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Home / Equine Research Bank / Sci Rep / Rare and common variant discovery by whole-genome sequencing...
Scientific reports2021; 11(1); 16057; doi: 10.1038/s41598-021-95669-1

Rare and common variant discovery by whole-genome sequencing of 101 Thoroughbred racehorses.

Abstract: The Thoroughbred breed was formed by crossing Oriental horse breeds and British native horses and is currently used in horseracing worldwide. In this study, we constructed a single-nucleotide variant (SNV) database using data from 101 Thoroughbred racehorses. Whole genome sequencing (WGS) revealed 11,570,312 and 602,756 SNVs in autosomal (1-31) and X chromosomes, respectively, yielding a total of 12,173,068 SNVs. About 6.9% of identified SNVs were rare variants observed only in one allele in 101 horses. The number of SNVs detected in individual horses ranged from 4.8 to 5.3 million. Individual horses had a maximum of 25,554 rare variants; several of these were functional variants, such as non-synonymous substitutions, start-gained, start-lost, stop-gained, and stop-lost variants. Therefore, these rare variants may affect differences in traits and phenotypes among individuals. When observing the distribution of rare variants among horses, one breeding stallion had a smaller number of rare variants compared to other horses, suggesting that the frequency of rare variants in the Japanese Thoroughbred population increases through breeding. In addition, our variant database may provide useful basic information for industrial applications, such as the detection of genetically modified racehorses in gene-doping control and pedigree-registration of racehorses using SNVs as markers.
© 2021. The Author(s).
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Publication Date: 2021-08-06 PubMed ID: 34362995PubMed Central: PMC8346562DOI: 10.1038/s41598-021-95669-1Google 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 research article focuses on the discovery of rare and common genetic variations in Thoroughbred racehorses using whole-genome sequencing. It indicates that these genetic differences could influence variations in traits and phenotypes among individual horses.

Primary Objectives and Methods

  • The primary aim of the research was to construct a single-nucleotide variant (SNV) database using data from 101 Thoroughbred racehorses. SNVs are small scale genetic alterations, and their study provides valuable insights into individual genetic differences among organisms.
  • The researchers used whole-genome sequencing (WGS), a process that allows the detailed mapping of every gene in an organism’s genome, to detect these SNVs.

Key Findings

  • From the 101 Thoroughbred racehorses, a total of 12,173,068 SNVs were identified. Of these, about 6.9% were rare variants, which only appeared in one allele in the 101 horses.
  • The number of SNVs detected in individual horses ranged from approximately 4.8 to 5.3 million.
  • Each horse had a maximum of 25,554 rare variants. Some of these were functional variants, such as non-synonymous substitutions, start-gained, start-lost, stop-gained, and stop-lost variants. These could potentially affect the differences in traits and phenotypes among the horses.
  • The researchers found that one breeding stallion had a smaller number of rare variants compared to other horses. This suggests that the frequency of rare variants in the Japanese Thoroughbred population might increase through breeding.

Implications and Applications

  • The SNV database created in this study could prove vital for a range of applications in the equine industry. It could be used for the detection of genetically modified racehorses in gene-doping control, which is the practice of using genetic modification to enhance the performance of horses.
  • In addition, it could be useful for pedigree-registration of racehorses, using SNVs as markers. This would allow for the precise tracing of a horse’s lineage, which is valuable for breeders and racehorse owners.

Cite This Article

APA
Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Kusano K, Nagata SI. (2021). Rare and common variant discovery by whole-genome sequencing of 101 Thoroughbred racehorses. Sci Rep, 11(1), 16057. https://doi.org/10.1038/s41598-021-95669-1

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 11
Issue: 1
Pages: 16057
PII: 16057

Researcher Affiliations

Tozaki, Teruaki
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan. ttozaki@lrc.or.jp.
  • Equine Department, Japan Racing Association, 6-11-1, Roppongi, Minato, Tokyo, 106-8401, Japan. ttozaki@lrc.or.jp.
Ohnuma, Aoi
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.
Kikuchi, Mio
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.
Ishige, Taichiro
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.
Kakoi, Hironaga
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.
Hirota, Kei-Ichi
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.
Kusano, Kanichi
  • Equine Department, Japan Racing Association, 6-11-1, Roppongi, Minato, Tokyo, 106-8401, Japan.
Nagata, Shun-Ichi
  • Genetic Analysis Department, Laboratory of Racing Chemistry, 1731-2, Tsurutamachi, Utsunomiya, Tochigi, 320-0851, Japan.

MeSH Terms

  • Animals
  • Breeding
  • Female
  • Genotype
  • Horses / genetics
  • Horses / physiology
  • Male
  • Pedigree
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Whole Genome Sequencing / methods

Conflict of Interest Statement

The authors declare no competing interests.

References

This article includes 39 references
  1. Bower MA, Campana MG, Whitten M, Edwards CJ, Jones H, Barrett E, Cassidy R, Nisbet RE, Hill EW, Howe CJ, Binns M. The cosmopolitan maternal heritage of the Thoroughbred racehorse breed shows a significant contribution from British and Irish native mares.. Biol Lett 2011 Apr 23;7(2):316-20.
    doi: 10.1098/rsbl.2010.0800pmc: PMC3061175pubmed: 20926431google scholar: lookup
  2. International Stud Book Committee (ISBC), Statistical Information Booklet 2018. https://www.internationalstudbook.com/resources/. Accessed 29 July 2021 (2018).
  3. Tozaki T, Kikuchi M, Kakoi H, Hirota KI, Nagata SI. A genome-wide association study for body weight in Japanese Thoroughbred racehorses clarifies candidate regions on chromosomes 3, 9, 15, and 18.. J Equine Sci 2017;28(4):127-134.
    doi: 10.1294/jes.28.127pmc: PMC5735309pubmed: 29270069google scholar: lookup
  4. Hill EW, McGivney BA, Gu J, Whiston R, Machugh DE. 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 Genomics 2010 Oct 11;11:552.
    doi: 10.1186/1471-2164-11-552pmc: PMC3091701pubmed: 20932346google scholar: lookup
  5. Tozaki T, Miyake T, Kakoi H, Gawahara H, Sugita S, Hasegawa T, Ishida N, Hirota K, Nakano Y. A genome-wide association study for racing performances in Thoroughbreds clarifies a candidate region near the MSTN gene.. Anim Genet 2010 Dec;41 Suppl 2:28-35.
    doi: 10.1111/j.1365-2052.2010.02095.xpubmed: 21070273google scholar: lookup
  6. Gu J, MacHugh DE, McGivney BA, Park SD, Katz LM, Hill EW. Association of sequence variants in CKM (creatine kinase, muscle) and COX4I2 (cytochrome c oxidase, subunit 4, isoform 2) genes with racing performance in Thoroughbred horses.. Equine Vet J Suppl 2010 Nov;(38):569-75.
    doi: 10.1111/j.2042-3306.2010.00181.xpubmed: 21059062google scholar: lookup
  7. Fawcett JA, Sato F, Sakamoto T, Iwasaki WM, Tozaki T, Innan H. Genome-wide SNP analysis of Japanese Thoroughbred racehorses.. PLoS One 2019;14(7):e0218407.
    doi: 10.1371/journal.pone.0218407pmc: PMC6655603pubmed: 31339891google scholar: lookup
  8. Shin DH, Lee JW, Park JE, Choi IY, Oh HS, Kim HJ, Kim H. Multiple Genes Related to Muscle Identified through a Joint Analysis of a Two-stage Genome-wide Association Study for Racing Performance of 1,156 Thoroughbreds.. Asian-Australas J Anim Sci 2015 Jun;28(6):771-81.
    doi: 10.5713/ajas.14.0008pmc: PMC4412973pubmed: 25925054google scholar: lookup
  9. Wong JK, Wan TS. Doping control analyses in horseracing: a clinician's guide.. Vet J 2014 Apr;200(1):8-16.
    doi: 10.1016/j.tvjl.2014.01.006pubmed: 24485918google scholar: lookup
  10. Wilkin T, Baoutina A, Hamilton N. Equine performance genes and the future of doping in horseracing.. Drug Test Anal 2017 Sep;9(9):1456-1471.
    doi: 10.1002/dta.2198pubmed: 28349656google scholar: lookup
  11. Tozaki T, Gamo S, Takasu M, Kikuchi M, Kakoi H, Hirota KI, Kusano K, Nagata SI. Digital PCR detection of plasmid DNA administered to the skeletal muscle of a microminipig: a model case study for gene doping detection.. BMC Res Notes 2018 Oct 10;11(1):708.
    doi: 10.1186/s13104-018-3815-6pmc: PMC6180624pubmed: 30309394google scholar: lookup
  12. Tozaki T, Karasawa K, Minamijima Y, Ishii H, Kikuchi M, Kakoi H, Hirota KI, Kusano K, Nagata SI. Detection of phosphorothioated (PS) oligonucleotides in horse plasma using a product ion (m/z 94.9362) derived from the PS moiety for doping control.. BMC Res Notes 2018 Oct 29;11(1):770.
    doi: 10.1186/s13104-018-3885-5pmc: PMC6206624pubmed: 30373660google scholar: lookup
  13. Tozaki T, Ohnuma A, Takasu M, Kikuchi M, Kakoi H, Hirota KI, Kusano K, Nagata SI. Droplet Digital PCR Detection of the Erythropoietin Transgene from Horse Plasma and Urine for Gene-Doping Control.. Genes (Basel) 2019 Mar 21;10(3).
    doi: 10.3390/genes10030243pmc: PMC6471249pubmed: 30901981google scholar: lookup
  14. Haughan J, Jiang Z, Stefanovski D, Moss KL, Ortved KF, Robinson MA. Detection of intra-articular gene therapy in horses using quantitative real time PCR in synovial fluid and plasma.. Drug Test Anal 2020 Jun;12(6):743-751.
    doi: 10.1002/dta.2785pubmed: 32133745google scholar: lookup
  15. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Kusano K, Nagata SI. Microfluidic Quantitative PCR Detection of 12 Transgenes from Horse Plasma for Gene Doping Control.. Genes (Basel) 2020 Apr 23;11(4).
    doi: 10.3390/genes11040457pmc: PMC7230449pubmed: 32340130google scholar: lookup
  16. Cheung HW, Wong KS, Lin VYC, Wan TSM, Ho ENM. A duplex qPCR assay for human erythropoietin (EPO) transgene to control gene doping in horses.. Drug Test Anal 2021 Jan;13(1):113-121.
    doi: 10.1002/dta.2907pubmed: 32762114google scholar: lookup
  17. Al Abri MA, Holl HM, Kalla SE, Sutter NB, Brooks SA. Whole genome detection of sequence and structural polymorphism in six diverse horses.. PLoS One 2020;15(4):e0230899.
    doi: 10.1371/journal.pone.0230899pmc: PMC7144971pubmed: 32271776google scholar: lookup
  18. Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lear TL, Adelson DL, Bailey E, Bellone RR, Blöcker H, Distl O, Edgar RC, Garber M, Leeb T, Mauceli E, MacLeod JN, Penedo MC, Raison JM, Sharpe T, Vogel J, Andersson L, Antczak DF, Biagi T, Binns MM, Chowdhary BP, Coleman SJ, Della Valle G, Fryc S, Guérin G, Hasegawa T, Hill EW, Jurka J, Kiialainen A, Lindgren G, Liu J, Magnani E, Mickelson JR, Murray J, Nergadze SG, Onofrio R, Pedroni S, Piras MF, Raudsepp T, Rocchi M, Røed KH, Ryder OA, Searle S, Skow L, Swinburne JE, Syvänen AC, Tozaki T, Valberg SJ, Vaudin M, White JR, Zody MC, Lander ES, Lindblad-Toh K. Genome sequence, comparative analysis, and population genetics of the domestic horse.. Science 2009 Nov 6;326(5954):865-7.
    doi: 10.1126/science.1178158pmc: PMC3785132pubmed: 19892987google scholar: lookup
  19. Kalbfleisch TS, Rice ES, DePriest MS Jr, Walenz BP, Hestand MS, Vermeesch JR, O Connell BL, Fiddes IT, Vershinina AO, Saremi NF, Petersen JL, Finno CJ, Bellone RR, McCue ME, Brooks SA, Bailey E, Orlando L, Green RE, Miller DC, Antczak DF, MacLeod JN. Improved reference genome for the domestic horse increases assembly contiguity and composition.. Commun Biol 2018;1:197.
    doi: 10.1038/s42003-018-0199-zpmc: PMC6240028pubmed: 30456315google scholar: lookup
  20. Raudsepp T, Finno CJ, Bellone RR, Petersen JL. Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era.. Anim Genet 2019 Dec;50(6):569-597.
    doi: 10.1111/age.12857pmc: PMC6825885pubmed: 31568563google scholar: lookup
  21. Jagannathan V, Gerber V, Rieder S, Tetens J, Thaller G, Drögemüller C, Leeb T. Comprehensive characterization of horse genome variation by whole-genome sequencing of 88 horses.. Anim Genet 2019 Feb;50(1):74-77.
    doi: 10.1111/age.12753pubmed: 30525216google scholar: lookup
  22. Park L. Relative mutation rates of each nucleotide for another estimated from allele frequency spectra at human gene loci.. Genet Res (Camb) 2009 Aug;91(4):293-303.
    doi: 10.1017/S0016672309990164pubmed: 19640324google scholar: lookup
  23. Lyons DM, Lauring AS. Evidence for the Selective Basis of Transition-to-Transversion Substitution Bias in Two RNA Viruses.. Mol Biol Evol 2017 Dec 1;34(12):3205-3215.
    doi: 10.1093/molbev/msx251pmc: PMC5850290pubmed: 29029187google scholar: lookup
  24. Litterman AJ, Kageyama R, Le Tonqueze O, Zhao W, Gagnon JD, Goodarzi H, Erle DJ, Ansel KM. A massively parallel 3' UTR reporter assay reveals relationships between nucleotide content, sequence conservation, and mRNA destabilization.. Genome Res 2019 Jun;29(6):896-906.
    doi: 10.1101/gr.242552.118pmc: PMC6581050pubmed: 31152051google scholar: lookup
  25. Dassi E, Zuccotti P, Leo S, Provenzani A, Assfalg M, D'Onofrio M, Riva P, Quattrone A. Hyper conserved elements in vertebrate mRNA 3'-UTRs reveal a translational network of RNA-binding proteins controlled by HuR.. Nucleic Acids Res 2013 Mar 1;41(5):3201-16.
    doi: 10.1093/nar/gkt017pmc: PMC3597683pubmed: 23376935google scholar: lookup
  26. Viļuma A, Mikko S, Hahn D, Skow L, Andersson G, Bergström TF. Genomic structure of the horse major histocompatibility complex class II region resolved using PacBio long-read sequencing technology.. Sci Rep 2017 Mar 31;7:45518.
    doi: 10.1038/srep45518pmc: PMC5374520pubmed: 28361880google scholar: lookup
  27. Klumplerova M, Splichalova P, Oppelt J, Futas J, Kohutova A, Musilova P, Kubickova S, Vodicka R, Orlando L, Horin P. Genetic diversity, evolution and selection in the major histocompatibility complex DRB and DQB loci in the family Equidae.. BMC Genomics 2020 Sep 30;21(1):677.
    doi: 10.1186/s12864-020-07089-6pmc: PMC7525986pubmed: 32998693google scholar: lookup
  28. Moore CB, Wallace JR, Wolfe DJ, Frase AT, Pendergrass SA, Weiss KM, Ritchie MD. Low frequency variants, collapsed based on biological knowledge, uncover complexity of population stratification in 1000 genomes project data.. PLoS Genet 2013;9(12):e1003959.
    pmc: PMC3873241pubmed: 24385916doi: 10.1371/journal.pgen.1003959google scholar: lookup
  29. Ameur A, Dahlberg J, Olason P, Vezzi F, Karlsson R, Martin M, Viklund J, Kähäri AK, Lundin P, Che H, Thutkawkorapin J, Eisfeldt J, Lampa S, Dahlberg M, Hagberg J, Jareborg N, Liljedahl U, Jonasson I, Johansson Å, Feuk L, Lundeberg J, Syvänen AC, Lundin S, Nilsson D, Nystedt B, Magnusson PK, Gyllensten U. SweGen: a whole-genome data resource of genetic variability in a cross-section of the Swedish population.. Eur J Hum Genet 2017 Nov;25(11):1253-1260.
    doi: 10.1038/ejhg.2017.130pmc: PMC5765326pubmed: 28832569google scholar: lookup
  30. Bomba L, Walter K, Soranzo N. The impact of rare and low-frequency genetic variants in common disease.. Genome Biol 2017 Apr 27;18(1):77.
    doi: 10.1186/s13059-017-1212-4pmc: PMC5408830pubmed: 28449691google scholar: lookup
  31. Hirota K, Kakoi H, Gawahara H, Hasegawa T, Tozaki T. Construction and validation of parentage testing for thoroughbred horses by 53 single nucleotide polymorphisms.. J Vet Med Sci 2010 Jun;72(6):719-26.
    doi: 10.1292/jvms.09-0486pubmed: 20124759google scholar: lookup
  32. Eichler EE, Flint J, Gibson G, Kong A, Leal SM, Moore JH, Nadeau JH. Missing heritability and strategies for finding the underlying causes of complex disease.. Nat Rev Genet 2010 Jun;11(6):446-50.
    doi: 10.1038/nrg2809pmc: PMC2942068pubmed: 20479774google scholar: lookup
  33. Bower MA, McGivney BA, Campana MG, Gu J, Andersson LS, Barrett E, Davis CR, Mikko S, Stock F, Voronkova V, Bradley DG, Fahey AG, Lindgren G, MacHugh DE, Sulimova G, Hill EW. The genetic origin and history of speed in the Thoroughbred racehorse.. Nat Commun 2012 Jan 24;3:643.
    doi: 10.1038/ncomms1644pubmed: 22273681google scholar: lookup
  34. Guo J, Zhu X, Badawy S, Ihsan A, Liu Z, Xie C, Wang X. Metabolism and Mechanism of Human Cytochrome P450 Enzyme 1A2.. Curr Drug Metab 2021;22(1):40-49.
    doi: 10.2174/1389200221999210101233135pubmed: 33397254google scholar: lookup
  35. Scarth JP, Teale P, Kuuranne T. Drug metabolism in the horse: a review.. Drug Test Anal 2011 Jan;3(1):19-53.
    doi: 10.1002/dta.174pubmed: 20967889google scholar: lookup
  36. Rubinacci S, Delaneau O, Marchini J. Genotype imputation using the Positional Burrows Wheeler Transform.. PLoS Genet 2020 Nov;16(11):e1009049.
    pmc: PMC7704051pubmed: 33196638doi: 10.1371/journal.pgen.1009049google scholar: lookup
  37. Lippold S, Matzke NJ, Reissmann M, Hofreiter M. Whole mitochondrial genome sequencing of domestic horses reveals incorporation of extensive wild horse diversity during domestication.. BMC Evol Biol 2011 Nov 14;11:328.
    doi: 10.1186/1471-2148-11-328pmc: PMC3247663pubmed: 22082251google scholar: lookup
  38. Hill EW, Bradley DG, Al-Barody M, Ertugrul O, Splan RK, Zakharov I, Cunningham EP. History and integrity of thoroughbred dam lines revealed in equine mtDNA variation.. Anim Genet 2002 Aug;33(4):287-94.
    doi: 10.1046/j.1365-2052.2002.00870.xpubmed: 12139508google scholar: lookup
  39. Bower MA, Whitten M, Nisbet RE, Spencer M, Dominy KM, Murphy AM, Cassidy R, Barrett E, Hill EW, Binns M. Thoroughbred racehorse mitochondrial DNA demonstrates closer than expected links between maternal genetic history and pedigree records.. J Anim Breed Genet 2013 Jun;130(3):227-35.
    doi: 10.1111/j.1439-0388.2012.01018.xpubmed: 23679948google scholar: lookup

Citations

This article has been cited 5 times.
  1. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Takahashi Y, Nagata SI. Short Insertion and Deletion Discoveries via Whole-Genome Sequencing of 101 Thoroughbred Racehorses.. Genes (Basel) 2023 Mar 3;14(3).
    doi: 10.3390/genes14030638pubmed: 36980910google scholar: lookup
  2. Yokomori T, Ohnuma A, Tozaki T, Segawa T, Itou T. Identification of Personality-Related Candidate Genes in Thoroughbred Racehorses Using a Bioinformatics-Based Approach Involving Functionally Annotated Human Genes.. Animals (Basel) 2023 Feb 20;13(4).
    doi: 10.3390/ani13040769pubmed: 36830556google scholar: lookup
  3. Suminda GGD, Ghosh M, Son YO. The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research.. Life (Basel) 2022 Nov 15;12(11).
    doi: 10.3390/life12111893pubmed: 36431028google scholar: lookup
  4. Tozaki T, Ohnuma A, Nakamura K, Hano K, Takasu M, Takahashi Y, Tamura N, Sato F, Shimizu K, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Hamilton NA, Nagata SI. Detection of Indiscriminate Genetic Manipulation in Thoroughbred Racehorses by Targeted Resequencing for Gene-Doping Control.. Genes (Basel) 2022 Sep 4;13(9).
    doi: 10.3390/genes13091589pubmed: 36140757google scholar: lookup
  5. Tozaki T, Ohnuma A, Kikuchi M, Ishige T, Kakoi H, Hirota KI, Kusano K, Nagata SI. Design and storage stability of reference materials for microfluidic quantitative PCR-based equine gene doping tests.. J Equine Sci 2021 Dec;32(4):125-134.
    doi: 10.1294/jes.32.125pubmed: 35023990google scholar: lookup
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