A genome-wide association study demonstrates significant genetic variation for fracture risk in Thoroughbred racehorses

Background: Thoroughbred racehorses are subject to non-traumatic distal limb bone fractures that occur during racing and exercise. Susceptibility to fracture may be due to underlying disturbances in bone metabolism which have a genetic cause. Fracture risk has been shown to be heritable in several species but this study is the first genetic analysis of fracture risk in the horse. Results: Fracture cases (n = 269) were horses that sustained catastrophic distal limb fractures while racing on UK racecourses, necessitating euthanasia. Control horses (n = 253) were over 4 years of age, were racing during the same time period as the cases, and had no history of fracture at the time the study was carried out. The horses sampled were bred for both flat and National Hunt (NH) jump racing. 43,417 SNPs were employed to perform a genome-wide association analysis and to estimate the proportion of genetic variance attributable to the SNPs on each chromosome using restricted maximum likelihood (REML). Significant genetic variation associated with fracture risk was found on chromosomes 9, 18, 22 and 31. Three SNPs on chromosome 18 (62.05 Mb – 62.15 Mb) and one SNP on chromosome 1 (14.17 Mb) reached genome-wide significance (p <0.05) in a genome-wide association study (GWAS). Two of the SNPs on ECA 18 were located in a haplotype block containing the gene zinc finger protein 804A (ZNF804A). One haplotype within this block has a protective effect (controls at 1.95 times less risk of fracture than cases, p = 1 × 10-4), while a second haplotype increases fracture risk (cases at 3.39 times higher risk of fracture than controls, p = 0.042). Conclusions: Fracture risk in the Thoroughbred horse is a complex condition with an underlying genetic basis. Multiple genomic regions contribute to susceptibility to fracture risk. This suggests there is the potential to develop SNP-based estimators for genetic risk of fracture in the Thoroughbred racehorse, using methods pioneered in livestock genetics such as genomic selection. This information would be useful to racehorse breeders and owners, enabling them to reduce the risk of injury in their horses

The utility of low-density genotyping for imputation in the Thoroughbred horse

BACKGROUND: Despite the dramatic reduction in the cost of high-density genotyping that has occurred over the last decade, it remains one of the limiting factors for obtaining the large datasets required for genomic studies of disease in the horse. In this study, we investigated the potential for low-density genotyping and subsequent imputation to address this problem. RESULTS: Using the haplotype phasing and imputation program, BEAGLE, it is possible to impute genotypes from low- to high-density (50K) in the Thoroughbred horse with reasonable to high accuracy. Analysis of the sources of variation in imputation accuracy revealed dependence both on the minor allele frequency of the single nucleotide polymorphisms (SNPs) being imputed and on the underlying linkage disequilibrium structure. Whereas equidistant spacing of the SNPs on the low-density panel worked well, optimising SNP selection to increase their minor allele frequency was advantageous, even when the panel was subsequently used in a population of different geographical origin. Replacing base pair position with linkage disequilibrium map distance reduced the variation in imputation accuracy across SNPs. Whereas a 1K SNP panel was generally sufficient to ensure that more than 80% of genotypes were correctly imputed, other studies suggest that a 2K to 3K panel is more efficient to minimize the subsequent loss of accuracy in genomic prediction analyses. The relationship between accuracy and genotyping costs for the different low-density panels, suggests that a 2K SNP panel would represent good value for money. CONCLUSIONS: Low-density genotyping with a 2K SNP panel followed by imputation provides a compromise between cost and accuracy that could promote more widespread genotyping, and hence the use of genomic information in horses. In addition to offering a low cost alternative to high-density genotyping, imputation provides a means to combine datasets from different genotyping platforms, which is becoming necessary since researchers are starting to use the recently developed equine 70K SNP chip. However, more work is needed to evaluate the impact of between-breed differences on imputation accuracy

Genetic diversity in the modern horse illustrated from genome-wide SNP data

Horses were domesticated from the Eurasian steppes 5,000-6,000 years ago. Since then, the use of horses for transportation, warfare, and agriculture, as well as selection for desired traits and fitness, has resulted in diverse populations distributed across the world, many of which have become or are in the process of becoming formally organized into closed, breeding populations (breeds). This report describes the use of a genome-wide set of autosomal SNPs and 814 horses from 36 breeds to provide the first detailed description of equine breed diversity. F(ST) calculations, parsimony, and distance analysis demonstrated relationships among the breeds that largely reflect geographic origins and known breed histories. Low levels of population divergence were observed between breeds that are relatively early on in the process of breed development, and between those with high levels of within-breed diversity, whether due to large population size, ongoing outcrossing, or large within-breed phenotypic diversity. Populations with low within-breed diversity included those which have experienced population bottlenecks, have been under intense selective pressure, or are closed populations with long breed histories. These results provide new insights into the relationships among and the diversity within breeds of horses. In addition these results will facilitate future genome-wide association studies and investigations into genomic targets of selection

Genetic Diversity in the Modern Horse Illustrated from Genome-Wide SNP Data

Horses were domesticated from the Eurasian steppes 5,000–6,000 years ago. Since then, the use of horses for transportation, warfare, and agriculture, as well as selection for desired traits and fitness, has resulted in diverse populations distributed across the world, many of which have become or are in the process of becoming formally organized into closed, breeding populations (breeds). This report describes the use of a genome-wide set of autosomal SNPs and 814 horses from 36 breeds to provide the first detailed description of equine breed diversity. FST calculations, parsimony, and distance analysis demonstrated relationships among the breeds that largely reflect geographic origins and known breed histories. Low levels of population divergence were observed between breeds that are relatively early on in the process of breed development, and between those with high levels of within-breed diversity, whether due to large population size, ongoing outcrossing, or large within-breed phenotypic diversity. Populations with low within-breed diversity included those which have experienced population bottlenecks, have been under intense selective pressure, or are closed populations with long breed histories. These results provide new insights into the relationships among and the diversity within breeds of horses. In addition these results will facilitate future genome-wide association studies and investigations into genomic targets of selection

A High Density SNP Array for the Domestic Horse and Extant Perissodactyla: Utility for Association Mapping, Genetic Diversity, and Phylogeny Studies

An equine SNP genotyping array was developed and evaluated on a panel of samples representing 14 domestic horse breeds and 18 evolutionarily related species. More than 54,000 polymorphic SNPs provided an average inter-SNP spacing of ∼43 kb. The mean minor allele frequency across domestic horse breeds was 0.23, and the number of polymorphic SNPs within breeds ranged from 43,287 to 52,085. Genome-wide linkage disequilibrium (LD) in most breeds declined rapidly over the first 50–100 kb and reached background levels within 1–2 Mb. The extent of LD and the level of inbreeding were highest in the Thoroughbred and lowest in the Mongolian and Quarter Horse. Multidimensional scaling (MDS) analyses demonstrated the tight grouping of individuals within most breeds, close proximity of related breeds, and less tight grouping in admixed breeds. The close relationship between the Przewalski's Horse and the domestic horse was demonstrated by pair-wise genetic distance and MDS. Genotyping of other Perissodactyla (zebras, asses, tapirs, and rhinoceros) was variably successful, with call rates and the number of polymorphic loci varying across taxa. Parsimony analysis placed the modern horse as sister taxa to Equus przewalski. The utility of the SNP array in genome-wide association was confirmed by mapping the known recessive chestnut coat color locus (MC1R) and defining a conserved haplotype of ∼750 kb across all breeds. These results demonstrate the high quality of this SNP genotyping resource, its usefulness in diverse genome analyses of the horse, and potential use in related species

Genetic Diversity in the Modern Horse Illustrated from Genome-Wide SNP Data

Peer reviewe

Genome-Wide Analysis Reveals Selection for Important Traits in Domestic Horse Breeds

Peer reviewe

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead