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Home / Equine Research Bank / Sci Rep / A genome-wide scan for candidate lethal variants in Thorough...
Scientific reports2020; 10(1); 13153; doi: 10.1038/s41598-020-68946-8

A genome-wide scan for candidate lethal variants in Thoroughbred horses.

Abstract: Domestic animal populations are often characterised by high rates of inbreeding and low effective population sizes due to selective breeding practices. These practices can result in otherwise rare recessive deleterious alleles drifting to high frequencies, resulting in reduced fertility rates. This study aimed to identify potential recessive lethal haplotypes in the Thoroughbred horse breed, a closed population that has been selectively bred for racing performance. In this study, we identified a haplotype in the LY49B gene that shows strong evidence of being homozygous lethal, despite having high frequencies of heterozygotes in Thoroughbreds and other domestic horse breeds. Variant analysis of whole-genome sequence data identified two SNPs in the 3'UTR of the LY49B gene that may result in loss of function. Analysis of transcriptomic data from equine embryonic tissue revealed that LY49B is expressed in the trophoblast during placentation stage of development. These findings suggest that LY49B may have an essential, but as yet unknown function in the implantation stage of equine development. Further investigation of this region may allow for the development of a genetic test to improve fertility rates in horse populations. Identification of other lethal variants could assist in improving natural levels of fertility in horse populations.
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Publication Date: 2020-08-04 PubMed ID: 32753654PubMed Central: PMC7403398DOI: 10.1038/s41598-020-68946-8Google 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 investigates potential lethal genetic variations in Thoroughbred horses, specifically identifying a harmful variant in the LY49B gene. The study aims to develop better control over breeding practices by improving fertility rates.

Research Context and Objectives

  • It is common for domestic animal populations, like horse breeds, to exhibit high rates of inbreeding and have small effective population sizes due to selective breeding practices.
  • Sometimes these practices can lead to deleterious recessive alleles (forms of a gene that are typically not observed in the animal but can be harmful) drifting to high frequencies, thereby reducing fertility rates.
  • This study intended to uncover recessive lethal haplotypes (sets of DNA variations that tend to be inherited together) in Thoroughbred horse breed, which has been selectively bred closed population for racing performance.
  • The overall objective was to improve fertility rates in horse populations through this investigation.

Findings and Analysis

  • Research identified a haplotype in the LY49B gene that appears to be homozygous lethal, despite having high frequencies of heterozygotes (organisms with two different forms of a particular gene, one inherited from each parent) in Thoroughbreds and other domestic horse breeds.
  • To make this discovery, the researchers examined whole-genome sequence data and spotted two single-nucleotide polymorphisms (SNPs) in the un-translated region (3’UTR) of the LY49B gene that might result in a loss of function.
  • An analysis of transcriptomic (the study of RNA molecules) data collected from equine embryonic tissue revealed that LY49B is expressed in the trophoblast (the outer layer of a mammalian blastocyst, providing nutrients to the embryo and developing into a large part of the placenta) during the placentation stage of development.

Significance and Implications of the Study

  • These discoveries suggest that the LY49B gene may play an essential, yet previously unknown role in the implantation stage of equine development.
  • The findings of this research underline the necessity for further investigations in this region because they might contribute to the development of a genetic test that could be used to enhance fertility rates in horse populations.
  • The identification and understanding of other lethal variants, like the ones in the LY49B gene, could offer significant support in improving natural levels of fertility in horse populations.

Cite This Article

APA
Todd ET, Thomson PC, Hamilton NA, Ang RA, Lindgren G, Viklund Å, Eriksson S, Mikko S, Strand E, Velie BD. (2020). A genome-wide scan for candidate lethal variants in Thoroughbred horses. Sci Rep, 10(1), 13153. https://doi.org/10.1038/s41598-020-68946-8

Publication

Scientific reports
ISSN: 2045-2322
NlmUniqueID: 101563288
Country: England
Language: English
Volume: 10
Issue: 1
Pages: 13153
PII: 13153

Researcher Affiliations

Todd, Evelyn T
  • School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia. evelyn.todd@sydney.edu.au.
Thomson, Peter C
  • School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia.
Hamilton, Natasha A
  • Racing Australia Equine Genetics Research Centre, Sydney, Australia.
Ang, Rachel A
  • School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia.
Lindgren, Gabriella
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
  • Livestock Genetics, Department of Biosystems, KU Leuven, Leuven, Belgium.
Viklund, Åsa
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Eriksson, Susanne
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Mikko, Sofia
  • Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Strand, Eric
  • Department of Companion Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Oslo, Norway.
Velie, Brandon D
  • School of Life and Environmental Sciences, The University of Sydney, Sydney, Australia.

MeSH Terms

  • 3' Untranslated Regions
  • Animals
  • Breeding
  • Female
  • Fertility / genetics
  • Genome-Wide Association Study
  • Haplotypes
  • Horses / genetics
  • Male
  • NK Cell Lectin-Like Receptor Subfamily A / genetics
  • Polymorphism, Single Nucleotide

Conflict of Interest Statement

N.A.H. is supported by Racing Australia in the form of salary. All other authors declare that they have no competing interests.

References

This article includes 84 references
  1. Spencer TE. Early pregnancy: concepts, challenges, and potential solutions.. Anim. Front. 2013;3:48–55.
    doi: 10.2527/af.2013-0033google scholar: lookup
  2. White JK, Gerdin AK, Karp NA, Ryder E, Buljan M, Bussell JN, Salisbury J, Clare S, Ingham NJ, Podrini C, Houghton R, Estabel J, Bottomley JR, Melvin DG, Sunter D, Adams NC, Tannahill D, Logan DW, Macarthur DG, Flint J, Mahajan VB, Tsang SH, Smyth I, Watt FM, Skarnes WC, Dougan G, Adams DJ, Ramirez-Solis R, Bradley A, Steel KP. Genome-wide generation and systematic phenotyping of knockout mice reveals new roles for many genes.. Cell 2013 Jul 18;154(2):452-64.
    doi: 10.1016/j.cell.2013.06.022pmc: PMC3717207pubmed: 23870131google scholar: lookup
  3. Dickinson ME, Flenniken AM, Ji X, Teboul L, Wong MD, White JK, Meehan TF, Weninger WJ, Westerberg H, Adissu H, Baker CN, Bower L, Brown JM, Caddle LB, Chiani F, Clary D, Cleak J, Daly MJ, Denegre JM, Doe B, Dolan ME, Edie SM, Fuchs H, Gailus-Durner V, Galli A, Gambadoro A, Gallegos J, Guo S, Horner NR, Hsu CW, Johnson SJ, Kalaga S, Keith LC, Lanoue L, Lawson TN, Lek M, Mark M, Marschall S, Mason J, McElwee ML, Newbigging S, Nutter LM, Peterson KA, Ramirez-Solis R, Rowland DJ, Ryder E, Samocha KE, Seavitt JR, Selloum M, Szoke-Kovacs Z, Tamura M, Trainor AG, Tudose I, Wakana S, Warren J, Wendling O, West DB, Wong L, Yoshiki A, MacArthur DG, Tocchini-Valentini GP, Gao X, Flicek P, Bradley A, Skarnes WC, Justice MJ, Parkinson HE, Moore M, Wells S, Braun RE, Svenson KL, de Angelis MH, Herault Y, Mohun T, Mallon AM, Henkelman RM, Brown SD, Adams DJ, Lloyd KC, McKerlie C, Beaudet AL, Bućan M, Murray SA. High-throughput discovery of novel developmental phenotypes.. Nature 2016 Sep 22;537(7621):508-514.
    doi: 10.1038/nature19356pmc: PMC5295821pubmed: 27626380google scholar: lookup
  4. Gao Z, Waggoner D, Stephens M, Ober C, Przeworski M. An estimate of the average number of recessive lethal mutations carried by humans.. Genetics 2015 Apr;199(4):1243-54.
    doi: 10.1534/genetics.114.173351pmc: PMC4391560pubmed: 25697177google scholar: lookup
  5. Ballinger MA, Noor MAF. Are Lethal Alleles Too Abundant in Humans?. Trends Genet 2018 Feb;34(2):87-89.
    doi: 10.1016/j.tig.2017.12.013pubmed: 29290402google scholar: lookup
  6. Mukai T, Chigusa SI, Mettler LE, Crow JF. Mutation rate and dominance of genes affecting viability in Drosophila melanogaster.. Genetics 1972 Oct;72(2):335-55.
    pmc: PMC1212831pubmed: 4630587doi: 10.1093/genetics/72.2.335google scholar: lookup
  7. Sulem P, Helgason H, Oddson A, Stefansson H, Gudjonsson SA, Zink F, Hjartarson E, Sigurdsson GT, Jonasdottir A, Jonasdottir A, Sigurdsson A, Magnusson OT, Kong A, Helgason A, Holm H, Thorsteinsdottir U, Masson G, Gudbjartsson DF, Stefansson K. Identification of a large set of rare complete human knockouts.. Nat Genet 2015 May;47(5):448-52.
    doi: 10.1038/ng.3243pubmed: 25807282google scholar: lookup
  8. Curik I, Ferencakovic M, Solkner J. Inbreeding and runs of homozygosity: a possible solution to an old problem.. Livest. Sci. 2014;166:26–34.
    doi: 10.1016/j.livsci.2014.05.034google scholar: lookup
  9. Keller LF, Waller DM. Inbreeding effects in wild populations.. Trends Ecol. Evol. 2002;17:230–241.
    doi: 10.1016/S0169-5347(02)02489-8google scholar: lookup
  10. Charlesworth D, Willis JH. The genetics of inbreeding depression.. Nat Rev Genet 2009 Nov;10(11):783-96.
    doi: 10.1038/nrg2664pubmed: 19834483google scholar: lookup
  11. Hoff JL, Decker JE, Schnabel RD, Taylor JF. Candidate lethal haplotypes and causal mutations in Angus cattle.. BMC Genomics 2017 Oct 18;18(1):799.
    doi: 10.1186/s12864-017-4196-2pmc: PMC5648474pubmed: 29047335google scholar: lookup
  12. VanRaden PM, Olson KM, Null DJ, Hutchison JL. Harmful recessive effects on fertility detected by absence of homozygous haplotypes.. J Dairy Sci 2011 Dec;94(12):6153-61.
    doi: 10.3168/jds.2011-4624pubmed: 22118103google scholar: lookup
  13. Fasquelle C, Sartelet A, Li W, Dive M, Tamma N, Michaux C, Druet T, Huijbers IJ, Isacke CM, Coppieters W, Georges M, Charlier C. Balancing selection of a frame-shift mutation in the MRC2 gene accounts for the outbreak of the Crooked Tail Syndrome in Belgian Blue Cattle.. PLoS Genet 2009 Sep;5(9):e1000666.
    doi: 10.1371/journal.pgen.1000666pmc: PMC2739430pubmed: 19779552google scholar: lookup
  14. Zhang C, MacNeil MD, Kemp RA, Dyck MK, Plastow GS. Putative Loci Causing Early Embryonic Mortality in Duroc Swine.. Front Genet 2018;9:655.
    doi: 10.3389/fgene.2018.00655pmc: PMC6304751pubmed: 30619476google scholar: lookup
  15. Charlier C, Li W, Harland C, Littlejohn M, Coppieters W, Creagh F, Davis S, Druet T, Faux P, Guillaume F, Karim L, Keehan M, Kadri NK, Tamma N, Spelman R, Georges M. NGS-based reverse genetic screen for common embryonic lethal mutations compromising fertility in livestock.. Genome Res 2016 Oct;26(10):1333-1341.
    doi: 10.1101/gr.207076.116pmc: PMC5052051pubmed: 27646536google scholar: lookup
  16. Sonstegard TS, Cole JB, VanRaden PM, Van Tassell CP, Null DJ, Schroeder SG, Bickhart D, McClure MC. Identification of a nonsense mutation in CWC15 associated with decreased reproductive efficiency in Jersey cattle.. PLoS One 2013;8(1):e54872.
    doi: 10.1371/journal.pone.0054872pmc: PMC3551820pubmed: 23349982google scholar: lookup
  17. Derks MFL, Megens HJ, Bosse M, Lopes MS, Harlizius B, Groenen MAM. A systematic survey to identify lethal recessive variation in highly managed pig populations.. BMC Genomics 2017 Nov 9;18(1):858.
    doi: 10.1186/s12864-017-4278-1pmc: PMC5680825pubmed: 29121877google scholar: lookup
  18. Derks MFL, Gjuvsland AB, Bosse M, Lopes MS, van Son M, Harlizius B, Tan BF, Hamland H, Grindflek E, Groenen MAM, Megens HJ. Loss of function mutations in essential genes cause embryonic lethality in pigs.. PLoS Genet 2019 Mar;15(3):e1008055.
    doi: 10.1371/journal.pgen.1008055pmc: PMC6436757pubmed: 30875370google scholar: lookup
  19. Bourneuf E, Otz P, Pausch H, Jagannathan V, Michot P, Grohs C, Piton G, Ammermüller S, Deloche MC, Fritz S, Leclerc H, Péchoux C, Boukadiri A, Hozé C, Saintilan R, Créchet F, Mosca M, Segelke D, Guillaume F, Bouet S, Baur A, Vasilescu A, Genestout L, Thomas A, Allais-Bonnet A, Rocha D, Colle MA, Klopp C, Esquerré D, Wurmser C, Flisikowski K, Schwarzenbacher H, Burgstaller J, Brügmann M, Dietschi E, Rudolph N, Freick M, Barbey S, Fayolle G, Danchin-Burge C, Schibler L, Bed'Hom B, Hayes BJ, Daetwyler HD, Fries R, Boichard D, Pin D, Drögemüller C, Capitan A. Rapid Discovery of De Novo Deleterious Mutations in Cattle Enhances the Value of Livestock as Model Species.. Sci Rep 2017 Sep 13;7(1):11466.
    doi: 10.1038/s41598-017-11523-3pmc: PMC5597596pubmed: 28904385google scholar: lookup
  20. Schubert M, Jónsson H, Chang D, Der Sarkissian C, Ermini L, Ginolhac A, Albrechtsen A, Dupanloup I, Foucal A, Petersen B, Fumagalli M, Raghavan M, Seguin-Orlando A, Korneliussen TS, Velazquez AM, Stenderup J, Hoover CA, Rubin CJ, Alfarhan AH, Alquraishi SA, Al-Rasheid KA, MacHugh DE, Kalbfleisch T, MacLeod JN, Rubin EM, Sicheritz-Ponten T, Andersson L, Hofreiter M, Marques-Bonet T, Gilbert MT, Nielsen R, Excoffier L, Willerslev E, Shapiro B, Orlando L. Prehistoric genomes reveal the genetic foundation and cost of horse domestication.. Proc Natl Acad Sci U S A 2014 Dec 30;111(52):E5661-9.
    doi: 10.1073/pnas.1416991111pmc: PMC4284583pubmed: 25512547google scholar: lookup
  21. Cruz F, Vilà C, Webster MT. The legacy of domestication: accumulation of deleterious mutations in the dog genome.. Mol Biol Evol 2008 Nov;25(11):2331-6.
    doi: 10.1093/molbev/msn177pubmed: 18689870google scholar: lookup
  22. Marsden CD, Ortega-Del Vecchyo D, O'Brien DP, Taylor JF, Ramirez O, Vilà C, Marques-Bonet T, Schnabel RD, Wayne RK, Lohmueller KE. Bottlenecks and selective sweeps during domestication have increased deleterious genetic variation in dogs.. Proc Natl Acad Sci U S A 2016 Jan 5;113(1):152-7.
    doi: 10.1073/pnas.1512501113pmc: PMC4711855pubmed: 26699508google scholar: lookup
  23. Bosse M, Megens HJ, Derks MFL, de Cara ÁMR, Groenen MAM. Deleterious alleles in the context of domestication, inbreeding, and selection.. Evol Appl 2019 Jan;12(1):6-17.
    doi: 10.1111/eva.12691pmc: PMC6304688pubmed: 30622631google scholar: lookup
  24. Wright S. Evolution in Mendelian Populations.. Genetics 1931 Mar;16(2):97-159.
    pmc: PMC1201091pubmed: 17246615doi: 10.1093/genetics/16.2.97google scholar: lookup
  25. Husemann M, Zachos FE, Paxton RJ, Habel JC. Effective population size in ecology and evolution.. Heredity (Edinb) 2016 Oct;117(4):191-2.
    doi: 10.1038/hdy.2016.75pmc: PMC5026761pubmed: 27553454google scholar: lookup
  26. García-Dorado A. Understanding and predicting the fitness decline of shrunk populations: inbreeding, purging, mutation, and standard selection.. Genetics 2012 Apr;190(4):1461-76.
    doi: 10.1534/genetics.111.135541pmc: PMC3316656pubmed: 22298709google scholar: lookup
  27. Casas E, Kehrli ME Jr. A Review of Selected Genes with Known Effects on Performance and Health of Cattle.. Front Vet Sci 2016;3:113.
    doi: 10.3389/fvets.2016.00113pmc: PMC5156656pubmed: 28018909google scholar: lookup
  28. 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
  29. Petersen JL, Mickelson JR, Rendahl AK, Valberg SJ, Andersson LS, Axelsson J, Bailey E, Bannasch D, Binns MM, Borges AS, Brama P, da Câmara Machado A, Capomaccio S, Cappelli K, Cothran EG, Distl O, Fox-Clipsham L, Graves KT, Guérin G, Haase B, Hasegawa T, Hemmann K, Hill EW, Leeb T, Lindgren G, Lohi H, Lopes MS, McGivney BA, Mikko S, Orr N, Penedo MC, Piercy RJ, Raekallio M, Rieder S, Røed KH, Swinburne J, Tozaki T, Vaudin M, Wade CM, McCue ME. Genome-wide analysis reveals selection for important traits in domestic horse breeds.. PLoS Genet 2013;9(1):e1003211.
    doi: 10.1371/journal.pgen.1003211pmc: PMC3547851pubmed: 23349635google scholar: lookup
  30. Petersen JL, Mickelson JR, Cothran EG, Andersson LS, Axelsson J, Bailey E, Bannasch D, Binns MM, Borges AS, Brama P, da Câmara Machado A, Distl O, Felicetti M, Fox-Clipsham L, Graves KT, Guérin G, Haase B, Hasegawa T, Hemmann K, Hill EW, Leeb T, Lindgren G, Lohi H, Lopes MS, McGivney BA, Mikko S, Orr N, Penedo MC, Piercy RJ, Raekallio M, Rieder S, Røed KH, Silvestrelli M, Swinburne J, Tozaki T, Vaudin M, M Wade C, McCue ME. Genetic diversity in the modern horse illustrated from genome-wide SNP data.. PLoS One 2013;8(1):e54997.
    doi: 10.1371/journal.pone.0054997pmc: PMC3559798pubmed: 23383025google scholar: lookup
  31. Orlando L, Librado P. Origin and Evolution of Deleterious Mutations in Horses.. Genes (Basel) 2019 Aug 28;10(9).
    doi: 10.3390/genes10090649pmc: PMC6769756pubmed: 31466279google scholar: lookup
  32. Aurich C. Reproductive cycles of horses.. Anim Reprod Sci 2011 Apr;124(3-4):220-8.
    doi: 10.1016/j.anireprosci.2011.02.005pubmed: 21377299google scholar: lookup
  33. Allen WR, Wilsher S. Half a century of equine reproduction research and application: A veterinary tour de force.. Equine Vet J 2018 Jan;50(1):10-21.
    doi: 10.1111/evj.12762pubmed: 28971522google scholar: lookup
  34. . An Introduction to the General Stud Book.. .
  35. Hill EW, Gu J, McGivney BA, MacHugh DE. Targets of selection in the Thoroughbred genome contain exercise-relevant gene SNPs associated with elite racecourse performance.. Anim Genet 2010 Dec;41 Suppl 2:56-63.
    doi: 10.1111/j.1365-2052.2010.02104.xpubmed: 21070277google scholar: lookup
  36. Gu J, Orr N, Park SD, Katz LM, Sulimova G, MacHugh DE, Hill EW. A genome scan for positive selection in thoroughbred horses.. PLoS One 2009 Jun 2;4(6):e5767.
    doi: 10.1371/journal.pone.0005767pmc: PMC2685479pubmed: 19503617google scholar: lookup
  37. Cunningham EP, Dooley JJ, Splan RK, Bradley DG. Microsatellite diversity, pedigree relatedness and the contributions of founder lineages to thoroughbred horses.. Anim Genet 2001 Dec;32(6):360-4.
    doi: 10.1046/j.1365-2052.2001.00785.xpubmed: 11736806google scholar: lookup
  38. Todd ET, Ho SYW, Thomson PC, Ang RA, Velie BD, Hamilton NA. Founder-specific inbreeding depression affects racing performance in Thoroughbred horses.. Sci Rep 2018 Apr 18;8(1):6167.
    doi: 10.1038/s41598-018-24663-xpmc: PMC5906619pubmed: 29670190google scholar: lookup
  39. Corbin LJ, Blott SC, Swinburne JE, Vaudin M, Bishop SC, Woolliams JA. Linkage disequilibrium and historical effective population size in the Thoroughbred horse.. Anim Genet 2010 Dec;41 Suppl 2:8-15.
    doi: 10.1111/j.1365-2052.2010.02092.xpubmed: 21070270google scholar: lookup
  40. McGivney BA, Han H, Corduff LR, Katz LM, Tozaki T, MacHugh DE, Hill EW. Genomic inbreeding trends, influential sire lines and selection in the global Thoroughbred horse population.. Sci Rep 2020 Jan 16;10(1):466.
    doi: 10.1038/s41598-019-57389-5pmc: PMC6965197pubmed: 31949252google scholar: lookup
  41. Woolliams JA, Berg P, Dagnachew BS, Meuwissen TH. Genetic contributions and their optimization.. J Anim Breed Genet 2015 Apr;132(2):89-99.
    doi: 10.1111/jbg.12148pubmed: 25823835google scholar: lookup
  42. Ng PC, Henikoff S. SIFT: Predicting amino acid changes that affect protein function.. Nucleic Acids Res 2003 Jul 1;31(13):3812-4.
    doi: 10.1093/nar/gkg509pmc: PMC168916pubmed: 12824425google scholar: lookup
  43. Futas J, Horin P. Natural killer cell receptor genes in the family Equidae: not only Ly49.. PLoS One 2013;8(5):e64736.
    doi: 10.1371/journal.pone.0064736pmc: PMC3665701pubmed: 23724088google scholar: lookup
  44. Kelley J, Walter L, Trowsdale J. Comparative genomics of natural killer cell receptor gene clusters.. PLoS Genet 2005 Aug;1(2):129-39.
    doi: 10.1371/journal.pgen.0010027pmc: PMC1193534pubmed: 16132082google scholar: lookup
  45. Rahim MM, Tu MM, Mahmoud AB, Wight A, Abou-Samra E, Lima PD, Makrigiannis AP. Ly49 receptors: innate and adaptive immune paradigms.. Front Immunol 2014;5:145.
    doi: 10.3389/fimmu.2014.00145pmc: PMC3980100pubmed: 24765094google scholar: lookup
  46. Gays F, Aust JG, Reid DM, Falconer J, Toyama-Sorimachi N, Taylor PR, Brooks CG. Ly49B is expressed on multiple subpopulations of myeloid cells.. J Immunol 2006 Nov 1;177(9):5840-51.
    doi: 10.4049/jimmunol.177.9.5840pubmed: 17056508google scholar: lookup
  47. Hiby SE, Regan L, Lo W, Farrell L, Carrington M, Moffett A. Association of maternal killer-cell immunoglobulin-like receptors and parental HLA-C genotypes with recurrent miscarriage.. Hum Reprod 2008 Apr;23(4):972-6.
    doi: 10.1093/humrep/den011pubmed: 18263639google scholar: lookup
  48. Hiby SE, Apps R, Sharkey AM, Farrell LE, Gardner L, Mulder A, Claas FH, Walker JJ, Redman CW, Morgan L, Tower C, Regan L, Moore GE, Carrington M, Moffett A. Maternal activating KIRs protect against human reproductive failure mediated by fetal HLA-C2.. J Clin Invest 2010 Nov;120(11):4102-10.
    doi: 10.1172/JCI43998pmc: PMC2964995pubmed: 20972337google scholar: lookup
  49. Long W, Shi Z, Fan S, Liu L, Lu Y, Guo X, Rong C, Cui X, Ding H. Association of maternal KIR and fetal HLA-C genes with the risk of preeclampsia in the Chinese Han population.. Placenta 2015 Apr;36(4):433-7.
    doi: 10.1016/j.placenta.2014.05.008pubmed: 24951171google scholar: lookup
  50. Leon L, Felker AM, Kay VR, Tu MM, Makrigiannis AP, Croy BA. Ly49 knockdown in mice results in aberrant uterine crypt formation and impaired blastocyst implantation.. Placenta 2016 Mar;39:147-50.
    doi: 10.1016/j.placenta.2016.01.013pubmed: 26992687google scholar: lookup
  51. Lima PD, Tu MM, Rahim MM, Peng AR, Croy BA, Makrigiannis AP. Ly49 receptors activate angiogenic mouse DBA⁺ uterine natural killer cells.. Cell Mol Immunol 2014 Sep;11(5):467-76.
    doi: 10.1038/cmi.2014.44pmc: PMC4197209pubmed: 24954223google scholar: lookup
  52. Allen WR, Wilsher S. A review of implantation and early placentation in the mare.. Placenta 2009 Dec;30(12):1005-15.
    doi: 10.1016/j.placenta.2009.09.007pubmed: 19850339google scholar: lookup
  53. Noronha LE, Antczak DF. Maternal immune responses to trophoblast: the contribution of the horse to pregnancy immunology.. Am J Reprod Immunol 2010 Oct;64(4):231-44.
    doi: 10.1111/j.1600-0897.2010.00895.xpubmed: 20618178google scholar: lookup
  54. Donaldson WL, Oriol JG, Pelkaus CL, Antczak DF. Paternal and maternal major histocompatibility complex class I antigens are expressed co-dominantly by equine trophoblast.. Placenta 1994 Feb-Mar;15(2):123-35.
    doi: 10.1016/S0143-4004(05)80449-7pubmed: 8008728google scholar: lookup
  55. Bacon SJ, Ellis SA, Antczak DF. Control of expression of major histocompatibility complex genes in horse trophoblast.. Biol Reprod 2002 Jun;66(6):1612-20.
    doi: 10.1095/biolreprod66.6.1612pubmed: 12021038google scholar: lookup
  56. Steri M, Idda ML, Whalen MB, Orrù V. Genetic variants in mRNA untranslated regions.. Wiley Interdiscip Rev RNA 2018 Jul;9(4):e1474.
    doi: 10.1002/wrna.1474pmc: PMC6002891pubmed: 29582564google scholar: lookup
  57. Di Giammartino DC, Nishida K, Manley JL. Mechanisms and consequences of alternative polyadenylation.. Mol Cell 2011 Sep 16;43(6):853-66.
    doi: 10.1016/j.molcel.2011.08.017pmc: PMC3194005pubmed: 21925375google scholar: lookup
  58. Lewis SL, Holl HM, Streeter C, Posbergh C, Schanbacher BJ, Place NJ, Mallicote MF, Long MT, Brooks SA. Genomewide association study reveals a risk locus for equine metabolic syndrome in the Arabian horse.. J Anim Sci 2017 Mar;95(3):1071-1079.
    doi: 10.2527/jas.2016.1221pubmed: 28380523google scholar: lookup
  59. Dorairaj JJ, Salzman DW, Wall D, Rounds T, Preskill C, Sullivan CA, Lindner R, Curran C, Lezon-Geyda K, McVeigh T, Harris L, Newell J, Kerin MJ, Wood M, Miller N, Weidhaas JB. A germline mutation in the BRCA1 3'UTR predicts Stage IV breast cancer.. BMC Cancer 2014 Jun 10;14:421.
    doi: 10.1186/1471-2407-14-421pmc: PMC4059881pubmed: 24915755google scholar: lookup
  60. Kim KH, Abu Elneel K, Shin JW, Keum JW, Seong D, Kwak S, Lee R, Gusella JF, MacDonald ME, Seong IS, Lee JM. Full sequence of mutant huntingtin 3'-untranslated region and modulation of its gene regulatory activity by endogenous microRNA.. J Hum Genet 2019 Oct;64(10):995-1004.
    doi: 10.1038/s10038-019-0639-8pmc: PMC7324902pubmed: 31296921google scholar: lookup
  61. Hou J, An X, Song Y, Gao T, Lei Y, Cao B. Two Mutations in the Caprine MTHFR 3'UTR Regulated by MicroRNAs Are Associated with Milk Production Traits.. PLoS One 2015;10(7):e0133015.
    doi: 10.1371/journal.pone.0133015pmc: PMC4505847pubmed: 26186555google scholar: lookup
  62. Clop A, Marcq F, Takeda H, Pirottin D, Tordoir X, Bibé B, Bouix J, Caiment F, Elsen JM, Eychenne F, Larzul C, Laville E, Meish F, Milenkovic D, Tobin J, Charlier C, Georges M. A mutation creating a potential illegitimate microRNA target site in the myostatin gene affects muscularity in sheep.. Nat Genet 2006 Jul;38(7):813-8.
    doi: 10.1038/ng1810pubmed: 16751773google scholar: lookup
  63. Librado P, Gamba C, Gaunitz C, Der Sarkissian C, Pruvost M, Albrechtsen A, Fages A, Khan N, Schubert M, Jagannathan V, Serres-Armero A, Kuderna LFK, Povolotskaya IS, Seguin-Orlando A, Lepetz S, Neuditschko M, Thèves C, Alquraishi S, Alfarhan AH, Al-Rasheid K, Rieder S, Samashev Z, Francfort HP, Benecke N, Hofreiter M, Ludwig A, Keyser C, Marques-Bonet T, Ludes B, Crubézy E, Leeb T, Willerslev E, Orlando L. Ancient genomic changes associated with domestication of the horse.. Science 2017 Apr 28;356(6336):442-445.
    doi: 10.1126/science.aam5298pubmed: 28450643google scholar: lookup
  64. Fages A, Hanghøj K, Khan N, Gaunitz C, Seguin-Orlando A, Leonardi M, McCrory Constantz C, Gamba C, Al-Rasheid KAS, Albizuri S, Alfarhan AH, Allentoft M, Alquraishi S, Anthony D, Baimukhanov N, Barrett JH, Bayarsaikhan J, Benecke N, Bernáldez-Sánchez E, Berrocal-Rangel L, Biglari F, Boessenkool S, Boldgiv B, Brem G, Brown D, Burger J, Crubézy E, Daugnora L, Davoudi H, de Barros Damgaard P, de Los Ángeles de Chorro Y de Villa-Ceballos M, Deschler-Erb S, Detry C, Dill N, do Mar Oom M, Dohr A, Ellingvåg S, Erdenebaatar D, Fathi H, Felkel S, Fernández-Rodríguez C, García-Viñas E, Germonpré M, Granado JD, Hallsson JH, Hemmer H, Hofreiter M, Kasparov A, Khasanov M, Khazaeli R, Kosintsev P, Kristiansen K, Kubatbek T, Kuderna L, Kuznetsov P, Laleh H, Leonard JA, Lhuillier J, Liesau von Lettow-Vorbeck C, Logvin A, Lõugas L, Ludwig A, Luis C, Arruda AM, Marques-Bonet T, Matoso Silva R, Merz V, Mijiddorj E, Miller BK, Monchalov O, Mohaseb FA, Morales A, Nieto-Espinet A, Nistelberger H, Onar V, Pálsdóttir AH, Pitulko V, Pitskhelauri K, Pruvost M, Rajic Sikanjic P, Rapan Papeša A, Roslyakova N, Sardari A, Sauer E, Schafberg R, Scheu A, Schibler J, Schlumbaum A, Serrand N, Serres-Armero A, Shapiro B, Sheikhi Seno S, Shevnina I, Shidrang S, Southon J, Star B, Sykes N, Taheri K, Taylor W, Teegen WR, Trbojević Vukičević T, Trixl S, Tumen D, Undrakhbold S, Usmanova E, Vahdati A, Valenzuela-Lamas S, Viegas C, Wallner B, Weinstock J, Zaibert V, Clavel B, Lepetz S, Mashkour M, Helgason A, Stefánsson K, Barrey E, Willerslev E, Outram AK, Librado P, Orlando L. Tracking Five Millennia of Horse Management with Extensive Ancient Genome Time Series.. Cell 2019 May 30;177(6):1419-1435.e31.
    doi: 10.1016/j.cell.2019.03.049pmc: PMC6547883pubmed: 31056281google scholar: lookup
  65. Petersen JL, Mickelson JR, Cleary KD, McCue ME. The American Quarter Horse: population structure and relationship to the thoroughbred.. J Hered 2014 Mar-Apr;105(2):148-62.
    doi: 10.1093/jhered/est079pmc: PMC3920813pubmed: 24293614google scholar: lookup
  66. Beeson SK, Mickelson JR, McCue ME. Exploration of fine-scale recombination rate variation in the domestic horse.. Genome Res 2019 Oct;29(10):1744-1752.
    doi: 10.1101/gr.243311.118pmc: PMC6771410pubmed: 31434677google scholar: lookup
  67. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, Maller J, Sklar P, de Bakker PI, Daly MJ, Sham PC. PLINK: a tool set for whole-genome association and population-based linkage analyses.. Am J Hum Genet 2007 Sep;81(3):559-75.
    doi: 10.1086/519795pmc: PMC1950838pubmed: 17701901google scholar: lookup
  68. Storey J, Bass A, Dabney A, Robinson D. q-value estimation for false discovery rate control v. R package version 2.18.0.. (Accessed 6 September 2018).
  69. 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
  70. Ablondi M, Viklund Å, Lindgren G, Eriksson S, Mikko S. Signatures of selection in the genome of Swedish warmblood horses selected for sport performance.. BMC Genomics 2019 Sep 18;20(1):717.
    doi: 10.1186/s12864-019-6079-1pmc: PMC6751828pubmed: 31533613google scholar: lookup
  71. Velie BD, Shrestha M, Franҫois L, Schurink A, Tesfayonas YG, Stinckens A, Blott S, Ducro BJ, Mikko S, Thomas R, Swinburne JE, Sundqvist M, Eriksson S, Buys N, Lindgren G. Using an Inbred Horse Breed in a High Density Genome-Wide Scan for Genetic Risk Factors of Insect Bite Hypersensitivity (IBH).. PLoS One 2016;11(4):e0152966.
    doi: 10.1371/journal.pone.0152966pmc: PMC4829256pubmed: 27070818google scholar: lookup
  72. Petersen JL, Valberg SJ, Mickelson JR, McCue ME. Haplotype diversity in the equine myostatin gene with focus on variants associated with race distance propensity and muscle fiber type proportions.. Anim Genet 2014 Dec;45(6):827-35.
    doi: 10.1111/age.12205pmc: PMC4211974pubmed: 25160752google scholar: lookup
  73. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform.. Bioinformatics 2009 Jul 15;25(14):1754-60.
    doi: 10.1093/bioinformatics/btp324pmc: PMC2705234pubmed: 19451168google scholar: lookup
  74. Faust GG, Hall IM. SAMBLASTER: fast duplicate marking and structural variant read extraction.. Bioinformatics 2014 Sep 1;30(17):2503-5.
    doi: 10.1093/bioinformatics/btu314pmc: PMC4147885pubmed: 24812344google scholar: lookup
  75. McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo MA. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data.. Genome Res 2010 Sep;20(9):1297-303.
    doi: 10.1101/gr.107524.110pmc: PMC2928508pubmed: 20644199google scholar: lookup
  76. DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C, Philippakis AA, del Angel G, Rivas MA, Hanna M, McKenna A, Fennell TJ, Kernytsky AM, Sivachenko AY, Cibulskis K, Gabriel SB, Altshuler D, Daly MJ. A framework for variation discovery and genotyping using next-generation DNA sequencing data.. Nat Genet 2011 May;43(5):491-8.
    doi: 10.1038/ng.806pmc: PMC3083463pubmed: 21478889google scholar: lookup
  77. Lu S, Wang J, Chitsaz F, Derbyshire MK, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Marchler GH, Song JS, Thanki N, Yamashita RA, Yang M, Zhang D, Zheng C, Lanczycki CJ, Marchler-Bauer A. CDD/SPARCLE: the conserved domain database in 2020.. Nucleic Acids Res 2020 Jan 8;48(D1):D265-D268.
    doi: 10.1093/nar/gkz991pmc: PMC6943070pubmed: 31777944google scholar: lookup
  78. Iqbal K, Chitwood JL, Meyers-Brown GA, Roser JF, Ross PJ. RNA-seq transcriptome profiling of equine inner cell mass and trophectoderm.. Biol Reprod 2014 Mar;90(3):61.
    doi: 10.1095/biolreprod.113.113928pmc: PMC4435230pubmed: 24478389google scholar: lookup
  79. Bushnell B. BBMap short read aligner.. (Accessed 29 August 2019).
  80. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner.. Bioinformatics 2013 Jan 1;29(1):15-21.
    doi: 10.1093/bioinformatics/bts635pmc: PMC3530905pubmed: 23104886google scholar: lookup
  81. Liao Y, Smyth GK, Shi W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.. Bioinformatics 2014 Apr 1;30(7):923-30.
    doi: 10.1093/bioinformatics/btt656pubmed: 24227677google scholar: lookup
  82. Robinson MD, McCarthy DJ, Smyth GK. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data.. Bioinformatics 2010 Jan 1;26(1):139-40.
    doi: 10.1093/bioinformatics/btp616pmc: PMC2796818pubmed: 19910308google scholar: lookup
  83. Read JE, Cabrera-Sharp V, Offord V, Mirczuk SM, Allen SP, Fowkes RC, de Mestre AM. Dynamic changes in gene expression and signalling during trophoblast development in the horse.. Reproduction 2018 Oct 1;156(4):313-330.
    doi: 10.1530/REP-18-0270pmc: PMC6170800pubmed: 30306765google scholar: lookup
  84. Velie BD, Fegraeus KJ, Solé M, Rosengren MK, Røed KH, Ihler CF, Strand E, Lindgren G. A genome-wide association study for harness racing success in the Norwegian-Swedish coldblooded trotter reveals genes for learning and energy metabolism.. BMC Genet 2018 Aug 29;19(1):80.
    doi: 10.1186/s12863-018-0670-3pmc: PMC6114527pubmed: 30157760google scholar: lookup

Citations

This article has been cited 9 times.
  1. Laseca N, Cánovas Á, Valera M, Id-Lahoucine S, Perdomo-González DI, Fonseca PAS, Demyda-Peyrás S, Molina A. Genomic screening of allelic and genotypic transmission ratio distortion in horse. PLoS One 2023;18(8):e0289066.
    doi: 10.1371/journal.pone.0289066pubmed: 37556504google scholar: lookup
  2. Jaworska J, de Mestre AM, Wiśniewska J, Wagner B, Nowicki A, Kowalczyk-Zięba I, Wocławek-Potocka I. Populations of NK Cells and Regulatory T Cells in the Endometrium of Cycling Mares-A Preliminary Study. Animals (Basel) 2022 Nov 30;12(23).
    doi: 10.3390/ani12233373pubmed: 36496894google scholar: lookup
  3. Wen X, Luo S, Lv D, Jia C, Zhou X, Zhai Q, Xi L, Yang C. Variations in the fecal microbiota and their functions of Thoroughbred, Mongolian, and Hybrid horses. Front Vet Sci 2022;9:920080.
    doi: 10.3389/fvets.2022.920080pubmed: 35968025google scholar: lookup
  4. Reich P, Falker-Gieske C, Pook T, Tetens J. Development and validation of a horse reference panel for genotype imputation. Genet Sel Evol 2022 Jul 4;54(1):49.
    doi: 10.1186/s12711-022-00740-8pubmed: 35787788google scholar: lookup
  5. Laseca N, Anaya G, Peña Z, Pirosanto Y, Molina A, Demyda Peyrás S. Impaired Reproductive Function in Equines: From Genetics to Genomics. Animals (Basel) 2021 Feb 3;11(2).
    doi: 10.3390/ani11020393pubmed: 33546520google scholar: lookup
  6. Godoy JA, Bazzicalupo E, Casas-Marce M, Cruz F, Fernández J, Hasselgren M, Kleinman-Ruiz D, Lorenzo-Fernández L, Lucena-Perez M, Marmesat E, Martínez-Cruz B, Mayor-Fidalgo L, Pérez-Sorribes L, Soriano L. Genomic Insights Into the Origin, Decline and Recovery of the Once Critically Endangered Iberian Lynx. Mol Ecol 2025 Dec;34(23):e17719.
    doi: 10.1111/mec.17719pubmed: 40067056google scholar: lookup
  7. Rodrigues GRD, Cyrillo JNSG, Mota LFM, Schmidt PI, Valente JPS, Oliveira ES, Albuquerque LG, Brito LF, Mercadante MEZ. Effect of genomic regions harboring putative lethal haplotypes on reproductive performance in closed experimental selection lines of Nellore cattle. Sci Rep 2025 Feb 3;15(1):4113.
    doi: 10.1038/s41598-025-88501-7pubmed: 39900660google scholar: lookup
  8. Besnard F, Guintard A, Grohs C, Guzylack-Piriou L, Cano M, Escouflaire C, Hozé C, Leclerc H, Buronfosse T, Dutheil L, Jourdain J, Barbat A, Fritz S, Deloche MC, Remot A, Gaussères B, Clément A, Bouchier M, Contat E, Relun A, Plassard V, Rivière J, Péchoux C, Vilotte M, Eche C, Kuchly C, Charles M, Boulling A, Viard G, Minéry S, Barbey S, Birbes C, Danchin-Burge C, Launay F, Mattalia S, Allais-Bonnet A, Ravary B, Millemann Y, Guatteo R, Klopp C, Gaspin C, Iampietro C, Donnadieu C, Milan D, Arcangioli MA, Boussaha M, Foucras G, Boichard D, Capitan A. Massive detection of cryptic recessive genetic defects in dairy cattle mining millions of life histories. Genome Biol 2024 Sep 30;25(1):248.
    doi: 10.1186/s13059-024-03384-7pubmed: 39343954google scholar: lookup
  9. Schmidt PI, Mota LFM, Fonseca LFS, Dos Santos Silva DB, Frezarim GB, Arikawa LM, de Abreu Santos DJ, Magalhães AFB, Cole JB, Carvalheiro R, de Oliveira HN, Null DJ, VanRaden P, Ma L, de Albuquerque LG. Identification of candidate lethal haplotypes and genomic association with post-natal mortality and reproductive traits in Nellore cattle. Sci Rep 2023 Jun 27;13(1):10399.
    doi: 10.1038/s41598-023-37586-zpubmed: 37369809google scholar: lookup
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