Genetic test for liver copper accumulation in dogs

Information

  • Patent Grant
  • 12227805
  • Patent Number
    12,227,805
  • Date Filed
    Monday, June 28, 2021
    3 years ago
  • Date Issued
    Tuesday, February 18, 2025
    2 days ago
Abstract
The present disclosure provides methods of determining the susceptibility of a dog to liver copper accumulation, comprising detecting in a biological sample obtained from the dog the presence or absence in the genome of the dog of one or more polymorphisms, and methods of treating or breeding the dog based on such determination.
Description
SEQUENCE LISTING

The specification incorporates by reference the Sequence Listing submitted herewith via EFS on Jun. 28, 2021. Pursuant to 37 C.F.R. § 1.52(e)(5), the Sequence Listing text file, identified as 069269_0466_SL.txt, is 85,750 bytes and was created on Jun. 28, 2021. The Sequence Listing, electronically filed herewith, does not extend beyond the scope of the specification and thus does not contain new matter.


FIELD OF THE INVENTION

The invention relates to a method of determining the susceptibility of a dog to, or the likelihood that a dog is protected from, liver copper accumulation and copper-associated liver disease.


BACKGROUND OF THE INVENTION

Copper is an important trace mineral for a number of metabolic processes within the body and, as such, is an essential part of the diet. Once absorbed through the gut, copper is mainly stored in the liver although it can also be found in other tissues such as bone marrow, muscle and spleen. As well as storing copper, the liver plays a central role in coordinating the transport and excretion of copper via ceruloplasmin and the bile salts respectively. Generally, deficiencies of copper are a more common issue that toxicities. However, toxicities do occur and can have serious implications for an affected animal.


Although liver diseases are uncommon in dogs, one of its most common forms is chronic hepatitis (CH). CH is a histologic diagnosis, characterised by the presence of fibrosis, inflammation, and hepatocellular apoptosis and necrosis. Cirrhosis can result as the end stage of the disease. One of the causes of CH is hepatic copper accumulation.


Hepatic copper accumulation can result from increased uptake of copper, a primary metabolic defect in hepatic copper metabolism, or from altered biliary excretion of copper. In the latter case, copper toxicity is secondary to hepatic inflammation, fibrosis, and cholestasis, although it is unclear to what extent this occurs in the dog. In secondary copper storage disease, copper accumulation is mainly restricted to periportal parenchyma and hepatic copper concentrations are lower than accumulation in familial storage diseases. Whilst, the nature of the initiating factor(s) and of the sensitizing antigen is unknown, immunological abnormalities and morphologic features observed in primary biliary cirrhosis are concurrent with an immune mediated mechanism.


The small intestine is recognized as the main site of dietary copper absorption in mammals. Transport from the intestinal lumen into intestinal mucosa is a carrier-mediated process involving a saturable transport component. Once in mucosal cells, approximately 80% of the newly absorbed copper is in the cytosol, mainly bound to metallothioneins (MT). These are low molecular weight inducible proteins with many functions including homeostasis, storage, transport and detoxification of metals. After passage through the enterocytes, copper enters the portal circulation where it is bound to carrier proteins peptides and amino acids and is transported to the liver with lesser amounts entering the kidney. In most mammals, copper is excreted easily, and the main route of excretion of copper is the bile.


Dogs with excessive hepatic copper accumulation are typically treated with D-penicillamine, a potent copper chelator. Ultimately however, the most successful treatment available for dogs with CH is liver transplantation.


The genetic basis for hepatic copper accumulation is unknown. This is made difficult by the fact that copper is involved in numerous different biological pathways, each of which is highly complex and involves a large number of genes.


WO 2009/044152 A2 discloses a method of determining the susceptibility of a dog to liver copper accumulation comprising detecting the presence or absence of (a) a polymorphism in the GOLGAS, ATP7a or UBLS gene of the dog that is indicative of susceptibility to liver copper accumulation and/or (b) a polymorphism in linkage disequilibrium with a said polymorphism (a), and thereby determining the susceptibility of the dog to liver copper accumulation.


WO 2010/038032 A1 and WO 2010/116137 A1 disclose further polymorphisms for use in a method of determining the susceptibility of a dog to liver copper accumulation. They also disclose polymorphisms for use in a method of determining the likelihood that a dog is protected from liver copper accumulation.


SUMMARY OF THE INVENTION

The inventors have discovered a number of polymorphisms in the genome of the dog that are associated with susceptibility to liver copper accumulation. They have also discovered polymorphisms in the genome of the dog that are associated with protection from liver copper accumulation. The discovery of these polymorphisms provides the basis for a test to predict the susceptibility of a dog to, or the likelihood of protection of a dog from, liver copper accumulation by screening for the polymorphisms. The predictive power of the test can be magnified using models that involve combining the results of detecting one or more of the defined polymorphisms. A genetic test which combines the results of detecting one or more polymorphisms indicative of protection from liver copper accumulation with the results of detecting one or more polymorphisms indicative of susceptibility to liver copper accumulation in dogs would be particularly informative with regards to the likelihood that a dog is at risk of liver copper accumulation.


The accumulation of copper in the liver of a dog may lead to one or more diseases or conditions of the liver that are attributable to high liver copper. For example, high liver copper can lead to chronic hepatitis, liver cirrhosis and ultimately liver failure. The invention thus enables dogs to be identified which are at risk of developing, or are not protected from, such liver diseases or conditions that are associated with high copper. Once the susceptibility of a dog to liver copper accumulation has been identified, or once a dog has been identified as not having one or more mutations indicative of protection from liver copper accumulation, it is possible to identify suitable preventative measures for that dog, with the aim of maintaining the liver copper level at a low or normal level, such as by administering a low copper foodstuff (e.g. the foodstuff disclosed in WO 2009/044152 A2). Furthermore, dogs that are identified as not having mutations associated with susceptibility to liver copper accumulation, or that are identified as having mutations associated with protection from liver copper accumulation, are ideal for use in breeding programs with the aim of producing dogs that are less likely to suffer from liver disease or other conditions associated with high copper.


Thus, the invention provides a method of testing a dog to determine the susceptibility of the dog to liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from:

    • (a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;
    • (b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or
    • (c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


The invention also provides:

    • a database comprising information relating to one or more polymorphisms as defined herein and their association with the susceptibility of a dog to liver copper accumulation;
    • a method of determining the susceptibility of a dog to liver copper accumulation, comprising:
      • (a) inputting to a computer system data concerning the presence or absence in the genome of the dog of one or more polymorphisms as defined herein;
      • (b) comparing the data to a computer database, which database comprises information relating to one or more polymorphisms as defined herein and their association with the susceptibility of a dog to liver copper accumulation; and
      • (c) determining on the basis of the comparison the susceptibility of the dog to liver copper accumulation;
    • a computer program comprising program code means that, when executed on a computer system, instruct the computer system to perform a method of the invention;
    • a computer storage medium comprising the computer program of the invention and the database of the invention;
    • a computer system arranged to perform a method of the invention comprising:
      • (a) means for receiving data concerning the presence or absence in the genome of the dog of a polymorphism as defined herein;
      • (b) a database comprising information relating to one or more polymorphisms as defined herein and their association with the susceptibility of a dog to liver copper accumulation;
      • (c) a module for comparing the data with the database; and
      • (d) means for determining on the basis of said comparison the susceptibility of the dog to liver copper accumulation;
    • a method of determining the susceptibility of a dog to liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from the polymorphisms as defined herein; use of one or more polymorphisms selected from the polymorphisms as defined herein for determining the susceptibility of a dog to liver copper accumulation; and a method of selecting a dog for producing offspring likely to be protected from liver copper accumulation comprising:
      • determining whether the genome of a candidate first dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation according to the method of the invention and thereby determining whether the candidate first dog is suitable for producing offspring likely to be protected from liver copper accumulation;
      • optionally, determining whether the genome of a second dog of the opposite sex to the first dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation according to the method of the invention; and
      • optionally, mating the first dog with the second dog in order to produce offspring likely to be protected from liver copper accumulation.


The inventors have discovered polymorphisms associated with the protection of a dog from liver copper accumulation. Therefore, the invention provides a method of testing a dog to determine the likelihood that the dog is protected from liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from (a) Chr22_3135144 (SEQ ID NO: 145) and (b) one or more polymorphisms in linkage disequilibrium with (a).


The invention also provides:

    • a database comprising information relating to one or more polymorphisms as defined herein and their association with the protection of a dog from, or susceptibility of a dog to, liver copper accumulation;
    • a method of determining the likelihood that a dog is protected from liver copper accumulation, the method comprising:
      • (a) inputting to a computer system data concerning the presence or absence in the genome of the dog of one or more polymorphisms as defined herein;
      • (b) comparing the data to a computer database, which database comprises information relating to one or more polymorphisms as defined herein and their association with the protection of a dog from, or susceptibility of a dog to, liver copper accumulation; and
      • (c) determining on the basis of the comparison the likelihood that the dog is protected from liver copper accumulation;
    • a computer program comprising program code means that, when executed on a computer system, instruct the computer system to perform a method of the invention;
    • a computer storage medium comprising the computer program according to the invention and the database according to the invention;
    • a computer system arranged to perform a method of the invention comprising:
      • (a) means for receiving data concerning the presence or absence in the genome of the dog of one or more polymorphisms as defined herein;
      • (b) a database comprising information relating to said polymorphisms and their association with the protection of a dog from, or susceptibility of a dog to, liver copper accumulation;
      • (c) a module for comparing the data with the database; and
      • (d) means for determining on the basis of said comparison the likelihood that the dog is protected from liver copper accumulation;
    • a method of determining the likelihood that a dog is protected from liver copper accumulation, comprising detecting the presence or absence in the genome of the dog of one or more polymorphisms selected from (a) Chr22_3135144 (SEQ ID NO: 145) and (b) one or more polymorphisms in linkage disequilibrium with (a);
    • use of a polymorphism as defined herein for determining the likelihood that a dog is protected from liver copper accumulation; and
    • a method of selecting a dog for producing offspring likely to be protected from liver copper accumulation comprising:
      • determining whether the genome of a candidate first dog comprises one or more polymorphisms indicative of protection from liver copper accumulation according to the method of the invention and thereby determining whether the candidate first dog is suitable for producing offspring likely to be protected from liver copper accumulation;
      • optionally, determining whether the genome of a second dog of the opposite sex to the first dog comprises one or more polymorphisms indicative of protection from liver copper accumulation according to the invention; and
      • optionally, mating the first dog with the second dog in order to produce offspring likely to be protected from liver copper accumulation.





BRIEF DESCRIPTION OF THE FIGURES


FIG. 1 depicts the average copper levels by gender and ATP7A genotype in Labrador Retrievers (data of Table 9). The y-axis is dry liver weight copper (mg/kg). The x-axis is ATP7A genotype: from left to right, the first three bars are for the female dogs in the study and the last two bars are for the male dogs in the study. Error bars are standard error.



FIG. 2 is a box-plot of copper-histological scores by gender and ATP7A genotype in Labrador Retrievers (data of Table 9). The y-axis is the copper histological score values. The x-axis is ATP7A genotype: from left to right, the first three are for the female dogs in the study and the last two are for the male dogs in the study. The kruskal-walis p-value is 0.000396.



FIG. 3 shows the variable length of a coding repeat in ATP7B. Top: The bases and their corresponding amino acids (AA). The chromosomal location of the boxed C is 3135287. Bottom: Ensembl, NCBI and sequencing of a Beagle and a group of Labradors reveal a different number of a CGCCCC repeat. As a consequence, the boxed amino acids alanine (A) and proline (P) are more or less produced. SEQ ID NOs: 236, 237 and 238 are polynucleotide sequences containing two, three and four repeats respectively.



FIG. 4 shows the location of the ATP7B CGCCCC repeat between heavy metal associated domain 3 and 4.



FIG. 5 shows the ATP7B 4145G>A SNP (Chr22_3167534). The vertical line on the far right shows the approximate position of the mutation. The G>A substitution leads to a glutamine amino acid (AA).



FIG. 6 shows the LD structure in the first 15 Mb of chr 22. Arrows at the top of the triangle indicate the location of the coding mutations. The line pointed at by the arrows depicts high LD of the coding mutations with several SNPs in the area.



FIG. 7 shows the effect of the number of risk alleles on quantitative liver copper levels. The x-axis is the number of risk alleles and the y-axis is liver copper in mg/kg. The horizontal line indicates normal liver copper level of 400 mg/kg.



FIG. 8 shows stepwise modelling of the histology copper score. X1 to X17 are the factors in Table 21.



FIG. 9 shows stepwise modelling of the log-quantitative copper score. X1 to X17 are the factors in Table 21.



FIG. 10 illustrates schematically embodiments of functional components arranged to carry out the present invention.





BRIEF DESCRIPTION OF THE SEQUENCES

SEQ ID NOs: 1 to 5 show the polynucleotide sequences encompassing the SNPs used in the three region model in Example 2 and are also in Table 4.


SEQ ID NOs: 6 to 141 show the polynucleotide sequences encompassing further SNPs that may be used to determine the susceptibility of a dog to liver copper accumulation. These sequences are also in Tables 5 and 6.


SEQ ID NO: 142 is the polynucleotide sequences of the ATP7A coding region SNP that is associated with the protection of a dog from liver copper accumulation (ChrX_63338063). This sequence is also shown in Table 8.


SEQ ID NO: 143 is the polynucleotide sequence of a SNP (ChrX_63397393 ATP7a Reg16 F 42) that is in linkage disequilibrium with SNP ChrX_63338063. This sequence is also shown in Table 8.


SEQ ID NOs: 144 to 158 show the polynucleotide sequences encompassing the SNPs of the invention. These sequences are also shown in Table 18.


SEQ ID NOs: 159 to 226 show the polynucleotide sequences encompassing SNPs that are in linkage disequilibrium with the SNPs in Table 18. These sequences are also shown in Table 20.


SEQ ID NOs: 227 to 235 are primer sequences.


SEQ ID NOs: 236, 237 and 238 are polynucleotides containing two, three or four CGCCCC repeats respectively for the repeat sequence at genomic location 22:3135287. These sequences are also shown in Table 12.


SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created on Oct. 30, 2018, is named 069269_0297_SL.txt and is 85,712 bytes in size.


DETAILED DESCRIPTION OF THE INVENTION

Identifying Susceptibility to or Protection from Liver Copper Accumulation


Accumulation of copper in the liver leads to liver disease in a number of dog breeds, including the Labrador Retriever, Doberman Pinscher, German Shepherd, Keeshond, Cocker Spaniel, West Highland White Terrier, Bedlington Terrier, and Skye Terrier. The mean copper concentration in the liver of normal dogs of any breed is 200 to 400 mg/kg on a dry weight basis, although newborns generally have higher liver copper concentrations. The amount of copper in the liver of a dog may be measured by biopsy.


A dog that is susceptible to liver copper accumulation has a tendency to accumulate copper such that its liver copper concentration reaches a level above 400 mg/kg on a dry weight basis. Determining the susceptibility of a dog to liver copper accumulation according to the invention involves determining the risk or likelihood that the dog will accumulate liver copper to a level above 400 mg/kg, for example above 600 mg/kg, above 800 mg/kg, above 1000 mg/kg, above 1500 mg/kg, above 2000 mg/kg, above 5000 mg/kg, or above 10000 mg/kg.


A dog that is protected from liver copper accumulation has a low risk or likelihood of accumulating liver copper such that its liver copper concentration is less likely to reach a level above 400 mg/kg on a dry weight basis. The liver copper concentration of a dog that is protected from liver copper accumulation will be below 600 mg/kg, for example below 500 mg/kg, below 400 mg/kg, or below 300 mg/kg. Determining the likelihood that a dog is protected from liver copper accumulation according to the invention involves determining the likelihood that the dog will accumulate liver copper to a level below 600 mg/kg, for example below 500 mg/kg, below 400 mg/kg, or below 300 mg/kg.


The accumulation of liver copper may be assessed by histochemistry. For example, liver copper concentration may be semiquantitatively assessed by histochemistry using the rubeanic acid staining technique for evaluation of copper distribution as previously described (Van den Ingh et al., (1988) Vet Q 10: 84-89). The concentration may be graded in a scale of 0 to 5 as follows: 0=no copper present; 1=solitary liver cells and/or reticulohistiocytic (RHS) cells containing some copper positive granules; 2=small groups of liver cells and/or RHS cells containing small to moderate numbers of copper positive granules; 3=larger groups or areas of liver cells and/or RHS cells containing moderate numbers of copper positive granules; 4=large areas of liver cells and/or RHS cells with many copper positive granules; and 5=diffuse presence of liver cells and/or RHS cells with many copper positive granules. According to this grading system, copper scores above 2 are abnormal.


Therefore determining the likelihood that a dog is protected from liver copper accumulation according to the invention can involve determining the likelihood that the dog would be given a score of less than or equal to 3, for example less than or equal to 2.5, 2, 1.5, or less than or equal to 1, using the grading system described in Van den Ingh et al. Determining the susceptibility of a dog to liver copper accumulation according to the invention can involve determining the risk or likelihood that the dog would be given a score of greater than or equal to 2, for example greater than or equal to 2.5, 3, 3.5, or greater than or equal to 4, using the grading system described in Van den Ingh et al.


The likelihood of protection or susceptibility may for example be expressed as a risk factor, percentage or probability. It may be possible to determine whether or not a dog will accumulate copper to the levels described above. For example, the method of determining the susceptibility of a dog to, or the likelihood of protection of a dog from, liver copper accumulation may comprise determining whether or not a dog will accumulate copper to a level above 400 mg/kg.


Accumulation of liver copper to a level above 400 mg/kg is associated with liver disease and may ultimately lead to liver failure. Therefore, determining whether the genome of a dog comprises one or more polymorphisms indicative of protection from liver copper accumulation indicates that the dog is less likely to develop a disease or condition attributable to liver copper accumulation such as chronic hepatitis, cirrhosis and liver failure. Conversely, determining whether the genome of a dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation indicates the susceptibility of the dog to such a disease or condition. Therefore, the invention provides a method of testing for the susceptibility of a dog to, or the likelihood of protection of a dog from, a disease associated with liver copper accumulation, such as chronic hepatitis, cirrhosis and liver failure.


Polymorphisms and Indication of Susceptibility to, or Protection from, Copper Accumulation


The inventors have discovered a number of polymorphisms in the genome of the dog that are associated with susceptibility to liver copper accumulation. The present invention therefore relates to a method of determining the susceptibility of a dog to liver copper accumulation using one or more polymorphic markers at these genomic locations.


The present invention therefore provides a method of testing a dog to determine the susceptibility of the dog to liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or


(c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


The inventors have also discovered polymorphisms in the genome of the dog that are associated with protection from liver copper accumulation. The present invention therefore relates to a method of determining the likelihood that a dog is protected from liver copper accumulation using one or more polymorphic markers at these genomic locations.


The invention therefore also provides a method of testing a dog to determine the likelihood that the dog is protected from liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from (a) Chr22_3135144 (SEQ ID NO: 145) and (b) one or more polymorphisms in linkage disequilibrium with (a).


The phrase “detecting the presence or absence of a polymorphism” typically means determining whether a polymorphism is present in the genome of the dog. Polymorphisms include Single Nucleotide Polymorphisms (SNPs), microsatellite or repeat polymorphisms, insertion polymorphisms and deletion polymorphisms. Preferably the polymorphism is a SNP. Detecting the presence or absence of a SNP means genotyping the SNP or typing the nucleotide(s) present in the genome of the dog for the SNP. Typically, the nucleotide present at the same position on both homologous chromosomes will be determined. In other words, one or both alleles are genotyped and the identities of one or both alleles are determined based on the genotyping. A dog may be determined to be homozygous for a first allele, heterozygous or homozygous for a second allele of the SNP. When the polymorphism is a microsatellite or repeat sequence, typically the method will involve determining the number of repeats.


Determining a phenotype of an individual, such as the susceptibility of the individual to, or the protection of the individual from, a disease or condition, is not limited to the detection of a polymorphism that is causal for the disease or condition. In genetic mapping studies, genetic variation at a set of marker loci in a sample of individuals is tested for association with a given phenotype. If such an association is found between a particular marker locus and the phenotype, it suggests that either the variation at that marker locus affects the phenotype of interest, or that the variation at that marker locus is in linkage disequilibrium with the true phenotype-related locus, which was not genotyped. In the case of a group of polymorphisms that are in linkage disequilibrium with each other, knowledge of the existence of all such polymorphisms in a particular individual generally provides redundant information. Thus, when determining whether the genome of a dog comprises one or more polymorphisms indicative of susceptibility to, or protection from, liver copper accumulation or to copper-associated liver disease, it is necessary to detect only one polymorphism of such a group of polymorphisms.


As a result of linkage disequilibrium, a polymorphism that is not a functional susceptibility/protective polymorphism, but is in linkage disequilibrium with a functional polymorphism, may act as a marker indicating the presence of the functional polymorphism. A polymorphism that is in linkage disequilibrium with a polymorphism of the invention is indicative of susceptibility to, or protection from, liver copper accumulation.


Accordingly, any one of the polymorphic positions as defined herein may be typed directly, in other words by determining the nucleotide present at that position, or indirectly, for example by determining the nucleotide present at another polymorphic position that is in linkage disequilibrium with said polymorphic position.


Linkage disequilibrium is the non-random gametic association of alleles at different loci in a population. Polymorphisms that have a tendency to be inherited together instead of being inherited independently by random assortment are in linkage disequilibrium. Polymorphisms are randomly assorted or inherited independently of each other if the frequency of the two polymorphisms together is the product of the frequencies of the two polymorphisms individually. For example, if two polymorphisms at different polymorphic sites are present in 50% of the chromosomes in a population, then they would be said to assort randomly if the two alleles are present together on 25% of the chromosomes in the population. A higher percentage would mean that the two alleles are linked. It follows that a first polymorphism is in linkage disequilibrium with a second polymorphism if the frequency of the two polymorphisms together is greater than the product of the frequencies of the two polymorphisms individually in a population. Preferably, a first polymorphism is in linkage disequilibrium with a second polymorphism if the frequency of the two polymorphisms together is more that 10% greater, for example more than 30%, more than 50% or more than 70% greater, than the product of the frequencies of the two polymorphisms individually.


Research has shown that linkage disequilibrium is extensive in dogs (Extensive and breed-specific linkage disequilibrium in Canis familiaris, Sutter et al., Genome Research 14: 2388-2396). Polymorphisms which are in linkage disequilibrium are often in close physical proximity, which is why they are co-inherited. Polymorphisms which are in linkage disequilibrium with the polymorphisms mentioned herein are located on the same chromosome. Polymorphisms which are in linkage disequilibrium in dogs are typically within 5 mb, preferably within 2 mb, within 1 mb, within 700 kb, within 600 kb, within 500 kb, within 400 kb, within 200 kb, within 100 kb, within 50 kb, within 10 kb, within 5 kb, within 1 kb, within 500 bp, within 100 bp, within 50 bp or within 10 bp of the polymorphism.


It would be within the capability of the skilled person to use routine techniques to identify polymorphisms that are in linkage disequilibrium with any one of the polymorphic positions as defined herein. Once a potential polymorphism has been selected, the skilled person can readily determine whether this polymorphism, and what version or allele of the polymorphism, is significantly correlated with any of the polymorphisms defined herein.


In more detail, to determine whether a polymorphism is in linkage disequilibrium with any one of the polymorphisms defined herein, the skilled person should genotype the candidate polymorphism and one or more of the polymorphisms defined herein in a panel of dogs. The size of the panel should be adequate enough to achieve a statistically significant result. Typically, samples from at least 100, preferably at least 150 or at least 200, different dogs should be genotyped. The dogs in the panel may be of any breed, but typically will have the same or similar genetic breed background. Once the polymorphisms have been genotyped in the panel of dogs, linkage disequilibrium between one or more pairs of polymorphisms can be measured using any one of a number of readily available statistical packages. An example of a free software package is Haploview (Haploview: analysis and visualisation of LD and haplotype maps, Barrett et al, 2005, Bioinformatics, 21(2): 263-265), downloadable at http://www.broadinstitute.org/haploview/haploview. Another example of software that can be used is PLINK (http://pngu.mgh.harvard.edu/purcell/plink/).


A measure of linkage disequilibrium is D′. A range of 0.5 to 1 for D′ is indicative of a pair of polymorphisms being in linkage disequilibrium, with 1 indicating the most significant linkage disequilibrium. Therefore if D′ is found to be from 0.5 to 1, preferably from 0.6 to 1, 0.7 to 1, from 0.8 to 1, from 0.85 to 1, from 0.9 to 1, from 0.95 to 1 or most preferably 1, for a candidate polymorphism and a specific polymorphism defined herein, the candidate polymorphism may be said to be predictive of the polymorphism defined herein and will thus indicate susceptibility to or protection from liver copper accumulation. In a preferred method of the invention, a polymorphism that is in linkage disequilibrium with a polymorphism defined herein is within 680 kb and on the same chromosome as the polymorphism defined herein and the calculated measure of linkage disequilibrium between the pair of polymorphisms, D′, is greater than or equal to 0.9.


Another measure of linkage disequilibrium is R-squared, where R is the correlation coefficient. R-squared, which is also known as the ‘Coefficient of determination’, is the fraction of the variance in the genotypes of the first polymorphism which is accounted for in the genotypes of the second polymorphism. Therefore an R-squared of 0.5 for a candidate polymorphism and a specific polymorphism defined herein would mean that the candidate polymorphism accounts for 50% of the variance in the specific polymorphism. R-squared is producible from standard statistical packages such as Haploview. Typically, an R-squared of 0.25 or greater (R of >0.5 or <−0.5) is considered a large correlation. Therefore if R-squared is found to be 0.5 or more, preferably 0.75 or more, 0.8 or more, 0.85 or more, 0.9 or more, or 0.95 or more for a candidate polymorphism and a specific polymorphism defined herein, the candidate polymorphism may be said to be predictive of the polymorphism defined herein and will thus indicate susceptibility to or protection from liver copper accumulation. In a preferred method of the invention, a polymorphism that is in linkage disequilibrium with a polymorphism defined herein is within 680 kb and on the same chromosome as the polymorphism defined herein and the calculated measure of linkage disequilibrium between the pair of polymorphisms, R-squared, is greater than or equal to 0.5.


It is also possible to build a haplotype of polymorphisms in LD with the polymorphisms of the invention. Even if one or more polymorphisms are individually only weakly in LD with the polymorphisms of the invention, they may be in strong LD if they are used in combination. For example, any one polymorphism may have an R-squared value below 0.25. However, two or more mutations individually having an R-squared of below 0.25 may in combination have an R-squared of greater than 0.5. Therefore, these polymorphisms may be used in combination to determine the susceptibility of the dog to, or the likelihood of protection of the dog from, liver copper accumulation.


Therefore, the method of the invention may comprise detecting the presence or absence of two or more polymorphisms in linkage disequilibrium with a polymorphism defined herein, wherein R-squared for each of said two or more polymorphisms individually may be less than or equal to 0.25, but R-squared for the combination of said two or more polymorphisms is greater than or equal to 0.5.


Once a polymorphism has been identified as being in linkage disequilibrium and therefore correlated with a polymorphism defined herein, the skilled person can readily determine which version of the polymorphism, i.e. which allele, is associated with susceptibility to or protection from liver copper accumulation. This could be achieved by phenotyping a panel of dogs for liver copper accumulation and classifying the dogs in terms of the level of liver copper accumulation. The panel of dogs are then genotyped for the polymorphism of interest. The genotypes are then correlated with the level of liver copper in order to determine the association of the genotypes with liver copper level and thereby determine which allele is associated with susceptibility to or protection from liver copper accumulation.


The polymorphisms of the invention that have been found to be indicative of susceptibility of a dog to liver copper accumulation are identified in Tables 17 and 18. Specifically, they are: Chr22_3167534 (SEQ ID NO: 144), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr32_38904515 (SEQ ID NO: 156), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr8_4892743 (SEQ ID NO: 157), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr8_4880518 (SEQ ID NO: 158), Chr10_65209946 (SEQ ID NO: 155) and Chr22_3135144 (SEQ ID NO: 145).


In addition, a microsatellite repeat in the ATP7B gene was found to be associated with susceptibility to liver copper accumulation. This is a CGCCCC repeat on chromosome 22 starting at genomic location 3135287 (22:3135287). The repeat sequence is illustrated in FIG. 3 (SEQ ID NOs: 236 to 238). There may be two (SEQ ID NO: 236), three (SEQ ID NO: 237), four (SEQ ID NO: 238) and potentially more repeats. Therefore the method of the invention may comprise determining the number of CGCCCC repeats in the genome of the dog.


The method of determining susceptibility of a dog to liver copper accumulation comprises detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or


(c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


Any number and any combination of polymorphisms may be detected to carry out the invention. Preferably at least 2 polymorphisms are detected. Preferably 2 to 5, 3 to 8, 5 to 10 or 8 to 15 polymorphisms are detected.


The DNA of a dog may be typed at the respective positions of:

    • (i) one or more polymorphisms (a);
    • (ii) one or more polymorphisms (b);
    • (iii) one or more polymorphisms (c);
    • (iv) one or more polymorphisms (a) and one or more polymorphisms (b);
    • (v) one or more polymorphisms (a) and one or more polymorphisms (c); or
    • (vi) one or more polymorphisms (b) and one or more polymorphisms (c).


Preferably the method of determining the susceptibility of a dog to liver copper accumulation comprises detecting in a sample the presence or absence in the genome of the dog of:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), Chr19_6078084 (SEQ ID NO: 148), Chr3_86838677 (SEQ ID NO: 152), Chr10_65209946 (SEQ ID NO: 155) and ChrX_63338063 (SEQ ID NO: 142); or


(b) ChrX_120879711 (SEQ ID NO: 147), Chr15_62625262 (SEQ ID NO: 149), Chr22_3167534 (SEQ ID NO: 144), Chr8_4892743 (SEQ ID NO: 157), Chr24_4011833 (SEQ ID NO: 153) and Chr18_60812198 (SEQ ID NO: 154).


The alleles of the mutations that associated with high copper are provided in Table 18. Thus, the method of determining the susceptibility of a dog to liver copper accumulation of the invention may comprise determining the presence or absence of the A allele for Chr22_3167534 (SEQ ID NO: 144), the A allele for Chr20_55461150 (SEQ ID NO: 146), the C allele for ChrX_120879711 (SEQ ID NO: 147), the C allele for Chr32_38904515 (SEQ ID NO: 156), the T allele for Chr19_6078084 (SEQ ID NO: 148, the A allele for Chr15_62625262 (SEQ ID NO: 149), the G allele for Chr14_39437543 (SEQ ID NO: 150), the A allele for Chr15_62625024 (SEQ ID NO: 151), the C allele for Chr3_86838677 (SEQ ID NO: 152), the T allele for Chr8_4892743 (SEQ ID NO: 157), the G allele for Chr24_4011833 (SEQ ID NO: 153), the A allele for Chr18_60812198 (SEQ ID NO: 154), the A allele for Chr8_4880518 (SEQ ID NO: 158), the T allele for Chr10_65209946 (SEQ ID NO: 155) and/or the G allele for Chr22_3135144 (SEQ ID NO: 145), and thereby determining whether the genome of the dog has a polymorphism indicative of susceptibility to copper accumulation.


Every extra copy of the CGCCCC repeat at chromosome location 22:3135287 was found to increase the risk of copper accumulation. Thus, the method of determining the susceptibility of a dog to liver copper accumulation may comprise determining the number of CGCCCC repeats at chromosome location 22:3135287. The presence of two or more repeats, for example three or four repeats is indicative of susceptibility to liver copper accumulation.


In a preferred method of the invention, a polymorphism in linkage disequilibrium with a polymorphism (a) is a SNP. As a result of being in linkage disequilibrium, the polymorphism will be indicative of susceptibility to liver copper accumulation. Examples of SNPs in linkage disequilibrium with polymorphisms (a) are provided in Table 19 and the sequences surrounding the SNPs are shown in Table 20. These SNPs can either be used on their own, or in combination with one or more polymorphisms (a) and/or (c), to determine the susceptibility of a dog to liver copper accumulation. The method of the invention may therefore comprise detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from the polymorphisms in Tables 19 and 20.


The inventors previously discovered polymorphisms in the ATP7A gene that are indicative of protection from liver copper accumulation e.g. (ChrX_63338063; SNP


ATP7a_Reg3_F_6; SEQ ID NO: 142). Thus, the method of determining the susceptibility of a dog to liver copper accumulation may further comprise detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from:

    • (d) ChrX_63338063 (SNP ATP7a_Reg3_F_6; SEQ ID NO: 142); and/or
    • (e) one or more polymorphisms in linkage disequilibrium with a said polymorphism (d).


The A allele of Chr22_3135144 and the T allele of ChrX_63338063 are associated with low copper or protection from liver copper accumulation. Conversely, the G allele of Chr22_3135144 and the C allele of ChrX_63338063 are associated with high copper or susceptibility to liver copper accumulation. Thus, the method of determining the susceptibility of a dog to liver copper accumulation may comprise determining the presence or absence of the A or G allele of Chr22_3135144 and/or the T or C allele of ChrX_63338063. The presence of the A allele of Chr22_3135144 and/or the T allele of ChrX_63338063 indicate that the dog is likely to be protected from liver copper accumulation and the presence of the G allele of Chr22_3135144 and/or the C allele of ChrX_63338063 indicate that the dog is likely to be susceptible to liver copper accumulation.


The polymorphisms that have been found to be associated with protection from liver copper accumulation may be used in a method of determining the likelihood that a dog is protected from liver copper accumulation. Thus, the invention provides a method of testing a dog to determine the likelihood that the dog is protected from liver copper accumulation, comprising detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from (a) Chr22_3135144 (SEQ ID NO: 145) and (b) one or more polymorphisms in linkage disequilibrium with (a).


Any number and any combination of polymorphisms may be detected to carry out the invention. Preferably at least two polymorphisms are detected. Preferably 2 to 5, 3 to 8, 5 to 10 or 8 to 15 polymorphisms are detected.


Therefore, the DNA of a dog may be typed at the respective positions of

    • (i) polymorphism (a); and/or
    • (ii) one or more polymorphisms (b).


The method of determining the likelihood that a dog is protected from liver copper accumulation may further comprise detecting in a sample the presence or absence in the genome of the dog of (c) ChrX_63338063 (SNP ATP7a_Reg3_F_6; SEQ ID NO:142) and/or (d) one or more polymorphisms in linkage disequilibrium with (c). An example of a polymorphism that is in linkage disequilibrium with ChrX_63338063 (SNP ATP7a_Reg3_F_6; SEQ ID NO: 142) is ChrX_63397393 (SNP ATP7a_Reg16 F 42; SEQ ID NO: 143). Further examples are provided in Tables 19 and 20. Therefore the method of determining the likelihood that a dog is protected from liver copper accumulation may further comprise detecting in a sample the presence or absence in the genome of the dog of (c) ChrX_63338063 (SNP ATP7a_Reg3_F_6; SEQ ID NO:142) and/or (d) ChrX_63397393 (SNP ATP7a_Reg16 F 42; SEQ ID NO: 143).


Preferably the method of determining the likelihood that a dog is protected from liver copper accumulation comprises detecting in a sample the presence or absence in the genome of the dog of: Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), Chr19_6078084 (SEQ ID NO: 148), Chr3_86838677 (SEQ ID NO: 152), Chr10_65209946 (SEQ ID NO: 155) and ChrX_63338063 SEQ ID NO: 142.


As indicated above, the A allele of Chr22_3135144 and the T allele of ChrX_63338063 are associated with low copper or protection from liver copper accumulation. Conversely, the G allele of Chr22_3135144 and the C allele of ChrX_63338063 are associated with high copper or susceptibility to liver copper accumulation. Thus, the method of determining the likelihood that a dog is protected from liver copper accumulation may comprise determining the presence or absence of the A or G allele of Chr22_3135144 and/or the T or C allele of ChrX_63338063. The presence of the A allele of Chr22_3135144 and/or the T allele of ChrX_63338063 indicate that the dog is likely to be protected from liver copper accumulation and the presence of the G allele of Chr22_3135144 and the C allele of ChrX_63338063 indicate that the dog is not likely to be protected from liver copper accumulation.


The polymorphisms that have been found to be associated with high liver copper or susceptibility to liver copper accumulation described herein may also be used in a method of determining the likelihood that a dog is protected from liver copper accumulation. Determining the absence of an allele that is associated with high liver copper can help to determine the likelihood that a dog is protected from liver copper accumulation. The method of determining the likelihood that a dog is protected from liver copper accumulation may therefore comprise detecting in a sample the presence or absence in the genome of the dog of one or more polymorphisms selected from:


(e) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19 6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(f) one or more polymorphisms in linkage disequilibrium with a said polymorphism (e); and/or


(g) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


The inventors have previously discovered that polymorphisms in or in the region of the canine GOLGAS, ATP7A and UBLS genes are indicative of susceptibility to liver copper accumulation in dogs (Examples 1 and 2). Therefore these polymorphisms could be used in combination with the polymorphisms of the invention to provide an enhanced genetic test for determining the risk or likelihood that a dog is susceptible to or protected from liver copper accumulation. The method of determining the susceptibility of a dog to, or the protection of a dog from, liver copper accumulation of the invention may therefore further comprise detecting the presence or absence of (I) a polymorphism in the GOLGAS, ATP7A or UBLS gene of the dog that is indicative of susceptibility to liver copper accumulation and/or (II) a polymorphism in linkage disequilibrium with a said polymorphism (I). Any number and any combination of these polymorphisms may be detected in addition to the polymorphisms of the invention. Preferably at least 2 of these further polymorphisms are detected. Preferably 2 to 5, 3 to 8 or 5 to 10 polymorphisms are further detected.


Therefore, the DNA of a dog may be further typed at the respective positions of (i) polymorphism (I) and/or (ii) one or more polymorphisms (II). Additionally, the DNA of the dog may be typed at the respective positions of:

    • (i) two or more polymorphisms (I);
    • (ii) two or more polymorphisms (II); or
    • (iii) one or more polymorphisms (I) and one or more polymorphisms (II).


When there are two polymorphisms (I), each polymorphism may be in a separate one of the GOLGAS, ATP7A and UBLS genes or in just one of those genes. When there are three or more polymorphisms (I), for example 3 to 10 such polymorphisms, the polymorphisms may be in the same gene, in two of the genes or in all three genes.


Similarly when there are two polymorphisms (II), each polymorphism may be in linkage disequilibrium with a polymorphism in a separate one of the GOLGAS, ATP7A and UBLS genes or in just one of those genes. When there are three or more polymorphisms (II), for example 3 to 10 such polymorphisms, the polymorphisms may be in linkage disequilibrium with a polymorphism in the same gene, in two of the genes or in all three genes.


A preferred method of the invention further comprises detecting the presence or absence of at least one polymorphism (I) in the GOLGAS, ATP7A or UBLS gene of the dog that is indicative of susceptibility to liver copper accumulation and at least one polymorphism (II) in linkage disequilibrium with a said polymorphism (I).


In a preferred method of the invention, the polymorphism (I) and/or (II) is a SNP. The SNP may be any SNP in or in the region of the GOLGAS, ATP7A or UBLS gene of the dog that is indicative of susceptibility to liver copper accumulation and/or a SNP that is in linkage disequilibrium thereof.


The method of the invention may, therefore, further comprise determining whether the genome of a dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation selected from the SNPs identified in Table 4, Table 5 and Table 6. In Tables 4 and 5 each SNP is located at position 61 in the sequence. The first and second alleles are provided for each SNP at that location ([first/second]). In Table 6, the first and second alleles for each SNP are also indicated. Any number of the SNPs may be used from Tables 4, 5 and 6 and in any combination. The SNPs may be combined with a different type of polymorphism.


Preferably, the method of determining the susceptibility of a dog to, or the likelihood of protection of the dog from, liver copper accumulation further comprises detecting the presence or absence of one or more SNPs selected from the SNPs in Table 4 and Table 6 and/or one or more SNPs in linkage disequilibrium thereof. Therefore preferably the one or more SNPs are selected from BICF2P506595 (position 61 of SEQ ID NO:1), BICF2P772765 (position 61 of SEQ ID NO:2), BICF2S2333187 (position 61 of SEQ ID NO:3), BICF2P1324008 (position 61 of SEQ ID NO:4), BICF2P591872 (position 61 of SEQ ID NO:5), ATP7a_Reg4_F_9 (position 164 of SEQ ID NO: 131), UBLS Reg1F_16 (position 97 of SEQ ID NO: 132), golga5_Reg1 24 (position 70 of SEQ ID NO: 133), golga5_26 (position 88 of SEQ ID NO: 134), golga5_27 (position 104 of SEQ ID NO: 135), golga5_28 (position 139 of SEQ ID NO: 136), golga5_29 (position 128 of SEQ ID NO: 137), golga5_30 (position 95 of SEQ ID NO: 138), golga5_31 (position 106 of SEQ ID NO: 139), atp7areg17_32 (position 95 of SEQ ID NO: 140), atp7areg17_33 (position 90 of SEQ ID NO: 141) and one or more SNPs in linkage disequilibrium thereof. Accordingly, any of these 16 SNPs or any SNPs that are in linkage disequilibrium with any if these 16 SNPs may be typed. Preferably at least 2 of these 16 SNPs or SNPs in linkage disequilibrium are typed.


More preferably, the method of the invention further comprises detecting the presence or absence of one or more SNPs selected from the SNPs in Table 4. Accordingly, any of these 5 SNPs or any SNPs that are in linkage disequilibrium with any of these 5 SNPs may be typed. Preferably at least 2 of these 5 SNPs or SNPs in linkage disequilibrium are typed. More preferably all 5 positions are typed. Preferably therefore, the nucleotide(s) that are typed are selected from positions equivalent to:

    • position 61 of SEQ ID NO: 1 (BICF2P506595, SNP1);
    • position 61 of SEQ ID NO: 2 (BICF2P772765, SNP 2);
    • position 61 of SEQ ID NO: 3 (BICF2S2333187, SNP 3);
    • position 61 of SEQ ID NO: 4 (BICF2P1324008, SNP 4);
    • position 61 of SEQ ID NO: 5 (BICF2P591872, SNP 5); or any positions


      which are in linkage disequilibrium with any one of these positions. Preferably, the method comprises detecting the presence or absence of the SNPs BICF2P506595 (SEQ ID NO:1), BICF2P772765 (SEQ ID NO:2), BICF2S2333187 (SEQ ID NO:3), BICF2P1324008 (SEQ ID NO:4), and BICF2P591872 (SEQ ID NO:5).


SNP 1 is located within an intron of the GOLGAS gene. SNPs 2, 3 and 4 are located in the region of the UBLS gene. SNP 5 is located in the region of the ATP7A gene. The detection method of the invention therefore relates to any SNP that lies within or in the region of one or more of these genes (in coding regions or otherwise), or any other SNP that is in linkage disequilibrium.


Example 2 demonstrates the use of SNPs 1 to 5 to establish a Boolean model of susceptibility to copper accumulation. Table 3 represents the binary conditions of alleles at three genomic locations. The binary values are indicative of a dog having alleles that are indicative of susceptibility to copper accumulation (“bad” alleles). For instance 000 represents not having any of the three bad alleles. 111 represents having all three bad alleles.


The A allele for SNP BICF2P506595 (SNP 1), the G allele for SNP BICF2P772765 (SNP 2), the C allele for SNP BICF2S2333187 (SNP 3), the G allele for SNP BICF2P1324008 (SNP 4) and the A allele for SNP BICF2P591872 (SNP 5) have been determined by the inventors to be indicative of susceptibility to liver copper accumulation. Dogs that are homozygous for these alleles are susceptible to liver copper accumulation. Therefore, a preferred method of the invention further comprises determining the presence or absence of the A allele for SNP BICF2P506595, the G allele for SNP BICF2P772765 (SNP 2), the C allele for SNP BICF2S2333187 (SNP 3), the G allele for SNP BICF2P1324008 (SNP 4) and/or the A allele for SNP BICF2P591872 (SNP 5) and thereby determining whether the genome of the dog comprises a polymorphism indicative of susceptibility to liver copper accumulation. A more preferred method comprises detecting the presence or absence of the AA genotype for SNP BICF2P506595, the GG genotype for SNP BICF2P772765, the CC genotype for SNP BICF2S2333187, the GG genotype for SNP BICF2P1324008 and/or the AA or AG genotype for SNP BICF2P591872.


Therefore, a preferred method of determining the susceptibility of a dog to, or the likelihood that a dog is protected from, liver copper accumulation further comprises detecting the presence or absence of:

    • (i) An AA genotype for SNP BICF2P506595 (SNP 1);
    • (ii) A GG genotype for SNP BICF2P772765 (SNP 2);
    • (iii) A CC genotype for SNP BICF2S2333187 (SNP 3);
    • (iv) A GG genotype for SNP BICF2P1324008 (SNP 4); and/or
    • (v) An AA or AG genotype for SNP BICF2P591872 (SNP 5);


      and thereby determining whether the genome of the dog comprises one or more polymorphisms indicative of protection from and/or susceptibility to liver copper accumulation. A more preferred method comprises detecting the presence or absence of a genotype (i); a genotype (ii), (iii) and (iv); or a genotype (v). An even more preferable method comprises detecting the presence or absence of all 5 genotypes (i) to (v).


Typing the nucleotide(s) present in the genome of the dog at a position identified in any of Tables 4, 5, 6, 8, 18 and 20 may mean that the nucleotide present at this position in a sequence corresponding exactly with the sequence identified in Tables 4, 5, 6, 8, 18 and 20 is typed. However, it will be understood that the exact sequences presented in SEQ ID NOs: 1 to 5 identified in Table 4, SEQ ID NOs: 6 to 130 in Table 5, SEQ ID NOs: 131 to 141 in Table 6, SEQ ID NO: 142 and SEQ ID NO: 143 in Table 8, SEQ ID NOs: 144 to 158 in Table 18 and SEQ ID NOs: 159 to 226 in Table 20 will not necessarily be present in the dog to be tested. Typing the nucleotide present may therefore be at a position identified in Tables 4, 5, 6, 8, 18 and 20 or at an equivalent or corresponding position in the sequence. The term equivalent as used herein therefore means at or at a position corresponding to that identified in Tables 4, 5, 6, 8, 18 and 20. The sequence and thus the position of the SNP could for example vary because of deletions or additions of nucleotides in the genome of the dog. Those skilled in the art will be able to determine a position that corresponds to or is equivalent to the relevant position in each of SEQ ID NOs: 1 to 226, using for example a computer program such as GAP, BESTFIT, COMPARE, ALIGN, PILEUP or BLAST. The UWGCG Package provides programs including GAP, BESTFIT, COMPARE, ALIGN and PILEUP that can be used to calculate homology or line up sequences (for example used on their default settings). The BLAST algorithm can also be used to compare or line up two sequences, typically on its default settings. Software for performing a BLAST comparison of two sequences is publicly available through the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/). This algorithm is further described below. Similar publicly available tools for the alignment and comparison of sequences may be found on the European Bioinformatics Institute website (http://www.ebi.ac.uk), for example the ALIGN and CLUSTALW programs.


There are a variety of different methods that can be used to determine whether a polymorphism is indicative of either susceptibility to or protection from liver copper accumulation. Typically, the candidate polymorphism is compared to a database of polymorphisms and their association with susceptibility to or protection from liver copper accumulation. Such a database is generated by phenotyping a panel of dogs for liver copper accumulation, for example by liver biopsy, and classifying the dogs in terms of the level of copper accumulation. The dogs in the panel are also genotyped for a panel of polymorphisms. It is then possible to determine the association of each genotype with the level of liver copper. Determining whether a polymorphism is indicative of either susceptibility to or protection from liver copper is therefore achieved by locating the polymorphism in the database.


If a polymorphism of interest is not located in a database as described above, it is still possible to determine whether the polymorphism is indicative of either susceptibility to or protection from liver copper accumulation. This could be achieved by phenotyping a panel of dogs for liver copper accumulation and classifying the dogs in terms of the level of liver copper accumulation. The panel of dogs are then genotyped for the polymorphism of interest. The genotypes are then correlated with the level of liver copper in order to determine the association of the genotypes with liver copper level.


Once the presence or absence of the one or more polymorphisms of the invention have been detected in the genome of the dog, whether the dog is protected from, or susceptible to, liver copper accumulation is thereby determined. The genotype of each polymorphism alone or in combination with other polymorphisms is indicative of the protection from, or susceptibility of the dog to, liver copper accumulation.


To determine whether the susceptibility of a dog to, or the likelihood that a dog is protected from, liver copper accumulation, one may genotype one or more of the polymorphisms defined herein. The presence of one or more alleles that are associated with high copper indicates that the dog is susceptible to liver copper accumulation. Conversely, the presence of one or more alleles associated with low copper indicates that the dog is likely to be protected from liver copper accumulation. For example, to determine whether a dog is protected from liver copper accumulation one may genotype the SNP at Chr22_3135144 in the genome of the dog using a DNA sample from the dog. This functional mutation is located in ATP7B (on the X chromosome) and the A allele is protective. Once the genotype of the SNP has been determined it is possible to determine whether the dog is protected from liver copper accumulation. The presence of the A allele is indicative of protection from liver copper accumulation. A dog that is homozygous for the allele (AA) is most likely to be protected from liver copper accumulation. A preferred method of the invention therefore comprises determining the presence or absence of a A allele of the ATP7B SNP in the genome of the dog. The method may comprise determining whether the dog is homozygous or heterozygous for the A allele of the ATP7B SNP.


If the method comprises testing for the presence or absence of multiple polymorphisms indicative of susceptibility to, or protection from, liver copper accumulation, a model may be used that combines the results to provide an overall assessment of the risk or likelihood that the dog will be susceptible to, or protected from, liver copper accumulation. Example 6 explains how a model can be generated using multiple polymorphisms. Preferably, a stepwise modelling technique is used. A simplified example of model generation is described in Example 2. Table 3 sets out the different possible genotypes of the combination of 5 SNPs in the region of the GOLGAS, UBLS and ATP7A genes and the percentage of dogs with those genotypes that have high copper (liver levels of above 600 mg/kg). In this Example, to determine the susceptibility of a dog to liver copper accumulation one may genotype the 5 SNPs in the genome of the dog using a DNA sample from the dog. Once the genotypes of the SNPs have been determined, these can be converted into binary values based on the key provided in Example 2, i.e. based on the degree of association of the genotype with high copper. Then, Table 3 is used to convert the binary values into a risk factor based on the percentage of dogs that have that genotype pattern and high copper.


A dog may be tested by a method of the invention at any age, for example from 0 to 12, 0 to 6, 0 to 5, 0 to 4, 0 to 3, 0 to 2 or 0 to 1 years old. Preferably the dog is tested at as young an age as possible, for example within the first year, first 6 months or first 3 months of its life. The dog is preferably tested before copper accumulation occurs. The history of the dog may or may not be known. For example, the dog may be a pup of known parents and the history of the parents with respect to copper accumulation may be known. Alternatively, the dog may be a stray or a rescued dog with unknown parentage and history.


The dog to be tested by any method of the present invention may be of any breed. The invention provides a method of determining whether the genome of a mixed or crossbred dog, or a mongrel or out-bred dog comprises one or more polymorphisms indicative of protection from, or susceptibility to, liver copper accumulation.


In the method of the invention, the dog may be one that is suspected of being susceptible to liver copper accumulation. Alternatively, the dog may be suspected of being protected from liver copper accumulation.


Typically the dog will have genetic inheritance of a breed selected from Labrador Retriver, Doberman Pinscher, German Shepherd, Keeshond, Cocker Spaniel, West Highland White Terrier, Bedlington Terrier and Skye Terrier. The dog may be a mixed or crossbred dog, or a mongrel or out-bred dog. The dog may have at least 25%, at least 50%, or at least 100% of its genome inherited from any pure breed or more preferably from any of the breeds described herein. The dog may be a pure-bred. In one embodiment of the invention, one or both parents of the dog to be tested are or were pure-bred dogs. In another embodiment, one or more grandparents are or were purebred dogs. One, two, three or all four of the grandparents of the dog that is tested may be or may have been pure-bred dogs.


Preferably, the dog has genetic breed inheritance of Labrador Retriever. The dog may be a purebred Labrador Retriever. Alternatively, the dog may be a mixed or crossbred dog, or an outbred dog (mongrel). One or both of the parents of the dog may be a pure-bred Labrador Retriever dog. One, two, three or four of the grandparents of the dog may be a pure-bred Labrador Retriever dog. The dog may have at least 50% or at least 75% of the Labrador Retriever breed in its genetic background. Thus, at least 50% or at least 75% of the dog's genome may be derived from the Labrador Retriever breed.


The genetic breed background of a dog may be determined by assessing the allelic frequencies of genetic markers, for example SNPs or microsatellites. The combinations of allelic frequencies of different SNPs or microsatellites in a dog provide a signature that allows the breed of a dog or the breeds that make up a mixed breed dog to be determined. Such a genetic test may be a commercially available test. Alternatively, the dog may not need to be tested for the genetic inheritance of a particular breed because it is suspected of having a particular breed inheritance for example by the dog owner or veterinarian. This could be for example because of knowledge of the dog's ancestry or because of its appearance.


The predictive test of the invention may be carried out in conjunction with one or more other predictive or diagnostic tests such as determining the genetic breed background/inheritance of the dog or susceptibility to one or more other diseases.


Detection of Polymorphisms


The detection of polymorphisms according to the invention may comprise contacting a polynucleotide or protein in a sample from the dog with a specific binding agent for a polymorphism and determining whether the agent binds to the polynucleotide or protein, wherein binding of the agent indicates the presence of the polymorphism, and lack of binding of the agent indicates the absence of the polymorphism.


The method is generally carried out in vitro on a sample from the dog, where the sample contains DNA from the dog. The sample typically comprises a body fluid and/or cells of the dog and may, for example, be obtained using a swab, such as a mouth swab. The sample may be a blood, urine, saliva, skin, cheek cell or hair root sample. The sample is typically processed before the method is carried out, for example DNA extraction may be carried out. The polynucleotide or protein in the sample may be cleaved either physically or chemically, for example using a suitable enzyme. In one embodiment the part of polynucleotide in the sample is copied or amplified, for example by cloning or using a PCR based method prior to detecting the polymorphism.


In the present invention, any one or more methods may comprise determining the presence or absence of one or more polymorphisms in the dog. The polymorphism is typically detected by directly determining the presence of the polymorphic sequence in a polynucleotide or protein of the dog. Such a polynucleotide is typically genomic DNA, mRNA or cDNA. The polymorphism may be detected by any suitable method such as those mentioned below.


A specific binding agent is an agent that binds with preferential or high affinity to the protein or polypeptide having the polymorphism but does not bind or binds with only low affinity to other polypeptides or proteins. The specific binding agent may be a probe or primer. The probe may be a protein (such as an antibody) or an oligonucleotide. The probe may be labelled or may be capable of being labelled indirectly. The binding of the probe to the polynucleotide or protein may be used to immobilise either the probe or the polynucleotide or protein.


Generally, in the method, a polymorphism can be detected by determining the binding of the agent to the polymorphic polynucleotide or protein of the dog. However, in one embodiment the agent is also able to bind the corresponding wild-type sequence, for example by binding the nucleotides or amino acids which flank the variant position, although the manner of binding to the wild-type sequence will be detectably different to the binding of a polynucleotide or protein containing the polymorphism.


The method may be based on an oligonucleotide ligation assay in which two oligonucleotide probes are used. These probes bind to adjacent areas on the polynucleotide that contains the polymorphism, allowing after binding the two probes to be ligated together by an appropriate ligase enzyme. However, the presence of a single mismatch within one of the probes may disrupt binding and ligation. Thus, ligated probes will only occur with a polynucleotide that contains the polymorphism, and therefore the detection of the ligated product may be used to determine the presence of the polymorphism.


In one embodiment the probe is used in a heteroduplex analysis based system. In such a system when the probe is bound to a polynucleotide sequence containing the polymorphism it forms a heteroduplex at the site where the polymorphism occurs and hence does not form a double strand structure. Such a heteroduplex structure can be detected by the use of a single or double strand specific enzyme. Typically, the probe is an RNA probe, the heteroduplex region is cleaved using RNAase H and the polymorphism is detected by detecting the cleavage products.


The method may be based on fluorescent chemical cleavage mismatch analysis which is described for example in PCR Methods and Applications 3, 268-71 (1994) and Proc. Natl. Acad. Sci. 85, 4397-4401 (1998).


In one embodiment a PCR primer is used that primes a PCR reaction only if it binds a polynucleotide containing the polymorphism, for example a sequence-specific PCR system, and the presence of the polymorphism may be determined by detecting the PCR product. Preferably the region of the primer that is complementary to the polymorphism is at or near the 3′ end of the primer. The presence of the polymorphism may be determined using a fluorescent dye and quenching agent-based PCR assay such as the Taqman PCR detection system.


The specific binding agent may be capable of specifically binding the amino acid sequence encoded by a polymorphic sequence. For example, the agent may be an antibody or antibody fragment. The detection method may be based on an ELISA system. The method may be an RFLP based system. This can be used if the presence of the polymorphism in the polynucleotide creates or destroys a restriction site that is recognized by a restriction enzyme.


The presence of the polymorphism may be determined based on the change that the presence of the polymorphism makes to the mobility of the polynucleotide or protein during gel electrophoresis. In the case of a polynucleotide, single-stranded conformation polymorphism (SSCP) or denaturing gradient gel electrophoresis (DDGE) analysis may be used. In another method of detecting the polymorphism, a polynucleotide comprising the polymorphic region is sequenced across the region that contains the polymorphism to determine the presence of the polymorphism.


The presence of the polymorphism may be detected by means of fluorescence resonance energy transfer (FRET). In particular, the polymorphism may be detected by means of a dual hybridisation probe system. This method involves the use of two oligonucleotide probes that are located close to each other and that are complementary to an internal segment of a target polynucleotide of interest, where each of the two probes is labelled with a fluorophore. Any suitable fluorescent label or dye may be used as the fluorophore, such that the emission wavelength of the fluorophore on one probe (the donor) overlaps the excitation wavelength of the fluorophore on the second probe (the acceptor). A typical donor fluorophore is fluorescein (FAM), and typical acceptor fluorophores include Texas red, rhodamine, LC-640, LC-705 and cyanine 5 (Cy5).


In order for fluorescence resonance energy transfer to take place, the two fluorophores need to come into close proximity on hybridisation of both probes to the target. When the donor fluorophore is excited with an appropriate wavelength of light, the emission spectrum energy is transferred to the fluorophore on the acceptor probe resulting in its fluorescence. Therefore, detection of this wavelength of light, during excitation at the wavelength appropriate for the donor fluorophore, indicates hybridisation and close association of the fluorophores on the two probes. Each probe may be labelled with a fluorophore at one end such that the probe located upstream (5′) is labelled at its 3′ end, and the probe located downstream (3′) is labelled at its 5′ end. The gap between the two probes when bound to the target sequence may be from 1 to 20 nucleotides, preferably from 1 to 17 nucleotides, more preferably from 1 to 10 nucleotides, such as a gap of 1, 2, 4, 6, 8 or 10 nucleotides.


The first of the two probes may be designed to bind to a conserved sequence of the gene adjacent to a polymorphism and the second probe may be designed to bind to a region including one or more polymorphisms. Polymorphisms within the sequence of the gene targeted by the second probe can be detected by measuring the change in melting temperature caused by the resulting base mismatches. The extent of the change in the melting temperature will be dependent on the number and base types involved in the nucleotide polymorphisms.


Polymorphism typing may also be performed using a primer extension technique. In this technique, the target region surrounding the polymorphic site is copied or amplified for example using PCR. A single base sequencing reaction is then performed using a primer that anneals one base away from the polymorphic site (allele-specific nucleotide incorporation). The primer extension product is then detected to determine the nucleotide present at the polymorphic site. There are several ways in which the extension product can be detected. In one detection method for example, fluorescently labelled dideoxynucleotide terminators are used to stop the extension reaction at the polymorphic site. Alternatively, mass-modified dideoxynucleotide terminators are used and the primer extension products are detected using mass spectrometry. By specifically labelling one or more of the terminators, the sequence of the extended primer, and hence the nucleotide present at the polymorphic site can be deduced. More than one reaction product can be analysed per reaction and consequently the nucleotide present on both homologous chromosomes can be determined if more than one terminator is specifically labelled.


The invention further provides primers or probes that may be used in the detection of any of the polymorphisms defined herein for use in the prediction of susceptibility to or protection from liver copper accumulation. Polynucleotides of the invention may also be used as primers for primer extension reactions to detect the SNPs defined herein.


Such primers, probes and other polynucleotide fragments will preferably be at least 10, preferably at least 15 or at least 20, for example at least 25, at least 30 or at least 40 nucleotides in length. They will typically be up to 40, 50, 60, 70, 100 or 150 nucleotides in length. Probes and fragments can be longer than 150 nucleotides in length, for example up to 200, 300, 400, 500, 600, 700 nucleotides in length, or even up to a few nucleotides, such as five or ten nucleotides, short of a full length polynucleotide sequence of the invention.


Primers and probes for genotyping the polymorphisms of the invention may be designed using any suitable design software known in the art using the sequences in Tables 4, 5, 6, 8, 18 and 20. Homologues of these polynucleotide sequences would also be suitable for designing primers and probes. Such homologues typically have at least 70% homology, preferably at least 80, 90%, 95%, 97% or 99% homology, for example over a region of at least 15, 20, 30, 100 more contiguous nucleotides. The homology may be calculated on the basis of nucleotide identity (sometimes referred to as “hard homology”).


For example, the UWGCG Package provides the BESTFIT program that can be used to calculate homology (for example used on its default settings) (Devereux et al (1984) Nucleic Acids Research 12, p38′7-395). The PILEUP and BLAST algorithms can be used to calculate homology or line up sequences (such as identifying equivalent or corresponding sequences (typically on their default settings), for example as described in Altschul S. F. (1993) J Mol Evol 36:290-300; Altschul, S, F et al (1990) J Mol Biol 215:403-10.


Software for performing BLAST analyses is publicly available through the National Center for Biotechnology Information (http://www.ncbi.nlm.nih.gov/). This algorithm involves first identifying high scoring sequence pairs (HSPs) by identifying short words of length W in the query sequence that either match or satisfy some positive-valued threshold score T when aligned with a word of the same length in a database sequence. T is referred to as the neighborhood word score threshold (Altschul et al, supra). These initial neighborhood word hits act as seeds for initiating searches to find HSPs containing them. The word hits are extended in both directions along each sequence for as far as the cumulative alignment score can be increased. Extensions for the word hits in each direction are halted when: the cumulative alignment score falls off by the quantity X from its maximum achieved value; the cumulative score goes to zero or below, due to the accumulation of one or more negative-scoring residue alignments; or the end of either sequence is reached. The BLAST algorithm parameters W, T and X determine the sensitivity and speed of the alignment. The BLAST program uses as default a word length (W) of 11, the BLOSUM62 scoring matrix (see Henikoff and Henikoff (1992) Proc. Natl. Acad. Sci. USA 89: 10915-10919) alignments (B) of 50, expectation (E) of 10, M=5, N=4, and a comparison of both strands.


The BLAST algorithm performs a statistical analysis of the similarity between two sequences; see e.g., Karlin and Altschul (1993) Proc. Natl. Acad. Sci. USA 90: 5873-5787. One measure of similarity provided by the BLAST algorithm is the smallest sum probability (P(N)), which provides an indication of the probability by which a match between two polynucleotide sequences would occur by chance. For example, a sequence is considered similar to another sequence if the smallest sum probability in comparison of the first sequence to the second sequence is less than about 1, preferably less than about 0.1, more preferably less than about 0.01, and most preferably less than about 0.001.


The homologous sequence typically differs by at least 1, 2, 5, 10, 20 or more mutations, which may be substitutions, deletions or insertions of nucleotides.


The polynucleotides of the invention such as primers or probes may be present in an isolated or substantially purified form. They may be mixed with carriers or diluents that will not interfere with their intended use and still be regarded as substantially isolated. They may also be in a substantially purified form, in which case they will generally comprise at least 90%, e.g. at least 95%, 98% or 99%, of polynucleotides of the preparation.


Detector Antibodies


A detector antibody is an antibody that is specific for one polymorphism but does not bind to any other polymorphism as described herein. Detector antibodies are for example useful in purification, isolation or screening methods involving immunoprecipitation techniques.


Antibodies may be raised against specific epitopes of the polypeptides of the invention. An antibody, or other compound, “specifically binds” to a polypeptide when it binds with preferential or high affinity to the protein for which it is specific but does substantially bind not bind or binds with only low affinity to other polypeptides. A variety of protocols for competitive binding or immunoradiometric assays to determine the specific binding capability of an antibody are well known in the art (see for example Maddox et al, J. Exp. Med. 158, 1211-1226, 1993). Such immunoassays typically involve the formation of complexes between the specific protein and its antibody and the measurement of complex formation.


For the purposes of this invention, the term “antibody”, unless specified to the contrary, includes fragments that bind a polypeptide of the invention. Such fragments include Fv, F(ab′) and F(ab′)2 fragments, as well as single chain antibodies. Furthermore, the antibodies and fragment thereof may be chimeric antibodies, CDR-grafted antibodies or humanised antibodies.


Antibodies may be used in a method for detecting polypeptides of the invention in a biological sample (such as any such sample mentioned herein), which method comprises:


I providing an antibody of the invention;


II incubating a biological sample with said antibody under conditions which allow for the formation of an antibody-antigen complex; and


III determining whether antibody-antigen complex comprising said antibody is formed.


Antibodies of the invention can be produced by any suitable method. Means for preparing and characterising antibodies are well known in the art, see for example Harlow and Lane (1988) “Antibodies: A Laboratory Manual”, Cold Spring Harbor Laboratory Press, Cold Spring Harbor, NY For example, an antibody may be produced by raising an antibody in a host animal against the whole polypeptide or a fragment thereof, for example an antigenic epitope thereof, hereinafter the “immunogen”. The fragment may be any of the fragments mentioned herein (typically at least 10 or at least 15 amino acids long).


A method for producing a polyclonal antibody comprises immunising a suitable host animal, for example an experimental animal, with the immunogen and isolating immunoglobulins from the animal's serum. The animal may therefore be inoculated with the immunogen, blood subsequently removed from the animal and the IgG fraction purified. A method for producing a monoclonal antibody comprises immortalising cells which produce the desired antibody. Hybridoma cells may be produced by fusing spleen cells from an inoculated experimental animal with tumour cells (Kohler and Milstein (1975) Nature 256, 495-497).


An immortalized cell producing the desired antibody may be selected by a conventional procedure. The hybridomas may be grown in culture or injected intraperitoneally for formation of ascites fluid or into the blood stream of an allogenic host or immunocompromised host. Human antibody may be prepared by in vitro immunisation of human lymphocytes, followed by transformation of the lymphocytes with Epstein-Barr virus.


For the production of both monoclonal and polyclonal antibodies, the experimental animal is suitably a goat, rabbit, rat, mouse, guinea pig, chicken, sheep or horse. If desired, the immunogen may be administered as a conjugate in which the immunogen is coupled, for example via a side chain of one of the amino acid residues, to a suitable carrier. The carrier molecule is typically a physiologically acceptable carrier. The antibody obtained may be isolated and, if desired, purified.


Detection Kit


The invention also provides a kit that comprises means for typing one or more of the polymorphisms defined herein. In particular, such means may include a specific binding agent, probe, primer, pair or combination of primers, or antibody, including an antibody fragment, as defined herein which is capable of detecting or aiding detection of the polymorphisms defined herein. The primer or pair or combination of primers may be sequence specific primers that only cause PCR amplification of a polynucleotide sequence comprising the polymorphism to be detected, as discussed herein. The primer or pair of primers may alternatively not be specific for the polymorphic nucleotide, but may be specific for the region upstream (5′) and/or downstream (3′). These primers allow the region encompassing the polymorphic nucleotide to be copied. A kit suitable for use in the primer-extension technique may specifically include labelled dideoxynucleotide triphosphates (ddNTPs). These may for example be fluorescently labelled or mass modified to enable detection of the extension product and consequently determination of the nucleotide present at the polymorphic position.


The kit may also comprise a specific binding agent, probe, primer, pair or combination of primers, or antibody that is capable of detecting the absence of the polymorphism. The kit may further comprise buffers or aqueous solutions.


The kit may additionally comprise one or more other reagents or instruments that enable any of the embodiments of the method mentioned above to be carried out. Such reagents or instruments may include one or more of the following: a means to detect the binding of the agent to the polymorphism, a detectable label such as a fluorescent label, an enzyme able to act on a polynucleotide, typically a polymerase, restriction enzyme, ligase, RNAse H or an enzyme which can attach a label to a polynucleotide, suitable buffer(s) or aqueous solutions for enzyme reagents, PCR primers which bind to regions flanking the polymorphism as discussed herein, a positive and/or negative control, a gel electrophoresis apparatus, a means to isolate DNA from sample, a means to obtain a sample from the individual, such as swab or an instrument comprising a needle, or a support comprising wells on which detection reactions can be carried out. The kit may be, or include, an array such as a polynucleotide array comprising the specific binding agent, preferably a probe, of the invention. The kit typically includes a set of instructions for using the kit.


Bioinformatics


The sequences of the polymorphisms may be stored in an electronic format, for example in a computer database. Accordingly, the invention provides a database comprising information relating to one or more polymorphisms selected from:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or


(c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158);


and their association with the susceptibility of a dog to liver copper accumulation. The database may also comprise information relating to any of the other polymorphisms described herein. The database may include further information about the polymorphism, for example the degree of association of the polymorphism with the susceptibility of a dog to liver copper accumulation.


The invention also provides a database comprising information relating to one or more polymorphisms selected from:


(a) Chr22_3135144 (SEQ ID NO: 145); and


(b) one or more polymorphisms in linkage disequilibrium with (a);


and their association with the protection of a dog from liver copper accumulation.


The database may also comprise information relating to any of the other polymorphisms described herein. The database may include further information about the polymorphism, for example the degree of association of the polymorphism with the protection of a dog from liver copper accumulation.


A database as described herein may be used to determine whether the genome of a dog comprises one or more polymorphisms indicative of protection from, or susceptibility to, liver copper accumulation. Such a determination may be carried out by electronic means, for example by using a computer system (such as a PC).


Typically, the determination of whether the genome of a dog comprises one or more polymorphisms indicative of susceptibility to or protection from liver copper accumulation will be carried out by inputting to a computer system genetic data from the dog to a computer system; comparing the genetic data to a database as defined herein; and on the basis of this comparison, determining whether the genome of a dog comprises one or more polymorphisms indicative of susceptibility to, or protection from, liver copper accumulation. This information can then be used to guide the management of the liver copper levels of the dog or can be used for informed breeding purposes.


The invention also provides a computer program comprising program code means for performing all the steps of a method of the invention when said program is run on a computer. Also provided is a computer program product comprising program code means stored on a computer readable medium for performing a method of the invention when said program is run on a computer. A computer program product comprising program code means on a carrier wave that, when executed on a computer system, instruct the computer system to perform a method of the invention is additionally provided.


As illustrated in FIG. 10, the invention also provides an apparatus arranged to perform a method according to the invention. The apparatus typically comprises a computer system, such as a PC. In one embodiment, the computer system comprises: means 20 for receiving genetic data from the dog; a module 30 for comparing the data with a database 10 comprising information relating to polymorphisms; and means 40 for determining on the basis of said comparison whether the genome of a dog comprises one or more polymorphisms indicative of protection of a dog from, or susceptibility of a dog to, liver copper accumulation.


Breeding Tool


Breeding value is defined as the value of an individual as a parent and is commonly used for improving desirable traits of life-stock in the farming industry. In order to improve the overall copper handling ability of dogs and to reduce the incidence of copper associated diseases, such as chronic hepatitis, it would be advantageous to select dogs for breeding that are protected from, or are not susceptible to, liver copper accumulation. This problem is solved by the use of polymorphisms that can be used to determine whether a dog is protected from, or not susceptible to, liver copper accumulation in order to inform breeding.


For example, the copper handling ability of the offspring of two dogs may be influenced by the genotype of the parents at the ATP7B locus. The transfer of a particular variant at this locus could be beneficial to the offspring. By determining the genotype at this locus it will be possible to assess the breeding value of a prospective parent and thereby make decisions as to whether a given breeding pair are appropriate.


Accordingly, the invention provides a method of selecting a dog for producing offspring protected from liver copper accumulation comprising determining whether the genome of a dog comprises one or more polymorphisms indicative of protection from liver copper accumulation by a method of the invention in a candidate first dog; and thereby determining whether the candidate first dog is suitable for producing offspring protected from liver copper accumulation. The method may further comprise determining whether the genome of a dog comprises one or more polymorphisms indicative of protection from liver copper accumulation by a method of the invention in a second dog of the opposite sex to the first dog. If the results are that the first and/or second dog has a genotype indicative of protection from liver copper accumulation, the first dog may then be mated with the second dog in order to produce offspring protected from liver copper accumulation.


For example, the method may comprise determining the presence or absence of one or more polymorphisms selected from Chr22_3135144 (SEQ ID NO: 145) and one or more polymorphisms in linkage disequilibrium thereof in the genome of the candidate first dog. More preferably the method further comprises determining the presence or absence of the SNP ChrX_63338063 (ATP7a_Reg3 F 6 SNP; SEQ ID NO: 142) or one or more polymorphisms in linkage disequilibrium with said SNP such as ChrX_63397393 (ATP7a_Reg16 F 42 SNP; SEQ ID NO:143). The method of the invention may comprise determining the presence or absence of the A allele of Chr22_3135144 (SEQ ID NO: 145) and/or the T allele of ChrX_63338063 (SEQ ID NO:142). The presence of one or more of these SNPs indicates that the first dog is protected from liver copper accumulation and is therefore a good candidate to be mated with a second dog. Homozygosity in either the first and/or second dog is most preferable as this increases the likelihood that the offspring will be homozygous and thereby protected from liver copper accumulation.


The invention also provides a method of selecting a dog for producing offspring protected from liver copper accumulation by making use of the polymorphisms of the invention that are indicative of susceptibility to copper accumulation. The absence of such polymorphisms in the genome of the dog indicates that the dog is a good candidate for mating. The method of the invention may therefore comprise determining whether the genome of the candidate first dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation; and thereby determining whether the candidate first dog is suitable for producing offspring protected from liver copper accumulation.


The method may comprise detecting the presence or absence in the genome of the candidate first dog of one or more polymorphisms selected from:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or


(c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


The method may further comprise determining whether the genome of a second dog of the opposite sex to the first dog comprises one or more polymorphisms indicative of susceptibility to liver copper accumulation. The method may therefore comprise detecting the presence or absence in the genome of a second dog of one or more polymorphisms selected from:


(a) Chr22_3167534 (SEQ ID NO: 144), Chr22_3135144 (SEQ ID NO: 145), Chr20_55461150 (SEQ ID NO: 146), ChrX_120879711 (SEQ ID NO: 147), Chr19_6078084 (SEQ ID NO: 148), Chr15_62625262 (SEQ ID NO: 149), Chr14_39437543 (SEQ ID NO: 150), Chr15_62625024 (SEQ ID NO: 151), Chr3_86838677 (SEQ ID NO: 152), Chr24_4011833 (SEQ ID NO: 153), Chr18_60812198 (SEQ ID NO: 154), Chr10_65209946 (SEQ ID NO: 155), and the CGCCCC repeat at chromosome location 22:3135287;


(b) one or more polymorphisms in linkage disequilibrium with a said polymorphism (a); and/or


(c) Chr32_38904515 (SEQ ID NO: 156), Chr8_4892743 (SEQ ID NO: 157) and Chr8_4880518 (SEQ ID NO: 158).


If the results are that the genome of the first and/or second dog does not have a genotype indicative of susceptibility to liver copper accumulation, the first dog may then be mated with the second dog in order to produce offspring that is not susceptible to liver copper accumulation.


The method may further comprise detecting the presence or absence in the genome of the candidate first dog of (I) a polymorphism in the GOLGAS, ATP7A or UBLS gene that is indicative of susceptibility to liver copper accumulation and/or (II) a polymorphism in linkage disequilibrium with a said polymorphism (I). Preferably, the method comprises determining the presence or absence of one or more polymorphisms selected from the SNPs identified in Tables 4 to 6 and one or more polymorphisms in linkage disequilibrium thereof in the genome of the candidate first dog. The presence of one or more of these polymorphisms indicates that the first dog is susceptible to liver copper accumulation and is therefore not a good candidate to be mated with a second dog to produce offspring protected from liver copper accumulation.


The candidate first dog and/or second dog may be of any breed. Preferably the candidate first dog and/or second dog has genetic breed inheritance of a breed selected from Labrador Retriver, Doberman Pinscher, German Shepherd, Keeshond, Cocker Spaniel, West Highland White Terrier, Bedlington Terrier and Skye Terrier. More preferably, the candidate first dog and/or second dog has genetic inheritance of the Labrador Retriever breed. The dog may be a purebred Labrador Retriever. Alternatively, the dog may be a mixed or crossbred dog, or an outbred dog (mongrel). One or both of the parents of the dog may be a pure-bred Labrador Retriever dog. One, two, three or four of the grandparents of the dog may be a pure-bred Labrador Retriever dog. The dog may have at least 50% or at least 75% of the Labrador Retriever breed in its genetic background. Thus, at least 50% or at least 75% of the dog's genome may be derived from the Labrador Retriever breed.


The genetic breed inheritance of a dog may be determined by assessing the allelic frequencies of genetic markers, for example SNPs or microsatellites. The combinations of allelic frequencies of different SNPs or microsatellites in a dog provide a signature that allows the breed of a dog or the breeds that make up a mixed breed dog to be determined. Such a genetic test may be a commercially available test. Alternatively, the dog may not need to be tested for a particular breed inheritance because it is suspected of having a particular breed inheritance for example by the dog owner or veterinarian. This could be for example because of knowledge of the dog's ancestry or because of its appearance.


Most purebred dogs of breeds recognized by all-breed club registries are controlled by “closed studbooks”. A studbook is typically the official registry of approved dogs of a given breed kept by, for example, a breed association or kennel club. It is generally termed a “closed” studbook if dogs can only be added if their parents were both registered. Most breeds have closed studbooks, resulting in inbreeding, as genetic diversity cannot be introduced from outside the existing population. In a number of breeds recognized by kennel clubs this has resulted in high incidences of genetic diseases or disorders and other problems such as reduced litter sizes, reduced lifespan and inability to conceive naturally.


In order to avoid the problems associated with inbreeding, it would be advantageous to select dogs for breeding within a particular breed that are more distantly related to each other compared to dogs that are more closely related. Therefore in one aspect of the invention, the genetic breed inheritance of the candidate first dog and of the candidate second dog is determined in order to determine the degree of relatedness of the two dogs. In this aspect of the invention, the term “genetic breed inheritance” relates to the dog's genetic ancestry within a particular breed. The dog's genetic breed inheritance may be determined as described herein. By determining the dogs' genetic inheritance, it is possible to distinguish between dogs within a single breed in order to determine how closely related they are.


Therefore, in one aspect of the invention the degree of relatedness of the candidate first dog and the candidate second dog is determined, which comprises comparing the genetic breed inheritance of the candidate first dog with the candidate second dog of the same breed. Preferably the dogs are purebred dogs. The genetic breed inheritance of each dog may for example be determined by identifying the presence or absence of one or more breed-specific polymorphisms in said dog.


The degree of relatedness may be determined from the number of breed-specific polymorphisms that the dogs have in common. For example, two dogs of the same breed may have from 0 to 100% of the breed-specific polymorphisms tested in common, for example from 10 to 90%, from 20 to 80%, from 30 to 70% or from 40 to 60%. Therefore, two dogs may have at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80% or 90% of the breed-specific polymorphisms tested in common. The percentage of tested breed-specific polymorphisms in common between two dogs may be used as a measure of their degree of relatedness. In this aspect of the invention, the two dogs would only be mated together if they are sufficiently genetically unrelated. For example, they may only be mated together if they have less than 60%, 50%, 40%, 30% or less than 20% of the breed-specific polymorphisms tested in common.


The invention also provides a method of selecting one or more dogs for breeding with a subject dog, the method comprising:

    • (a) determining for a subject dog and for each dog in a test group of two or more dogs of the opposite sex to the subject dog whether the genome comprises one or more polymorphisms indicative of protection from, and/or one or more polymorphisms indicative of susceptibility to, liver copper accumulation; and
    • (b) selecting one or more dogs from the test group for breeding with the subject dog.


The test group may consist of at least 2, 3, 4, 5, 10, 15, 20, 25, 30, 50, 75, 100 or 200 different dogs, for example from 2 to 100, from 5 to 70 or from 10 to 50 dogs. The dogs are typically selected from the test group on the basis of being protected from liver copper accumulation. The dog or dogs selected from the test group may have the same or similar genetic breed inheritance as the subject dog.


The subject dog and each dog in the test group may be of any breed. Preferably the subject dog and/or each dog in the test group has genetic breed inheritance of a breed selected from Labrador Retriver, Doberman Pinscher, German Shepherd, Keeshond, Cocker Spaniel, West Highland White Terrier, Bedlington Terrier and Skye Terrier. More preferably the dog has genetic breed inheritance of the Labrador Retriever breed. The dog may be a purebred Labrador Retriever. Alternatively, the dog may be a mixed or crossbred dog, or an outbred dog (mongrel). One or both of the parents of the dog may be a pure-bred Labrador Retriever dog. One, two, three or four of the grandparents of the dog may be a pure-bred Labrador Retriever dog. The dog may have at least 50% or at least 75% of the Labrador Retriever breed in its genetic background. Thus, at least 50% or at least 75% of the dog's genome may be derived from the Labrador Retriever breed.


The dog within the test group that is most likely to be protected from liver copper accumulation, based on the presence or absence of polymorphisms associated with protection from or susceptibility to liver copper accumulation, may be selected for breeding with the subject dog. Alternatively, a number of the dogs within the test group that are likely to be protected from liver copper accumulation are selected for breeding with the subject dog. For example, at least 2, 3, 4, 5, 10, 15 or 20 dogs in the test group may be selected. A further selection may then be made from the group of selected dogs based on other factors, for example geographical location, age, breeding status, medical history, disease susceptibility or physical characteristics.


As explained above, it is desirable to mate dogs within the same breed that are most genetically unrelated. This is in order to increase or maintain genetic diversity within the breed, and to reduce the likelihood of problems relating to inbreeding arising within the offspring. A further selection of the dogs from the test group may therefore be based on the genetic relatedness of the dogs with the subject dog. Accordingly, the method may further comprise:


(a) comparing the genetic breed inheritance of the subject dog with the genetic breed inheritance of each dog in a test group of two or more dogs of the same breed and of the opposite sex to the subject dog;


(b) determining from the comparison the degree of relatedness between the subject dog and each dog in the test group; and


(c) selecting one or more dogs from the test group for breeding with the subject dog.


The dogs may be selected from the test group on the basis of their relatedness to the subject dog (i.e. the dog to be bred from). Preferably the dog or dogs selected from the test group are the most distantly related (i.e. have the lowest degree of relatedness) within the test group of dogs. The genetic breed inheritance of the subject dog and the dogs in the test group may be already known or may be determined e.g. by a commercially available breed test.


The invention thus provides a method of recommending one or more suitable dogs for breeding with a subject dog. The recommendation may be made to the subject dog's owner or carer, a veterinarian, dog breeder, kennel club or breed registry.


The invention also relates to a method of breeding dogs, wherein the protection from, or susceptibility to, liver copper accumulation of at least two dogs of the opposite sex is determined, optionally within the same breed, before breeding them together.


The protection from, or susceptibility to, liver copper accumulation of a dog may be stored in an electronic format, for example in a computer database. Accordingly, the invention provides a database comprising information relating to the susceptibility to, or protection from, liver copper accumulation and sex of one or more dogs. The database may include further information about the dog, for example the dog's genetic breed inheritance, breeding status, age, geographical location, medical history, disease susceptibility or physical characteristics. The database will typically further comprise a unique identifier for each dog, for example the dog's registered name. The database may be accessed remotely, for example using the internet.


The invention is illustrated by the following Examples:


Example 1

Whole Genome Association Study and Identification of Regions Potentially Containing Informative Genes


This Example describes the general approach that was taken to develop a genetic predictive test for copper accumulation. It also details the methodology used for a whole genome association study and the identification of regions of the genome potentially containing informative genes.


The general approach used to develop a genetic predictive test for copper accumulation was as follows. First, collected samples from dogs diagnosed as “affected” or “unaffected” by liver copper accumulation were run on a genotyping array with a large number of markers. This is known as a “whole genome association study”. Analysis of this data gave an indication of regions potentially containing informative genes. Informative SNPs in regions with interesting genes were then used in model generation. In parallel, the interesting genes were sequenced to look for coding mutations or other mutations that better describe the genetic effect on the disease. These mutations were then used in further model generation. In practice, this process involved loops and parallel tracks because of ongoing improvements in technology.


Patient Recruitment


Data were collected from 254 Labrador retrievers. The dogs were recruited in two ways. Clinically affected dogs were admitted to the Hepatology department of the Faculty of Veterinary Medicine, Utrecht University by a referring veterinarian. First line relatives of affected dogs were actively recruited via registration files of the Dutch Labrador retriever breed club.


Diagnosis


Every dog underwent a physical examination and blood was collected for coagulation testing, determination of liver enzymes (Alkaline phosphatase and Alanine Amino Transferase), bile acids and albumin. An EDTA blood sample was used for DNA isolation.


Liver biopsies were obtained from 239 dogs by Menghini technique, ultrasound guided with a Trucut 14 Gauge needle device, collected during laparoscopy or laparotomy or taken after euthanasia (Teske et al., 1992, Vet. Rec. 131:30-32). Liver biopsies were fixed in 4% buffered formalin for 3 hours, transferred to 70% ethanol and embedded in paraffin. Five micron sections were mounted on slides and stained with Haematoxylin and Eosin (routine evaluation), von Giesson (reticulin staining) and rubeanic acid (copper staining).


Diagnosis was based on histological evaluation of a liver biopsy by our board certified pathologist (TSGAMvdI). Severity of copper accumulation was scored on a scale from 0 to 5 as described previously (Teske et al., 1992, Vet. Rec. 131:30-32). An additional liver biopsy was collected in a copper free container, freeze dried and quantitative copper was determined by Instrumental Neutron Activation Analysis (INAA) in dry weight liver (Bode et al., 2008, Anal. Bioanal. Chem. 390:1653-1658).


The histology score is described below:


Grade 0—no copper.


Grade 1—solitary liver cells contain some copper positive granules.


Grade 2—small groups or area of liver cells contain small to moderate amounts of copper positive granules.


Grade 3—larger groups or areas of liver cells contain moderate amounts of copper positive granules, sometimes associated with copper containing macrophages.


Grade 4—large areas of liver cells with many copper positive granules, usually associated with copper containing macrophages.


Grade 5—diffuse pan-lobular presence of liver cells with many copper positive granules, usually associated with copper containing macrophages.


Sample Phenotyping


Copper-Associated Chronic Hepatitis has previously been phenotypically characterised (Hoffmann et al., 2006, J. Vet. Intern. Med. 20: 856-861). Four phenotypes were defined based on evaluation of the liver biopsies.


For the purposes of the 22 k chip data (see below) we designated liver copper concentrations above 600 mg/kg dry weight as “affected” and below 400 mg/kg dry weight as “unaffected” (quantaff).


A binary phenotype for the most clear copper toxicosis cases and controls was also applied (cutox). A case was defined as having a liver copper level>1200 mg/kg or copper staining>3 and histological signs of hepatitis. A control was defined as having liver copper level<400 mg/kg and staining of <2 and no abnormalities on histology. A more separated phenotype was used to increase the resolution of the genetic mapping.


A semi-quantitative scoring by the pathologist based on rubeanic acid staining was used as a quantitative phenotype (ra) (score 0-5) and was available in all dogs that underwent a liver biopsy.


Quantitative copper level in liver tissue was used as a quantitative phenotype (cuq) and ranged from 65 to 3870 mg/kg.


Genotyping (Illumina 22K Chip)


Genome-wide genotyping was carried out using the first generation Illumina canine genotyping array, which aims to measure approximately 22,000 SNP loci (22K chip). We ran 251 dog DNA samples on this array.


Chi-Squared Analysis


The data were analysed with a collection of chi-squared tests. A two degrees of freedom test was used. Loci were then ranked by p-value to prioritise further investigation.


Pairwise Analysis


Typically genetic mapping is done by genotyping selected samples on markers spread across the whole genome. The samples are phenotyped for a trait such as a disease. The samples are typically selected from a single sub population and selected to be as unrelated within that population as possible. This is done to reduce the risk of getting false positive hits from the population structure.


In previous canine genetic studies it was difficult to satisfy these stringent criteria as dogs are constantly under large amounts of varying genetic selection. This creates population structure in the dataset across subtypes of breeds, geographies, time and social cliques. New methods had to be developed to analyse the canine genetic data in the presence of population structure and closely related samples. Pair-wise mapping was the most successful method developed for this purpose.


A method was developed to determine the polymorphisms associated with a genetic trait in a group of individuals, namely “Partition Mapping” (also known as “2D mapping”). The method is currently limited to binary conditions (case/control studies). Complex diseases with a genetic link are generally driven by more than one gene. These genes can interact in non-linear ways, making them more difficult to map using traditional methods. By working on the level of a pair of individuals it is possible to factor out the impact of multiple genes because a locus will either be contributing to the phenotype on that pair of individuals or not. The full working of this process is described below. After running this analysis it is possible to extract the risk alleles in each area and build a model to predict the phenotype using other methods.


The “Partition Mapping” algorithm scans through the genome stopping every 50 kilobases. At each of these points, every pair of individuals is analysed. For each pair, the genotypes for the whole chromosome are analysed comparing the likelihood of the genotypes under three possible scenarios. The first scenario is that there is a recessive mutation driving the phenotype in this pair of individuals. The second scenario is that there is a dominant mutation driving the phenotype in this pair of individuals. The third scenario is that there is no important mutation for the phenotype in the pair of dogs at this location. The likelihoods are calculated using a hidden markov model, described below. By comparing these likelihoods it is possible to derive a Bayes-Factor for this pair of individuals towards or against the presence of a recessive or dominant phenotype-driving mutation at that point. The log of these values is taken; a positive value then represents more weight towards the recessive or dominant mutation scenario, a negative value represents more evidence towards there being no important mutation here.


The pairs of individuals are sorted in order of the Log-Bayes factors at that locus. The pairs' Log-Bayes-Factors are then summed up in descending order taking a record of the cumulative weight of evidence at each percentile of the data. In most cases some Log-Bayes-Factors will be positive and some will be negative. This will give the effect of the recorded value rising for a percentage of the data and then falling. The maximum of this value gives a measure of the weight of evidence towards either the recessive or dominant models. This is referred to as the “peak-value”.


In some cases the algorithm has bias towards particularly homozygous areas of the genome or areas with a high density of polymorphisms. This effect is quantified by running the process with every pair permuted across the four possible case/control states (case-case, case-control, control-case, control-control). For any locus, one subtracts the peak-value under the permuted model from the normal peak-value, and this gives a corrected peak-value. It is then possible to compare the corrected peak-values across the genome giving regions of interest. This method has been used to map a number of locations associated with copper loading in the liver. These locations are marked by haplotype patterns indicative of a trait-linked gene. The locations were then investigated for likely genes.


Region Gene Analysis


Regions identified in the whole genome association study were then analysed for likely genes. The process involved identifying the informative region boundaries; identifying all genes in the region in Ensembl; looking for relevant protein domains related to copper or liver function; looking for membership of pathways linked to copper; and looking for genes expressed in relevant tissues. Based on this information, genes were then prioritised by likelihood of involvement with the disease.


A number of candidate genes associated with copper accumulation or liver disease were identified by this process.


Genotyping (Illumina 170K Chip)


A newer SNP chip than the 22K chip described above became available which has 172,115 markers from more varied sources (170K chip). This chip contains on average more than 70 markers per Mb. We ran the same and further DNA samples on this array as were run on the 22K chip.


Analysis


Using the results from the 170K chip, genome wide association analysis was performed with GenABEL software (Aulchenko et al., 2007, Bioinformatics, 23: 12941296). SNPs that were successfully typed in 98% of individuals and individuals that had 98% of SNPs successfully genotyped were kept in the analysis. SNPs were kept in the analysis when at least 20 carriers were present. Significantly associated SNPs were checked for Hardy Weinberg Equilibrium (HWE) after analysis.


Genetic kinship was estimated based on autosomal genotype information. Heritability for three traits (copper toxicosis, rubeanic acid stain score and quantitative liver copper in mg/kg) was estimated by a polygenic model (Aulchenko et al., 2007, Genetics, 177: 577-585) in which population sub-structuring was accounted for by calculating the genetic kinship matrix. Age and sex were modeled as covariates. Population stratification was checked by a multidimensional scaling plot. Correction for stratification was performed by performing a score test on residuals of the estimates of the polygenic model and genomic control. The functions grammas (Amin et al., 2007, PloS One, 2: e1274) and fasta (Chen et al., 2007, Am. J. Hum. Genetics, 81: 913-926) were used to correct for population stratification. A thousand permutations were used in grammas analysis to obtain genome wide corrected p-values. The X-chromosome was analyzed separately for males and females.


The pairwise method described above was applied here also.


In total, 109496 markers and 253 dogs passed quality control. A summary of phenotypes and calculated heritability (H2) for each trait is depicted in Table 1.









TABLE 1







Summary of phenotypes



















Age in








years





Nr of

Nr of
Mean


Phenotype
H2

individuals
Sex
individuals
(Sd)
















Copper
0.64
Cases
33
Males
8
6.2 (2.2)


toxicosis



Females
25



(cutox)

Controls
62
Males
30
6.0 (2.6)






Females
32



Rubeanic
0.49

235
Males
80
5 9 (2.6)


acid stain



Females
155



score (ra)








(0-5)









The genome wide association analysis resulted in hits that were close to being genome wide significant results. Results of the top 5 significant SNPs for all three analyses are depicted in Table 2.












P-values for Fasta analysis of each of the three phenotypes.











Phenotype
Chromosome
Location
SNP name
p-value














Cutox
31
36465117
BICF2P124447
6.632271e−05



27
40245328
BICF2P154172
1.939526e−04



38
12095696
BICF2P981165
2.029342e−04



38
11652179
BICF2P514131
2.138857e−04



10
67858787
BICF2S23647325
2.733150e−04


Ra
22
7767302
BICF2G630316066
4.016960e−06



22
12463818
BICF2S23122114
1.464354e−05



22
12495308
BICF2S23320612
1.464354e−05



22
12511354
BICF2S2417189
1.464354e−05



22
7548442
BICF2G630315950
1.526836e−05


Cuq
18
38185045
BICF2G630699136
1.514989e−06



27
43555866
BICF2G630153553
2.723925e−06



18
40278498
BICF2G630697308
3.293349e−06



18
40223465
BICF2G630697352
5.019301e−06



18
40227604
BICF2G630697350
5.019301e−06









A close to genome wide significant region (p-value after 1000 permutations in grammas was 0.11) was identified with the ra genotype on chromosome 22. The associated region was found to span a 15 Mb region at the beginning of the chromosome. The candidate gene ATP7B was located in this region at 3.12-3.16 Mb. The analysis of this gene is described in Example 5.


Example 2

Three Region Model Generation


This Example describes the generation of a three-region model for determining susceptibility to liver copper accumulation. This work is also described in WO 2009/044152 A2, WO 2010/038032 A1 and WO 2010/116137 A1.


SNPs in and around the genes prioritised in the region analysis described in Example 1 were extracted from the dataset. These were analysed singly and in haplotypes looking for informative allele patterns associated with liver copper level.


The most significant (by 1 degree freedom chi-squared test) of these patterns were used in the model. SNPs near three genes (ATP7A, UBLS-ortholog and GOLGAS) were chosen for use in the model. A Boolean model was then generated, with each gene pattern being represented by either a 0 or a 1 (1 being the higher risk genotype or pattern) and the combination of the three patterns by a three number pattern (e.g. 0-0-0 or 0-1-1). 1-1-1 therefore represents the greatest risk of high liver copper.


Table 3 shows the result of the three-region model for predicting copper accumulation. Each region uses either a single SNP or a group of SNPs. The model shows a clear difference in risk of disease depending on the genotype of the dog using this simple model of SNPs in three genomic regions.









TABLE 3







A model predicting copper accumulation using genetic


mutations in three regions of the genome.













Chr 8 location:
Chr X
Chr 32






4850000 bp
location:
location:

Average

Number


(near
63000000 bp
40000000 bp
3 allele
of Cu2
% dogs
of dogs


GOLGA5)
(near ATP7A)
(near UBL5)
pattern
conc
affected
with pattern
















1
1
1
111
1253.09
81.5%
27


1
1
0
110
733.40
60.0%
20


1
0
1
101
1138.90
77.8%
9


1
0
0
100
737.84
60.7%
28


0
1
1
011
502.27
42.9%
7


0
1
0
010
670.83
63.6%
11


0
0
1
001
450.00
50.0%
4


0
0
0
000
332.47
7.1%
14










The key to the binary values in Table 3 is as set out below


Genomic location Chromosome 8 (CFA8), GOLGA5 gene region:


1=if there is an AA genotype at SNP BICF2P506595


0=if there is any other genotype at SNP BICF2P506595


Genomic location Chromosome 32 (CFA32), UBL5 gene region:


1=if there is a GG at BICF2P772765, a CC at BICF2S2333187 and a GG at BICF2P1324008


0=if any of those SNPs show a different genotype


Genomic location Chromosome X (CFAX), ATP7A gene region:


1=if there is an AA or an AG at BICF2P591872


0=if there is a GG at BICF2P591872


Table 3 represents the binary conditions of alleles at three genomic locations. At genomic location CFA8, one SNP was used (SNP 1). At genomic location CFA32 three SNPs were used (SNPs 2, 3 and 4). At genomic location CFAX one SNP was used (SNP 5). The binary values are indicative of a dog having alleles that are indicative of susceptibility to copper accumulation (“bad” alleles). For instance 000 represents not having any of the three bad alleles. 111 represents having all three bad alleles.


Table 4 shows the position and sequence of the SNPs used for the results in Table 3. The results implicated three genomic locations (in and around the GOLGAS, UBL5 and ATP7A genes) associated with susceptibility to copper accumulation. Further SNPs in these regions that are indicative of susceptibility to copper accumulation are provided in Table 5.









TABLE 4







Position and sequence of SNPs used for results in Table 3
















Gene






Location
containing



SNP name
SEQ ID
Chromosome
 in
or close to
SNP Sequence


(SNP no.)
NO:
in cafam 2
canfam 2
mutation
SNP = [first allele/sccond allele]















BICF2P506595
1
 8
 4886813
GOLGA5
CTCAGAACTAGATAGGCTAATAAGTGATAGGCCTTGTGTTTTC


(SNP 1)




CTAGAGTGTGCTTTAAA[A/G]GTTTCTTAAGCTAAAAAATTA







CATTCGTGAGAAAATTGAAATAAAAGGAAAACAGTCATG





BICF2P772765
2
32
39278300
UBL5
TCTCAGATACTTGATAGCCAGCATTTCCCCCCATTTTCTTCCA


(SNP 2)




AGAGCACGAAAGCATAG[A/G]AATGATATTACATCTCGTATG







GTGAATGTGACACAGCCGTCAGTTGCGTTAGCTCTGCTT





BICF2S2333187
3
32
39390236
UBL5
TATTACCCTGGTCTCCAGCCACTCCTTTACCTTCCATTAGCCC


(SNP 3)




ACACCTGCTCTACACAC[T/C]ATTGCTCATGGAAGCCTTGCC







ACGTGCAGTCGCCACTCTGAAATGCCAGCATCGCTCCCA





BICF2P1324008
4
32
40043909
UBL5
GACCTGACAGATTATGTAGACTTTGTTTTCAAAGGGAGCACCT


(SNP 4)




GCTGGATATACAACATG[A/G]CACTAAA7TGTGCTCCACATC







CTTGGCAGAGGTGGGGGGCGGGGCACAAAGGAAGAAACC





BICF2PS91872
5
X
62989720
ATP7A
GGGCCCAGCAAGTGGCAGAACTGGGAAGACCCCCTCTTCTTCC


(SNP 5)




GCCTGGAGCAGTGGTGT[A/G]GCAGCACACCACAGGAGTCTG







AAAGGGTGGGGAGTCCAAACGGGAACATATACCTGAGAT
















TABLE 5







Position and sequence of further SNPs indicative of susceptibility 


to liver copper accumulation















Chromo-
Loca-

Minor




SEQ
some in
tion in
Allele
Allele



SNP name
ID
canfam
canfam
Fre-
Fre-
SNP Sequence


(SNP no.)
NO:
2
2
quency
quency
SNP = [first allele/second allele]





BICF2P1246154
  6
 X
47335181
0.999507
0.000493
GGCAACAGGGACAGGCTGCTGGGCCACACACTCACCCACACT


(SNP 6)





AGGAGACAAGATCCTCCA[T/C]ATCCTGGGTCTCTATCAGT








CAATCACCTAGACCAGTGGGCCAGAGGACAGGGTCCAGCTG





BICF2P463335
  7
 X
44401786
0.000493
0.000493
GTTGAGAGAGATCATACAGATTCATGTGGCAGGTGCACACTT


(SNP 7)





TTTCTACCTCTTACAACG[T/C]ATTCTCTCTGGCCATTCCT








TCTCCTGGGTCCCAAAGTCGGAGAGCTTAGCGGGAGCCTAG





BICF2P1246989
  8
 8
 4149835
0.999506
0.000494
ataagttcacattttgGTGTTTCAAGTGGACATGAATGGAGG


(SNP 8)





GGAGGGCCCTGTTCAATC[T/C]ACTAAAGTGTTTTTTCATC








TTGTTTTTGTGGAAATCAAATCAAGAAGCAGAGTTTTATGT





BICF2P723557
  9
 8
 3406227
0.999014
0.000986
ACTCTCCCGATGTGGGCACCATATGGTGGACCACTTTCTGTG


(SNP 9)





TGAGATGCCTGCTCTTAT[T/C]GCCATGTCCTGTGAAGACA








CCATGCTGGTGGAAGCATTTGCCTTTGCCCTGGGTGTTGCC





BICF2S2342729
 10
 8
 5393517
0.999014
0.000986
AATCTAAGTAGACTGAGTGGTCACCTTCAGCGCTCAGACCTG


8





AGCATACAAAGCATGGAA[A/G]GTTACTGTGATTCAGCTGA


(SNP 10)





TGTAATGGAATGAAATAAATATAAGAGTTTGGTAACCTAAT





BICF2P312189
 11
 8
 5773958
0.9990l4
0.000986
TGGAGAGTGCTGGCAGGCAGGGGCAGGCAAACAACAATAGCA


(SNP 11)





AAGATCTCTTCCACGCTT[T/C]TACTTCCTCAAAAGTCCAA








GCCCTCTTAAGATCGCATTTTCTTAGTGACCTTCACTCTAA





BICF2S2432154
 12
 X
56410647
0.999014
0.000986
TTCTTTGCTAGGCCAAGGGCAGAGAATGCATGCCCCCCCTTA


3





CCTCCCAGGGCCCAAGAG[C/G]CATCCTGAGCTGAGTCTAT


(SNP 12)





GGCTCCTGGTGGGGGGCGGCTGTGGGTTGGGGGGGCACAGA





BICF2P1273450
 13
 8
 3160594
0.999013
0.000987
ggtgtcaccaatgccagcgagcaccagctggagggaacagga


(SNP 13)





cacaggtcctccgtcCTG[T/C]GACACTCGGATCTGGGGCT








TTGCCTCCAAAACGGAGACCATGCCTGTCCATGGTTCTACG





BICF2P1439540
 14
 8
 3771142
0.998521
0.001479
CTCTAGAACCCTTCAGGTAGACTACATTCACTTTCTACTACA


(SNP 14)





ACTTCATCACCACAACCA[A/T]CTCCCAGTAACCCCCtttt








tttcttctcctttttttattttttccttctttttgctcgtc





BICF2P506204
 15
 8
 4191144
0.998521
0.001479
TCCCATGGGTTGAAGGATATCTGGCAGACGGCTCCAACTCCA


(SNP 15)





GTAAAGCCTCAGGCCTCA[A/G]CCAGGAGTTCCCCGGGGCT








TCATTCCCATCCCAGACTTTGCCCAGGGCTGATTTGAAAGT





BICF2P380732
 16
 8
 3299879
0.998519
0.001481
TCTTCCTTGCAGATTGGATGGCTGTAGCCTCACCTCACACTG


(SNP 16)





TTGCTGGGATCTGTCCAC[A/G]CTTCTGACCTCCAGCAAGA








GCCTCCGGGAGCTAAGCCTGGGCAGCAATGACCTGGGAGAT





BICF2G6301602
 17
 X
73980557
0.004955
0.004955
TATTGCTAGTAAAGCCAAACTTTCTATTCCACAATTATAAAC


0





TCATGGAGATGGTAATTA[T/C]AGTGCATTATTTGTCAAAT


(SNP 17)





TTTATTATTTTTTCAAATCCCAAAGAAAATGTGATATTCTA





BICF2S2362356
 18
32
38362784
0.994576
0.005424
AAGAACAAGGATACAATCTAAGTGATAATCATCCAGCATGTA


9





CTTGTCCTGTTTTCAGAT[T/G]ATCAGCTTAAGTCAAGAGG


(SNP 18)





AATTTTTAGTGCTTACAAATATTTCAAGTGATTTTTCCAGA





BICF2P216837
 19
 8
 7474389
0.012327
0.012327
TGAAGGGGTGCTACTCAGGGCTCTTCATTTAACCTTCCAGGA


(SNP 19)





TGTTTTCCTATGTACTCA[T/C]TCTTCCTTTTGGTTGCTCC








TTCTTCTTGCATTTCTTTATCTCTTTACAGAATCATCCAGG





BICF2S2292214
 20
 X
75388683
0.986193
0.013807
acaaccctaaaatttcagtgattcagtacaacaaaggtttat


6





tATAACCATTCAGGGATC[C/G]AAGTTGGTAGAAACTTCAC


(SNP 20)





TACAATACCTGCTTCCAGTCAACAAGACAGAAAAAGAAAAA





BICF2G6301571
 21
 X
74415223
0.01382
0.01382
GCAGGGTTGATATATAACTAGTATGCATTAGGTAGACACCTA


4





TTTTGATTACTCACTATT[T/G]TAATATCAGCCTGGTAGTA


(SNP 21)





AGAACCAAATCTATTATGTAAAGTGCATAGAGAATTGaaag





BICF2G6301567
 22
 X
74439123
0.0143
0.0143
CTAGCTAGCCACCCAACTCCCCACATGCCCAGAGTCATCGTT


4





TATCTTTTCACATCAGCA[T/C]TACATTTTGGCTTGCATTC


(SNP 22)





AAACATTAGCCCATTTTTTTTCCTTTTGTTTTATTTATAGA





BICF2P426463
 23
 8
 5833993
0.015286
0.015286
TTTTCTCTTTTTCCATAAATGCTCTGGGCTTATTTTCATTAT


(SNP 23)





CTAGTATTTCTCTTCTGA[A/G]GCTAACTCCCAAAGAGTTT








TGTGCATCCTTATTTCCATCACAAGGTCAATGTACGAGTTA





BICF2S2292668
 24
 8
 7502279
0.015779
0.015779
GGGCCCAAGGGCTGAGGATCTCTGTACCTTCTGCTTCTTGGC


8





AGCCCAGGCTGGGTAGCA[T/G]TTCTTGGAAGAGGATTTCC


(SNP 24)





CATGAGTTGTTAACAGAAGGGCGGGCTTCCAGGCGCTGCTT





BICF2P1113947
 25
32
38074100
0.981169
0.018831
CATCTTTGCTTGGGGCCTGGGGTTTTTATTGAGGATTGTGAT


(SNP 25)





CTGGTGTATGTGTCTCCT[T/C]AGGCATCCAGAAACCATTC








AGAACAAGAACAAGCGTCCAGGTATCCTCTGTAAGTCACTT





BICF2P342874
 26
 X
44861101
0.020217
0.020217
ACAAACCCTCAGACCCAGATACACAGTATCATGTGGACACAG


(SNP 26)





ACATGTAACACCAAAATG[A/C]CCAACATCATGTGACTACA








GGCCCTAAGCAACTAGGTGTAACATCACTTGGTTATGGGCC





BICF2P1171925
 27
32
36457625
0.022189
0.022189
AATGCAGTAATACATGTAGCTAAACCTAACCATCAGAGTCTG


(SNP 27)





TTCTATCCTTCTACAAAA[A/G]TAGGGTTGGAGCTGAGCAC








ATAGGTAGCATACATCTAGCAAAAGTTTTTGCCTTCAgatt





BICF2G6301720
 28
 X
71984532
0.025641
0.025641
ttgtggggtcaggtgagttatggacccctccctactcttctg


0





ctatcttgccccCTACAG[T/G]GGTTGCTATTTTGATGTAA


(SNP 28)





TCACAAAACGACCTGGCAATAAAACCTTTTTCTAATTAggg





BICF2P1286548
 29
 X
57448138
0.026423
0.026423
GATGCAAGCTGGGACAGAATAAGGTACTGGGCTGTGTCAAGC


(SNP 29)





CCCAGTAAGAGAGGAGCA[T/C]TGTAGGGTAGTTAGGATGG








ACTTAATGGAGATGAGTCCTAGGGAGCCACACTCAGAGTTA





BICF2P790089
 30
32
38885957
0.0286
0.0286
TAAACACCCCCAATCACTACCATCCTCACACCTAAGGATACA


(SNP 30)





CAATGTGTCTACTTTATG[A/G]TATGTCTTTACTATTCGTT








GCTTATGAAATTTTATTCATTAWCTAAAACAGGGAAAAAAG





BICF2G6301671
 31
 X
72619011
0.9714
0.0286
TATAGYTGGSCAATTAAATCTCCTATTCTTTTGTCTCAAAGG


3





ATATTTGAAATTACATAG[T/C]TCTTTTCTCATATAAAACC


(SNP 31)





TACCATACAATCATTAGATGATCCTTCTTAGTTAATTTTTT





BICF2P276536
 32
 8
 3149437
0.966436
0.033564
GATGCTGTGGGCCAGTCCAGAACCCACCTGAGAGAAACAAAC


(SNP 32)





AGGCCTCTTTGCCAGCAG[A/G]GCAGCGTCAGTGTCACCCC








TGTGACATGTCAGAACCTCCCTGAAAGTTCATCTAACCTCT





BICF2G6301565
 33
 X
74531965
0.963018
0.036982
GGCTCAGAAGAAAAATCAGCCCAGTTCACATCCAATGTTTCC


8





ACACATCTAATCGTCTTG[A/G]GTTCAGAGGTAGATGTGGT


(SNP 33)





ATCACTTAYATGGACACATATAACAGCTGGCCCCCACCTCT





BICF2P308749
 34
 8
 7325380
0.962032
0.037968
gtttcagttaattatagtccttactggatccgattgctgtgg


(SNP 34)





cgctaaaatgaAAGAAGG[T/C]Agggtacctgggtggctca








ggggttgagaatctgcttttgactcaggtcatgatcccagg





BICF2P872820
 35
 8
 6388554
0.956114
0.043886
CAGAGTAGCATTATTTTCTGCTGTATGAGGACACTTTTGTTA


(SNP 35)





TATCCACAGTGGACAGAA[A/G]ACTGGGTTTTAGAAGATGC








TCAATTGAAACAAGACTGAGGGCTCACAAATTCCTGCTCCA





BICF2G6301621
 36
 X
73592920
0.955084
0.044916
TTACTTATTCATCTGAGACCAAGGCCACTGTGGTGAACCTAC


0





AAAGCCTTACAAAGCAGG[A/G]CCAGAAGGGCACATAAATC


(SNP 36)





ACTTGACTAACATTTGGTCAAAATAGCTCTTGGGCTCTTTT





BICF2G6301620
 37
 X
73593955
0.049456
0.049456
ATAAAAATAAAAGAGCTATTAATAAGAACTCATAAAATCTAC


9





ATAAATATAGTAACAGGT[T/C]AATATTCCCAGCATATTTT


(SNP 37)





TACAAATCATCTATAAAGAGCATGAGAGCATATAGGGATTA





BICF2P1149405
 38
32
41212550
0.941321
0.058679
GCAACAACCTGGTTTGTGTGTGGGAAGCTAATGCCTCCCCAA


(SNP 38)





ATGCAGCAAACTCTCCTC[T/C]TGATTTTAGAAAAGCAGTT








TAGTTACAGGCAAATGCATACATGCATGATAAATACTACTC





BICF2G6301617
 39
 X
73672050
0.940828
0.059172
GATTTTATAAAACATGATGACCTTGGCATTTATATAGTAGAT


3





ATTACTACTCTGAAATTC[C/G]AGGAAGTATGATCATAAAC


(SNP 39)





TCACACTTAATCTGGTAGTAAGTATGGACAATGTATCAAAGG





BICF2P401962
 40
 8
 4495597
0.935897
0.064103
CTTGGTTGAGTTAAAACATTTGCCCATGCAATTTAATGCATG


(SNP 40)





TCCCTGTGGGGTTGGAAC[T/C]GACGTACACCCGAGCCAAC








AGCCTTTCATGGCAGACGCCATCAGGCAGGTGACCCCCACC





BICF2P991264
 41
 8
 3165755
0.071992
0.071992
CCTTCCACACGCTCAGGTTGGCACGGAGGGGGTGTCCTTGCC


(SNP 41)





TGAGGGGTCCTGGCACAG[T/C]CATCAGGGCACACAGCTGA








TAACCCAAGGGAGCAGTAGGCAAGACCTCATGGGCGCCGGG





BICF2S2323084
 42
 X
58531292
0.079389
0.079389
ATTCTCTTTGCTGTCTCCTGTATACAGAGATAAAAGCAAGAG


7





TTTTCCCCTTCAGGTTTC[T/C]GAAACCCAGCTTCCTTTAG


SNP 42)





ATTTTAAGGGGTATTCTGTGTACCCATTTCCCACCTTCTGC





BICF2P1252842
 43
 8
 4618608
0.919132
0.080868
GCGGGTTGGGACCCCCCCTTCTGCTGCTCCCACTTCAGAGTT


(SNP 43)





GTGGCGTCACTAAGATGA[C/G]ACCTCATGTCGGGAACCTG








AGAGTCCCTCGGGAGTTGTGcagggactgtagccgacctat





BICF2G6301719
 44
 X
71984983
0.913947
0.086053
ACATATGCACAGTGAATCGTGGATTGTTGTGTTTGATTTCTT


8





ACATGATACAATAAAAGG[A/G]AAGTAGTTGAAGCAAAACT


(SNP 44)





TTAGTTTAAAGGAAACAATTTCTCTATCATAATGTTCAGTG





BICF2P1364202
 45
 8
 3175135
0.910256
0.089744
CCCACAGACCCCAGGTGCTGACCACAGCAGCCACTTGGGCCC


(SNP 45)





CCAATGCAGGAGACACCT[T/C]GGGAATGAAGGGGACAAGG








CCAGCTCAGGCACATCGTCAGTGCACCTGATGGGAAGGCCG





BICF2P963708
 46
 8
 5472668
0.095945
0.095945
ATCTGATCCTAGCCAATGGAAAGCAATTTGAGATAGGAATCA


(SNP 46)





TATCTTGTTTTGGTTTAT[A/G]TGCTTTCTTTGGAGTTTTG








CACATCATAGATAACTGTAAATTTGTAGAATAAATGTTTGA





BICF2S2293948
 47
 8
 7696228
0.098619
0.098619
GTCAATGCCATTAACCTGGCGAAGCTGCTCGAGCATCCACTG


1





CGATCTCCGCACGAACGA[T/C]GTGGAGCCTTCAAACTGTT


(SNP 47)





TGACCTTCGTGATGGATGCTTGTGTGGGTTTCTTGTTTGTC





BICF2P1028186
 48
32
40758922
0.107495
0.107495
ACTGGTTAATAAGACTTCACAGATTTTATCCATCATGTTGAT


(SNP 48)





TATCTGTATATGTATTTT[T/C]TACCACTTAGGATAAAGTT








CTGTTATCTGTAATTGATTCCAACCAGCATGTTTGCTCCAA





BICF2P19238
 49
32
40849057
0.897012
0.107988
CTTCTTCTTTCCCATTGGATTCTTTCATCAATCGTAGGTAGT


(SNP 49)





TCTTAATGAAGATCTGTG[A/G]TAAAGCCATTCATCTATTC








ATTCAACAAATGGCATCACAGAAAAGAAAAATAACCTTTAT





BICF2P247312
 50
 8
 7825200
0.112426
0.112426
GGGACACATTTCTGGACAGACCTCTGATCACACTCACAGGAC


(SNP 50)





AGCAAGAGGAAGCTCTGG[A/G]TACAAGTACAGGGAAAAAA








GAAAGAAATGGTCACAGGGAAGCTGCCGCAGGAAAAAGGTA





BICF2S2301711
 51
 8
 7615543
0.881164
0.118836
GGGCAGATCCTCAGTGAGTATTGGCTCATGTTCTCCGAGGGA


8





AGTAGAGTCCCAGAAGAA[A/G]GATGCTAAGGTGCCAAGAT


(SNP 51)





TCCTGAGCCTGTGTGTGGTACAGTCACAGCAGTACTCCTGA





BICF2P132419
 52
32
35699747
0.874506
0.125494
TCATCTCCATTTGTAATAGAAACCACATATATAGAGAGATTG


(SNP 52)





GATTATTAACCACTAAAA[T/C]GTAGCCACTCAAGGGGAGG








GGGGGAATGCATTTGGTTTATTTCCCATGTCAAAACAGAAT





BICF2S2311591
 53
32
40712955
0.873393
0.126607
AACACTGCTAATAAATATTTATAATGGTTTGAGGAAAATATC


1





AGGTGTGAGATGTCTTCA[T/C]ATCATATAATATATCATAA


(SNP 53)





TATCCTCTAAAAAAGCTCTAAGCATAGGTCTATGGAACTCA





BICF2G6305317
 54
 X
43502595
0.127219
0.127219
AAGCAATCCAGGAGTCTTTCTCCGGGTAGCAGGCTCGCTTTA


73





CAGGTTAAGGCTGGATGA[A/G]AAGGAAGAACCTGAGCTTC


(SNP 54)





AAATTATCATCTGAGTAGAGCTGATACCCATGGTTACATTA





BICF2G6305878
 55
32
38771348
0.127838
0.127838
GATTTTATTCTTTACTTTGATTTTTTTTAAGTTTTACTATGA


26





TATTCAATATGATTGTGG[T/C]TCATGAGATTCCTCTTTTT


(SNP 55)





AGCTGTATCATTAACTACAGAGCGTTCTCAAATATTTTTCT





BICF2P1007047
 56
 8
 4812890
0.87092
0.12908
GTGGCCGGAGGGGGTGGGCCCTACTGTGGCCCAGCTTCACGT


(SNP 56)





CCCACTGGCCAAACATCA[A/G]GATGCAGACACCCAGGTCC








CTTGTGCTGCCTGCTGAGGCTAGGAGCAGCGACTGGAAATG





BICF2G6305318
 57
 X
43317321
0.869329
0.130671
GATGGGAGACCTCATACACATGCAAAGATCACTATTAAAGAC


04





TCTCGAGCAAAGATCGAA[T/C]GGACTGTGGCAAGCTGCCG


(SNP 57)





CGCATGCCAATCAACAAATGCCTCCGACCATGGATCTAACC





BICF2S2363287
 58
 8
 5056863
0.866371
0.133629
CAACAAGGTTTTTAAGGTTCTTTTCACTACCTTCTTCTTTTT


6





GTACTTGCTTAGGACACC[T/C]GTATGTCTTCACAATATCA


(SNP 58)





CCTGAAAGTCCTTTAGGAGATATACTCAAAAAATAAATAAA





BICF2G6301558
 59
 X
75321307
0.865385
0.134615
caacctgagctgaaggcagacactcaactgttgagctaccca


7





ggtgtaccAAACACATCT[A/G]CTCTTAACCAAGCTTATTC


(SNP 59)





TTTGCTATATTTGGCAAATTGTGGCATGTCTACAGTACTCA





BICF2P482693
 60
 X
43587959
0.804897
0.135108
ATTCCCCATGTTTGAGGAAATCACAGGAGCCACTAGGAAATC


(SNP 60)





AACCATTTCCCAACCAAC[T/C]TGATGATTTCCTGATCCAA








AGGTTCTCCCAGGACAAATATGAGGTAGCCTTTCACACTCT





BICF2P940430
 61
32
40921126
0.136364
0.136364
CAGTCTTGTAGGAGAGTAGATTGACTCACAGAACTGGCAAGA


(SNP 61)





TTGGGAATCTGAGCATTG[T/C]CACTTGAGTCTTAAAACGT








TTACGATTTTATTTCTAGTATTTCAATAAGAAACACATTCT





BICF2P786384
 62
32
36389913
0.136723
0.136723
GAATACATTGCCAGAATAATTTCAAGTTCTCAAATCTCAACT


(SNP 62)





AATAAGATTTTCGTTAAA[T/G]AAGGCATTCAATCATCACT








TACTGACAACCCACAAAATTAGGCACTGATGAAAAATTAGC





BICF2P1340243
 63
32
41050914
0.150394
0.150394
AAGTTAAGATATTCAAGAAAGAGAAGAGAGTGACTGAGCTAA


(SNP 63)





AAAGAAAATCAGATCTCT[T/C]CCAGGCTTTAAAATAATCT








CCACAATACTGGGCAATCCATGTAGTCTCCCCAGTTCCATT





BICF2S2362644
 64
32
36617978
0.153846
0.153846
CTCAAAAGGAAAAGCCTGTGGAAAGGCAAAGAGGTATGTGAA


5





AGAGGTAAGTTCAAAATG[C/G]TGACATGACCAGTGTACAT


(SNP 64)





AGATTACAGGGTACTTGGAGGAGCAGTGTAGAAAGGAGTCCA





BICF2P161586
 65
32
37795702
0.156312
0.156312
TTCTATGAAATAGCTACCATTCTGGTTGGTATCTTCTGTTGA


(SNP 65)





TTTAGATGATGAAGGAAG[T/C]ATAAGAAGTAAGGCTTATG








AGTTTATAAAGCTTTAGTTAAAGCTTTGATTGTGACAAAGC





BICF2P579617
 66
32
36631235
0.162389
0.162389
AGAGGAGAAAACACAGCTAAAAACTTTTTTACAGACTGGACA


(SNP 66)





AAGGTGCTTACACTTTTC[A/G]TATTgggcagaatgagggg








atgaaaacaccagtggtctttttgaagccacacaaattcag





BICF2G6301628
 67
 X
73386098
0.835968
0.164032
AGGATGAATATTTATTAACAGTAAATATACATTTTTATTGTT


0





CTATATACTCTAAAGACA[A/G]TTGTAGACAGTAAGATATA


(SNP 67)





TCAATTTTAGAAACAGAAATAATGTTAATTGTATAATATGG





BICF2P721687
 68
32
40771787
0.829389
0.170611
CAGGGATTCCTAAAGGGTGACATGGTATGGTCTAACACTTCC


(SNP 68)





TCACTGTCCTTTTCCCAG[A/C]TGATATAAGAGGAGGACCA








GAGAGACACATAAACTGTCTGAGTCTTTAGCATTGTGATAA





BICF2P504739
 69
32
37328946
0.827909
0.172091
ACACTAATGGGTAGAGAATACACGTCCATCAGTCATCAATGT


(SNP 69)





AATCTACTAACAGCCTCA[C/G]AGTCTGGCAGTTTTCAGTG








AAAAGAGGAGTCATCTCCATTTATTCGAtcaatcagttgac





BICF2S2333187
 70
32
39390236
0.825444
0.174556
TATTACCCTGCTCTCCAGCCACTCCTTTACCTTCCATTAGCC


4





CACACCTGCTCTACACAC[T/C]ATTGCTCATGGAAGCCTTG


(SNP 70)





CCACGTCCAGTCGCCACTCTGAAATGCCAGCATCCCTCCCA





BICF2P772765
 71
32
 3978300
0.816075
0.183925
TCTCAGATACTTGATAGCCAGCATTTCCCCCCATTTTCTTCC


(SNP 71)





AAGAGCACGAAAGCATAG[A/G]AATGATATTACATCTCGTA








TGGTGAATGTGACACAGCCGTCAGTTGCGTTAGCTCTGCTT





BICF2S2318354
 72
32
35849858
0.18787
0.18737
ACAGGAAGGAGAACTGAGCATCAAGAGAGTTCAGAACATGAT


(SNP 72)





CATTGGGTCAGTTTGTGG[C/G]TGCATTAACTTTTCCCCAA








AACAGAAAGCAACAGAGACTTCTGTAGGTCAGTCAACAGTG





BICF2G6305880
 73
32
38521693
0.810052
0.189948
TTACCATTACTATAACCCAAGTTATAGTATACTATAACCAAG


54





TCCTTAATTGACTTGATG[T/C]TTGTGCAGCTGATTTTAAA


(SNP 73)





TCTATTTAGAATAATAGTTTACTTGTGACAATTCATATTAA





BICF2S2331344
 74
 8
 6343006
0.809665
0.190335
TTGGTCGACTGACTGATTGGTTTTACTGTGGAGGAAAGAAAA


5





GGGAATTTTCCCAAAGAG[A/G]ACAGAGAGAAAACATGGAA


(SNP 74)





TTGAGCAAAGGGAGAATAGAGAGACAGGGCAGCCACTGAAG





BICF2P675334
 75
 8
 4477476
0.19428
0.19428
TGCCTTATCCTCCAGCTCCTCCCTCACCATCTTGGAAACTAG


(SNP 75)





CTCAAATGTCACTGGTAC[T/G]TGTCTTTCTTTTGATCTTT








CTGAAAGACAAACATGATCCCATCACCTCTGCCTTTAGAAC





BICF2G6301740
 76
 X
71722644
0.80441
0.195759
ACTCCTAAGTAAAAGTTAAATTAACAGATTTGCCATCAAGTA


9





CCTTGCCCATTTTTCCTA[T/C]AGATCGACTTTTTACTGGA


(SNP 76)





TGATCCCCTTGATAATAATCTTGATCTATGTTTTAATTCCA





BICF2P798346
 77
 8
 4651519
0.195759
0.195759
ctggtgggcttgtcaggggcaggatgttgtgtggtgagcaca


(SNP 77)





gaattaaaactaggaGCT[T/C]gaagcgcctggggggctca








gttggttgacggactgccttcatctcaggtcatgatccctg





BICF2P1150684
 78
 8
 7652070
0.802761
0.197239
CATACAGCGAAGAGATAAAAACACAGGATGCTGGGCTCACGA


(SNP 78)





CCATGACCGGAAAAGGAC[A/G]GCGAGGAAAAGCAAGTATG








AGCAGCCCAAAGTCCTTTTTCCAGCACTGGCCATAGGAGGA





BICF2P1348758
 79
32
36083895
0.801579
0.198421
CAGAGATGAGGAATCAGACTCCTCGTCCTCTGCTTCTCTACA


(SNP 79)





ATGGCTCATGTTCTCCTT[T/C]CCCCTCAGCTGTTGCATTA








ACAGAGGTCAACCCATTCTTCTAAATTTAAATCTCCCAGAA





BICF2G6301759
 80
 X
71555277
0.198617
0.198617
AATCAAACAAGTGCTAGAACATAGAACAAGTGGCTCATCTTT


9





TCCCCAAATGTCTGGATA[A/G]GAAAAAAAAAATCTAAACA


(SNP 80)





AATGCTAGATGTTAAGTATCTGAAATGATCAGCCCATGAAA





BICF2G6301609
 81
 X
73800072
0.200197
0.200197
TCCATACCAGTCCTTGTTGTCTACCCCGAACTTCACCTCTCT


0





AGGCACAGACAGCTCTAA[A/C]TTTCACTCATAGGTATCTT


(SNP 81)





ATGCTGACCTGGCCTGCCTCCtgttttgttttgttttgttt





BICF2S2352402
 82
 X
64785623
0.79931
0.20069
CAAAAAATTCCCTGAGCCCAGCATCAAGGTACCTGGTTTGGA


7





GTGGGTGGGTCCTCAGAA[A/C]GAATGGGTGTGGTGTACAT


(SNP 82)





TTAGCAAGTTATGTAGCATGTGTCTGTGTAGTCTCACCTCT





BICF2P591872
 83
 X
62989720
0.795252
0.204748
GGGCCCAGCAAGTGGCAGAACTGGGAAGACCCCCTCTTCTTC


(SNP 83)





CGCCTGGAGCAGTGGTGT[A/G]GCAGCACACCACAGGAGTC








TGAAAGGGTGGGGAGTCCAAACGGGAACATATACCTGAGAT





BICF2G6305877
 84
32
38968302
0.794379
0.205621
atataatataacttatttaaaatatttGAAGATATTTCTATA


12





GTTATGCTCTACCATTTG[T/C]TATTATAAGATTTCCAACA


(SNP 84)





GCTTACTTCTTGTATGAAATTAATTTACCAGCCCCTCACCT





BICF2G6305877
 85
32
38964413
0.792899
0.207101
CCCTATTCTATAAACATTCCCTCTCTGGCCATCCTGTCAAGT


22





GGGCCCTGACAGTGTGCC[C/G]CAGAAGCTCCCTAGCCTTT


(SNP 85)





GCCCATTCCAGCTATGGCTAGCCTGCCACCAGCCATACACA





BICF2G6301855
 86
 X
66396513
0.218164
0.218164
CACTGTGAGGTCTGAATGGAGACATTCATGATAGACTCCAGG


7





ATTTTCCCAGCTATTAAG[T/C]CATGGGCCATAAACTGGAA


(SNP 86)





CACTTGGAAACAGTCCATAGGTTCATATTAAAGAATATGTT





BICF2P652606
 87
32
37855796
0.776134
0.223866
GCAAAAGGAACATGAGTTCTGATCTTCTGTAAAGGAGGCTAA


(SNP 87)





TTTACTAATGGTCATAAC[T/C]GTGGcctgagggtcaagtt








tctaattaaacgtgcatcttggggYggactagaatactttc





BICF2S2331279
 88
32
36791310
0.224852
0.224852
CAAGGSCCAGGTACCCTGAAGGAGTCCGCTTCACCCAGGCAT


9





GATGTGTTTGACAGTCTT[T/C]GTAATTGATACAGCCATTG


(SNP 88)





GCATCCTCTTGCGGCCAAYATCAGCTCCACTTCAACCTCGG





BICF2S2303948
 89
 8
 5896281
0.773669
0.226331
TGCAATGGGTTTTGAAATTAGAGGACATCACAGCAGAGTAGA


(SNP 89)





ATGGTTTGGAACAGGGGA[A/G]TATGATTAGGATTAATGAG








ATGAAAGAAAATTCTGGCTAGAGGGCTAGAAGAGCCATGGA





BICF2P506595
 90
 8
 4886813
0.228304
0.228304
CTCAGAACTAGATAGGCTAATAAGTGATAGGCCTTGTGTTTT


(SNP 90)





CCTAGAGTGTGCTTTAAA[A/G]GTTTCTTAAGCTAAAAAAT








TACATTCGTGAGAAAATTGAAATAAAAGGAAAACAGTCATG





BICF2S2313060
 91
 8
 5180802
0.228304
0.228304
GATACTTTGGGCTCTGGGTGGGAGCCAGCAGTGGTGGGGCAG


0





GGCAGGAGTCCAGCAAGG[T/C]GTCTGGGCATACATGTCTG


(SNP 91)





AGAGTAGGAAAACCACACCATTGCACCTTGCCTTTGACTTC





BICF2P1270451
 92
 8
 5580117
0.229783
0.229783
TCAAGGATCAGAAAAATAAAAGCAAAGAAAGAGGCAAAGAAA


(SNP 92)





GAAGAAATGAAATACCTA[A/G]TGGCAGAAGTAGGCAGAGA








AATAAAGGCTAAAAGAAAATGGCAGAGGATTGTTTGAAAGG





BICF2G6305882
 93
32
37876000
0.23001
0.23001
TATGTTATACTATTTTAGTATCTTAATAAATATGATTAGCCA


67





AAATAGTTTTATCATCCT[C/G]AAAAGTGCAGCATATATTA


(SNP 93)





TTTTCTATTAAATTCAGAATAGGTATAAACTAGAAAGCATT





BICF2S2312207
 94
 8
 4965974
0.76999
0.23001
ACAGCAGTTCTGAGGATGGACTCGCAGAGGCTCCTGACAAGC


4





AGAATGACCAGGCCGAGC[A/G]GAAAGGTCAGTGCTGCCAG


(SNP 94)





TCTAGCCAGAAGTGGGGGAGAGAGGATGTAGGAGCAGTACT





BICF2P555643
 95
32
40258722
0.230769
0.230769
ACTGTACTCAAAAAAGTTCTGTTTGCCTAAATGGGATCAGCC


(SNP 95)





TCTAATGGATGCCAGTGA[T/C]GGGAGGCTGTTCATCATCC








CTTCGGGATAATTCAGAGCCTAGGCAGAGGCCCAGCGTTCA





BICF2S2325999
 96
 8
 4990277
0.231732
0.231732
TACAGGCCCCAGGAAGGAGCCACCAGATGCCCAGGACTGGGC


9





CCAGGAATGATGGAGGCT[A/G]TACAGCTGGCTGCCTGCAC


(SNP 96)





TGGCTGCCGCCCCTGTCATCCAGTGTCACAGAGCAGCACCT





BICF2G6301652
 97
 X
72989415
0.251482
0.251482
AGACATTGCCAAGAAGTATCCACAATGAACAGTTTGAAGGGG


5





ATCCAGAAAAGCACAGGG[T/C]CTACTTCCGCTGGATGAGC


(SNP 97)





AGCAGTGAGAACCACAGTCAGGTAGGTCTTAAAGCAAAGTT





BICF2G6301955
 98
 X
60108249
0.737179
0.262821
GCTTTGAAAACCAACAGGAAATACATCCAGGAAAGCTATACA


2





ACTGTGGTGAAAGGAAAG[A/G]AAAATCTGCTCTTAAAAGG


(SNP 98)





TTGTGTGCAGACTCACTTGCCCCAGAAACCAGTGCGAAAAC





BICF2G6301788
 99
 X
70145192
0.271019
0.271019
GAGATGTGTAAAATTTAATAGAAATGAAACTTGCCAAAACAG


4





ACCTCTGTACTCGTCAGC[A/G]TTCTAAGTCCATCTTTCTG


(SNP 99)





TAGCATGTAAGTAGAATAATGTTCTATTAATTTCCTCTATG





BICF2G6305875
100
32
39023585
0.706931
0.293069
GTTCTTTCTATTCTATCACACATACCACCCCCCTGCCCACAG


98





TACCCCTTTCTGCCATGT[T/C]TCAGACTCCTACACAAGAG


(SNP 100)





GTTCTCTCTCCTGGCTTCCAGTTAGACAGGCAGGTAAAGCT





BICF2P285901
101
 8
 6743491
0.70069
0.29931
TAAAAAAATACAACAGTAGCATTAGAAGACATGCTAAGCGGC


(SNP 101)





TGTATTAGAGAAGGTTAG[T/C]GCTGGCCTGAAGTTTAGAA








ACCTTCCCTTCTCTTTTTTTTTTTCCTTCCCTTCTCTTTAA





BICF2P811511
102
32
36167454
0.30583
0.30583
TCAAGAGTACTAGAGCATCTATAATCAATGGTAAATTGGGGA


(SNP 102)





ACTAGTGAAACAAGTTTA[T/C]AGGACAAATAACATAAATA








AGGATTTTTTTTTAAATTTGGAAAATTGTGGAATAATGATA





BICF2P1146265
103
 X
63433179
0.693725
0.306275
AGAATTCAATTTTGGGGAGCCAGGAAACCAGATTAGTTTTCC


(SNP 103)





AAAGGGAAGTGCCATTTG[T/C]ATCTATCCCGGTGGGGCTG








CCAAGAATTCCCTGGGGTGGGAGACGGCGCTTCTGTGGATT





BICF2P243607
104
 X
57821508
0.690523
0.309477
CACCAGAGAGCCCCGCAAGATCATACTGCACAAGGGCTCCAC


(SNP 104)





TGGCCTGGGCTTCAACAT[T/C]GTAGGAGGAGAGGATGGAG








AAGGCATTTTTGTTTCCTTCATCCTGGCAGGAGGCCCAGCT





BICF2P382932 
105
 X
64010327
0.690335
0.309665
TGGTGATGATTTATCCCCCATGTTCAAGATTTATCCTCCCTG


(SNP 105)





TCTCAAGAAATCATGTCA[T/C]TACAGGCATCCTTAAAGTC








ACAAGACTGGGAAGTAAATACTGATGAGGTCCAAGACCTGG





BICF2P1061734
106
 X
57654632
0.69003
0.30997
AGCATAGTGTACCCACATATAAGGTCACATCTGAGGCCAGGG


(SNP 106)





AGTCGGGGTCTTGAAGAT[T/G]ATGACTGATCATGTGCTTG








AGGATGATGATGATCATGTGCTTTTCCTGGCTGTGCAGTTG





BICF2S2293723
107
 X
57492668
0.310158
0.310158
gtgtgtgtgtgtgtgtgtgtgtgtTTAATTCTTTGTGAGAAG


5





CCCCTCATTTTGACCTAA[A/G]TTTGGTAGAGGCCCCAGGG


(SNP 107)





GATCTGAGAGGAGAACAAAAGGATAAACCATTTGCTGTTCA





BICF2S2293748
108
 X
73723672
0.687068
0.312932
CCAACTTTCACTAGCATCACAGCCCCTATCAATCTCTGTTCT


9





TTTTTCTGTCAGTACCAT[A/G]TTTGCTCCTACTACATCYA


(SNP 108)





ATCTGTGAGCTCACAGGATGAGGACCAACAGCTGCCCTGAG





BICF2P903726
109
32
40883681
0.329389
0.329389
TGTCTTACCTCTCTCTATTCCCTTGTCCATAGTAGTATTAAA


(SNP 109)





TATATCTTCCTGAACACA[A/G]ATCTGATCCAGTCTCTTTT








TGTAATTAAAAGCCTTTGCTAGCTTTGGTGATCACCTCCAG





BICF2P1324008
110
32
40043909
0.664179
0.335821
GACCTGACAGATTATGTAGACTTTGTTTTCAAAGGGAGCACC


(SNP 110)





TGCTGGATATACAACATG[A/G]CACTAAATTGTGCTCCACA








TCCTTGGCAGAGGTGGGGGGCGGGGCACAAAGGAAGAAACC





BICF2P320425
111
 8
 7105593
0.336283
0.336283
CAGAGGAAAAGGAGAAGGTCCCACTTAGGGGACTGGAGAGGA


(SNP 111)





GTGGGGGAACATCACCAG[A/C]GCCTTCCTGAGCCAGGCCC








CCTGTGGGGAGAAGCTCTCCCCAGGACTGGGTGCCTTTGAA





BICF282321071
112
 8
 6397309
0.634615
0.365385
tcctccctctccccatccccattctcatgcaagtgtgctctc


3





tctctAAAACACCCCCCC[A/C]CACACACACACACAGACAC


(SNP 112)





AACCAAAtttgggtctcaatgtcttgaccaaggaaaaggca





BICF2G6301842
113
 X
66756995
0.367793
0.367793
gagaagaaggaggagaaagaggaaaagTATATTTGATGGAAT


4





GAAAAACAAGAGTTCAAT[T/C]TCACTCTGGTCTGGGGTGA


(SNP 113)





CCACTATTAGTCCTTCAACATCTTCCTTGAAGGAATTTTAA





BICF2G6301589
114
 X
74179959
0.631164
0.368836
CTGGAATTCTGTCAGATCAACATTCAGAGCTCCATCAAATCT


7





GAGGGAAGCAGTGATAGA[A/G]GATACAATTTGACCTTTCA


(SNP 114)





GTCTATTCAGGTTCATGTAGGTTAGGCATTCAATATCAAAG





BICF2P305287
115
 8
 3258209
0.371175
0.371175
CCACATGTGGTTACACCACTGTGTTATCCTTCCACCTGTCCC


(SNP 115)





ATCAACCCACCCGCACAT[A/G]TCACAGTGCCTCTGTCCTC








AAAGAACACTGTATCCAACACCTCCACATCCTCTCAGCATG





BICF2G6301666
116
 X
72647220
0.615878
0.384122
ATTCCTATGGTGGGCGCTGCACATTTCCTCCCAGGGGAAGGG


2





CAAGGGTCCTGCATTTCT[A/G]TGCTTTCCAGGGCCTCCGC


(SNP 116)





ACCAAGAGCAATTGCTAGGTCACGCATGCCCCTGCACTTCC





BICF2G6301785
117
 X
70302610
0.606541
0.393459
CATGTCATCACTAACTAATTTATTAACAAGAGTTTTATTCTT


4





TGAAAAACAAAATCACTC[A/G]CATTACTCAGTTGCTTATT


(SNP 117)





CCTTGATTCATATACAAATGACTGATAACATGAGATAAAAA





BICF2P170917
118
32
38039478
0.600592
0.399408
GATGATTTAGTTGTTTGAATGATCTGGCATATAAATCTTCCA


(SNP 118)





AATCTGTGTCCATTGGAT[T/C]GCTTACAGTTTAATCTTTT








TATTTCTTCCCAGAATCACATTTTTTCATTATTTATCTTTG





BICF2G6305882
119
32
38333881
0.425201
0.425201
AGTTAAATTCTGTGAATAACTAGAATCCGTTATACTTTTTCT


07





GAAATGAAGTCTGTAGGC[A/T]TTTCAACAGCAAAAGGAAT


(SNP 119)





TCTGWTTTTYAAAACTATACATAATGCTTCTTAAAAGCCCT





BICF2P702899
120
32
39207136
0.428854
0.428854
AATGCCAACTTTAAAAACGCATTCAAGGTTTTCCTCTGTAAA


(SNP 120)





TGCATTCCTCATTTTGGA[T/C]GTGATGTAAAATCTTATTC








AGTGTTTTGTTTTTTTTTCCCCCCACAGGTCTCAACAATTA





BICF2P1388432
121
 8
 7178740
0.446203
0.446203
GGTGGGACCGGCCATCAGCAGGCGGGCCAGCGCCCCACAGAT


(SNP 121)





GTTGTCACGGACCCGATC[A/G]TGGCGCTCCCGTGCCAGGA








GGGGCAACAGAAGCCCCAGCAGCTTGGGGAAGTATCTGGTT





BICF2P588571
122
32
37214320
0.454635
0.454635
AGGGGACTTGTGCTAATCACTGGGCAAATTTTATGAACTTCT


(SNP 122)





GAATTTTAAAGCAAAAGA[A/G]AAGGTGAAAGAATGGAAAG








AAGGTGTGAGTGTTTGAGGAAAACTTCTTCTTTGGGGTTGA





BICF2S2291251
123
 8
 6934693
0.544872
0.455128
TACACAAGCAAGGCAGTATGCCCTGTCTCCTTCCCTTGGGCC


8





ACCTGCACTTAGACATGG[T/C]AGGTTCCAGTGATGTGTCT


(SNP 123)





AGTCTCTAGCAAGCAGGGCTTGCTTCTGCTCTATCCATCCA





BICF2P223099
124
 8
 7427438
0.53002
0.469398
CTGTCCTTGGTCTGGACCTGCTGTGAAGACCAAGTGCTTCCT


(SNP 124)





GAGATCTCTCTGAGTCTA[A/G]TTTCCAGAGCAGTGAGTGA








GAAATGAAATGAGCCGAGGATTGCCCTCCCTCCTATGGACT





BICF2P568891
125
 8
 7938712
0.475321
0.475321
TAAGCCATCAGCATGGGCTCCTAGGGGTCTGTTCAACTCCCT


(SNP 125)





TGTGGTGTCTTACTGCTC[A/G]AGCAAAGGAACAGTCTGGT








ACAGTGGGAGCAAGAGCTGAGGTTGGAGAGTGGGGACACAG





BICF2G6301950
126
 X
60714796
0.521308
0.478692
GAGGAGGTGGAAGTGATTAAGTTTAAAATTTCTGGGGTGGTT


7





TCTGGCGACATGAAGCTG[A/C]GAGCTAGAATGCCTTTCAA


(SNP 126)





TCTCATAATTTCTTTAATTTGGTGATTATACCAGAGCCACA





BICF2P814468
127
32
37551101
0.517787
0.482213
CCTGACAAACACTACCTCTGCTCTTCAAAAGCAATAAGCATT


(SNP 127)





TATTCTGTGACACATTTA[A/G]ATACAAAGTCAATTACAAT








AGAGTATAAGTACAATACTAGGGAAAGTACAAAGTCATAYG





BICF2P948321
128
32
37526448
0.511834
0.488166
GCATGATGAAATCAGAAAAAGTATGTAAGTTTCTAGAAGAAG


(SNP 128)





CTAGATATATGGTAACTT[A/T]GGTCAAATAGAACCATGTA








GTGAAAAGAATATGAGTTTTCAAGTTCAATAAAAAACAAAA





BICF2P807378
129
32
37648000
0.510848
0.489152
ATGCATAAGTTTCCAAAAGAGTTCAGGATTCCAAAATAAAAG


(SNP 129)





CTTCACTAAAAGATTCAT[A/C]GCAAAAGAGTAATGAACAA








TTAAAGTCATAGGATATCTAAAATGAAAAACTGTTAGACTG





BICF2P175415
130
 8
 6494289
0.489645
0.489645
AGATGGCTTAGTTGTTTCTCTTTCCTCCTGAAGTCCACAGCT


(SNP 130)





TAGTTACTTGGACTCTCC[A/G]AAATaggatcgttggacat








ttgaggaaagctctagcatgaaagccatagactaaaaaaca









Example 3

Identification of Further SNPs Associated with Susceptibility to Liver Copper Accumulation and Protective SNPs


This Example describes the identification of further SNPs associated with susceptibility to liver copper accumulation and also some protective SNPs in the ATP7A gene. This work is also described in WO 2010/038032 A1 and WO 2010/116137 A1.


The three genes identified in Example 2 were investigated to identify further SNPs associated with susceptibility to liver copper accumulation. Thirty-three amplicons covering every exon of the three identified genes were chosen. These were amplified in 72 samples of genomic DNA from dogs of the Labrador Retriever breed. The samples were taken from dogs with either high copper (liver levels of copper above 600 mg/kg) or normal copper liver levels (below 400 mg/kg). The amplified product was sequenced in both directions by the Sanger method. The software ‘Seqman 4.0’ supplied by DNASTAR was used to assemble the sequence in each amplicon. The assembly was then examined to find single base variations (SNPs). These variations were then genotyped by examining the base-intensity at the SNP in the sequence from both directions. If the genotypes of a SNP from the two directions disagreed in more than 10 samples the SNP was classed as an artefact and ignored. The identified susceptibility SNPs are set out in Table 6.


Discovery of a Protective SNP in the Coding Region of ATP7A


A protective SNP was discovered (ATP7A Reg3 F 6; ChrX_63338063). This is provided in Table 7 and the sequence surrounding the SNP is provided in Table 8. This SNP is in the coding region of the ATP7A gene (an X chromosome-linked gene) and results in a change in the coding sequence. A study of average liver copper levels by gender and ATP7A genotype was conducted (Table 9). FIG. 1 illustrates the data from Table 9 graphically. FIG. 2 illustrates the same data as copper-histological scores. The p-value (0.000396) was determined from a Kruskal-Wallis test on the histological score with gender-genotype as the groups. It is clear from the data that the presence of the T allele is indicative of a dog being protected from high liver copper.


The results may explain the female bias of chronic hepatitis. Male dogs have only one copy of the X chromosome and so are hemizygous at the ATP7A locus. An X-linked recessive gene-effect is more likely to be seen in males than females because of the hemizygous state of the male X chromosome. The protective effect here is recessive so we see more cases in the female population.


The protective SNP results in a change of a Threonine to Isoleucine at amino acid 328 of ATP7A leading to a decrease in the number of potential hydrogen bonds from 3 to 0 and an increase in hydrophobicity, potentially altering the shape of the protein. The Threonine at this position is conserved across many mammals, including horse, human, chimpanzee and dolphin, indicating the importance of this amino acid in the function of the protein.


Discovery of a Further Protective, but Non-Coding SNP, in ATP7A


Sequencing the ATP7A gene revealed an intronic SNP that is almost in complete linkage disequilibrium with coding SNP ATP7a_Reg3 F 6 (ChrX_63338063). Like the coding SNP, the intronic SNP (ATP7a_Reg 16_F42) is significantly associated with protection from liver copper accumulation (Table 7). The significance of both was measured using a chi-squared with two degrees of freedom on the independence of genotype and disease status. Disease status was positive for >600 mg/kg dry liver weight copper quantification and >=2.5 histology score; negative for <400 mg/kg dry liver weight copper quantification and <2.5 histology score. The expected table was based upon a Bayesian estimate of genotype frequencies and disease frequency within the sample assuming independence of the two variables.


The calculated measures of linkage disequilibrium between the non-coding SNP and the coding SNP are: D′=0.93 and R-squared=0.86. The SNPs are therefore almost in complete disequilibrium.


The sequence surrounding ATP7a_Reg 16_F42 is shown in Table 8.


Example 4

Investigation into Breed and Geographic Diversity of the ATP7A Protective SNP


This Example describes an investigation into breed and geographic diversity of the ATP7A protective coding region SNP.


The ATP7A coding region SNP (ATP7A Reg3 F 6; ChrX_63338063) was genotyped in samples of DNA from dogs of other breeds in addition to Labrador Retriever to determine whether the SNP is present in other breeds. Table 10 shows the results, with the number of dogs of each genotype. The ‘T’ column refers to homozygote females (TT) and hemizygote males (T). The results demonstrate that the SNP is present in diverse dog breeds and therefore may be used as in indicator of protection from copper accumulation in a wide variety of different breeds, mixed bred dogs and mongrels. The T allele of the SNP has also been found in US and Japanese Labrador populations, demonstrating that geographical location of the dog is not a hindrance to the utility of the SNP.









TABLE 6







Sequence of further SNPs indicative of susceptibility to liver copper accumulation.













SEQ






SNP name
ID
Sequence
First
Second
Sequence


(SNP no.)
NO:
to the Left of the SNP
Allele
Allele
to Right of the SNP





ATP7a_Reg4_F_9
131
CTCTCATTTTGTGTATTGATTTGAG
A
C
CCTTAGTTCCCAAGTTCCTATCTTG




GACTCTGTCCTTTTTGTTCTCTTAG


TTTACCTCATGATCACATTTTAATA




GTGTTTTGTAACCATTTTTGTGGTT


TCAATGAAATTTGTAGGAAAACAGC




CTTGCCACAAAAGGCCTTATGAAGT


AGAAGGAAAGATATAAGGTTACTAT




CCTGCATATGAGTGATGTGCAGGAC


TCTCTATGGACCTTGGTTG




AACTTTGACTTTCTGACAGCCAGTT







TTTGTGTTTTGTT








UBL5_Reg1F_16
132
TTGCAGATTATATGATAAATATAGT
T
C
ACTTAACTAGGTAGGCCACAGAGTA


(SNP 132)

TGTAGCTTCAAAAATGACTATAACG


TGATAGTATGCAAGTTATTAAAATC




AACAGAAAAAAATTAACTTATCAAA


TGTTAGCAAGGCATAACACATATAT




AACTTTTCAAATTTCCCCATA


TTCTACTTAATGAGGTTTCTATAAT







CAAGGCTTGTCAAGTCCATTATGTT







C





golga5_Reg1_24
133
TCAGACTGAATCTAAAGCCACATAT
C
T
TTAGCTGGCACCGCAAATGTAAAAG


(SNP 133)

ATTTCCTCAGCAGCTGATAACATTA


TAGGCTCTAGGACGCCAGTGGAGGC




GAAATCAGAAAGCCACTAT


TTCCCATCCTATTGAAAATGCATCT







GTTCCTAGGCCA





golga5_26
134
TCTTGTGCTTGTTCTTTATCACCAT
G
A
ATTTCATCAAAAGGAAATATTTTGA


(SNP 134)

TCATTCAGTACATCCAAATTTTGAA


GAATTTAAGTGATTTTTTTATGATA




ATCCTTAGAGCTCTATAGCCTCTAT


TTTTAGCTATAGCAGTCACCTTGAG




GTAGGAGAATGA


CCAAAAGACATTCTAC





golga5_27
135
AAAAATATACTCTCTTTCTTACAGA
T
C
ACTGACCACAACCCAACACCTACTC


(SNP 135)

AACCTCTAATAATTCAGATTCTGGC


ATGATGGCAAATCMCMTRAACTGTY




CATGAAGTTCAGGAGGATTCTTCAA


TAWTYTCSGATTGGRRAWTMAAYKG




AGGAAAATGTATCATCAAGTGCTGC


TTRAGGAATGAA




CTC








golga5_28
136
TTTGCCCAAGAAAAATGAAGACCTA
T
G
TGTGTCAGGAACTGTTTTAGGTATT


(SNP 136)

TGACCATGGAAAGACTTGATACATA


GGGGATGAAGTAGGGAACACTGATT




ATGCTGGAGTACTAGTAGTCAGACC


TAGSTTCTGTTTATTCATGTCTCAC




CACCCAAGTCTTTTCACGTGTTCAT


TTTGTAGGAATTYCMHTAMATAGAA




TCAGTATAGATGCGGCACACGTTGG


RAADA




CTGAGTCCCTCCG








golga5_29
137
TCTCAGTACTCACAGGTACTTACAA
C
T
TGCCAAKTTGATTCTCTGGCCCATT


(SNP 137)

ATACAACACTAAGAGGTTTCACAAA


AATAGTTTGAAAATCTCTTCTGTAG




ACAGTACTCTTACATAGCACATGCT


GAGTATAGGAATTACCACAGAGTTT




GTACTCTCTGTTCCATTCTATTTTA


TGAGAAATTGATGAATGCCACGCTT




TTACTATTTTAAAATATGGATTGTG


TACCTGTGGGAACGTAGATTCTA




AT








golga5_30
138
CAGATGATGAGTCTGGAGCTGGTGA
T
A
GCACAGAAAGAAAGTGCTCATTAGT


(SNP 138)

TCTGGGCTGGAGATAATGAACCTGG


GTCAACTCTCAGCAACACTTGGTAT




GAGTCATCAGCTTTGGAGA-


TTGTAAACTTTAATTTTTGCTGACT




AAGGGTGTCTGGCCTCACTCTTGCT


TCATGGAGAAATAATGTTTTT





golga5_31
139
TAATGATACAGAAATGAATTTGGCA
G
T
GCATCGGCTCCTTCTGTGCTATTTT


(SNP 139)

GGAATGTATGGAAAAGTCCGAAAAG


CCGGTGGCTCCAGTCACAGCCCCAT




CTGCTAGTTCAATTGACCAGTTTAG


CAAGCAGAGCTGATACCTAAAGTGA




GTAAGCAAGTGCAGTACTGGTGAGG


CATTTACCCTACTTCCTCTCTCAAT




AATGG








atp7areg17_32
140
CATCACTTAAAATCATCTCAGCAAG
T
C
ATTTGCTTTGCTGGATTGAAAAAGT


(SNP 140)

TGTTGTTGAAGATGATTTTTTATAA


CTGGAAGTAATTAGAATGACTTCTC




AGTATATTCCAATCTTATTCTATAC


ATACTCCCACCTTGAATTCTCCTAA




TTCAGAAGCTTGGAATTCT


TATCAAAGGCTGGGAG





atp7areg17_33
141
ATATGGAGAAATGAGCTCTTATACA
G
A
CACACATCATTTGATTGAGCAATTC


(SNP 141)

CTTTCAGTGGACATGTAAACTGTTA


CACTTCCAGCCATATTCTGGACATA




TTGTCTTTTTGGAGAGCATTTGGCA


ATTTACAAGTATAAAAAGATGCATG




GGATCTATCAAAGT


TTT-GA

























TABLE 7









Amino

Base
Amino
Amino
Association


Amplicon
SNP
Exonic or
Coding
acid
Base in
change
Acid in
Acid
with


name
position
intronic
change
number
Genbank
to
Genbank
change to
phenotype







ATP7A
ATP7A
Exonic
Yes
328
C
T
T
I
0.001669996


Reg 3
30,374










ATP7A
ATP7A
Intronic
No
NA
C
T
NA
NA
0.001796187


Reg 16
89,705
















TABLE 8







Sequences or SNPs indicative of protection from liver copper accumulation.














SEQ


Wild
Alter-



SNP name
ID

Sequence
type
native
Sequence


(SNP no.)
NO:
Comment
to the Left of the SNP
Allele
Allele
to Right of the SNP





ATP7a_Reg3_
142
coding
AAATATTGAAAGTGCTTTATCTACA
C
T
TCCAGAAACCCTGAGAAAAGCAATA


F_6;

change,
CTCCAATATGTAAGCAGCATAGTAG


GAGGCCATATCACCAGGACAATACA


ChrX_63338063

pro-
TTTCTTTAGAGAATAGATCTGCCAT


GAGTTAGTATTGCTAGTGAAGTTGA


(SNP 142)

tective
AGTAAAGTACAATGCAAGCTTAGTC


GAGTACCTCAAACTCTCCCTCCAGC




T
A


TCACCTCTTCA





ATP7a_Reg16_
143
Intronic,
TTAAAATAACTACTTGCAGTGATTT
C
T
CTTCACCTTAAAAAGAAAAAGAAAG


F_42

pro-
CTTTCCCCCAGTATAAAATGTCAGT


TATTAGTTTTCAGTGTCATTTGCCT


(SNP 143)

tective
TTTGTCTCAATCCACCC


TAAAATG




T





















TABLE 9









Average Copper




Gender
Genotype
Level
Count





















Females
TT
323.3
3




CT
818.3
22




CC
1041.3
45



Males
T
437.5
13




C
905.8
34






















TABLE 10










T (Mutant






associated






with low copper



Breed
C
CT
levels)





















Labrador
31
13
28



Retriever






Miniature
3
2
8



Poodle






Golden
0
0
1



Retriever










Example 5

ATP7B Sequencing


This Example describes the sequencing of ATP7B (cDNA and gDNA) and the elucidation of mutations associated with copper accumulation.


ATP7B Sequencing—cDNA


Amplicon Choice and Primer Sequences


Primers were developed with Perl Primer and checked for specificity using NCBI Primer Blast. Primers needed to be designed that were specific for the active ATP7B, rather than the pseudogene of ATP7B (a 1106 bp fragment at genomic position (4:38596510-38597615). The primers (Table 11) were secured by developing primers that mismatch the pseudogene of ATP7B. According to the NCBI database the fragment of main focus was located in exon 2 of ATP7B. However, Ensemble states this fragment is both exon 2 (ENSCAFE00000046065) and exon 3 (ENSCAFE00000046071) with a 33 base pair intron in between.









TABLE 11







Primer information













Forward primer
Reverse primer





sequence
sequence
Size of


Gene
Exon
5′ → 3′
5′ → 3′
amplicon





ATP7B
NCBI: 2
GTTACCCTGCAGCTG
ATGGCGAGCATCAC
332 bp


chr 22
Ensembl:
AGAGT
AGTATC




2 & 3
Location:
Location:





790G > A 5024-
790G > A 5355-





790G > A 5043
790G > A 5336





(SEQ ID NO: 227)
(SEQ ID NO: 228)










Sequencing


Polymerase chain reaction (PCR) was performed using Pfx polymerase (Invitrogen, Carlsbad, USA). Results of the sequencing were analyzed using SeqMan (DNAstar8.1). Results were compared with NCBI (Build2.1) and Ensembl (CanFam 2.0 May 2005, database version 62.2r). The Labrador pedigrees were checked for Mendelian inconsistencies.


Results


Sequencing of Beagle cDNA prepared from liver RNA for primer optimization had revealed an interesting fragment and, due to the simultaneous gDNA sequencing of ATP7B, only this part of DNA was eventually sequenced in our Labrador subset. The sequencing results revealed two interesting coding, non-synonymous mutations: a SNP and a repeat. Furthermore we were able to resolve one of the discrepancies between the two genomic browsers NCBI and Ensembl. Because the sequence of exon 1 of ATP7B is not yet elucidated, the numbering of the exons starts with exon 2.


ATP7B Coding Repeat (Chr22_3135287)


There is a discrepancy between two online genome databases (NCBI and Ensembl) in predicting the exon structure of the ATP7B gene. According to NCBI, exon 2 is 1237 base pairs (bp) in length. However, Ensembl states that these 1237 bp are two exons, namely exon 2 (971 bp), intron 2-3 (33 bp) and exon 3 (233 bp). Our sequencing results show that exon two is indeed 1237 base pairs long and there is no intronic sequence.


Another remarkable discovery was that the 33 bp coding fragment is variable in length (FIG. 3). Ensemble shows four repeats, while NCBI shows heterozygosity (3 and 4 repeats). The Beagle we sequenced is also heterozygous but with two and three repeats. In our Labrador subset we found homozygous (3 repeats), heterozygous (3 and 4 repeats) and homozygous (4 repeats) dogs. The chromosomal location of the first C in the repeat is 22:3135287. The repeat is located between the third and fourth heavy metal associated domain of ATP7B (FIG. 4). Multi species alignment among eutherian mammals shows that this particular region is not well conserved. The dog is the only species in which a CGCCCC repeat at this position is found.


The sequence surrounding the repeat from NCBI is shown in Table 12.









TABLE 12







Sequence upstream and downstream of the CGCCCC repeat (SEQ ID NOs 236, 237, 238, and 239).










CGCCCC repeat (two,



500 bp upstream
three or four repeats)
500 bp downstream





tcagcacccaggaggcagtcatcacttaccagc
CGCCCCCGCCCC;
aagaaccccggcaccgggcaggtgcgatactg


cttatcttattcaaccccaggacctcagggacc
CGCCCCCGCCCCCGCCCC;
tgatgctcgccattgtgggcatgacctgtgca


atgtaaacgacatggggtttgaagctgtcatca
or
tcctgcgtccagtcgatcgaaggcctgatctc


agaacagagtggcacccgtaagcctgggaccca
CGCCCCCGCCCCCGCCCC
ccagagggaaggggtgcagcaaatatctgtct


ttgatattgggcggttacagaggaccaacccaa
CGCCCC
ctctggctgaagggaccgcagtggttctctat


agatgcctttgacttctgataaccagaatctca

gatccctctataattggcccggaagaactccg


ataactctgagaccttgggccatcaagggagcc

agctgccgtcgaggagatgggatttgagactt


atgtggttaccctgcagctgagagtcgacggaa

cagtcctctctggtatgtagtggcaccccggg


tgcactgtcagtcttgtgtcctgaacattgaag

tcttctcctctctccttgggccttacggcaga


agaatataggccaactccccggggttcagaatg

gtgcctgcagggtggcacaggggagccacccc


tgcaagtgtccttggagaacagaacggcccaag

agctgctcgcctgtcgggttggccaagtcccg


tacagtacgacccttcttgtgtcaccgcagggg

cagcgtttccctgtgtgttgaatgtgtccggg


ccctgcagagggccattgaagctctcccaccag

tgggagaaagagaactttctggtgtgtagatt


ggaactttaaagtttctcttcctgccgcagcag

ttgcctctcatggggctgggactacattgcta


caggaagtgagacaggtaacaggttttcggcat

aattctttgttgttgttattttttttaact


gtgc (SEQ ID NO: 239)










ATP7B 790G>A (Chr22_3135144)


Approximately 144 bp upstream of the repeat we found a non-synonymous mutation (ATP7B 790 G>A). This SNP is also located in exon 2 on chromosomal position 3135144. It is a G>A substitution and as a consequence the amino acid alanine is substituted by threonine. The SNP is located in the third heavy metal associated domain.


ATP7B Sequencing—Genomic


Resequencing (Sanger) of ATP7B was performed by Beckmann Coulter in 98 dogs from which complete phenotypic data was available. Exons and exon-intron boundaries were sequenced.


Results of the sequencing were analyzed using SeqMan (DNAstar8.1). Results were compared with NCBI (Build2.1) and Ensembl (CanFam 2.0 May 2005, database version 62.2r). The Labrador pedigrees were checked for Mendelian inconsistencies.


Results


Analysis of whole gDNA sequencing of ATP7B in 98 Labradors revealed 2 exonic non-synonymous mutations (including SNP ATP7B 790 G>A; Chr22_3135144) and 4 exonic synonymous mutations. Nine single base-pair substitutions in introns were detected. Further, 3 single base-pair indels and a 7 bp deletion were detected in intronic regions. The coding repeat of 6 base pairs (described above) was also found. Statistical analysis of relation with the phenotype was performed. Only the repeat and the 2 non-synonymous SNPs had a significant association with the phenotype in this group of 98 Labradors. These three mutations were studied in an extended set of dogs (see next section) and evidence for functional effects was searched for.


ATP7B 4145G>A


The ATP7B 4145G>A SNP is located at the end of ATP7B, approximately 154 bp upstream of the stop codon (exon 21, chromosomal position 3167534). It is a non-synonymous mutation in which a G>A substitution leads to the amino acid glutamine instead of arginine (FIG. 5).


Typing Mutations in Extended Set of Labradors and Effect Prediction


Two interesting SNPs (SNP790G>A and SNP4145G>A) and a repeat found in ATP7B were further analyzed in a larger subset of Labrador retrievers. For SNP790G>A, 267 Labradors and 1 Beagle (control) were typed and for SNP4145G>A a total of 242 Labradors were typed by SNaPshot. For the repeat, 216 dogs were typed by Genescan. The protocols used for typing the mutations are described in more detail below.


Genescan


Genescan was performed to type the DNA fragment length polymorphism in ATP7B using a 3-primer protocol. The Pfx polymerase was used for PCR amplification of the amplicon because Platinum Taq polymerase is not able to detect shot tandem GC-repeats. The same primers as used for sequencing were also used for the Genescan, except that there was a M13-tail added to the forward primer. Primer sequences are listed in Table 13.









TABLE 13







Primer sequences for Genescan








Primer
Sequence (5′ → 3′)





M13-tailed

GTTTTCCCAGTCACGACGTTACCCTGCAGCTGAGAGT



forward primer
(SEQ ID NO: 229)





Reverse primer
ATGGCGAGCATCACAGTATC



(SEQ ID NO: 228)





6-FAM-labeled

GTTTTCCCAGTCACGAC



M13 primer
(SEQ ID NO: 230)





The underlined sequence is the M13-tail added to the forward primer.






Genescan results were analyzed with the Applied Biosystems GeneMapper Software Version 4.0. Focus was on the length and the differences in length of the microsatellite and if the individuals were homozygous or heterozygous at this locus for the microsatellite. Peaks were compared with each other and with the size standard to determine reliability of the peak.


SNaPshot


SNaPshot was performed for a precise SNP analysis in an extended group of Labrador retrievers.


For 790G>A the (functional ATP7B specific) primers used for sequencing were also used for the PCR reaction of the SNaPshot protocol. PCR primers for SNP 4145G>A were developed with Perl Primer and checked with NCBI Primer Blast. These primers were specific for the functional ATP7B gene because an intronic sequence was also incorporated. In addition, for both SNPs a SNaPshot primer was designed. The primer sequences are provided in Table 14.









TABLE 14







Primer information








SNP 790G > A
SNP 4145G > A












Primer
Sequence (5′→3′)
Location
Primer
Sequence (5′→3′)
Location





PCR
GTTACCCTGCAGC
3135024-
PCR
CGTCTGGATGGGAA
3167222-


forward
TGAGAG
3135043
forward
GTTTCTC
3167242


primer
(SEQ ID NO 231)

primer
(SEQ ID NO: 233)






PCR
ATGGCGAGCATCA
3135355-
PCR
TTGTCGGACTTCAGG
3167600-


reverse
CAGTATC
3135336
reverse
GAGG
3167582


primer
(SEQ ID NO 228)

primer
(SEQ ID NO: 234)






SNaPshot
AGGGTCGTACTGT
3135164-
SNaPshot
CCGGCGGTGGGACT
3167514-


primer
ACTTGGG
3135145
primer
CCCCGC
3167533


(Rv)
(SEQ ID NO 232)

(Fw)
(SEQ ID NO 235)









The SNaPshot protocol was the same for both SNPs, except for the PCR step. The template of SNP 4145G>A was created using standard Platinum Taq polymerase. In contrast, the template of SNP 790G>A was created using the Pfx polymerase, which is able to amplify GC-rich stretches more accurately.


Results were analyzed with the Applied Biosystems GeneMapper Software Version 4.0. Focus was on the different colors, with each color representing another base, and on the heterozygosity or homozygosity of the individuals. Peaks were compared with each other and with the size standard to determine reliability of a peak.


Multi Species Alignment


To check the conservation of the regions of the mutations among other species, a multi-species alignment was performed using the Ensemble multispecies alignment tool Both the single bases are highly conserved over different species, whereas the coding repeat is not. The dog is the only species with a repeat at that position.


Prediction of Mutations Effect


Both SNPs were evaluated for possible predicted deleterious effects on protein function with several prediction programs:

    • Align-GVGD (http://agvgd.iarc.fr/index.php).
    • The tool combines the biophysical characteristics of amino acids and protein multiple sequence alignments to predict where missense substitutions in genes of interest fall in a spectrum from enriched deleterious to enriched neutral.
    • PolyPhen (http://genetics.bwh.harvard.edu/pph/index.html).
    • Prediction of the possible impact of an amino acid substitution on the structure and function of a human protein using straightforward physical and comparative considerations.
    • PhD-SNP (http://gper.biocomp.unibo.it/cgi/predictors/PhD-SNP.cgi).
    • The tool is used as a predictor of human deleterious Single Nucleotide Polymorphisms.
    • SNAP (http://rostlab.org/services/snap/).
    • This is a method for evaluating effects of single amino acid substitutions on protein function.


Because the prediction programs are predominantly based on human data input, not all the programs could predict the effect of canine amino acid substitutions. According to the used prediction programs, ATP7B 790 G>A is suspected to have the most deleterious effects on protein function.


LD Calculations


Two measures of LD (D′ with confidence interval and R-squared) were calculated using the program Haploview for the coding mutations in ATP7B and 672 SNPs in the first part of ATP7B. Results for the top three most associated SNPs from the GWAS are depicted in Table 15. High D′ and low R-squared indicate a difference in allele frequencies of any combination of mutations measured. LD structure in the region (first 15 Mb of Chr 22) is depicted in FIG. 6. High LD between the mutations and several SNPs in this region is present, resulting in a large area that is associated in the GWAS analysis.









TABLE 15







Measures of LD for 3 coding mutations in ATP7B and top


3 SNPs from GWAS analysis













933_938Dup







CGCCCC
4145G > A
BICF2G6303159
BICF2G6303160
BICF2S23122114



3135287
3167534
50 7548442
66 7767302
12463818




















790 G > A
D'
1.0
D′
1.0
D′
1.0
D′
1.0
D′
0.819


3135144
CLD′
0.42-1.0
CLD′
0.64-1.0
CLD′
0.15-0.99
CLD′
0.58-1.0
CLD′
0.35-0.95



R2
0.018
R2
0.085
R2
0.021
R2
0.044
R2
0.031


933_938Dup


D′
1.0
D′
1.0
D′
1.0
D′
1.0


CGCCCC


CLD′
0.32-1.0
CLD′
0.08-0.98
CLD′
0.89-1.0
CLD′
0.89-1.0 


3135287


R2
0.043
R2
0.01
R2
0.4
R2
0.376


4145G > A




D′
0.93
D′
0.35
D′
0.31


3167534




CLD′
0.79-0.98
CLD′
 0.21-0.48
CLD′
0.17-0.44







R2
0.213
R2
0.065
R2
0.31










Statistical Associations of the Coding Mutations with the Phenotype


The coding mutations in ATP7B were typed in an extended set of Labradors and a linear model was used to determine the magnitude and direction of effect of a mutation (beta) and the significance of association (p-value) for the single mutations and with all mutations in the same model. For 211 Labradors all three mutations in ATP7B and the mutation in ATP7A were typed. In this set, the number of risk alleles of each dog was determined and the effect of the number of risk alleles on liver copper based on RA staining was calculated.


Linear modeling with ra-scoring for copper as outcome variable was performed with age, sex and mutations as covariates for the ATP7B coding mutations. Both single allelic effects as well as effects of each mutation corrected for the other two were calculated and results are summarized in Table 16. Mutations were modeled in an additive way, so effect was estimated for every extra copy of the allele.


The 790 G/A (Chr22_3135144) mutation was found to be protective, whereas every extra copy of the repeat (Chr22_3135287) and every extra A in at position 4145 (Chr22_3167534) resulted in significantly higher RA scoring for liver copper.









TABLE 16







Linear modelling for RA phenotype and coding mutations in ATP7B










Single alleles in the model
All alleles in the model













Mutation
Beta
95% CI
p-value
Beta
95% CI
p-value
















790 G > A
−0.46
−0.75-0.17 
0.00216
−0.26
−0.56-0.05 
0.099


933_938Dup
0.42
0.02-0.81
0.0398
0.51
0.12-0.91
0.012


CGCCCC








4145G > A
0.48
0.26-0.70
3.53e−05
0.51
0.27-0.75
3.62e−05









To study the effect of all known coding mutations contributing to the disease phenotype, linear modeling was performed in 211 Labradors for which the three mutations in ATP7B were typed successfully as well as the previously discovered ATP7A coding mutation. The number of risk alleles for each individual dog was counted. The risk alleles were: C for the ATP7A coding mutation, G for ATP7B 790, G/A (Chr22_3135144), 3 repeats for the ATP7B repeat at chromosome location 22:3135287, and A for ATP7B 4145 G/A (Chr22_3167534). Outcome variable was liver copper level based on RA copper staining (levels 0-5) and number of risk alleles was modeled as covariate. Every extra risk allele resulted in a significant increase in RA staining score of 0.33 with a very significant p-value of 3.5 e-08. FIG. 7 shows the effect of the number of risk alleles on quantitative liver copper levels.


Example 6

SNP Genotyping and Model Generation


This Example describes genotyping of SNPs and model generation.


SNPs were identified by SOLID sequencing (using the SOLID 3 sequencing platform) of CACH-phenotyped DNA samples. In addition, SNPs from previous work and sequencing of the ATP7A, COMMD1, ATOX1 and ATP7B genes were included in the analysis.


The SNPs were genotyped by GeneSeek on all available phenotyped DNA samples. SNPs were analysed with a collection of chi-squared tests. A two degrees of freedom test was used with a null hypothesis of independence between phenotype and genotype. Phenotypes used were:

    • Histology score>=2.5 vs. histology score<2.5
    • Quantitative copper>600 vs. Quantitative copper<400
    • As well as the chi-squared tests a correlation co-efficient test was applied against quantitative copper and histology score. The test was performed in MATLAB using the corrcoef function producing a p-value and a correlation coefficient.


      Loci were then ranked by p-value to prioritise further investigation. Genomic regions beyond a significance of 0.001 were investigated for potential candidate genes as described in the section headed “Region gene analysis” in Example 1.


Genotypes were then inspected for the selected SNPs. Because the corrcoef function can sometimes provide false positives in ordinal data (like genotypes) with low membership of groups the SNPs were filtered for only those that contain ten or more samples in at least two groups that have a difference in the phenotype. The remaining SNPs were used in model generation.


The final data consists of 386 SNPs genotyped on 260 samples. Analysis identified many SNPs that are significantly associated with susceptibility to, or protection from, liver copper accumulation. This analysis is shown in Table 17. Further information on the SNPs, including the surrounding sequences, is provided in Table 18.


Examples of SNPs in linkage disequilibrium with the SNPs, and which are therefore also associated with susceptibility to, or protection from, liver copper accumulation are provided in Tables 19 and 20.









TABLE 17







Results of the analysis of the GeneSeek data. Mutations indicative of


“protection” from liver copper accumulation are in bold.




















corrcoef

corrcoef
corrcoef
corrcoef










pvalue -
corrcoef
pvalue - log
R - log
pvalue -
corrcoef
chisquared
chisquared






SNP name
cuquant
R - cuquant
cuquant
cuquant
cuhist
R - cuhist
pval - quantaff
pval - hist_aff
chr
Loc
Info
genes






















Chr22_3167534
0.00828
0.297627
0.007077
0.241694
6.00E−05
0.298521
1.66E−01
2.22E−03
chr22
3167534
Exonic coding
ATP7B-coding


Chr20_55461150
0.164589
−0.10583
0.014631
−0.18482
0.009595
−0.16689
3.46E−03
2.88E−01
chr20
55461150
Nearby
STXB2 bile acid gene)


ChrX_120879711
0.04194
−0.15439
0.003159
−0.22257
0.42838
−0.05136
3.91E−03
2.39E−01
chrX
1.21E+08
Nearby
MTMR1


Chr32_38904515
0.043678
−0.15139
0.049299
−0.14759
0.141384
−0.09501
4.95E−03
2.72E−01
chr32
38904515
Exonic coding
UBL5 ortholog - coding


Chr19_6078084
0.015583
0.193361
0.000449
0.277662
8.69E−06
0.298791
1.11E−02
3.94E−03
chr19
6078084
Nearby
microsomal glutathione














S-transferase 2 (GST)


Chr15_62625262
0.000339
−0.26857
0.000306
−0.27052
0.01002
−0.16628
1.13E−02
7.12E−02
chr15
62625262
Exonic noncoding
unknown


Chr14_39437543
0.007167
0.203766
0.00359
0.220272
0.007118
0.174397
2.33E−02
7.37E−02
chr14
39437543
Nearby
Interleukin-6 Precursor (IL-6)


Chr15_62625024
0.023044
−0.17375
0.002611
−0.22881
0.000993
−0.21255
3.14E−02
2.27E−02
chr15
62625024
Exonic coding
Unknown



ChrX_63338063


0.034843


−0.15568


0.040425


−0.15124


0.000895


−0.2084


3.85E−02


2.38E−02


chrX


63338063


Exonic
coding


ATP7A



Chr3_86838677
0.000256
0.276149
0.000973
0.25003
0.000456
0.226406
1.63E−01
4.69E−02
chr3
86838677
Nearby
KRT18 (Indian














childhood cirrhosis - keratin














18 ortholog)


Chr8_482743
0.004603
0.328072
0.005334
0.322881
0.287162
0.113417
1.96E−01
5.76E−01
chr8
4892743
intronic
GOLGA5


Chr24_4011833
0.030795
−0.15758
0.048763
−0.14394
0.005057
−0.17472
2.20E−01
8.27E−02
chr24
4011833
Nearby
FOXA2


Chr18_60812198
0.005568
−0.02432
0.021119
0.058831
0.562541
−0.0378
4.31E−01
5.25E−01
chr18
60812198
Potentially URT
ATOX1


Chr8_4880518
0.00302
0.224225
0.073156
0.136583
0.58772
0.035242
4.78E−01
4.03E−01
chr8
4880518
intronic
GOLGA5


Chr10_65209946
0.108151
0.120486
0.047767
0.14817
0.00069
0.215782
5.07E−01
2.77E−01
chr10
65209946
UTR
COMMD1


Chr22_3135144

0.019406


0.184089


0.026966


0.174352


0.00047


0.232303


5.21E−01


5.61E−01


chr22


3135144


Exonic
coding


ATP7B - coding

















TABLE 18







Sequences of the mutations in Table 17




















High



SNP
canfam2
canfam2


Rsq-
copper



(SEQ ID NO:)
chromosome
location
base1
base2
histology
allele
Sequence





Chr22_3167534
chr22
3167534
G
A
 0.298521
A
GAGAGGTACGAGGCCCAGGCGCAGGGCCGCATGAAGCCCCT


(SEQ ID NO: 144)






GACGGCGTCCCAGGTCAGCGTGCACATTGGCATGGATGACC









GGCGGTGGGACTCCCCGC[G/A]GGCCACGCCCTGGGACCA









GGTCAGCCGTGTCAGCCAGGTGTCTCTGTCCTCCCTGAAGT









CCGACAAGCTGTCCCGACACAGCGCCGCGGCCGACGACGGC





Chr20_55461150
chr20
55461150
A
G
-0.16689
A
CGGGGCTNGATCTCACGACCCTGACATAGTGACCTGAGCCA


(SEQ ID NO: 146)






AAACCAAGAGTTGGACGCTCAATNGACTGAGCCTCCCGGGA









GCCCCAAAGTCAAGAGAC[A/G]CTACAGATGCGTTGGGCA









CAATGACAGGGGAGGAAGCTGAGGTCTGNTGGNGGAGGTTC









TGCACCTCCCAGCAGGACCCNGCACACAGCAGGTGCCTGCT





ChrX_120879711
chrX
120879711
C
T
-0.05136
C
GGGGAGTCCGGCATGGCCCCCTGTCAGCCCTGTCCCCTCAG


(SEQ ID NO: 147)






GGTGTCTTGGCCGGGTTGCTCCCTGACAAGCTCTCCCTCCT









CTCTCTTCAGGTTCAGCC[C/T]GAATCTGACACCATGCCC









CTAGGGAAGAGCAGCGAGCTTTGGAAGCAGGGAGAAGACCT









ATAGGAGGCCGAGGGCCTGGGGATGCCCAGCTGTCTGGGGC





Chr32_38904515
chr32
38904515
C

-0.09501
C
AAGAAAAAGAAAAACCCAGCCATCAAGGGTGTGCATGTCTG


(SEQ ID NO: 156)






TGAAAGCTCCAGACAGGATGATCGAGGTTGTTTGCAACGAC









AGTCTAGAGAAGAAGGTG[C/-]GCGTTAAGTGCAACACTG









ATGACACCATCGGGGACCTTAAGAAGCTGATTGCAGCCCAG









ACTGGCACCTGTTGGAACAAGACCATCCTGAAGAAGTGGTA





Chr19_6078084
chr19
6078084
G
T
 0.298791
T
CCTTCAGAGAGAACCCAGGACAATTACTAAACTACCGTGCC


(SEQ ID NO: 148)






CTGGAAGATGTTTTGTGACTCCTCACTCCCTCTGCCTTGCT









TATTGGCCATTATTTTTT[G/T]ATCCCTCTCTCTTCTACC









ATTATTAATCAAACACAACAAACAAAACACTTCTAACAAGG









ATATTAGGTTTGTATACATTTTTTTTAAAAACAGCAACTTA





Chr15_62625262
chr15
62625262
A
G
-0.16628
A
ACTTCCTGATTGCTACTGTCTGGACACTAGGTTTTGCGATT


(SEQ ID NO: 149)






TGTTCTCCCCTTCCAGTGTTTCACAGTCTGGTGGAACTTCA









GGAAACATTTGACTCCGC[A/G]TTGCTGAGCAGCAGGTAT









TTATGTGTTGAGTCGTGGCCATCTGATTCGTACAGAATCGC









TTTTACTATCTCTTTATTGCTAGTCCAGTATATTCTTCCCT





Chr14_39437543
chr14
39437543
A
G
 0.174397
G
CAGGGAACATTTTCAAAGATGTAGAAAATCCCAAGACATGT


(SEQ ID NO: 150)






TAACATAGGGAATGCATGTAAAGATGCAATCAAAAGCCTTT









GAAATGACAACCACTTAT[A/G]TAAGACCTAGCAATGTGC









ACTTCCAAACATTAACTAAAAGTTCTATCTCCCCCCTCTGG









GTTCCTTAAACATTACACCTCTCTGCCTATCAAAGCACCTA





Chr15_62625024
chr15
62625024
A
G
-0.21255
A
TTCCTCATAGGAAATTTGGCCTTCTCTGATATTTTGGTTGT


(SEQ ID NO: 151)






GCTGTTTTGCTCACCTTTTACACTGACCTCTGTCCTGCTGG









ATCAGTGGATGTTTGGCA[A/G]AGTCATGTGTCACATTAT









GCCTTTTCTTCAATGTGTGTCAGTTCTGGTTTCAACTTTAA









TTCTAATATCAATTGCCATTGTCAGGTATCATATGATCAAG





ChrX_63338063
chrX
63338063
C
T
-0.2084
C
See Table 8


(SEQ ID NO: 142)












Chr3_86838677
chr3
86838677
A
C
 0.226406
C
ATCCAGAAGAAGTCTGCTAGGGGTAACTATCTTTTCGCTCT


(SEQ ID NO: 152)






CTGTTTATGCCAACATTTCACAAAAGCTTGTCTCCCGTGAC









TTAAATAGATACACCCAG[A/C]GTGTATGTTGGGGATTTT









TGCAAGTATCCTTAGGAGGCCCTACGTCGTAAGGCACAGTC









ATAAGACCTCGCGTCCCTATTCCCTCATCTGTAAAATGGTG





Chr8_4892743
chr8
4892743
C
T
 0.113417
T
GCCTAGCATTATTCCTGACATGTGTTAGGTCCTCAACAAAT


(SEQ ID NO: 157)






AGTAGCTAATATACTTTCTGGATTTCTTTCTTTTTGGCTAA









GTAGAAGAGCTGGTGCTG[C/T]CATCCTTATAGTCTGTAT









AGTAGGATTTCTTTTCTTTCCTTTTCTTTTTTAAAGATTTT









ACTTATTTACTCATGAGAGACACAGACTGAGAGAGAGAGGC





Chr24_4011833
chr24
4011833
G
A
-0.17472
G
CAAGGTCTGTGGATGTGCTTACTCCGTCCTCACCACAAACA


(SEQ ID NO: 153)






CCGATGTCTCGGACACACTCAGTGAGCCCAGGTTAGGAAGC









CAGGATTGCAGGGCCAAG[G/A]GTATAAGGAGGTGTCCTG









GGAGCCTCAAAAGAAAAATACAAAAGTATGAAGACTCAGAA









TAAATTCTTACAAATCTTGCTGTGTCTTCCCACAGATGGCA





_60812198
chr18
60812198
A
G
-0.0378
A
Gaaaggccgtttcctacctcggccccaagtagtgagggcct


(SEQ ID NO: 154)






Ggaccctgagcccatgatggaccaaagggagcaggtgggtg









aggccccagcccttggac[A/G]gaatatttcattagctaa









tgcaaatcatgagttcagggaatcctcacagccccctgaga









atacgcagagcactgtgttatgtctcccagggtccctttta





Chr8_4880518
chr8
4880518
T
A
 0.035242
A
AGAGAGAGGAGAAGCAGGCTCTATGCAGGAAGCCCGATGTG


(SEQ ID NO: 158)






GGACTCGATCCCAGGTCTCCAGGATCATGCCCTGAGCCAAA









GGCAAGACGCTCAACCAC[T/A]TAGCCACCCAGGCGTCCC









TTTTACCTTAGTTTTTGTCCTAAAGCTTCATATAAATGGAA









TCATGTAGTATGTATGTGTGTACACTCTCTTTTCTGACTTC





Chr10_65209946
chr10
65209946
A
T
 0.215782
T
AAAGTATCAGCACACTGATGCAGCCAGCCTAGCTGAAG


(SEQ ID NO: 155)






ATGGAGTTGTTGAAGCANAGGTGTTCATGATCCCTCCC









CAGTGACCTGCGATTTTTTTTTTN[A/T]AATCTTATT









CGCCCATTTTATTAAATCCNCAAATTCAAATCTGTTTG









TCTCACTTGCTGAGATTTCTTTTGTCTTTCTCTTTCAT









TCATTCTTACAGTTG





Chr22_3135144
chr22
3135144
G
A
0.232303
G
CGACGGAATGCACTGTCAGTCTTGTGTCCTGAACATTG


(SEQ ID NO: 145)






AAGAGAATATAGGCCAACTCCCCGGGGTTCAGAATGTG









CAAGTGTCCTTGGAGAACAGAACG[G/A]CCCAAGTAC









AGTACGACCCTTCTTGTGTCACCGCAGGGGCCCTGCAG









AGGGCCATTGAAGCTCTCCCACCAGGGAACTTTAAAGT









TTCTCTTCCTGCCGC
















TABLE 19







SNPs that are in LD with SNPs in Tables 17 and 18






















P value,
P value,




Distance


P value,
P value,
quantitative
quantitative


SNP in Table
SNP in LD
between


histology
histology
copper
copper


17/18
with 1st
1st and

R-
phenotype, 1st
phenotype, 2nd
phenotype, 1st
phenotype,


(1st SNP)
SNP (2nd SNP)
2nd SNPs
D′
squared
SNP
SNP
SNP
2nd SNP


















Chr22_3167534
Chr22_9075014
5907480
0.826688
0.658336
0.000102
0.838726
0.011219
0.662255


Chr22_3167534
Chr22_9110499
5942965
0.826688
0.658336
0.000102
0.838726
0.011219
0.662255


Chr22_3167534
Chr22_12226464
9058930
0.775399
0.506036
0.000102
0.961949
0.011219
0.822992


Chr22_3167534
Chr22_12167150
8999616
0.776521
0.519594
0.000102
0.935438
0.011219
0.815249


Chr20_55461150
Chr20_55413165
47985
1
0.618847
0.013353
0.002002
0.02121
0.006836


Chr20_55461150
Chr_55722677
261527
0.981609
0.604767
0.013353
0.001949
0.02121
0.006911


Chr20_55461150
Chr20_51285925
4175225
0.864011
0.516789
0.013353
0.019014
0.02121
0.003384


Chr20_55461150
Chr20_51293507
4167643
0.864011
0.516789
0.013353
0.019014
0.02121
0.003384


ChrX_120879711
ChrX_121658683
778972
1
0.614854
0.439138
0.122152
0.003469
0.006726


ChrX_120879711
ChrX_121460633
580922
1
0.614854
0.439138
0.122152
0.003469
0.006726


ChrX_120879711
ChrX_122098973
1219262
0.985408
0.597007
0.439138
0.14357
0.003469
0.007408


ChrX_120879711
ChrX_121686983
807272
1
0.614854
0.439138
0.122152
0.003469
0.006726


Chr32_38904515
Chr32_38901362
3153
1
1
0.203207
0.096572
0.095103
0.012416


Chr32_38904515
Chr32_41530572
2626057
0.918132
0.746623
0.203207
0.478783
0.095103
0.067148


Chr32_38904515
Chr32_41464680
2560165
0.930789
0.775057
0.203207
0.40641
0.095103
0.053666


Chr32_38904515
Chr_39410526
506011
0.974846
0.897803
0.203207
0.101671
0.095103
0.004032


Chr32_38904515
Chr32_39400223
495708
0.975
0.94828
0.203207
0.092261
0.095103
0.009802


Chr19_6078084
Chr19_6118863
40779
1
1
1.44E−05
1.12E−06
0.000718
0.000995


Chr19_6078084
Chr19_5955685
122399
1
0.962909
1.44E−05
7.35E−07
0.000718
0.000352


Chr19_6078084
Chr19_11224079
5145995
0.904645
0.519971
1.44E−05
2.03E−05
0.000718
0.015058


Chr19_6078084
Chr19_11219212
5141128
0.904645
0.519971
1.44E−05
2.03E−05
0.000718
0.015058


Chr19_6078084
Chr19_3103155
2974929
0.985272
0.948479
1.44E−05
3.27E−07
0.000718
0.000352


Chr19_6078084
Chr19_3132042
2946042
0.98518
0.948389
1.44E−05
2.84E−07
0.000718
0.000352


Chr15_62625262
Chr15_62710768
85506
0.982189
0.931938
0.013595
0.028102
0.000506
0.000519


Chr15_62625262
Chr15_62710622
85360
0.955267
0.866969
0.013595
0.037358
0.000503
0.000281


Chr15_62625262
Chr15_60266576
2358686
0.799649
0.50462
0.013595
0.097143
0.000503
0.02112


Chr15_62625262
Chr15_61996961
628301
0.861755
0.708941
0.013595
0.148755
0.000503
0.002744


Chr14_39437543
Chr14_39362812
74731
1
1
0.010528
0.012587
0.005583
0.006317


Chr14_39437543
Chr14_39525972
88429
1
0.983673
0.010528
0.026677
0.005583
0.006317


Chr14_39437543
Chr14_34279412
5158131
0.761669
0.537724
0.010528
0.00068
0.005583
0.01334


Chr14_39437543
Chr14_34385007
5052536
0.903595
0.547279
0.010528
0.000433
0.005583
0.035825


Chr14_39437543
Chr14_39185668
251875
0.965622
0.901263
0.010528
0.007561
0.005583
0.006455


Chr15_62625024
Chr15_62564157
60867
0.977671
0.497765
0.001012
0.000129
0.002747
0.002696


Chr15_62625024
Chr15_62596216
28808
0.79665
0.466377
0.001012
0.002047
0.002747
0.006061


ChrX_63338063
ChrX_64356804
1018741
0.989019
0.946875
0.001246
0.000247
0.034731
0.005983


ChrX_63338063
ChrX_64247356
909293
0.989019
0.946875
0.001246
0.000247
0.034731
0.005983


ChrX_63338063
ChrX_64596205
1258142
0.989019
0.946875
0.001246
0.000247
0.034731
0.005983


ChrX_63338063
ChrX_64318806
980743
0.989019
0.946875
0.001246
0.000247
0.034731
0.005983


Chr3_86838677
Chr3_86858401
19724
1
1
0.000661
0.000937
0.001572
0.003251


Chr3_86838677
Chr3_86974042
135365
0.949195
0.870279
0.000661
0.000305
0.001572
0.00148


Chr3_86838677
Chr3_86397551
441126
0.739619
0.527699
0.000661
0.004155
0.001572
0.023787


Chr3_86838677
Chr3_86403839
434838
0.739619
0.527699
0.000661
0.004155
0.001572
0.023787


Chr3_86838677
Chr3_86948527
109850
0.949195
0.870279
0.000661
0.000305
0.001527
0.00148


Chr8_4892743
Chr8_4892196
547
1
1
0.274005
0.098475
0.004869
0.014759


Chr8_4892743
Chr8_4889521
3222
1
1
0.274005
0.238005
0.004869
0.026988


Chr8_4892743
Chr8_11618239
6725496
0.845679
0.650159
0.274005
0.013872
0.004869
0.034342


Chr8_4892743
Chr8_11613479
6720736
0.845679
0.650159
0.274005
0.013872
0.004869
0.034342


Chr8_4892743
Chr8_9064669
4171926
0.966276
0.825462
0.274005
0.013109
0.004869
0.006045


Chr8_4892743
Chr8_9054168
4161425
0.966699
0.825173
0.274005
0.012575
0.004869
0.006045


Chr8_4892743
Chr8_5938207
1045464
1
1
0.274005
0.177173
0.004869
0.018788


Chr8_4892743
Chr8_5896281
1003538
1
1
0.274005
0.255392
0.004869
0.025001


Chr24_4011833
Chr24_9568995
5557162
0.968436
0.770885
0.002878
0.005212
0.028429
0.018937


Chr24_4011833
Chr24_9311101
5299268
0.968436
0.770885
0.002878
0.005212
0.028429
0.018937


Chr24_4011833
Chr24_9391376
5379543
0.968436
0.770885
0.002878
0.005212
0.028429
0.018937


Chr18_60812198
Chr18_42897855
17914343
0.687167
0.073112
0.447897
0.198618
0.047887
0.125786


Chr18_60812198
Chr18_45266899
15545299
0.781952
0.069095
0.447897
0.218449
0.047887
0.624226


Chr8_4880518
Chr8_19298728
14418210
0.69073
0.065351
0.579649
0.317402
0.066075
0.937917


Chr8_4880518
Chr8_6295891
1415373
0.385029
0.059849
0.579649
0.369191
0.066075
0.205044


Chr10_65209946
Chr10_65089416
120530
1
0.459482
0.003119
0.009497
0.141706
0.192725


Chr10_65209946
Chr10_65142039
67907
1
0.459482
0.003119
0.009497
0.141706
0.192725


Chr22_3135144
Chr22_3067105
68039
0.984428
0.879056
0.00026
0.000877
0.015303
0.012789


Chr22_3135144
Chr22_3349188
214044
0.969246
0.864914
0.00026
0.000456
0.015303
0.004781


Chr22_3135144
Chr22_13256436
10121292
0.943853
0.667922
0.00026
0.000326
0.015303
0.089054


Chr22_3135144
Chr22_13202693
10067549
0.953395
0.53079
0.00026
0.00268
0.015303
0.090825


Chr22_3135144
Chr22_10985753
7850609
0.984186
0.864323
0.00026
0.000905
0.015303
0.014708


Chr22_3135144
Chr22_10587732
7452588
0.984186
0.864323
0.00026
0.000905
0.015303
0.014708


Chr22_3135144
Chr22_14998527
11863383
0.776007
0.405128
0.00026
0.000216
0.015303
0.000397


Chr22_3135144
Chr22_11895473
8760329
0.962141
0.676774
0.00026
0.004793
0.015303
0.019903
















TABLE 20







Sequences of the SNPs (2nd SNPs) in Table 19














High



SNP in Table 19


copper



(2nd SNP)
base1
base2
allele
Sequence





Chr22_9075014
T
C
C
TgcctctccactactcactcttctcttgaaagattatttcCTgcttaaactggcccgtgactt


(SEQ ID NO: 159)



cctgctgcCAGAACCATGGAATGGCCTCCTGAGGGAGGCTCCCTATGCTGCTCCCAT[T/C]A






GCAGATATTGCAGCGTCACAGTATAACTCAGTGGCTTGAAATGATGGCTATTTATCATTGCTC






AGTAATTTGagtggctcgaagaggatagaatttcatttctttctcagataat





Chr22_9110499
T
C
C
TGTACAGCTGACTCCCTGAGAAAGGACATCCTGGGTCACCTTTCAAGTATTTCCTGGCATGGA


(SEQ ID NO: 160)



AACCCCATATCTTCAAACACAAAAATCAGAAAATCACAGTCCTTATCTGTTTGGGCC[T/C]A






TTTATAGGAGAGTCTTTTTATTGCCTGGAATTGTATATTTTTACATTTCTTAGATTTCTACAA






AATAATATTTGTGCCTTCTTTGAAGTATAATATTATTTATTAAAGTTGCTTT





Chr22_12226464
T
C
T
ATTAATACATTCTTAGTGTCTTCTTTAAAAATGCAACTTCCATGCTTTATAAAATACCAACAA


(SEQ ID NO: 161)



ATGCTTTACATCTTTATGATGGTAATTTTGGATCAATACTGGAGGATTTTAAAAAAA[T/C]C






TCTGCTTCCCCTGCTTGTGTGGTCTCTCACGCGCTCTCATTCTCACTCTGTCAAATAAATAAA






CAAAATCTTTCCAAAAAGACAAAGTCCTTGTGAAAACTGAGAAGGCCTGTGA





Chr22_12167150
G
A
G
ATTTGTACTTTCTTTTCACTTCTCCTGCGTGGTGCGTATCTCTCCAGTCTGTGTTCTTTAGGC


(SEQ ID NO: 162)



ATACATTGCTGTATGTGCTTTAAATAGAATCCTACCTTATATACTGCTTAATAACCT[G/A]T






GACCATAAGATCAGGttccatgtcttcaaagattctcctcatcattttcacgggtataggcat






agattacaattgatccattccccactttgcacatttagattgttttcacttt





Chr20_55413165
T
C
T
TgcaatgactctgtttacaaataaggtcacaatctcaggtAccagagcttagggcttcaacct


(SEQ ID NO: 163)



gtcttgggggagggtggGcaggataccattcagtccataacaGCAGAAGATCCCGGT[T/C]G






TCCTCACAGTATGGTGGGCAGTGGCCAGCCCTCCGGACTTTCACCTCCAGGGGGCAGGCGGAG






AAGCTAAAGGGGGGTCTCATGGCCTCCCAGCTCCTCCCTTTGCCCCTGCAAT





Chr20_55722677
G
A
G
ACCCACGCCCAGCATCTAAGAGGCCAACCCCTCCCTGCTGTGGGCTCCTGGGCTTCTCAACCC


(SEQ ID NO: 164)



CCAAGGAGGGGACTGCAGTCCAGCGTGCCGACAGCTGCCTCCACCCCAAAGGGGGCC[G/A]A






TGGCTGGTGAGTGGAGACTGAGTGCATGACCGACTTTTTTAGCCAAGACTTTTTCTTAATTGT






TAGAGATGGCAAActcaagcaaatgggaaactcatccgctcaagtaaccagc





Chr20_51285925
T
C
C
GCCTCGTGGGACAGCTTTCTAGCACTTTCCCCTTTTTAAGAGATTGACTGCAATTTCTATAAT


(SEQ ID NO: 165)



AACATCACATTAGCTAGAAATTAATGTCCTCATTAAGACAGCAATTAGGCACATTAG[T/C]G






CGGCAATAAAAGAGAAGCTTATGAAATAATTGCTGGTTCCGAAATGCCTTTAATTTAGTGTTT






TATATTGCGCCATGTTATTAATTTTTTCCCTCGGCAGAAGATAATAAGAGAA





Chr20_51293507
A
G
G
CATAAATGCCCCCCCCACCTCTGTGTCTGTGCAGAAACCAAAAGTCTTGGGCTTCTATGATCC


(SEQ ID NO: 166)



CCAGTGAGTGCTAGGAGCAGGACCGCAATCACAGCAGCACATCCTAGAAAGGACTTA[A/G]G






AGCCAGATACTACCATCCTATTCACTCAGGTAATCCTCACAGTAAACCGCAATGGCATAAAAA






ATATTACCTCCAGGGCCCAACGGACGgactcttgatctcagggttgtgagtt





ChrX_121658683
T
C
C
ATGAGATATGTCTGCTCAGCCACTGTCTGGGGCCTTGTAATTGAAGCCTTATAATTAGCATGA


(SEQ ID NO: 167)



AGTCACCAGCTTGGTCCTGCTGAAAGGGCACAGGGTGGGGTGTGAAAGGAGGATGGC[T/C]A






AGGGCTCGTCCACAGGAAACATTTTCTAAACACTAGAGAGGAGGCAGCCAAAGAGCTCCCTTC






CTCATCGCCCATGGACCCCACTGCTATGCTGGCAATTCCCCTTTTGGTTAAT





ChrX_121460633
G
T
T
TTCCTGTGCAGAGGGACACGTGAAGGCCCTAGGTCCTCCTGGGAGAAAAGATTTCCCTCCTAA


(SEQ ID NO: 168)



TGATCCAGGGACTAGGATTTCATTCTGAAATGGAATGGAGAATGGCAGGTGTGGCTT[G/T]C






TGGGGATTGAGAACCACAGGCCCCAGGAGATTCAGGAAAGGACAGTAATGCCCTGCTGCTCAG






GCCCCGGTGGAGGAATCATATCCTCAGCTCAGCAACACCACCCGCCCCCCTA





ChrX_122098973
A
G
G
ACATCGGCTAAACAAAAACAGGAGAATCCCATTATAAGACGGTTCCTGTAGTACAGATGTGTC


(SEQ ID NO: 169)



TGGGTGAAGCCTGGGTTGTATCGTGGCCCCATGTAGAGCCAGCCTGGGCAGAGAGCT[A/G]G






TCTACCCACTAAGCAACTGCAAGAGGCAAAGTGCAGCATTGATGTCACGAGGTCCAGCATCAA






CTAGGACCATCCCCATCCATGTGAGCAGGCTCACACGTGGAATCGCAGTGGA





ChrX_121686983
G
A
A
CCGTGCTTCACAGGCGAGAATCTGAATGACCGTGATGCCACCACATGTCACCATCCCCTTTTC


(SEQ ID NO: 170)



CACTGGGAAAGGGGTCCTTGTTGCCTTCCAGCTCCAGAATTGCATCCTCACAATTTC[G/A]G






AGGCCCTTCCTCCTGCTAAGCtctgtgcttttccagaaagtagagcataagacaagggcttat






atgcaagtatattttttggaaaatatgatcccagagagcaggagtgagaact





Chr32_38901362
T
A
A
ACTCCATGAAATGGTTTATTTTATCCTATGAATCgatgtgGagaacaaaggcaaaagaaatat


(SEQ ID NO: 171)



agaaaaatattaaatttCcttacaatgtacagcccattgataatattttagacagtg[T/A]g






agtgatcttgcttatggagctcaactgcctcaatgttaatccttagctaaaggcaaaagacaa






tcttagtttgacattagcctgaccgccttatgctatccctaacccccgtccc





Chr32_38901353
T
G
G
AATCCAAATACTCCATGAAATGGTTTATTTTATCCTATGAATCgatgtggagaacaaaggcaa


(SEQ ID NO: 172)



aagaaatatagaaaaatAttaaatttccttacaatgtacagcccattgataatattt[T/G]a






gacagtgtgagtgatcttgcttatggagctcaactgcctcaatgttaatccttagctaaaggc






aaaagacaatcttagtttgacattagcctgaccgccttatgctatccctaac





Chr32_41530572
G
T
T
AGGAAAAATATGCTTGCTTTTGAAGGAATCAATTTGTGGTTTCTTTTAATGAGTTATCAAACT


(SEQ ID NO: 173)



ATTAATAAGCATTAATTATTTATTGTGTAAGGCAAAGTGCTTCTTAATAGGTATTCT[G/T]T






CCTTAACTTAGAACATTCACAGATTCCCAATAGCCTCTAGTGCAGAAGAAGTCTGCCGCTCTT






CTTTCCTCCTTTCACTAGTCTCTCCTATATCTGTGATACCTCCAATCATAGC





Chr32_41464680
G
A
A
CttccatgttctgtctccctttctgatatttcctactcatTccAGAAAATATTCTTAATGAAG


(SEQ ID NO: 174)



CCTCTGATACGGTCTTGAGGATCCTCAGAGACCATATGTCAGTCTGTCAATGAAGCA[G/A]A






AATCAAGATGTTTGGATCCCTAGTAGATATGTAATCAAAATGCCATGGGAATACAGAGAAGGG






GAGTCATTTGTATCAGTTAGTGTTAAAAATTATTATCACGCTCTTGATATTA





Chr32_39410526
C
A
A
GAGAATACTGAAGACGTAATGAAGTTGAGTTCCACCTTTATAATAATTCCGTTTTACCCTAAA


(SEQ ID NO: 175)



GGGGAATATTCAAAAATGTGACATCGCTCTACCAGACCACCTTGCGACTGCTCTAAA[C/A]G






ATTGGCAGGGGCAAGAACTTGTGTCACTGATAGGCGGGATTTTTTAGTCCTCTCTGCAAATCA






TTAAGAAAATGTTCCAACGCAACAAAACAAAATATGGTGGCGATCCCTGAAC





Chr32_39400223
G
A
A
ACCTGATAACACCGCCTCAGTGGAGAACGAGTTGGCACTTCAGGACAGATTTCCCTGCCAGAG


(SEQ ID NO: 176)



CCTATTCCTGTTTGACACTTTCATTTGAAGAAACCCACTCATGGTTTCTTCTCTCCA[G/A]G






GTTTAAAACCGAGATCAAGTATATCTCTTTAATAATGTCACATTCCAAAGAATGACTCCGATA






AGGGGATTGTTCAAGGGCTTGGGTATTCACATAAGGGCTATCATGCGGGGAG





Chr19_6118863
T
C
T
TCCTCTAGATCTGACCTACATTTCAAAAATATATGAGTGGGCTATAACCAGGAATGTCTTCTC


(SEQ ID NO: 177)



TTGCTGCCATTATTCACACTGCATTTTCTGAAGTTGttttttttttttttttttttt[T/C]C






CCCTCGGTGACTTTAATGGCCATTGAGGGAACTGTAGACATTGGGAGTCTTTATACAGCCCTA






GTGAAATGGCGAGTGTTATCAATAGGGTGGCTGAATGGTACGGCTCTGGGC





Chr19_5955685
A
G
A
CATCTGTGACCCTTGGATTCAAACCAAGTAGGATGCAAACCTCAGAACTTCTGGCATTTCGGA


(SEQ ID NO: 178)



TGCACTGATCTCTGCCAGCCCCTTGCCCTCTTCTAATGGGATAGAAGCTGATGATGT[A/G]A






GACACCGCGTGCACCATCTGCCCAAGACGTCCCAGTTGATGCCACTCATCCTGGTTTGTGCAA






AAAATTCTCTATTTGCCCTAATTCCACCGCTCAGCAACTGGAAGGACCTGAG





Chr19_11224079
A
G
G
TCACAATGGCTTTTTTTTTTTTAAGATTTAACAGGAATTTTGTGATCCTTTATATGATATGTT


(SEQ ID NO: 179)



TCAATGAAGCCTTTTGGGAAAGGTTCTTAATGTGAAAGAATTTTCACAGAGAATATC[A/G]G






AAATAAATGTGCAAAAGGGAGTCGTTTTAGGATTAGAGATATGCATGGAAGAGGGAAAAAGCC






TACTTATATTACTAGAAAATAATTTTCAATTTAGAAGTTATACTGAACTATT





Chr19_11219212
G
A
A
CCCATTTTTTTAGGATTGATAAACTGATCATCTAACAGATATTATATACAAAAGTCAGAGAAG


(SEQ ID NO: 180)



ACACAATAGCCAACCCTGTGTGTAAGGAAAATGACAGAGTTGGTTAAAGAGAAAAGA[G/A]A






AAGGAGGTACACAGAGAGATGTAGAGGTCACATTAAAAATGAACGTTGTCCATGTCTATGAAA






GATGGAAGGTAATTCTATGCCTATAAGGTATGTTATAAGTTAAATTAATTGT





Chr19_3103155
T
C
C
AACAAACCTACCAAACAGGACAAACCAGTCCGGATTATATAATATGTAAATATGCCAGGGAGC


(SEQ ID NO: 181)



TGGGGAGCATACTTGTGGGAGGATAAGCTGGAGCAATGGTTAAATGAGCTCAATCCT[T/C]A






CTATACTTGAAGGTAGTAGCCTCTTCATTCACACTCCATGGCTAGCCCTTTGTAACTAAAATA






TGGAAAACACAACCAATGAAGAAGTTACATGTATCCCTAAAAATACCACCTA





Chr_3132043
A
G
G
CCCTTGGCGTTCTAAAGTCCAGCCCCCTCTCTTCGCATTCTGTGCTTTCTCCTGTGTGGC[A/


(SEQ ID NO: 182)



G]GTCTCTGTGCTTTATCTGCACATAAACACTTCACAAATTTCCGTTCCAGCTTAGTTCTCT





Chr15_62710768
G
A
A
TTAAGTTTAGAAAAAACAAATTCAAGAACAAGCTTTTTATATTTAACATCGATGAATCAGAAG


(SEQ ID NO: 183)



ATACGGGGttttttaaaTtattaaactaaaattattaaaCTGGTCCTGTTTGGGTATA[G/A]






GTTATCTTAATTATGCTAATCTGGAATCTTAAAGCATTTTTAAACTAATATTTTAAGAAACCA






AGTTTTAGATTTATTCCAACCTTGGGCTAGAAAAGGATGACCTTTGTGGGCC





Chr15_62710622
C
T
T
TgagccacccaggtgccccAAAACATGATTAGTCTTGAAACAAAGTGTATCACAATAATGATT


(SEQ ID NO: 184)



CAATTAGATGAATAAAATGTAGTTTTTGAGAATGGTAAACACTATGTAAGAGTAAAG[C/T]T






AGCCTATTTGATCAGTAAACCTATTTAAGTTTAGAAAAAACAAATTCAAGAACAAGCTTTTTA






TATTTAACATCGATGAATCAGAAGATACGGGGttttttaaattattaaacta





Chr15_60266576
C
T
T
AGATGTCATGCTATGATATATTTAAATAAGTTACAGACATGTATAATTTCCATGGTATGTTTT


(SEQ ID NO: 185)



ACATTCatataaaaattAactattcataaaatataataaaatGTAGTGTTTTTCTTA[C/T]T






GAGCTTCAGTGATCATAATTTGTATATTAACTTAATGACCAGAAATAATTAAGTAAAGCTAGT






TAAATTCTTGGGATGTTATGGATTATGTTATTTGGTTGGCTGTTCATGATAA





Chr15_61996961
A
G
G
TGTTTTGAATTTAAGGTGTTTTTCCAGGCTGAGAAGAAACGTGAGCTCTTGGAAATTAT[A/


(SEQ ID NO: 186)



G]ATTAACGTATCTAATGCATATACCCTAGAGGGCAAGGAAATTTCTATTCATTCCCTGTAT





Chr14_39362812
C
T
C
CCCCCAGGATCTGTCAGTAATCCCTGACTGCCTGCAGACCACATGGGGAGAGGGATCCATTCC


(SEQ ID NO: 187)



TATGACAGAGAATTTATACTGGCTTGTGAGCTGAACAGATACCTCAGAAGATGTTCA[C/T]C






TGTGAGACAGAGAGACATGGTGACAAATACAAGTGTCAGCCAACAGCAGCACCAAGTCCAGGA






ATGGCTGCCTGAGCTGGATGGAACCTCACTATCCAGAGCCATCCATAGGCCG





Chr14_39525972
A
G
G
AGAGCCAACGCTGGATCTCAGGGAGAATCTAGAAGGCCAGCTGACCAGAAAACCAACTGG[A/


(SEQ ID NO: 188)



G]CAGACAGAAGCTGGGAGCAGCGCCTGTGGAGGCAGGCACGAGAGGCCCCGGTGCAGCCGC





Chr14_34279412
G
C
C
CTGGGTGGCTGTTGGAGAGAGTGTGTTGTGTTGTTCCCAGGGTTAGTCCTAGGAATGGTAGAG


(SEQ ID NO: 189)



CCTGTCAAGTTCTCCCTGAAAGTCACGTCACTCCCCACTTCAGCAGGCCCAGCCTGT[G/C]T






TGTATCCCTGCAGCACTGCCTCAGGATCCTTGCTCTGCAGTGATCAGAGTCATCTGATAAGCC






TGTCCCTGTCTAGGCTGATATTAATTTCAGGTTGTCACCCTCTATGCCTCTT





Chr14_34385007
T
C
C
GGCCTTATGAAGACTTCTCTGATCTGTTGATCTGATGTACCCAGATTCTGAATCCCTAATTAG


(SEQ ID NO: 190)



ACTCAATTAGGACACTCCTGGAGGTGACTACTGCTTTCTTAGACTTTGTCACTCAAA[T/C]A






TCTAATACATTCGACTTTGACCCATGGATTTATTGAGTTCCTCTTGCACACCCAGTTCAGTAG






ATGTGGTCCACTATTTTGGTGCATCGACTGCTCTAGAATTTAGCTTTTGGAA





Chr14_39185668
C
A
C
AtgacacatgcaagtgctcaataacgttagACACTGTACTGTTAATTAAAGGTCTATCGCCCC


(SEQ ID NO: 191)



TTTAAACAAAATGTCCAGAATGTTCATGTTCACCAAAAGTGAAAGGCATTCATGTCT[C/A]T






GTTTCTGTTGAGTTCACTGTCACCTTTGTGCCTAGAAAGGAGAAGACACACTGGTTTTTCCTC






CTCTAGAGAAGTGCAGATTTGTATAGGTGAGGAGTATACATAGGTTGTGGGC





Chr15_62564157
G
A
G
CTTTGGGAATGAGGCCTGTCCCGCTAGCCTGCTTCATTTACTCTCATGATTCTTGGCAAAGTT


(SEQ ID NO: 192)



CTTATAAGTCACGTTCAAATTATCAGGCTTCATTCCTAGTCTGAGCAGACTTGTCCC[G/A]T






CTCCCAGCCTGTGGATGTTCAAGAAGCGCAACTTGGTTTTATGTTTATTAATCAAAAGCCCTT






TAGCCTCTGATGAACCTCTGAGGGTGGCTTTAAAGCCCCGCGCCTGCTCTGA





Chr15_62596216
T
C
C
AAAGAAAAAAGTAAGGGTCAAAACACTAGCaaaattaaatTaaaaaaataaGAAAAACAAGTC


(SEQ ID NO: 193)



ACACTTTTTTTTTTTTTTTGGTCATTTGGGAAAAGCACAATATTTTGCTTGATTACT[T/C]T






TCCTCACTTTTCAACTAGTAATATAGATTGCATGAAAAATAAACAAAACAAGTAAACTTTAAA






TGTTTGCTGGTGTAGAGGTGAATAAGAACAATCCATGGATTTTGCAATCACA





ChrX_64356804
T
C
C
TCTAGCTCCAGTCTCCTTTATTCAGTGCCACCTTCATTTTTCCATTCCAGCCAAATTAGTGTT


(SEQ ID NO: 194)



TTCATTCTCTCAAGCATTTTCATCTATGTACTTCCTGAACCCTCTTCATGGAAGACA[T/C]C






CTCTACTCTTCAGCATATTACTATCCCAGCATCCCTTACCCTGATAGTTTAACTTGATTCTTT






ATCTACCTGATTCAGTAATATTTCTCTATTCTTATCATATTCAGCAATGTTC





ChrX_64247356
T
C
C
TCCCCTACTGAAAACAAATTCCCCCATCTTCACCCTACCATGGGGATTTTACATTTGTTACCA


(SEQ ID NO: 195)



GATTTGGGGCAAACTCATCCTATTTTCCCTTCAGTGTGGAGAAGAGATTTTGGAAAA[T/C]A






GACCATGCAAATCTCTAAGCTCACAATAAACTGAATTGGAGAGGCATAAAACCTGACAGGAAA






AAAAGGTGTGAACTTGATCTTTAGCTTGCTGTTCTGGTTTAATAGGTTTCTG





ChrX_64596205
T
G
G
AAGGGTGAACTGACTTTTAGTCAGAATGTTTATTTTTAACAGATTATAAAATAGCCACCTATT


(SEQ ID NO: 196)



TAGATGGATAAATGTATTGTGATTATGGTGTTGTTTATAAAAAGAATTTTCAGGATT[T/G]T






CCACAAAACTTAATGTTAGTATTAGTTATTAAGAGtacaatggaatatcattcagccatataa






aagaatgaaatcttgctatttgcaatgacatagatggagctagagagtata





ChrX_64318806



unknown





Chr3_86858401
T
C
T
ATGAGTTTGCAATTCTAGCCGGTGCATGAGGACTTCTCCCTTTCCCGAGCCCTCCCGGAAAGT


(SEQ ID NO: 197)



TTGGCCAGATCCCCAGCCCAAATGGCAGCATGTGCTCGGGAAGATGATTAATGTTAG[T/C]G






CGAGGCTCCAGAGAATCTCTCAGGGCCCTTTTGTTTATTAAATAGAAAAATTCATGTTTAAAT






ATAATGTCAAGGGGATGACACGGACCAACATGATCCAAGACAGACTGCCGGC





Chr3_86974042
T
C
C
CTCCCACTAACTAGCAGGTATACATAGTTAAATTTCTCTAACACAGAGCAATACTACCTTCCA


(SEQ ID NO: 198)



CACCAGAAAATGGCAAAGGCTAAATATAACCACAGATCTCAAGGCTACTGAACTACA[T/C]G






CAGGTAATAGATTATATTTAAAACATATCAGATGAATCTGCACTAATACTGGGGGCCTATAAA






ACTTTCTAACATACAGTAGTATAAGCAGGATTTCCAATCAGTGAGAAAAGGA





Chr3_86397551
A
C
A
ATGTGTAATTTACAAAGAGTTCATATATTACTTTATCAGTTAAGCTTTTGTAATTCCATA[A/


(SEQ ID NO: 199)



C]TCTATACTAATTTTAAAGAGGAGTGATTCCTTCTTGCAATTAGTTTATTGCCTCCGTATG





Chr3_86403839
A
G
A
ATATATCATTCCACCTATAGTAATTTTCACTAATCTGCCCATTTATTCCCTAGTGCATACCCT


(SEQ ID NO: 200)



TAATATAAATCTGCAACAAGAATATAACTTTTCTAAAAAAAAAAAAAAAGTGTACAT[A/G]C






ATTAGTGATGTGTGTGACCAACTAAATACCAGTGTATAAGCCCATGCCCATATTTCATTTTCA






CGAATTATGTTTGCTGCATAAATAAGACTTGTAGCTTTTTAAACTTACCTCT





Chr3_86948527
G
A
A
GTGTCAGTATGTTAAGCCACTAGTGCACTGTTAACTGCTGCCATGACTAAGAAAAAACACAGA


(SEQ ID NO: 201)



AGCTGCTGCTGCTACTATGTCACTCTTGTCATTTTTAAGGTGAATCCTCATATGAAT[G/A]A






GAGGGAGTACATGCTTAATGGTCAGAGTGACAGCTTTTGCTTCATGGCGAGCCATCGAAACCC






CACAAATCTCTTTGCCCCAACAGATTCTTCACCTTTCTTCTCCAGAAATGAA





Chr8_4892196
A
G
G
TtatggatcttacaatctagtgattgaaacaCAAATTAGATTTGGGCTTGTCTATAAAACTGG


(SEQ ID NO: 202)



GATATTTTCTGATATTGGAATGAATACTGGGACAGTCCCTTAATTTTGGTTTCATGA[A/G]T






GATTAGTCTTATGATACATAGTTTATGTGTAATTGCTATTTCTAATCCAAAATAAATTGGACC






TTTCGTTTAGATTAAACATGGAGTCTTTGATGTAAATACCGTAGAAGGAGTC





Chr8_44889521
C
G
G
TgctgtctaaacaggagcttgaaggatgagtaggaagagaTttcagatagaacagctgtgctg


(SEQ ID NO: 203)



gagcaaagagggtctgaGggagcatggtatatttagtggacggcagctagttgcctg[C/G]c






actggagcatggcgggtggggagtaagaggtgggagagaaaactcaatgacaggcagaagcca






gaccatgaagGGCCTCACATCCTGTGCAGAGGAGTTTGATTTTTATCTCCT





Chr8_11618239
T
C
C
TTTGTCCTTGAAAGAAGTTTTTCTCTTTCCTTTCCCATTTTCTTTTCTTCCTATTTGCTTAAT


(SEQ ID NO: 204)



TATCTGTTGCCAGATAATTCACACCTAAGTTCATAGAGGACCAATGTCACAGATATT[T/C]T






CTTAAACAAAACTGGCTTTGTAACAATAAAATTTGTCTGTTTAAAATGTAACTAATATCGGAG






ATATTTACCTAAGGAAGTATTTGTAAATAGTATCTAGAAATGCAAGAAAATA





Chr8_11613479
C
T
T
GCCAACGCTAAGATTCATAGTCTATTTTTTACTCAACACCAAATAAAGGTACCATTTCTAATC


(SEQ ID NO: 205)



CAAGAACTTCACTCTGCTGTCTTCTAGCACATTGGCATTTTCCACAGGCATTTCTTG[C/T]T






TTACTTGATGTATTTTTTTCCAGTTTTTCTTAATATGATATCTGAGAAATTTTTTTGCTAAGT






ATTGATTCAAAAATTTAAAATTAAGGTTAAATTGTGGCTAATCAGCATACTG





Chr8_9064669
C
T
C
TTTTATCATGCCAGGAAATTCTTGGAATGTAGCCACTGTCTGATATTTATGGTTCCATAAGCA


(SEQ ID NO: 206)



TTTGACTCTGAAAAGTCTCTAATTCTGGAAAACGGCCACTGATCAGTTGTTAATGCA[C/T]A






GCAGTAGGAAAAAAGTCACCCCTTAAAAGGAGAGAGAGGACAAAAGGAACAGCTTGTGAGGCT






AAAAGTATGACAAGTATGACGTCTACCTATACAGGAAGTGTATATGCATCT





Chr8_9054168
A
G
A
GCTAATAAAGGATCAACCTCTGGGCTGCAGAATAACCTAATCTATTCATACCTCAGTGAC[A/


(SEQ ID NO: 207)



G]TCCTGAATTAGAACCGGGGGCTGATGAACTCCAATGCACCAGCCAACCAACCAGAGTTAG





Chr8_5938207
T
C
T
TGAATGACTTTTTCAACCCGAATTTTCATGACATTTTTGTCATGACATTTCTCATATAACCTA


(SEQ ID NO: 208)



CCGCATGTAAAGCAAGATCTCCTATTGGATTCTGCTTATTTTTTGTCATCTTCCAA[[T/C]G






GTCTTAGGCAAATGAAGTTTAAGTAGTAAGATTATATGCCTCCTCCCACTTTGGTGCATGCAC






ACAGATGCAGGAACATGCTTAGTAACTAATCTTTGTGGGACATAGGAATGCC





Chr8_5896281
G
A
G
GCCAGCTCTAATGAGTTTGTTTCCAAGCGGTGCTTCCAGAAATTGTTAGTGGTTGGTAGTTGC


(SEQ ID NO: 209)



AATGGGTTTTGAAATTAGAGGACATCACAGCAGAGTAGAATGGTTTGGAACAGGGGG[G/A]T






ATGATTAGGATTAATGAGATGAAAGAAAATTCTGGCTAGAGGGCTAGAAGAGCCATGGAAGAA






AATATACACTAACCCTTTGGAGTGTTCCTCCAAGTGAAGATTTGCAACATTT





Chr24_9568995
T
C
C
ACGAGAAGCAAGATTGCCATACCGTTCCTGGTACCGGGCCATGACGTTGACCTTCAAAAGCCC


(SEQ ID NO: 210)



TGAAACGGCTGTTTTCCTGGCTGCTGTGAGCTGTGGAACTCAGGAGTAGGTATTTCC[T/C]G






AAAACATTTAACATCCCATAGCAAAGGTGTTGGAGGCGTCGTCTCCATTGTCGTTTCTCCCGG






GCTGTGGTTGGCCTTTCTGCGTGAGTGCTTCTCCCCGCTGCGGGCTGGCTCT





Chr24_9311101
G
A
G
TAGGAAAAAACATCTGGCCTCTGACTCGGATCCAGTCATCCCAGCCTCATTCACACCCACCCA


(SEQ ID NO: 211)



TCAGCTCTCAGAGAACCTTCTGAGACTTCGATAAATAGCTGAGCCCTTAAAATGACA[G/A]C






ATTGATTTGGCATGGTTTGGGCAATAACTTCTGGCTGCTGTGATTTTTAGGTTTTGAATATTT






AGTTTCTGGAAACTCTGATAGAATGAATAACTTTATATGTTTATTTAATTCT





Chr24_9391376
T
C
C
GTCTACTGAAGCCAGACAGTTGGTTCATTAGATTAATTAAAGTGCAAACTAACCCCAATCTGG


(SEQ ID NO: 212)



TGTTTTGATAACGGCCACAGGGCTCTTGAAGTTGGAATCGGCCAGCATTTGACAGTG[T/C]T






CTCATTAAAGCCACAGTGGAATTGCCTCTATGGTTTCTCCTAAACTTTTGAATTTACCTTATA






ACAAAGAAGTGGACTTTGAGCATCCCTGATTGTTTTTTCAGTGTTAACTGCT





Chr18_42897855
T
C
T
TGTTGCTTTCCTGCACACAAGCAGTTGAACCAGAGTAGGGAGGAATCATTTTTAGGAATGTGT


(SEQ ID NO: 213)



TATTATTATTTTTTAGGAATGCACAAAACCCATGCCAAAAAGCCCATCCACGTCTAA[T/C]G






TCCTTGAACCTCTCCTTCACTACCAATTGTATTCTTTTATGTTCCCAATCAACTGGCTGGCCT






GAAATAGATTTCTCCTACCAAGAAATGTAGATAAAAATATTTATTTCTGGAA





Chr18_45266899
G
G
G
GTCTCAGCCCTCTATTCCAGAAGGTAGGACTGGCCCTGGGCCTGTCTACGAGGTGGTGGCTGC


(SEQ ID NO: 214)



GAGCCCTCAAGGCCTGGCATTGTCAAAGTTCTGACAACCTTCCCCACCTATGGCAGC[T/G]C






AGTGTTAGACGCTCCAGGCTGAGGGTTGATGCACACTTTTTCGGCTTCCAAAGTGTGGCCTTC






TCCTCAGGGCTTCCCATGGGGTCCACAGGCTGGCAGCAACCTCTTGGAGAAA





Chr8_19298728
G
A
A
CAGCTGTGTCATGGAAATGGCACTTTAAAAATTCATATGAATCTTAACAGTAAAGCACAAGAC


(SEQ ID NO: 215)



TTTGGAGATATTTCTCCTGTTGAATAGCTGCTTGGGGATGTGCCACAGATCTGTAGA[G/A]G






TCAGCATTCACTCTAAGTTCCCGGGAACCATGAGACAGCAGCAACCATGGCCACcacagcaac






acagcaggtgcccataagcccattttacagatggagaaattgggtccagaga





Chr8_6295891
T
C
C
CCTCTGGCTCCCCAGAACCTCAGAGCTTAGGGGATGTAGTGGTTGTAATCCTGGATCCCTCTG


(SEQ ID NO: 216)



TGGGGTGGCAGGTCTGGAGTGGTGAGCTACTGTGAGGGAACTGGGGTAACTGTGACC[T/C]G






AGAAGAAAGGAGCGAGGGAGTGAGTGTGTGTCTGTGAAATATGCCTCTGTGTGTATAAACAGG






GCTGGAGGGCTCAGTGCCCCCCACTCCCAAAGATCCACCTGTTACATCCCCG





Chr10_65089416
G
A
A
TtcttctcttgtgactggtcactaaagacagagatttcagGagagctgactttggtaggaatt


(SEQ ID NO: 217)



ctcacccttttctggccTaggccTATAATTTTTATACCGACAGCTGGAGTCCCAGAT[G/A]G






AAGAGACCTTAAACTCTTTGGACTATGAAGAACCTGTTTTTTCTCTCTCTCTCTTTTTTTTCC






CCTTAAAACAAAAATTTATTTTCCTCAGGCCTCatcctgtacccagtcttgt





Chr10_65142039
A
C
C
AGCTCCAATTTAGTCATATACTAAAGAATCAGGTCATACTCTAGGCAGACTCTAGGCAGTTAG


(SEQ ID NO: 218)



CACATGAAACCAGTTCACATGCTTTATCATCATCCTTTTTGTTCTCAAAACAGCCAA[A/C]A






ACAGTTCTGTATAAGATATTTCACATGTTTAATTCTTTCAGTTCTTCTAGCAAGCAGGAAGCT






TAGAACAAGATTTTAGTATTTGGTTTAGATAACAATTGCAAATAggagcacc





Chr22_3067105
G
A
G
GACTTTTCTAGAGAGACCATGGAAGATGCATGTGGGGCCTGCCCAGGCTGCCACAGGGGAAAG


(SEQ ID NO: 219)



GAGCCGGGAGGAGGGAGCTGTCAGGCCACTTCCTCTGATGGCCCCTCAGCAGCAGGA[G/A]G






AGAGCATTTCCTCACCAGATCCCACTCAACACTGGCCACGGTCCCCCTGTGGACTTCAGAACT






GACTCAGAACTAACCTGACTGACTGCGTATGATTTGTCTTTTTAGGAGGACC





Chr22_3349188
G
A
G
CCCGCGCCAGGCCGGTCCTCTCCTCCCAGCTCCTCCTCTCCCGCTCGCAGTCAGGGCAGCCAG


(SEQ ID NO: 220)



GGAGGGGAGAAATTCTCATCTCAAAACTAGTAAGACAAGGCCCCGCAGCGGGTCTGC[G/A]G






CGCGGAGGCGGCTGCCTCTCCTGGTCCATACTGGACACAGCTGACCACATTTCAACAGGTAAG






AATCATTTTAAATATTACCCTTAAACCAAAAAAAGTTCTTCTTTTGCTTCTA





Chr22_13256436
T
G
G
CAGTATTCCGATTCTTCTATTTGCTAATTTTAAAGTGCAGATCTAAGAGGACAACCTTATTAT


(SEQ ID NO: 221)



TATTTCCATGGTCTTAGAGATCATCTTACTGTTGCCCCACAATGTCCATGCTTCCCG[T/G]G






AAAGATGTGTGTATCCAGACTCAAAGTGAATCTAATAGGGAAGGAAGACTGAGAATTCTATTA






GTAAGCAACCCGTATTTAACAACATGGCCCAGTTTGAAGATTTGCAGAAACA





Chr22_13202693
G
A
G
TCAGGAGTGAGCCTGTACGTTATCCTGACTACTGATTCCCTTGCACCAAAAAAGCAACGGGAG


(SEQ ID NO: 222)



CATAAGGGCAAGATATGACCTTTAGCTAAAGGGTTGCAAGTTATATTACTAGTCGTC[G/A]C






TGCTCAAACACCCAGCACCAGACCCTGCATAGAATACAGAAAAGAGTCCTCACCATCAAGCCA






CTACCACCTGAAGCATGAAGGAGAGAACAAGGAGAGATCACCTCCTAAGTGT





Chr22_10985753
G
C
G
CtgacctctgCTCTAGTCAATTGCTCTGAAAGTACAGTCCTCTGATCCTAGACTCGAACCCTC


(SEQ ID NO: 223)



TCAAGCATAACAGTTCCATCTACTATTCACTAATCCATTTATTTAACTGGGAGTGTT[G/C]T






ATGCTTTGGCTCTGGGATATGAAGGAAAGGACATTGTGCCCGAACATATAGGAAAGTTATTGT






TTAAGGAGATATACAGGGAAATAATTTTAAAACACCATGGTAATCTTttcct





Chr22_10587732
A
G
A
CGTTTTCCTTATAAATTTTTagaaaacagaacaggaaaaaAaaaaaaAgaaagaaaacagaac


(SEQ ID NO: 224)



agagaacaaaCCAACATGTCTTGATGCCTCCAGGAACCAGTTTTCTCATAGCCTTAG[A/G]G






GAAACAATTTACAAAATATCTGAAAAGCCTGCAGATATCTTAGATCCAAGATTCCAAGGCATA






AAAATGTAAGTGATCATGTACTACGTATTACTGAAATACAGAAAGCAACCAA





Chr22_14998527
G
A
G
AGCACCTTGAGAATGGTGTAGTGGAAAGAAAGTTGACTTTTAGTAACTATGCATTTGTCTCGT


(SEQ ID NO: 225)



TAATGCAGTTTCTCACCTGCTTTGAGATAATGGGAAATGGAACTAACAGGTAGTGGT[G/A]A






CACAGATGATGGACAATATAAAGATTTGAGATATATATAAAAAAAATTTGATCATTATATGTA






CACTTTGCTAGTTTTGCTCTACATTTTTTATCCACACAAAAAGTAATTTGCA





Chr22_11895473
A
F
A
TAAGTAGCCTTTAGTGCAAGGAAAAGAAAAAGGCAGTAAGGATGAACCTTTGTTTCAAAGGTA


(SEQ ID NO: 226)



TTAGGAGTCATTTAAGGAATTTCAAAAAAAAAAAAAAGAAGTGACATGATTTTGAAC[A/G]A






AGAAGTGACTGTCAGTACTATAAAGAGCACATTGCCTCAAGGAGAAACTGAAGTTAGAGAAGC






CAAATTGGCTGATAAAAATCTAGGCCGGAGATGCAAACACCTAAATGAAAAC










Model Generation


The mutations identified in Tables 17 to 20 can be used on their own to determine susceptibility to, or protection from, liver copper accumulation. However, a more accurate method of assessing susceptibility to, or protection from, liver copper accumulation may be achieved through the use of models involving combinations of mutations. The mutations in Tables 17 and 18 were used in model generation as described below.


Variables


The variables chosen were all the mutations identified in the Geneseek genotyping as well as gender coded as 0 for male 1 for female. Genotypes were coded in ordinal form as 0, 1 or 2 (count of second allele).


Two reporter variables were used, log 10-quantitative copper and histology score. Both of these appear to respond linearly to the genetics and approximately to each other and so make good candidates for linear modelling of this type.


Method


Due to the number of variables and the sample size available, not all genetic effects can be modelled together. To solve this a stepwise modelling technique was used. This technique determines which factors should be used in a model by inserting and removing them while observing the significance of the estimates of coefficients in the model. The precise method used is described below:

    • 1. The data was mean-patched to allow for missing data.
    • 2. A stepwise regression was carried out on the mean-patched data, using the MATLAB stepwise command. This uses a confidence interval around the coefficients of 0.9.
    • 3. The selected variables and co-efficients were then recorded and residuals inspected for an appropriate variance distribution.
    • 4. To explore appropriate cutoffs for a diagnostic, odds-ratios, prevalance-corrected positive predicted value and prevalance-corrected negative predicted value were generated for all potential cutoffs to generate a chart showing the trade-off between PPV and NPV at different cutoffs. For these purposes a positive was >2.5 on the histology scale and >600 mg/kg copper on the quantitative copper scale.


      The key to the factors used in model determination is shown in Table 21:












TABLE 21







Factor
Name









X1
Chr32_38904515 (UBL5 ortholog)



X2
Chr20_55461150 (STXB2)



X3
Chr19_6078084 (microsomal glutathione




S-transferase 2 (GST))



X4
Chr3_86838677 (KRT18 (Indian childhood cirrhosis)



X5
Chr14_39437543 (Interleukin-6 Precursor (IL-6))



X6
Chr8_4880518



X7
Chr8_4892743



X8
gender



X9
Chr24_4011833



X10
Chr10_65209946 (COMMD1)



X11
Chr22_3167534 (ATP7B)



X12
Chr22_3135144 (ATP7B)



X13
ChrX_63338063 (ATP7A)



X14
Chr18_60812198 (ATOX1)



X15
Chr15_62625024 (unknown gene)



X16
Chr15_62625262 (unknown gene)



X17
ChrX_120879711 (MTMR1)











Results


Modelling using the stepwise tool produced the predictive functions shown in FIGS. 8 and 9. FIG. 8 illustrates stepwise modelling of the histology copper score. FIG. 9 illustrates stepwise modelling of the log-quantitative copper score.

Claims
  • 1. A method of treating or breeding a dog, comprising: (a) genotyping a biological sample obtained from the dog to determine in a genome of the dog presence or absence of a polymorphism of Chr22_3167534 (position 101 of SEQ ID NO: 144; and(b) administering to the dog a low copper food stuff or a therapeutic amount of a copper chelator when the polymorphism is present; orbreeding the dog when the polymorphism is absent.
  • 2. The method of claim 1, further comprising genotyping the biological sample obtained from the dog to determine presence or absence of one or more polymorphisms selected from the group consisting of BICF2P506595 (position 61 of SEQ ID NO:1), BICF2P772765 (position 61 of SEQ ID NO:2), BICF2S2333187 (position 61 of SEQ ID NO:3), BICF2P1324008 (position 61 of SEQ ID NO: 4), BICF2P591872 (position 61 of SEQ ID NO:5), ATP7a_Reg4_F_9 (position 164 of SEQ ID NO: 131), UBL5_Reg1F_16 (position 97 of SEQ ID NO: 132), golga5_Reg1_24 (position 70 of SEQ ID NO: 133), golga5_26 (position 88 of SEQ ID NO: 134), golga5_27 (position 104 of SEQ ID NO: 135), golga5_28 (position 139 of SEQ ID NO: 136), golga5_29 (position 128 of SEQ ID NO: 137), golga5_30 (position 95 of SEQ ID NO: 138), golga5_31 (position 106 of SEQ ID NO: 139), atp7areg17_32 (position 95 of SEQ ID NO: 140), and atp7areg17_33 (position 90 of SEQ ID NO: 141).
  • 3. The method of claim 1, further comprising genotyping the biological sample obtained from the dog to determine in the genome of the dog the presence or absence of one or more polymorphisms selected from the group consisting of Chr10_65209946 (position 101 of SEQ ID NO: 155), Chr22_3135144 (position 101 of SEQ ID NO: 145), Chr20_55461150 (position 101 of SEQ ID NO: 146), Chr19_6078084 (position 101 of SEQ ID NO: 148), Chr3_86838677 (position 101 of SEQ ID NO: 152), and ChrX_63338063 (position 102 of SEQ ID NO: 142).
  • 4. The method of claim 1, wherein the dog has genetic inheritance of the Labrador Retriever breed.
  • 5. The method of claim 1, further comprising genotyping the biological sample obtained from the dog to determine in the genome of the dog the presence or absence of one or more polymorphisms selected from the group consisting of Chr22_3135144 (position 101 of SEQ ID NO: 145), Chr20_55461150 (position 101 of SEQ ID NO: 146), ChrX 120879711 (position 101 of SEQ ID NO: 147), Chr19_6078084 (position 101 of SEQ ID NO: 148), Chr15_62625262 (position 101 of SEQ ID NO: 149), Chr14_39437543 (position 101 of SEQ ID NO: 150), Chr15 62625024 (position 101 of SEQ ID NO: 151), Chr3 86838677 (position 101 of SEQ ID NO: 152), Chr24_4011833 (position 101 of SEQ ID NO: 153), Chr18_60812198 (position 101 of SEQ ID NO: 154), CGCCCC repeat at chromosome location 22 starting at genomic location 3135287, Chr32_38904515 (position 101 of SEQ ID NO: 156), Chr8_4892743 (position 101 of SEQ ID NO: 157), Chr8_4880518 (position 101 of SEQ ID NO: 158), ChrX 63338063 (position 102 of SEQ ID NO: 142), BICF2P506595 (position 61 of SEQ ID NO: 1), BICF2P772765 (position 61 of SEQ ID NO:2), BICF2S2333187 (position 61 of SEQ ID NO: 3), BICF2P1324008 (position 61 of SEQ ID NO:4), BICF2P591872 (position 61 of SEQ ID NO: 5), ATP7a_Reg4_F_9 (position 164 of SEQ ID NO: 131), UBL5_Reg1F_16 (position 97 of SEQ ID NO: 132), golga5_Reg1_24 (position 70 of SEQ ID NO: 133), golga5_26 (position 88 of SEQ ID NO: 134), golga5_27 (position 104 of SEQ ID NO: 135), golga5_28 (position 139 of SEQ ID NO: 136), golga5_29 (position 128 of SEQ ID NO: 137), golga5_30 (position 95 of SEQ ID NO: 138), golga5_31 (position 106 of SEQ ID NO: 139), atp7areg17_32 (position 95 of SEQ ID NO: 140), and atp7areg17_33 (position 90 of SEQ ID NO: 141).
  • 6. A method of treating or breeding a dog, comprising: (a) inputting to a computer system genotyping data concerning presence or absence in a genome of the dog a polymorphism of Chr22_3167534 (position 101 of SEQ ID NO: 144);(b) comparing the genotyping data to a computer database, wherein the computer database comprises information of the risk of dog liver copper accumulation associated with a polymorphism of Chr22_3167534 (position 101 of SEQ ID NO: 144);(c) determining whether the dog is at risk of liver copper accumulation based on the comparison; and(d) administering to the dog a low copper food stuff or a therapeutic amount of a copper chelator if the dog is determined to be at risk of liver copper accumulation, orbreeding the dog if the dog is determined to be not at risk of liver copper accumulation.
Priority Claims (1)
Number Date Country Kind
1120989 Dec 2011 GB national
CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional of and claims priority to U.S. patent application Ser. No. 16/181,516, filed on Nov. 6, 2018, which is a divisional of U.S. patent application Ser. No. 14/363,751, filed Jun. 6, 2014, which is a national phase application under 35 U.S.C. § 371 of International Application No. PCT/GB2012/053038, filed Dec. 6, 2012, which claims the benefit of Great Britain Application No. 1120989.7, filed Dec. 6, 2011, all of which applications are incorporated herein by reference in their entireties.

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