COMPOSITIONS AND METHODS COMPRISING BIOMARKERS OF SPERM QUALITY, SEMEN QUALITY AND FERTILITY

Information

  • Patent Application
  • 20090246771
  • Publication Number
    20090246771
  • Date Filed
    November 03, 2008
    16 years ago
  • Date Published
    October 01, 2009
    15 years ago
Abstract
Provided are compositions and methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining sperm DNA from a test subject; determining the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and thereby determining or diagnosing abnormal sperm or fertility. Provided are compositions and methods for identifying agents that cause spermatogenic deficits or abnormal sperm fertility, comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with a test agent; culturing the contacted cells; determining, using a genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the above group; and identifying at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility.
Description
FIELD OF THE INVENTION

Particular aspects relate generally to DNA methylation and epigenetic reprogramming during development and gametogenesis, and more particularly to novel and effective epigenetic biomarkers and methods for determining and/or diagnosis of sperm quality, semen quality and fertility, comprising determining the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1. Additional aspects relate to compositions and methods for identifying and/or screening for agents that cause spermatogenic deficits or abnormal sperm fertility, comprising contacting human (or murine, rat, Etc.) ES-cell derived primordial germ cells with a test agent and determining the methylation status of at least one CpG dinucleotide sequence from at least one sequence as disclosed herein.


BACKGROUND

Ten to twenty percent of couples attempting pregnancy are infertile. Male-factor infertility accounts entirely for approximately 20% of these cases, and is contributory in an additional 30% [1,2]. Well defined causes of male-factor infertility are known to include congenital and acquired dysfunction of the hypothalamic-pituitary-testicular endocrine axis, anatomic defects, chromosomal abnormalities, and point mutations [3-5]. However, these diagnoses account for only a small proportion of cases, and etiology remains unknown for most male-factor infertility patients [1,2].


The mammalian germ line undergoes extensive epigenetic reprogramming during development and gametogenesis. In males, dramatic chromatin remodeling occurs during spermatogenesis [6,7], and widespread erasure of DNA methylation followed by de novo DNA methylation occurs developmentally in two broad waves [6,8-11]. The first occurs before emergence of the germ line, establishing a pattern of somatic-like DNA hypermethylation in cells of the pre-implantation embryo that are destined to give rise to all cells of the body, including germ cells. The second widespread occurrence of erasure takes place uniquely in primordial germ cells. Subsequent de novo methylation occurs during germ cell maturation and spermatogenesis, establishing a male germ line pattern of DNA methylation that remains hypomethylated compared with somatic cell DNA [8,12-16].


A small number of studies have addressed the epigenetic state of the human male germ line. Substantial variation in DNA methylation profiles is reported in ejaculated sperm of young, apparently healthy men. Notable distinctions were observed both between samples from separate men and among individually assayed sperm from the same man [17].


Although this variation suggests that DNA methylation may be used as a biomarker of sperm quality, semen quality and fertility were not assessed in this study [17].


SUMMARY OF EXEMPLARY ASPECTS

Male-factor infertility is a common condition, and etiology is unknown for a high proportion of cases. Abnormal epigenetic programming of the germline is disclosed as a mechanism compromising spermatogenesis of some men currently diagnosed with idiopathic infertility. During germ cell maturation and gametogenesis, cells of the germ line undergo extensive epigenetic reprogramming. This process involves widespread erasure of somatic-like patterns of DNA methylation followed by establishment of sex-specific patterns by de novo DNA methylation.


According to particular aspects, incomplete reprogramming of the male germ line results in both altered sperm DNA methylation and compromised spermatogenesis.


Particular aspects provide the first discovery and disclosure ever of a broad epigenetic defect associated with abnormal semen parameters. Additional aspects relate to an underlying mechanism for these broad epigenetic changes, comprising improper erasure of DNA methylation during epigenetic reprogramming of the male germ line.


Concentration, motility and morphology of sperm was determined in semen samples collected by male members of couples attending an infertility clinic. METHYLIGHT™ and ILLUMINA™ assays were used to measure methylation of DNA isolated from purified sperm from the same samples. Methylation at numerous sequences was elevated in DNA from poor quality sperm, and provide novel and effective epigenetic biomarkers of sperm quality, semen quality and fertility.


Particular exemplary aspects, provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and determining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain aspects, the determined methylation status of the at least one CpG sequence is hypermethylation. In particular embodiments, determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties. Preferably, treating comprises use of bisulfite treatment of the DNA.


In certain aspects, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.


In particular aspects, abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, abnormal total normal morphology, abnormal volume, and abnormal viscosity. In certain embodiments, abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, and abnormal total normal morphology.


Certain aspects of the methods, comprise determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8 and PLAGL1. In certain embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, and PLAGL1 SEQ ID NOS:7 and 19.


Yet additional aspects, provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence from each of a repetitive DNA element sequence group, a maternally imprinted gene sequence group, and a non-imprinted gene sequence group; and determining, based on the methylation status of the at least one CpG sequence from each of the groups, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain implementations, the at least one gene sequence from a repetitive element group comprises at least one selected from the group consisting of SAT2CHRM1 SEQ ID NOS:9 and 21. In certain aspects, the at least one gene sequence from a maternally imprinted gene group comprises at least one selected from the group consisting of PLAGL1 SEQ ID NOS:7 and 19, MEST SEQ ID NOS:5 and 17, and DIRAS3 SEQ ID NOS:3 and 15. In particular embodiments, the at least one gene sequence from a non-imprinted gene group comprises at least one selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, SFN SEQ ID NOS:6 and 18, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.


Yet further aspects provide methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with at least one test agent; culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development; obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility. In certain aspects, the determined methylation status of the at least one CpG sequence is hypermethylation. In certain embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 shows, according to particular exemplary aspects, box plots illustrating associations between semen parameters and level of methylation (PMR) in DNA isolated from 65 study sperm samples. DNA methylation was measured by MethyLight. Methylation targets were sequences specific to the genes HRAS, NTF3, MT1A, PAX8, PLAGL1, DIRAS3, MEST and SFN and the repetitive element Satellite 2 (SAT2CHRM1). P-value for trend over category of semen parameter is given for each plot. Rows: DNA methylation targets; columns: semen parameters.



FIG. 2 shows, according to particular exemplary aspects, cluster analysis of 36 MethyLight targets in 65 study sperm DNA samples. Left: dendrogram defining clusters; rows: 35 methylation targets; columns: 65 study samples ordered left to right on sperm concentration (samples A-G were also included in Illumina analyses (see FIG. 3)) with poor to good concentration (blue), motility (purple), and morphology (green) represented by darkest to lightest hue; body of figure: standardized PMR values represented lowest to highest as yellow to red. X=missing.



FIG. 3 shows, according to particular exemplary aspects, Results of Illumina analysis of 1,421 autosomal sequences in DNA isolated from sperm and buffy coat. Seven study sperm samples (A-G; ordered left to right on sperm concentration), screening sperm (S), two buffy coat (1-2). Level of DNA methylation scored as β-value. Color: β-value for column sample at row sequence (green: βP<0.1; yellow: 0.1≦β≦0.25; orange 0.25<β≦0.5; red: β>0.5). Ml and PI: maternally and paternally imprinted genes (black bar). Sequences assigned to tertile of median β-value among buffy coat DNA samples (I, II, III) and sorted within tertile on median βP-value among sperm DNA samples. Box 1: sequences with sperm-specific DNA methylation; Box 2: sequences with buffy coat-specific DNA methylation.





DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Overview. There have been several prior art attempts in the art to assess sperm DNA methylation together with either sperm quality or fertility outcomes. However, the measures of DNA methylation used were limited, consisting of either a nonspecific genome-wide measure [18], or small and specialized subsets of DNA methylation targets [19-21].


Specifically, in the only study prior art study addressing the relationship between DNA methylation and fertility outcomes, immunostaining was used to measure genome-wide levels of DNA methylation in samples of ejaculated sperm collected for conventional in vitro fertilization (IVF) [18], and no association was observed between sperm DNA methylation and either fertilization rate or embryo quality in 63 IVF cycles. There was, however, a possible association with pregnancy rate after transfer of good quality embryos. Interpretation of these results is limited by both small sample size and the use of a single summary measure of genome-wide DNA methylation.


Moreover, with respect to the prior art studies [19-21] with small and specialized subsets of DNA methylation targets, sequence-specific measures were used to investigate the relationship between methylation of human sperm DNA and spermatogenesis. One study assessed DNA from spermatogonia and spermatocytes microdissected from seminiferous tubules of biopsied testicular tissue with spermatogenic arrest. DNA profiles consistent with correctly established paternal imprints were reported in all samples [19]. In the remaining two studies [20 and 21], DNA profiles were measured at specific DMRs associated with each of two genes, one paternally and one materially imprinted, and the resulting profiles were related to concentration of ejaculated sperm, an indicator of sperm quality. One of these studies reported correctly erased maternal imprints and correctly established paternal imprints in DNA from sperm of low concentration [21]. By contrast, the second reported that although maternal imprinting of MEST was correctly erased in DNA from sperm of low concentration, methylation at an H19 sequence typically de novo methylated in spermatogenesis was incomplete in these samples [20]. No compelling explanation was offered for the apparently differing results of these studies. It is noteworthy, however, that each addressed sequences of only one or two imprinted genes, an extremely small and specialized subset of DNA methylation targets in the human genome. Data from these published studies could not, therefore, have revealed a disruption involving large numbers of genes, or shown that genes that are not imprinted are also affected.


Particular aspects provide methods for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and determining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject. In certain embodiments the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.


In particular aspects at least on CpG dinucleotide sequence within an amplicon is determined. In preferred aspects, the at least one amplicon sequence is selected from the group consisting of: HRAS SEQ ID NOS:20, NTF3 SEQ ID NO: 14, MT1A SEQ ID NO:16, PAX8 SEQ ID NO:13, DIRAS3 SEQ ID NO:15, PLAGL1 SEQ ID NO:19, SFN SEQ ID NO:18, SAT2CHRM1 SEQ ID NO:21, MEST SEQ ID NO:17, RNR1 SEQ ID NO:22, CYP27B1 SEQ ID NO:23 and ICAM1 SEQ ID NO:24.


Preferably, the amplicon is part of a contiguous CpG island sequence. In preferred aspects, the CpG island sequence is selected from the group consisting of: HRAS SEQ ID NOS:63, NTF3 SEQ ID NO:2, MT1A SEQ ID NO:4, PAX8 SEQ ID NO:1, DIRAS3 SEQ ID NO:3, PLAGL1 SEQ ID NO:7, SFN SEQ ID NO:6, SAT2CHRM1 SEQ ID NO:9, MEST SEQ ID NO:5, RNR1 SEQ ID NO:10, CYP27B1 SEQ ID NO:11 and ICAM1 SEQ ID NO:12.


Coordinate methylation within CpG islands. According to particular aspects, and as recognized in the relevant art, hypermethylation is coordinate within a CpG island. For Example, data (see Eckhardt et al., Nat Genet. 2006 December; 38(12):1378-85. Epub 2006 Oct. 29; incorporated by reference herein in its entirety) has been generated by analyzing methylation (using bisulfite sequencing) in CG-rich regions across entire chromosomes to provide a methylation map of the human genome (at least of the CPG rich regions thereof). To date, these data comprise methylation data of 3 complete human chromosomes (22, 20, and 6) for a variety of different tissues and cell types. Based on these data, for methylation patterns within CpG dense regions, methylation is typically found to be either present for all methylatable cytosines or none. This methylation characteristic or pattern is referred to in the art as “co-methylation” or “coordinate methylation.” The findings of this paper support a “significant correlation” of comethylation over the distance of at least 1,000 nucleotides in each direction from a particular determined CpG within a CpG dense region (see, e.g., page 2, column 2, 1st full paragraph, of Eckhardt et al publication document). Furthermore, such co-methylation forms the basis for long-standing common methods such as MSP and particular MethyLight embodiments that rely on such co-methylation (e.g., as employed herein, the primers and/or probes each typically encompass multiple CpG sequences), and has now been further confirmed over entire chromosomes by Eckhardt et al. Therefore, in view of the teachings of the present specification, there is a reasonable correlation between the claimed coordinately methylated sequences, and the recited methods and exemplary methylation marker sequences.


Measurement of DNA Methylation of the Genomic DNA of Spermatozoa at CpG Islands, DMRs of Imprinted Genes and Repetitive Elements

The present specification describes and discloses the first study ever to investigate the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. Abnormal epigenetic programming of the germ line is herein disclosed as a mechanism compromising fertility of particular men currently diagnosed with idiopathic infertility. Aspects of the present invention indicate that one or more epigenetic processes lead to abnormal spermatogenesis and compromised sperm function.


To assess sperm DNA, methylation at specific targets that are both more numerous and less specialized, a relatively large set of sequence-specific assays was selected for use in the presently disclosed studies and invention.


Specifically, DNA methylation was measured in ejaculated spermatozoa-interrogating sequences in repetitive elements, promoter CpG islands, and differentially methylated regions (DMRs) of imprinted genes. Then, to address the possible role of epigenetic programming in abnormal human spermatogenesis, sequence-specific levels of DNA methylation were related to standard measures of sperm quality.


Applicants' observations indicate a broad epigenetic abnormality of poor quality human sperm in which levels of DNA methylation are elevated at numerous sequences in several genomic contexts. Previous studies of DNA methylation in poor quality sperm interrogated only imprinted loci, measuring methylation of sequences in only one or two genes [19-21].


Aspects of the present invention provide, inter alia, compositions and methods having substantial utility for diagnosing or determining the presence of abnormal sperm or fertility (e.g., comprising at least one of abnormal sperm concentration, abnormal total normal morphology, abnormal motility, abnormal volume, and abnormal viscosity).


As described in the working Example 1, herein below, Applicants initially evaluated 294 MethyLight reactions for the presence of methylation in sperm DNA from an anonymous semen sample obtained from a sperm bank. Standard semen analysis was then conducted on samples collected by 69 men during clinical evaluation of couples with infertility. Thirty seven selected MethyLight reactions were used to assay sperm DNA from 65 of the study samples.


At many of the 37 sequences, methylation levels were elevated in DNA from poor quality sperm. For example, striking associations with each of sperm concentration, motility and morphology were observed for five sequences: HRAS, NTF3, MT1A, PAX8 and the maternally imprinted gene PLAGL1 (FIG. 1). Applicants also found elevated DNA methylation to be significantly associated with poor semen parameters for the DIRAS3 and MEST maternally imprinted genes (FIG. 1).


Associations between results of each of the 37 MethyLight assays and sperm concentration were highly significant for HRAS, NTF3, MT1A, PAX8, DIRAS3 and PLAGL1 and were also significant (somewhat less) for SFN, SAT2CHRM1 and MEST (see Table 1 of Example 1, and see also FIG. 1).


Unsupervised cluster analysis identified three distinct clusters of sequences based on DNA methylation profiles in the 65 samples (FIG. 2). The middle cluster shown in FIG. 2 includes eight of the above nine sequences (all except MT1A) individually associated with semen parameters, and includes not only three sequences that are differentially methylated on imprinted loci, but also three single copy sequences specific to non-imprinted genes, and a repetitive element, Satellite 2 (referred to herein as SAT2CHRM1).


Significantly, this surprising result indicates that sperm abnormalities may be associated with a broad epigenetic defect of elevated DNA methylation at numerous sequences of diverse types, rather than a defect of imprinting alone as previously suggested [20].


To learn more about the possible extent of this apparent defect, the ILLUMINA™ platform was used to conduct DNA methylation analysis of 1,421 sequences in autosomal loci (discussed in more detail under Example 1 herein below). Briefly, the results of the ILLUMINA™ analyses appear in FIG. 3. Box 1 of FIG. 3 identifies 19 sequences with sperm-specific DNA methylation.


Various semen parameters have been correlated herein with abnormal DNA methylation (sperm concentration; total normal morphology; motility, volume, viscosity, etc.). According to preferred aspects, three of these semen parameters show the highest correlations with abnormal DNA methylation: sperm concentration; total normal morphology; and motility. FIG. 2, for example, shows that the corresponding MLL reactions are clustered based on sperm concentration.


Particular aspects of the present invention, therefore, provide marker(s) and marker subsets having utility for determining at least one of (A) abnormal sperm concentration, (B) abnormal morphology, and (C) abnormal motility. With respect to (A), abnormal sperm concentration, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, and CYP27B1. Nine of these markers have p-values well below 0.05, and therefore are very significant. Additionally provided are the markers, RNR1 and CYP27B1, both having p-values of 0.02, and therefore also provide for utility in this respect.


With respect to (B), abnormal total motile sperm, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A (NTF3 and MT1A equally significant), SAT2CHRM1, DIRAS3, PLAGL1, MEST, PAX8, and SFN. These markers have p-values well below 0.05, and therefore are very significant. Additionally provided are the markers: RNR1 (p-value 0.04) and CYP27B1 and BDNF (both with p-value of 0.05), and therefore also provide for utility in this respect.


With respect to (C), abnormal motility, markers are provided in the following order of statistical significance from left to right, based on the p-value: MT A, MEST, NTF3, PLAGL1. Additionally provided are the markers PAX8 AND ICAM1 (both having p-values of 0.05), and therefore also provide for utility in this respect.


Improper Erasure of Pre-Existing Methylation

According to particular aspects, only sequence-specific measures of DNA methylation are expected to reveal variation at individual sites, because of the enormous number of methylation targets in the human genome. These include millions of repetitive DNA elements for which methylation is postulated to silence parasitic and transposable activity. There are also large numbers of target sequences corresponding to single copy genes. Examples include thousands of promoter CpG islands for which methylation appears to mediate expression of genes in a tissue- and lineage-specific fashion, and DMRs associated with dozens of imprinted genes for which parent-of-origin DNA methylation marks are believed to mediate monoallelic expression in somatic cells.


As disclosed herein, Applicants' high-throughput analysis addressed hundreds of DNA methylation targets, and was thus designed to reveal methylation defects.


Elevated DNA methylation could, in theory, arise from either de novo methylation or improper erasure of pre-existing methylation. Although Applicants cannot rule out the possibility that processes responsible for de novo methylation are inappropriately activated in abnormal spermatogenesis, according to particular aspects, disruption of erasure is most likely the primary mechanism underlying abnormal spermatogenesis. Widespread erasure of DNA methylation occurs in both the pre-implantation embryo and again, uniquely, in primordial germ cells around the time that they enter the genital ridge. Several factors point to disruption of the second erasure as underlying the defect(s) described herein. Primordial germ cells arise from cells of the proximal epiblast which have themselves embarked upon somatic development, as shown by expression of somatic genes [25,26]. The germ cell lineage must therefore suppress the somatic program, which in mice is accomplished in part by genome-wide erasure of DNA methylation soon after germ cells migrate to the genital ridge [27]. This erasure affects DNA methylation on single copy genes, imprinted genes and repetitive elements [27]. Therefore, disruption of the second, genital ridge erasure most likely results in the type of pattern we observe in poor quality sperm, with elevated levels of DNA methylation at DNA sequences of each of these sequence types. Further, because this second erasure is confined to primordial germ cells, Applicants further reasoned that its disruption would be compatible with normal somatic development.


In humans, primordial germ cells colonize the genital ridge at about 4.5 weeks of gestation. Applicants are not aware of data describing DNA methylation in the human germ line at this date; however, the DMR in MEST at which Applicants found elevated DNA methylation in poor quality sperm is reportedly unmethylated in the male germ line by week 24 of gestation [28]. Potential causes of disrupted erasure have not been investigated. However, weeks 4.5-24 of gestation represent post-implantation stages of development wherein fetal physiology may be influenced by maternal factors and environmental compounds that cross the placenta. Possible origins of male infertility as early as 4.5 weeks of human gestation have not been studied. However, transient in vivo chemical exposure at 7-15 days post conception, which includes the analogous stage of murine development [29,30], results in spermatogenic deficits in rats with grossly normal testes [31] and may be associated with elevated methylation of sperm DNA [32].


Taken together, the observations disclosed herein indicate for the first time that epigenetic mechanisms contribute to a substantial portion of male factor infertility, and provide novel compositions and methods for the diagnosis, detection or determination of abnormal sperm or fertility. Also provided are methods for screening for agents that cause spermatogenic deficits, abnormal sperm or fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells with at least one test agent; culturing the contacted germ cells; obtaining a sample of genomic DNA from the contacted cultured germ cells; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes spermatogenic deficits, abnormal sperm or fertility.


Example 1
Sequence-Specific Levels of DNA Methylation were Related to Standard Measures of Sperm Quality

Overview. This is the first study ever to describe the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. To assess sperm DNA methylation at specific targets that are both more numerous and less specialized, a relatively larger set of sequence-specific assays was selected for use in the present study. DNA methylation was measured in ejaculated spermatozoa-interrogating sequences in repetitive elements, promoter CpG islands, and differentially methylated regions (DMRs) of imprinted genes. Then, to address the possible role of epigenetic programming in abnormal human spermatogenesis, sequence-specific levels of DNA methylation were related to standard measures of sperm quality.


Materials and Methods

Semen samples. Study semen samples were collected by 69 consecutive men ages 22-49 years who were partners of women undergoing evaluation for infertility at the Endocrine/Infertility Clinic of the Los Angeles County/University of Southern California Keck School of Medicine Medical Center. One additional semen sample was obtained from a sperm bank. The study was approved by the Institutional Review Board of the University of Southern California. Informed consent was not required because this research involved stored materials that had previously been collected solely for non-research purposes and were anonymous to the researchers/authors.


Semen Analysis. Standard semen analysis was performed using WHO criteria and Strict Morphology as previously described [33,34]. Semen volume, sperm concentration and motility, and leukocyte count were measured using the MicroCell chamber (Conception Technologies, San Diego, Calif.). Sperm morphology was assessed with the use of prestained slides (TestSimplets, Spectrum Technologies, Healdsburgh, Calif.), and percentage of morphologically normal sperm was documented. The samples were categorized according to concentration (<5, 5-20, >20 million sperm/ml), motility (<10, 10-50, >50 total motile sperm count (×106)), and morphology (<5%, 5-14%, >14% normal) of sperm [33,35]. Presence of any white blood cells, round cells, or epithelial cells was recorded. Following semen analysis, samples were stored at −30° C. until processing for molecular analysis.


Sperm Separation from Seminal Plasma. Semen samples were allowed to thaw at 37° C. Sperm were separated from seminal plasma using ISOLATE® Sperm Separation Medium (Irvine Scientific, Santa Ana, Calif.), a density gradient centrifugation column designed to separate cellular contaminants (including leukocytes, round cells, and miscellaneous debris) from spermatozoa [24]. Separation was performed according to the manufacturer's protocol [36], and the purity of separated sperm from contaminating cells was documented by light microscopy.


DNA isolation. DNA was isolated from purified sperm as previously described [37], with 0.1×SSC added to the Lysis buffer, and samples incubated at 55° C. over night or longer to complete the lysis procedure.


Laboratory Analysis of DNA Methylation. Sodium bisulfite conversion was performed as previously described [23]. The amount of DNA in each aliquot was normalized, and a bisulfite-dependent, DNA methylation-independent control reaction was performed to confirm relative amounts of DNA in each sample. METHYLIGHT™ analyses were performed as previously described [23]. Reaction IDs and sequences of the primers and probes used in the 294 METHYLIGHT™ reactions are as previously published (see Table S1 (Sections A-B): doi:10.1371/journal.pone.0001289.s001 (0.10 MB PDF; incorporated by reference herein in its entirety). Additionally, according to particular aspects of the present invention, names of preferred markers and respective primers, probes and genomic sequences corresponding to the respective amplicons are listed below in TABLE 1.









TABLE 1







Primers and Probes for exemplary preferred MethyLight Assays.
















Genomic sequence




Forward
Reverse
Probe Oligo
corresponding to



Primer
Primer
Sequence
amplicon Sequence


Gene
(SEQ ID NO:)
(SEQ ID NO:)
(SEQ ID NO:)
(SEQ ID NO:)





HRAS
GAGCGATGACG
CGTCCACAAAA
6FAM-
CGTCCACAAAATGGTTCTGG




GAATATAAGTT
TAATTCTAAAT
CACTCTTACCC
ATCAGCTGGATGGTCAGCGC



GG
CAACTAA
ACACCGCCGAC
ACTCTTGCCCACACCGCCGG



(SEQ ID
(SEQ ID
G-BHQ-1
CGCCCACCACCACCAGCTTA



NO: 46)
NO: 47)
(SEQ ID
TATTCCGTCATCGCTC





NO: 48)
(SEQ ID NO: 20)





NTF3
TTTCGTTTTTG
CCGTTTCCGCC
6FAM-
CCCCGCCCTTGTATCTCATG



TATTTTATGGA
GTAATATTC
TCGCCACCACG
GAGGATTACGTGGGCAGCCC



GGATT
(SEQ ID
AAACTACCCAC
CGTGGTGGCGAACAGAACAT



(SEQ ID
NO: 29)
G-BHQ-1
CACGGCGGAAACGG



NO: 28)

(SEQ ID
(SEQ ID NO: 14)




NO: 30)





MT1A
CGTGTTTTCGT
CTCGCTATCGC
6FAM-
CGTGTTCCCGTGTTACTGTG



GTTATTGTGTA
CTTACCTATCC
TCCACACCTAA
TACGGAGTAGTGGGTCCGAG



CG
(SEQ ID
ATCCCTCGAAC
GGACCTAGGTGTGGACAGGG



(SEQ ID
NO: 35)
CCACT-BHQ-1
ACAGGCAAGGCGACAGCGAG



NO: 34)

(SEQ ID
(SEQ ID NO: 16)





NO: 36)





PAX8
CGGGATTTTTT
ACCTTTCCCCA
6 FAM-
CGGGACCTCCCTGTCGTACC



TGTCGTATTTG
TACTACCTCCG
ACGAACAATTC
TGAGAGGAGGGCCTGGCCCG



A
(SEQ ID
ACGAACCAAAC
TGAACTGCCCGTACACGGAG



(SEQ ID
NO: 26)
CCTCCT-BHQ-1
GCAGCATGGGGAAAGGC



NO: 25)

(SEQ ID
(SEQ ID NO: 13)





NO: 27)





DIRAS3
GCGTAAGCGGA
CCGCGATTTTA
6 FAM-
GCGCAAGCGGAATCTATGCC



ATTTATGTTTGT
TATTCCGACTT
CGCACAAAAAC
TGTTACCCACACTCCCTGCG



(SEQ ID
(SEQ ID
GAAATACGAAA
CCCCCGCACCCCGCTCCTGT



NO: 31)
NO: 32)
ACGCAAA-
GCGCAAGTCGGAATATAAAA





BHQ-1
CCGCGG





(SEQ ID
(SEQ ID NO: 15)





NO: 33)





PLAGL1
ATCGACGGGTT
CTCGACGCAAC
6FAM-
ACCGACGGGCTGAATGACAA



GAATGATAAATG
CATCCTCTT
ACTACCGCGAA
ATGGCAGATGCCGTGGGCTT



(SEQ ID
(SEQ ID
CGACAAAACCC
TGCCGCCCGCGGCAGCCAAG



NO: 43)
NO: 44)
ACG-BHQ-1
AGGATGGCTGCGCCGAG





(SEQ ID
(SEQ ID NO: 19)





NO: 45)





SFN
GAGGAGGGTTC
ATCGCACACGC
6FAM-
GAGGAGGGCTCGGAGGAGAA



GGAGGAGAA
CCTAAAACT
TCTCCCGATAC
GGGGCCCGAGGTGCGTGAGT



(SEQ ID
(SEQ ID
TCACGCACCTC
ACCGGGAGAAGGTGGAGACT



NO: 40)
NO: 41)
GAA-BHQ-1
GAGCTCCAGGGCGTGTGCGA





(SEQ ID
C





NO: 42)
(SEQ ID NO: 18)





SAT2CHR
TCGAATGGAAT
CCATTCGAATC
6FAM-
TCGAATGGAATCAACATCCA


M1
TAATATTTAAC
CATTCGATAAT
CGATTCCATTC
ACGGAAAAAAACGGAATTAT



GGAAAA
TCT
GATAATTCCGT
CGAATGGAATCGAAGAGAAT



(SEQ ID
(SEQ ID
TT-MGBNFQ
CATCGAATGGACCCGAATGG



NO: 49)
NO: 50)
(SEQ ID
(SEQ ID NO: 21)





NO: 51)





MEST
CGGCGTTCGGT
CACACTCACCT
6 FAM-
CGGCGCCCGGTGCTCTGCAA



GTTTTGTAA
ACGAAAACGAT
ACGCACCATAA
CGCTGCGGCGGGCGGCATGG



(SEQ ID
CTC
CCGCGTTATCC
GATAACGCGGCCATGGTGCG



NO: 37)
(SEQ ID
CATACC-BHQ-1
CCGAGATCGCCTCCGCAGGT




NO: 38)
(SEQ ID
GAGTGTG





NO: 39)
(SEQ ID NO: 17)





RNR1
CGTTTTGGAGA
AAACAACGCCG
6 FAM-
CGCTCTGGAGACACGGGCCG



TACGGGTCG
AACCGAA
ACCGCCCGTAC
GCCCCCTGCGTGTGGCACGG



(SEQ ID
(SEQ ID
CACACGCAAA-
GCGGCCGGGAGGGCGTCCCC



NO: 52)
NO: 53)
BHQ-1
GGCCCGGCGCTGCTC





(SEQ ID
(SEQ ID NO:22)





NO: 54)





CYP27B1
GGGATAGTTAG
CCGAATATAAC
6FAM-
GGGACAGCCAGAGAGAACGG



AGAGAACGGAT
CACACCGCC
CCAACCTCAAC
ATGCCCATGAAATAAGGAAA



GTTT
(SEQ ID
TCGCCTTTTCC
AGGCGAGTTGAGGCTGGGGG



(SEQ ID
NO: 56)
TTATTTCA-
CGGTGTGGCTACACTCGG



NO: 55)

BHQ-1
(SEQ ID NO: 23)





(SEQ ID





NO: 57)





ICAM1
GGTTAGCGAGG
TCCCCTCCGAA
6 FAM-
GGCCAGCGAGGGAGGATGAC



GAGGATGATT
ACAAATACTAC
TTCCGAACTAA
CCTCTCGGCCCGGGCACCCT



(SEQ ID
AA
CAAAATACCCG
GTCAGTCCGGAAATAACTGC



NO: 58)
(SEQ ID
AACCGAAA-
AGCATTTGTTCCGGAGGGGA




NO: 59)
BHQ-1
(SEQ ID NO: 24)





(SEQ ID





NO: 60)









Thirty-five METHYLIGHT™ reactions were selected for analysis of study sperm DNA samples based on cycle threshold (C(t)) values from analysis of the anonymous sample of sperm DNA. In brief, C(t) value is the PCR cycle number at which the emitted fluorescence is detectable above background levels. The C(t) value is inversely proportional to the amount of each methylated locus in the PCR reaction well, such that a low C(t) value suggests that the interrogated sequence is highly methylated. C(t) values of 35 or less were interpreted as an indication that a given sequence was methylated in the anonymous sample and selected 33 reactions on this basis. Three additional reactions were included, for which C(t) values slightly exceeded 35. Two (CYP27B1 and HOXA10) were selected based on gene function potentially related to fertility, and one (a non-CpG island reaction for IFNG) based on prior observation by applicants of hypomethylation in tumor versus normal tissue. When multiple reactions for a single locus resulted in C(t) values of less than 35, we selected only the reaction with the lowest C(t) value. Results of METHYLIGHT™ analysis were scored as PMR values as previously defined [23]. Following METHYLIGHT™ analyses, DNA remained from a subset of abnormal samples with greater sperm concentration. ILLUMINA™ analysis was performed on sodium bisulfite-converted sperm DNA of selected remaining samples, the anonymous semen sample, and purchased buffy coat DNA (HemaCare® Corporation, Van Nuys, Calif.) at the USC Genomics Core. Sodium bisulfite conversion for ILLUMINA™ assay was performed using the EZ-96 DNA Methylation Kit™ (ZYMO Research) according to manufacturer's protocol. Illumina Methods and reagents are as previously described [38]. The primer names and probe IDs are listed as previously published (see Table S2; doi:10.1371/journal.pone.0001289.s002 (0.20 MB PDF; incorporated by reference herein in its entirety), identifying 1,421 autosomal sequences of the GoldenGate Methylation Cancer Panel 1, more fully described elsewhere [39,40]. Results of ILLUMINA™ assays were scored as β-values [38]. Relevant amplicons and CpG islands are provided below in TABLE 2 below.


Statistical association analyses of METHYLIGHT™ data. Associations between the ranked METHYLIGHT™ data and categorized semen values (Table 1) were tested using simple linear regression, with the semen characteristic categories scored as 0: low, 1: mid, 2: high. For selected sequences, boxplots of the methylation values (on the log(PMR+1) scale) are shown in FIG. 1. The top and bottom of the box denote the 75th and 25th percentiles, and the white bar the median. Whiskers are drawn to the observation farthest from the box that lies within 1.5 times the distance from the top to the bottom of the box, with values falling outside the whiskers denoted as lines. Results of this analysis were included in FIG. 1 for sequences associated with sperm concentration using the Benjamini and Hochberg procedure [41] to control the false discovery rate at 5%.









TABLE 2





Exemplary, preferred amplicons and CpG islands





















Reaction
HUGO Gene
Previously
Source of
UniGene
Reaction
Alternate Gene


Number
Nomenclature
Published?
published reaction
Number
ID
Name





HB-144
HRAS
Yes
Widschwendter, M.
Hs.37003
H-HRAS-M1B
V-Ha-ras Harvey rat





et al Cancer Res


sarcoma viral





64, 3807-3813 (2004)


oncogene homolog








(HRAS); HRAS 1


HB-251
NTF3
Yes
Weisenberger, D. J.
Hs.99171
H-NTF3-M1B
Neurotrophin 3





et al Nature Genet





38, 787-793 (2006).


HB-205
MT1A
Yes
Weisenberger, D. J.
Hs.655199
H-MT1A-M1B
Metallothionein





et al Nature Genet


1A/Metallothionein-I





38, 787-793 (2006).


HB-212
PAX8
No

Hs.469728
H-PAX8-M3B
Paired Box Gene 8/








PAX8, Paired








Domain Gene 8,








PPARG Fusion Gene


HB-043
DIRAS3
Yes
Fiegl, H. et al
Hs.194695
H-DIRAS3-M1B
Ras homolog gene





Cancer Epidemiol


family, member





BioMark Prev


I/NOEY2; DIRAS





13, 882-888 (2004)


family, GTP-binding








RAS-like 3 (ARHI)


HB-199
PLAGL1
Yes
Weisenberger, D. J.
Hs.444975
H-PLAGL1-M1B
Pleiomorphic





et al Nature Genet


adenoma gene-like





38, 787-793 (2006).


1/LOT1/Zac1


HB-174
SFN
Yes
Weisenberger, D. J.
Hs.523718
H-SFN-M1B
Stratifin/14-3-3





et al Nature Genet


protein sigma





38, 787-793 (2006).


HB-289
SAT2CHRM1
Yes
Weisenberger, D. J.
N/A
H-SAT2CHRM1-M1M
SATELLITE 2





et al Nucleic Acids


CHROMOSOME 1





Res 33, 6823-6836 (2005)


HB-493
MEST
No

Hs.270978
H-MEST-M2B
PEG1


HB-071
RNR1
Yes
Muller, H. M. et al.
N/A
H-RNR1-M1B
Ribosomal RNA





Cancer Lett209,





231-236 (2004)


HB-076
ICAM1
Yes
Ehrlich, M. et al.
Hs.643447
H-ICAM1B-M1B
Intercellular





Oncogene 21,


adhesion molecule 1





6694-6702 (2002)


(CD54), human








rhinovirus receptor


HB-223
CYP27B1
Yes
Weisenberger, D. J.
Hs.524528
H-CYB27B1-M1B
cytochrome P450,





et al Nature Genet


family 27, subfamily





38, 787-793 (2006).


B, polypeptide 1




















GenBank
mRNA


Transcription


Reaction
HUGO Gene
Chromosomal
Accession
accession
Parallel/
Length of
Start (GenBank


Number
Nomenclature
Location
Number
number
Antiparallel
Sequence (bp)
Numbering)





HB-144
HRAS
11p15.5
AC137894
NM_176795
Antiparallel
165000
157238


HB-251
NTF3
12p13
AC135585
NM_002527
Parallel
35700
7048


HB-205
MT1A
16q13
AC106779
NM_005946
Parallel
158297
18787


HB-212
PAX8
2q12
AC016683
S77905
Antiparallel
179937
116171


HB-043
DIRAS3
1p31
AF202543
U96750
Parallel
7242
2053


HB-199
PLAGL1
6q24-q25
AL109755
U72621
Antiparallel
89669
53085


HB-174
SFN
1p35.3
AF029081
BC023552
Parallel
10034
8563


HB-289
SAT2CHRM1
1
X72623
N/A
Parallel
1352
N/A


HB-493
MEST
7q32.2
NC_000007
NM_177524
Parallel
20084
5893


HB-071
RNR1
13p12
X01547
N/A
Parallel
850
482


HB-076
ICAM1
19p13.3-
AC011511
BC015969
Parallel
156503
85732




p13.2


HB-223
CYP27B1
12q14.1
AY288916
AB005038
Parallel
7587
1324




















Amplicon Start
Amplicon End
Mean






Location Relative
Location Relative
Distance from




Amplicon
Amplicon
to Transcription
to Transcription
Transcription


Reaction
HUGO Gene
Location Start
Location End
Start (bp,
Start (bp,
Start (bp,


Number
Nomenclature
(GenBank Numbering)
(GenBank Numbering)
GenBank sequence)
GenBank Sequence)
GenBank sequence)





HB-144
HRAS
156015
155920
1223
1318
1271


HB-251
NTF3
7503
7576
455
528
492


HB-205
MT1A
18175
18254
−612
−533
−573


HB-212
PAX8
72708
72632
43463
43539
43501


HB-043
DIRAS3
1953
2038
−100
−15
−58


HB-199
PLAGL1
53045
52969
40
116
78


HB-174
SFN
8848
8928
285
365
325


HB-289
SAT2CHRM1
1074
1153
N/A
N/A
N/A


HB-493
MEST
6057
6144
164
251
207


HB-071
RNR1
219
293
−263
−189
−226


HB-076
ICAM1
85597
85676
−135
−56
−96


HB-223
CYP27B1
1728
1805
404
481
443


















Amplicon
Amplicon
UCSC
UCSC
Location of


Reaction
HUGO Gene
Location Start
Location End
Strand
Assembly
Amplicon in Gene


Number
Nomenclature
(UCSC Numbering)
(UCSC Numbering)
(+/−)
Date
(e.g., promoter, exon)





HB-144
HRAS
524232
524327
+
May 2004
Exon2


HB-251
NTF3
5473982
5474055
+
May 2004
Exon1


HB-205
MT1A
55229471
55229550
+
May 2004
Promoter


HB-212
PAX8
113709183
113709259
+
May 2004
Exon 9


HB-043
DIRAS3
68228349
68228434

May 2004
Promoter (in Exon3)


HB-199
PLAGL1
1443711135
144371211
+
May 2004
Exon1


HB-174
SFN
26874056
26874136
+
May 2004
Exon1


HB-289
SAT2CHRM1
no perfect
no perfect

May 2004
N/A




match
match


HB-493
MEST
129919339
129919425
+
March 2006
exon1/intron1


HB-071
RNR1
N/A
N/A

May 2004
Promoter


HB-076
ICAM1
10242630
10242709
+
May 2004
Promoter


HB-223
CYP27B1
56446731
56446808

May 2004
Exon1



















500 (approx. ±


Estimated CpG Island
Location of
Location of




250) bp sequence
CpG

Length (GenBank)
CpG Island
CpG Island


Reaction
HUGO Gene
comprising amplicon
Island

(SEQ ID NO:)
Start (GenBank
End (GenBank


Number
Nomenclature
(Genbank sequence)
yes/no

(>0.6 CpG:GpC)
numbering)
numbering)

















HB-144
HRAS
155726-156225
(Yes)
3354
(SEQ ID NO: 63)
156171
159524


HB-251
NTF3
7301-7800
Yes
609
(SEQ ID NO: 2)
7246
7854


HB-205
MT1A
18201-18700
Yes
1209
(SEQ ID NO: 4)
17842
19050


HB-212
PAX8
72426-72925
Yes
1250
(SEQ ID NO: 1)
73859
72610


HB-043
DIRAS3
1751-2250
Yes
552
(SEQ ID NO: 3)
1804
2355


HB-199
PLAGL1
52751-53250
Yes
1478
(SEQ ID NO: 7)
53667
52190


HB-174
SFN
8637-9136
Yes
661
(SEQ ID NO: 6)
8684
9344


HB-289
SAT2CHRM1
 851-1350
(Yes)
(500
(SEQ ID NO: 9))
N/A
N/A


HB-493
MEST

Yes
2799
(SEQ ID NO: 5)
4293
7091


HB-071
RNR1
 1-500
yes
850
(SEQ ID NO: 10)
1
850


HB-076
ICAM1
85376-85875
Yes
2038
(SEQ ID NO: 12)
84047
86084


HB-223
CYP27B1
1501-2000
yes
747
(SEQ ID NO: 11)
1345
2091














Reaction
HUGO Gene
Amplicon Start relative
Reaction
Bisulfite Conversion:


Number
Nomenclature
to CGI start
Type
Top/Bottom Strand





HB-144
HRAS
N/A
Methylated
Bottom


HB-251
NTF3
257
Methylated
Top


HB-205
MT1A
333
Methylated
Top


HB-212
PAX8
1151
Methylated
Top


HB-043
DIRAS3
149
Methylated
Top


HB-199
PLAGL1
622
Methylated
Top


HB-174
SFN
116
Methylated
Top


HB-289
SAT2CHRM1
N/A
Methylated
Top


HB-493
MEST
1764
Methylated
Top


HB-071
RNR1
219
Methylated
Top


HB-076
ICAM1
1685
Methylated
Top


HB-223
CYP27B1
383
Methylated
Top









Statistical cluster analysis of METHYLIGHT™ data. Hierarchical cluster analysis of 36 loci was performed, using correlation to measure the distance between any two loci and Ward's method of linkage [42]. SASH1 was omitted from the cluster analysis because only a single sample showed positive methylation. The 65 study samples were ordered from left to right by increasing semen concentration.


Display of ILLUMINA™ data. ILLUMINA™ data were displayed graphically in FIG. 3 with results for study samples ordered left to right in columns by sperm concentration. Rows corresponding to each of the 1,421 sequences were divided into three tertiles of median β-value among buffy coat DNA samples (I, II, III), then sorted within tertile by median β-value among all sperm DNA samples. Box 1 contains all sequences tertile I with median β-value among sperm DNA samples >0.5; box 2 contains all sequences within tertile III with median β-value among sperm DNA samples <0.1. Maternal or paternal imprinting status of each locus was scored according to the categorization of R. Jirtle [43]. All sequences specific to genes imprinted in humans were individually reviewed to determine whether they have been reported as belonging to a DMR for which parent of origin marks are maintained by DNA methylation [44-66]. Sequences meeting these criteria were scored as maternally imprinted (MI) or paternally imprinted (PI) with an indicator set for each on FIG. 3.


Results

Standard semen analysis was conducted on samples collected by 69 men during clinical evaluation of couples with infertility. Among the 69 samples, semen volume ranged from 0.5 to 7.8 ml; total count 0 to 864 million sperm; total motile count 0 to 396.3 million sperm; and percentage normal sperm forms 0 to 26%. Four samples were found to be azoospermic and excluded from subsequent analysis of DNA methylation.


Applicants evaluated 294 METHYLIGHT™ reactions for the presence of methylation in sperm DNA from an anonymous semen sample obtained from a sperm bank. Primers and probes were as previously published (see Table S1 (Sections A-B), found at doi:10.1371/journal.pone.0001289.s001 (0.10 MB PDF); incorporated by reference herein in its entirety; Primers, probes and reaction IDs for 294 MethyLight Assays: Group A, used in screening procedure and analysis of 65 study samples; Group B, used only in screening procedure; and Group C, new assays designed to DMRs of maternally imprinted genes and used only in analysis of 65 study samples.


The 35 selected reactions of Table S1A were used to assay sperm DNA from 65 study samples.


At many of the 35 sequences methylation levels were elevated in DNA from poor quality sperm. For example, striking associations with each of sperm concentration, motility and morphology were observed for five sequences: HRAS, NTF3, MT1A, PAX8 and PLAGL1 (FIG. 1).


PLAGL1 is maternally imprinted. Our METHYLIGHT™ assay for this gene interrogates a differentially methylated CpG island [22]. To determine whether other maternally imprinted genes are methylated in abnormal sperm, METHYLIGHT™ was used to interrogate the differentially methylated sequence of DIRAS3. At this sequence greater DNA methylation was also observed in samples with poorer semen parameters (FIG. 1, row 6). These results appeared to conflict with those of Marques et al [20] who reported no association between low sperm count and methylation of a DMR in a third maternally imprinted gene, MEST. We therefore used METHYLIGHT™ to assess the methylation status of a differentially methylated MEST sequence investigated by these authors [20], and found elevated DNA methylation to be significantly associated with poor semen parameters (FIG. 1), in agreement with our PLAGL1 and DIRAS3 results.


After correction for multiple comparisons, estimated associations between results of each of the 37 METHYLIGHT™ assays and sperm concentration were highly significant for HRAS, NTF3, MT1A, PAX8, DIRAS3 and PLAGL1 and marginally significant for SFN, SAT2CHRM1 and MEST (Table 3, FIG. 1).









TABLE 3







Trend p-values for associations between MethyLight


results and semen parameters (see Methods).









Parameter of Standard Semen Analysis










MethyLight Reaction
Concentration
Motility
Morphology













*HRAS.HB.144
0.00006
0.00001
0.06265


*NTF3.HB.251
0.00029
0.00026
0.00464


MT1A.HB.205
0.00048
0.00026
0.00119


*PAX.8.HB.212
0.00086
0.00405
0.05143


*DIRAS3.HB.043
0.00109
0.00159
0.06016


*PLAGL1.HB.199
0.00213
0.00255
0.01951


*SFN.HB.174
0.00307
0.00804
0.79899


*SAT2CHRM1.HB.289
0.00448
0.00109
0.06793


*MEST.HB.493
0.00711
0.00373
0.00359


RNR1.HB.071
0.02
0.04
0.89


CYP27B1
0.02
0.05
0.10


MADH3.HB.053
0.09
0.15
0.35


BDNF.HB.257
0.11
0.05
0.26


PSEN1.HB.263
0.16
0.27
0.81


CGA.HB.237
0.23
0.34
0.93


SERPINB5.HB.208
0.23
0.64
0.80


ICAM1.HB.076
0.24
0.29
0.05


MINT1.HB.161
0.24
0.60
0.34


PTPN6.HB.273
0.24
0.09
0.08


ALU.HB.296
0.25
0.29
0.87


CYP1B1.HB.239
0.28
0.42
0.61


SP23.HB.301
0.28
0.48
0.48


IFNG.HB.311
0.33
0.22
0.93


C9.HB.403
0.37
0.35
0.89


GP2.HB.400
0.41
0.39
0.94


GATA4.HB.325
0.45
0.20
0.12


UIR.HB.189
0.48
0.47
0.70


TFF1.HB.244
0.48
0.96
0.93


LDLR.HB.219
0.51
0.39
0.11


SASH1.HB.085
0.51
0.15
0.15


ABCB1.HB.051
0.54
0.27
0.16


HOXA10.HB.270
0.63
0.84
0.13


MTHFR.HB.058
0.70
0.38
0.43


LINE1.HB.330
0.87
0.47
0.14


LZTS1.HB.200
0.90
0.95
0.73


SMUG1.HB.086
0.90
0.36
0.76



IGF2.HB.345

0.91
0.71
0.11





*Belongs to cluster 2 (see FIG. 2).



Assay interrogates a non-differentially methylated sequence.



Trends were assessed over the following categories of semen parameters: Concentration (<5, 5-20, >20 × 106 sperm per ml), Morphology (<5%, 5-14%, >14% normal sperm forms), Motility (<10, 10-50, >50 total motile sperm count (×106)).






Applicants then subjected METHYLIGHT™ data from 36 of the assays to unsupervised cluster analysis. (Data for SASH1 were not included, because methylation at this sequence was detected in only one sample.) This analysis identified three distinct clusters of sequences based on DNA methylation profiles in the 65 samples (FIG. 2). Notably, the middle cluster shown in FIG. 2 includes eight of the nine sequences (all except MT1A) individually associated with semen parameters. This middle cluster includes not only three sequences that are differentially methylated on imprinted loci, but also three single copy sequences specific to non-imprinted genes, and a repetitive element, Satellite 2 [23] (reaction named SAT2CHRM1).


Significantly, this surprising result indicates that sperm abnormalities may be associated with a broad epigenetic defect of elevated DNA methylation at numerous sequences of diverse types, rather than a defect of imprinting alone as previously suggested [20].


To learn more about the possible extent of this apparent defect, the ILLUMINA™ platform was used to conduct DNA methylation analysis of 1,421 sequences in autosomal loci. Included in this analysis was: DNA from the anonymous sperm sample used in the METHYLIGHT™ screen (FIG. 3, columns S); two purchased samples of buffy coat DNA allowing for observation of methylation patterns in somatic cells (FIG. 3, columns 1-2), and seven study sperm DNA samples remaining after METHYLIGHT™ analysis (FIGS. 2-3, columns A-G).


Results of ILLUMINA™ analyses appear in FIG. 3. A large number of genes were similarly methylated in both sperm DNA and buffy coat DNA (blue regions on the left bar, I; red regions on the right bar, III), while others tended to be more methylated in DNA isolated from only one of these cell types. Boxes enclose sequences for which we observed particularly strong patterns of cell type-specific methylation. Box 1 identifies 19 sequences with sperm-specific DNA methylation. At these sequences, methylation profiles of all DNA from samples of study sperm (A-G) closely resemble those from the anonymous sperm sample and differ greatly from those of buffy coat DNA. Box 2 identifies 102 sequences with buffy coat-specific DNA methylation. This set is larger in number than the sperm-specific set, as expected, given that sperm DNA is reportedly hypomethylated compared with somatic cell DNA [14]. The buffy coat-specific set comprises 7.2% of the 1,421 sequences including the majority of DMRs associated with imprinted genes that are on the Illumina panel. At many buffy coat-specific sequences, DNA methylation was elevated in study sperm DNA, most notably in sample A that had been isolated from sperm with the lowest concentration among samples A-G. Methylation of sample A DNA is elevated (β>0.1) at 76 of the 102 sequences in box 2, including all 10 that are known DMRs associated with imprinted genes.


Several factors assure us that our observations did not arise from somatic cell contamination of separated sperm samples [21]. Somatic cells are far larger than sperm and readily identified by microscopic evaluation of semen samples. Even if somatic cells are present in the neat ejaculate, the ISOLATE® sperm separation technique is specifically designed to separate spermatozoa from somatic cells and miscellaneous debris [24]. Moreover, although microscopic evaluation of semen samples conducted before sperm separation identified white blood cells in five of the 65 neat semen samples, excluding results on these five samples from statistical analyses had minimal effect on associations between DNA methylation and semen parameters, and DNA from these samples were excluded from ILLUMINA™ assays.


Various semen parameters have been correlated with abnormal DNA methylation (sperm concentration; total normal morphology; motility, volume, viscosity, etc.). According to preferred aspects, three of these semen parameters show the highest correlations with abnormal DNA methylation: sperm concentration; total normal morphology; and motility. FIG. 2, for example, shows that the corresponding MLL reactions are clustered based on sperm concentration.


Particular preferred aspects, therefore, provide marker(s) and marker subsets having utility for determining at least one of abnormal sperm concentration, abnormal morphology, and abnormal motility.


In particular aspects, with respect to (A) abnormal sperm concentration, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, and MEST. All of these nine markers have p-values well below 0.05, and therefore, all nine are very significant. Additionally provided are two more markers, RNR1 and CYP27B1, both have p-value of 0.02, that are therefore also of utility in this respect.


In particular aspects, with respect to (B) abnormal total motile sperm, markers are provided in the following order of statistical significance from left to right, based on the p-value: HRAS, NTF3, MT1A (NTF3 and MT1A equally significant), SAT2CHRM1, DIRAS3, PLAGL1, MEST, PAX8, & SFN. Again, these have very significant p-values. Additionally provided are three more markers: RNR1 (p-value 0.04) and CYP27B1, BDNF, both with p-value of 0.05, that are therefore also of utility in this respect.


In particular aspects, with respect to (C) abnormal motility, markers are provided in the following order of statistical significance from left to right, based on the p-value: MT1A, MEST, NTF3, PLAGL1. Additionally, PAX8 AND ICAM1 both have p-values of 0.05, and are thus also of utility in this respect.


Example 2
Additional Aspects Provide Methods for Screening for Agents that Cause Spermatogenic Deficits, Abnormal Sperm or Abnormal Fertility
Overview

As stated herein above, this is the first study ever to describe the epigenetic state of abnormal human sperm using an extensive panel of DNA methylation assays. According to additional aspects, Applicants data has provided novel methylation-based markers for abnormal human sperm and/or fertility.


As recognized in the art, transient in vivo chemical exposure at 7-15 days post conception, which includes the analogous stage of murine development [29,30], results in spermatogenic deficits in rats with grossly normal testes [31] but likely associated with elevated methylation of sperm DNA [32].


According to additional aspects, therefore, Applicants' data provides for methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility. In particular aspects, ES-cell derived primordial germ cells are exposed to chemical test agents, followed by CpG methylation analysis as described and provided for herein, to allow for a high-throughput screening assay to test and identify agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility. Culturing of embryonic stem (ES) cells to efficiently provide for primordial germ cells is known in the art. For example, human embryonic stem (ES) cells are propagated on mouse embryo fibroblast feeder cells as described (67). A multistep induction procedure incorporating several previously described protocols can be used to convert ES cells into primordial germ cells at high efficiency. For example, ES cells are treated with bone morphogenetic protein-2 for a brief 24 period in combination with activin and FGF-2 in chemically defined medium. After 24 hours the BMP-2 is removed and retinoic acid is added. As will be appreciated in the art, a range of doses of each factor may be employed in a matrix design over a variable time course to optimize the yield of c-kit positive/placental alkaline phosphatase positive cells. These cells are isolated by flow cytometry and subjected to Q-RTPCR to analyze for the presence of primordial germ cell and gonocyte specific genes such as VASA. According to particular aspects, up to 10% of the treated cells are vasa positive following optimal treatment. Primordial germ cells and gonocytes may also be isolated from embryonic and fetal gonads by the use of c-kit and placental alkaline phosphatase in combination with flow cytometry, following collagenase and Tryple Express™ digestion of the tissue.


Particular aspects, therefore, provide methods for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells; contacting the germ cells or descendants thereof, with at least one test agent; culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development; obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof; determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; and identifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility. In certain embodiments, the determined methylation status of the at least one CpG sequence is hypermethylation. In preferred embodiments, the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.


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Claims
  • 1. A method for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject;determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; anddetermining, based on the methylation status of the at least one CpG sequence, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject.
  • 2. The method of claim 1, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
  • 3. The method of claim 1, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
  • 4. The method of claim 3, wherein treating comprises use of bisulfite treatment of the DNA.
  • 5. The method of claim 1, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.
  • 6. The method of claim 1, wherein abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, abnormal total normal morphology, abnormal volume, and abnormal viscosity.
  • 7. The method of claim 6, wherein abnormal sperm comprises at least one of abnormal sperm concentration, abnormal motility, and abnormal total normal morphology.
  • 8. The method of claim 7, comprising determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8 and PLAGL1.
  • 9. The method of claim 8, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, and PLAGL1 SEQ ID NOS:7 and 19.
  • 10. A method for determining or diagnosing abnormal sperm or fertility, comprising: obtaining a sample of human sperm DNA from a test subject;determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence from each of a repetitive DNA element sequence group, a maternally imprinted gene sequence group, and a non-imprinted gene sequence group; anddetermining, based on the methylation status of the at least one CpG sequence from each of the groups, the presence or diagnosis of abnormal sperm or fertility with respect to the test subject.
  • 11. The method of claim 10, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
  • 12. The method of claim 10, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
  • 13. The method of claim 12, wherein treating comprises use of bisulfite treatment of the DNA.
  • 14. The method of claim 10, wherein the at least one gene sequence from a repetitive element group comprises at least one selected from the group consisting of SAT2CHRM1 SEQ ID NOS:9 and 21.
  • 15. The method of claim 10, wherein the at least one gene sequence from a maternally imprinted gene group comprises at least one selected from the group consisting of PLAGL1 SEQ ID NOS:7 and 19, MEST SEQ ID NOS:5 and 17, and DIRAS3 SEQ ID NOS:3 and 15.
  • 16. The method of claim 10, wherein the at least one gene sequence from a non-imprinted gene group comprises at least one selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, SFN SEQ ID NOS:6 and 18, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.
  • 17. A method for screening for agents that cause spermatogenic deficits, abnormal sperm or abnormal fertility comprising: obtaining human ES-cell derived primordial germ cells;contacting the germ cells or descendants thereof, with at least one test agent;culturing the contacted germ cells or the descendants thereof under conditions suitable for germ cell proliferation or development;obtaining a sample of genomic DNA from the contacted cultured germ cells or the descendants thereof;determining, using the genomic DNA of the sample, the methylation status of at least one CpG dinucleotide sequence of at least one gene sequence selected from the group consisting of HRAS, NTF3, MT1A, PAX8, DIRAS3, PLAGL1, SFN, SAT2CHRM1, MEST, RNR1, CYP27B1 and ICAM1; andidentifying, based on the methylation status of the at least one CpG sequence, at least one test agent that causes at least one of spermatogenic deficits, abnormal sperm, and abnormal fertility.
  • 18. The method of claim 17, wherein the determined methylation status of the at least one CpG sequence is hypermethylation.
  • 19. The method of claim 17, wherein determining the methylation status of at least one CpG dinucleotide sequence comprises treating the genomic DNA, or a fragment thereof, with one or more reagents to convert 5-position unmethylated cytosine bases to uracil or to another base that is detectably dissimilar to cytosine in terms of hybridization properties.
  • 20. The method of claim 19, wherein treating comprises use of bisulfite treatment of the DNA.
  • 21. The method of claim 17, wherein the at least one gene sequence is selected from the group consisting of HRAS SEQ ID NOS:63 and 20, NTF3 SEQ ID NOS:2 and 14, MT1A SEQ ID NOS:4 and 16, PAX8 SEQ ID NOS:1 and 13, DIRAS3 SEQ ID NOS:3 and 15, PLAGL1 SEQ ID NOS:7 and 19, SFN SEQ ID NOS:6 and 18, SAT2CHRM1 SEQ ID NOS:9 and 21, MEST SEQ ID NOS:5 and 17, RNR1 SEQ ID NOS:10 and 22, CYP27B1 SEQ ID NOS:11 and 23 and ICAM1 SEQ ID NOS:12 and 24.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is claims the benefit of priority to U.S. Provisional Patent Application Ser. No. 60/985,170 filed 2 Nov. 2007, and incorporated by reference herein in its entirety.

FEDERAL FUNDING ACKNOWLEDGEMENT

This work was at least in part supported by the Southern California Environmental Health Sciences Center (grant # 5P30ES007048) funded by the National Institute of Environmental Health Sciences. The United States government therefore has certain rights in the invention.

Provisional Applications (1)
Number Date Country
60985170 Nov 2007 US