
trichorhinophal
C0300E10

angeal

syndrome I

(human)

832.
L0274A03-3
Ptpn2
protein tyrosine
L0274A03

phosphatase,

non-receptor

type 2

833.
H3005H07-3
1810031K02Rik
RIKEN cDNA
H3005H07

1810031K02

gene

834.
H3109H12-3
1810009M01Rik
RIKEN cDNA
H3109H12

1810009M01

gene

835.
J0008D01-3
Enpp1
ectonucleotide
J0008D01

pyrophosphatase/

phosphodiesterase 1

836.
H3119H05-3
Mafb
v-maf
H3119H05

musculoaponeurotic

fibrosarcoma

oncogene

family, protein

B (avian)

837.
H3048G11-3
Blvrb
biliverdin
H3048G11

reductase B

(flavin

reductase

(NADPH))

838.
H3107D05-3
1110004C05Rik
RIKEN cDNA
H3107D05

1110004C05

gene

839.
H3006B01-3
Cklfsf3
chemokine-like
H3006B01

factor super

family 3

840.
L0853H04-3

transcribed
L0853H04

sequence with

weak similarity

to protein

pir: A43932

(H. sapiens)

A43932 mucin

2 precursor,

intestinal -

human

(fragments)

841.
C0949G05-3
BM221093
ESTs
C0949G05

BM221093

842.
K0648D10-3
Tlr1
toll-like
K0648D10

receptor 1

843.
H3014E09-3
BC017643
cDNA sequence
H3014E09

BC017643

844.
H3022D06-3
Il2rg
interleukin 2
H3022D06

receptor,

gamma chain

845.
L0201A03-3
2410004H05Rik
RIKEN cDNA
L0201A03

2410004H05

gene

846.
H3026E03-5

Mus musculus

H3026E03

2 days neonate

thymus thymic

cells cDNA,

RIKEN full-

length enriched

library,

clone: E430039

C10

product: unknown

EST, full

insert sequence

847.
H3091E12-3
Abhd2
abhydrolase
H3091E12

domain

containing 2

848.
H3003E01-3
Cutl1
cut-like 1
H3003E01

(Drosophila)

849.
H3016H08-5
Crsp9
cofactor
H3016H08

required for

Sp1

transcriptional

activation,

subunit 9,

33 kDa

850.
C0118E09-3
Oas1a
2′-5′
C0118E09

oligoadenylate

synthetase 1A

851.
L0535B02-3
Col15a1
procollagen,
L0535B02

type XV

852.
L0500E02-3
Sgcg
sarcoglycan,
L0500E02

gamma

(dystrophin-

associated

glycoprotein)

853.
H3077B08-3
5330431K02Rik
RIKEN cDNA
H3077B08

5330431K02

gene

854.
J0209G02-3
Gnb4
guanine
J0209G02

nucleotide

binding protein,

beta 4

855.
C0661E01-3
Lcn7
lipocalin 7
C0661E01

856.
K0221E09-3
Scml2
sex comb on
K0221E09

midleg-like 2

(Drosophila)

857.
C0184F12-3
D8Ertd594e
DNA segment,
C0184F12

Chr 8, ERATO

Doi 594,

expressed

858.
L0602B03-3
Myoz2
myozenin 2
L0602B03

859.
C0944F04-3
1110055E19Rik
RIKEN cDNA
C0944F04

1110055E19

gene

860.
L0004A03-3
Gli2
GLI-Kruppel
L0004A03

family member

GLI2

861.
L0860B03-3

ESTs
L0860B03

AV321020

862.
L0841F10-3
2310045A20Rik
RIKEN cDNA
L0841F10

2310045A20

gene

863.
L0008H10-3
Agrn
agrin
L0008H10

864.
C0128B02-3
Casq1
calsequestrin 1
C0128B02

865.
C0645C09-3
BM209340
ESTs
C0645C09

BM209340

866.
H3082B03-3
Mylk
myosin, light
H3082B03

polypeptide

kinase

867.
C0309D09-3

transcribed
C0309D09

sequence with

moderate

similarity to

protein

sp: P00722 (E. coli)

BGAL_ECOLI

Beta-

galactosidase

(Lactase)

868.
H3157H09-3
BG076287
ESTs
H3157H09

BG076287

869.
H3061D03-3
Pcsk5
proprotein
H3061D03

convertase

subtilisin/kexin

type 5

870.
L0843D01-3
3732412D22Rik
RIKEN cDNA
L0843D01

3732412D22

gene

871.
L0702H07-3
5830415L20Rik
RIKEN cDNA
L0702H07

5830415L20

gene

872.
L0548G08-3
Xin
cardiac
L0548G08

morphogenesis

873.
L0803E02-3
Nkd1
naked cuticle 1
L0803E02

homolog

(Drosophila)

874.
C0925G12-3
Fbxo30
F-box protein
C0925G12

30

875.
L0911A11-3
2010313D22Rik
RIKEN cDNA
L0911A11

2010313D22

gene

876.
AF084466.1
Rrad
Ras-related
AF084466

associated with

diabetes

877.
H3073G09-3
1600029N02Rik
RIKEN cDNA
H3073G09

1600029N02

gene

878.
L0815B08-3
1100001D19Rik
RIKEN cDNA
L0815B08

1100001D19

gene

879.
J1037H05-3
D230016N13Rik
RIKEN cDNA
J1037H05

D230016N13

gene

880.
K0421F09-3

transcribed
K0421F09

sequence with

weak similarity

to protein

ref: NP_081764.1

(M. musculus)

RIKEN cDNA

5730493B19

[Mus musculus]

881.
H3082E06-3
1110003B01Rik
RIKEN cDNA
H3082E06

1110003B01

gene

882.
C0935B04-3
Hhip
Hedgehog-
C0935B04

interacting

protein

883.
H3116B02-3
1110007C05Rik
RIKEN cDNA
H3116B02

1110007C05

gene

884.
C0945G10-3
Tp53i11
tumor protein
C0945G10

p53 inducible

protein 11

885.
K0440G09-3
Tgfb3
transforming
K0440G09

growth factor,

beta 3

886.
L0916G12-3
BM118833
ESTs
L0916G12

BM118833

887.
L0505A04-3
Dnajb5
DnaJ (Hsp40)
L0505A04

homolog,

subfamily B,

member 5

888.
L0542E08-3
Usmg4
upregulated
L0542E08

during skeletal

muscle growth 4

889.
L0223E12-3
Sparcl1
SPARC-like 1
L0223E12

(mast9, hevin)

890.
K0349C07-3
4631423F02Rik
RIKEN cDNA
K0349C07

4631423F02

gene

891.
C0302A11-3

EST BI988881
C0302A11

892.
C0930C11-3
Fgf13
fibroblast
C0930C11

growth factor

13

893.
H3022A11-3
Cald1
caldesmon 1
H3022A11

894.
C0660B06-3
Csrp1
cysteine and
C0660B06

glycine-rich

protein 1

895.
L0949F12-3
Heyl
hairy/enhancer-
L0949F12

of-split related

with YRPW

motif-like

896.
K0225B06-3
Unc5c
unc-5 homolog
K0225B06

C (C. elegans)

897.
K0541E04-3
Herc3
hect domain
K0541E04

and RLD 3

898.
C0151A03-3
BC026744
cDNA sequence
C0151A03

BC026744

899.
L0045C07-3
6-Sep
septin 6
L0045C07

900.
L0509E03-3
Ryr2
ryanodine
L0509E03

receptor 2,

cardiac

901.
H3049B08-3
Tes
testis derived
H3049B08

transcript

902.
L0533C09-3
BM123974
ESTs
L0533C09

BM123974

903.
H3108C01-3
4930444A02Rik
RIKEN cDNA
H3108C01

4930444A02

gene

904.
C0110C06-3
Epb4.1l1
erythrocyte
C0110C06

protein band

4.1-like 1

905.
C0324H08-3
Enah
enabled
C0324H08

homolog

(Drosophila)

906.
C0917A09-3

ESTs
C0917A09

BB231855

907.
L0854B10-3
Anks1
ankyrin repeat
L0854B10

and SAM

domain

containing 1

908.
K0326D08-3
Ly75
lymphocyte
K0326D08

antigen 75

909.
H3074H01-3
C430017H16
hypothetical
H3074H01

protein

C430017H16

910.
H3131D02-3
Tnk2
tyrosine kinase,
H3131D02

non-receptor, 2

911.
C0112B03-3
Heyl
hairy/enhancer-
C0112B03

of-split related

with YRPW

motif-like

912.
L0514A09-3
6430511F03
hypothetical
L0514A09

protein

6430511F03

913.
C0234D07-3
Fbxo30
F-box protein
C0234D07

30

914.
H3152A02-3
St6gal1
beta galactoside
H3152A02

alpha 2,6

sialyltransferase 1

915.
H3075C04-3
Ches1
checkpoint
H3075C04

suppressor 1

916.
L0600E02-3
BM125123
ESTs
L0600E02

BM125123

917.
K0501F10-3
BM237456
ESTs
K0501F10

BM237456

918.
K0301H08-3
Oxct
3-oxoacid CoA
K0301H08

transferase

919.
L0229E07-3
Lu
Lutheran blood
L0229E07

group

(Auberger b

antigen

included)

920.
H3077C06-3
4931430I01Rik
RIKEN cDNA
H3077C06

4931430I01

gene

921.
J0807D02-3

Mus musculus

J0807D02

10 days neonate

cerebellum

cDNA, RIKEN

full-length

enriched

library,

clone: B930022I23

product: unclassifiable,

full

insert sequence.

922.
H3118G11-3
C130068N17
hypothetical
H3118G11

protein

C130068N17

923.
L0818F01-3
Smarcd3
SWI/SNF
L0818F01

related, matrix

associated,

actin dependent

regulator of

chromatin,

subfamily d,

member 3

924.
C0359A10-3
BM198389
ESTs
C0359A10

BM198389

925.
G0108E12-3
1190009E20Rik
RIKEN cDNA
G0108E12

1190009E20

gene

926.
C0941C09-3
Gja7
gap junction
C0941C09

membrane

channel protein

alpha 7

927.
H3111B03-5

UNKNOWN
H3111B03

H3111B03

SEQ

ID
UG
CHR_LOCATION
60mer

NO:
CLUSTER
PENG [A]
SEQUENCE

1.

No Chromosome location
ATGAGCCTAGA

info available
ACTCACATGCA

TTTTCCTGACT

TCTATCATTAG

AATAAGTTCAT

CAAGA

2.
Mm.389
Chromosome 15
CCTATTGTTGA

GTGTCAAACAT

CACCACTAAGT

GGATGGTTATG

TAGTCCATTAT

CCAAA

3.
Mm.103301
Chromosome 4
TACCTGAACCA

CTCTCTACTGT

TGTTGTCACAA

GGCAAAAGTG

GCATTCCTTCC

TCCAAG

4.
Mm.231395
Chromosome 7
CCCTTTGCTGT

GTGGGCAGTAC

TCTGAAGCAGG

CAAATGGGTCT

TAGGATCCCTC

CCAGA

5.
Mm.222000
Chromosome 6
TCCAAAGATAA

AATGAGCAAC

CGCACTGGCTT

AGCCATAGATG

ACTGACAGTGA

TTGGAA

6.
Mm.10756
Chromosome 1
TGCCTTGGAGG

GCAACAAGGA

GCAGATACAG

AAGATCATTGA

GACACTGTTCA

CAGCAGC

7.
Mm.268474
Chromosome 10
CATGAATTCCA

AACCAGTTATT

ATTAACATGAA

CCTGAACCTGA

ACAATTATGAC

TGTGC

8.
Mm.45436
Chromosome 10
TTTCTGTCACT

GCTCAGGCCAA

GGTCTATGAAC

GTTGTGAGTTT

GCCAGAACTCT

GAAAA

9.
Mm.39102
Chromosome 4
TTCATACCAAG

GAACCTGACCT

CTCTGACAATT

GCATTTTGAAC

ATTGTTGTCCC

CAAAG

10.
Mm.247272
Chromosome 16
CATTGGAAACA

GACACGTTTGT

AGGCATTTGCG

TATTCTTGAAG

AGACTGTTTTA

TGAAT

11.
Mm.200506
Chromosome 12
GTAATGGAGA

ATGTATCTGAA

CCCATATCAAG

CCATCTCTCTT

CCTTAACATGT

TAAGCA

12.
Mm.7044
Chromosome 2
ACACCTCTAAC

TCCCAAGAAG

ACGGAGTGAA

TGTCCTCTCCT

TTACTTGTGAA

ATCATTT

13.
Mm.6793
Chromosome 7
GTGAGATTCGG

CAGCATAAATT

GCGGAAACTG

AACCCACCCGA

TGAGAGTGGTC

CTGGCT

14.
Mm.8245
Chromosome X
TCATAAGGGCT

AAATTCATGGG

TTCCCCAGAAA

TCAACGAGACC

ACCTTATACCA

GCGTT

15.
Mm.217235
Chromosome 5
AAAGACTGAG

AGGAGTCATG

AACCAGGGTA

AAACTTATTGG

TGCTTTGAGAC

TTCCAGCA

16.
Mm.230301
Chromosome 15
GCAGCATCGCT

TCCTTGGTTTA

TTCTTTGTGTTT

GTTCCTTCAGT

AAACATTTATT

GAGC

17.

Chromosome 2
TTTTAACGGAG

CCTGAATATAG

CAGGTTTAAAA

TTTAAACAGGT

ATAAAATGAA

AAATAA

18.
Mm.36571
Chromosome 4
TAGCATGAACC

ACCATGTTTGG

CAATACTGTAT

TTTAGAAAGAA

TTAATGGACTG

GAGAG

19.
Mm.46424
Chromosome 11
CCTGAGCTCAC

TGTTTCTCATG

CTGTCTTGAGA

CAAAGTATCCA

TATGGAACCTA

GGTTA

20.
Mm.44508
Chromosome 1
GCTGGTGTTTG

TGTCAAGAAA

ATGGCTGAAGC

TTGTTTCCAGG

CTGTAGGAATG

TTGAAC

21.
Mm.4909
Chromosome 4
ACTTAAGTTAT

CTGCATAGAGG

CAATCCTCCTG

GGTTTGCTTTA

TGTCTCGAAAA

TCTAA

22.
Mm.26437
Chromosome 12
GGGCAAAGGT

ACTTTCTGACA

AACTGAGTACC

TGAGATCAACC

CCCAAGAAGG

GAAAAAA

23.
Mm.295683
Chromosome 5
ACTATGCAATT

GGACAGATGG

ATTACCAAGGA

GACTAAAAAT

ATATTCTTTGA

CTTTGGG

24.
Mm.195099
Chromosome 5
TCACTGACCTC

AACCCCTCCTG

CAGAGAAGCC

TGAAGACCCCA

AAAGCTGCCA

GTCCAAA

25.
Mm.196617
Chromosome 10
GATATAATGTG

ATAAAGTTCCA

AAAGGATCTCT

CTGGCTGAAGG

AGATACTGGAT

GGAAC

26.
Mm.260421
No Chromosome location
CTGAACCCCAA

info available
TTAATAGCAAA

GGATATATCTC

TCTTCAAAAAC

GGATAGATTTC

TGAAG

27.
Mm.3333
Chromosome 6
TTTTGTTCTCTC

CATCTGTTAGC

CGTTCTGAGGA

CTGAATGCAGA

TTGTCAGCTCA

AAAA

28.
Mm.37657
Chromosome 16
GCCAATCTCAG

AACCCACATAG

AAGGGTCTGCA

GTATTATTCCT

GTTTCATGTGT

GCACA

29.
Mm.156914
Chromosome 11
AGTGCAAAATT

TGGTTTGTTGG

TGTGCTTTTCT

GGTTTAGGAGC

CTGAAACAAG

CACACT

30.
Mm.30074
Chromosome 11
CATGAGTAAGT

TGTGAAGGCTG

GACCCACATCT

TGATACTTGTT

TTCTGCATCTT

GGGCA

31.
Mm.217705
Chromosome 12
TAGACGTTGTA

AAAAGGAGCC

AAGTTTATCAT

TTTGTTCCTTA

AATCCGTCATA

TGTGGG

32.
Mm.1650
Chromosome 11
ACTGTGGTGAC

AGCTTCCTAAC

GTGTTTGTGTC

TAAAATAAACT

ATCCTTAGCAT

CCTTC

33.
Mm.103987
Chromosome 15
TATAAATAGAA

AGTGAACCTGT

AACCTACCACG

GTATCTATCAT

AACACTAGACT

TTCAG

34.
Mm.22753
Chromosome 14
CATCCTACAAA

GAGGATAAGC

ACTTTGGGTAC

ACTTCCTACAG

CGTGTCTAACA

GTGTGA

35.
Mm.143774
Chromosome Multiple
CCTGAAAATCT

Mappings
GTCATGTCCAC

CTTGGAGCCTG

AGTAACTTTGA

ACAGCTGGTAA

CTAGT

36.

Chromosome 17
AGTCAAGGAG

CCTAAAGATTA

TTATGTCAGAG

AGACCAGCTTT

AGATACACCCC

TGAGCA

37.
Mm.19325
Chromosome 10
TTATGCTGCAG

TTTCACTTGGA

AAAGGGACAA

GGAGCCTTCTA

TTGTCCCCTGT

TTGTAG

38.
Mm.100525
Chromosome 9
GTAACCAAGA

GCCCTGAATAA

GGAATTCATTG

TAGTAGTGAAA

GGGAAACTAA

TGCTCTT

39.
Mm.32810
Chromosome 4
TCCCATGCCTT

CCCAGAGGGA

ATTTTAACAAT

GTAACAATAA

ATGCTTGGCCT

TGAAGCT

40.
Mm.182645
Chromosome 9
AGGACATCTTC

CCAGATCTCAA

AAGAAGAAGA

GAGCCTGTAAC

CACCTCCATGA

CCTAAA

41.
Mm.262549
Chromosome 6
TCCTGTGGGAG

ATCCCATAAAT

CCTGAACCTCA

CGTAGTGTTAC

TTTTCCAGGTC

ATTCT

42.
Mm.253853
Chromosome 13
CGACGACGAG

TTCGAAGACGA

CCTGCTCGACC

TGAACCCCAGC

TCAAACTTTGA

GAGCAT

43.
Mm.171544
Chromosome 12
GAAGAGATGG

AAGATGGTAGT

GCCTTGAACAC

AGCCACCCAA

GCAAAGTTGA

AGAACAGG

44.
Data not found
Chromosome 9
GCCTGCAGGA

GTTTGTGTTGG

TAGCCTCCAAG

GAGCTGGAAT

GTGCTGAAGAT

CCAGGCT

45.
Mm.1682
Chromosome 2
CTGTCTTCTAA

TTCCAAAGGGT

TGGTTGGTAAA

GCTCCACCCCC

TTTTCCTTTGC

CTAAA

46.
Mm.123240
No Chromosome location
TTCACAGGGTT

info available
CCTGGTGTTGC

ATGCAGAGCCT

GAACAAAAGA

CTCAGGTGGAC

CTGGAA

47.
Mm.41932
Chromosome 17
TCTACAAGGAA

GCATTCAACCA

CCAAGAGGAG

CTTGGACCACG

TTCACTCTGTA

TTCTTT

48.
Mm.173544
Chromosome 4
GGGCCTGAACT

ATGGCTTAATT

TACATTAATTA

GTTAACATTAA

49.
Mm.149539
Chromosome 2
TCACACAGTAA

GGAGC

TGTGTTGTGAT

TTCAACTCCCA

AGACGCCCTTT

ATGTCCATTCT

GGAAAAATAC

AATAAA

50.
Mm.370
Chromosome 4
ACTGATGTTTC

TGCACACTGCC

CAGTGGTTTCT

TTAAGCACTTT

CTGGAATAAAC

GATCC

51.
Mm.28614
Chromosome 1
TCACAGATGTA

TGTGGAGGGGT

TGTTTTCTGAG

TACTAGACTAC

CCTCTGTGGTT

ATAAA

52.
Mm.24145
Chromosome 12
TCGGGGATGG

AGCTGAGATGT

TCCACCACAAC

CCAAGATCTAA

GAGTATTGTTT

TGAAGA

53.
Mm.159218
Chromosome 16
GGAGACTGAA

GCTTTTATTGT

TTAATGTTGAA

GATATTGATCT

ACAAGGTGGG

AATGGTG

54.
Mm.217664
Chromosome 2
AACTGTGGGTA

TAATTGTAAGA

GCCTGAAACTT

CCAGAACTGG

AGAAACTGTCA

CTGGGA

55.
Mm.221743
Chromosome 17
GTGTTGTGATT

GTCGTCCCTGC

TTAATGAACCC

ACCTGAGGGA

CAGTTAGTGTC

TTACCC

56.
Mm.206775
Chromosome 5
CTATATGAACT

GAGAAACAAC

ACGTATGCTGA

ACCCCAATTCT

ACAACAAAGT

CTACGCC

57.
Mm.32373
Chromosome 3
GGAATATATTA

TGTAGACTATT

CTGGCCTGAAC

CTTGTGGTTGA

CTGATGCTCTG

CCTCC

58.
Mm.261771
Chromosome 14
TTGGGTGATCC

ATATTTTTCAA

ACCCATACTCC

CAAAAGGAGA

CCTACTTAAAT

TTCTCT

59.
Mm.252843
Chromosome 10
GTTCCTGAAGC

TCTTGATATTT

TAGGACAAAA

CCCACCACGAC

AAAATGAGAA

GGAATTT

60.
Mm.27451
Chromosome 7
TGACTTCAAAT

GTCCCATCCCA

CCCAAAGAGC

CTGTGATAACA

GATGTCTCTGG

CTATAT

61.
Mm.15781
Chromosome 7
TGGGTAGGTTC

CTAGGTCTCCC

TGATATCTAAG

CTACAGTTATA

CTGTAGCTGTG

TGACA

62.
Mm.170657
Chromosome 19
CCTGTCTCAGA

ACTCAAAGAAT

AAATCCAGTGT

ATCTTCAGAGT

CACTTTGTAAC

CCTAC

63.
Mm.152120
Chromosome 6
TACTCCCTGGA

GACTAGAACC

GTGGCTATAGC

GGAGCATGCTC

CAGAGCACAG

GACTGAT

64.
Hs.5831
No Chromosome location
GGGACACCAG

info available
AAGTCAACCA

GACCACCTTAT

ACCAGCGTTAT

GAGATCAAGA

TGACCAAG

65.
Mm.389
Chromosome 15
GAAAACCAAA

ACTCTTGGTCA

GAGACAATAT

GCAAAACAGA

GATGTCAAGTA

CTATGTCC

66.
Mm.86910
Chromosome 1
TCAAGGAGACT

GTAGACTTAAA

GGCAGAACCC

CGTAACAAAG

GGCTCACAGGT

CATCCTC

67.
Mm.9537
Chromosome 2
CACCACGGACT

ACAACCAGTTC

GCCATGGTATT

TTTCCGAAAGA

CTTCTGAAAAC

AAGCA

68.
Mm.22650
Chromosome 12
GTACCCTCTGA

CTGTATATTTC

AATCGGCCTTT

CCTGATAATGA

TCTTTGACACA

GAAAC

69.
Mm.221600
Chromosome 5
AAGAACTACTG

ATACAGAACC

ACTTCAGTTGT

TCAGTTAGAAT

CTTTTTAAGAC

TCTCTC

70.
Mm.173358
Chromosome 2
CTTGACCTTTA

GATGGAAATTG

TACCTAGAGAC

GAGAAGGAGC

CAAACTAAGGT

CTGTCA

71.
Mm.2534
Chromosome 9
GGAACGGACA

ACGTGGCTTTG

TCCCTGGGTCG

TACTTGGAGAA

GCTCTGAGGAA

AGGCTA

72.
Mm.28280
Chromosome X
TTCGAATGCAC

ATCATTGACAA

GTTTCTCTTAT

TGCCTTTCCAC

TCTGGATGGGA

CCCTG

73.
Mm.23172
No Chromosome location
GCCTGGAGACT

info available
GAAGGCAGTTT

TACAAAGGAA

AACTTAGATTT

CTATTCATTTG

CTTTTG

74.
Mm.10809
Chromosome 1
CTGGATGAAG

AAACAGAGCA

TGATTACCAGA

ACCACATTTAG

TCTCCCTTGGC

ATTGGGA

75.
Mm.23955
Chromosome 5
TTAATATTGTC

AATGTCAGGG

GGTTCCCTGTC

TCAGAGCATTA

TGTGTACTAAC

TGTAGC

76.
Mm.268680
No Chromosome location
CCAGAGTTTTT

info available
TCCATCATGTT

TTGCCCCAAAG

ACCTCGGTTTG

TAGAAGCCCA

AGGAAA

77.
Mm.90241
Chromosome 6
GACAGGGTCA

ATGTTTATTAT

ACATACTGCAC

TGATGAGAAC

AATATCATATG

TGAAGAG

78.
Mm.230635
Chromosome 8
ACTCTCAGCTT

CCTGTTGGCAA

CAGTGGCAGTG

GGAATTTATGC

CATGTAAATGC

AATAC

79.
Mm.270136
Chromosome 7
GACAGGGACT

CCATATGGAAG

TAAGGACGTTT

ACCTCATTACT

AAGTCTCGTCA

AAAGAA

80.
Mm.266485
Chromosome 15
CTCGGATCTTC

ATGTTCTTCAG

TAAGAATCTCT

CTGTGGATTTG

GAACAATCGTA

AATAA

81.
Mm.32929
Chromosome 7
CTAAGACACCT

GTGATTTGGCA

ACTGGTCAATT

CATGCTTGTTA

CATTCAGAACT

CAGGA

82.
Mm.145
Chromosome 11
TCCCTCTCTGT

GAATCCAGATT

CAACACTTTCA

ATGTATGAGAG

ATGAATTTTGT

AAAGA

83.
Mm.288474
Chromosome 5
TTCTCAGTTCA

GTGGATATATG

TATGTAGAGAA

AGAGAGGTAA

TATTTTGGGCT

CTTAGC

84.
Mm.18626
Chromosome 6
CTGACCAAGGT

GGCTGACTCCA

GCCCTTTTGCC

TCTGAACTGCT

AATTCCAGATG

ACTGC

85.
Mm.173282
Chromosome 4
GATACCTGGCT

TATCTTTTATC

AACAGCAAATT

ATGCAGTGGTG

GAAATGTCATC

ACAGA

86.
Mm.76649
Chromosome 3
GTTTGAGAAGA

GACATTATTTA

TAAAACCCAG

ATCCTTAATAC

TGTTTATTACA

GCCCCG

87.

Chromosome 13
CTCTGATACTG

AATAAACCTGA

TGTGATGTACT

TATAGTCCTTA

AGTCTTGAGAG

TTAGA

88.
Data not found
Chromosome 3
GGCAACTACG

ACTTTGTAGAG

GCCATGATTGT

GAACAATCAC

ACTTCACTTGA

TGTAGAA

89.
Mm.1643
Chromosome 19
ACTTCATAGGA

TTCACAATGGA

GAGGGCTAGG

AAGATACTGG

ACAATTTTCAG

CAGTGTG

90.
Mm.247493
Chromosome 4
CACCTCTTGTC

TCCAGCCATGC

CCAGGATCAAT

TCTAGAATCAG

AGGCTACCCCT

GCCTG

91.
Mm.182599
Chromosome 16
CGTCAGTGACC

CACTCAATACT

GTGGTGGGAA

GTAAGATGATG

CCAAATCTATA

ACCTGT

92.
Mm.4159
Chromosome 2
CGAATGAGAA

TGCATCTTCCA

AGACCATGAA

GAGTTCCTTGG

GTTTGCTTTTG

GGAAAGC

93.
Mm.259061
Chromosome 10
CCGGCGGGCCC

TAGTTTCTATG

TATTTAGAATG

AACTCGTGTAC

ATATGTAAAGA

TCTTT

94.
Mm.27498
Chromosome 6
CAAGCTGGTTG

GAGCCTCCAGC

CTTCAAAATTC

TGAATCTAATA

AACATTAATGC

ACACT

95.
Mm.267078
Chromosome 5
CAATCCTAGAA

CAACTACTTGA

GTGTTGTGAGT

GTTCAGATACT

CATTAATATAT

ATGGG

96.
Mm.24457
Chromosome 4
TCCCACCTCTC

TGATGAGTTAT

AGCCAAGAAG

CCTTAGGAGTC

TCCATAAGGCA

TATTCA

97.
Mm.116862
Chromosome 3
AAGAAATATTC

CCACTTCAGAG

TGTGTAAGCAA

TATTTAAACCC

AGATAAAGAT

GCATGC

98.
Mm.196869
Chromosome 5
TTTGGGAGTGG

GCTTCATGAAT

GCGCTCTTACC

AAAGGAGCCA

TGTTTCCATTG

TATCAA

99.
Mm.21013
No Chromosome location
TTTCATTAAAC

info available
TAATATTTATT

GGGAGACCAC

TAAGTGTCAAC

CACTGTGCTAG

TAGAAG

100.
Mm.153315
Chromosome 1
AAGTGACTCCA

TTTTCATATGT

ACTTAAACACA

GAGTTCCTGTG

GCCTCTGTAAG

CTCAG

101.
Mm.22479
Chromosome 15
CAAGGTGAAG

AGCCTGGAAA

CTGAGAACAG

GAGACTGGAG

AGCAAAATCC

GGGAACATCT

102.
Mm.44876
Chromosome 3
GCATGTGATTG

ATTCATGATTT

CCCCTTAGAGA

GCAAGTGTTAC

CAAAGTTCTGT

TGAGC

103.
Mm.290934
Chromosome 12
TGCTCCAGATG

TGAAACTTATA

GACGTAGACTA

CCCTGAAGTGA

ATTTCTATACA

GGAAG

104.
Mm.221788
Chromosome 2
TGTACAACTGA

ACTCACCTCTT

GTGAAGAATTA

TGATTGTCTTA

CTTGTAAAGAA

AGCAC

105.
Mm.33498
Chromosome 16
TTTTGCAGGGG

TCGAGTGTGAT

GCATTGAAGGT

TAAAACTGAA

ATTTGAAAGAG

TTCCAT

106.
Mm.87180
Chromosome 7
CAAACAGAAA

ACAGGGAGAT

GTAAAACAGTT

TCAACTCCATC

AGTTATGAAAC

CATAGCT

107.
Mm.133615
Chromosome 9
TCAGCAAATTG

GCGATTTCGGA

ATCCTATGACA

CCTACATCAAT

AGGAGTTTCCA

GGTGA

108.
Mm.1956
Chromosome 14
CATGTGCAACC

TCATGGGAAA

AATAGTAACTT

GAATCTTCAGT

GGTTAGAAATT

AAAGAC

109.
Mm.60230
Chromosome 17
GTCTCAAGGAT

CTGGGACCAG

AACTGGGAAA

GAAAAGGAAT

GACCAAGACA

AGATCATAC

110.
Mm.143141
Chromosome Un
TGAATCAGAG

AAAAGAGAGT

TGGTGTTTAAA

GAATATGGGC

AAGAGTATGCT

CAGGTGAC

111.
Mm.40268
Chromosome 3
AAAGGAAATC

ATATCAGGATA

AGATTTGTATC

TGATGAGTATT

TTCCATCTGAA

CCCGGA

112.
18413
Chromosome 11
CAGTCCTCTTG

AAAGGTCTCAG

AAGCTGGTGA

GCAATTACTTG

GAGGGACATG

ACTAATT

113.
Mm.2877
Chromosome 16
AGAGGAGTCTC

CTTATATTAAT

GGCAGGCATTA

TAGTAAAATTA

TCATTTCCCCT

GAGGA

114.
Mm.297591
Chromosome 11
GCATGAGTGTA

TAGGTGAAGGT

TTCACTTTAAG

ATGCTGTCTTC

AGTTCTCTTGC

CTATG

115.
Mm.2284
Chromosome 9
ATCGTCTCTGA

TTATGACAAGG

GCTATGTGGTG

TGGCAGGAGG

TATTTGATAAT

AAAGTG

116.
Mm.15622
Chromosome 4
CTGTTCGTGTT

GGGTTTTGTTC

ATGTCAGATAC

GTGGTTCATTC

TCAGGACCAA

GGGAAA

117.
Mm.196692
Chromosome 10
GTGCAATAGA

AATATATGATT

TCAAACACATT

TCTGAACTGCC

AGGGCAAGAA

AGTATAG

118.

No Chromosome location
CTTGTCGTTTT

info available
TGGGGGTTGTA

ATATCTAAGGG

TGAAAAAATTA

ATTTCCAAAGC

CAAGA

119.
Mm.29268
Chromosome 4
CAACTGTTTAC

CTGGAAATGTA

GTCCAGACCAT

ATTTATATAAG

GTATTTATGGG

CATCT

120.
Mm.220988
Chromosome 8
CCTTCCAGAGC

TTTGCCAAATT

TGGAAAATTTG

GAGATGACCTG

TACTCCGGATG

GTTGG

121.
Mm.173383
Chromosome 2
TAGGTGAGTTA

GGAATCTGCCA

TAAGGTCGTTT

ATAGGATCTGT

TTATATGAAGT

AATGG

122.
Mm.249937
Chromosome 8
ATGACTTTCTC

TGCTTGGTTGG

AGAAGAAGAA

TCTTTACTATT

CAGCTTCTTTT

CTTTTT

123.
Mm.28559
Chromosome X
CCGGGGTGGG

AAGTTGTTTTT

TCCTGGGGGTT

TTTTCCCCTTA

TTTGTTTTGGG

GCCCCT

124.
Mm.38094
Chromosome X
GGAAGATGGG

TAAATAGTAGA

CTGTGGTGTAT

TTGGAACAAG

GTAGCTTTAAA

GACACAA

125.
Mm.41694
Chromosome 5
CCAGGTTCAGA

GCGGACTGCTA

ATAATAATGTG

TGTATTGATCG

AGGAAAAAGT

GCGGAG

126.
Mm.32947
Chromosome 14
TGCATGGGAA

ATTTCTACGTG

GCTCACTTCAC

CAAGGCTTATT

GCACTGGGAA

AAGAAGA

127.
Mm.486
Chromosome X
TTAACCTAAAG

GTGCAACCTTT

TAATGTGACAA

AAGGACAGTA

TTCTACAGCTC

AAGACT

128.
Mm.5624
Chromosome 17
TCCCCACTACT

ATAAGGCCAA

GGAGCTAGAA

GATCCCCATGC

TAAGAAAATG

CCCAAAAA

129.
Mm.6888
Chromosome 19
ATAGGTACTCC

CCGATTCCCAA

GGAGCAGCTA

GTGGAACCCTG

GAGTTTTGGGT

AGTAGA

130.
Mm.2271
No Chromosome location
AGTAGTATTTC

info available
CAGTATTCTTT

ATAAATTCCCC

TTGACATGACC

ATCTTGAGCTA

CAGCC

131.
Mm.1155
Chromosome 1
ACCGCTACTTG

GAGCCTGTTCA

CTGTGTTTATT

GCAAAATCCTT

TCGAAATAAAC

AGTCT

132.
Mm.8856
Chromosome 17
TGAACTCTGAC

CTTTTGCAACT

TCTCATCAACA

GGGAAGTCTCT

TCGTTATGACT

TAACA

133.
Mm.2580
No Chromosome location
GTCTGTTCTTG

info available
GGAATGGTTTA

AGTAATTGGGA

CTCTAGCTCAT

CTTGACCTAGG

GTCAC

134.
Mm.35104
No Chromosome location
CCAGCCTGACC

info available
AGATTTTAGTT

ACCTTTTAAGG

AAGAGAGATTT

ATTCTAATGCC

ATAAA

135.
Mm.22673
Chromosome 1
CACCTCTGTGC

TTTGAAGGTTG

GCTGACCTTAT

TCCCATAATGA

TGCTAGGTAGG

CTTTA

136.
Mm.2720
Chromosome 2
CTGAGCTCAGG

CTGAGCCCACG

CACCTCCAAAG

GACTTTCCAGT

AAGGAAATGG

CAACGT

137.
Mm.4487
Chromosome 7
AGAACAGCAG

TTAGTTCCTGG

TTCTGAGAACC

ACTTGTCCCAG

TATGACACCTC

TTACTA

138.
Mm.4348
Chromosome 12
ATGTGTGTACT

CAGGACAGAA

TCCAGAGATTT

CTTTTTTATAT

AGCTTGATATA

AAACAG

139.
Mm.448
Chromosome 8
ACGTTTCACAC

AGTGGTATTTC

GGCGCCTACTC

TATCGCTGCAG

GTGTGCTCATC

TGTCT

140.
Mm.23942
Chromosome 11
TTTTTTAATTCT

GCAAATTGTCT

CACAGTGGAAT

GAGGAAATGA

GTTAGAGATCA

CAGCC

141.
Mm.1109
Chromosome 6
GTGCTATCTTT

ACTCACTCCCA

AGACATACAC

AGGAGCCTTTA

ATCTCATTAAA

GAGACA

142.
Mm.2692
Chromosome 3
GAGGTCCAAGT

TTAAATGTTAG

TCTCCTAACAA

CTGTCAAATCA

ATTTCTAGCCT

CTAAA

143.
Mm.21630
Chromosome 9
CTTCTAGATCC

TTCTGCAGAAA

TCATCGTCCTA

AAGGAGCCTCC

AACTATTCGAC

CGAAT

144.
Mm.17537
Chromosome 18
ACTTATTCATC

CTTGCCTATAC

CCACCCCCCAA

AAACAGGTTTT

ATTAATAAAAA

ATGTG

145.
Mm.1585
Chromosome 13
TACAGTAACAA

GCAAGCTATCA

TCCATTTTTAC

AATAAAGTTGT

CAGCATTCATG

TCAGC

146.
Mm.103104
Chromosome 15
TTATTTACTTT

ATCTTAGTATG

TAACCTTAGCT

GACCTGAAACC

CACTGGTAGAC

TAGAC

147.
Mm.206536
Chromosome 4
CCTGTCCTGAG

TTCATGGCCAA

AACTTAAATAA

GAGAAGGAGG

AGAGGGTCAG

ATGGATA

148.
Mm.156600
Chromosome 6
AAAGGGGCCT

GAGTATACGCT

GTTGCAAGCTG

TATACTTCATT

TCCTTCGGCTG

GTTTAT

149.
Mm.254385
Chromosome 3
TATCCGGACAG

TCTATGTGAAA

TAGGACCAAG

GTCGAAAGCC

GGAAAGACAT

CAACAGAA

150.
Mm.2570
Chromosome 4
CTGCTTTTCCC

TGACATGGATG

CGTAATCACGG

GGTCAAATTAC

ACCTATCCAAC

ACCAT

151.
Mm.153911
Chromosome 14
AACAAAGAGG

ACAGTATGAAT

TTGAATAGCTC

CCACTAGATAA

GCAATTTCCAC

GAGAAC

152.
Mm.28130
Chromosome 1
CTGACTGTGAA

TGTCGTGACTC

AGAGCAAAGA

CAGAGAATAT

ATTTAATTCAT

GTTGTAC

153.
Mm.3267
Chromosome 14
GCCTGAAGAA

CATGACAGAA

CTCTTCTCAAT

ATTCGTTGGGC

TTTCAGAATCA

TAAACAT

154.
Mm.45436
Chromosome 10
CCTGTGTGAAT

AAAAATACAA

GAACTGCTTAT

AGGAGACCAG

TTGATCTTGGG

AAACAGC

155.
Mm.200362
Chromosome X
GTAAGAAATAT

TAGACTGATTG

GAGTTAAAGTA

GCACTCTACAT

TTACCATGGTG

TTTGG

156.
Mm.143819
Chromosome 1
TGTGAAAGATT

GTGCATCTGCA

TTCAACTACCC

TGAACCCTTAG

GGAAGAAATG

GATTCC

157.
Mm.27923
Chromosome 11
AGCTGCCTACT

AGCAGTTTAAC

AAGGAGCCTTG

CTGTCTCAGAC

AGGTGAAAGA

AAATGT

158.
Mm.40894
Chromosome 3
CCATGTTTGAA

AGTATGTAATG

AAGAGGAGCC

TATTAACCATA

TGAAAGACAG

GAATACT

159.
Mm.160389
Chromosome 7
GTGAATTGGAT

GCATAGCATGT

TTTGTATGTAA

ATGTTCCTTAA

AAGTGTCACCA

TGAAC

160.
Mm.142524
Chromosome 8
ACCCACTGACT

AGGATAACTG

GAAAGGAGTC

TGACCTGAATG

ACGCATTAAAC

TCCTGCA

161.
Mm.2970
Chromosome 14
CCCGCTTCAAT

GAGAACAACA

GGAGAGTCATT

GTGTGTAACAC

GAAGCAGGAC

AATAACT

162.
Mm.24138
Chromosome 2
ATATTAACTCT

ATAAAATAAG

GCTGTCTCTAA

AATGGAACTTC

CTTTCTAAGGG

TCCCAC

163.
Mm.275894
Chromosome 14
TGTGGGTTTTT

TGAAGAATTAA

TGAGCATGTAC

ATAGAAATAGT

GACTGCTTGAA

TCCTG

164.
Mm.566
Chromosome 5
CTACTCTTAAT

GATGTTATCTT

AACACTGAAAT

TGCCTGAAACC

CATTTACTTAG

GACTG

165.
Mm.40268
Chromosome 3
TCGACCATTTC

TAGGCACAGTG

TTCTGGGCTAT

GGCGCTGTATG

GACATATCCTA

TTTAT

166.
Mm.24208
Chromosome X
TCTGAATCTGG

GCACTGAAGG

GATGCATAAA

ATAATGTTAAT

GTTTTCAGTAA

TGTCTTC

167.
Mm.34490
Chromosome 11
GATCCTTAGGT

CTCCATAGGAT

GATTTTTGAGG

TAGTTAATCAG

TGTAAACTCTT

ACACA

168.
Mm.9749
Chromosome 19
CTCAGCAGTAA

CAGAGAAAAG

ATGAATGAAG

CCACTGAGGCT

TCGTGAATGAA

TGAATCT

169.
Mm.154804
Chromosome 8
CTTTGTTCCTA

CCCAGCCACCA

AAGCCACCTAC

ATAACAATCCA

CTCATGTACTA

GCAAA

170.
Mm.90787
Chromosome X
AAATTGTCTAC

GCATCCTTATG

GGGGAGCTGTC

TAACCACCACG

ATCACCATGAT

GAATT

171.
Mm.36217
Chromosome 6
ACATGATGTGA

AAGAATCATTG

AAGATCACAGT

TGTCTACCGAG

TTCAGATTTCC

TTACA

172.
Mm.1834
Chromosome 4
CACCCCCCAGA

AAATGAGACT

ATTGAACATTT

TCCTTTGTGGT

AAGATCACTGG

ACAGGA

173.
Mm.214593
Chromosome 9
AGTGATGGGG

ACCATGACGA

GCTGTAGCCTG

AACCTCAAGGC

CTGCAACCAGT

CTACTGA

174.
Mm.24045
Chromosome 12
AAAGGTCCCA

GGTTTCGATCT

GTTTGGAGTTT

GGAGTCTAATG

GTTGCATAGAT

AAACAG

175.
Mm.18517
Chromosome 8
TCTATGTGCAT

TAGGGGGTGA

CCCAGGGAAA

TCCAAAGGGA

ACAGTATTTGA

TTTCTCAC

176.
Mm.249873
Chromosome 5
CTACACATGTA

CTTTAGGATTC

TAGGTTTCTCC

CTGAGCCCTGC

TTTCGATGTAA

CACTG

177.
Mm.2128
Chromosome 3
AAGTCTAAAG

GGAATGGCTTA

CTCAATGGCCT

TTGTTCTGGGA

AATGATAAGAT

AAATAA

178.
Mm.254240
Chromosome 15
GGAAGAAAAA

GACCTCAGGA

AAAAATTTAAG

TACGACGGTGA

AATTCGAGTTC

TATATTC

179.
Mm.19185
Chromosome 19
GGATGAAGAA

ACTGAGTTTGT

CCCTTCTGAGA

TCTTCATGCAC

CAAGCAATCCA

CACCAT

180.
Mm.10222
Chromosome 15
CTGTTCAGGCT

CAAACAATGG

GTTCCTCCTTG

GGGACATTCTA

CATCATTCCAA

GGAAAA

181.
Mm.141936
Chromosome 1
AGGAGTTCCCA

GTTTTGACACA

TGTATTTATAT

TTGGAAAGAG

ACCAACACTGA

GCTCAG

182.
Mm.18821
Chromosome 17
CTCAATAAAAG

CTCTAAGGAGA

CATCACAACCC

AGTCTTAAGGG

TTCATGAGGTT

TTAAT

183.
Mm.29487
Chromosome 19
ACTTAAAATGT

AGACTGTTCAT

ACAGTGGGTAC

CAGTATGAGTT

GAATGTGTGTA

TTACT

184.
Mm.117294
Chromosome 10
TTTCATAATAG

AACCGTCTACC

AGTGACCTCTT

GATTATGATTT

GATTTGACTGC

AAAAC

185.
Mm.114683
Chromosome 3
ATCCATGTGGC

ATCAATTCAAT

TATGTATAATA

ATGACTTTACA

AGGGCCCCTTA

AAACC

186.
Mm.21596
Chromosome 6
CACAAAAGTC

AAATGTGGATA

TCGTACGCTGC

ATCACGTCATA

GACAAGTCTAA

AGAAGA

187.
Mm.4213
Chromosome 6
CTATCAGGATA

GTGATAAGAA

CGTCATTCTCC

GACATTATGAA

GACATGGTAGT

CGATGA

188.
Mm.212279
Chromosome 6
GGAGATCATCA

CTCTTGTATGA

AATATACTAAC

TCCAAACCTTT

TTAGAGCAGAT

TAGGC

189.
Mm.89568
Chromosome 12
ACTATTAAGCA

CTCAGGAGAAT

GTAGGAAAGA

TTTCCTTTGCT

ACAGTTTTTGT

TCAGTA

190.
Mm.10878
Chromosome 5
AAAGAGAAAA

TATGTCAGATG

GTGATACCAGT

GCAACTGAAA

GTGGTGATGAA

GTTCCTG

191.
Mm.980
Chromosome 4
GAGAGAGGAA

TGGGGCCCAG

AGAAAAGAAA

GGATTTTTACC

AAAGCATCAA

CACAACCAG

192.
Mm.37773
No Chromosome location
GTTGTACTACT

info available
GGAAAGATTTT

GCTGGGACATA

CAATATGTGTG

AGAAAAATAG

AGTTGT

193.
Mm.24498
Chromosome 5
AGACCAAAGA

CACGGACATTG

TGGATGAAGCC

ATCTACTACTT

CAAGGCCAAT

GTCTTCT

194.
Mm.28406
Chromosome 19
CAGAGCAGGG

GGCTTTTATTT

TTATTTTTTAA

TGGAAAATAAT

CAATAAAGACT

TTTGTA

195.
Mm.39856
Chromosome 7
CTTGGCAGCTC

TCCTTACTTCT

GGGACATTTGC

CACTGTGGTAC

TGCCAGGAAG

GAATCT

196.
Mm.275813
Chromosome 12
ACTTATAGAAA

AGGACAGGTT

GAAGCCTAAG

AAGAAAGAGA

AGAAAGATCC

GAGCGCGCT

197.
Mm.684
Chromosome 7
TAGTTCAGTGA

ACAAGTATCTG

TCAATGAGTGA

GCTGTGTCAAA

ATCAAGTTATA

TGTTC

198.
Mm.217227
Chromosome 2
CATGAATGTCA

AAACCTAATTA

CAAAGCATCG

GTCTCTTTGTT

GTGAGGTATCA

GAACCC

199.
Mm.202348
Chromosome 15
CCTGTCTCATG

GGAGATTTGAA

TCATAAGGAG

AATCACTTTTT

GTAACTTTATT

GAGGAA

200.
Mm.6272
Chromosome 9
AAGTAAATATG

CAAAGGAGAG

AAGTTAGAGA

AACTCCTCTCA

TAAGAAAAAT

GTCTTCCC

201.
Mm.254859
Chromosome 17
TCGGAACTGTC

CCTTAAGGAGG

GTGATATCATC

AAGATCCTCAA

TAAGAAGGGA

CAGCAA

202.
Mm.8249
Chromosome 1
TTAGTGGGCTG

AACCTATCGGT

TTTAACTGGTT

GTCTTAATTAA

CCATAAACTTG

GAGAA

203.
Mm.147226
Chromosome 8
TTTTGTACAAC

CCTGACTCGTT

CTCCACAACTT

TTTCTATAAAG

CATGTAACTGA

CAATA

204.
Mm.10727
Chromosome 8
AGACTTGGAA

AAGGCTTGGGT

ACAATTAAGA

AAAACCCTACA

TCCCACCCTCC

TCTTGAC

205.
Mm.221768
Chromosome 6
TAATAAAGAA

ACTGTGGAAAT

ACTTGGATTTC

TACTGAAGACA

AAAGACTTCTA

GGCTGG

206.
Mm.214742
Chromosome 10
AGGTTAAACAT

ATATTCTTGGA

AACATGAAATC

ACAACTCTCAA

AAACCGTGAA

CCACCA

207.
Mm.1359
Chromosome 7
CCTCGTGTTGT

CTTCTTTGGAC

CTCAGTTTTTC

CATGAACCAG

AAGAGAATTG

GAACAAG

208.
Mm.217839
Chromosome 10
AATAGCAATGT

ATCAAACAATG

GATGTGAAAA

AGATGCGCTCT

ATCATCATGAA

AATGCC

209.
Mm.4619
Chromosome 17
TCTCTGGAGAA

ATCAGTAACTG

CAAAAGGAAG

AGAGGGTCTTT

AAAGCACATGT

AGTAAT

210.
Mm.173427
Chromosome 2
TGGAATGTTGA

AGAATGAAAT

CTCGAGGGAAT

TAGAGGTTGAG

GTCATCTGGAT

ATTCAG

211.
Mm.27789
Chromosome 6
ATAGAACCAAT

GTAGGAAAAT

CAGGCAAAAT

AAAATGATGAT

CAGTCCATGTC

ATCATGG

212.

No Chromosome location
AGATGGGAAA

info available
AAGTACTGTAG

GTTCCTGAACT

CTGGATCTCAA

GCAGAAATGT

ACTGTCT

213.
Mm.221816
Chromosome 18: not
AGGAAAACCC

placed
CGGTAGTTAGG

ACATCTGAATT

CTCAATTATTG

GATTGCCAAAA

GTGAAA

214.
Mm.273506
Chromosome 2
GTTTTTGGAAT

TTGGACCTGAA

AATTGTACCTC

ATGGATTAAGT

TTGCAGAATTA

GAGAC

215.
Mm.21104
Chromosome 17
TGGGACCTGTG

AAGCGACTGA

AGAAAATGTTT

GAAACAACAA

GATTGCTTGCA

ACAATTA

216.
Mm.182542
No Chromosome location
TCCATTATTAC

info available
ATACAACAATC

AAGAAAAAGA

CAGAAAACTA

CCCTTAGAGAG

ATCAGGG

217.
Mm.260378
Chromosome 4
ATTCAACAGCA

TTCTAGGAAAA

TGGCAAGAAA

GTAAATTATCA

TCCATTTCAGG

TCTGTG

218.
Mm.260433
Chromosome 18
CCATATGATCA

CAGTCGTGTTA

AACTGCAAAGT

ACTGAAAATG

ATTATATTAAT

GCCAGC

219.
Mm.29216
Chromosome 18
GGGCCATATTT

TAAAGATAAG

GAGAGAGAAA

CTAGCATACAG

AATTTTCCTCA

TATTGAG

220.
Mm.248291
Chromosome 1
GAAAGGCGTTT

ATTCAGAAAAT

GATGGTAAGAT

TCAGACTTTAA

AGCACAGTTAG

ACCCA

221.
Mm.2681
Chromosome 13
TAAGGTGTTTT

CTCCAGTTAAG

TTCAGTTCCTG

AATAGTAGTGA

TTGCCCCAGTT

GCAAC

222.
Mm.119383
Chromosome 2
CCACCATAAAG

GAAAAAGGAC

ATGTGTATGAG

TAGGTGTTCAT

CTATGTGCATA

ATTGGC

223.
Mm.263733
Chromosome 12
GCACAAGATG

GAGTCATTAAA

ATTAAGGCATC

ATCATTTTCAG

CATATAACATA

GCAGAG

224.
Mm.221860
Chromosome 1
GATTAAAAAC

ATTAGGGATGA

GAAATAATAA

GGGCTTGCAAC

TGTGTAGAAGC

TAGAGCC

225.
Mm.46455
Chromosome 4
TGAAGTACACT

CTCTAAATGAA

AATGGGCTATA

AATATGTTTGA

GTAGGATAGG

AGGAAG

226.
Mm.5522
Chromosome 9
GTGTAAGAAA

AGATGGGACT

GACAATAAAA

ATGAAGGTCA

GGTAAGAAGT

ACCAGACTCC

227.
Mm.25836
Chromosome 16
GGGAAATATG

CAGCGTTCTAT

GTTTCCATAAG

TGATTTTAGCA

GAATGAGGTAT

TATGTG

228.
Mm.1401
Chromosome 1
GTAGGACTGTA

GAACTGTAGA

GGAAGAAACT

GAACATTCCAG

AATGTGTGGTA

AATTGAA

229.
Mm.222325
Chromosome 16
TCATAGGTCTC

CATTTAGTTCA

AGTGTTTTATG

GACAATCAGC

AAGTTTAGGCT

CATAGG

230.

No Chromosome location
TTGGAATATAT

info available
GAATGACAAA

GAAATGGGAA

AAACTGCTGAA

CCCGAGTCTCT

GAATGTC

231.
Mm.174026
Chromosome 10
CTATCTTGAAT

TGCTAGATTAA

AGAGAAAGAA

AATGTTAGAGC

AAAATAGGAA

CCTGGCC

232.
Mm.173446
Chromosome 9
AATCCCTAGAG

AAAATGGGAA

TAGAAATAAG

CTGCATACAAA

CTCAAAGACAC

AGATACT

233.
Mm.182873
Chromosome 1
AGACTGAAGA

AAACCTTAAAA

TACCCAAAATT

CAGGGGAGAC

ATAGCAACTGA

GTCTCAT

234.
Mm.1781
Chromosome 11
AGAGGACTTCC

TGTCTGTATCA

GATATTATTGA

CTACTTCAGGA

AAATGACGCTG

TTGCT

235.
Mm.216167
Chromosome 10
ATGGAGATGTG

TAAACAGTAG

GACATTTCGAT

AACTATGTCAG

GTCAGTTCTTA

GTTCAG

236.
Mm.221604
Chromosome 12
GAGGCTATTAT

AAATAACCTGA

AATGCATATGA

GAACTGAACGT

GTAATAATTCA

GCTCC

237.
Mm.222320
Chromosome X
AAGTCGGAAT

ATGTCTTAGTG

TTCTTCTCACT

TAGCTCAGTGT

AAGATGGTAG

CTCAAGT

238.
Mm.1430
Chromosome 4
CACTTTTCTAT

GAAGAAAGCC

GTGTGTAAAGT

TTCCGTGACAG

TAGTAATGGAA

ATATCT

239.
Mm.24905
Chromosome 15
TGTAAGAATAC

AAGGTAAAAC

AAAATAGAGA

AATACAGGCAT

CATATCTGCAA

ATCGCCG

240.
Mm.221718
Chromosome 3
CAGAAACAGT

AGTATGGGGTT

AAATCACAATG

AGGGAAATTAT

AGGGATATGC

AGCCAAG

241.
Mm.217090
Chromosome 9
ACTGAAAGTTG

GGGAGATACA

TGTAATTTAAT

AGGATAGGGT

ACTTAGGTCCA

GACAACC

242.
Mm.102470
Chromosome 15
AAGCTGTTGAA

TATGGACGTAA

CTGTAAATCCC

AGAGTGTTTTA

TTTTGAGATGA

GAGTT

243.
Mm.217865
Chromosome 6
TTTATCAAACA

TGGAAACATCT

AGAGACTATG

GGAGAGAAAA

TGGGTTTTTAG

ATATGGG

244.
Mm.203206
No Chromosome location
GGAAGTTAATA

info available
GAACTGTTCAA

AATGTGAAAGT

GGAAATAGCG

TCAATAAGGA

AAGCCCC

245.
Mm.9714
Chromosome 11
AGTGTAGTTTT

CAGTGGACAG

ATTTGTTAGCA

TAAGTCTCGAG

TAGAATGTAGC

TGTGAA

246.
Mm.249965
No Chromosome location
GAAAGTGGGG

info available
AATGAAAAGT

ATAACAAAGT

AAAAAGAGAA

TTTCTAGGCCC

TTTAGGCCC

247.
Mm.11186
Chromosome 11
GGTTTTCTCTT

GTTTTATCATG

ATTCTTTTTAT

GAAGCAATAA

ATCCATTTCCC

TGTTGG

248.

No Chromosome location
CTTTTTGAGGT

info available
TTATTTTTCCA

CAGTTTTCATT

TGTTCATTAGG

CATTTTCCCTT

TTACT

249.
Mm.250102
Chromosome 9
AGTGTTTTTCT

TTAATTCTTGA

GGTTGTTATTG

TAATATTTACA

TATAGTGCAAG

AATGT

250.
Mm.138048
Chromosome 10
TAAAGTATCCA

CTGAAGTCACT

ATGGAAAACA

GCCTTTTGATT

TATGGACTATT

TAGCTC

251.
Mm.212863
Chromosome 19
GCCTAGTTTTT

TCAGCATCAAT

TTTGGAAAACC

TTAGACCACAG

GCATATTTCGT

CAAGT

252.

No Chromosome location
TCATTTTTCAA

info available
GTCGTCAAGGG

GATGTTTCTCA

TTTTCCGTGAC

GACTTGAAAA

ATGACG

253.
Mm.78729
No Chromosome location
CTGAAAATCAC

info available
GGAAAATGAG

AAATACACACT

TTAGGACGTGA

AATATGTCGAG

GAAAAC

254.
Mm.107869
No Chromosome location
GCGAGAAAAC

info available
TGAAAATCACG

GAAAATGAGA

AATACACACTT

TAGGACGTGA

AATATGGC

255.
Mm.36410
Chromosome 2
AGAAAGCTAT

GGACTGGATA

GGAGGAGAAT

GTAAATATTTC

AGCTCCACATT

ATTTATAG

256.
Mm.68486
Chromosome 12
ACAAAAAGGT

TACCTATGAAG

ACAGTGAAAT

AAGAGAGAAA

TGTTTAGTACC

TCAGGTTG

257.
Mm.249862
Chromosome 7
CTAAGGGAGG

AAATGTTGGTA

TAAAATGTTTA

AAAGAACTTG

GAGGCAAACTT

GGAGTGG

258.
Mm.182670
Chromosome 6
CCACATCATTG

GAAAGAAATA

CACTTATCTTA

ATTGCCATGGA

ATAGGAGCAT

GAAAGTC

259.
Mm.221086
Chromosome 4
ATGAGAAATA

CACACTTTAGG

ACGTGAAATAT

GGCGAGGAAA

ACTGAAAAAG

GTCTATTC

260.
Mm.269426
Chromosome 4
CCTGTGAACTG

AAAATGCAGA

TGATCCACAGG

CTAAATGGGA

AACCTGGAGA

GTAGATGA

261.
Mm.107869
No Chromosome location
GCGAGAAAAC

info available
TGAAAATCACG

GAAAATGAGA

AATACACACTT

TAGGACCAGA

AATATGGC

262.
Mm.25571
Chromosome X
TGGAGGAAATT

GATTGAAAAA

CGATTGGTCAA

ATCGAAAATG

GAGAAAACTC

ATGTTCAC

263.
Mm.103648
Chromosome 1
CTTCATCCTGG

TTTTCACGGCA

ATAATAATGAT

GAAAAGACAA

GGTAAATCAA

ATCACTG

264.
Mm.123225
No Chromosome location
ACTGAAAATCA

info available
TGGAAAATGA

GAAACATCCAC

TTGACGACTTG

AAAAATGACG

AAATCAC

265.
Mm.871
Chromosome 11
CAAGCACTGTG

CTGCAAAATGT

CGGTGGAATAT

GATAAGTTCCT

AGAATCTGGAC

GAAAA

266.
Mm.217877
Chromosome 1
TTTGAGAAGAA

AGGCATACACT

TGAAATAAAG

GCAAAAACATT

ATACTGTCTAC

CGAGAC

267.
Mm.38058
Chromosome 13
GAAGAAAACG

AGGTGAAGAG

CACTTTAGAAC

ACTTGGGGATT

ACAGACGAAC

ATATCCGG

268.
Mm.43952
Chromosome 13
ATCATAAAAAC

TGTGGAAATCC

ATATTGCCCTT

TTAAAAGAAA

ACTATGGGGAT

GGAGAG

269.
Mm.8709
Chromosome 5
AAATGGCAGA

AGAAAGGGTT

AATGGCTGGA

AAAATGGATC

AGTAGTCTTGC

AGAGGAACC

270.

Chromosome 10
ATTTTAGGGGG

CTTTATTGTTA

CTTGACGTGGA

ATTTGAAAACT

AAAAAGATGA

GTCTGG

271.
Mm.276728
Chromosome 11
GTGGAAATCA

GAGATCTAAGT

ACGTTTATGCA

TAGGAGTAGG

AATGAGGGGTT

ATTAAAG

272.
Mm.30052
Chromosome 4
AAACCCCCCAA

GTAGCCCAAA

GGCCCGCTTCC

CACCAAAATGT

TTTTTATGTTTT

AAGGA

273.
Mm.105080
Chromosome 16
ATTATGATGCC

TGTAACACACA

GAAGTATCTGA

CTGTGAACGAA

TCAACCTCATG

GATGA

274.
16169
Chromosome 2
AGAAGAGATA

CTGAGCCAATG

AACCCTTTCGT

ATAGGATTCAT

GACAAAACCA

AACTCAG

275.

No Chromosome location
CTGCCTTCCCA

info available
TAAAAATAAA

AGGCATGCAA

AACCAATTTTT

GGCCAGGCCC

AGTTAAGA

276.
Mm.28088
Chromosome 5
ACAAGCCCTGG

GCCTCTGAGAC

CACCCGACACA

CCATCCTACCA

AGAAGCCTCTA

AGTAT

277.
Mm.29981
Chromosome 13
CAAGTCAGCA

AGAAGCCAAC

CTTGGTGAAAT

AATTCTGGTTG

TTTGAAAGCTA

GGTCTTG

278.
Mm.250067
Chromosome 1
GGTCAAGAGA

GTGCCAACTAG

CTTTGTTTAAA

AAATCCTAGTC

CTGAATCCACA

AGCCTG

279.
Mm.222100
Chromosome 9
AGTGGAAGCCT

TATAAGCATTG

AACCCAGGAT

GAGTCGCTCGT

ATTTCCACCTT

ACTCAT

280.
Mm.259829
Chromosome 15
CTTCCCACAAC

CCCACCGTACC

TTGTCTATGTA

TGCATGTTTTT

GTAAAAAAGA

AAAAAG

281.

No Chromosome location
TGCCTGACTCC

info available
AAGAAAAGAA

GCCAGAACTCG

GAACCATAGTC

ATCTTTAAAGA

TCTTCT

282.
Mm.45194
No Chromosome location
GTTAATATTAT

info available
TAACTGAGCCT

GCCCATACCCC

CCGTGGTCATT

GGTGTTGGGTG

CAGTG

283.
Mm.157778
Chromosome 7
GGAGGACGAC

ATCCTCATGGA

CCTCATCTGAA

CCCAACACCCA

ATAAAGTTCCT

TTTAAC

284.
Mm.295706
Chromosome 15: not
TCTGAACCTCA

placed
ACCCATCACCA

ACCCCGTGTCT

TCAACATTACT

TTCCAAAAAAG

TCTGG

285.
Mm.217064
Chromosome 10
AGGAGCCTGTG

TCCTTATAGAG

TTGGAATTAAC

TTCAGCCCTCT

ATCTCACTTCC

TCTGT

286.
Mm.29587
Chromosome 2
GAAAAAAGAT

GAGATCTCCTC

CATGACAAGA

GCCTGCATACA

ACATTTGAGTA

CCCTTCT

287.
Data not found
No Chromosome location
TTTGATTTTAG

info available
CAGAAACCAC

CACCAAAATTG

TGCCTTAGCTG

TATTTCTGTTT

AGGGGA

288.
Mm.103701
Chromosome 1
AGATACTATGG

TACTGTCATGA

AATGCAGTGG

GACTCTATTCA

AACAACCCTCC

AAAATG

289.
Mm.157781
Chromosome 7
AGAGAACCCA

CACTCCTTTCA

TCAAGACTTGC

AGAGCATCCCA

CAACCAAGAT

GCTATTT

290.
Mm.218764
Chromosome 17
TATGAGCCTGA

CCCACACTCTC

TGTAAGGTGTG

ACTTTATAAAT

AGACTTCTCCG

GGTGT

291.

Chromosome 9
ATACCCCACCA

CAACCTCTCAA

AAGAGGGCTCT

TAACTTGGAAG

GATAAAATAA

ATCAGG

292.
Mm.1994
No Chromosome location
TATCCTCCCAC

info available
AAAGATGAGA

GGAGCCCATCC

AGTGTTACTGT

TAGAAGTCACA

GTGAAA

293.
Mm.221745
Chromosome 3
TATTGTCCAAT

GAAACCCACA

AACTACCCTCT

ATCTGGAGTTG

GAACATTTATC

TGCATT

294.
Mm.250157
Chromosome 9
TAAGGAGACT

GCCCTACAAAA

CTACGATACTA

CTATCACTTTA

AAAATTAGTGT

AAAGGG

295.
Mm.48757
Chromosome 7
TCAAGGCCAA

GTTTCTGCAAG

AAGCAAGGAT

CCTGAAACAGT

ACAACCACCCC

AACATTG

296.
97587
Chromosome X
GATTGCCAGAG

ACTTACACTTA

ATAGAGTCATA

AAGCCCATAG

AGCCTGAGTGA

GAGCCA

297.
Mm.103259
Chromosome X
TTATTCCTGAA

GCCCCCGCTAC

AGATGTTTCCA

CAACCGAAGA

AGCGGTCTCCA

AAGAGC

298.
Mm.9911
Chromosome 7
AGCTCCACATG

AACTCACAGA

AGAACCAGGC

TAAGTACCCAA

GGACCGAGCTC

AAGGACA

299.
Mm.276293
Chromosome 15
ACCATTATTCT

TTTAAAAAACC

CAAAAACCAC

CAGCAAGGGG

GCCTTTGGTTG

GCCTCAA

300.
Mm.218714
No Chromosome location
CTTCATCTTAA

info available
AACTCCAGAAC

AACTCCCTTCC

TAACCTGGAAC

CCAGCAGCTTT

CAGTT

301.
Mm.261348
No Chromosome location
CTGCACGCCCC

info available
AGGAGCCTGG

GTGAAGCATCA

CAGCACTAAGT

CATGTTAAAAG

GAGTCT

302.
Mm.200585
Chromosome 2
CACTGGAGCAC

TGAACATGATG

TACAAGTATCA

CACAGAAAAG

CAGCACTGGAC

TGTACT

303.
Mm.202727
Chromosome 12
ATAAGAACTTA

TAGGAACCCCA

ACTCCCCATGA

AAAATATAAG

ACCTCAAGGCC

TGGGGA

304.
Mm.100527
Chromosome 3
GCCCACCAACT

CTAATTTGTGC

TACTTATATAT

ATTCCTGGGAG

TAGGACTGTCC

TCCTG

305.
Mm.2364
Chromosome 10
CAGTCAGGTCT

TCCAGAACAAT

TACAACCCCGA

GGAGAACCTC

AATGACGTGCT

TCTCCT

306.
Mm.169672
Chromosome 11
CGTAGCTCGCT

GGTAGAAAGC

CTGACCACCAT

GCATACGATCC

TGGGTTTCAAC

AAGGAA

307.
Mm.196532
Chromosome 19
GAGCCTGAGAT

CTACGAGCCCA

ATTTCATCTTC

TTCAAGAGGAT

TTTTGAGGCTT

TCAAG

308.
Mm.41803
Chromosome 11
GAGTCTGTGGG

TATTCGCCTGA

ACAAGCATAA

GCCCAACATCT

ATTTCAAGCCC

AAGAAA

309.
Mm.98232
Chromosome 11
AGCATCAAAC

AAAGCACATA

AACTCGTACAT

AAGCAAGGGA

TGTCCTTATTG

GTCAAACA

310.
Mm.197271
Chromosome 2
GGGAAAAAAT

AGCAAAACCC

CAAACTCCACA

ACCACAAAAA

CCTGTTAATTA

TGGTGGCA

311.
Mm.30058
Chromosome 9
ACACAGAGCC

AGAAAACCCA

GGCCTGAAGA

CATCCCCTAGT

CCTGCTGAGAG

ACCACAGT

312.
Mm.259849
Chromosome 11
CGACCAATCTG

CCTGGGAAAC

AACACCCCACA

GAACGGGGCTT

CAGAAACACG

TGAGTGA

313.
Mm.45054
Chromosome 19
GTTTAGGTGAG

TTTCCATTGTA

TCTTATAACAG

AGAAACCCATT

AGGCAGTAGTT

AGTTC

314.
Mm.268521
Chromosome 10
TCGAAACACCT

ACCAAATACCA

ATAATAAGTCC

AATAACATTAC

AAAGATGGGC

ATTTCC

315.
76964
No Chromosome location
TGCTACCCTCC

info available
AGGACCAACG

ATGGATGCACC

ACGGAGTCCCA

AGAGCTGAAA

AGCAGAA

316.
Mm.23149
Chromosome 14
CGGAGCTCTTC

AGAACCCCAA

CTCTCTCTGGC

TGGCTACCCCC

AGAACTCCTAG

GTTTAT

317.
Mm.362
Chromosome 9
ATAAAGAGAA

TTCCCACCACC

CTGGGCGAAG

GAATTACCAGC

AATAAAACCTA

TTCCTTC

318.
Mm.11484
Chromosome 7: not placed
ACTTTCAAGTC

TGAATCCTATG

AGCCTGAAGTG

AGATCTTATTT

AGAAACAGAA

CCCCAA

319.
Mm.40331
Chromosome 5
GACAAGCCCTT

AGGGAGCCAG

AAAAAGAGCA

GGAAGAAGTT

AAAATGTTTAA

TTTTTTAA

320.
Mm.188475
Chromosome 16
GCCCAAGAGCT

AGAAAACCTA

CTCTATGTGTA

GAGATACTTCC

TATTAAAATAA

TAGTAC

321.
Mm.216782
Chromosome 9
CTCCACTTTTA

AAGTCTGTAGG

AATAGGAGCC

GATTAGACAAC

TCTCGGTCTCA

TGCTCA

322.
Mm.2877
Chromosome 16
TTTCTGGGATC

CCACTGCACCG

CCATTTCTTCC

CAGATTTATGT

GTATAACTTAA

ACTGG

323.
Mm.27723
Chromosome 17
ATACAGTAGAT

GCTGAACACAC

TTGAGTCCATC

ATGAGGGGGT

AATAAGTCTCA

CCAGCA

324.
Mm.39040
Chromosome 2
TCTTATACTTT

CAACAAAGCT

GAACCCTAACA

TTACACTAACC

AGCAGCTCAAC

ACGAGT

325.
Mm.26700
Chromosome 7
CTGAATGTATA

CACACCCACAG

GAGACTGTGGC

TGAGCGTTCAT

CCAAATAAATT

TGAAT

326.
Mm.35046
Chromosome 4
GTTCCTGTTCA

GAGTGCCTGAA

AACCCAAAGT

GTCTGAGAGTC

TGAAGGAATTC

AACTGT

327.
Mm.24781
Chromosome 6
AAACACCCAC

ACTTGAAACTT

CCATGAACCCA

CTCAAATTCAT

TTCTATCCCCC

TTTGGA

328.
Mm.945
Chromosome 7
TCATGGAGATA

TAACTATAGAG

ATAAAGAGCG

ACACCCTGTCT

GAAGCAATCA

GCGTCCG

329.
Mm.31482
Chromosome 4
GGACACTGTGA

ACACTGTGTGG

ACAGAGCCCA

CAACTTCTCCA

TTTGTGTCTGG

CAGCAA

330.
Mm.14302
Chromosome 9
AGGAAAGAAA

GGGGTTAGAAT

CTCTCAGGAGA

TTAAAGTTTCT

GCCTAACAAG

AGGTGTT

331.
Mm.28451
Chromosome 16
CTCAAGACTTT

GCCAACATGTT

CCGTTTCTTAC

ACCCTGAACCC

TGATCGGAACA

TTCAT

332.
Mm.200891
Chromosome 11
TCTGTACATGG

CCGAAAATCA

GAGTCCACCAT

ATTCTTTTGAA

TATCCAGGGTT

CTCTGA

333.
Mm.193835
Chromosome 6
TTCTGGCTCCT

TATTTCAGTTC

TCTTTAAAACC

AGTTCAACACC

AGTGTGTTAAA

AAGAA

334.
Mm.31129
Chromosome 9
GCAGATTTAAC

AACTAGCAACT

CTGTCATCTTT

TTCTAAAAATG

ACCAACTGCTG

ATTAC

335.
Mm.154695
Chromosome 17
CTTAAAAAGG

GAGATACAGTT

TTACTCTGATC

CAGCAAATCTA

GTTAAGACACT

AGAATG

336.
Mm.9043
Chromosome 7
CTTCCTGAACC

ATTACCAGATG

GAAAACCCAA

ATGGCCCGTAC

CCATATACTCT

GAAGTT

337.
Mm.134338
Chromosome 11
GTAACGGAGC

CTGGGGGTTGA

AGGTTATCTTT

ACATATATGTA

CAAACTGTTGT

CAAGAG

338.
Mm.259795
Chromosome 7
TCCCCACCACT

CATGGGGATCT

TCAAGAAGCAT

CACCATTCACT

GAAAGGTCCTA

AAAAA

339.
Mm.24449
Chromosome 10
GCGCAGAGGC

AAACCAACGT

GGAGCCAGAC

ATTGGTGAACC

CAACCTATCCA

CACCTTCA

340.
Mm.259702
Chromosome 6
CTTATTTTAGA

CAGATCCAAA

GTTCTCACAAG

CCCCCTTTCTT

TGCTCTGCCTA

TCATCG

341.
Mm.11161
Chromosome 8
AACCTCTGAAC

CTAATCACTGT

GGATTCCCACC

AACACCATATA

TGAAAATGCA

GGCCGA

342.
Mm.1428
Chromosome 14
TGCGGAAGGA

GGGGATTCAA

ACCAGAAAAC

GGAAGCCCAA

GAACCTGAATA

AATCTAAGA

343.
Mm.275718
Chromosome 2
CCCTAGTCCGT

TTTCTGATCAG

TCAGAACCCAC

AATAACTACTA

GTAGTCCTGTG

GCTTT

344.
Mm.218038
Chromosome 9
GTAGCCACCAA

GCCACAAGTA

ACAAATGATCT

CTGTGAATGCC

ATATGGAAACT

TTTATT

345.
Mm.216977
Chromosome 9
GGCTCCATTTC

TGAACTCTGTG

TTAAGCTAATA

AGATTTTAAAT

AAACGCTGATG

AAAGC

346.
Hs.158323
No Chromosome location
TGCTGGGGGCC

info available
TAGAACCCTGA

GACATAGACC

ATGGATAAATG

GCAACCGGGG

TGGCAAA

347.
Mm.217130
Chromosome 18
AACGCAAAGA

GCAAGAACCA

AACAAAGACA

GGAACAACTC

GCAGAAGAAA

TCCCGCCTGG

348.
Mm.57171
Chromosome 6
TGTTTTCTGAT

GACCAAAGCA

ATGACAAGGA

GCAGAAAGAA

GAACTGAACG

AATTGATCA

349.
Mm.174523
Chromosome 10
CCCACCACTGA

ATATAGACCAT

ACTGTGAGAG

GACCATAATTA

GGTCCTGAATT

TTTAAT

350.
Mm.103389
Chromosome 3
GTATGACTTCC

AACCAGAAAA

AGGCTCTAAAA

GCTGAACACAC

TAACCGGCTGA

AAAACG

351.
Mm.80565
Chromosome 3
CTTCTGGCTCC

CTTACATGAAG

GACTGATTTAA

GAAACCAGAC

CATTCCTTTAC

TTTGAA

352.
Mm.215689
Chromosome X
GCAGGGTGCTT

ACTTTCTCAGA

GCCTGAAGTTA

CTTCCATTGTT

TTGGCACTGAA

TAACA

353.
Mm.200518
Chromosome 6
TTAGCACAAGA

GAAAAGCTGA

GAACGTGGGTT

TTGCCTCCTTC

AGAAATATGTC

TGGCTC

354.
Mm.152289
Chromosome 17
ACACAGCACCC

ACAACTAATCT

TGGGACACCCC

TATCTGGTTGG

AAGAGAGTAA

ACTAAT

355.
Mm.24767
Chromosome 19
CAATGGCCTAT

TCTGTCAGATG

GGTGTCCTTTC

AAGGGTGACA

ACTACAGAAC

ACAAGTA

356.
Mm.260244
Chromosome 12
AAAGTAGGTTC

ACACAGTAAA

GGGATAATACC

ATCTGGAACAA

TGATCAGTGTA

GAGTTA

357.
Mm.249888
Chromosome 4
CACCTGGGTCT

ACAGCTACTCT

GATTCTACAAA

GACAGGGTCA

AGCATCTCTAA

CAAAGT

358.
15182
Chromosome 10
TATTAAACCCA

GGAGATACAA

GGAGTCTGCCA

TTAACCTCTCT

GTAACTCAAGA

GTAGTT

359.

No Chromosome location
TTCCTCCCAAA

info available
ATGGAGTTTCC

TCTTCAAACCA

CAGCTCCCCCA

AGATCTATCCT

GATAT

360.
Mm.21836
Chromosome 5
TATGTCTTGAT

ACTGGACCCAC

ACTACTGGGGC

ACTCCAAAAA

ACCGTTGTGAA

CTACAA

361.
Mm.208743
Chromosome 11
AGTAAAGGGC

ACCGGAAATGT

TAAATCCTTGT

TTAGGATATGA

AAGGAATTAG

GGGATGG

362.
Mm.217288
Chromosome 11
GAATGTCTGAT

ACATGACCCAT

CAGTTAGGAAC

CACTGAACTAG

AGGAGTAGCT

AAACTC

363.
Mm.45371
Chromosome 13
GCTTCTACTGG

CTCTTGTATGC

ATATGTGCACT

TATCCAGACTG

AGGATTTTACA

AAGCA

364.
Mm.113272
Chromosome X
CTGTCTAAGCG

CTGAACCACTT

AGCAGAAATG

ACACCCATATG

AGAGCTTGTGC

CAAATA

365.
Mm.173357
Chromosome 14
AAAGGAGACT

GCATCAGGTAT

TCTGATAGAGA

GCTGAGGAAG

AGATTGAGGTA

TGGGATT

366.
Mm.234023
No Chromosome location
TGACTGGAATC

info available
ACCACCCTTGC

CTGAGTTTGCG

ATCTCACAGTT

GGAACTGAGA

GTTTCC

367.
Mm.5675
Chromosome 12
GGATCAGATG

ATGCACCATTG

CTTTCCATTGC

TACATTTAAAA

TCTTTTACTAG

TCAACC

368.
Mm.11978
Chromosome 1
TTGAGACCTTA

AAGAAATAAC

AAACTCAAGG

AAGATTAGGGT

CCAGTGTTTAA

GTCATGG

369.
Mm.228379
Chromosome 12
GTCTCCTTTGT

GTTATTGCCTT

CCCAACACTTC

TAAGTCCCAGC

TCAACAGCTAC

TTCTA

370.
Mm.17675
Chromosome 1
CACAGCTGCTT

GTAGTCATCAT

TCCAGTGAGGA

GTAAGAAGAA

TTTTATGTGTG

TCTCTA

371.
Mm.20355
Chromosome 4
AACTTAAACAG

TCTCCCACCAC

CTACCCCAAAA

GATACTGGTTG

TATTTTTTGTTT

TGGT

372.
Mm.28721
Chromosome 2
CAGCAGAAA

GGCTCCCACCA

AGAAGGCCAA

CAGCACAACC

ACAGCCAGCA

GGATGTGTT

373.
Mm.25072
Chromosome 17
GGCTTCACATC

TAAGTGGGGA

CTATTTTAACT

TATTTACAGGT

ATATGGTGTGG

AAATAA

374.
Mm.233802
Chromosome 7
CGCTCAGTTGT

AGAAAGCAAC

AAGGACACAA

ACTTGATTGCC

CAAAGTCACTG

CCAGTTA

375.
Mm.1389
Chromosome 7
GTCTGAACACA

CTATTATGTAT

CCATCCAATCT

CAACTGAATAA

AGGGAGATGC

CTTTTG

376.
Mm.221547
Chromosome 14
AAAGAATTTCA

AGAACGAAGC

ATAGGTGGTTA

TGTAGTTTGAT

TACAGAAAAG

AGATGCC

377.
Mm.4697
Chromosome 11
AAACCACCTTC

AGTGTGAGGA

GCCCACGTCAG

TTGTAGTATCT

CTGTTCATACC

AACAAT

378.
Mm.100116
Chromosome 6
GCACTCCAGCC

TGATTCTTTGA

GACTTTGGGGT

ACACATATTGA

AAGTACTTTGA

ATTTG

379.
Mm.231395
Chromosome 7
ACTGTATCGGT

TCCATGTAAGT

CTGACCAGTCA

AAGGCAAGAG

GTATCAAGGTG

GAGAAA

380.

Chromosome 18
GTGTTTGAATT

AAAACCCCCAC

CCTCGGAGGCC

TTTAAAGAAAT

GGTTTTTGTCC

GTTGT

381.
Mm.149642
Chromosome 6
CTCTCGACAAA

ATATAAATGGA

CAGTACCAAAC

TAAGAGGGAT

ATAAGTGGGA

GCAAAGG

382.
Mm.202311
Chromosome 11
TATGGTACGAG

TTTAGGGCTTA

GTCAGTTTACA

ATGGGGATTGA

ATTTTGTGTCA

AAACC

383.
Mm.235234
No Chromosome location
CTGGCTCCTAC

info available
TGGCAACAGG

CATACTTGTGG

TTTAATACAGA

GAAACAAAAC

ATTCATA

384.
Mm.27968
Chromosome 1
TTTGACCTAAT

GAAATACCCAT

TTCATCTGTGA

CAACACATAGC

CCAGTAAACAT

CACTG

385.
Mm.37806
Chromosome 14
CCTGTTCCTAG

TATCCTGGCGT

CCACATATACC

CAAAGTTAGGC

ATACTAACCAA

GAGAT

386.
Mm.2901
Chromosome 2
CTGGAACTCAG

CACTGCCCACC

ACACTTGGTCC

GAAATGCCAG

GTTTGCCCCTC

TTAAGT

387.

Chromosome 12
CCTGGAGGTCT

CCACCTGAAGT

TCCCTGATGCA

GGGTCAGTCCA

GCCTTGGTAAG

GGCCA

388.
Mm.182611
Chromosome 12
AAATGAGAAC

CAGATTACCAA

AATTACCACTA

CCACCAAAATA

ACCCCTCTGAT

TCCTTG

389.
Mm.225096
Chromosome 2
CAGATAGATG

ACAGCAGGAA

ATTTTCTTTATT

TCCTGAAAGAA

AATACCAGACT

CTCAAC

390.
Mm.174047
No Chromosome location
GGTGCCAAATG

info available
CGGCCATGGTG

CTGAACAATTT

ATCGTCAGAGG

GGAAGAACAG

TTGACC

391.
Data not found
No Chromosome location
CCAAAACAGA

info available
GCCAACACCAC

CGACAACAAC

CCCACAGCAA

ACCCGGAGAG

AAACCCAAA

392.
Mm.12900
Chromosome 1
TTTCAACCCGC

CCATTATTTCC

AGATTTATCCG

CATCATTCCTA

AAACATGGAA

CCAGAG

393.
Mm.143742
Chromosome 5
TGGAGACTGA

GTTCGACAATC

CCATCTACGAG

ACTGGCGAAA

CAAGAGAGTA

TGAAGTTT

394.
Mm.250079
Chromosome 11
GATACAACAG

CATCTGTTTTC

CAAGGAGAAA

TCATTTGAGGA

ACAAAACCTAT

CAAGAGA

395.
Mm.45048
Chromosome 2
AACTAGAAAA

CATAGATGCAC

AGGACTCGGAT

CCATGATATTT

ACACTGGGAA

ATGTTCT

396.
Mm.34384
Chromosome 6
ATCTCAAGATT

TCTATCCAAGT

GGAAACAAAC

TGAATCATGCA

CACGACTTATC

TGTGTG

397.
Mm.19839
Chromosome 13
AGAGGAGCCA

CACTTGATGTG

AATTAAACTCA

TAAACATTATG

CCACTAACAGC

TTTTAT

398.
Mm.4312
Chromosome 4
CTGCCGCCTGT

ACAAAGGAAA

CTGAACCTTTT

TCATATTCTAA

TAAATCAATGT

GAGTTT

399.
Mm.206841
Chromosome 3
AAGCTGAGATT

AAACGGCTAC

ACAATACCATC

ATAGATATCAA

CAACCGAAAA

CTCAAGG

400.
Mm.28865
Chromosome 4
GACTTGGGAA

AACAATGCAA

CTCCCATAAAC

CAAAACTCCAA

TTCCATGCCTA

ACTTGCT

401.
Mm.2666
Chromosome 4
AGCAGGGAAC

AATTTGAGTGC

TGACCTATAAC

ACATTCCTAAA

GGATGGGCAG

TCCAGAA

402.
Mm.6251
Chromosome 1
AGCTCCAACTC

AACAGATGGCT

ACACAGGCAG

TGGGAACACTC

CTGGGGAGGA

CCATGAA

403.
Mm.103450
Chromosome 10
ACTAGCTGCAT

TGTAAAGAAA

CAAATCGAAA

CTGAGTCTTTT

CACATATTGTG

ACGGACA

404.
Mm.24276
Chromosome 6
GTAGGGTCATC

ATACACCCAGA

CTACCGCCAAG

ATGAACCTAAC

AATTTTGAAGG

AGACA

405.
Mm.11092
Chromosome 11
TCCCCACCACG

AATTATCGTGG

CTAGTGGATGA

AGGCCACTAAT

ACAGGTTCAAA

TTGTT

406.
Mm.23837
Chromosome 5
TATGTGCATAG

GCTGGAGTTTT

GGTTATACATG

GTACACTTTTG

GGCCAATATAA

TAGGA

407.
Mm.9706
Chromosome 12
CCACACTCCCT

GGAGACAATG

TCTGCCATTTT

TGCATCACTTG

TCAAACCACTA

ACTTCT

408.
Mm.173615
Chromosome 6
TCGGTTGACCT

GATTCCACCAA

GGAGAAGGAG

ATCAAGGAAG

AGTAAACTGTA

AGAGCAT

409.
Mm.133615
Chromosome 9
GAGTGCTTTGA

TGGTTGTTAGG

GACCGTAAGA

ATAGTCCTGTG

TCAGACAGCA

GATTCTA

410.
Mm.255931
Chromosome 19
AACTGTCATAA

AATCCAACGTG

CCTTCATGATC

AAAGTTCGATA

GTCAGTAGTAC

TAGAA

411.
Mm.289605
Chromosome 5
ACTCTCATCTG

TAAAGCCTTCC

CATCTCATTAT

TCCTTGCACTA

ACCACAGCCAC

TAGGA

412.
Mm.197224
Chromosome 11
CAGACTGAAA

GGAAATTCCAA

AGAAAACAAA

AACCTTTCAAT

CTATGAACTCA

ATGGCTG

413.
Mm.219663
Chromosome 15
CTGAGAATAAC

CTACTACCACC

TCTCTTTTCCC

ACCAACATCCA

AGTGCCAGCG

GTGGTT

414.
Mm.134516
Chromosome 14
AGCGACATGC

AACCAAATACC

ACTCAAAACA

AAAATCCAGC

AAAACTGAGTT

GTGAGGGA

415.
Mm.35474
Chromosome 14
GTTTGTACATG

TAAAAGATTGA

CCAGTGAAGCC

ATCCTATTTGT

TTCTGGGGAAC

AATGA

416.
Mm.173781
Chromosome 3
ACTTAGACCAC

AACAGCATCTA

AGCATCATTAC

CTTAAGTACTA

AAGCAAAAAT

CTAGTC

417.
Mm.60590
Chromosome 15
TAAACCACTCT

TAAACTGCTGG

CTCCAGTGTTT

TTAGAATGATA

TGAAGTCATTT

TGGAG

418.
Mm.2408
Chromosome 6
AGTAAGTGCCA

TTATCCACCCA

ACTACCAACCA

ATGCCTAAGCA

GATTCTATATC

TTAGC

419.
Mm.31672
Chromosome 5
GCTTCTGGCAG

AGATCTGTTTA

GCATAGTGTGG

TATTAATTATA

GCAAATGTTAA

GGTAG

420.
Mm.250054
Chromosome 15
GTTGTCTGAAT

AATAGCACCCA

AGAAAAAGTG

TGGAGATCAGT

AGGTATTCATT

AAGCAT

421.
Mm.5202
Chromosome 10
TAAAGGAGCTT

TCCACATGAAC

TCACAATTTTC

TTGAAATAAAC

TTCTTAACCAA

CTGCC

422.
Mm.987
Chromosome 1
GTCACTTGGAT

GGTGTATTTAT

GCACAAAAGG

GCTCAGAGACT

AAAGTTCCTGT

GTGAAC

423.
Mm.159956
Chromosome 7
GTCATGAACCC

AATACACTGTG

GAAATGTGTGA

TTCTTTATATT

AAACGTCTGCT

GTTCA

424.
Mm.31672
Chromosome 5
TGTCGATACCA

TCTAAAGACCA

CAACTTCTAGC

CATAGGGTATT

TCATATATGTC

CATTT

425.
Mm.221754
Chromosome 7
ATGCAAACCTA

AAAAGCACCC

AAAAAATTCAC

ATTGGACTGAA

GAAGAGTGAT

CCAAGCA

426.
Mm.1114
Chromosome X
TTTGAGACCCT

TTCATAAGCCC

AATTATACAGA

TATCCAATATT

ACTGCAATCAT

TGGAG

427.

Chromosome 13
ACCTAAATTTC

CACAGGCAACT

TACTTTGTTAT

TAAATTTGGGG

ATCATATCCTG

TGCCC

428.
Mm.260376
Chromosome 9
TTTTTTCAGAC

TTAAGAACAGC

TAAACAAAAC

CTTCCTCTAGC

TTTTTCATCAC

ATCCAG

429.
Mm.249886
Chromosome 17
ATAATGATGAT

GATAACAACA

AGAAAACAGA

CTCGAACCTAA

AGACGCTGGTC

TCAGATA

430.
Mm.4987
Chromosome 5
CGCAAACATAC

CCTGTATAAGA

AGGCTCCTAAC

GAGAGATTTAT

TAACAACACTA

TATAT

431.
Mm.233117
Chromosome 19
TTTGACTGGGA

CCAGCCCAGCC

ATTCTCAGCCT

CTCGACATGTA

ATTTCATTTCT

TTTAC

432.
Mm.24576
Chromosome 3
AGGACTCATAG

ACTTACAGAAT

GATGCCGAATG

GAATGTTTTGT

GCATGACCTTT

TAACC

433.
Mm.143813
No Chromosome location
CCACCTCGCCC

info available
AAGTCTCCTTT

TACTGAAATAA

AATTTGAGGGG

AAGAGAAAAA

ATTTAC

434.
Mm.15383
Chromosome 15: not
GATGTTCTTCT

placed
GTAAAAGTTAC

TAATATATCTG

TAAGACTATTA

CAGTATTGCTA

TTTAT

435.
Mm.23572
Chromosome 2
CTTAAGATTCA

GGAAAATGGTT

CTTTCTGCCCT

TCCTAGCGTTT

ACAGAACAGA

CTCCGA

436.
Mm.24138
Chromosome 2
TATATTGACAT

CCATAACACCA

AAAACTGTCTT

TTTAGCTAAAA

TCGACCCAAGA

CTGTC

437.
Mm.3645
Chromosome 9
TCTTTAGTGCT

GCATTTAAGTG

GCATACAAAAT

ACAATCCCATA

TGTATGAACTG

TTGTG

438.
Mm.86813
Chromosome 16
AATCTATGCCA

GATACTGTATA

TTCTACCATGG

TGCTAATATCA

GAGCTAAATG

ATACTC

439.
Mm.136022
Chromosome 2
AATTTACACAT

GTGGTAGTAGT

AGGTCCAGATT

CCTAAGTTACA

GTGTGCTGAAA

AATAA

440.
Mm.11819
Chromosome 1
ATGAGGCTAA

ATTTGAAGATG

ATGTCAACTAT

TGGCTAAACAG

AAATCGAAAC

GGCCATG

441.
Mm.86813
Chromosome 16
TCTACTACTTT

GCTTATCATGT

TCACTGCAAGG

GAGGCAACGT

ATGGGTTGCTC

TCTTCA

442.
Mm.196253
Chromosome 16
GTACTGAACTC

ACAAGCGTATC

TCCTATTTTAT

GAGAGAATAC

TGTGATAACAA

AAAGTG

443.
Mm.6483
Chromosome 7
TTGGCCCACCC

CCAAAGGGCC

AAGATTATAAG

TAAATAATTGT

CTGTATAGCCT

GTGCTT

444.
Mm.3453
Chromosome 4
CTGGGAACCAC

CTAATGGTATT

ATTCCTGTGGC

CATTTATCAAT

ACCTTATGAGA

CTATT

445.
Mm.22929
Chromosome 4
TCCTCTGGGGT

AAATGAGCTTG

ACCTTGTGCAA

ATGGAGAGAC

CAAAAGCCTCT

GATTTT

446.
Mm.233891
Chromosome 2
GCCGCAACGC

AACAGAAATT

GTTTTTAATTT

CATGTAAAATA

AGGGATCAATT

TCAACCC

447.
Mm.25941
No Chromosome location
ACTTTTGGGTC

info available
TTTAGAACTGA

GCCCACCTACT

GAGTCTCAGTT

TCTGTTGGTGT

GACCT

448.
Mm.17185
Chromosome 12
TGCTTACTAAG

AAGCCAGTTTG

GGTGGGTAAA

GCTCTCTGGAA

GAAGGAACTTT

GCTTCT

449.
Mm.3266
Chromosome 11
TCCCAATGTGT

AGAATTCAACT

ATGTAACGCAA

TGGTACATTCT

CACTGGATGAG

ATAGA

450.
Mm.930
Chromosome 13
CTTATGGACAC

TATGTCCAAAG

GAATTCAGCTT

AAAACTGACC

AAACCCTTATT

GAGTCA

451.
Mm.29454
Chromosome 12
GCCATATGATG

AACAGAATTTC

AAGAATGCTGT

TTTATGCCTTT

TAACCTCCAAA

GCAGT

452.
Mm.288252
Chromosome 15
TCATTTTCCTG

TCTAGGCTAAA

GCTAAACTTAA

ACTATGGCTTT

ACGTAAATTAA

GCTCC

453.
Mm.24223
Chromosome 16
CAACATCTAAC

GCTTTACATAA

ATGCCCTTTTA

GCTTCTCTATT

TCGACACAACT

GTGAT

454.
Mm.9277
Chromosome 17
TTACCCAAATA

AGCATTTTTTA

AATATACCCTG

TACTGTAGGAT

AGTGATGAAC

GCCTAG

455.
Mm.459
Chromosome 1
ATAAGCCGTAT

CTGGGTCTTGG

ACTACTTTGGT

GGACCTAAAGT

AGTGACACCTG

AAGAA

456.
Mm.4190
Chromosome 8
AAGTGGAATG

GAGCCGGCCA

AGCTGAGCCTG

ACTTTTTTCAA

TAAAACATTGT

GTACTTC

457.
Mm.4159
Chromosome 2
CTTAAAACTAC

TGTTGTGTCTA

AAAAGTCGGT

GTTGTACATAG

CATAAAAATCC

TTTGCC

458.
Mm.19352
Chromosome 14
CAGCTGCCTAA

CCCGCAACATT

TGCATTATGTT

CAGACTGTAAC

CTGCTTACTGA

TGGTA

459.
Mm.233010
Chromosome 10
CTGTGGTACCA

AGGAGTTATTT

TGGATGATTAG

AAGCACAGAA

TGATCAGGCCT

TTAGAG

460.
Mm.2580
Chromosome Multiple
TTGTTTTTGTTT

Mappings
TTAACCTAGAA

GAACCAAATCT

GGACGCCAAA

ACGTAGGCTTA

GTTTG

461.
Mm.42193
Chromosome 13
TGCCTGAAAAC

ACTTAACACTG

ATTGTCTAAGA

GATGAAAGTCC

TCCAAAGATGA

CACAG

462.
Mm.134712
Chromosome 10
ACTTCAGTTAA

TGGGTTTATAA

AGTCAAGCACT

GGCATTGGTCA

GTTTTGTATGA

TAGGA

463.
Mm.34883
Chromosome 9
TCCCCTATGCG

GTACGACCTTT

ACTGTCAGAAA

TATATTTAAGA

AAATGTTCTAA

ACGGT

464.
Mm.9953
Chromosome 9
GATCCAGCCTT

CTATGAAGAAT

GCAAACTGGA

GTATCTCAAGG

AAAGGGAAGA

ATTCAGA

465.
Mm.741
Chromosome Multiple
CATGACTGTTG

Mappings
AGTTCTCTTTA

TCACAAACACT

TTACATGGACC

TTCATGTCAAA

CTTGG

466.
Mm.19844
Chromosome 5
CTTGTAATCAG

ACACGTGTTTT

CCTAAAATAAA

GGGTATAGAC

AAAATTTAAGC

CCATGG

467.
Mm.3468
Chromosome 11
TGTCTGAAGAT

GCTTGAAAAAC

TCAACCAAATC

CCAGTTCAACT

CAGACTTTGCA

CATAT

468.
Mm.369
Chromosome 4
TACTCCCATTA

CTATTTGCTGG

TAATAGTGTAA

CGCCACAGTAA

TACTGTTCTGA

TTCAA

469.
Mm.22753
Chromosome 14
CAGCCGATGCT

TTTTCAATAGG

ATTTTTATGCT

TTGTGTACCTC

AACCAAGTATG

AAGAG

470.
Mm.2012
Chromosome 6
GGGACACTTAA

TTTACATGTAC

TTTAACCCCAT

GAAAGAGTCT

AGATAGAGAG

AAGACAC

471.
Mm.22547
Chromosome 8
GCCTGCCAGTA

ACCCCAGGAA

GAGTCTAGCTT

CAAAAACCCA

CAAACTCATTA

TTTTTAA

472.
Mm.39298
Chromosome 3
AATCTAGATGT

TAGAAATCAAT

GTGTATGATGT

ATTGTATTTAG

ACCATACCCGT

GACCG

473.
Mm.57177
Chromosome 2
ACGATGAGCA

GTGTTTGAAAG

CTTTCCAGTGA

GAACTATAATC

CGGAAAAATG

AATGTTT

474.
Mm.41333
Chromosome 10
GATGCGTGAA

ATGTTCCTCCA

GGAAAAGCCA

TTCAAGCCTGA

TTATTTTTCTA

AGTAACT

475.
Mm.100666
Chromosome 1
CATCTTAGATC

TCAGAGACTTG

AACCTTGAAGC

TGTTCCTAGTA

CCCAGATGTGG

ATGGA

476.
Mm.2423
Chromosome 15
CGTGTCCTACA

CAATGGTGCTA

TTCTGTGTCAA

ACACCTCTGTA

TTTTTTAAAAC

ATCAA

477.
Mm.15185
Chromosome 8
AAGGAGCCAC

GATAATACTTG

ACCTCTGTGAC

CAACTATTGGA

TTGAGAAACTG

ACAAGC

478.
Mm.20458
No Chromosome location
GTTTATAGGTA

info available
GACCTAAGAG

ATAAAACTGCA

GGGTATCACAT

TAACGTTGGTT

AAAAGA

479.
Mm.26786
Chromosome 15
AAACTTGAGAC

ATTTTGTAGGA

CGCCTGACAAA

GCGTAGCCTTT

TTCTTGTGTCA

GGATG

480.
Mm.565
Chromosome 12
CTCATACCAAA

GAAATACTTGA

CACTGCTTTGA

AGGAGATAGA

TGAAGTTGGGG

ATCTGC

481.
Mm.290404
Chromosome 12
AAATCCAGCCT

TTAAAAGCTCA

GTTTCTTCCTC

TAAGTGAATGT

CATTACTCTGG

TATAC

482.
Mm.5378
Chromosome 6
ACCAGGAACTC

TGGTAACATTT

GAGGGCATGC

AGATAAAATA

ATAAAGAATG

AGAACATT

483.
Mm.29564
Chromosome 8
TCAACATCTAT

GACCTTTTTAT

GGTTTCAGCAC

TCTCAGAGTTA

ATAGAGACTG

GCTTAG

484.
Mm.261624
Chromosome 13
GACCGAGAGC

CACCACAAGG

CCAAGGGAAA

ATAAGACCAG

CCGTTCACTCA

CCCGAAAAG

485.
Mm.3152
Chromosome 11
TTCTACCTCAC

TAACTCCACTG

ACATGGTGTAA

ATGGTACATCT

CAGTGGTGGTG

ATGCA

486.
Mm.18742
Chromosome 7
TTGGAGAAATT

AGGAGTTGTAA

GCAGGACCTA

GGCCTGCTTGA

TTCTTTCCCAC

CTAAGT

487.
Mm.3137
Chromosome 1
TTATTGAAAAG

TTTGAAGTTAG

AACTTAGGCTG

TTGGAATTTAC

GCATAAAGCA

GACTGC

488.
Mm.227260
Chromosome 2
CACCATTTCCA

ACTTGCTGTCT

CACTAATGGGT

CTGCATTAGTT

GCAACAATAA

ATGTTT

489.
Mm.3295
Chromosome 1
AACAAGAGAT

CCTGTGGATGA

GGGGGTCTGTA

TAAGTTATACT

CCAATAAAGCT

TTACCT

490.
Mm.38783
No Chromosome location
TTTTGACCAGT

info available
TGAACCCATTT

TGTTTTCCTAG

CGAACACTAGC

ATAATATTGGA

AAAGC

491.
Mm.257899
Chromosome 1
GTGAGGATTGG

AATTAGAACAT

TCATAAGAAA

ATATGACCCAA

CATTTCTTAGC

ATGACC

492.
Mm.7500
Chromosome 7
CGCCCTGGAGC

CTCTGTCAAGT

CTTGGACCAAG

TAAAAATAAA

GCTTTTTGAGA

CAGCAA

493.
Mm.142455
Chromosome 14
AAGATGGAGA

GTTGTCCAAAC

AAGATCCCAA

GTCTAAATAGA

GCAAGGGATTC

TGAGGTG

494.
Mm.200886
Chromosome 2
GTTTTAAAAGG

TGCCAGGGGTA

CATTTTTGCAC

TGAAACCTAAA

GATGTTTTAAA

AACAC

495.
Mm.25311
Chromosome 15
TCTGAGGTATT

AAAATATCTAG

ACTGAATTTTG

CCAAATGTAAG

AGGGAGAAAG

TTCCTG

496.
Mm.282049
No Chromosome location
AAGTATTGCTA

info available
GACTGAAACC

ACTTGAACTTC

TCAGAGAGGTT

AGACTGACAG

AAGGTGT

497.
Mm.41264
Chromosome X
ACATTTTTGTC

ATCATCATGTA

AATCCCACGAT

TTCAAACTGTA

AACATCTGTTC

AGTGG

498.
Mm.24584
Chromosome 11
CTGGGGAAATT

GATCTTTAAAT

TTTGAAACAGT

ATAAGGAAAA

TCTGGTTGGTG

TCTCAC

499.
Mm.45173
Chromosome 3
AGGACTCAAA

ACTATATTAAT

CTGCTCTGAGA

TAATGTTCCAA

AAGCTCCAAA

GAAAGCC

500.
Mm.151315
Chromosome 1
GCTCCAACATG

CCATGTATTGT

ATAGACTTTTA

CTACAATTCAA

ATAACGTGTAC

AGCTT

501.
Mm.25492
Chromosome 8
CAGCTGAATGG

GTTTTGGTTTG

CAGGAAAACA

GTCCAGAGCTT

TGAAAAGGCTC

CTAAGA

502.
Mm.227732
Chromosome 3
TGTTTTTATTG

TGTTTGGTGGA

GAAGAATAAT

ACACTTCTTGC

CTAAATCCAGA

AGCCCC

503.
Mm.27061
Chromosome 6
TCCAGTTCCCG

AAGAAGCTGA

TAGGAATTGCC

CTTGTGCATAT

ACTACACAAGC

ATGCTA

504.
Mm.4165
Chromosome 19
CATAAAGACAT

AGTGGAGGTTC

TGTTTACTCAG

CCGAATGTGGA

GCTGAACCAGC

AGAAT

505.
Mm.27098
Chromosome 5
GGATTCGGCTC

GATGAATGAA

GCACTTTATGG

ACTGCGGGGAT

CAGTTACTGCC

ACACCC

506.
Mm.7046
Chromosome 2
TGCTTTTACCA

TGTTCTCGAGG

TTCCTGAACAA

AGAGCCTTACT

GATAGTTCCGC

TGCAA

507.
Mm.29329
Chromosome 4
TGAAGCAAAA

AACATAAAAC

CTCACCACTGC

CTGCTGAACCT

AGAACCTTTTG

TTGGGGC

508.
Mm.381
Chromosome 4
GAATCCTTAGA

TGAAGTTATGG

ATTACTTTGTT

AACAACACGC

CTCTCAACTGG

CTGGTA

509.
Mm.38399
Chromosome 1
GATATTAGTAG

TATATCATAAA

ACTTGAGAAAT

AAAGATGCGCT

CACCCCCTATC

TGTTG

510.
Mm.39298
Chromosome 3
TGTGATAAAGT

TGTGACATACG

TATTAGTTGGC

ACATATTTAAG

CTCCAAATCAG

TTTGC

511.
Mm.260244
Chromosome 12
TAAAAGTTAAA

GTAAGCGAAG

AAAGGAAGCT

GTATCTACACT

GCTTTCCAGTT

TAATCAG

512.
Mm.193099
Chromosome 1
GGAGATTTTTC

TCTTCAGGGTG

TCTACATACCT

TACACACACTT

GTGTCTTAATA

AGCAA

513.
Mm.156919
Chromosome 2
AATCCATGGGA

GGGGGGAACA

AGTCCAGACTG

CTTAAGAAATG

AGTAAAATATC

TGGCTT

514.
Mm.1568
Chromosome 11
AATGTGGAGTG

TGGAGAAGGG

CATTTCTGCCA

TGATAACCAGA

CCTGTTGTAAA

GACAGT

515.
Mm.14860
Chromosome 19
TGACATGAATG

AAATCAAAGT

ATTTTACCAGA

AGAAGTATGG

AATCTCTCTTT

GCCAAGC

516.
Mm.27816
Chromosome 13
ACTGGATACTG

TAACTATGAGA

ATAAAATATAG

AAGTGACAGA

CGTCTACAGCA

TTCCAG

517.
Mm.275696
Chromosome 10
ATACAAGCAA

GCTGTTAAAGA

TCTTGGATCCC

ATTCTATAGTG

TGTATACCTAA

ATCAAC

518.
Mm.245007
Chromosome 1: not placed
AGCATCAACTG

TCCTGTCAAGC

ACAAAAAATG

AAGAAGAAAA

TAATTACCCAA

AAGATGG

519.
Mm.27112
Chromosome 12
CCTCTGTTCTG

AGGAACATTCT

AGCATAGAAA

ATGGAATATGC

TGCAAACATTT

CTAGAT

520.
Mm.212870
Chromosome 1
GTGTAGAAGCC

TATTGAAATAT

CAGTCCTATAA

AGACCATCTCT

TAATTCTAGGA

AATGG

521.
Mm.19182
Chromosome 7
CTGATCCCGCC

TCATCTCGCTG

CTCCGTGCTGC

CCTAGCATCCA

AAGTCAAAGTT

GGTTT

522.
Mm.10727
Chromosome 8
TGTAGAAAATG

TGGCCTCTCGT

TATAAATGAAA

ATAAATGTTTA

ATTTAATGGGA

GTTTC

523.
Mm.6105
Chromosome 2
GGTGCCACAG

AGAAGAGCCC

AGTTGGAAGCT

ATACCCGATTT

AATTCCAGAAT

TAGTCAA

524.
Mm.193099
Chromosome 1
CAGTGTTGTTT

AAGAGAATCA

AAAGTTCTTAT

GGTTTGGTCTG

GGATCAATAG

GGAAACA

525.
Mm.200518
Chromosome 6
ATAACTATATA

TACTTAGAGTC

TGTCATACACT

TTGCCACTTGA

ATTGGTCTTGC

CAGCA

526.
Mm.6419
Chromosome 5
CCTTGGGACAT

TTTTGTGGAGT

AGTTTGCAGTG

AGATAACAGT

GCAATAAAGA

TACAGCA

527.
Mm.46067
Chromosome 14
TCTATACCTGG

ATAAAAAGAA

ACCTACACTTC

ACTGTAAAACT

TCATGTTTCAA

GGCAAG

528.
Mm.192991
Chromosome 8
CCTGTTTACTA

AACCCCCGTTT

TCTACCGAGTA

CGTGAATAATA

AAAGCCTGTTT

GAGTC

529.
Mm.33903
Chromosome 13
ACCGTGTAGAC

ACTCATATTTT

GCATGACATGA

TCTACCATTCG

GTGTAAACATT

TGTGT

530.
Mm.2436
Chromosome 6
GCCAAAGGAA

AATGTTTCAGA

TGTCTATTTGT

ATAATTACTTG

ATCTACCCAGT

GAGGAA

531.
Mm.28392
Chromosome 7
TCCAGAAGCTG

CATTGCCAACA

TCACACCCCAA

AATTGTCCTGA

CATCGCTGCCC

GCATT

532.
Mm.2814
Chromosome X
AAGGACTCTGA

GGCCATCCGTA

GTCAGTATGCT

CATTACTTTGA

CCTCTCTTTGG

TGAAT

533.
Mm.296913
Chromosome 13
ATCTCCCAAGG

CAAAGAACTG

AAACTCAGAG

CTGTCTGGATT

GAAGAAATGT

GTGTTGTT

534.
Mm.1186
Chromosome 3
ATGAAGGTAG

GATAATTAATT

ACAAGTCCACA

TCATGAGACAA

ACTGAAGTAAC

TTAGGC

535.
Mm.296074
Chromosome 1
GGTGTAGCCAT

ACAATACACA

AATACAATAG

ATATTCTCTCT

ACAATCTTTAT

GGTGTGG

536.
Mm.29045
Chromosome 6
GGAGAAGCAG

ATTATCTGTGT

GGCTTCCTCTT

TCTGTTCTAAT

ACTGGTAATCA

GTGGAC

537.
Mm.1314
Chromosome 6
GTGAACACCA

GAATTTAATTT

CCATACTTGTA

CAGGTAGGACT

ATTCTTCAGCT

CTCTAC

538.
Mm.46354
Chromosome 9
GGCTTCACACA

TGTGGAGATAA

GCCCCAAAGA

AATGACCATCA

TATATGTGGAA

GCCTCT

539.
Mm.144089
Chromosome 15
GTTTGTAAAGT

TGGTGATTATA

TTTTTTGGGGG

CTTTCTTTTTAT

TTTTTAAATGT

AAAG

540.
Mm.77396
Chromosome 17
ATGGAATTCTG

TTAGAGTAAAA

AAGAGAAAAG

CAGATACTATT

GGCTGGCCTTG

GAGGTC

541.
Mm.87452
Chromosome 1
AATAGTGCTGA

ATTTGTCTAAA

CAGAATTGAG

AGGTCATAGA

AATCCTTAACA

GGGTAAC

542.
Mm.297991
Chromosome 13
TATGAAGATTT

GGGAAAGAAC

AGCTATCTGAC

ACCTGGAAGG

CTCAGCCAGAG

TAACAGT

543.
Mm.22240
Chromosome 4
GAGGCAACATT

CCTTATTCACC

AACTAGTCTCA

AAAGATTGTCT

TAAGCCCTGAC

GATGG

544.
Mm.248549
Chromosome 9
TAATGAAGGAT

GTATAATTGAT

GCCAAATAAG

CTTGTTCTTTA

GTCACGATGAC

GTCTTG

545.
Mm.46067
Chromosome 14
CAGTTTGCGAA

GTAGAATTTTG

TTTCTAAAAGT

AAAAGCTAAG

TTGAAGTCCTC

ACAGAG

546.
Mm.259614
Chromosome 11
TAGAAAAGAT

CACCAACAGCC

GGCCTCCCTGT

GTCATCCTGTG

ACTAAGAAAT

GATTCTT

547.
Mm.4182
Chromosome 7
TATCTAAGAGC

CAAGTCTATGG

CATTAGCTGTG

AGAAGTAGTTA

CCACTGTAATT

CACCT

548.
Mm.36389
Chromosome 12
AAATTATCACT

TGGATACGGA

GGAACATGACT

AGGCACATTTT

ATGAATACTCC

AAATCC

549.
Mm.11982
Chromosome 10
AACTATTGGTG

GTATATTTTTG

AACACAGGTTA

ACTGTGGAGGT

TATCTGCTAAT

AGCAA

550.
Mm.29058
Chromosome 18
ACCTCTGGAAC

AGGCATTGGA

GGACTGCCATG

GTCACACAAA

GAAACAGAAC

TTTTACAT

551.
Mm.132946
Chromosome 1
CCAGTATACCT

ACAAAATGAC

CCACAAGTAAC

CCGCATGAGTC

CAAGTTGTCAG

CCATAT

552.
Mm.30024
Chromosome 6
GTAAAGGGAC

CATTACTAAGT

GTATTTCTCTA

GCATATTATGT

TTAAGGGACTG

TTCAAG

553.
Mm.24887
Chromosome 1
CTCTAAGTCAT

TCATTTTGTAA

AATTATTATAG

AGAAATCTCTA

CTTATACAGAT

GCAAT

554.
Mm.2668
Chromosome 2
TCTAATCTCAG

GGCCTTAACCT

GTTCAGGAGA

AGTAGAGGAA

ATGCCAAATAC

TCTTCTT

555.
Mm.29181
Chromosome 6
ATTCAGATCAG

GAAAGGTTGA

AATGGTCTTCG

TTACCAGGAGG

TCTACATTTAT

TAATTT

556.
Mm.28908
Chromosome 8
CAGTTATGGGC

TTCCATTTTCA

AATATCTTTTC

AACTGTAATGA

CTATGACAGGA

ACTGA

557.
Mm.4509
Chromosome 17
GCTTTCTATGC

ACGTATTGTAC

AAATTGTGCTT

TGTGCCACAGG

TCATGATCGTG

GATGA

558.
Mm.2777
Chromosome Multiple
TGGCTAGATTT

Mappings
AATTGAGGATA

AGGTTTCTGCA

AACCAGAATTG

AAAAGCCACA

GTGTCG

559.
Mm.29656
Chromosome 5
AGAGGACCATT

ATGAAGAAGC

TGTTCTCTTTC

CGGTCAGGGA

AGCATACCTAG

ACTGAAA

560.
Mm.12616
Chromosome 14
AGAAAAGAAA

AAAGCAGAGA

AAAAGTTCATT

GACATAGCAG

CTGCTAAAGAA

GTCCTCTC

561.
Mm.2144
Chromosome 12
ATATTTGCTTA

TTTAAGCGTAC

GTTCCTTTGGT

TTATAGAGAAC

ACCCCCAAATC

ACCTG

562.
Mm.222258
Chromosome 9
GACTCTCCAAC

TTACAGACTTT

TATCAGATATG

GAGAAGATAA

TGTTAAGAGAC

TTCACA

563.
Mm.143846
Chromosome 1
TAAAATCCCAT

TGAAAGTGGA

CTCAGTTGTAA

GAATAACAAT

GTGTACCATTC

TGGAATG

564.
Mm.4182
Chromosome 7
CCAATGAACCG

ACAGTGTCAAA

ACTTAACTGTG

TCCAATACCAA

AATGCTTCAGT

ATTTG

565.
Mm.182649
Chromosome 11
TCAAATCAGTT

TCAACTTTCAT

AAAATGGATTC

TTTAATGGATG

GAGACTTACTC

GTCGG

566.
Mm.160141
Chromosome 2
CTATACACAAG

ATATGCTAGGA

GATGTGAAAG

ATAATGGAGA

CTTTCCAGTAA

GCACTTT

567.
Mm.34609
Chromosome 5
CTGAGATTTTT

CAAATCTTTGG

CAACTGAGATG

GGATGGATCCA

TTTAATTAGAG

AACGG

568.
Mm.2632
Chromosome 3
AAATGTCTTTC

CAACAGTAATG

GTACTATGTCT

ATCCCCTAATA

AAACTTCACTT

CAGCC

569.
Mm.9652
Chromosome X
TGAACATTCAC

AGGATTTCTAA

CTATACTGATA

TAAACCCAGTG

TTTTCTGGACT

CAGGG

570.
Mm.117294
Chromosome 10
CAACAAAGTTG

ATTTACATGTA

TAATCCACACC

CTTAAAGATGA

ACAGTTAGAGT

AGCAC

571.
Mm.142714
Chromosome 15
TGGACACAGTT

CACTAAATTCC

TGATTTAGTCA

AAGTAACTAG

ACTGAAAGAA

CCTAAAC

572.
Mm.17484
Chromosome 6
TTGTTGTGGCT

TCACACTTAAA

TTGTTAGAAGA

AACTTAAAACA

CCTAAGTGACT

ACCAC

573.
Mm.28252
Chromosome 18
TGAACACATCA

AGTATTCTGGA

GCTTCAGCGGC

AGTTAAATGCC

AGTGACGAAC

ATGGAA

574.
Mm.88747
Chromosome 5
AAGGTCCAAA

ATACAGACATT

TTTGCTAGGGC

CTAGAAATCGA

CCATAAAACAC

ACTGCA

575.

No Chromosome location
GACTGAAATG

info available
AAAGTTCCACT

AACGGTATTTG

CTCTAGTGATA

TGTGGACATTG

TGATAT

576.
Mm.106185
Chromosome X
TCAAATAAAA

AACCCTTAATC

AGGCTGTAAAT

CAAATGACACT

ATGCGATGTCA

CTACAG

577.
Mm.221935
Chromosome 1
GCACTATAAAT

TTCATCTTTTG

AAGGTTGTTGA

CTACAAGGGTA

CAAAAATGAT

ACAGGC

578.
Mm.4973
Chromosome 11
CTTGCATGAGT

GCGTGTTTAAG

TTCTCGGAATT

TCCTGAGAGGA

TGGAGTGCCAT

TGTTA

579.
Mm.265620
Chromosome 2
AGTGTTAGCTG

CAAAGCTACA

AAGCTCTGGAA

TGGTTACATTA

TGATTCTGGAA

CGTTCG

580.
Mm.30241
Chromosome 8
TCCAGACTTCT

CAGAGACAAG

GATCTTGCCTT

ATTTTCAAATG

GTGCTAAATTT

AAATTC

581.
Mm.9772
Chromosome 14
AGTGACTTCCA

CCTTTTAATGT

CATTAAAAGCA

GGAGCTTAAAC

TAAAAGCAGC

ATTCCA

582.
Mm.2241
Chromosome 6
ACATACATTTC

ATCACCAATAT

GTTTTATCTTA

CCCCATCTCTC

AGAGTGTTCCC

TGCAA

583.
Mm.21657
Chromosome 4
TTTTTTGTATT

ATTGTGTTTTG

TGCTACTGTAG

TTTTGGTGTGG

CACTATTATAA

TTAAA

584.
Mm.40298
Chromosome 15
CTTAGGGAGAC

TACTAACATGG

AGAGAATGCC

GTGTATACCTC

ACGTACTGTGT

GCTTTA

585.
Mm.3845
Chromosome 18
CATACATAGAA

GCAAAATACTT

TAACTGCTGTA

AACCTTCAAAA

GTTAGTAGACG

TGAGG

586.
Mm.45759
Chromosome 10
ACTTCCTGCAA

TACATCCCAGT

AGGTACACCTA

GTTTACAATTT

AAACTAGTTTG

TGAAA

587.
Mm.34557
Chromosome 10
GGAGGCACAT

AATTCCAAGCA

ATACAGGCTGT

TAAAATATAAA

TAATGGGAACT

GTGATT

588.
Mm.221706
Chromosome 1
AAGCGTTAGG

AAGGAAATTTC

CTGGAAGGAT

AGGTTGTCTTC

CTAGCAGCCTC

GTCAATA

589.
Mm.24807
Chromosome 3
TTTTTTAACTT

CACTCATGACA

ACAGAGGAAG

AAAGGAATTG

AGGTTTAGGTA

AGTTCTC

590.
Mm.24045
Chromosome 12
AGGCATATCTC

ATAGAGCCTTA

AGTTAGAATCT

TACTCTTATGG

AAGGAGTTATT

TCCTA

591.
Mm.34027
Chromosome 1
GATCACCTCAT

TCCTCGACTGT

GAGATGAGTTT

ATGAAAAGAA

TTAAAAGTGAG

CACTTG

592.
Mm.6404
Chromosome 5
TAAAGGTAACT

CCATCAAGATG

AGAAGCCTTCC

GAGACTTTGTA

ATTAAATGAAC

CAAAA

593.
Mm.8155
Chromosome 17
GGCCAGGTATA

TGTGTACCAGT

GCTCTTCAAAG

GGAGAACCATT

AAAACCAACA

TGGAAT

594.
Mm.2793
Chromosome 9
CCAAGAGATTA

TTTAACATTTT

ATTTAATTAAG

GGGTAGGAAA

ATGAATGGGCT

GGTCCC

595.
Mm.118
Chromosome 8
AGTGAACGAA

AAAGACACCTT

AACATGTTTCA

TCTACTCAGTG

AGGAACGACA

AGAACAA

596.
Mm.8040
Chromosome 12
GATATTTATTG

AGTGTCAAATA

AAAAGGTGCC

ATAATCTTCAG

TAGCGTACACA

GTAGAG

597.
Mm.200608
Chromosome 14
GTGTTACCAGA

AGAAGTCTCTA

AGGATAACCCT

AAGTTTATGGA

CACAGTGGCG

GAGAAG

598.
Mm.29101
Chromosome 6
TGTCTTTATTTT

AATGCCAAAA

GGAAGTGATTA

TGCAGCTGTGT

GTAGAGTTTCA

GAGCA

599.
Mm.201248
Chromosome 1
AGAACAAACT

GGAATTTTATT

CTGAAGCTTGC

TTTAAAGACAC

TGATGTGCCTA

AACGCT

600.
Mm.20156
Chromosome 2
TATGGTCTTTC

CAAGGAAACT

AGTCACAGTGT

CATCTTAATCT

TACTGATCCAA

TAAAAC

601.
Mm.248334
Chromosome 15
ATCCTCCTGAT

TGGTCTGAATG

CATTTCCAATG

ATGTCAGGGA

GTCTGCCTTCC

TCAGCC

602.
Mm.259704
Chromosome 13
TAAGCCCTGTC

TTCTGGGAAAT

ATCAGTTTTAA

AGAGAACTTTT

GTGCAATTCCA

AATGA

603.
Mm.29771
No Chromosome location
GGAAGATTAAT

info available
TTTCCAGGGAT

TGTATCAATCA

GGACCATTTTT

GTGGGGCACTT

GGGAC

604.
Mm.21440
Chromosome 2
ATGTGATCTAC

AGTGGTGTGAC

AACTTGCCTTG

TATCTGATGGA

CTGTCCAGATT

TATGG

605.
Mm.29975
Chromosome 2
AAACGAAGTG

ACTTTCCATGA

ATGCCTTTAAC

ATTCTTGTGTC

AACATTTGGTA

CTAAAC

606.
Mm.17580
Chromosome 13
AATACTCATTA

TGCTGTGTGGG

AATTTCCTGAT

TACTAGAAGCT

GACCTCTGCTA

TCCTG

607.
Mm.2018
Chromosome 8
GAATTATTATA

AACAATAATGT

GTTACAGAAGC

TGATGCTGACC

TTGTGTTACTG

AGCAC

608.
Mm.14627
Chromosome 9
TTCTTGAGGTT

TAAGGACGAC

AACTTTATGGA

CCCTGAATGGA

AACTGAGGAA

TCACAAG

609.
Mm.86611
Chromosome 5
GTCACATGCCA

ATAAAAACAG

GAAACTCTGAA

AATAATATGAA

TGTACAGTATC

AGACCG

610.
Mm.252080
No Chromosome location
CCCTATTGCAA

info available
ATTGATTTGTT

TTCCCTTAACC

CTGTTCCCTTT

TAACCCCGGCT

TTTTT

611.
Mm.25264
Chromosome 10
CATTGCATCGT

TTTCCAACATA

CTTTTAGATTT

ACAAAGTAAA

ACCAACCATGG

ATCTGC

612.
Mm.173217
Chromosome 17
TTGAGAAATTA

AAAACAAATA

TCCAAAATCGA

CTTTTCCTCAA

GGCTATGTGCT

TCGTCC

613.
Mm.105182
Chromosome 5
ACGACTCTTGT

TAATGTGCGTT

TCTCATGGAGT

AATTTTCAGAG

CCTGAACTTGT

AGCAC

614.
Mm.3596
Chromosome 2
GTTGGTGTGTC

CTGAAAGGGA

TGGAGTTATGG

CAGAAGTGCTT

TTGTGATCAAC

TGGTTT

615.
Mm.143818
Chromosome 2
CAGAAAACTC

AAGTCATGGAC

TATGCGAGTCA

AGAATTAAAAT

ACAACTGTATT

ATGTGC

616.
Mm.4587
Chromosome Multiple
AAATTTCTCAT

Mappings
TTAATTTTCCA

GTCTCGATTGC

AGTAACAAAG

TCAACCACACA

GTCAGA

617.
Mm.5236
Chromosome 2
GGAGGAAGAC

AACTGAACATT

TGTATAAAACG

TAAAAAGTTTA

CTGATTGGGGT

GGGACA

618.
Mm.31402
Chromosome 16
CAGCAGCTTAC

AAACACTGAA

GTTAGGCGACT

AGAGAAAAAC

GTTAAAGAGGT

ATTAGAA

619.
Mm.68134
Chromosome 14
GAGAAATGTTA

GTAAAATGGTA

AAAGGGAATC

ACGTGACATTC

AGGGTAGGAA

GAGCTTG

620.
Mm.180776
Chromosome 3
TCAGGAAAAA

TGTCATAAGCC

ATCTGGTAAGT

TTTCTTAAAGG

ATGTTGTTAAG

AAGTCC

621.
Data not found
No Chromosome location
CAAAACAAAT

info available
ACATATTATAA

AATAAAAGAA

AAGGCGTGAT

AAATGGATGTG

ACAAAATT

622.
Mm.265969
Chromosome 15
GTAGGGAAAA

TATGTCCATAG

GTTTTAGGAAA

CACTTAGCCTT

TAATATACTGG

TTGTAG

623.
Mm.26430
Chromosome 4
GTATACAGATG

GTAGTTAGAAA

TACTGGATGAA

CTGATCAGTTA

TTGTGTGTAGA

AAGTG

624.
Mm.171547
Chromosome 4
TTGTATCCCAA

AGGGAAACGG

GAATCAAGAT

ACGGACCTATG

CTTTTCATATG

AAACCGT

625.
Mm.4639
Chromosome 16
TGCAGCTAAGG

TACATTTGTAG

AAAAGACATTT

CCGACAGACTT

TTGTAGATAAG

AGGAA

626.
Mm.31530
Chromosome 6
GGCAATGGAA

AATGTTGAAAT

CCATTCAGTTT

CCATGTTAGCT

AAATTACTGTA

AGATCC

627.
Mm.28867
Chromosome 1
CCCCAAAGAA

AACTGGAAAA

ATTGTTTTCCA

CTCCTGAAATT

TCTTGGATGGG

CCCCCTG

628.
Mm.181004
Chromosome 5
CCAGACAGTGT

ATTCTTCGGAC

AAATGGTGTGA

AAGTGAAATA

AGAATTCATAA

TGTAAC

629.
Mm.179011
Chromosome 2
AGCAAAAGTA

TGTATATTTTA

GCTTGTCATGA

AATGTCAACGA

AGGACACTGA

GAAAGAG

630.
Mm.212874
Chromosome 6
TAGAATGGGA

ATTTTCTGTCT

CATAGTGACAT

ATTGCTATGTT

TAACAGTGAAC

ACTCAC

631.
Mm.254904
Chromosome X
TGACGGTATAT

TTGCAAAAAG

AGAAAGAAAA

ATCTGGTATTT

GCAATGATCTG

TGCCTTC

632.
Mm.86150
Chromosome 16
GAAATATCATT

TGTAGCTTTAA

GGCTAGAAAA

TGAAAAAGAA

TCCAAGCCAGT

AGAAGGC

633.
Mm.275985
Chromosome 8
ATACCAGGAA

AATAAAAGTA

CCAGTAAGGA

AGCATCAAATC

AAGATGTCATA

GTCAGTGG

634.
Mm.17827
Chromosome 3
CAGTGTAAATA

TAGCATATGGT

TAGGTGGTGAG

AAAATGATCTT

GAGACTGATA

AGAATC

635.
Mm.86385
Chromosome 3
ATCCTTTAGAT

GTTAGTACAGT

GTTTATGAGAA

AACTGTTACTA

GAAGCTGAAG

AACAGC

636.
Mm.2655
Chromosome 17
AGTGTTCTATA

TGTGTAAATTA

GTATTTTCAAC

TGGAAAATGTT

GGCTGGTGCAA

AAGGC

637.
Mm.188851
Chromosome Multiple
GTCTGGGCTAG

Mappings
TGCCCGTTTTT

AACCCTACCCA

TTGATCATTTC

AAGAAACCTCT

GGTTA

638.
Mm.228682
Chromosome 16
TGTAAGACCAT

TTCTAAATTGC

TGGTAATAGAA

ACTCATGGCAG

TAAAAATGTAA

CCTCG

639.
Mm.2992
Chromosome 18
ACTGGAATAG

GAATGTGATGG

GCGTCGCACCC

TCTGTAAATGT

GGGAATGTTTG

TAACTT

640.
Mm.28580
Chromosome X
TCTACTAGAAG

GGTTAAAAGCC

ATATGAATGCA

AGAAATCATTT

GAGGCTTAAA

ATGCTG

641.
Mm.62886
Chromosome 8
GGACACCATTT

TTCATGTTAAA

TAGATTTTAAC

CTCGTATCTAT

GCATAGGCTAA

GGTGG

642.
Mm.65363
Chromosome 2
TAGATAAAGCC

CGTATGAGAA

GAGAAAACCA

AATTAATCCAC

TTCAGCAAAAA

GAAAGCC

643.
Mm.22288
Chromosome 7
CAATGTCAGAC

TGCCATGTTCA

AGTTTTAATTT

CCTCATAGAGT

GTATTTACAGA

TGCCC

644.

No Chromosome location
CTTTGGGGGGG

info available
GTTTTGGAAAA

CCGGTTTTTTC

GGGGGGGTTTC

CTTTTGGGGGG

TTTTT

645.
Mm.283461
No Chromosome location
GCCATACAGCT

info available
TATATTTGTAC

TGGTATGTCCA

GAAATCATGG

AGGAAAGAAA

AGTAAAA

646.
Mm.143724
Chromosome X
TGGTGTTTTGA

TTACAGTGAGA

CATCACAGGTT

ATCTAAAAGCC

CTTCGTTATAA

CCAGC

647.
Mm.217092
Chromosome 3: not placed
TATTTGGTGGT

AAAGAATATG

GTTGAAAATTG

TCATCCACATG

CATGCATCAAG

TAACAC

648.
Mm.87062
Chromosome 6
CGAGGAGTTAT

TAGGGAGAAT

CATGGAGCCAC

ATAAGAAAAT

CTTGGGCAAGA

AAAGAGG

649.
Mm.21126
Chromosome 1
TGGTGACAGG

ATTACGTGAAA

ATCTCTGACAT

TGTGATAAACT

CGATAAAGGCT

TAAGAG

650.
Mm.11778
Chromosome 1
ACCCTTTGCTT

AAATAGTGGG

AAAACGTGAA

TGTTTAGCATA

ATATAAAAAC

ATGCAGGC

651.
Mm.261448
Chromosome 14
GTTGGACTCTA

ATACAACTGAC

CATTGAAAAAT

GAACAACGGC

TTATTGTTTTG

TAACAG

652.
Mm.250414
Chromosome 7
TTCCTACAAAG

TGTGTTTCTAT

AGGATTACTAG

AGTAGCGGTTT

TGTACTGTGAG

GAAAC

653.
Mm.33764
No Chromosome location
TAGATAACAGT

info available
GACTATTGACG

ATTTTAGTAAA

AGAAAGTTGA

CATGCGTACCG

CTACCT

654.
Mm.27579
Chromosome X
GGGGGGACAG

TTAATATCGTT

TGTTAGATACC

ATAAGTGGTGG

AAATAAAGTG

ACTAAAG

655.
Mm.71633
Chromosome 13
AAAGAGGAAA

CTGTCCTATTT

CTCAACTGATA

AGTACTCCTGG

TAAGATGTAAT

ATTTGC

656.
Mm.173983
Chromosome Un: not
CAAATGTACTG

placed
AGAAACAAAA

TCATGAACGAC

CTTGAAATCAC

CTTCTTATTTC

AGCTCC

657.
Mm.117055
Chromosome 5
AACATAAATCA

AAATATACTTA

GGAATATTTAC

AATTAAACATG

ATGTTTTAAAC

TTAGT

658.
Mm.141083
Chromosome 2
GACTATTTATT

AGATTAGAAA

GTCATGTTTCA

CTCGTCAACTG

AGCCAAATGTC

TCTGTG

659.
Mm.198119
Chromosome 1
ACAAACACAT

GAAAAAATCA

AGTAGGAACT

GGAGAAACGT

CTCACAGTTAA

GAATGTTTG

660.
Mm.6156
Chromosome 5
AATTCACAGAT

GGCTTACATTT

ATGTAAAGAAT

TCCTGTAAGGC

ACTCATGTTTG

ACATC

661.
Mm.6456
Chromosome 5
TATACCAAACT

GAAAACGTTTA

AATCTCAAATG

AAGTAAGCAA

GGTTTTGTTCT

CCCTGC

662.
Mm.30015
Chromosome 4
TAGCCATTTAG

GAGATGTCCCT

TCAAAGTGACG

TGATGATGGAC

TTGCACTTGGG

AATCA

663.
Mm.31079
No Chromosome location
GCTCAGCTTAG

info available
GCTAGACTTTG

ACCAGGTAAG

CAGAAGAAAT

GAGAAACAAA

ACTCAGCA

664.
Mm.295618
Chromosome X
TATCACTGGAA

TATTGAAAGGT

TGTATGTAGTA

TGGGAGATCA

ACTTTCTTCCC

TAAGGT

665.
Mm.171323
Chromosome 4
ACTGCTGAGAA

AAACAAAATTC

ACTACATACCT

CAATAGTTATT

TACCATGAGAT

TGGCG

666.
Mm.173106
Chromosome 1
GAAGGAAATG

CAAACACCTTT

GAACTTCAATT

CTTTCAGTAGG

AAAACAAGAA

TTGTCCC

667.
Mm.206737
Chromosome 1
AGAAAAACAC

TAAACTCCAAA

TTAGTATAATA

ACGAGCACTAC

AGTGGTGAAA

AAGCTCC

668.
Mm.19945
Chromosome 14
AAAGGAATCTT

AAGAGTGTAC

ATTTGGAGGTG

GAAAGATTGTT

CAGTTTACCCT

AAAGAC

669.
Mm.182061
Chromosome 11
GAAATGGATTT

TGAGGCTTTGA

AAATGAAAAT

GGCTAGTATCT

CAAAGATGTCA

GTATCC

670.
Mm.265618
Chromosome 14
ACTATTTCTTG

TCAATAGTTTG

GCAAAAGACG

ACTAATTGCAC

TGTATATTGCC

AGTGTA

671.
Mm.22687
Chromosome 7
TCCTCTAAAGA

TGTGTCTTATA

TACATGATTGT

CATTGGTGGGC

TCAAACAATAA

GGGTG

672.
Mm.56769
Chromosome 10
TTGGAAACTAC

AAGTAACCCTC

AGACGGCCTA

ATTCTTATAAT

CCGGAAAAAC

ACCCCAA

673.
Mm.34356
Chromosome 8
GTGTGATAATC

TTTTCATGTTTT

CTAGAGCAAA

GACAAAGCAG

TTACTCTTCTA

TCGCAA

674.
Mm.34510
Chromosome 3
GGCTTTAGAGA

AAACTTCGGTC

TTCAAAGAACT

CTTCTAATTAG

TTCCTTCTTGG

AAAAA

675.
Mm.4664
Chromosome 4
AAAGTAGGAG

ATGAGATTTAC

ATTTCCCCAAT

ATTTTCTTCAA

CTCAGAAGAC

GAGACTG

676.
Mm.24730
Chromosome 2
AGTCCTCTGCA

TGTTTCCAAAA

TTTCCTTTACA

TGAAGGCTATA

TTGGATCAGAG

CTTAC

677.
Mm.159840
Chromosome 5
AAGAATAAAT

CACTTGAAATC

ATACTGTTTTT

GGAAATCCAA

ACTGTTTAAAG

AAAACTT

678.
Mm.291487
Chromosome 6
GTTAGATGCCA

TTGAAGGGGA

AATAACTTTGG

CTAATAGCTTG

GAAAACTCAGT

ACTAAG

679.
Mm.73777
Chromosome 18
AGCAGATATGT

GACTTCTCATA

TACACAGTTAC

GCTAACTCAGG

TGTATGATGAA

TACAG

680.
Mm.221709
Chromosome 19
TGTCTATGGGA

GAAGTAATAG

CCTGAAATAAG

ATAAGGCTCAA

ACAAACACTAC

TTACTT

681.
Mm.259122
Chromosome 5
GGGAAGAAAA

AGAATTGGTCG

GAAGATGTTCA

GGTTTTTCGAG

TTTTTTCTAGA

TTTACA

682.
Mm.218530
Chromosome 11
CTTGAAGAAA

AGTATATCACG

TAGGCATAGAT

GAGAAAGCCG

TTTGATCAAGT

CTGGTTA

683.
Mm.108076
Chromosome 13
TCCTTCAGTCA

GATATCTGTCC

CAGAGAAAGG

AAAATAAGGA

GCATGGTAAG

AAATGAGT

684.
Mm.204920
Chromosome 13
TATGGAATGGA

GAAATAAATA

CATCTGTGTTG

AAGAACCTTTT

GATGGAACTA

ATACCGC

685.
Mm.162073
Chromosome 6
AGGTCAATGTT

AAGTTTTCTGA

GTTTAATATAT

AGTTAGGGTGA

AAGACTTAGCA

CACGG

686.
Data not found
No Chromosome location
AATGCTTAACT

info available
TTGAGTCACAC

TGTTTACCCTT

CCTATGAGGTT

GCATTTTGACA

ACAAC

687.
Mm.248267
Chromosome 18
TAAAGGGAAC

CCCCATTTCTG

ACCCATTAGTA

GTCTTGAATGT

GGGGCTCTGAG

ATAAAG

688.
Mm.20847
No Chromosome location
CCCCTTTTTGT

info available
AACTGGGATAT

AAATCCTTGAA

AGAAAGGAGA

ATTTAGAGTTT

TGCCCC

689.
Mm.200366
Chromosome 5
GTCAGTGAGTT

GGTTTCCTTTC

CATCAGGAAA

AATGGATTCTG

TAAAGAGTCA

GGGCGTT

690.
Mm.28835
Chromosome 8
GAAAGCCGTC

AGCGAAAGTTT

TCTCGTGACCC

GTTGAATCTGA

TCCAAACCAGG

AAATAT

691.
Mm.25148
Chromosome X
GAAATATGTTA

ACTAAGAGCA

GCCCAAAAAT

ACTGGATATGC

TTATCCAATCG

CTTAGTT

692.
Mm.10760
Chromosome 15
GTATACAATGC

TATTTTTAGGT

TAAGGCCTAAA

CTTCTGAAGAT

CTTGGTAACAG

CAGAG

693.
Mm.89961
Chromosome 13
GGATGAAGTG

GAAGATTACTG

GCAGGTCCAA

AAACCTGATTT

TCTAGTACATT

TCACTCT

694.
Mm.8655
Chromosome 1
TTCAATCAAGA

AAGTAGATGTA

AGTTCTTCAAC

ATCTGTTTCTA

TTCAGAACTTT

CTCAG

695.
Mm.28890
No Chromosome location
AAATTTTCTTA

info available
AAGCTATGAAC

TCTGACTTTTG

ATTTTGTGTTT

CCATTTAGTAG

AAACT

696.
Mm.3368
Chromosome 13
AGAATCTCACT

ACTAAAGTCAA

GTATAGAAATA

ACTGTTCTTAT

GTTTTCCTCCA

AGGCC

697.
Mm.143689
Chromosome X
ATCTTTGGCTA

TATTTTCCTGG

TAGCATATGAC

AAATGTTTCTA

CAGTGAGAAG

CTGAGA

698.
Mm.27385
Chromosome 15
GGGTTATAATG

CACTGAGATCC

AGAAGTTGGG

AAAACTCAATA

AATGTACAAA

GGAAAGC

699.
Mm.171399
Chromosome 1
TACTTGTGTGA

CAAGCTAGAG

AAGTTACAGA

AGAGAAATGA

CGAACTAGAA

GAGCAATGC

700.
Mm.4554
Chromosome 4
TAAATAATCCC

TTCCCATGAGC

CCACTGCTCTG

AATGGACAAG

CTGTCCTTATC

TTCAAT

701.
Mm.27800
Chromosome 18
AAATAGTTGTT

TTTAAGGTTGA

AGGAAGAGAC

ATTCCGATAGT

TCACAGAGTAA

TCAAGG

702.
Mm.268027
Chromosome 2
TGAATCTACAG

GCAACTCTTCA

TCTCTGTAATG

CTACCTGACTT

CTCTTGTGAGG

AGCTG

703.
Mm.103300
Chromosome 14
TGGCAAAGAG

TAGATGAGAA

AATGTTGGATT

TAAATCAGCAG

ACTCATTTCAT

ACTTTGC

704.
Mm.22194
Chromosome 10
ACCACGTTTAA

ATGACCAGTCT

CAGGATAAAG

AGTTTTACAGA

AAATTTAAAAT

GCCTGG

705.
Mm.29820
Chromosome 14
GACATCGTTTT

CTCTCTAAATT

CAGTAGCAGTT

TCATCGACAGT

GCCATTGAACT

ATGGG

706.
Mm.4859
Chromosome 4
TCTGTGGGGTT

CTCATGCCAGT

GTCTGAAATCT

CACCTCACTAG

AGATGTTTCTC

GAATT

707.
Mm.30111
Chromosome 11
TTCCAGTTCTC

ATGTCTTGAGA

TTTCAAGTAAA

GATGTGTTAGT

GTAAGCTCAGA

TCCGA

708.
Mm.37770
Chromosome 14
AACCATTGGGA

AAATGCAATAC

AGATAAACTA

GAGATTCGTAT

AATGCCACGTG

TTAGCT

709.
Mm.447
Chromosome 1
GTGAATGGAGT

GTTTACTGTAT

GTAAGAAAGA

AGAAAAGTGG

AACTACATTTG

CTATGAG

710.
Mm.182857
Chromosome 5
TTCACAATTTA

GACACAAGATT

TGGAAGATTGA

AACTGACATGA

AAGTCTTCTTC

CTGAG

711.
Mm.2277
Chromosome Multiple
GAAGATTTTTT

Mappings
GATGTATAAAA

GTGGCGTCTAC

TCCAGTAAATC

CTGTCATAAAA

CTCCA

712.
Mm.27436
Chromosome 15
AGAATGAACC

AGAATGGAGA

AAACGTAAAA

TTTGAAGAATC

TCGTTGAAGAG

CTATTTGC

713.
Mm.133824
Chromosome 10
TCGACAAGAG

GTAATCCGAGA

AATGGAGCAG

AAAACCTCCTT

GCACTTCAGTG

ATATACA

714.
Mm.27829
Chromosome 4
TATATGCAACT

TCATAGATCCT

CTGCAATATGT

ACTTAGCTACC

TAAGCATGAA

ATAGAC

715.
Mm.34674
Chromosome 19
CGTCATATATC

CTATTTGTAAT

CAAGAGGAAA

GACTACATTAA

GAAGATAGGG

TGCATAG

716.
Mm.4481
Chromosome 6
CTCAGATCAGT

TCTTTAGAAAG

AGCTGGTATAG

AAATGGGTGAT

GTAAAACTTGA

GAAGC

717.
Mm.203928
Chromosome 19
AATGAAAATCT

GCGTCTAACTT

TTGAAAGTAAG

TGTTAACTTAC

TTGAATGCTGG

TTCCC

718.
Mm.214553
Chromosome 15
AATCTTCGACC

AGACATTGGAT

ATTTGAACTAT

CCTGAAACATT

TTAGAAATATC

CAGGC

719.
Mm.22370
Chromosome 8
TACCCCATTAA

AGGCATCAAAT

CCGGGTTTAGA

TCAGTCCCTCT

GAAGAATGGG

TACAGT

720.
Mm.4462
Chromosome 15
TTTTTTCTCTTG

CCAATGTATTT

TTGTAAGGCTC

GTAAATAAATT

ATTTTGAACAA

AACA

721.
Mm.18635
Chromosome 7
CACACCCTCTG

ATGTTCCAAAA

GCTCCAGGACC

AGATCTTCAAT

CTCATGAAGTA

TGACA

722.
Mm.162929
Chromosome 19
CCCAGGTATTT

CTAAGCATGCT

AGGTTTGAGGT

CATTTACCATG

TTCAAATAAAA

GACGG

723.
Mm.255070
Chromosome 9
GGAGCAAAAC

TTGAATAATGT

CCTTTATCCTG

ATTTGAAATAA

TCACGTCATCT

TTCTGC

724.
Mm.173654
Chromosome X
TGGAATAAGA

AAGAATCTGTG

GTAGAAATAAT

AGACTTGCTAC

ATAGGGTTAGC

TAAGGC

725.
Mm.30664
Chromosome 11
ACCACAGTTTA

TCAGCATTTGA

AGATTTCCTTG

ATGATCCATAC

TTGTCTTGGGA

TAGGG

726.
Mm.788
Chromosome 15
AGGGTCAGCG

CCGAATCTTGT

GGACACACTG

ACAAGGATGTC

TAATCCAAATA

GATGTAT

727.
Mm.248907
Chromosome 9
AGTGGAGTATT

CAGTCTGGAGT

TTCAGGATTTT

GTGAATAAATG

CTTAATAAAGA

ACCCT

728.
Mm.34399
Chromosome 4
TTTGGGCCCTT

AAAAACATATT

TCAGTTTTGCC

CAAGTGAGGC

CTTAAAAATTG

CCCATG

729.
Mm.424
Chromosome Multiple
AAAGGAAAAT

Mappings
AAAGTGGATCT

GAAAGTAGAC

TCTGCTTCTGC

GCATGTGTGAG

TGGTGCC

730.
Mm.259278
Chromosome Multiple
TTCACTCCTGG

Mappings
ACTGTGATTTT

CAGTGGGAGA

TGGAAATTTTT

CAGAGAACTG

AACTGTG

731.
Mm.219676
Chromosome 2
CACCATCCTTC

CAGAATATGGT

ATGAAAAATCT

ATGCAAACTGT

GTAAGCTTTTG

CTCAT

732.
Mm.145306
Chromosome 12
TTGTGGAGTGT

GAAATAAAGG

ATAATTGCCTA

CCTCTAGCAAG

TGGATCTTATT

ATGTTG

733.
Mm.22564
Chromosome 17
ACCAGAAAGG

ACAGTCTGGAC

TTCAGCCAACA

GGACTCCTGAG

CTGAGATGAA

GTAACAA

734.
Mm.274876
Chromosome 7
GATACTGCCGG

CTTTGAAAATG

AAGAACAGAA

GCTAAAATTCC

TGAAGCTTATG

GGTGGC

735.
Mm.205421
Chromosome 14
CCATTTGAGCC

TCACTGCAATG

TTAGTGCAGAG

GAGAAAACAA

TTTTTAATGTA

ATCTTG

736.
Mm.268911
Chromosome 1
GGCAACTTGTA

AAGTGTGTTCA

TTCTAACTGTT

AAACTGAGAA

AACTTGAGAAC

ATACTG

737.
Mm.269064
Chromosome 14
CAGAAGAGAT

TCTGAAAATGT

TAGTTGTGGTG

ACTCTAATGTA

GATCCATAACT

GAAAAG

738.
Mm.218665
Chromosome 15
TATCGTAAGTT

GCACCTATTGT

TAAGTGGAAA

ATGCTCTGATT

ACACTCAGGA

AGCTGGG

739.
Mm.21450
Chromosome 5
TGTTTTGTCCC

TAAATCACCAC

CACTCACTATT

TCTCCCAGGGT

CTGATAATGCC

TTTAC

740.
Mm.28908
Chromosome 8
AGCCACTTTAA

CTCTAAACTCG

AATTTCAAAGC

CTTGAGTGAAG

TCCTCTAGAAT

GTTTA

741.
Mm.259295
Chromosome 17
GCTTTGTTTAA

ATGGTCAGACT

CCCAAACATTG

GAGCCTTTTGA

ATGTGTTCTGA

GACCT

742.
Mm.154623
Chromosome 18
CCTTAGAAAGA

TGGTAATTCAC

TTTAGGTAAAA

GTACTATTTCA

CGCCATTATGA

AACCC

743.
Mm.29628
Chromosome 19
TAAAATGAGG

CTTTTGGAAAG

AAAGATGAAA

ACGTAGAATGT

AGTGCTAAGA

ACGTTTCC

744.
Mm.163
Chromosome 2
GCAGTTACTCA

TCTTTGGTCTA

TCACAACATAA

GTGACATACTT

TCCTTTTGGTA

AAGCA

745.
Mm.6272
Chromosome 9
TGCTTAGAACT

ACATAGAATCA

GAAGCAAAAT

GGATGCCTTAG

CACTGAGGAA

AGGTTTC

746.
Mm.70065
Chromosome 10
GGTTTTCGAAC

CACGTACCTTT

ATGCCTCGTGA

TTGTGAAACAT

TGACTTTTGTA

AACCC

747.
Mm.21579
Chromosome 13
GTTCACTGTAG

AAATTTGTGAT

AAGAAAGACA

CACAGACGTA

GAAAATGAGA

ATACTTGC

748.
Mm.21138
Chromosome 14
AAAGACTTTTT

TGGACTTAATA

CTGATTCTGTG

AAAACTGAAG

AAGTGTAGATG

TCTCCC

749.
Mm.486
Chromosome X
CTGGTGTGGGA

TATTTTCCACA

CTTTAGAATTT

GTATAAGAAA

CTGGTCCATGT

AAGTAC

750.
Mm.247440
Chromosome X
TAAAGGTTTTA

GTGTCCTAACT

CCCCAGGATCA

GGAGATTATCC

CAACTATTTCT

GGGGT

751.
Mm.34462
Chromosome 5
CTGAATTTTGA

TCACTTGTGGT

TTCTCATGGTG

ACCTCCATTTG

CAACAAAAAG

ATGTCT

752.
Mm.154684
Chromosome 2
TGTGCTTTACC

AAAATGGGAA

ATAATTCTGCT

TTAGAGGATAC

TATCAAGACAA

CCTTAC

753.
Mm.30251
Chromosome 17
TCTGTGAGATG

TTGTAGACATT

CCGTAAGAGA

ATCCAGAATGA

TAGCAGGATCA

GGAAAG

754.
Mm.243085
Chromosome 6
CTTACATGATC

TCCTAAAAGGA

TGGGCCCCTCC

TTCCTTTTGCG

GGTTGAAAGTA

ATGAA

755.
Mm.41525
Chromosome 10
CTGTTTAAAAA

ATGAAATCAG

GAAGCTTGAA

GAAGACGATC

AGACGAAAGA

CATTTGAGC

756.
Mm.45563
Chromosome 1
TGAATATAGTA

GGGCCATGAGT

ATATAAAATCT

ATCCAGTCAAA

ATGGCTAGAAT

TGTGC

757.
Mm.221705
Chromosome 19
GGGGGAAATT

CTATATGAGCT

TCGTTTTCTAA

TGACTTACATG

GATAGTATGGA

AACTTC

758.
Mm.19142
Chromosome Multiple
AAACTTGAAA

Mappings
ACACAGACATT

GAAGGAATCA

TAGGTATTTTT

GCTTTATGCTC

TCTGGCA

759.
Mm.139860
Chromosome 16
AATAAGCAGG

AAGAATTTGAC

TTGGAAAACTA

ATACACGCATG

TTAGGCATTCT

CAAGGC

760.
Mm.200936
Chromosome 5
TCCCACTGTTT

ACAGATGTAGT

TCTTGTGCACA

GGTGCCACTAG

CTGGTACCCTA

GGCCT

761.
Mm.37562
Chromosome 7
TATTTTTGTCA

TTGCCTCTAGT

GATTTTTGTAA

ATGGGAATGG

AAAAGTACAA

GGCAACC

762.
Mm.35600
Chromosome 9
TTAACTGGCCT

GTCAAACTGGT

CTTGAAGCGTC

TCTAAGTGAAG

AGCCAGAAGA

AACCCT

763.
Mm.213128
Chromosome 9
CAATGTGATTT

TTCAATGGTAT

TAGTTCAAATT

GACGTGGATTC

ATGCCACATGG

AAATC

764.
Mm.46501
Chromosome 12
AACTGAATAA

AGTTGACCAGA

AAGTGAAAGT

CTTTAACATGG

ATGGAAAAGA

CTTCATCC

765.
Mm.227202
Chromosome 3
GGATATAAAGT

GTATTTCTTTC

AGTGATTTCTC

AGTGCATAAG

AAGTGCATAA

GTCTCAG

766.
Mm.43444
Chromosome 6
TAGCTTTTTAA

AAGAAGTTTTT

CTACCTACAGT

GACCATTGTTA

AAGGAATCCAT

CCCAC

767.
Mm.248456
Chromosome 13
ATTTGCAAGGT

CAGAAACTAG

CCAAGGTCCTT

CTCAGGCATCT

ATCCTTAACTT

GGTCTC

768.
Mm.30103
Chromosome 11
TTGGAATTTGA

GGAGGAGAAA

TGAAAAAACA

GTGTGTCCCTG

GTGTCACCCTG

GCATCAT

769.
Data not found
Chromosome 10
TCTTATGATTT

AAGTGATTGGT

GGATAAATGTA

TAGGAATTTTA

CACTCCAGCAG

CATGG

770.
Mm.26658
Chromosome 9
GCCTCAAATGG

AACCACAAGT

GGTGTGTGTTT

TCATCCTAATA

AAAAGTCAGG

TGTTTTG

771.
Mm.34702
Chromosome 8
CCGTACACAAA

AGTGAAGATTT

CAGCGAAATG

CCAAGGAAGT

GCCATCTATCT

GGCTTCT

772.
Mm.2433
Chromosome 17
AAGAAAATGC

TGTATGATGTT

AGAAGACATT

GTAATTATCAT

CCCGTGTCTTT

GCTGTAC

773.
Mm.270044
Chromosome 8
GGCATTTCAGT

TTATCTTGGGT

TTGTAATTAGT

TAAAACAAAA

ACCAACCTAGG

TCTGTG

774.
Mm.268014
Chromosome 10
ATTAGCCAAGG

AGTCCGGACAT

AATATTTATCC

AGATCTCTAAG

CAGTTAGCTTT

AAATT

775.
Mm.549
Chromosome 10
TACATTAGCTA

ATACTAACCAC

ATAGAATATCA

GACTTAGATAC

GTGAATAGGG

ATCCTG

776.
Mm.276062
Chromosome 4
AAGATTTTCTA

GTCACTGCATA

AAGGAAACGC

CTAAGAGTTGC

CGTATTGCTTT

CTGAGA

777.
Mm.26939
Chromosome 3
ACAAGAATTCA

TTCTTAACATT

TGAACGAGTGT

ATTTGCTTAGG

TCGATGAAAGT

GTTGC

778.
Mm.247480
Chromosome X
AGGATTTTCTC

ATGAAGAACC

AGATGACATGT

GGTAATAACAT

TAGCTGTCTAG

TTTCTC

779.
Mm.182877
Chromosome 1
TAGAGTCATGA

AGAACAGAAA

TTCAAGGTCAT

TTTCAATTACA

GAGTGAGGTTA

GAGCCA

780.
Mm.121973
Chromosome 15
TCTAAAACATG

CCAAATGACTT

ATGTCACAAAG

AATAGGTCCTA

ATATACTGTAT

ACCCC

781.
Mm.139738
Chromosome 13
GTGTTTCTTCC

CATTTGTAAAT

GTCCTGAACCA

TAAATTACTAT

CAGGATTAACT

GACAG

782.
Mm.27969
Chromosome 1
GAAGCTGGAA

GCATTTGTTTT

TGAAGTTGTAC

ATATTGATAAG

TCAGCGTATGT

GTCAGA

783.
Mm.222307
Chromosome 2
TTACATGGCAA

ATCTGAAAGG

AAGACTTAAGC

AGGGTAAAGTT

AATTGAAAGG

AGGAGCT

784.
Mm.1258
Chromosome 6
AGCAATCTTTG

TATCAATTATA

TCACACTAATG

GATGAACTGTG

TAAGGTAAGG

ACAAGC

785.
Mm.24933
Chromosome 1
GGTGTATGGAA

ATAAAGTTTAG

TCAATGTTGAA

AATCTCTCCTG

GTTGAATGACT

TGCTC

786.
Mm.1940
Chromosome 15
CTTTCAGTCTC

CTTCTGTGTCT

CGAACCTTGAA

CAGGATGTGAT

AACTTTTCTAG

ACCAC

787.
Mm.215584
Chromosome 2
GACTGTTTCTG

GGAAAATAAG

TATGTGAAGTG

ATGCAGAAAA

TCCATCTAGAC

AGTTGAG

788.
Mm.216113
No Chromosome location
TGGTGGCTTGA

info available
TTGATTTGATC

TGAGAGCAGTT

TATAACATAAT

GGAGAACTGTT

TGCAG

789.
Mm.2623
Chromosome 13
AGAAGTCTACC

TTTAAGATGAC

CTATATTGGAG

AGATATTCACT

AAGATTCTGTT

GCTTC

790.
Mm.264709
No Chromosome location
ACTCTCTGGTC

info available
ATGATGGTTTT

CCGAAATCAG

GTTCCTGACCT

GAAAATTTGGG

TTAATC

791.
Mm.20323
Chromosome 5
GTTTTCATGCT

TTGGAAGTCTT

TTCTTTGAAAA

GGCAAACTGCT

GTATGAGGAG

AAAATA

792.
Mm.222093
Chromosome 1
GTGTGTAGGAA

AATGTAATTAA

GTACAAGGCTT

GTTTATGGGTG

GCTATGGAATG

CAGTC

793.
Mm.25035
Chromosome 6
GTTTCCTCATC

AGGTGTAATGG

CGTGTCCTAAT

GAAGCTATTTC

TTATGTATAAC

AGAGA

794.
Mm.103545
Chromosome 11
TGAAAAAATG

AAAAGAATCA

GAGATGAAAT

AGGAGCGCTC

AGAAGTTTTTA

TGTTCTCCC

795.
Mm.26229
Chromosome 11
AAAGAAATGA

AAACCGTCATT

TGCGATTTTCA

GGGTACGTTTC

TAATGTATCCA

GAAGTC

796.
Mm.22699
Chromosome 15
TTTCCAGTGTT

CTAGTTACATT

AATGAGAACA

GAAACATAAA

CTATGACCTAG

GGGTTTC

797.
Mm.275510
Chromosome 17
TTTTGACTCAG

TTGACTGTCTC

AGACTGTAAG

ACCTGAATGTC

TCTGCTCCGAA

TTCCTG

798.
Mm.275745
Chromosome 3
CCCGAGTTACT

AACAACATTCT

TTTGCTATATG

TAGATCAAGAT

TAACAGTTCCT

CATTC

799.
Mm.80676
No Chromosome location
GTTTTGGTGCA

info available
AAAGTCGTCCT

GTGTCTCTTGT

TCCCTTCATTA

GAAAACATGCT

AGAGG

800.
Mm.197381
Chromosome 12
AGGAAGGAAA

ATAGGCTTTGT

TGTATGTACAT

AAGTGGAATTA

ACAAGAGTCTT

TAGTCC

801.
Mm.276618
Chromosome 15
TACAGGGAAT

GGTCTAAGCAT

ACCATTTCATT

CACTGTATTAG

TAGACATAACT

GTTGAG

802.
Mm.46636
Chromosome 10
GAAACGGGCTT

TGTTGTAAAGG

TAATGAATAGG

AAACTCCTCAG

ATTCAATGGTT

AAGAA

803.
Mm.132926
Chromosome 13
AAGTTAAGGA

AATACTGAGA

ATCGGTCAGTT

AACACTCTGAA

AAGCTATTCAA

AGCATAG

804.
Mm.62
Chromosome 15
AAATACATGCA

TTTGTACAGTG

GGCCCTGTTCT

TGTGAAGTCCA

TCTCCATGGTC

ATTAG

805.
Mm.117473
Chromosome 9
CCGTTTTATTG

ATTGGAAATGT

AAGACTCAAA

GAACTCAGGTT

TACTGGCCAAG

ATGGCA

806.
Mm.2692
Chromosome 3
GGAAAGAGAG

ATCAAACTAGG

AACCTACAAG

ATAGTTCACTA

GCCTAAGATCT

TTACTTG

807.
Mm.196533
Chromosome 9
TTGATTGGTGT

TTCTGAGCATT

CAGACTCCGCA

CCCTCATTTCT

AATAAATGCA

ACATTG

808.
Mm.216997
Chromosome 10
CTAGTGAAATT

TATGTCAGAAT

GACATATCTGA

ACTCTGAATTC

ATCTCTAGTTT

CCACG

809.
Mm.29476
Chromosome 11
TAGTTAATACT

TCTCTGAAATA

CATGGTAACAA

CTAGTAAGCAA

GAGATACCGC

AGATTG

810.

No Chromosome location
TGGATTATTCC

info available
CGCCAAAGCA

CCCAAGTCGGC

CTGTTTAATTG

GAGAAAGATG

GAATTAA

811.
Mm.41781
Chromosome 19
GATCCAGGCA

ACCTCTGTTTA

CCCTGGGGCCT

ACAATGCCTTT

CAGATCCGTTC

TGGAAA

812.
Mm.142105
Chromosome 3
GTTCCATCTGA

CTTAAACAAAA

ACCGTAGTTTC

CAGCTCAGAAT

CATCCTAACAT

AGAAA

813.
Mm.203928
Chromosome 19
GTAGGGGAAT

AACTAACCAA

AGTAGAGGGA

ATTCTAAGTTT

AGTAGTAAATG

TGGCTTGG

814.
Mm.24128
Chromosome 6
GGTGTGGGACT

TATGGGGTCTA

CACAAAGGTA

AAGAATTACGT

GGACTGGATCC

TGAAAA

815.
Mm.221784
Chromosome 1
AGGTATGACAT

TTTACATCCTT

GAATCTTACTT

ACTATGTGCTA

AACAATTGGCA

GAAGG

816.
Mm.86699
Chromosome 16
TGCTTGTGTGA

ACTACCTCAGG

ATGAAGGGTA

ATGTTTAACAT

TCCATACATGC

CTACTG

817.
Mm.3317
Chromosome 5
CGATGGACCCA

AGATACCGAC

ATGAGAGTAGT

GTTGAGGATCA

ACAGTGCCCAT

TATTAT

818.
Mm.22383
Chromosome 15
GCAGCCAAAA

TGGAAATGTTT

AAATTAACTGT

GTTGTACAAAT

GTACCCAACAC

AAAACC

819.
Data not found
Chromosome 13
TTGACATGATA

CATTACGCCTT

TGCAGTGAGCT

AATAAGCTAAC

ATTTGTGCACA

GATAA

820.
Mm.257567
Chromosome 15
TCTCAACTCAT

CTCAGATTAGG

AAGTATTTGGC

AGTATTAGCCA

TCATGTGTCCC

TGTGA

821.
Mm.12912
Chromosome 7
ATTTTCATGCC

GAATATTCCAG

CAGCTATTATA

AAATGCTAAAT

TCACTCATCCT

GTACG

822.
Mm.465
Chromosome 6
GAGAATTAATC

ATAAACGGAA

GTTTAAATGAG

GATTTGGACTT

TGGTAATTGTC

CCTGAG

823.
Mm.21764
Chromosome 18
CATGAGCAAA

GCCCACCCTCC

CGAGCTGAAG

AAGTTTATGGA

CAAGAAGTTAT

CATTGAA

824.
Mm.222266
Chromosome 19
CTCTGTAAAGT

CAAGTTGCATT

GCATTTACAGT

TAATTATGGAA

AAGTCCTAAAT

CTGGC

825.
Mm.40285
Chromosome 12
TTTTCAGGGCT

ATAAAAGTATT

ATGTGGAAATG

AGGCATCAGA

CCACCGGACGT

TACCAC

826.
Mm.41940
Chromosome Multiple
AAGAAGCTGA

Mappings
GGAAAAACAG

GAGAGTGAGA

AACCGCTTTTG

GAACTATGAGT

TCTGCTCT

827.
Mm.263124
Chromosome 15
CCTGATGGAGT

CTGTGTTACTC

AGGAGGCAGC

AGTTATTGTGG

ATTCTCAAACA

AGGAAA

828.
Mm.21974
Chromosome 9
AGCAAATGGG

CATTTTACAAG

AAGTACGAATC

TTATTTTTCCT

GTCCTGCCCCT

GGGGGT

829.
Mm.25843
Chromosome 6
CTGCACTTGAA

TGGACTGAAA

ACTTGCTGGAT

TATCTAGAACA

ACAAGATGAC

ATGCTAC

830.
Mm.896
Chromosome 1
AGATTTCACCG

TACTTTCTGAT

GGTGTTTTTAA

AAGGCCAAGT

GTTGCAAAAGT

TTGCAC

831.
Mm.30466
Chromosome 15
ATAAAACCAC

AAACTAGTATC

ATGCTTATAAG

TGCACAGTAGA

AGTATAGAACT

GATGGG

832.
Mm.260433
Chromosome 18
ACCTAAATGTT

CATGACTTGAG

ACTATTCTGCA

GCTATAAAATT

TGAACCTTTGA

TGTGC

833.
Mm.145384
Chromosome 4
TTTATAGTTCT

AGGTTTACACC

AGAGAGGAGT

TAATTTATCAA

CAGCCTAAAAC

TGTTGC

834.
Mm.28385
Chromosome Multiple
TTCTTCCACGA

Mappings
ACAGATATTAT

GTCATTTTATC

CAATGCCGATA

AAGGAGAAAC

AACTTG

835.
Mm.27254
Chromosome 10
TACGTGGTCTG

GGGACCTGATG

TTGGAATCCTA

TTGTTGTTAAT

AAAACTGAGT

AAAGGA

836.
Mm.233891
Chromosome 10
ACCAACTTCTG

TCAAAGAACA

GTAAAGAACTT

GAGATACATCC

ATCTTTGTCAA

ATAGTC

837.
Mm.24021
Chromosome 7
TGACACAAATA

GAGGGGTCAA

TAAATTTTTAG

CCAAAAGCTTC

AAATTCTTTCA

GGAAGC

838.
Mm.141021
Chromosome 7
ATCACCATTGT

TAGTGTCATCA

TCATTGTTCTT

AACGCTCAAA

ACCTTCACACT

TAATAG

839.
Mm.292081
Chromosome 8
GCCGCTTTTTT

GTAACCTAAAA

GGCCCCATGAA

TAAGGGCCCAT

GTTTTGGGCAT

TTGTA

840.
Mm.275315
Chromosome 12
CCAAGAACAA

GTATAAACTTA

AGCTCTGTAGA

ACTGAAATTCT

TTCAAGTCCTT

TCGATC

841.
Mm.221696
Chromosome 6
AGGACATCTTG

CAACTTCTATG

CAATAATAAG

GATTTCCATCT

GACAAATAAG

ACAAGTG

842.
Mm.33922
Chromosome 5
GGGGAGTTCTA

ATAATAGTACC

ATTCATATCAG

CAAGAACCTA

AAAATGGTTCT

GACTTT

843.
Mm.27182
Chromosome 11
TGCCACTAGTT

CTGACTTGGGG

AATATGGTCCC

TTAAACATGCC

AAAGTGAGCTT

TTTAA

844.
Mm.2923
Chromosome X
CATCAATCCTT

TGATGGAACCT

CAAAGTCCTAT

AGTCCTAAGTG

ACGCTAACCTC

CCCTA

845.
Mm.8766
Chromosome 14
CAGTTGGAAA

AATGGATGAA

GCTCAATGTAG

AAGAGGGATT

ATACAGCAGA

ACTCTGGCA

846.
Mm.249306
Chromosome Un: not
TCAGTCAAATG

placed
TGCATAACTGT

AAATCAACACT

AAGAGCTCTGG

AAGGTTAAAA

AGGTCA

847.
Mm.87337
Chromosome 7
AGCAGGTGTTT

CGGACTTGCAA

TGAGCAATGCA

ATTTTTTCTAA

ATATGAGGATA

TTTAC

848.
Mm.258225
Chromosome 5
CTTGCTTCTTT

AGCAAAATATT

CTGGTTTCTAG

AAGAGGAAGT

CTGTCCAACAA

GGCCCC

849.
Mm.24159
Chromosome 11
TCTCAATTTTC

AAGGTGTATTT

CCTATCAGGAA

ACTTGAAGATA

ATATGGTCTGA

ACCCA

850.
Mm.14301
Chromosome 5
ACTGGACAAA

GTATTATGACT

TTCAACACCAG

GAGGTCTCCAA

ATACCTGCACA

GACAGC

851.
Mm.233547
Chromosome 4
GGCTGTTGAGT

GTAAAATGTGC

TTTGTGTTTGC

TTACAACATCA

GCTTTTAGACA

CACAG

852.
Mm.72173
Chromosome 14
TGAGTGCAATG

TGTCAGATTTC

ACCAAGAGAT

CTCCAAGGTTT

GTAGGTAATTT

GTGGTT

853.
Mm.101992
Chromosome Multiple
GTCATTGTCCA

Mappings
AGGTGACAGG

AGGAACTCAGT

CGTTAAAATGA

CGAGCCTTATT

TCATGA

854.
Mm.9336
Chromosome 3
TCTTAGAATCT

GGAATTGAGTG

CCATATTTTCT

GTTCTCCAATG

ATACCTGGAGA

AATCC

855.
Mm.15801
Chromosome 4
TGCTTTCTTAT

TCTTTAAAGAT

ATTTATTTTTCT

TCTCATTAAAA

TAAAACCAAA

GTATT

856.
Mm.159173
Chromosome X
CTGCATGTTAT

AACTTTATATG

ATGGTGTAGTG

CATATAAGCTA

TGAGAATCAGT

TATAC

857.
Mm.235074
Chromosome 8
CGTGCTGGAGG

ACGAGAGATTC

CAGAAGCTTCT

GAAGCAAGCA

GAGAAGCAGG

CTGAACA

858.
Mm.141157
Chromosome 3
TGGAGGCTTTG

TACCCAAAACT

TTTCAAGCCTG

AAGGAAAAGC

AGAACTGCGG

GATTACA

859.
Mm.39046
Chromosome 6
TGGAGGATCTG

TGTGAAAAAG

AAGTCACCCTC

ACAAACCGCC

GTGCCTAAGGA

CTCTGTC

860.
Mm.12090
Chromosome 1
CTATTTTGTGT

AGACATCGTCT

TGCCTGAATAG

ACTGTGGGTGA

ATCCAAATTTG

GTCCA

861.
Mm.221891
Chromosome 5: not placed
TAATTATCTAC

ATTGGGGTAAT

TGAAGTAGAA

AGATCCATCTT

AACTACGGTAA

TCTCCG

862.
Mm.235020
Chromosome 5
TTGGGTATCGT

TTATGTTTCCA

TCATAACACAT

GCAATAACATC

TAGGAAATCTT

TACCG

863.
Mm.269006
Chromosome 4
TCTGATGTGGA

AGTGCGGTCAT

TCCTGGTTTAA

CTCACAGCAAC

TTTTAATTGGT

CTAAG

864.
Mm.12829
Chromosome 1
ATCTCCTGTTA

ATGTATTTGGG

TCAAATGCAAG

GCCTTAATAAA

GAAATCTGGG

GCAGAA

865.
Mm.222131
No Chromosome location
GCAGCAAGAG

info available
AAAAGAGCAA

GAGAGCCAAA

GGCAAGAAAT

CTCTCTGTCAC

TCCCTTTTA

866.
Mm.288200
Chromosome 16
TGAGGAAAAG

CCCCATGTGAA

ACCTTATTTCT

CTAAGACCATC

CGTGATCTGGA

AGTCGT

867.
Mm.213420
Chromosome 11
ACCGGCTGTAC

CCAAATAGAA

CGTCATTTTGA

TATGAAGGATT

TCAGCCCCTGA

AGATTT

868.
Mm.131026
Chromosome 2
ATGGTTTCTTC

CAGCAATTTAG

CATTGCCTGAG

GGGTCTAAAA

GAATAAGTTGG

TTCTTG

869.
Mm.3401
Chromosome 19
ACAATCTCTGT

CAGCGAAAAG

TTCTACAACAG

CTGTGCTGCAA

AACATGTACAT

TCCAAG

870.
Mm.18830
No Chromosome location
AACTGTTACTG

info available
GATTGAAATTC

CCATCCCCTTT

CCCTAAAAATT

GTGCCTTAGAA

AACCC

871.
Mm.46184
Chromosome 5
CGACTGAGGTT

ATGACATCCTT

AGACTTTGTTG

TATGCTGCTTC

GAATGAACCA

GAGATA

872.
Mm.10117
Chromosome 9
TGCCTCTTCAT

CGCCAGTGGTC

CAAAGGGCGC

AGAGAGCGCA

CTAGCAGTCAA

TAGTGTT

873.
Mm.30219
Chromosome 8
CCACTAATATT

TAGCCAGCCTT

CATGTAGAAG

ACACATGGAA

ACACAGAAGT

AAACTTTT

874.
Mm.276229
Chromosome 10
AGAAATGAAC

ATACATTGTCA

GCATTTAGAAG

TAAGTTGTGAA

GACAGGGACA

TTAAGTG

875.
Mm.260594
Chromosome 5
CAAACGGGAT

CCTGTCTTCTT

CTTTTCTAATA

GAATTTTGTAA

AGGAAATGAA

TGTAGCC

876.
Mm.29467
Chromosome 8
ACCGTTCTATC

ACTGTGGATGG

AGAAGAAGCG

TCACTATTGGT

CTATGACATTT

GGGAAG

877.
Mm.154121
Chromosome 7
CTATTTTTGGG

AGATGTCTATT

GCGGAGTACA

GTAATATATAC

CCAGAGTATGT

CTATAG

878.
Mm.260515
Chromosome X
ACCCAACTCCA

GTGCTCTCTGT

CTTTTAGTACA

GGATTTTCACC

CATGTGCATGA

AAAAT

879.
Mm.21686
Chromosome 13
TTACCATTTTT

GGTTAAATGGC

CAAATTCAGAA

AATAACTCCAT

TTGAATCTCCA

GCAGG

880.
Mm.222196
Chromosome 6
TCACCATACTT

TGAAAGTGTAA

ACTACCACATA

TTAACATGTGT

GATTTAAGACC

CTCAG

881.
Mm.275648
Chromosome 13
TGTTGCCCTCA

GATATGTCAGA

TCAACTTGGAA

GGAAAGACCTT

CTACTCCAAGA

AGGAC

882.
Mm.254493
Chromosome 8
TCTAACAAGTG

TATTTGTGTTA

TCTTTAAAATA

GAACAATTGTA

TCTTGAAATGG

TAAAT

883.
Mm.27571
Chromosome 7
CGACACTGGGT

GGCCCTGCGAC

AGGTAGATGG

CATCTACTATA

ATCTGGACTCA

AAGCTC

884.
Mm.41033
Chromosome 2
TCTCAGAGGTG

TTGAAGATTTA

TCATCTTGAAT

CCTCCACAAAT

ACAGATACAGT

CCCAA

885.
Mm.3992
Chromosome 12
TCTTTTCACCT

CGATCAGCATC

ATGAGTCATCA

CAGATCATGTA

ATTAGTTTCTG

GGCCA

886.
Mm.221415
Chromosome 6
TGGGAATTGCA

TTTAGGATAGA

ATTGTATCTGA

TTTGCAAAATC

CATAAGCTCTC

ATGCC

887.
Mm.20437
Chromosome 4
TACTCCCACAG

TTGTATAGAAG

TCGAATAGTGA

AGGAGCTGGG

AGAAAACTGCT

TCAGCT

888.
Mm.27881
Chromosome 3
CCGCACTTAGC

CTAGCACCTTT

CTTACATGATC

TCAAGTTGAAC

CGACTTCCTTA

ACTCT

889.
Mm.29027
Chromosome 5
GCTTTGGAATT

AAAGAGGAGG

ATATAGATGAA

AACCCCCTCTT

TTGAATTAAGA

TTTGAG

890.
Mm.68617
Chromosome 1
AAATCAGATAT

GCAGGTCATCT

GATAAATGAGT

TAATGTTTGAT

ATTCGGGGTAT

CTCAC

891.
Mm.260361
No Chromosome location
GAACCATATGC

info available
TGGAATGAAA

CATAAGAGTTT

TCAACAGTTAT

CCTCTCACCTC

TGTATG

892.
Mm.7995
Chromosome X
GTATCGTCAAT

CCCAGTCAGTA

AGATAAGTTGA

AACAAGATTAT

CCTCAAGTGTA

GATTT

893.
Mm.130433
Chromosome 6
GTCAAAAACG

CCTTCAGGAAG

CCTTAGAGCGT

CAGAAGGAGT

TTGATCCGACC

ATAACAG

894.
Mm.196484
Chromosome 1
AATAGAATCTT

TTCACTTAGGA

ATGGAGAACA

AGCCAGTTCAG

AGGACCCCAA

AGTCTAG

895.
Mm.103615
Chromosome 4
CGTGGAGGAT

GGGCTAGCCTG

AGCTCTGGGAC

TAATCTTTATT

ACATACTTGTT

AATGAG

896.
Mm.24430
Chromosome 3
CTTATAGGGAG

AATGTTCTATT

CCTCAATCCAT

ACTCATTCCTA

CAGTATGCGCT

CTGGA

897.
Mm.33788
Chromosome 6
AGCAGGGGGA

TTATGTTAAGT

CAAATGCGTGT

GTCTCAAAAGT

GACATGTTTAA

CTGCTC

898.
Mm.4079
Chromosome 5
ACTCTGTACCC

TACTGGAACCA

CTCTGTAAAGA

GACAAAGCTGT

ATGTGCCACTT

CAGTA

899.
Mm.258618
Chromosome X
TTACAGGTCAC

TGTTTGTCACT

TTTGTGTACCA

GCTTCCCCATT

AGAATTCAACC

GATAC

900.
Mm.195900
Chromosome 13
ATGGAAGCGA

GGTCATTCTGC

GAACATTGGA

GATCTTTTATT

ACAAGTCTGCT

TGTTAAT

901.
Mm.271829
Chromosome 6
TAAAATTAGTG

TCCTGGGAGAG

ATGACCATTTT

AACTTCTATGC

TTATTTCACAT

GGGAA

902.
Mm.213265
Chromosome 14
TCGACGTCAAT

CTTACCTCTCT

AGGCAACATGT

TATCCCCGGAT

GATCAGAAATT

CCCAA

903.
Mm.17631
Chromosome 8
ACCTGTGTTTT

GTTTTTGTTTT

AAGAAACCAA

AGTGCACCAA

GATAGCATGCT

CTTGAGA

904.
Mm.20852
Chromosome 2
CTGCAGGTAAC

TCTCATTGGAA

GAAAAAGAAA

CTACAAGAGC

AAACAGAAGC

CATGGGAA

905.
Mm.87759
Chromosome Multiple
AAAGATTTCAT

Mappings
CCACGTCTGGC

GTAGTGGAAA

ACCCGAAGGG

AATATGTAATG

ATCTTTC

906.
Mm.242207
No Chromosome location
GTGTTGTACCC

info available
TAATTTGAATT

TAAAGTAGGC

AGTAGGTAGG

GTTAATTGGTA

GACTATC

907.
Mm.32556
Chromosome 17
CTTGGGTTTGA

GCACTCAGAAC

ACATGGCTGCA

ATCATCAAGAC

AGTTCACAGTT

AGCTT

908.
Mm.2074
Chromosome 2
CCCTAAGACAA

TGAAACTCAGA

ACTCTGTGATT

CCTGTGGAAAT

ATTTAAAACTG

AAATG

909.
Mm.268854
Chromosome 3
ATTTATAGAGG

TATCCTTAACA

TGCTGACTTCA

GTAACTGCCCT

TGTTTCTAAGG

AAGTC

910.
Mm.1483
Chromosome 16
ACCTGTAGCTT

CACTGTGAACT

TGTGGGCTTGG

CTGGTCTTAGG

AACTTGTACCT

ATAAA

911.
Mm.103615
Chromosome 4
TAATCCCTGGC

AAAGTCAAGA

CTGTGGGAAAC

TAGAACTGGTT

ACTCACTACTG

CTGGTA

912.
Mm.19738
Chromosome X
TTAGCTTCATG

ACCCCAAGGTT

AAGGTTCTGCC

AACAAGCATTC

TGCCTGACATC

TACTT

913.
Mm.276229
Chromosome 10
AATAAAGGCC

CCTTAGAAGCT

ACTGTAAAGCT

CTTCAAAGTTT

TCATGTAATCA

TAGGCA

914.
Mm.149029
Chromosome 16
AGAGATGGAG

ACTACACTGGG

TAGATTCTAGT

TTTTAGTTCTT

ATTAATGTGGG

GGAGTA

915.
Mm.268534
Chromosome 12
TATGGCCATTT

GGTTTCAGCAT

GTCAGGAGATT

TCTAATGATTT

GTGGCAATATC

AGCAA

916.
Mm.221782
Chromosome 19
TGTGTCAAGAT

AATCCTGAGTC

AACCTGGACAC

TTAATCCCTTT

GGACCTCTATC

TGGAG

917.
Mm.34527
Chromosome X
CCACCCATTAA

AATGACAGTAC

AAGTAGACCA

CAGTTTAAAGT

AGTTAGTCTAA

TTCTAC

918.
Mm.13445
Chromosome 15
CATAGTGGAA

ATATGCTCATC

TTTTATGCTAT

ATGTATTAAAC

CTCGACTTAGC

CCTGAA

919.
Mm.29236
Chromosome 7
GTTGAGGCTGA

CGACCTCCCAG

AGGCAATCTCT

GGATCTGGAAC

TTTGGGCATCA

TCGGA

920.
Mm.12454
Chromosome 1
ACCAACCAGG

GACTAGTTTGA

TGCTATCTTTG

CCTGTCTCTTG

GCTCTTAACAA

TGCCTA

921.
Mm.125975
Chromosome 7
CCAGGGAAGG

AACGATCCATT

CAGTGGTTTTA

AAATATCTCTT

CCTCAACAGAA

AAAGAT

922.
Mm.138073
Chromosome 2
GGTGCAAGCTA

GTACTCACACT

GTCACACCTTT

ACGCATGCGA

AAGGTAATGTG

CTAAAT

923.
Mm.140672
Chromosome 5
AGATCAGTGCT

CTGGACAGTAA

GATCCATGAGA

CGATTGAGTCC

ATAAACCAGCT

CAAGA

924.
Mm.218312
Chromosome 1
ATATCCCTGCT

AACTTAACAGC

AGTTAGTTTCC

TTGTTATGAAT

AAAAATGACA

GTCTGG

925.
Mm.260102
Chromosome 5
AAAGCAAATG

TTAGTAAAAAG

CTGGTGTGCAT

AGTCTTGTTAC

ATTGATGCAGT

TTTTCC

926.
Mm.3096
Chromosome 11
CAACTTGCTGA

ATAATGACTTC

CATTGAGTAAA

CATTTGGCTCT

GGTTATCTTCA

GGGAT

927.
Data not found
No Chromosome location
AGGAATTAGTA

info available
ACGTTTCATCC

AAGTAACCTTG

TTACAGTGAAC

AAGTGTCAAGT

GCTCA

The following Examples are intended to illustrate, but not limit, the invention.

EXAMPLES
Example 1
Signature Patterns of Gene Expression in Mouse Atherosclerosis and their Correlation to Human Coronary Disease

Mouse genetic models of atherosclerosis allow systematic analysis of gene expression, and provide a good representation of the human disease process (Breslow (1996) Science 272: 685-688). ApoE-deficient mice predictably develop spontaneous atherosclerotic plaques with numerous features similar to human lesions (Nakashima et al. (1994) Arterioscler Thromb 14: 133-140; Napoli et al. (2000) Nutr Metab Cardiovasc Dis 10: 209-215; Reddick et al. (1994) Arterioscler Thromb 14: 141-147. On a high-fat diet, the rate and extent of progression of lesions are accelerated. In addition to environmental influences such as diet, the genetic background of mice has also been found to have an important role in disease development and progression. Whereas C57B1/6 (C57) mice are susceptible to developing atherosclerosis, the C3H/HeJ (C3H) strain of mice is resistant (Grimsditch et al. (2000) Atherosclerosis 151:389-397. Previously, genetic-based diet and age induced transcriptional differences have been demonstrated between these two strains (Tabibiazar et L. (2005) Arterioscler Thromb Vasc Biol 25:302-308.

To more fully characterize the vascular wall gene expression patterns that are associated with atherosclerosis, a systematic large scale transcriptional profiling study was undertaken to take advantage of a longitudinal experimental design, and mouse genetic model and diet combinations that provide varying susceptibility to atherosclerosis. In this experiment, atherosclerosis-associated genes were studied independent of other variables. Primarily, these studies investigated differential gene expression over time in apoE-deficient mice on an atherogenic diet, with comparison to apoE-deficient mice (C57BL/6J-Apoe^tm1Unc) on normal diet as well as C57B1/6 and C3H/HeJ mice on both normal chow and atherogenic diet. Identification of atherosclerosis-associated genes was facilitated by development of permutation-based statistical tools for microarray analysis which takes advantage of the statistical power of time-course experimental design and multiple biological and technical replicates. Using these tools, hundreds of known and novel genes that are involved in all stages of atherosclerotic plaque, from fatty streak to end stage lesions, were identified. To further examine the expression of individual genes in the context of particular biological or molecular pathways, a pathway enrichment methodology with gene ontology (GO) terms for functional annotation was utilized. Using classification algorithms, a signature pattern of expression for a core group of mouse atherosclerosis genes was identified, and the significance of these classifier genes was validated with additional mouse and human atherosclerosis samples. These studies identified atherosclerosis related genes and molecular pathways.

Methods
Atherosclerotic Lesion Analysis

For select time points for various experimental groups, 5 to 7 female mice were used for histological lesion analysis. Atherosclerosis lesion area was determined as described previously (Tabibiazar et al. (2005), supra). Briefly, the arterial tree was perfused with PBS (pH 7.3) and then perfusion-fixed with phosphate-buffered paraformaldehyde (3%, pH 7.3). The heart and full length of the aorta to iliac bifurcation was exposed and dissected carefully from any surrounding tissues. Aortas were then opened along the ventral midline and dissected free of the animal and pinned out flat, intimal side up, onto black wax. Aortic images were captured with a Polaroid digital camera (DMC1) mounted on a Leica MZ6 stereo microscope, and analyzed using Fovea Pro (Reindeer Graphics, Inc. P.O. Box 2281, Asheville, N.C. 28802). Percent lesion area was calculated as total lesion area/total surface area.

Experimental Design, RNA Preparation and Hybridization to Microarrays

All experiments were performed following Stanford University animal care guidelines (Saadeddin et al. (2002) Med Sci Monit 8:RA5-12). Three week old female apoE knock-out mice (C57BL/6J-Apoe^tm1Unc), C57B1/6J, and C3H/HeJ mice were purchased from Jackson Labs (Bar Harbor, Me.). At four weeks of age the mice were either continued on normal chow or were fed high fat diet which included 21% anhydrous milkfat and 0.15% cholesterol (Dyets #101511, Dyets Inc., Bethlehem, Pa.) for maximum period of 40 weeks. At each of the time-points, including 0 (baseline), 4, 10, 24 and 40 weeks, for each of the conditions (strain-diet combination), 15 mice (3 pools of 5) were harvested for RNA isolation (total of 405 mice). Additional mice were used for histology for quantification of atherosclerotic lesions as described above. A separate cohort of sixteen-week-old apoE-deficient mice on high fat diet for two weeks (4 pools of 3 aortas) was also used for classification purposes.

After perfusion of mice with saline, the aortas were carefully dissected in their entireties from the aortic root to the common iliac and subsequently were flash frozen in liquid nitrogen. Total RNA was isolated as described previously (Tabibiazar et al. (2003) Circ Res 93:1192-1201) using a modified two-step purification protocol. RNA integrity was also assessed using the Agilent 2100 Bioanalyzer System with RNA 6000 Pico LabChip Kit (Agilent).

First strand cDNA was synthesized from 10 μg of total RNA from each pool and from a whole 17.5-day embryo for reference RNA in the presence of Cy5 or Cy3 dCTP, respectively. Hybridization to a mouse 60mer oligo microarray (G4120A, Agilent Technologies, Palo Alto, Calif.) (Carter et al. (2003) Genome Res 13:1011-1021) was performed following manufacture's instructions, generating three biological replicates for each of the time points. The RNA from the group of sixteen-week-old mice was linearly amplified and hybridized to a different array (G4121A, Agilent Technologies). Technical validation of the microarray has been performed previously using quantitative real-time reverse transcriptase polymerase chain reaction (results reported in Tabibiazar et al. (2005), supra). Primers and probes for 10 representative differentially expressed genes were obtained from Applied Biosystems Assays-on-Demand. A total of 90 reactions, including triplicate assays on three pools of five aortas, was performed from representative RNA samples used for microarray experiments, demonstrating a high correlation between the two platforms (Pearson correlation of 0.82).

Data Processing

Image acquisition of the mouse oligo microarrays was performed on an Agilent G2565AA Microarray Scanner System and feature extraction was performed with Agilent feature extraction software (version A.6.1.1, Agilent Technologies). Normalization was carried out using a LOWESS algorithm. Dye-normalized signals of Cy3 and Cy5 channels were used in calculating log ratios. Features with reference values of <2.5 standard deviation for the negative control features were regarded as missing values. Those features with values in at least 2/3 of the experiments and present in at least one of the replicates were retained for further analysis. Reproducibility of microarray results, as measured by the variation between arrays for signal intensities, was assessed using box plots (GeneData, Inc., South San Francisco, Calif.). For further statistical analysis of the data, a K-nearest-neighbor (KNN) algorithm was applied to impute missing values (Troyansakaya et al. (2001) Bioinformatics 17:520-525). Numerical raw data were then migrated into an Oracle relational database (CoBi) that has been designed specifically for microarray data analysis (GeneData, Inc.). Heat maps were generated using “HeatMap Builder” software (Blake and Ridker (2002) J Intern Med 252:283-294). All microarray data were submitted to the National Center for Biotechnology information's Gene Expression Omnibus (GEO GSE1560; www.ncbi.nlm.nih.gov/geo/).

Data Analysis

i) Principal Components Analysis

For each gene the average log expression values were computed at the four post-baseline observation times, 4, 10, 24, and 40 weeks. This was done separately for the six different (diet, strain) combinations, for example ApoE on high fat, presumably the most atherogenic combination. Differences of these vectors were taken for various interesting contrasts, e.g., for ApoE, high-fat minus C3H, normal chow, giving N=20280 vectors of length 4, one for each gene. Principal components analysis of the N vectors showed a consistent pattern, with the first principal vector indicating a roughly linear increase with observation time.

ii) Time Course Regression Analysis

A standard ANACOVA model was fit separately to the log expression values for each gene, using a model incorporating strain, diet, and time period effects. A single important “z value” was extracted from each ANACOVA analysis, for example corresponding to the significance of the time slope difference between the ApoE, high-fat combination and the average of the other five combinations. The N z-values were then analyzed simultaneously, using empirical Bayes false discovery rate methods described previously (Efron (2004) J Amer Stat Assoc 99:82-95; Efron and Tibshirani (2002) Genetic Epidemiology 23:70-86; Efron et al. (2001) J Amer Stat Assoc 96:1151-1160. These analyses identified a set of several hundred genes clearly associated with atherosclerosis progression.

iii) Time Course Area Under the Curve Analysis

Area under the curve (AUC) analysis was employed as described previously (Tabibiazar et al. (2005), supra). For each sequence of 4 triplicate gene expression measurements over time, the measurement at time 0 was subtracted from all values. The signed area under the curve was then computed. The area is a natural measure of change over time. These areas were then used to compute an F-statistic for the 6 groups (3 mouse strains and 2 diets) and 3 replicates (between sum of squares/within sum of squares). A permutation analysis, similar to that employed in Significance Analysis of Microarrays (SAM) (Tusher et al. Proc Natl Acad Sci 98:5116-5121), was carried out to estimate the false discovery rate (q-value or “FDR”) for different levels of the F-statistic.

iv) Enrichment Analysis

For enrichment analysis, the Expressionist software (GeneData, Inc.), which employs the Fisher exact test to derive biological themes within particular gene sets defined by functional annotation with Gene Ontology (GO) terms (www.geneontology.org) and Biocarta pathways (www.biocarta.com/genes/allpathways.asp), was used. In this way, over-representation of a particular annotation term corresponding to a group of genes was quantified.

v) Support Vector Machine for Gene Selection

For supervised analyses, the Expressionist software (GeneData USA), which employs Support Vector Machine (SVM) algorithm (Burges (1998) Data Mining and Knowledge Discovery 2:121-167), was used to rank genes based on their utility for class discrimination between time points 0, 4, 10, 24, and 40 weeks in apoE mice on high-fat diet. SVM is a binary classifier, so in order to classify multiple categories, N classifiers were created that classify one group vs. a combination of the rest of the groups (“one vs. all” classifiers) (Ramaswamy et al. (2001) Proc Natl Acad Sci 98:15149-15154). The larger set of genes identified by the time-course analysis was used for this analysis. This method was then used to determine the optimal number of ranked genes to classify the experiments into their correct groups at minimal error rate. The optimal error rate or misclassification is calculated by cross-validation with 25% of the experiments as the test group and the rest as the training group. This is reiterated 1000 times (FIG. 5A). In this study, a linear Kernel was used, since a nonlinear Gaussian kernel yielded similar results. This minimal subset of classifier genes was then used for cross-validation as well as classification of other independent gene expression profiling datasets.

vi) Analysis of Independent Datasets.

The SVM algorithm was utilized for classification of independent groups of experiments (Yeang et al. (2001) Bioinformatics 17 Suppl 1:S316-322). In this analysis, the primary time-course experiments were used (corresponding to 5 time points mentioned above) as the training set and the independent set of experiments (different array and labeling methodology) as the test set. SVM output for each experiment based on one-versus-all comparisons was represented graphically in a heatmap format (FIG. 5B), which is the normalized margin value for each of the 5 SVM classifiers mentioned above. The SVM output permits classification of a new experiment according to the 5 SVM hyperplane. The SVM algorithm (Linear Kernel) was also utilized for external validation by classifying different sets of human expression data. In these analyses, a confusion matrix was generated using cross validation with repeated splits into 75% training and 25% test sets to determine the accuracy of classification based on the small subset of genes identified earlier. Results are represented in tabular fashion (Table 3).

Transcriptional Profiling of Human Atherosclerotic Tissue and Atherectomy Samples

For one set of samples, coronary arteries were dissected from explanted hearts of patients undergoing orthotopic heart transplantation. Arteries were divided into 1.5 cm segments, classified as lesion or non-lesion after inspection of the luminal surface under a dissecting microscope. RNA was isolated from each individual sample and hybridized to a microarray. A central portion (1-2 mm) of each segment was removed and stored in OCT for later histological staining (hematoxylin and eosin, Masson's trichrome). Samples (n=40) were derived from 17 patients (male 13, female 4, mean age 43 years). Six patients had a diagnosis of ischemic cardiomyopathy, while 11 were classified as non-ischemic, although some vessel segments from the latter had microscopic evidence of coronary artery disease. Of 21 diseased segments, 7 were classified as grade 1, 4 grade III and 9 grade V, according to the modified American Heart Association criteria (Virmani et al. (2000) Arterioscler Thromb Vasc Biol 20:1262-1275), and one sample had only macroscopic information available. For a second set of tissues, coronary atherectomy samples were obtained with a cutting atherectomy catheter system (Fox Hollow Inc., Redwood City, Calif.), for chronic atherosclerosis lesions (n=28) and in-stent restonsis lesions (n=14). Patient characteristics in both groups were similar (male 78% vs. 71%, mean age 64 vs. 67). RNA was isolated from each individual sample, labeled by direct or linear amplification methods, and hybridized as described above to a 22 k feature custom cardiovascular oligonucleotide microarray designed in conjunction with Agilent Technologies (G2509A, Agilent Inc., Palo Alto, Calif.). Common reference RNA for all human hybridizations was a mixture of 80% HeLa cell RNA and 20% human umbilical vein endothelial cell RNA. Data processing and analysis were performed as described above. For 2-class comparison of gene expression, Significance Analysis of Microarrays (SAM) was used (www-stat.stanford.edu/tibs/SAM/; Tabibiazar et al. (2003), supra; Tusher et al. (2002), supra).

Results and Discussion
Atherosclerosis in the Genetic Models

To correlate the gene expression results with the extent of disease in each experimental group, the total atherosclerotic plaque burden in the aorta was determined by calculating a percent lesion area from the ratio of atherosclerotic area to total surface area. ApoE-deficient mice (C57BL/6J-Apoe^tm1Unc) (n=7) on high-fat diet were compared to other control mice (n=5-7 for each mouse-diet combination). Representative time-intervals were used for analysis, including baseline measurements in mice prior to initiation of high-fat diet at 4 weeks and end-point measurements corresponding to 40 weeks on either high-fat or normal diet (FIGS. 1, 2). Gross histological evaluation of these mice demonstrated increased atherosclerotic lesions in ApoE-deficient mice on high-fat diet involving about 50% of the entire aorta, and lesser area involved in ApoE-deficient mice on normal diet (FIG. 2). As expected, the control mice on either diet did not demonstrate evidence of atherosclerosis throughout the course of the experiment (Jawien et al. (2004) J Physiol Pharmacol 55:503-517; Nishina et al. (1990) J Lipid Res 31:859-869). Although some fatty infiltrates were noted on histological evaluation of the aortic root in C57 mice on high-fat diet, there were no obvious changes in inflammatory cell infiltrate (Tabibiazar et al. (2005), supra). The metabolic and lipid profiles of these mice were not obtained in this study, since they are well described in the literature (Grimsditch et al., supra Nishina et al. (1990), supra; Nishina et al. (1993) Lipids 28:599-605).

Temporal Patterns of Gene Expression

Employing a number of mouse models with different propensity to develop atherosclerosis, two different diets, and a longitudinal experimental design, it was possible to factor out differentially regulated genes that are unlikely to be related to the vascular disease process in the apoE deficient model. For instance, age-related and diet-related gene expression patterns that are not linked to vascular disease were eliminated by virtue of their expression in the genetic models that did not develop atherosclerosis. However, the complexity of the experimental design provided significant difficulties related to statistical analysis. Although analytic methods have been proposed to address a single set of time-course microarray data (Luan and Li (2003) Bioinformatics 19:474-482; Park et al. (2003) Bioinformatics 19:694-703; Peddada et al. (2003) Bioinformatics 19:834-841; Xu and Li (2003) Bioinformatics 19:1284-1289), there was no accepted algorithm for comparing differences in patterns of gene expression across multiple longitudinal datasets.

Using principle component analysis, it was determined that the greatest variation in the data was between time points, correlating with the progression of disease described previously for the apoE knockout mouse on high fat diet (Nakashima et al. (1994) Arterioscler Thromb 14:133-140; Reddick et al. (1994) Arterioscler Thromb 14:141-147). Given this finding, a linear regression model was utilized to identify genes that were differentially expressed in ApoE-deficient mice on high-fat diet, compared with all other experimental groups across time. This comparison across strains and dietary groups was employed to focus the analysis on atherosclerosis-specific genes, taking into account gene expression changes in the vessel wall associated with aging, diet, and genetic background. Empirical Bayes and permutation methods were employed to derive a false discovery rate (FDR) and minimize false detection due to multiple testing. With high stringency limits, global FDR <0.05 and local FDR <0.3, 667 genes demonstrated a linear increase with time, whereas only 64 genes showed the opposite profile (FIG. 3).

Genes with Increased Expression in the Atherosclerotic Vessel Wall

The identification of known genes previously linked to atherosclerosis validated the methodology and analysis algorithm. Most striking in this regard were inflammatory genes, including chemokines and chemokine receptors, such as Ccl2, Ccl9, CCr2, CCr5, Cklfsf7, Cxcl1, Cxcl12, Cxcl16, and Cxcr4 (FIG. 3). Also upregulated were interleukin receptor genes, including IL1r, IL2rg, IL4ra, IL7r, IL10ra, IL13ra, and IL15ra, and major histocompatibility complex (MHC) molecules such as H2-EB1 and H2-Ab. The value of transcriptional profiling in this disease was demonstrated by the identification of numerous inflammatory genes not previously linked to atherosclerosis, including CD38, Fcerlg, oncostatin M (Osm) and its receptor (Osmr).

Oncostatin M (Osm) and its cognate receptor (Osmr) are likely to have significant roles in atherosclerosis, based on number of studies that suggest several important related functions for these genes (Mirshahi et al. (2002) Blood Coagul Fibrinolysis 13:449-455. Osm is a member of a cytokine family that regulates production of other cytokines by endothelial cells, including 116, G-CSF and GM-CSF. Osm also induces Mmp3 and Timp3 gene expression via JAK/STAT signaling (Li et al. (2001) J Immunol 166:3491-3498). It induces cyclooxygenase-2 expression in human vascular smooth muscle cells (Bernard et al. (1999) Circ Res 85:1124-1131), as well as Abca1 in HepG2 cells (Langmann et al. (2002) J Biol Chem 277:14443-14450). Interestingly, Stat1, Jak3, Cox2, and Abca1 were among the disease-associated upregulated genes. Additionally, Osm produced by macrophages may contribute to development of vascular calcification (Shioi et al. (2002) Circ Res 91:9-16). This may occur via regulation of osteopontin or osteoprotegerin (Palmqvist et al. (2002) J Immunol 169:3353-3362, both of which have demonstrated significant changes in the dataset described herein. Osteopontin (Spp1) is thought to mediate type-1 immune responses (Ashkar et al. (2000) Science 287:860-864. While Spp1 has been extensively studied in atherosclerosis and other immune diseases, some of the osteopontin-related genes identified through these studies are novel and provide additional links between inflammation and calcification. Some of these include Cd44, Hgf, osteoprotegerin, Mglap, Il1Ora, Infgr, Runx2, and Ccnd1. Ibsp, (sialoprotein II), was also noted to be upregulated in these studies. Despite its similar expression profile to Spp1 in various cancer types and its binding to the same alpha-v/beta-3 integrin, the role of Ibsp in atherosclerosis has not been elucidated.

Known and novel genes were identified for many other protein classes that have been studied in atherosclerosis. Genes encoding endothelial cell adhesion molecules were among these groups, including Alcam and Vcam1. Extracellular matrix and matrix remodeling proteins were found to be upregulated, including fibronectin, Col8a1, Ibsp, Igsf4, Itga6, and thrombospondin-1. Matrix metalloproteinase genes such as Mmp2 and Mmp14 as well as those encoding tissue inhibitors of metalloproteinases, including Timp1, were also among the upregulated genes. Many transcription factors, lipid metabolism and vascular calcification genes, as well as macrophage and smooth muscle cell specific genes, were among those found to be upregulated. New genes were identified in each of these classes, for example, members of the ATP-binding-cassette family that were not previously associated with atherosclerosis were identified through these studies, including Abcc3 and Abcb1b.

Interesting genes linked to atherosclerosis for the first time through these studies encode a variety of functional classes of proteins. For example, genes encoding transcription factors Runx2 and Runx3 were linked to atherosclerosis in these studies. Cytoplasmic signaling molecules Vav1, Hras1, and Kras2 are factors that are well known to have critical signaling functions, but their role in atherosclerosis has not yet been defined. Wisp1 is a secreted wnt-stimulated cysteine-rich protein that is a member of a family of factors with oncogenic and angiogenic activity. Rgs1 is a member of a family of cytoplasmic factors that regulate signaling through Toll-like receptors and chemokine receptors in immune cells. Among the new classes of genes identified through these studies to be upregulated in atherosclerosis were those encoding histone deacetylases. Among those genes identified were Hdac7 and Hdac2. Although there is significant evidence that HDACs have important functions regulating growth, differentiation and inflammation, these molecules have not been well studied in the context of atherosclerosis (Dressel et al. (2001) J Biol Chem 276:17007-17013); Ito et al. (2002) Proc Natl Acad Sci 99:8921-8926). Histone deacetylase inhibitors have been postulated to modulate inflammatory responses (Suuronen et al. (2003) Neurochem 87:407-416).

The data from the experiments described herein has also yielded numerous ESTs and uncharacterized genes. These genes may be attractive candidates for further characterization. One example of such ESTs is 2510004L01Rik, a gene termed “viral hemorrhagic septicemia virus induced gene” (VHSV), which was originally cloned from interferon-stimulated macrophages. This gene is enriched in bone marrow macrophages, is upregulated by CMV infection and is similar to human inflammatory response protein 6 (Chin and Cresswell (2001) Proc Natl Acad Sci 98:15125-15130). Several ESTs such as 5930412E23Rik and 2700094L05Rik have been cloned from hematopoietic stem cells (genome-www5.stanford.edu/cgi-bin/source/sourceSearch), consistent with data suggesting cells in the diseased vessel wall may emanate from the bone marrow (Rauscher et al. (2003) Circulation 108:457-463.

Genes with Decreased Expression in the Atherosclerotic Vessel Wall

The 64 genes that showed decreased expression during progression of atherosclerosis were of interest, given the lack of previous attention to such genes. Sparcl1 (Hevin) is an extracellular matrix protein which is downregulated in the dataset described herein, and may have antiadhesive (Girard and Springer (1996) J Biol Chem 271:4511-4517) and antiproliferative (Claeskens et al. (2000) Br J Cancer 82:1123-1130) properties. It has been shown to be downregulated in neointimal formation and suggested to have a possible protective effect in the vessel wall (Geary et al. (2002) Arterioscler Thromb Vasc Biol 22:2010-2016). Another gene with decreased expression, Tgfb3, may also have a protective effect. The factor encoded by this gene has been shown to decrease scar formation, and to exert an inhibitory effect on G-CSF, suggesting an anti-inflammatory role that would counter pro-inflammatory factors in the vascular wall (Hosokawa et al. (2003) J Dent Res 82:558-564); Jacobsen et al. (1993) J Immunol 151:4534-4544).

Interestingly, numerous genes characteristic of various muscle lineages were shown to be downregulated. For smooth muscle cells, this might reflect decreased expression of differentiation markers. For example, the smooth muscle cell gene caldesmon encodes a marker of differentiated smooth muscle cells (Sobue et al. (1999) Mol Cell Biochem 190:105-118), and previous studies have noted that the population of differentiated contractile smooth muscle cells that express caldesmon is relatively lower in atherosclerotic plaque (Glukhova et al. (1988) Proc Natl Acad Sci 85:9542-9546). Other potential smooth muscle cell marker genes with decreased expression included Csrp1 and Mylk. Other downregulated skeletal and cardiac muscle genes included calsequesterin, which is expressed in fast-twitch skeletal muscle, Usmg4, which is upregulated during skeletal muscle growth, Xin, which is related to cardiac and skeletal muscle development, and Sgcg, that is strongly expressed in skeletal and heart muscle as well as proliferating myoblasts. The possible association of these and other myocyte related genes identified in this study to normal vascular function is not known.

Pathways Analysis

To identify important biological themes represented by genes differentially expressed in the atherosclerotic lesions, the genes were functionally annotated using Gene Ontology (GO) terms (www.geneontology.org) and curated pathway information. Enrichment analysis with the Fisher Exact Test demonstrated several statistically significant ontologies (Table 3), including several associated with inflammation. Inflammatory processes such as immune response, chemotaxis, defense response, antigen processing, inflammatory response, as well as molecular functions such as interleukin receptor activity, cytokine activity, cytokine binding, chemokine and chemokine receptor activity, Tnf-receptor, and MHC I and II receptor activity were noted to be significantly over-represented in the group of genes upregulated with atherosclerosis. Subanalysis of the inflammatory response pathways revealed genes characteristic of the macrophage lineage, as well as both the TH-1 and TH-2 T-cell populations, to be over-represented. Biocarta terms further delineated novel genes that were associated with pathways within the inflammation category, including classical complement, Rac-CyclinD, Egf, and Mrp pathways, as well as those known to be differentially regulated in atherosclerosis, such as Il2, Il7, Il22, Cxcr4, CCr3, Ccr5, Fcer1, and Infg pathways.

In addition to inflammation, other biological processes and molecular functions were over-represented in the group of differentially upregulated genes. These included expected pathways such as wound healing, ossification, proteo- and peptidolysis, apoptosis, nitric oxide mediated signal transduction, cell adhesion and migration, and scavenger receptor activity. However, several pathways that are less known for their role in atherosclerosis were also identified, including carbohydrate metabolism, complement activation, calcium ion hemostasis, collagen catabolism, glycosyl bonds and hydrolase activity, taurine transporter activity, heparin activity, etc. The lack of oxygen radical metabolism among the significant processes was surprising, but consistent with up-regulation of genes related to oxygen radical metabolism in all groups with aging.

Taken together, these pathway analyses support prior observations regarding the importance of inflammatory molecular pathways in atherosclerosis, but additionally, expand the repertoire of molecular pathways that are involved in this disease process.

Identification of Other Time-Related Patterns of Gene Expression in Atherosclerosis

The above analysis examined in detail genes with increased expression levels which correlate with atherosclerotic plaque development. However, additional patterns of gene expression were also identified in these longitudinal studies, to identify classes of genes and pathways not previously identified. For these analyses, the AUC algorithm was employed, which measured expression changes over time, made comparisons between the different strain/diet longitudinal datasets to identify gene expression changes specific for the apoE knockout model, and employed permutation to estimate the FDR (Tabibiazar et al. (2005), supra). Using this methodology several distinct gene expression patterns and pathways that reflect particular biological processes were identified (FIG. 4). For instance, some disease-related pathways were upregulated very early in the disease process and down-regulated thereafter (Pattern 6). Others were upregulated early and maintained at relative high expression throughout the time course of the disease (Pattern 8). Whereas the earlier pattern is enriched in pathways representing biological processes such as extracellular matrix and collagen metabolism, as well as DNA replication and response to stress, the later pattern is enriched in pathways representing biological processes such as fatty acid metabolism, oxidoreductase activity and heat-shock protein activity. Some disease related pathways were upregulated in both early and late phases of disease development (Pattern 3), including those associated with metabolism, such as glycolysis and gluconeogenesis. Other patterns (Pattern 4) are represented by key pathways regulating plaque development, including growth factor, cytokine, and cell adhesion activity. Interestingly, inflammation is represented in almost all of the patterns described herein.

Identification of Stage Specific Gene Expression Signature Patterns

Classification approaches to human cancer have provided significant insights regarding the clinical features of the tumor, including propensity to metastasis, drug responsiveness, and long term prognosis (Golub et al. (1999) Science 286:531-537; Lapointe et al. (2004) Proc Natl Acad Sci 101:811-816; Paik et al. (2004) N Engl J Med (“Multigene Assay to Predict Recurrence of Tamoxifen-Treated, Node-Negative Breast Cancer”); Sorlie et al. (2001) Proc Natl Acad Sci 98:10869-10874). For atherosclerosis, the clinical utility of classification algorithms will include prediction of future events. To establish a panel of genes whose expression in the vessel wall can accurately classify disease stage, and which may thus be useful for clinical genomic and biomarker applications, the support vector machines algorithm was employed on this comprehensive mouse model disease data set. Employing the SVM classification algorithm, 38 genes were identified that were able to accurately classify each experiment with one of five defined stages of atherosclerosis in mice (FIG. 5A). The results demonstrated that these genes can distinguish normal from severe lesions with 100% accuracy. The intermediate stages of the disease are also distinguished from the other stages with a high degree of accuracy (88-97%) (Table 3).

To validate the classifier genes, their ability to accurately categorize an independent group of 16 week old apoE knockout mice, which were evaluated with a different array and labeling methodology, was evaluated. The microarray utilized different probes for some of the same genes. Moreover, the labeling methodology used a linear amplification step which may introduce further variability in the data. Using the SVM classification algorithm, each of the 4 replicate experiments was accurately classified with the correct stage of the disease process (FIG. 5B). As indicated by the greater correlation between gene expression in this independent group of mice and gene expression patterns in the original experimental group aged 24 weeks, the classifier genes accurately matched this validation dataset to the closest timepoint in the database.

Identification of Mouse Disease Gene Expression Patterns in Human Coronary Atherosclerosis

The expression profile of differentially regulated mouse genes was investigated in human coronary artery atherosclerosis. For transcriptional profiling of human atherosclerotic plaque, 40 coronary artery samples, dissected from explanted hearts of 17 patients undergoing orthotopic heart transplantation, were used. Of the 21 diseased segments, lesions ranged in severity from grade I to V (modified American Heart Association criteria based on morphological description (Virmani et al., supra)). For the purpose of this analysis, human artery segments were classified as non-lesion or lesion (combined all grades). Atherosclerosis related mouse genes were matched to human orthologs by gene symbol or by known homology (www.ncbi.nlm.nih.gov/entrez/query.fcgi?DB=homologene). Comparison of expression of the mouse genes between lesion and non-lesion human samples using the significance analysis of microarrays algorithm (FDR <0.025) revealed more than 100 mouse genes with higher expression in the diseased human tissue (FIG. 6). In view of the differences between the tissue samples used in these gene expression experiments, these constitute an important common set of disease relevant genes.

To further test the relevance of our findings in mouse atherosclerosis, the accuracy of the mouse classifier genes was assessed in human atherosclerotic disease, employing established statistical methods. The mouse classifier genes were first used to predict various stages of coronary artery disease in the human arterial samples. The results demonstrated a high degree of accuracy in predicting atherosclerotic disease severity (71.2 to 84.7% accuracy) (Table 3).

Additionally, the mouse classifier genes were used to categorize human atherectomy tissue obtained from coronary vessels treated for chronic atherosclerosis or in-stent restenosis. The pathophysiological basis of restenosis is quite distinct from that of chronic coronary atherosclerosis, and it was of interest to demonstrate that the classifier genes could distinguish the disease processes (Rajagopal and Rockson (2003) Am J Med 115:547-553). The results (Table 3) demonstrated significant accuracy in distinguishing the two types of lesions (85.4 to 93.7% accuracy), further validating the significance of the mouse atherosclerosis gene expression patterns in human disease. The greater accuracy of classification with these samples compared to the arterial segments likely reflects less variation in the clinical profile of the patients, which have much less complex medication and comorbid features than the pre-cardiac transplant patients in the above analysis.

TABLE 2

Biological themes in atherosclerosis. Enrichment analysis of atherosclerosis-related genes

annotated with Gene Ontology and Biocarta terms demonstrates involvement of multiple

molecular pathways and biological processes. Probabilities (p-values) were derived

using Fisher exact test. 8478 of the entire microarray and 513 of genes in our set

(including additional 183 genes which demonstrated Pearson correlation >0.8

with the upregulated pattern) were annotated with GO, Biocarta, or other terms.

List gene #
Total gene #
p-value

Biological Process (GO annotation)

immune response
19
78
<0.0001

chemotaxis
10
23
<0.0001

cell surface receptor linked signal transduction
12
36
<0.0001

defense response
15
60
<0.0001

carbohydrate metabolism
14
67
<0.0001

antigen processing
5
9
<0.0001

locomotory behavior
4
6
<0.0001

inflammatory response
8
30
<0.0001

complement activation
5
12
<0.0001

proteolysis and peptidolysis
25
204
0.001

antigen presentation
4
10
0.002

intracellular signaling cascade
28
269
0.003

zinc ion homeostasis
2
2
0.004

transmembrane receptor protein tyrosine kinase activatic
2
2
0.004

hormone metabolism
2
2
0.004

hair cell differentiation
2
2
0.004

cell death
2
2
0.004

exogenous antigen via MHC class II
3
7
0.006

ossification
4
14
0.008

collagen catabolism
3
8
0.010

classical pathway
3
8
0.010

vesicle transport along actin filament
2
3
0.011

taurine transport
2
3
0.011

nitric oxide mediated signal transduction
2
3
0.011

negative regulation of angiogenesis
2
3
0.011

endogenous antigen via MHC class I
2
3
0.011

endogenous antigen
2
3
0.011

cellular defense response (sensu Vertebrata)
2
3
0.011

beta-alanine transport
2
3
0.011

lymph gland development
4
17
0.017

perception of pain
2
4
0.020

myeloid blood cell differentiation
2
4
0.020

female gamete generation
2
4
0.020

cytolysis
2
4
0.020

ATP biosynthesis
4
19
0.025

regulation of peptidyl-tyrosine phosphorylation
3
11
0.025

neurotransmitter transport
3
12
0.032

sex differentiation
2
5
0.032

exogenous antigen
2
5
0.032

cell adhesion
20
217
0.039

regulation of cell migration
3
13
0.040

wound healing
2
6
0.047

ureteric bud branching
2
6
0.047

cellular defense response
2
6
0.047

acute-phase response
2
6
0.047

regulation of transcription from Pol II promoter
6
44
0.048

hydrogen transport
3
14
0.049

calcium ion homeostasis
3
14
0.049

Molecular Functions (GO annotation)

acting on glycosyl bonds
12
31
<0.0001

interleukin receptor activity
8
13
<0.0001

hydrolase activity
67
641
<0.0001

cytokine activity
13
57
<0.0001

hematopoietin
9
32
<0.0001

complement activity
5
9
<0.0001

cytokine binding
3
3
<0.0001

C-C chemokine receptor activity
3
3
<0.0001

chemokine activity
4
7
<0.0001

cysteine-type endopeptidase activity
11
63
0.001

tumor necrosis factor receptor activity
3
5
0.002

platelet-derived growth factor receptor binding
2
2
0.004

cathepsin D activity
2
2
0.004

beta-N-acetylhexosaminidase activity
2
2
0.004

antimicrobial peptide activity
2
2
0.004

scavenger receptor activity
3
6
0.004

cysteine-type peptidase activity
9
56
0.006

mannosyl-oligosaccharide 1,2-alpha-mannosidase activi
3
7
0.006

receptor activity
42
479
0.009

taurine:sodium symporter activity
2
3
0.011

taurine transporter activity
2
3
0.011

myosin ATPase activity
2
3
0.011

MHC class I receptor activity
2
3
0.011

cathepsin B activity
2
3
0.011

calcium channel regulator activity
2
3
0.011

beta-alanine transporter activity
2
3
0.011

catalytic activity
23
230
0.012

solute:hydrogen antiporter activity
2
4
0.020

protein kinase C activity
2
4
0.020

tumor necrosis factor receptor binding
3
11
0.025

hydrogen-exporting ATPase activity
5
29
0.028

neurotransmitter:sodium symporter activity
2
5
0.032

MHC class II receptor activity
2
5
0.032

heparin binding
5
31
0.037

endopeptidase inhibitor activity
4
22
0.041

protein-tyrosine-phosphatase activity
7
54
0.043

hydrogen ion transporter activity
5
33
0.046

sulfuric ester hydrolase activity
2
6
0.047

Cellular Component (GO annotation)

extracellular space
139
1148
<0.0001

lysosome
26
66
<0.0001

extracellular
23
117
<0.0001

integral to membrane
138
1637
<0.0001

membrane
77
862
<0.0001

integral to plasma membrane
22
205
0.006

extracellular matrix
14
114
0.009

external side of plasma membrane
3
9
0.014

Biocarta Pathways

classicPathway
3
3
<0.0001

il22bppathway
4
7
<0.0001

nktPathway
5
12
<0.0001

Ccr5Pathway
5
13
0.001

reckPathway
4
8
0.001

compPathway
3
4
0.001

il7Pathway
4
10
0.002

TPOPathway
5
17
0.003

cxcr4Pathway
5
17
0.003

blymphocytePathway
2
2
0.004

il10Pathway
3
7
0.006

pdgfPathway
5
22
0.009

ionPathway
2
3
0.011

egfPathway
5
23
0.011

biopeptidesPathway
5
23
0.011

bcrPathway
5
25
0.015

ghPathway
4
17
0.017

fcer1Pathway
5
26
0.018

spryPathway
3
10
0.019

neutrophilPathway
2
4
0.020

mrpPathway
2
4
0.020

trkaPathway
3
11
0.025

pmlPathway
3
11
0.025

srcRPTPPathway
3
12
0.032

plcdPathway
2
5
0.032

ifngPathway
2
5
0.032

il2Pathway
3
13
0.040

RacCycDPathway
4
22
0.041

lymphocytePathway
2
6
0.047

nuclearRsPathway
3
14
0.049

cdMacPathway
3
14
0.049

CCR3Pathway
3
14
0.049

Summary annotation for inflammatory genes

defense
15
54
<0.0001

chemokine
9
22
<0.0001

Interleukin
9
38
<0.0001

cytokine
18
144
0.003

TNF
4
13
0.006

TH2
4
15
0.011

TH1
4
16
0.013

macrophage
3
13
0.040

TABLE 3

Classification of mouse and human atherosclerotic tissues employing mouse classifier

genes. To validate the accuracy of mouse classifier genes in predicting disease

severity we utilized various mouse and human expression datasets. The SVM algorithm

was utilized for cross validation of mouse experiments grouped on the basis of (A)

stage of disease (no disease- apoE time 0, mild disease- apoE at 4 and 10 weeks

on normal diet, mild-moderate disease- apoE at 4 and 10 weeks on highfat diet,

moderate disease-apoE at 24 and 40 weeks on normal diet, and severe disease- apoE

at 24 and 40 weeks on high fat diet); (B) 3 different time points (apoE at 0 vs. 10, vs.

40 weeks); (C) Human coronary artery with lesion vs. no lesion; and (D) atherectomy

samples derived from in-stent restenosis vs. native atherosclerotic lesions. For each

analysis, the accuracy of classification is represented in tabular fashion

with the confusion matrix generated using N-fold cross validation methods.

A

TRUE
TRUE
TRUE
TRUE
TRUE

PREDICTED
No dz
Mild_dz
Mild_mod dz
Mod_dz
Severe_dz
Correct [%]

No dz
64
0
1
0
0
98.5

Mild_dz
2
140
0
0
0
98.6

Mild_mod dz
0
0
148
20
0
88.1

Mod_dz
0
0
3
149
0
98.0

Severe_dz
0
0
0
0
173
100.0

Correct [%]
97.0
100.0
97.4
88.2
100.0

B

TRUE
TRUE
TRUE

PREDICTED
ApoE_T00_NC
ApoE_T10_HF
ApoE_T40_HF
Correct [%]

ApoE_T00_NC
68
0
0
100

ApoE_T10_HF
0
56
0
100

ApoE_T40_HF
0
0
76
100

Correct [%]
100
100
100

C

TRUE
TRUE

PREDICTED
Lesion
No lesion
Correct [%]

Lesion
183
33
84.7

No lesion
53
131
71.2

Correct [%]
77.5
79.9

D

TRUE
TRUE

PREDICTED
ISR
De novo
Correct [%]

ISR
345
44
88.7

De novo
59
652
91.7

Correct [%]
85.4
93.7

Example 2
Mouse Strain—Specific Differences in Vascular Wall Gene Expression and Their Relationship to Vascular Disease
Methods
RNA Preparation and Hybridization to the Microarray

Three-week old female C3H/HeJ, C57B1/6J, and apoE knock-out mice (C57BL/6J-Apoe^tm1Unc) were purchased from Jackson Labs (JAX® Mice and Services, Bar Harbor, Me.). At four weeks of age the mice were either continued on normal chow or switched to non-cholate containing high-fat diet which included 21% anhydrous milkfat and 0.15% cholesterol (Dyets #101511, Dyets Inc., Bethlehem, Pa.) for a maximum period of 40 weeks. At each of the time-points, including 0 (baseline), 4, 10, 24 and 40 weeks, for each of the conditions (strain-diet combination), 15 mice were harvested for RNA isolation, for a total of 450 mice. Following Stanford University animal care guidelines, the mice were anesthetized with Avertin and perfused with normal saline. The aortas from the root to the common iliacs were carefully dissected, flash frozen in liquid nitrogen, and divided into three pools of five aortas for further RNA isolation. Total RNA was isolated as described in Tabibiazar et al. (2003) Circ Res 93:1193-1201. First strand cDNA was synthesized from 10 μg of total RNA from each pool and from whole 17.5-day embryo for reference RNA in the presence of Cy5 or Cy3 dCTP, respectively, and hybridized to a mouse 60mer oligo microarray (G4120A, Agilent Technologies, Palo Alto, Calif.), generating three biological replicates for each time point.

Data Processing

Array image acquisition and feature extraction was performed using the Agilent G2565AA Microarray Scanner and feature extraction software version A.6.1.1. Normalization was carried out using a LOWESS algorithm, and Dye-normalized signals were used in calculating log ratios. Features with reference values of <2.5 standard deviations above background for the negative control features were regarded as missing values. Those features with values in at least 2/3 of the experiments and present in at least one of the replicates were retained for further analysis. For SAM analyses, a K-nearest-neighbor (KNN) algorithm was applied to impute for missing values. (Tabibiazar et al. (2003), supra.)

Data Analysis

Experimental design and analysis flow chart is depicted in FIG. 7. Significance Analysis of Microarrays (SAM) was employed to identify genes with statistically different expression between the C3H and C57 mice at baseline. (Tabibiazar et al. (2003), supra; Tusher et al. (2001) PNAS 98:5116-5121; Chen et al. (2003) Circulation 108:1432-1439.) For partitioning clustering of the genes with K-Means and self-organizing-maps (SOM), we used positive correlation for distance determination and required complete linkage, which uses the greatest distance between genes to ascribe similarity. SOM and K-Means analyses were performed using Expressionist software (GeneData, Inc., USA). Heatmaps were generated using HeatMap Builder. For enrichment analysis we used the EASE analysis software which employs Gene Ontology (GO) annotation and the Fisher's exact test to derive biological themes within particular gene sets. (Hosack et al. (2003) Genome Biol. 4:R70.) For time-course study, a new statistical algorithm, the Area-Under-Curve (AUC) analysis was devised. For each sequence of 4 triplicate gene expression measurements over time, we first subtracted the measurement at time 0 from all values. We then computed the signed area under the curve. The area is a natural measure of change over time. These areas were then used to compute an F-statistic for comparing C57 and C3H mice across the different diets. A permutation analysis, similar to that employed in SAM, was carried out to estimate the false discovery rate (q-value or “FDR”) for different levels of the F-statistic. For ease of presentation, genes which meet our FDR cutoffs will be referred to as “significant” throughout the remainder of the article. All microarray data were submitted to the NCBI Gene Expression Omnibus (GEO GSE1560; http://www.ncbi.nlm.nih.gov/geo/).

Aortic Lesion Analysis

For select time points within various experimental groups, 5 to 7 female mice were used for histological lesion analysis. Atherosclerosis lesion area was determined as described in Tangirala et al. (1995) 36:2320-2328.

Quantitative Real-Time Reverse Transcriptase—Polymerase Chain Reaction

Primers and probes for 10 representative differentially expressed genes were obtained from Applied Biosystems Assays-on-Demand. A Total of 90 reactions were performed from representative RNA samples used for microarray experiments. These included triplicate assay on three pools of five aortas. cDNA was synthesized and Taqman was performed as described in Tabibiazar et al. (2003), supra.

Results
Baseline Differences in Gene Expression Patterns Between the Mouse Strains

Differences in gene expression levels between the two strains at baseline, before effects of aging or diet become apparent, may identify genes that play a role in determining vascular wall disease susceptibility. To identify such genes SAM was used to compare the vascular wall gene expression of C3H vs. C57 mice at 4 weeks of age, with all animals on normal chow diet. SAM identified 311 genes as being significantly differentially expressed (FDR <0.1 with >1.5 fold difference), and expression patterns of these genes provided a clear partition between C3H and C57 mice (FIG. 8). A separate 2-class comparison (SAM, FDR <0.1) between C57 and apoE-deficient mice with a C57B1/6 genetic background revealed only a few genes, including Apo-E, which were differentially expressed in the 2 groups of mice (data not shown).

Comparison of C3H and C57 vascular wall gene expression at baseline provided a list of compelling candidate genes which reflected differences in biological processes such as growth, differentiation, and inflammation as well as molecular functions such as cathecholamine synthesis, phosphatase activity, peroxisome function, insulin like growth factor activity, and antigen presentation (FIG. 8). These processes were exemplified by higher expression of genes such as Cdkn1a, Pparbp, protein tyrosine phosphatase-4a2, and Socs5 in C3H mice, compared with genes such as ABCC1, H2-D1, Bat5, IGFBP1, SCD1, and Serpine6b which demonstrated higher expression in C57 mice. These fundamental baseline gene expression differences may determine disease susceptibility as the mice are exposed to age-related stimuli or dietary challenges.

Age-Related Differences in Gene Expression Patterns Between the Mouse Strains

To further examine the vascular wall gene expression differences between C57 and C3H mice, an analysis was performed to identify genes differentially expressed in response to aging (FIG. 9). Data was collected at five time points over a 40 week period. To identify such genes, we developed the Area Under the Curve (AUC) analysis. The AUC analysis relies on a permutation procedure to reduce the number of potential false positives generated due to multiple testing, but still utilizes the increase in statistical power of time-course experimental design. Comparing C57 vs. C3H time-course differences on normal diet with a rigid cutoff (FDR <0.05) did not identify any genes. However, relaxing the AUC stringency (f-statistic >10, FDR <0.45) allowed a large number of genes (413) to be included for pathway over-representation analysis using GO annotation. Functional annotation and group over-representation analysis (Fisher test p-value <0.02) of the resultant differentially expressed genes revealed differences in a number of biological processes, including growth and development, as well as a number of molecular functions such as cell cycle control, regulation of mitosis, and metabolism (FIG. 9b). Some of these processes are exemplified by genes with higher expression in C57 mice, such as Aoc1 (pro-oxidative stress), Bub1 (cell cycle check point), Cyclin B2, as well as genes with higher expression in C3H, including INHBA and INHBB.

Temporally variable genes identified by AUC analysis were further characterized with K-Means clustering to identify dynamic patterns of expression during the aging process (FIG. 3c). Clusters 1, 4, and 9 revealed either higher overall expression or temporally increasing levels of expression in C3H mice compared with C57 mice. In contrast, clusters 2, 6, and 14 revealed the opposite pattern. Of the genes which were noted to be differentially expressed in the two strains during aging, 51 genes were also differentially expressed at baseline, suggesting that baseline differences of certain genes can further be affected with aging.

Diet-Related Differences in Gene Expression Patterns Between the Mouse Strains

Differential vascular wall response to atherogenic stimuli was determined by comparing temporal gene expression patterns in C57 vs. C3H mice on high-fat diet (FIG. 10A). Comparing C57 vs. C3H time-course differences on high-fat diet with a rigid cutoff (FDR <0.05) identified 35 genes, including Hgfl and Tgfb4, which were down regulated in C57 on high-fat diet. Additional known genes, as well as a number of ESTs were also identified. Employing a less stringent AUC cutoff allowed identification of a larger number of genes, which could be evaluated with pathway over-representation analysis using GO annotation. At this level of stringency (f-statistic >10, FDR<0.35), a total of 650 genes with temporally variable expression were identified. Genes that were also differentially regulated by the aging process (141 of 650 genes) were excluded from further analysis of this group. 38 of the remaining 509 genes were among those differentially expressed at baseline. Functional annotation and group over-representation analysis (Fisher test p-value <0.02) of these differentially expressed genes revealed differences in biological processes such as catabolism, oxygen reactive species and superoxide metabolism, and proteo- and peptidolysis as well as molecular functions such as fatty acid metabolism, oxidoreductase and methyltransferase activities (FIG. 10B). Interestingly, this analysis suggested important differences between the two mouse strains with respect to the activity of the peroxisome, microbody and lysosome. Some of these processes were exemplified by genes with higher expression in C3H mice, such as Ccs, Ephx2, Gpx4, Prdx6 (anti-oxidants), Sirt3 (transcriptional repressor), PPARα, and Mcd, as well as genes with higher expression in C57 mice, such as Lysyl oxidase and Cdkn1a. K-means clustering of these genes identified a small number of distinct expression patterns (FIG. 10C), with clusters 3 and 9 revealing increased gene expression in C3H mice and clusters 8 and 10 showing the opposite pattern.

Evaluation of Strain-Specific Differentially Regulated Genes in the apoE Model

Using these techniques, a significant number of genes have been identified that are differentially expressed in the atherosclerosis resistant C3H and susceptible C57 mice, some of which are likely involved in atherogenesis and some of which are likely irrelevant to the process. To further select genes most likely to be involved in atherogenesis, expression in apoE-deficient mice fed normal or high-fat diet over a period of 40 weeks was investigated (FIG. 11). We utilized SOM analysis to visualize the expression profiles of these subsets of genes throughout the development and progression of atherosclerosis in the ApoE-deficient mice. The analysis revealed several patterns of gene expression. For example, SOM cluster 8 demonstrated a consistently increasing pattern of expression which correlated with disease progression in the apoE-deficient mice (FIG. 11). As evidenced by the pie chart, this cluster is enriched with genes that were identified as more highly expressed in C57 versus C3H mice at baseline (i.e., potentially atherogenic). In contrast, clusters 4, 5, and 6 showed decreasing expression with disease progression. The decreased expression of genes in cluster 4 was somewhat attenuated with high-fat challenge of the ApoE-deficient mice. This cluster is particularly enriched with genes that had revealed a higher expression in C3H mice (i.e., potentially atheroprotective) with atherogenic stimuli and with aging.

Given C3H resistance and C57 susceptibility to atherosclerosis, as an initial hypothesis it was postulated that genes with higher expression in C3H mice confer resistance, whereas genes with higher expression in C57 mice may have a pro-atherogenic role. With this point of reference, gene clusters were further examined. For example, limiting the list of genes in SOM cluster 8 (genes with increased expression with atherosclerosis) to those that also had higher baseline expression in C57 mice yielded an interesting set of genes that may be atherogenic. This group included inflammation related genes such as H2-D1, Pdgfc, Paf, and Cd47. Other compelling genes included Agpt2, Mglap, Xdh, Th, and Ctsc. Conversely, limiting the list of genes in clusters 4 and 5 to those with higher expression in C3H mice identified a group of genes with potential athero-protective function. Some of those genes included Pparα, Pparbp, as well as Ptp4a1, and Mcd.

Lesion Analysis in the Genetic Models

To address whether some of the gene expression differences are related to presence of atherosclerotic lesion in C57 mice, the total atherosclerotic burden was determined in the aorta by calculating a percent lesion area in aortas of C57 (n=5) and C3H (n=5) mice. Comparisons were made at time 0 and 40 weeks on normal or high-fat diet. Non-cholate containing high-fat diet was used to prevent caustic effects on the vascular wall. As expected, C57 and C3H mice on either diet did not demonstrate evidence of atherosclerosis throughout the course of the experiment, suggesting that observed gene expression changes cannot be explained by different cellular composition of the vessel wall. Although minimal fatty infiltrates were noted on histological evaluation of the aortic root in C57 mice on high-fat diet, there were no obvious changes in inflammatory cell infiltrate.

Quantitative RT-PCR Validation of Expression Differences

To validate the array results with quantitative RT-PCR and assure that the statistical analyses were identifying truly differentially expressed genes, ten representative genes were assayed by quantitative RT-PCR. Several genes were used from each group of significant genes. There is high degree of correlation between the two methodologies (Pearson correlation of 0.86), validating the results of the microarray analyses.

Although the foregoing invention has been described in some detail by way of illustration and examples for purposes of clarity of understanding, it will be apparent to those skilled in the art that certain changes and modifications may be practiced without departing from the spirit and scope of the invention. Therefore, the description should not be construed as limiting the scope of the invention.

All publications, patents and patent applications cited herein are hereby incorporated by reference in their entirety for all purposes to the same extent as if each individual publication, patent or patent application were specifically and individually indicated to be so incorporated by reference.

	Number	Date	Country
Parent	11387484	Mar 2006	US
Child	12205618		US

METHODS AND COMPOSITIONS FOR DIAGNOSIS, MONITORING AND DEVELOPMENT OF THERAPEUTICS FOR TREATMENT OF ATHEROSCLEROTIC DISEASE

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