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BMC genomics2024; 25(1); 772; doi: 10.1186/s12864-024-10682-8

Genetic diversity and signatures of selection in Icelandic horses and Exmoor ponies.

Abstract: The Icelandic horse and Exmoor pony are ancient, native breeds, adapted to harsh environmental conditions and they have both undergone severe historic bottlenecks. However, in modern days, the selection pressures on these breeds differ substantially. The aim of this study was to assess genetic diversity in both breeds through expected (HE) and observed heterozygosity (HO) and effective population size (Ne). Furthermore, we aimed to identify runs of homozygosity (ROH) to estimate and compare genomic inbreeding and signatures of selection in the breeds. Results: HO was estimated at 0.34 and 0.33 in the Icelandic horse and Exmoor pony, respectively, aligning closely with HE of 0.34 for both breeds. Based on genomic data, the Ne for the last generation was calculated to be 125 individuals for Icelandic horses and 42 for Exmoor ponies. Genomic inbreeding coefficient (FROH) ranged from 0.08 to 0.20 for the Icelandic horse and 0.12 to 0.27 for the Exmoor pony, with the majority of inbreeding attributed to short ROHs in both breeds. Several ROH islands associated with performance were identified in the Icelandic horse, featuring target genes such as DMRT3, DOCK8, EDNRB, SLAIN1, and NEURL1. Shared ROH islands between both breeds were linked to metabolic processes (FOXO1), body size, and the immune system (CYRIB), while private ROH islands in Exmoor ponies were associated with coat colours (ASIP, TBX3, OCA2), immune system (LYG1, LYG2), and fertility (TEX14, SPO11, ADAM20). Conclusions: Evaluations of genetic diversity and inbreeding reveal insights into the evolutionary trajectories of both breeds, highlighting the consequences of population bottlenecks. While the genetic diversity in the Icelandic horse is acceptable, a critically low genetic diversity was estimated for the Exmoor pony, which requires further validation. Identified signatures of selection highlight the differences in the use of the two breeds as well as their adaptive trait similarities. The results provide insight into genomic regions under selection pressure in a gaited performance horse breed and various adaptive traits in small-sized native horse breeds. This understanding contributes to preserving genetic diversity and population health in these equine populations.
© 2024. The Author(s).
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Publication Date: 2024-08-08 PubMed ID: 39118059PubMed Central: PMC11308356DOI: 10.1186/s12864-024-10682-8Google 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 article is about a study examining genetic diversity and the effect of selection pressures in the Icelandic horse and Exmoor pony breeds, two ancient types of horses known for their resilience to harsh environments but which have also experienced significant genetic bottlenecks.

Research Goal and Methodology

  • The overall goal of the research was to study the genetic diversity in the Icelandic horse and the Exmoor pony, two distinct breeds that have experienced significant genetic ‘bottlenecks’. This refers to a sharp reduction in population size leading to genetic diversity loss.
  • The researchers looked at the expected and observed heterozygosity – measures of genetic diversity – and the effective population size (Ne). They also examined runs of homozygosity (ROH), sequences where both of a pair of chromosomes are identical, to compare genomic inbreeding and signatures of selection – the impact of evolutionary processes – in the breeds.

Results of the Research

  • According to the results, the expected heterozygosity was estimated at 0.34 and 0.33 in the Icelandic horse and Exmoor pony, respectively, aligning closely with the observed heterozygosity of 0.34 for both breeds. This suggests comparable levels of genetic diversity within both breeds.
  • The effective population size for the last generation was calculated to be 125 individuals for Icelandic horses and 42 for Exmoor ponies, based on genomic data. This suggests that the Icelandic horses have a larger pool of breeding individuals than the Exmoor ponies.
  • The genomic inbreeding coefficient, a measure of the degree to which individuals within a population are related, varied from 0.08 to 0.20 for the Icelandic horse and 0.12 to 0.27 for the Exmoor pony. This suggests more inbreeding among Exmoor ponies than Icelandic horses.

Unique Findings and Conclusion

  • Several ROH islands associated with performance were identified in Icelandic horse, indicating locations in their genome positively selected for specific performance traits. The identified ROH islands in Exmoor ponies were associated with traits such as coat colours, the immune system, and fertility.
  • While genetic diversity in Icelandic horses is deemed acceptable, a critically low genetic diversity was estimated for the Exmoor pony, suggesting the Exmoor pony breed may need intervention to maintain its genetic health.
  • The research concluded that the study’s findings provide insight into the genomic regions under selection pressure in a gaited performance horse breed, and various adaptive traits in small-sized native horse breeds. Thus, the findings could contribute to the preservation of genetic diversity and population health in these equine populations.

Cite This Article

APA
Sigurðardóttir H, Ablondi M, Kristjansson T, Lindgren G, Eriksson S. (2024). Genetic diversity and signatures of selection in Icelandic horses and Exmoor ponies. BMC Genomics, 25(1), 772. https://doi.org/10.1186/s12864-024-10682-8

Publication

BMC genomics
ISSN: 1471-2164
NlmUniqueID: 100965258
Country: England
Language: English
Volume: 25
Issue: 1
Pages: 772

Researcher Affiliations

Sigurðardóttir, Heiðrún
  • Department of Animal Biosciences, Swedish University of Agricultural Sciences, P.O. Box 7023, Uppsala, 75007, Sweden. heidrun.sigurdardottir@slu.se.
  • Faculty of Agricultural Sciences, Agricultural University of Iceland, Hvanneyri, Borgarbyggð, 311, Iceland. heidrun.sigurdardottir@slu.se.
Ablondi, Michela
  • Department of Veterinary Science, University of Parma, Parma, 43126, Italy.
Kristjansson, Thorvaldur
  • Faculty of Agricultural Sciences, Agricultural University of Iceland, Hvanneyri, Borgarbyggð, 311, Iceland.
Lindgren, Gabriella
  • Department of Animal Biosciences, Swedish University of Agricultural Sciences, P.O. Box 7023, Uppsala, 75007, Sweden.
  • Center for Animal Breeding and Genetics, Department of Biosystems, KU Leuven, Leuven, 3001, Belgium.
Eriksson, Susanne
  • Department of Animal Biosciences, Swedish University of Agricultural Sciences, P.O. Box 7023, Uppsala, 75007, Sweden.

MeSH Terms

  • Horses / genetics
  • Animals
  • Genetic Variation
  • Selection, Genetic
  • Homozygote
  • Iceland
  • Inbreeding
  • Genomics / methods
  • Polymorphism, Single Nucleotide
  • Heterozygote
  • Breeding
  • Genetics, Population

Conflict of Interest Statement

The authors declare competing interests concerning the commercial applications of the current study. GL is a co-inventor of a patent application concerning commercial testing of the DMRT3 mutation. The stated patent does not restrict research applications of the method. None of the other authors have any competing interests.

References

This article includes 146 references
  1. Eding H, Bennewitz J. Measuring genetic diversity in farm animals. In: Oldenbroek K, editor. Utilisation and conservation of farm animal genetic resources. 1st ed. Wageningen: Wageningen Academic; 2007. pp. 103–30.
  2. Wolliams J, Berg P, Mäki-Tanila A, Meuwissen T, Fimland E. Sustainable management of animal genetic resources. Ås (NO): Nordisk Genbank Husdyr; 2005.
  3. Adalsteinsson S. Origin and conservation of farm animal populations in Iceland. Z Tierz Züchtungsbio 1981;98:258–64.
  4. Arnórsson K. Ræktunin [The breeding]. In: Björnsson GB, Sveinsson HJ, editors. Íslenski hesturinn [The Icelandic horse]. 1st ed. Reykjavík: Mál og menning; 2006. pp. 202–47.
  5. Árnason T. Genetic studies on conformation and performance of Icelandic toelter horses [dissertation]. Uppsala: Reklam & katalogtryck; 1983 [cited 2024 February 11].
  6. Árnason T. Genetic studies on conformation and performance of Icelandic toelter horses: IV. Best linear unbiased prediction of ten correlated traits by use of an animal model. Acta Agr Scand 1984;34:450–62.
  7. Hreiðarsdóttir GE, Árnason Þ, Svansson V, Hallsson JH. Analysis of the history and population structure of the Icelandic horse using pedigree data and DNA analyses. Icel Agric Sci 2014;27:63–79.
  8. . Worldfengur - The studbook of origin for the Icelandic horse. Farmers Association of Iceland and FEIF International Federation of Icelandic Horse, Reykjavik. 2001. https://www.worldfengur.com. Accessed 11 February 2024.
  9. . The Exmoor Pony Society. https://exmoorponysociety.org.uk. Accessed 30 May 2024.
  10. Curik I, Ferenčaković M, Sölkner J. Inbreeding and runs of homozygosity: a possible solution to an old problem. Livest Sci 2014;166:26–34.
  11. Peripolli E, Munari DP, Silva MVGB, Lima ALF, Irgang R, Baldi F. Runs of homozygosity: current knowledge and applications in livestock. Anim Genet 2017;48:255–71.
    pubmed: 27910110
  12. 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;20:717.
    pmc: PMC6751828pubmed: 31533613
  13. Nolte W, Thaller G, Kuehn C. Selection signatures in four German warmblood horse breeds: tracing breeding history in the modern sport horse. PLoS ONE 2019;14:e0215913.
    pmc: PMC6483353pubmed: 31022261
  14. Hill EW, Stoffel MA, McGivney BA, MacHugh DE, Pemberton JM. Inbreeding depression and the probability of racing in the Thoroughbred horse. P Roy Soc B-Biol Sci 2022;289:20220487.
    pmc: PMC9240673pubmed: 35765835
  15. Santos WB, Schettini GP, Maiorano AM, Bussiman FO, Balieiro JCC, Ferraz GC. Genome-wide scans for signatures of selection in Mangalarga Marchador horses using high-throughput SNP genotyping. BMC Genomics 2021;22:737.
    pmc: PMC8515666pubmed: 34645387
  16. Cosgrove EJ, Sadeghi R, Schlamp F, Holl HM, Moradi-Shahrbabak M, Miraei-Ashtiani SR. Genome diversity and the origin of the arabian horse. Sci Rep 2020;10:9702.
    pmc: PMC7298027pubmed: 32546689
  17. Grilz-Seger G, Neuditschko M, Ricard A, Velie B, Lindgren G, Mesarič M. Genome-wide homozygosity patterns and evidence for selection in a set of European and Near Eastern horse breeds. Genes-Basel 2019;10:491.
    pmc: PMC6679042pubmed: 31261764
  18. Colpitts J, McLoughlin PD, Poissant J. Runs of homozygosity in Sable Island feral horses reveal the genomic consequences of inbreeding and divergence from domestic breeds. BMC Genomics 2022;23:501.
    pmc: PMC9275264pubmed: 35820826
  19. Sadeghi R, Moradi-Shahrbabak M, Miraei Ashtiani SR, Schlamp F, Cosgrove EJ, Antczak DF. Genetic diversity of persian arabian horses and their relationship to other native Iranian horse breeds. J Hered 2018;110:173–82.
    pubmed: 30590570
  20. Laseca N, Molina A, Ramón M, Valera M, Azcona F, Encina A. Fine-scale analysis of runs of homozygosity islands affecting fertility in mares. Front Vet Sci 2022;9.
    pmc: PMC8891756pubmed: 35252415
  21. Ablondi M, Dadousis C, Vasini M, Eriksson S, Mikko S, Sabbioni A. Genetic diversity and signatures of selection in a native Italian horse breed based on SNP data. Animals 2020;10:1005.
    pmc: PMC7341496pubmed: 32521830
  22. Grilz-Seger G, Druml T, Neuditschko M, Dobretsberger M, Horna M, Brem G. High-resolution population structure and runs of homozygosity reveal the genetic architecture of complex traits in the Lipizzan horse. BMC Genomics 2019;20:174.
    pmc: PMC6402180pubmed: 30836959
  23. Grilz-Seger G, Druml T, Neuditschko M, Mesarič M, Cotman M, Brem G. Analysis of ROH patterns in the Noriker horse breed reveals signatures of selection for coat color and body size. Anim Genet 2019;50:334–46.
    pmc: PMC6617995pubmed: 31199540
  24. McQuillan R, Leutenegger A-L, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L. Runs of homozygosity in European populations. Am J Hum Genet 2008;83:359–72.
    pmc: PMC2556426pubmed: 18760389
  25. Bizarria dos Santos W, Pimenta Schettini G, Fonseca MG, Pereira GL, Loyola Chardulo LA, Rodrigues Machado Neto O. Fine-scale estimation of inbreeding rates, runs of homozygosity and genome-wide heterozygosity levels in the Mangalarga Marchador horse breed. J Anim Breed Genet 2021;138:161–73.
    pubmed: 32949478
  26. Mousavi SF, Razmkabir M, Rostamzadeh J, Seyedabadi H-R, Naboulsi R, Petersen JL. Genetic diversity and signatures of selection in four indigenous horse breeds of Iran. Heredity 2023;131:96–108.
    pmc: PMC10382556pubmed: 37308718
  27. Árnadóttir E. Erfðafjölbreytileiki íslenska hrossastofnsins (Genetic diversity of the Icelandic horse population). BSc thesis, Agricultural University of Iceland. 2022.
  28. McCue ME, Bannasch DL, Petersen JL, Gurr J, Bailey E, Binns MM. A high density SNP array for the domestic horse and extant perissodactyla: utility for association mapping, genetic diversity, and phylogeny studies. PLOS Genet 2012;8:e1002451.
    pmc: PMC3257288pubmed: 22253606
  29. Petersen JL, Mickelson JR, Cothran EG, Andersson LS, Axelsson J, Bailey E. Genetic diversity in the modern horse illustrated from genome-wide SNP data. PLoS ONE 2013;8:e54997.
    pmc: PMC3559798pubmed: 23383025
  30. 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 Genomics 2020;21:94.
    pmc: PMC6990544pubmed: 31996125
  31. Petersen JL, Mickelson JR, Rendahl AK, Valberg SJ, Andersson LS, Axelsson J. Genome-wide analysis reveals selection for important traits in domestic horse breeds. PLOS Genet 2013;9:e1003211.
    pmc: PMC3547851pubmed: 23349635
  32. Gorssen W, Meyermans R, Janssens S, Buys N. A publicly available repository of ROH islands reveals signatures of selection in different livestock and pet species. Genet Sel Evol 2021;53:2.
    pmc: PMC7784028pubmed: 33397285
  33. Shrestha M, Solé M, Ducro BJ, Sundquist M, Thomas R, Schurink A. Genome-wide association study for insect bite hypersensitivity susceptibility in horses revealed novel associated loci on chromosome 1. J Anim Breed Genet 2020;137:223–33.
    pubmed: 31489730
  34. Rosengren MK, Sigurðardóttir H, Eriksson S, Naboulsi R, Jouni A, Novoa-Bravo M. A QTL for conformation of back and croup influences lateral gait quality in Icelandic horses. BMC Genomics 2021;22:267.
    pmc: PMC8048352pubmed: 33853519
  35. Sigurðardóttir H, Boije H, Albertsdóttir E, Kristjansson T, Rhodin M, Lindgren G. The genetics of gaits in Icelandic horses goes beyond DMRT3, with RELN and STAU2 identified as two new candidate genes. Genet Sel Evol 2023;55:89.
    pmc: PMC10712087pubmed: 38082412
  36. Albertsdóttir E, Eriksson S, Sigurdsson Á, Árnason T. Genetic analysis of ‘breeding field test status’ in Icelandic horses. J Anim Breed Genet 2011;128:124–32.
    pubmed: 21385227
  37. Velie BD, Shrestha M, Franҫois L, Schurink A, Tesfayonas YG, Stinckens A. 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:e0152966.
    pmc: PMC4829256pubmed: 27070818
  38. Purcell S, Chang C. PLINK v1.90. 2021. https://www.cog-genomics.org/plink/1.9/ Accessed 11 February 2024.
  39. Purcell S. PLINK: a toolset for whole-genome association and population-based linkage analysis. Am J hum Genet 2007;81:559–75.
    pmc: PMC1950838pubmed: 17701901
  40. Zheng X, Levine D, Shen J, Gogarten SM, Laurie C, Weir BS. A high-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 2012;28:3326–8.
    pmc: PMC3519454pubmed: 23060615
  41. R Core team. R: a language and environment for statistical computing. Vienna: R Foundation for Statistical Computing; 2019.
  42. Wellman R. Optimum Contribution Selection and Population Genetics. 2023. https://CRAN.R-project.org/package=optiSel. Accessed 11 February 2024.
  43. Barbato M, Orozco-terWengel P, Tapio M, Bruford MW. SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data. Front Genet 2015;6:109.
    pmc: PMC4367434pubmed: 25852748
  44. Corbin LJ, Liu A, Bishop S, Woolliams J. Estimation of historical effective population size using linkage disequilibria with marker data. J Anim Breed Genet 2012;129:257–70.
    pubmed: 22775258
  45. Sved J, Feldman M. Correlation and probability methods for one and two loci. Theor Popul Biol 1973;4:129–32.
    pubmed: 4726005
  46. Biscarini F, Cozzi P, Gaspa G, Marras G. detectRUNS. Detect runs of homozygosity and runs of heterozygosity in diploid genomes. 2018. https://cran.r-project.org/package=detectRUNS. Accessed 11 February 2024.
  47. Grilz-Seger G, Mesarič M, Cotman M, Neuditschko M, Druml T, Brem G. Runs of homozygosity and population history of three horse breeds with small population size. J Equine Vet Sci 2018;71:27–34.
  48. Nazari F, Seyedabadi H-R, Noshary A, Emamjomeh-Kashan N, Banabazi M-H. A genome-wide scan for signatures of selection in kurdish horse breed. J Equine Vet Sci 2022;113:103916.
    pubmed: 35218903
  49. Amano T, Yokawa H, Masuda Y, Tozaki T, Kawai M, Shirai K. Genome-wide search reveals the uniqueness of DNA regions associated with coat color and innate immunity in Hokkaido native horse. Anim Sci J 2023;94:e13884.
    pubmed: 37983921
  50. Cunningham F, Allen JE, Allen J, Alvarez-Jarreta J, Amode MR, Armean IM. Ensembl 2022. Nucleic Acids Res 2022;50:D988–95.
    pmc: PMC8728283pubmed: 34791404
  51. Thomas PD, Ebert D, Muruganujan A, Mushayahama T, Albou L-P, Mi H. PANTHER: making genome-scale phylogenetics accessible to all. Protein Sci 2022;31:8–22.
    pmc: PMC8740835pubmed: 34717010
  52. Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S. The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinform 2016;54:1301–13033.
    pubmed: 27322403
  53. Safran M, Rosen N, Twik M, BarShir R, Stein TI, Dahary D. The GeneCards suite. In: Abugessaisa I, Kasukawa T, editors. Practical guide to Life Science Databases. Singapore: Springer Nature Singapore; 2021. pp. 27–56.
  54. Hu Z-L, Park CA, Reecy JM. Bringing the animal QTLdb and CorrDB into the future: meeting new challenges and providing updated services. Nucleic Acids Res 2022;50:D956–61.
    pmc: PMC8728226pubmed: 34850103
  55. Schaefer RJ, Schubert M, Bailey E, Bannasch DL, Barrey E, Bar-Gal GK. Developing a 670k genotyping array to tag ~ 2 M SNPs across 24 horse breeds. BMC Genomics 2017;18:565.
    pmc: PMC5530493pubmed: 28750625
  56. Björnsson GB, Sveinsson HJ. Á spjöldum sögunnar [The history of the Icelandic horse]. In: Björnsson GB, Sveinsson HJ, editors. Íslenski hesturinn [The Icelandic horse]. 1st ed. Reykjavík: Mál og menning; 2006. pp. 76–101.
  57. Björnsson GB, Sveinsson HJ. Á tímamótum [At a turning point in time]. In: Björnsson GB, Sveinsson HJ, editors. Íslenski hesturinn [The Icelandic horse]. 1st ed. Reykjavík: Mál og menning; 2006. pp. 102–13.
  58. Árnason T, Klemetsdal G, Sigurssson Á. Nordiska hästraser - gamla genresurser ägnade for framtidens behov. In: International Symposium on Horse Breeding and Production in Cold Climatic Regions; 11–13 August; Hotel Saga. Reykjavík, Iceland; 1993.
  59. Kristjansson T. Erfðafjölbreytileiki íslenska hrossastofnsins og verndun hans. In: Dýrmundsson Ó, editor. Fjölrit LbhÍ Nr. 14. Íslensk búfjárrækt: Málstofa til heiðurs Hjalta Gestssyni níræðum. 2006 November 17; Reykjavik, Iceland. Hvanneyri, Iceland: The Agricultural University of Iceland; 2007. pp. 95–102.
  60. . Animal Importation. Act 1990 (IS) s 2.
  61. Sumreddee P, Hay EH, Toghiani S, Roberts A, Aggrey SE, Rekaya R. Grid search approach to discriminate between old and recent inbreeding using phenotypic, pedigree and genomic information. BMC Genomics 2021;22:538.
    pmc: PMC8278650pubmed: 34256689
  62. Stoffel MA, Johnston SE, Pilkington JG, Pemberton JM. Mutation load decreases with haplotype age in wild Soay sheep. Evol Lett 2021;5:187–95.
    pmc: PMC8190445pubmed: 34136268
  63. Ansari HA, Hediger R, Fries R, Stranzinger G. Chromosomal localization of the major histocompatibility complex of the horse (ELA) by in situ hybridization. Immunogenetics 1988;28:362–4.
    pubmed: 3169882
  64. Gustafson A, Tallmadge RL, Ramlachan N, Miller D, Bird H, Antczak DF. An ordered BAC contig map of the equine major histocompatibility complex. Cytogenet Genome Res 2003;102:189–95.
    pubmed: 14970701
  65. Kelley J, Walter L, Trowsdale J. Comparative genomics of major histocompatibility complexes. Immunogenetics 2005;56:683–95.
    pubmed: 15605248
  66. Holmes CM, Violette N, Miller D, Wagner B, Svansson V, Antczak DF. MHC haplotype diversity in Icelandic horses determined by polymorphic microsatellites. Genes Immun 2019;20:660–70.
    pubmed: 31068686
  67. Solé M, Ablondi M, Binzer-Panchal A, Velie BD, Hollfelder N, Buys N. Inter- and intra-breed genome-wide copy number diversity in a large cohort of European equine breeds. BMC Genomics 2019;20:759.
    pmc: PMC6805398pubmed: 31640551
  68. Laseca N, Molina A, Valera M, Antonini A, Demyda-Peyrás S. Copy number variation (CNV): a new genomic insight in horses. Animals 2022;12:1435.
    pmc: PMC9179425pubmed: 35681904
  69. Wang W, Wang S, Hou C, Xing Y, Cao J, Wu K. Genome-wide detection of copy number variations among diverse horse breeds by array CGH. PLoS ONE 2014;9:e86860.
    pmc: PMC3907382pubmed: 24497987
  70. Redon R, Ishikawa S, Fitch KR, Feuk L, Perry GH, Andrews TD. Global variation in copy number in the human genome. Nature 2006;444:444–54.
    pmc: PMC2669898pubmed: 17122850
  71. Andersson LS, Larhammar M, Memic F, Wootz H, Schwochow D, Rubin C-J. Mutations in DMRT3 affect locomotion in horses and spinal circuit function in mice. Nature 2012;488:642–6.
    pmc: PMC3523687pubmed: 22932389
  72. Kristjansson T, Bjornsdottir S, Sigurdsson A, Andersson L, Lindgren G, Helyar S. The effect of the ‘Gait keeper’ mutation in the DMRT3 gene on gaiting ability in Icelandic horses. J Anim Breed Genet 2014;131:415–25.
    pubmed: 25073639
  73. Velie BD, Fegraeus KJ, Solé M, Rosengren MK, Røed KH, Ihler C-F. 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;19:80.
    pmc: PMC6114527pubmed: 30157760
  74. Jäderkvist K, Andersson LS, Johansson AM, Árnason T, Mikko S, Eriksson S. The DMRT3 ‘gait keeper’ mutation affects performance of nordic and standardbred trotters. J Anim Sci 2014;92:4279–86.
    pubmed: 25085403
  75. Promerová M, Andersson L, Juras R, Penedo M, Reissmann M, Tozaki T. Worldwide frequency distribution of the ‘Gait keeper’ mutation in the DMRT3 gene. Anim Genet 2014;45:274–82.
    pubmed: 24444049
  76. Patterson L, Staiger E, Brooks S. DMRT3 is associated with gait type in Mangalarga Marchador horses, but does not control gait ability. Anim Genet 2015;46:213–5.
    pubmed: 25690906
  77. Novoa-Bravo M, Jäderkvist Fegraeus K, Rhodin M, Strand E, García LF, Lindgren G. Selection on the Colombian paso horse’s gaits has produced kinematic differences partly explained by the DMRT3 gene. PLoS ONE 2018;13:e0202584.
    pmc: PMC6097835pubmed: 30118522
  78. Chandra Paul R, Ba Nguyen T, Okuda Y, Nu Anh Le T, Mosese Dau Tabuyaqona J, Konishi Y. Distribution of the mutant allele of the DMRT3 gene associated with ambling gaits in Japanese native horse populations. Anim Sci J 2020;91:e13431.
    pubmed: 32761714
  79. Staiger EA, Almén MS, Promerová M, Brooks S, Cothran EG, Imsland F. The evolutionary history of the DMRT3 ‘Gait keeper’ haplotype. Anim Genet 2017;48:551–9.
    pubmed: 28741731
  80. Bas Conn L. The role of polymorphisms of the MSTN, GRIN2B and DOCK8 genes in the performance of pace-racing Icelandic horses. MSc thesis, Swedish University of Agricultural Sciences. 2018.
  81. Kang JU, Koo SH, Kwon KC, Park JW. Frequent silence of chromosome 9p, homozygous DOCK8, DMRT1 and DMRT3 deletion at 9p24. 3 in squamous cell carcinoma of the lung. Int J Oncol 2010;37:327–35.
    pubmed: 20596660
  82. Glessner JT, Li J, Wang D, March M, Lima L, Desai A. Copy number variation meta-analysis reveals a novel duplication at 9p24 associated with multiple neurodevelopmental disorders. Genome Med 2017;9:106.
    pmc: PMC5709845pubmed: 29191242
  83. Jäderkvist K, Holm N, Imsland F, Árnason T, Andersson L, Andersson LS. The importance of the DMRT3 ‘Gait keeper’ mutation on riding traits and gaits in Standardbred and Icelandic horses. Livest Sci 2015;176:33–9.
  84. Molt S, Bührdel JB, Yakovlev S, Schein P, Orfanos Z, Kirfel G. Aciculin interacts with filamin C and Xin and is essential for myofibril assembly, remodeling and maintenance. J Cell Sci 2014;127:3578–92.
    pubmed: 24963132
  85. Metallinos DL, Bowling AT, Rine J. A missense mutation in the endothelin-B receptor gene is associated with lethal white foal syndrome: an equine version of Hirschsprung disease. Mamm Genome 1998;9:426–31.
    pubmed: 9585428
  86. Santschi EM, Purdy AK, Valberg SJ, Vrotsos PD, Kaese H, Mickelson JR. Endothelin receptor B polymorphism associated with lethal white foal syndrome in horses. Mamm Genome 1998;9:306–9.
    pubmed: 9530628
  87. Yan GC, Croaker D, Zhang AL, Manglick P, Cartmill T, Cass D. A dinucleotide mutation in the endothelin-B receptor gene is associated with lethal white foal syndrome (LWFS); a horse variant of Hirschsprung disease (HSCR). Hum Mol Genet 1998;7:1047–52.
    pubmed: 9580670
  88. Yanagisawa M, Kurihara H, Kimura S, Tomobe Y, Kobayashi M, Mitsui Y. A novel potent vasoconstrictor peptide produced by vascular endothelial cells. Nature 1988;332:411–5.
    pubmed: 2451132
  89. Inoue A, Yanagisawa M, Kimura S, Kasuya Y, Miyauchi T, Goto K. The human endothelin family: three structurally and pharmacologically distinct isopeptides predicted by three separate genes. P Natl Acad Sci USA 1989;86:2863–7.
    pmc: PMC287019pubmed: 2649896
  90. Baynash AG, Hosoda K, Giaid A, Richardson JA, Emoto N, Hammer RE. Interaction of endothelin-3 with endothelin-B receptor is essential for development of epidermal melanocytes and enteric neurons. Cell 1994;79:1277–85.
    pubmed: 8001160
  91. Hosoda K, Hammer RE, Richardson JA, Baynash AG, Cheung JC, Giaid A. Targeted and natural (piebald-lethal) mutations of endothelin-B receptor gene produce megacolon associated with spotted coat color in mice. Cell 1994;79:1267–76.
    pubmed: 8001159
  92. Stanchina L, Baral V, Robert F, Pingault V, Lemort N, Pachnis V. Interactions between Sox10, Edn3 and Ednrb during enteric nervous system and melanocyte development. Dev Biol 2006;295:232–49.
    pubmed: 16650841
  93. Jäderkvist Fegraeus K, Velie BD, Axelsson J, Ang R, Hamilton NA, Andersson L. A potential regulatory region near the EDN3 gene may control both harness racing performance and coat color variation in horses. Physiol Rep 2018;6:e13700.
    pmc: PMC5974718pubmed: 29845762
  94. Fegraeus K, Rosengren MK, Naboulsi R, Orlando L, Åbrink M, Jouni A. An endothelial regulatory module links blood pressure regulation with elite athletic performance. PLOS Genet 2024;20:e1011285.
    pmc: PMC11182536pubmed: 38885195
  95. Stefánsdóttir G, Ragnarsson S, Gunnarsson V, Jansson A. Physiological response to a breed evaluation field test in Icelandic horses. Animal 2014;8:431–9.
    pmc: PMC3942816pubmed: 24387835
  96. Stefánsdóttir G, Ragnarsson S, Gunnarsson V, Roepstorff L, Jansson A. A comparison of the physiological response to tölt and trot in the Icelandic horse. J Anim Sci 2015;93:3862–70.
    pubmed: 26440166
  97. Hirst CE, Lim S-M, Pereira LA, Mayberry RA, Stanley EG, Elefanty AG. Expression from a betageo gene trap in the Slain1 gene locus is predominantly associated with the developing nervous system. Int J Dev Biol 2010;54:1383–8.
    pubmed: 20563991
  98. Pavlopoulos E, Trifilieff P, Chevaleyre V, Fioriti L, Zairis S, Pagano A. Neuralized1 activates CPEB3: a function for nonproteolytic ubiquitin in synaptic plasticity and memory storage. Cell 2011;147:1369–83.
    pmc: PMC3442370pubmed: 22153079
  99. Taal K, Tuvikene J, Rullinkov G, Piirsoo M, Sepp M, Neuman T. Neuralized family member NEURL1 is a ubiquitin ligase for the cGMP-specific phosphodiesterase 9A. Sci Rep 2019;9:7104.
    pmc: PMC6506465pubmed: 31068605
  100. Rieder S, Taourit S, Mariat D, Langlois B, Guérin G. Mutations in the agouti (ASIP), the extension (MC1R), and the brown (TYRP1) loci and their association to coat color phenotypes in horses (Equus caballus). Mamm Genome 2001;12:450–5.
    pubmed: 11353392
  101. Imsland F, McGowan K, Rubin C-J, Henegar C, Sundström E, Berglund J. Regulatory mutations in TBX3 disrupt asymmetric hair pigmentation that underlies Dun camouflage color in horses. Nat Genet 2016;48:152–8.
    pmc: PMC4731265pubmed: 26691985
  102. Lee S-T, Nicholls RD, Jong MT, Fukai K, Spritz RA. Organization and sequence of the human P gene and identification of a new family of transport proteins. Genomics 1995;26:354–63.
    pubmed: 7601462
  103. Sturm RA, Frudakis TN. Eye colour: portals into pigmentation genes and ancestry. Trends Genet 2004;20:327–32.
    pubmed: 15262401
  104. Sturm RA, Duffy DL, Zhao ZZ, Leite FP, Stark MS, Hayward NK. A single SNP in an evolutionary conserved region within intron 86 of the HERC2 gene determines human blue-brown eye color. Am J Hum Genet 2008;82:424–31.
    pmc: PMC2427173pubmed: 18252222
  105. Duffy DL, Montgomery GW, Chen W, Zhao ZZ, Le L, James MR. A three-single-nucleotide polymorphism haplotype in intron 1 of OCA2 explains most human eye-color variation. Am J Hum Genet 2007;80:241–52.
    pmc: PMC1785344pubmed: 17236130
  106. Sturm RA. Molecular genetics of human pigmentation diversity. Hum Mol Genet 2009;18:R9–17.
    pubmed: 19297406
  107. Kowalski EJA, Bellone RR. Investigation of HERC2 and OCA2 SNP for iris color variation in Puerto Rican Paso Fino horses. J Equine Vet Sci 2011;31:319.
  108. Bellone R, Lawson S, Hunter N, Archer S, Bailey E. Analysis of a SNP in exon 7 of equine OCA2 and its exclusion as a cause for Appaloosa spotting. Anim Genet 2006;37:525.
    pubmed: 16978190
  109. . General rules and regulations: Breeding rules and regulations. 2023. https://www.feiffengur.com/documents/FEIF Breeding_2023.pdf. Accessed 5 January 2024.
  110. Zhang T, Kim DH, Xiao X, Lee S, Gong Z, Muzumdar R. FoxO1 plays an important role in regulating β-cell compensation for insulin resistance in male mice. Endocrinology 2016;157:1055–70.
    pmc: PMC4769368pubmed: 26727107
  111. Puig O, Tjian R. Transcriptional feedback control of insulin receptor by dFOXO/FOXO1. Gene Dev 2005;19:2435–46.
    pmc: PMC1257398pubmed: 16230533
  112. Matsumoto M, Han S, Kitamura T, Accili D. Dual role of transcription factor FoxO1 in controlling hepatic insulin sensitivity and lipid metabolism. J Clin Invest 2006;116:2464–72.
    pmc: PMC1533874pubmed: 16906224
  113. Frank N, Geor RJ, Bailey SR, Durham AE, Johnson PJ. Equine metabolic syndrome. J Vet Intern Med 2010;24:467–75.
    pubmed: 20384947
  114. Bröjer J, Lindåse S, Hedenskog J, Alvarsson K, Nostell K. Repeatability of the combined glucose-insulin tolerance test and the effect of a stressor before testing in horses of 2 breeds. J Vet Intern Med 2013;27:1543–50.
    pubmed: 24033635
  115. Bailey SR, Habershon-Butcher JL, Ransom KJ, Elliott J, Menzies-Gow NJ. Hypertension and insulin resistance in a mixed-breed population of ponies predisposed to laminitis. Am J Vet Res 2008;69:122–9.
    pubmed: 18167097
  116. Jansson P-A. Endothelial dysfunction in insulin resistance and type 2 diabetes. J Vet Intern Med 2007;262:173–83.
    pubmed: 17645585
  117. Johnson P. The equine metabolic syndrome peripheral Cushing’s syndrome. Vet Clin N Am-Equine 2002;18:271–93.
    pubmed: 15635908
  118. Gieger C, Radhakrishnan A, Cvejic A, Tang W, Porcu E, Pistis G. New gene functions in megakaryopoiesis and platelet formation. Nature 2011;480:201–8.
    pmc: PMC3335296pubmed: 22139419
  119. Qayyum R, Snively BM, Ziv E, Nalls MA, Liu Y, Tang W. A meta-analysis and genome-wide association study of platelet count and mean platelet volume in African americans. PLOS Genet 2012;8:e1002491.
    pmc: PMC3299192pubmed: 22423221
  120. Freedman BI, Bowden DW, Ziegler JT, Langefeld CD, Lehtinen AB, Rudock ME. Bone morphogenetic protein 7 (BMP7) gene polymorphisms are associated with inverse relationships between vascular calcification and BMD: the diabetes heart study. J Bone Min Res 2009;24:1719–27.
    pmc: PMC2743282pubmed: 19453255
  121. Lumbroso S, Paris Fo, Sultan C. Activating Gsα mutations: analysis of 113 patients with signs of McCune-Albright syndrome - A European collaborative study. J Clin Endocr Metab 2004;89:2107–13.
    pubmed: 15126527
  122. Szmatoła T, Gurgul A, Jasielczuk I, Oclon E, Ropka-Molik K, Stefaniuk-Szmukier M. Assessment and distribution of runs of homozygosity in horse breeds representing different utility types. Animals 2022;12:3293.
    pmc: PMC9736150pubmed: 36496815
  123. Makvandi-Nejad S, Hoffman GE, Allen JJ, Chu E, Gu E, Chandler AM. Four loci explain 83% of size variation in the horse. PLoS ONE 2012;7:e39929.
    pmc: PMC3394777pubmed: 22808074
  124. Bartholazzi Junior A, Quirino CR, Vega WHO, Rua MAS, David CMG, Jardim JG. Polymorphisms in the LASP1 gene allow selection for smaller stature in ponies. Livest Sci 2018;216:160–4.
  125. Skujina I, Winton CL, Hegarty MJ, McMahon R, Nash DM, Morel MCGD. Detecting genetic regions associated with height in the native ponies of the British Isles by using high density SNP genotyping. Genome 2018;61:767–70.
    pubmed: 30184439
  126. Thomer A, Gottschalk M, Christmann A, Naccache F, Jung K, Hewicker-Trautwein M. An epistatic effect of KRT25 on SP6 is involved in curly coat in horses. Sci Rep 2018;8:6374.
    pmc: PMC5913262pubmed: 29686323
  127. Yuki KE, Marei H, Fiskin E, Eva MM, Gopal AA, Schwartzentruber JA. CYRI/FAM49B negatively regulates RAC1-driven cytoskeletal remodelling and protects against bacterial infection. Nat Microbiol 2019;4:1516–31.
    pubmed: 31285585
  128. Van den Eede A, Martens A, Lipinska U, Struelens M, Deplano A, Denis O. High occurrence of methicillin-resistant Staphylococcus aureus ST398 in equine nasal samples. Vet Microbiol 2009;133:138–44.
    pubmed: 18701224
  129. Sweeney CR, Timoney JF, Newton JR, Hines MT. Streptococcus equi infections in horses: guidelines for treatment, control, and prevention of strangles. J Vet Intern Med 2005;19:123–34.
    pubmed: 15715061
  130. Uzal FA, Navarro MA, Asin J, Henderson EE. Clostridial diseases of horses: a review. Vaccines 2022;10:318.
    pmc: PMC8876495pubmed: 35214776
  131. Warner SL, Boggs J, Lee JK, Reddy S, Banes M, Cooley J. Clinical, pathological, and genetic characterization of Listeria monocytogenes causing sepsis and necrotizing typhlocolitis and hepatitis in a foal. J Vet Diagn Invest 2012;24:581–6.
    pubmed: 22529130
  132. Irwin DM, Biegel JM, Stewart C-B. Evolution of the mammalian lysozyme gene family. BMC Evol Biol 2011;11:166.
    pmc: PMC3141428pubmed: 21676251
  133. Mastrangelo S, Tolone M, Sardina MT, Sottile G, Sutera AM, Di Gerlando R. Genome-wide scan for runs of homozygosity identifies potential candidate genes associated with local adaptation in Valle Del Belice sheep. Genet Sel Evol 2017;49:84.
    pmc: PMC5684758pubmed: 29137622
  134. Greenbaum MP, Yan W, Wu M-H, Lin Y-N, Agno JE, Sharma M. TEX14 is essential for intercellular bridges and fertility in male mice. P Natl Acad Sci-Biol 2006;103:4982–7.
    pmc: PMC1458781pubmed: 16549803
  135. Greenbaum MP, Iwamori N, Agno JE, Matzuk MM. Mouse TEX14 is required for embryonic germ cell intercellular bridges but not female fertility. Biol Reprod 2009;80:449–57.
    pmc: PMC2805395pubmed: 19020301
  136. Baudat F, Manova K, Yuen JP, Jasin M, Keeney S. Chromosome synapsis defects and sexually dimorphic meiotic progression in mice lacking Spo11. Mol Cell 2000;6:989–98.
    pubmed: 11106739
  137. Carrell D, De Jonge C, Lamb D. The genetics of male infertility: a field of study whose time is now. Arch Androl 2006;52:269–74.
    pubmed: 16728342
  138. Zhang J, Zhou D-x, Wang H-x, Tian Z. An association study of SPO11 gene single nucleotide polymorphisms with idiopathic male infertility in Chinese Han population. J Assist Reprod Gen 2011;28:731–6.
    pmc: PMC3170106pubmed: 21556891
  139. Ghalkhani E, Sheidai M, Gourabi H, Noormohammadi Z, Bakhtari N, Malekasgar AM. Study of single nucleotide polymorphism (rs28368082) in SPO11 gene and its association with male infertility. J Assist Reprod Gen 2014;31:1205–10.
    pmc: PMC4156955pubmed: 25005169
  140. Nicolini P, Amorín R, Han Y, Peñagaricano F. Whole-genome scan reveals significant non-additive effects for sire conception rate in Holstein cattle. BMC Genet 2018;19:14.
    pmc: PMC5830072pubmed: 29486732
  141. Sha Y-W, Xu X, Ji Z-Y, Mei L-B, Qiu P-P, Ji H. Sperm-egg fusion disorder in a Chinese male patient was associated with a rare ADAM20 variant. Oncotarget 2017;9:2086–91.
    pmc: PMC5788623pubmed: 29416755
  142. Zhu G-Z, Lin Y, Myles DG, Primakoff P. Identification of four novel ADAMs with potential roles in spermatogenesis and fertilization. Gene 1999;234:227–37.
    pubmed: 10395895
  143. vanH RH. ADAM 20 and 21; two novel human testis-specific membrane metalloproteases with similarity to fertilin-α. Gene 1998;206:273–82.
    pubmed: 9469942
  144. Li Y, Chen Y, Wu W, Li N, Hua J. MMPs, ADAMs and ADAMTSs are associated with mammalian sperm fate. Theriogenology 2023;200:147–54.
    pubmed: 36842259
  145. Cezard T, Cunningham F, Hunt SE, Koylass B, Kumar N, Saunders G. The European variation archive: a FAIR resource of genomic variation for all species. Nucleic Acids Res 2021;50:D1216–20.
    pmc: PMC8728205pubmed: 34718739
  146. Percie du Sert N, Hurst V, Ahluwalia A, Alam S, Avey MT, Baker M. The ARRIVE guidelines 2.0: updated guidelines for reporting animal research. PLOS Biol 2020;18:e3000410.
    pmc: PMC7360023pubmed: 32663219

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