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Scientific reports2024; 14(1); 22930; doi: 10.1038/s41598-024-73645-9

Analyses of whole-genome sequences from 185 North American Thoroughbred horses, spanning 5 generations.

Abstract: Whole genome sequences (WGS) of 185 North American Thoroughbred horses were compared to quantify the number and frequency of variants, diversity of mitotypes, and autosomal runs of homozygosity (ROH). Of the samples, 82 horses were born between 1965 and 1986 (Group 1); the remaining 103, selected to maximize pedigree diversity, were born between 2000 and 2020 (Group 2). Over 14.3 million autosomal variants were identified with 4.5-5.0 million found per horse. Mitochondrial sequences associated the North American Thoroughbreds with 9 of 17 clades previously identified among diverse breeds. Individual coefficients of inbreeding, estimated from ROH, averaged 0.266 (Group 1) and 0.283 (Group 2). When SNP arrays were simulated using subsets of WGS markers, the arrays over-estimated lengths of ROH. WGS-based estimates of inbreeding were highly correlated (r > 0.98) with SNP array-based estimates, but only moderately correlated (r = 0.40) with inbreeding based on 5-generation pedigrees. On average, Group 1 horses had more heterozygous variants (P < 0.001), more total variants (P < 0.001), and lower individual inbreeding (F; P < 0.001) than horses in Group 2. However, the distribution of numbers of variants, allele frequency, and extent of ROH overlapped among all horses such that it was not possible to identify the group of origin of any single horse using these measures. Consequently, the Thoroughbred population would be better monitored by investigating changes in specific variants, rather than relying on broad measures of diversity. The WGS for these 185 horses is publicly available for comparison to other populations and as a foundation for modeling changes in population structure, breeding practices, or the appearance of deleterious variants.
© 2024. The Author(s).
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Publication Date: 2024-10-02 PubMed ID: 39358442PubMed Central: 3559798DOI: 10.1038/s41598-024-73645-9Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The study is about the evaluation of whole-genome sequences of 185 North American Thoroughbred horses, looking at genetic variations and estimating coefficients of inbreeding. It aims to improve understanding of horse genetics and inbreeding metrics, as well as establish a baseline for genetic diversity among Thoroughbreds.

Overview of Research Methods

  • Whole-genome sequences from 185 North American Thoroughbreds, born between 1965 and 2020, were analyzed.
  • The horses were divided into two groups: Group 1 (82 horses born between 1965-1986) and Group 2 (103 horses born between 2000-2020, selected to maximize pedigree diversity).
  • Analyses focused on quantifying variants and estimating individual coefficients of inbreeding.

Main Findings

  • Over 14.3 million autosomal variants were identified with a range of 4.5-5.0 million per horse.
  • Mitochondrial sequences connected the Thoroughbreds with 9 out of 17 clades identified among diverse breeds.
  • Averages for individual coefficients of inbreeding, estimated from runs of homozygosity (ROH), were 0.266 for Group 1 and 0.283 for Group 2.
  • The study found that SNP arrays overestimated lengths of ROH when simulated with subsets of WGS markers.
  • Inbreeding estimates based on WGS were highly correlated with SNP array-based estimates, but only moderately with estimates based on 5-generation pedigrees.

Comparisons Between Groups

  • Group 1 horses generally had more heterozygous variants, total variants, and lower individual inbreeding.
  • However, distribution of variants, allele frequency, and extent of ROH overlapped among both groups, making it hard to identify the group of origin of any horse using these measures.
  • The study suggests specific variants should be monitored rather than overall measures of diversity within the Thoroughbred population.

Implications and Future Use

  • This research provides a valuable baseline for comparison to other horse populations and future studies on population structure, breeding practices, or deleterious variants.
  • The whole-genome sequences for these 185 horses have been made publicly available to assist in future research.

Cite This Article

APA
Bailey E, Finno CJ, Cullen JN, Kalbfleisch T, Petersen JL. (2024). Analyses of whole-genome sequences from 185 North American Thoroughbred horses, spanning 5 generations. Sci Rep, 14(1), 22930. https://doi.org/10.1038/s41598-024-73645-9

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 14
Issue: 1
Pages: 22930

Researcher Affiliations

Bailey, Ernie
  • University of Kentucky, Maxwell H. Gluck Equine Research Center, Lexington, KY, 40546, USA.
Finno, Carrie J
  • University of California-Davis, Population Health and Reproduction, Davis, CA, 95616, USA.
Cullen, Jonah N
  • Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN, 55108, USA.
Kalbfleisch, Ted
  • University of Kentucky, Maxwell H. Gluck Equine Research Center, Lexington, KY, 40546, USA. ted.kalbfleisch@uky.edu.
Petersen, Jessica L
  • Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, 68583-0908, USA. jessica.petersen@unl.edu.

MeSH Terms

  • Animals
  • Horses / genetics
  • Whole Genome Sequencing / methods
  • Polymorphism, Single Nucleotide
  • Pedigree
  • Inbreeding
  • Homozygote
  • North America
  • Male
  • Female
  • Genome
  • Genetic Variation
  • Breeding

References

This article includes 65 references
  1. Willett, P. The Classic Racehorse (University Press of Kentucky, 1982).
  2. Bower M A. The genetic origin and history of speed in the Thoroughbred racehorse. Nat. Commun. 3, 643 (2012).
    pubmed: 22273681doi: 10.1038/ncomms1644google scholar: lookup
  3. Binns, M. M. & Morris, T. Thoroughbred Breeding: Pedigree Theories and the Science of Genetics (J.A. Allen, 2011).
  4. Cunningham E P, Dooley J J, Splan R K, Bradley D G. Microsatellite diversity, pedigree relatedness and the contributions of founder lineages to thoroughbred horses. Anim. Genet. 32, 360–364 (2001).
    pubmed: 11736806doi: 10.1046/j.1365-2052.2001.00785.xgoogle scholar: lookup
  5. Petersen J L. Genetic diversity in the modern horse illustrated from genome-wide SNP data. PLoS One 8, e54997 (2013).
    pubmed: 23383025pmc: 3559798doi: 10.1371/journal.pone.0054997google scholar: lookup
  6. Orlando L, Librado P. Origin and evolution of deleterious mutations in horses. Genes (Basel) 10, 649 (2019).
    pubmed: 31466279doi: 10.3390/genes10090649google scholar: lookup
  7. Gaffney B, Cunningham E P. Estimation of genetic trend in racing performance of thoroughbred horses. Nature 332, 722–724 (1988).
    pubmed: 3357536doi: 10.1038/332722a0google scholar: lookup
  8. Sharman P, Wilson A J. Genetic improvement of speed across distance categories in thoroughbred racehorses in Great Britain. Heredity (Edinb) 131, 79–85 (2023).
    pubmed: 37244934doi: 10.1038/s41437-023-00623-8google scholar: lookup
  9. Durward-Akhurst S A. Predicted genetic burden and frequency of phenotype-associated variants in the horse. Sci. Rep. 14, 8396 (2024).
    pubmed: 38600096pmc: 11006912doi: 10.1038/s41598-024-57872-8google scholar: lookup
  10. Leroy G, Vernet E, Pautet M B, Rognon X. An insight into population structure and gene flow within pure-bred cats. J Anim Breed Genet. 131, 53–60 (2014).
    pubmed: 25099789doi: 10.1111/jbg.12043google scholar: lookup
  11. Wright S. Coefficients of Inbreeding and relationship. Am. Nat. 56, 330–338 (1922).
    doi: 10.1086/279872google scholar: lookup
  12. Caballero A, Villanueva B, Druet T. On the estimation of inbreeding depression using different measures of inbreeding from molecular markers. Evol. Appl. 14, 416–428 (2021).
    pubmed: 33664785doi: 10.1111/eva.13126google scholar: lookup
  13. Rodríguez-Ramilo S T, Fernández J, Toro M A, Hernández D, Villanueva B. Genome-wide estimates of coancestry, inbreeding and effective population size in the Spanish Holstein population. PLoS One 10, e0124157 (2015).
    pubmed: 25880228pmc: 4399946doi: 10.1371/journal.pone.0124157google scholar: lookup
  14. Ferenčaković M. Estimates of autozygosity derived from runs of homozygosity: Empirical evidence from selected cattle populations. J. Anim. Breed. Genet. 130, 286–293 (2013).
    pubmed: 23855630doi: 10.1111/jbg.12012google scholar: lookup
  15. Ablondi M. Genetic diversity in the italian holstein dairy cattle based on pedigree and SNP data prior and after genomic selection. Front. Vet. Sci. 8, 773985 (2021).
    pubmed: 35097040doi: 10.3389/fvets.2021.773985google scholar: lookup
  16. Bower M A. Truth in the bones: Resolving the identity of the founding elite Thoroughbred racehorses. Archaeometry 54, 916–925 (2012).
    doi: 10.1111/j.1475-4754.2012.00666.xgoogle scholar: lookup
  17. Giontella A. Mitochondrial DNA survey reveals the lack of accuracy in Maremmano horse studbook records. Animals (Basel) 10, 839 (2020).
    pubmed: 32408648pmc: 7278429doi: 10.3390/ani10050839google scholar: lookup
  18. Browning S R, Browning B L. Identity by descent between distant relatives: Detection and applications. Annu. Rev. Genet. 46, 617–633 (2012).
    pubmed: 22994355doi: 10.1146/annurev-genet-110711-155534google scholar: lookup
  19. Thompson E A. Identity by descent: Variation in meiosis, across genomes, and in populations. Genetics 194, 301–326 (2013).
    pubmed: 23733848pmc: 3664843doi: 10.1534/genetics.112.148825google scholar: lookup
  20. Jagannathan V. Comprehensive characterization of horse genome variation by whole-genome sequencing of 88 horses. Anim. Genet. 50, 74–77 (2019).
    pubmed: 30525216doi: 10.1111/age.12753google scholar: lookup
  21. Tozaki T. Rare and common variant discovery by whole-genome sequencing of 101 Thoroughbred racehorses. Sci. Rep. 11, 16057 (2021).
    pubmed: 34362995pmc: 8346562doi: 10.1038/s41598-021-95669-1google scholar: lookup
  22. Durward-Akhurst S A. Genetic variation and the distribution of variant types in the horse. Front. Genet. 12, 758366 (2021).
    pubmed: 34925451pmc: 8676274doi: 10.3389/fgene.2021.758366google scholar: lookup
  23. Chen C. Genome-wide assessment of runs of homozygosity by whole-genome sequencing in diverse horse breeds worldwide. Genes (Basel) 14, 1211 (2023).
    pubmed: 37372391doi: 10.3390/genes14061211google scholar: lookup
  24. McGivney B A. Genomic inbreeding trends, influential sire lines and selection in the global Thoroughbred horse population. Sci. Rep. 10, 466 (2020).
    pubmed: 31949252pmc: 6965197doi: 10.1038/s41598-019-57389-5google scholar: lookup
  25. Kalbfleisch T S. Improved reference genome for the domestic horse increases assembly contiguity and composition. Commun. Biol. 1, 197 (2018).
    pubmed: 30456315pmc: 6240028doi: 10.1038/s42003-018-0199-zgoogle scholar: lookup
  26. Katsonis P, Wilhelm K, Williams A, Lichtarge O. Genome interpretation using in silico predictors of variant impact. Hum. Genet. 141, 1549–1577 (2022).
    pubmed: 35488922pmc: 9055222doi: 10.1007/s00439-022-02457-6google scholar: lookup
  27. Gunning A C. Assessing performance of pathogenicity predictors using clinically relevant variant datasets. J. Med. Genet. 58, 547–555 (2021).
    pubmed: 32843488doi: 10.1136/jmedgenet-2020-107003google scholar: lookup
  28. Nicholas F W. Online mendelian inheritance in animals (OMIA): A comparative knowledgebase of genetic disorders and other familial traits in non-laboratory animals. Nucl. Acids Res. 31, 275–277 (2003).
    pubmed: 12520001pmc: 165521doi: 10.1093/nar/gkg074google scholar: lookup
  29. Hill E W, McGivney B A, Gu J, Whiston R, Machugh D E. A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses. BMC Genom. 11, 552 (2010).
    doi: 10.1186/1471-2164-11-552google scholar: lookup
  30. Hill E W. 2012 MSTN genotype (g.66493737C/T) association with speed indices in Thoroughbred racehorses. J. Appl. Physiol. 112, 86–90 (1985).
    doi: 10.1152/japplphysiol.00793.2011google scholar: lookup
  31. Farries G. Genetic contributions to precocity traits in racing Thoroughbreds. Anim. Genet. 49, 193–204 (2018).
    pubmed: 29230835doi: 10.1111/age.12622google scholar: lookup
  32. Achilli A. Mitochondrial genomes from modern horses reveal the major haplogroups that underwent domestication. Proc. Natl. Acad. Sci. U. S. A. 109, 2449–2454 (2012).
    pubmed: 22308342pmc: 3289334doi: 10.1073/pnas.1111637109google scholar: lookup
  33. Hill E W. History and integrity of thoroughbred dam lines revealed in equine mtDNA variation. Anim. Genet. 33, 287–294 (2002).
    pubmed: 12139508doi: 10.1046/j.1365-2052.2002.00870.xgoogle scholar: lookup
  34. Bower M A. Thoroughbred racehorse mitochondrial DNA demonstrates closer than expected links between maternal genetic history and pedigree records. J. Anim. Breed. Genet. 130, 227–235 (2013).
    pubmed: 23679948doi: 10.1111/j.1439-0388.2012.01018.xgoogle scholar: lookup
  35. McQuillan R. Runs of homozygosity in European populations. Am. J. Hum. Genet. 83, 359–372 (2008).
    pubmed: 18760389pmc: 2556426doi: 10.1016/j.ajhg.2008.08.007google scholar: lookup
  36. Castle K. An update on inbreeding in the Australian Thoroughbred horse population. Proc. Assoc. Advmt. Anim. Breed. Genet. 17, 525–528 (2007).
  37. Curik I, Ferenčaković M, Sölkner J. Inbreeding and runs of homozygosity: A possible solution to an old problem. Livest. Sci. 166, 26–34 (2014).
    doi: 10.1016/j.livsci.2014.05.034google scholar: lookup
  38. Szpiech Z A. Long runs of homozygosity are enriched for deleterious variation. Am. J. Hum. Genet. 93, 90–102 (2013).
    pubmed: 23746547pmc: 3710769doi: 10.1016/j.ajhg.2013.05.003google scholar: lookup
  39. Mezzavilla M. Increased rate of deleterious variants in long runs of homozygosity of an inbred population from Qatar. Hum. Hered. 79, 14–19 (2015).
    pubmed: 25720536doi: 10.1159/000371387google scholar: lookup
  40. Pemberton T J, Szpiech Z A. Relationship between deleterious variation, genomic autozygosity, and disease risk: Insights from The 1000 genomes project. Am. J. Hum. Genet. 102, 658–675 (2018).
    pubmed: 29551419pmc: 5985279doi: 10.1016/j.ajhg.2018.02.013google scholar: lookup
  41. Makanjuola B O. Identification of unique ROH regions with unfavorable effects on production and fertility traits in Canadian Holsteins. Genet. Sel. Evol. 53, 68 (2021).
    pubmed: 34461820pmc: 8406729doi: 10.1186/s12711-021-00660-zgoogle scholar: lookup
  42. Hill E W, Stoffel M A, McGivney B A, MacHugh D E, Pemberton J M. Inbreeding depression and the probability of racing in the Thoroughbred horse. Proc. Biol. Sci. 289, 20220487 (2022).
    pubmed: 35765835pmc: 9240673
  43. Zhang Q, Guldbrandtsen B, Bosse M, Lund M S, Sahana G. Runs of homozygosity and distribution of functional variants in the cattle genome. BMC Genom. 16, 542 (2015).
    doi: 10.1186/s12864-015-1715-xgoogle scholar: lookup
  44. Sams A J, Boyko A R. Fine-scale resolution of runs of homozygosity reveal patterns of inbreeding and substantial overlap with recessive disease genotypes in domestic dogs. G3 (Bethesda) 9, 117–123 (2019).
    pubmed: 30429214doi: 10.1534/g3.118.200836google scholar: lookup
  45. Beeson S K, Mickelson J R, McCue M E. Exploration of fine-scale recombination rate variation in the domestic horse. Genome Res. 29, 1744–1752 (2019).
    pubmed: 31434677pmc: 6771410doi: 10.1101/gr.243311.118google scholar: lookup
  46. Lawson J M. Does inbreeding contribute to pregnancy loss in Thoroughbred horses?. Equine Vet. J. .
    doi: 10.1111/evj.14057pubmed: 38221707google scholar: lookup
  47. Meyermans R, Gorssen W, Buys N, Janssens S. How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species. BMC Genom. 21, 94 (2020).
    doi: 10.1186/s12864-020-6463-xgoogle scholar: lookup
  48. Duntsch L, Whibley A, Brekke P, Ewen J G, Santure A W. Genomic data of different resolutions reveal consistent inbreeding estimates but contrasting homozygosity landscapes for the threatened Aotearoa New Zealand hihi. Mol. Ecol. 30, 6006–6020 (2021).
    pubmed: 34242449doi: 10.1111/mec.16068google scholar: lookup
  49. Bellone R R. Warmblood fragile foal syndrome type 1 mutation (PLOD1 c.2032G>A) is not associated with catastrophic breakdown and has a low allele frequency in the Thoroughbred breed. Equine Vet. J. 52, 411–414 (2020).
    pubmed: 31502696doi: 10.1111/evj.13182google scholar: lookup
  50. Mahon G A T, Cunningham E P. Inbreeding and the inheritance of fertility in the thoroughbred mare. Livest. Prod. Sci. 9, 743–754 (1982).
    doi: 10.1016/0301-6226(82)90021-5google scholar: lookup
  51. Todd E T, Hamilton N A, Velie B D, Thomson P C. The effects of inbreeding on covering success, gestation length and foal sex ratio in Australian thoroughbred horses. BMC Genet. 21, 41 (2020).
    pubmed: 32268877pmc: 7140579doi: 10.1186/s12863-020-00847-1google scholar: lookup
  52. Castaneda C. Thoroughbred stallion fertility is significantly associated with FKBP6 genotype but not with inbreeding or the contribution of a leading sire. Anim. Genet. 52, 813–823 (2021).
    pubmed: 34610162doi: 10.1111/age.13142google scholar: lookup
  53. Todd E T. Founder-specific inbreeding depression affects racing performance in Thoroughbred horses. Sci. Rep. 8, 6167 (2018).
    pubmed: 29670190pmc: 5906619doi: 10.1038/s41598-018-24663-xgoogle scholar: lookup
  54. Hill E W, McGivney B A, MacHugh D E. Inbreeding depression and durability in the North American Thoroughbred horse. Anim. Genet. 54, 408–411 (2023).
    pubmed: 36843349doi: 10.1111/age.13309google scholar: lookup
  55. Cullen J N, Friedenberg S G. Whole animal genome sequencing: User-friendly, rapid, containerized pipelines for processing, variant discovery, and annotation of short-read whole genome sequencing data. G3 (Bethesda) 13, 117 (2023).
    doi: 10.1093/g3journal/jkad117google scholar: lookup
  56. Janečka J E. Horse Y chromosome assembly displays unique evolutionary features and putative stallion fertility genes. Nat. Commun. 9, 2945 (2018).
    pubmed: 30054462pmc: 6063916doi: 10.1038/s41467-018-05290-6google scholar: lookup
  57. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009).
    pubmed: 19451168pmc: 2705234doi: 10.1093/bioinformatics/btp324google scholar: lookup
  58. Schaefer R J. Developing a 670k genotyping array to tag ~2M SNPs across 24 horse breeds. BMC Genom. 18, 565 (2017).
    doi: 10.1186/s12864-017-3943-8google scholar: lookup
  59. Felkel S. The horse Y chromosome as an informative marker for tracing sire lines. Sci. Rep. 9, 6095 (2019).
    pubmed: 30988347pmc: 6465346doi: 10.1038/s41598-019-42640-wgoogle scholar: lookup
  60. Danecek P. The variant call format and VCFtools. Bioinformatics 27, 2156–2158 (2011).
    pubmed: 21653522pmc: 3137218doi: 10.1093/bioinformatics/btr330google scholar: lookup
  61. Purcell S. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am. J. Hum. Genet. 81, 559–575 (2007).
    pubmed: 17701901pmc: 1950838doi: 10.1086/519795google scholar: lookup
  62. Gutiérrez J P, Goyache F. A note on ENDOG: a computer program for analysing pedigree information. J Anim Breed Genet. 122, 172–176 (2005).
    pubmed: 16130468doi: 10.1111/j.1439-0388.2005.00512.xgoogle scholar: lookup
  63. Quinlan A R, Hall I M. BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
    pubmed: 20110278pmc: 2832824doi: 10.1093/bioinformatics/btq033google scholar: lookup
  64. Bandelt H J, Forster P, Röhl A. Median-joining networks for inferring intraspecific phylogenies. Mol. Biol. Evol. 16, 37–48 (1999).
    pubmed: 10331250doi: 10.1093/oxfordjournals.molbev.a026036google scholar: lookup
  65. Leigh J W, Bryan D. PopART: Full-feature software for haplotype network construction. Methods Ecol. Evol. 6, 1110–1116 (2015).
    doi: 10.1111/2041-210X.12410google scholar: lookup

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