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Animals : an open access journal from MDPI2022; 12(23); 3293; doi: 10.3390/ani12233293

Assessment and Distribution of Runs of Homozygosity in Horse Breeds Representing Different Utility Types.

Abstract: The present study reports runs of homozygosity (ROH) distribution in the genomes of six horse breeds (571 horses in total) representing three horse types (primitive, light, and draft horses) based on the 65k Equine BeadChip assay. Of major interest was the length, quantity, and frequency of ROH characteristics, as well as differences between horse breeds and types. Noticeable differences in the number, length and distribution of ROH between breeds were observed, as well as in genomic inbreeding coefficients. We also identified regions of the genome characterized by high ROH coverage, known as ROH islands, which may be signals of recent selection events. Eight to fourteen ROH islands were identified per breed, which spanned multiple genes. Many were involved in important horse breed characteristics, including , , , , , , , and the zinc finger protein family. Regions of the genome with zero ROH occurrences were also of major interest in specific populations. Depending on the breed, we detected between 2 to 57 no-ROH regions and identified 27 genes in these regions that were common for five breeds. These genes were involved in, e.g., muscle contractility () and muscle development (, , ). To sum up, the obtained results can be furthered analyzed in the topic of identification of markers unique for specific horse breed characteristics.
Publication Date: 2022-11-25 PubMed ID: 36496815PubMed Central: PMC9736150DOI: 10.3390/ani12233293Google Scholar: Lookup
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  • Journal Article

Summary

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This study analyzes the distribution of runs of homozygosity (ROH) in the genomes of six horse breeds to understand differences between the breeds and types of horses. The information drawn from these analyses can be used to identify unique markers for specific horse breed characteristics.

Understanding Runs of Homozygosity (ROH)

  • ROH are stretches in the genome where the two copies of the chromosome are identical.
  • The study aims to explore the length, quantity, and frequency of these ROH characteristics in the genome.
  • Analyzed were genomes of six horse breeds: a total of 571 horses. These breeds come from three types: primitive, light, and draft horses.
  • The data was garnered using a 65k Equine BeadChip assay that is used to analyze the genotype of a horse.

Findings of the Study

  • The results show noticeable differences in the number, length and distribution of ROH between the different breeds.
  • In addition, differences were observed in genomic inbreeding coefficients i.e. the probability where both alleles of a gene come from the same ancestor.

Regions of Interest in the Genome

  • The study also investigated areas in the genome with a high occurrence of ROH, called ROH islands, often indicative of recent selection events.
  • Depending on the breed, between 8 to 14 ROH islands were identified. These islands span several genes and many are related to characteristics unique to horse breeds.

Regions with No-ROH Occurrences

  • The regions of the genome with no ROH occurrences also pose significant interest. Depending on the breed, there were 2 to 57 such regions detected.
  • Twenty-seven genes within these no-ROH regions were common for five breeds.
  • These genes are believed to be involved in functions such as muscle contractility and development.

Implications of the Research

  • Through these analyses, specific markers for distinctive horse breed characteristics can be identified.
  • This can be used in future studies and applications for equine genetic characterization and enhancement.

Cite This Article

APA
Szmatoła T, Gurgul A, Jasielczuk I, Oclon E, Ropka-Molik K, Stefaniuk-Szmukier M, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. (2022). Assessment and Distribution of Runs of Homozygosity in Horse Breeds Representing Different Utility Types. Animals (Basel), 12(23), 3293. https://doi.org/10.3390/ani12233293

Publication

ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 12
Issue: 23
PII: 3293

Researcher Affiliations

Szmatoła, Tomasz
  • Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland.
  • Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland.
Gurgul, Artur
  • Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland.
Jasielczuk, Igor
  • Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland.
Oclon, Ewa
  • Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland.
Ropka-Molik, Katarzyna
  • Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland.
Stefaniuk-Szmukier, Monika
  • Department of Animal Molecular Biology, National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland.
Polak, Grazyna
  • Office of the Director for Scientific Affairs, National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland.
Tomczyk-Wrona, Iwona
  • Department of Horse Breeding, National Research Institute of Animal Production, Krakowska 1, 32-083 Balice, Poland.
Bugno-Poniewierska, Monika
  • Department of Animal Reproduction, Anatomy and Genomics, University of Agriculture in Kraków, al. Mickiewicza 24/28, 30-059 Kraków, Poland.

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 80 references
  1. Purfield DC, Berry DP, McParland S, Bradley DG. Runs of homozygosity and population history in cattle.. BMC Genet 2012 Aug 14;13:70.
    doi: 10.1186/1471-2156-13-70pmc: PMC3502433pubmed: 22888858google scholar: lookup
  2. McQuillan R, Leutenegger AL, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L, Smolej-Narancic N, Janicijevic B, Polasek O, Tenesa A, Macleod AK, Farrington SM, Rudan P, Hayward C, Vitart V, Rudan I, Wild SH, Dunlop MG, Wright AF, Campbell H, Wilson JF. Runs of homozygosity in European populations.. Am J Hum Genet 2008 Sep;83(3):359-72.
    doi: 10.1016/j.ajhg.2008.08.007pmc: PMC2556426pubmed: 18760389google scholar: lookup
  3. Curik I, Ferencakovic M, Sölkner J. Inbreeding and runs of homozygosity: A possible solution to an old problem.. Livest. Sci. 2014;166:26–34.
  4. Ferencakovic M, Hamzic E, Gredler B, Curik I, Sölkner J. Runs of homozygosity reveal genomewide autozygosity in the Austrian Fleckvieh cattle.. Agric. Conspec. Sci. 2011;76:325–328.
  5. Szmatoła T, Gurgul A, Jasielczuk I, Ząbek T, Ropka-Molik K, Litwińczuk Z, Bugno-Poniewierska M. A Comprehensive Analysis of Runs of Homozygosity of Eleven Cattle Breeds Representing Different Production Types.. Animals (Basel) 2019 Nov 25;9(12).
    doi: 10.3390/ani9121024pmc: PMC6941163pubmed: 31775271google scholar: lookup
  6. Howrigan DP, Simonson MA, Keller MC. Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms.. BMC Genomics 2011 Sep 23;12:460.
    doi: 10.1186/1471-2164-12-460pmc: PMC3188534pubmed: 21943305google scholar: lookup
  7. Mastrangelo S, Tolone M, Di Gerlando R, Fontanesi L, Sardina MT, Portolano B. Genomic inbreeding estimation in small populations: evaluation of runs of homozygosity in three local dairy cattle breeds.. Animal 2016 May;10(5):746-54.
    doi: 10.1017/S1751731115002943pubmed: 27076405google scholar: lookup
  8. Nothnagel M, Lu TT, Kayser M, Krawczak M. Genomic and geographic distribution of SNP-defined runs of homozygosity in Europeans.. Hum Mol Genet 2010 Aug 1;19(15):2927-35.
    doi: 10.1093/hmg/ddq198pubmed: 20462934google scholar: lookup
  9. Pemberton TJ, Absher D, Feldman MW, Myers RM, Rosenberg NA, Li JZ. Genomic patterns of homozygosity in worldwide human populations.. Am J Hum Genet 2012 Aug 10;91(2):275-92.
    doi: 10.1016/j.ajhg.2012.06.014pmc: PMC3415543pubmed: 22883143google scholar: lookup
  10. Peripolli E, Munari DP, Silva MVGB, Lima ALF, Irgang R, Baldi F. Runs of homozygosity: current knowledge and applications in livestock.. Anim Genet 2017 Jun;48(3):255-271.
    doi: 10.1111/age.12526pubmed: 27910110google scholar: lookup
  11. Gibson J, Morton NE, Collins A. Extended tracts of homozygosity in outbred human populations.. Hum Mol Genet 2006 Mar 1;15(5):789-95.
    doi: 10.1093/hmg/ddi493pubmed: 16436455google scholar: lookup
  12. Solkner J, Ferencakovic M, Gredler B, Curik I. Genomic metrics of individual autozygosity, applied to a cattle population. In Proceedings of the 61st Annual Meeting of the European Association of Animal Production, Heraklion, Greece, 22–26 August 2010.
  13. Ferenčaković M, Hamzić E, Gredler B, Solberg TR, Klemetsdal G, Curik I, Sölkner J. Estimates of autozygosity derived from runs of homozygosity: empirical evidence from selected cattle populations.. J Anim Breed Genet 2013 Aug;130(4):286-93.
    doi: 10.1111/jbg.12012pubmed: 23855630google scholar: lookup
  14. Kim ES, Cole JB, Huson H, Wiggans GR, Van Tassell CP, Crooker BA, Liu G, Da Y, Sonstegard TS. Effect of artificial selection on runs of homozygosity in u.s. Holstein cattle.. PLoS One 2013;8(11):e80813.
  15. Librado P, Khan N, Fages A, Kusliy MA, Suchan T, Tonasso-Calvière L, Schiavinato S, Alioglu D, Fromentier A, Perdereau A, Aury JM, Gaunitz C, Chauvey L, Seguin-Orlando A, Der Sarkissian C, Southon J, Shapiro B, Tishkin AA, Kovalev AA, Alquraishi S, Alfarhan AH, Al-Rasheid KAS, Seregély T, Klassen L, Iversen R, Bignon-Lau O, Bodu P, Olive M, Castel JC, Boudadi-Maligne M, Alvarez N, Germonpré M, Moskal-Del Hoyo M, Wilczyński J, Pospuła S, Lasota-Kuś A, Tunia K, Nowak M, Rannamäe E, Saarma U, Boeskorov G, Lōugas L, Kyselý R, Peške L, Bălășescu A, Dumitrașcu V, Dobrescu R, Gerber D, Kiss V, Szécsényi-Nagy A, Mende BG, Gallina Z, Somogyi K, Kulcsár G, Gál E, Bendrey R, Allentoft ME, Sirbu G, Dergachev V, Shephard H, Tomadini N, Grouard S, Kasparov A, Basilyan AE, Anisimov MA, Nikolskiy PA, Pavlova EY, Pitulko V, Brem G, Wallner B, Schwall C, Keller M, Kitagawa K, Bessudnov AN, Bessudnov A, Taylor W, Magail J, Gantulga JO, Bayarsaikhan J, Erdenebaatar D, Tabaldiev K, Mijiddorj E, Boldgiv B, Tsagaan T, Pruvost M, Olsen S, Makarewicz CA, Valenzuela Lamas S, Albizuri Canadell S, Nieto Espinet A, Iborra MP, Lira Garrido J, Rodríguez González E, Celestino S, Olària C, Arsuaga JL, Kotova N, Pryor A, Crabtree P, Zhumatayev R, Toleubaev A, Morgunova NL, Kuznetsova T, Lordkipanize D, Marzullo M, Prato O, Bagnasco Gianni G, Tecchiati U, Clavel B, Lepetz S, Davoudi H, Mashkour M, Berezina NY, Stockhammer PW, Krause J, Haak W, Morales-Muñiz A, Benecke N, Hofreiter M, Ludwig A, Graphodatsky AS, Peters J, Kiryushin KY, Iderkhangai TO, Bokovenko NA, Vasiliev SK, Seregin NN, Chugunov KV, Plasteeva NA, Baryshnikov GF, Petrova E, Sablin M, Ananyevskaya E, Logvin A, Shevnina I, Logvin V, Kalieva S, Loman V, Kukushkin I, Merz I, Merz V, Sakenov S, Varfolomeyev V, Usmanova E, Zaibert V, Arbuckle B, Belinskiy AB, Kalmykov A, Reinhold S, Hansen S, Yudin AI, Vybornov AA, Epimakhov A, Berezina NS, Roslyakova N, Kosintsev PA, Kuznetsov PF, Anthony D, Kroonen GJ, Kristiansen K, Wincker P, Outram A, Orlando L. The origins and spread of domestic horses from the Western Eurasian steppes.. Nature 2021 Oct;598(7882):634-640.
    doi: 10.1038/s41586-021-04018-9pmc: PMC8550961pubmed: 34671162google scholar: lookup
  16. Remer V, Bozlak E, Felkel S, Radovic L, Rigler D, Grilz-Seger G, Stefaniuk-Szmukier M, Bugno-Poniewierska M, Brooks S, Miller DC, Antczak DF, Sadeghi R, Cothran G, Juras R, Khanshour AM, Rieder S, Penedo MC, Waiditschka G, Kalinkova L, Kalashnikov VV, Zaitsev AM, Almarzook S, Reißmann M, Brockmann GA, Brem G, Wallner B. Y-Chromosomal Insights into Breeding History and Sire Line Genealogies of Arabian Horses.. Genes (Basel) 2022 Jan 26;13(2).
    doi: 10.3390/genes13020229pmc: PMC8871751pubmed: 35205275google scholar: lookup
  17. Cosgrove EJ, Sadeghi R, Schlamp F, Holl HM, Moradi-Shahrbabak M, Miraei-Ashtiani SR, Abdalla S, Shykind B, Troedsson M, Stefaniuk-Szmukier M, Prabhu A, Bucca S, Bugno-Poniewierska M, Wallner B, Malek J, Miller DC, Clark AG, Antczak DF, Brooks SA. Genome Diversity and the Origin of the Arabian Horse.. Sci Rep 2020 Jun 16;10(1):9702.
    doi: 10.1038/s41598-020-66232-1pmc: PMC7298027pubmed: 32546689google scholar: lookup
  18. Dubois C, Ricard A. Efficiency of past selection of the French Sport Horse: Selle Français breed and suggestions for the future.. Livest. Sci. 2007;112:161–171.
  19. Prawocheński R. Hodowla Koni.. PWRiL; Warszawa, Poland: 2010.
  20. Fornal A, Radko A, Nogaj J, Zielinska-Darecka K, Piestrzynska-Kajtoch A. Malopolski Horse Stallions: Genetic Diversity Estimated on the Basisof Microsatellite DNA and Class I Markers.. Folia Bilogica 2018;66:83–87.
    doi: 10.3409/fb_66-2.09google scholar: lookup
  21. Polak G, Gurgul A, Jasielczuk I, Szmatoła T, Krupiński J, Bugno-Poniewierska M. Suitability of Pedigree Information and Genomic Methods for Analyzing Inbreeding of Polish Cold-Blooded Horses Covered by Conservation Programs.. Genes (Basel) 2021 Mar 17;12(3).
    doi: 10.3390/genes12030429pmc: PMC8002693pubmed: 33802830google scholar: lookup
  22. Jasielczuk I, Gurgul A, Szmatoła T, Semik-Gurgul E, Pawlina-Tyszko K, Stefaniuk-Szmukier M, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. Linkage disequilibrium, haplotype blocks and historical effective population size in Arabian horses and selected Polish native horse breeds.. Livest. Sci. 2020;239:104095.
  23. Gurgul A, Jasielczuk I, Semik-Gurgul E, Pawlina-Tyszko K, Stefaniuk-Szmukier M, Szmatoła T, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. A genome-wide scan for diversifying selection signatures in selected horse breeds.. PLoS One 2019;14(1):e0210751.
  24. Pasicka. Polish Konik Horse–Characteristics and historical background of native descendants of tarpan.. Acta Sci. Pol. 2013;12:25–38.
  25. Pasternak M, Krupinski J, Gurgul A, Bugno-Poniewierska M. Genetic, historical and breeding aspects of the occurrence of the tobiano pattern and white markings in the Polish population of Hucul horses–a review.. J. Appl. Anim. Res. 2020;48:21–27.
  26. Gurgul A, Jasielczuk I, Semik-Gurgul E, Pawlina-Tyszko K, Szmatoła T, Polak G, Bugno-Poniewierska M. Genetic Differentiation of the Two Types of Polish Cold-blooded Horses Included in the National Conservation Program.. Animals (Basel) 2020 Mar 24;10(3).
    doi: 10.3390/ani10030542pmc: PMC7143816pubmed: 32214005google scholar: lookup
  27. Tomczyk-Wrona I. Charakterystyka udziału ras tworzących w populacji ogierów małopolskich uznanych do programu ochrony zasobów genetycznych koni rasy małopolskiej.. Wiad. Zoot. 2014;4:125–135.
  28. 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
  29. R Core Team. R: A Language and Environment for Statistical Computing.. R Foundation for Statistical Computing, 2020, Vienna, Austria.
  30. Beeson SK, Mickelson JR, McCue ME. Equine recombination map updated to Eq쪳.0.. Anim Genet 2020 Mar;51(2):341-342.
    doi: 10.1111/age.12898pmc: PMC7054148pubmed: 31887785google scholar: lookup
  31. Howe KL, Achuthan P, Allen J, Allen J, Alvarez-Jarreta J, Amode MR, Armean IM, Azov AG, Bennett R, Bhai J, Billis K, Boddu S, Charkhchi M, Cummins C, Da Rin Fioretto L, Davidson C, Dodiya K, El Houdaigui B, Fatima R, Gall A, Garcia Giron C, Grego T, Guijarro-Clarke C, Haggerty L, Hemrom A, Hourlier T, Izuogu OG, Juettemann T, Kaikala V, Kay M, Lavidas I, Le T, Lemos D, Gonzalez Martinez J, Marugán JC, Maurel T, McMahon AC, Mohanan S, Moore B, Muffato M, Oheh DN, Paraschas D, Parker A, Parton A, Prosovetskaia I, Sakthivel MP, Salam AIA, Schmitt BM, Schuilenburg H, Sheppard D, Steed E, Szpak M, Szuba M, Taylor K, Thormann A, Threadgold G, Walts B, Winterbottom A, Chakiachvili M, Chaubal A, De Silva N, Flint B, Frankish A, Hunt SE, IIsley GR, Langridge N, Loveland JE, Martin FJ, Mudge JM, Morales J, Perry E, Ruffier M, Tate J, Thybert D, Trevanion SJ, Cunningham F, Yates AD, Zerbino DR, Flicek P. Ensembl 2021.. Nucleic Acids Res 2021 Jan 8;49(D1):D884-D891.
    doi: 10.1093/nar/gkaa942pmc: PMC7778975pubmed: 33137190google scholar: lookup
  32. 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 Aug;50(4):334-346.
    doi: 10.1111/age.12797pmc: PMC6617995pubmed: 31199540google scholar: lookup
  33. Grilz-Seger G, Mesaric 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.
  34. Druml T, Neuditschko M, Grilz-Seger G, Horna M, Ricard A, Mesaric M, Cotman M, Pausch H, Brem G. Population Networks Associated with Runs of Homozygosity Reveal New Insights into the Breeding History of the Haflinger Horse.. J Hered 2018 May 11;109(4):384-392.
    doi: 10.1093/jhered/esx114pubmed: 29294044google scholar: lookup
  35. 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 Jan 4;53(1):2.
    doi: 10.1186/s12711-020-00599-7pmc: PMC7784028pubmed: 33397285google scholar: lookup
  36. Zhang Q, Guldbrandtsen B, Bosse M, Lund MS, Sahana G. Runs of homozygosity and distribution of functional variants in the cattle genome.. BMC Genomics 2015 Jul 22;16(1):542.
    doi: 10.1186/s12864-015-1715-xpmc: PMC4508970pubmed: 26198692google scholar: lookup
  37. Marras G, Gaspa G, Sorbolini S, Dimauro C, Ajmone-Marsan P, Valentini A, Williams JL, Macciotta NP. Analysis of runs of homozygosity and their relationship with inbreeding in five cattle breeds farmed in Italy.. Anim Genet 2015 Apr;46(2):110-21.
    doi: 10.1111/age.12259pubmed: 25530322google scholar: lookup
  38. Fornal A, Kowalska K, Zabek T, Piestrzynska-Kajtoch A, Musiał AD, Ropka-Molik K. Genetic Diversity and Population Structure of Polish Konik Horse Based on Individuals from All the Male Founder Lines and Microsatellite Markers.. Animals (Basel) 2020 Sep 3;10(9).
    doi: 10.3390/ani10091569pmc: PMC7552212pubmed: 32899310google scholar: lookup
  39. Kondás K, Szláma G, Trexler M, Patthy L. Both WFIKKN1 and WFIKKN2 have high affinity for growth and differentiation factors 8 and 11.. J Biol Chem 2008 Aug 29;283(35):23677-84.
    doi: 10.1074/jbc.M803025200pmc: PMC3259755pubmed: 18596030google scholar: lookup
  40. Monestier O, Blanquet V. WFIKKN1 and WFIKKN2: "Companion" proteins regulating TGFB activity.. Cytokine Growth Factor Rev 2016 Dec;32:75-84.
    doi: 10.1016/j.cytogfr.2016.06.003pubmed: 27325460google scholar: lookup
  41. Haidet AM, Rizo L, Handy C, Umapathi P, Eagle A, Shilling C, Boue D, Martin PT, Sahenk Z, Mendell JR, Kaspar BK. Long-term enhancement of skeletal muscle mass and strength by single gene administration of myostatin inhibitors.. Proc Natl Acad Sci U S A 2008 Mar 18;105(11):4318-22.
    doi: 10.1073/pnas.0709144105pmc: PMC2393740pubmed: 18334646google scholar: lookup
  42. Brun C, Monestier O, Legardinier S, Maftah A, Blanquet V. Murine GASP-1 N-glycosylation is not essential for its activity on C2C12 myogenic cells but alters its secretion.. Cell Physiol Biochem 2012;30(3):791-804.
    doi: 10.1159/000341458pubmed: 22868230google scholar: lookup
  43. Spurlin BA, Park SY, Nevins AK, Kim JK, Thurmond DC. Syntaxin 4 transgenic mice exhibit enhanced insulin-mediated glucose uptake in skeletal muscle.. Diabetes 2004 Sep;53(9):2223-31.
    doi: 10.2337/diabetes.53.9.2223pubmed: 15331531google scholar: lookup
  44. Yoo M, Kim BG, Lee SJ, Jeong HJ, Park JW, Seo DW, Kim YK, Lee HY, Han JW, Kang JS, Bae GU. Syntaxin 4 regulates the surface localization of a promyogenic receptor Cdo thereby promoting myogenic differentiation.. Skelet Muscle 2015;5:28.
    doi: 10.1186/s13395-015-0052-8pmc: PMC4561423pubmed: 26347807google scholar: lookup
  45. Ono Y, Calhabeu F, Morgan JE, Katagiri T, Amthor H, Zammit PS. BMP signalling permits population expansion by preventing premature myogenic differentiation in muscle satellite cells.. Cell Death Differ 2011 Feb;18(2):222-34.
    doi: 10.1038/cdd.2010.95pmc: PMC3044455pubmed: 20689554google scholar: lookup
  46. Costamagna D, Mommaerts H, Sampaolesi M, Tylzanowski P. Noggin inactivation affects the number and differentiation potential of muscle progenitor cells in vivo.. Sci Rep 2016 Aug 30;6:31949.
    doi: 10.1038/srep31949pmc: PMC5004166pubmed: 27573479google scholar: lookup
  47. Gandini MA, Felix R. Molecular and functional interplay of voltage-gated Ca²⁺ channels with the cytoskeleton.. Curr Mol Pharmacol 2015;8(1):69-80.
  48. Shi N, Guo X, Chen SY. Olfactomedin 2, a novel regulator for transforming growth factor-β-induced smooth muscle differentiation of human embryonic stem cell-derived mesenchymal cells.. Mol Biol Cell 2014 Dec 15;25(25):4106-14.
    doi: 10.1091/mbc.e14-08-1255pmc: PMC4263453pubmed: 25298399google scholar: lookup
  49. Shimoide T, Kawao N, Morita H, Ishida M, Takafuji Y, Kaji H. Roles of Olfactomedin 1 in Muscle and Bone Alterations Induced by Gravity Change in Mice.. Calcif Tissue Int 2020 Aug;107(2):180-190.
    doi: 10.1007/s00223-020-00710-6pubmed: 32462291google scholar: lookup
  50. Bryan K, McGivney BA, Farries G, McGettigan PA, McGivney CL, Gough KF, MacHugh DE, Katz LM, Hill EW. Equine skeletal muscle adaptations to exercise and training: evidence of differential regulation of autophagosomal and mitochondrial components.. BMC Genomics 2017 Aug 9;18(1):595.
    doi: 10.1186/s12864-017-4007-9pmc: PMC5551008pubmed: 28793853google scholar: lookup
  51. Krüger K, Reichel T, Zeilinger C. Role of heat shock proteins 70/90 in exercise physiology and exercise immunology and their diagnostic potential in sports.. J Appl Physiol (1985) 2019 Apr 1;126(4):916-927.
  52. Denham J, McCluskey M, Denham MM, Sellami M, Davie AJ. Epigenetic control of exercise adaptations in the equine athlete: Current evidence and future directions.. Equine Vet J 2021 May;53(3):431-450.
    doi: 10.1111/evj.13320pubmed: 32671871google scholar: lookup
  53. Voisin S, Eynon N, Yan X, Bishop DJ. Exercise training and DNA methylation in humans.. Acta Physiol (Oxf) 2015 Jan;213(1):39-59.
    doi: 10.1111/apha.12414pubmed: 25345837google scholar: lookup
  54. Zhao W, Mu Y, Ma L, Wang C, Tang Z, Yang S, Zhou R, Hu X, Li MH, Li K. Systematic identification and characterization of long intergenic non-coding RNAs in fetal porcine skeletal muscle development.. Sci Rep 2015 Mar 10;5:8957.
    doi: 10.1038/srep08957pmc: PMC4354164pubmed: 25753296google scholar: lookup
  55. Roberts TC, Morris KV, Weinberg MS. Perspectives on the mechanism of transcriptional regulation by long non-coding RNAs.. Epigenetics 2014 Jan;9(1):13-20.
    doi: 10.4161/epi.26700pmc: PMC3928176pubmed: 24149621google scholar: lookup
  56. Bonilauri B, Dallagiovanna B. Long Non-coding RNAs Are Differentially Expressed After Different Exercise Training Programs.. Front Physiol 2020;11:567614.
    doi: 10.3389/fphys.2020.567614pmc: PMC7533564pubmed: 33071823google scholar: lookup
  57. Zheng L, Liu X, Chen P, Xiao W. Expression and role of lncRNAs in the regeneration of skeletal muscle following contusion injury.. Exp Ther Med 2019 Oct;18(4):2617-2627.
    doi: 10.3892/etm.2019.7871pmc: PMC6755471pubmed: 31572510google scholar: lookup
  58. Emerson RO, Thomas JH. Adaptive evolution in zinc finger transcription factors.. PLoS Genet 2009 Jan;5(1):e1000325.
  59. Nail AN, Smith JJ, Peterson ML, Spear BT. Evolutionary Analysis of the Zinc Finger and Homeoboxes Family of Proteins Identifies Multiple Conserved Domains and a Common Early Chordate Ancestor.. Genome Biol Evol 2020 Mar 1;12(3):174-184.
    doi: 10.1093/gbe/evaa039pmc: PMC7144352pubmed: 32125369google scholar: lookup
  60. Cassandri M, Smirnov A, Novelli F, Pitolli C, Agostini M, Malewicz M, Melino G, Raschellà G. Zinc-finger proteins in health and disease.. Cell Death Discov 2017;3:17071.
    doi: 10.1038/cddiscovery.2017.71pmc: PMC5683310pubmed: 29152378google scholar: lookup
  61. Sevane N, Dunner S, Boado A, Cañon J. Polymorphisms in ten candidate genes are associated with conformational and locomotive traits in Spanish Purebred horses.. J Appl Genet 2017 Aug;58(3):355-361.
    doi: 10.1007/s13353-016-0385-ypubmed: 27917442google scholar: lookup
  62. Boyko AR, Brooks SA, Behan-Braman A, Castelhano M, Corey E, Oliveira KC, Swinburne JE, Todhunter RJ, Zhang Z, Ainsworth DM, Robinson NE. Genomic analysis establishes correlation between growth and laryngeal neuropathy in Thoroughbreds.. BMC Genomics 2014 Apr 3;15:259.
    doi: 10.1186/1471-2164-15-259pmc: PMC4051171pubmed: 24707981google scholar: lookup
  63. Metzger J, Schrimpf R, Philipp U, Distl O. Expression levels of LCORL are associated with body size in horses.. PLoS One 2013;8(2):e56497.
  64. Mackiewicz D, de Oliveira PM, Moss de Oliveira S, Cebrat S. Distribution of recombination hotspots in the human genome--a comparison of computer simulations with real data.. PLoS One 2013;8(6):e65272.
  65. Eisen DP, Osthoff M. If there is an evolutionary selection pressure for the high frequency of MBL2 polymorphisms, what is it?. Clin Exp Immunol 2014 May;176(2):165-71.
    doi: 10.1111/cei.12241pmc: PMC3992028pubmed: 24255984google scholar: lookup
  66. Fijarczyk A, Babik W. Detecting balancing selection in genomes: limits and prospects.. Mol Ecol 2015 Jul;24(14):3529-45.
    doi: 10.1111/mec.13226pubmed: 25943689google scholar: lookup
  67. Wang X, Li G, Ruan D, Zhuang Z, Ding R, Quan J, Wang S, Jiang Y, Huang J, Gu T, Hong L, Zheng E, Li Z, Cai G, Wu Z, Yang J. Runs of Homozygosity Uncover Potential Functional-Altering Mutation Associated With Body Weight and Length in Two Duroc Pig Lines.. Front Vet Sci 2022;9:832633.
    doi: 10.3389/fvets.2022.832633pmc: PMC8957889pubmed: 35350434google scholar: lookup
  68. Ke T, Gomez CR, Mateus HE, Castano JA, Wang QK. Novel CACNA1S mutation causes autosomal dominant hypokalemic periodic paralysis in a South American family.. J Hum Genet 2009 Nov;54(11):660-4.
    doi: 10.1038/jhg.2009.92pubmed: 19779499google scholar: lookup
  69. Sintas C, Carreño O, Fernàndez-Castillo N, Corominas R, Vila-Pueyo M, Toma C, Cuenca-León E, Barroeta I, Roig C, Volpini V, Macaya A, Cormand B. Mutation Spectrum in the CACNA1A Gene in 49 Patients with Episodic Ataxia.. Sci Rep 2017 May 31;7(1):2514.
    doi: 10.1038/s41598-017-02554-xpmc: PMC5451382pubmed: 28566750google scholar: lookup
  70. Algahtani H, Shirah B, Algahtani R, Al-Qahtani MH, Abdulkareem AA, Naseer MI. A novel mutation in CACNA1A gene in a Saudi female with episodic ataxia type 2 with no response to acetazolamide or 4-aminopyridine.. Intractable Rare Dis Res 2019 Feb;8(1):67-71.
    doi: 10.5582/irdr.2018.01133pmc: PMC6409113pubmed: 30881862google scholar: lookup
  71. 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
  72. Macario AJ, Grippo TM, Conway de Macario E. Genetic disorders involving molecular-chaperone genes: a perspective.. Genet Med 2005 Jan;7(1):3-12.
  73. Hernandez-Torres F, Aranega AE, Franco D. Identification of regulatory elements directing miR-23a-miR-27a-miR-24-2 transcriptional regulation in response to muscle hypertrophic stimuli.. Biochim Biophys Acta 2014 Sep;1839(9):885-97.
    doi: 10.1016/j.bbagrm.2014.07.009pubmed: 25050919google scholar: lookup
  74. Chinchilla A, Lozano E, Daimi H, Esteban FJ, Crist C, Aranega AE, Franco D. MicroRNA profiling during mouse ventricular maturation: a role for miR-27 modulating Mef2c expression.. Cardiovasc Res 2011 Jan 1;89(1):98-108.
    doi: 10.1093/cvr/cvq264pubmed: 20736237google scholar: lookup
  75. Lozano-Velasco E, Contreras A, Crist C, Hernández-Torres F, Franco D, Aránega AE. Pitx2c modulates Pax3+/Pax7+ cell populations and regulates Pax3 expression by repressing miR27 expression during myogenesis.. Dev Biol 2011 Sep 1;357(1):165-78.
    doi: 10.1016/j.ydbio.2011.06.039pubmed: 21749861google scholar: lookup
  76. Sun Q, Zhang Y, Yang G, Chen X, Zhang Y, Cao G, Wang J, Sun Y, Zhang P, Fan M, Shao N, Yang X. Transforming growth factor-beta-regulated miR-24 promotes skeletal muscle differentiation.. Nucleic Acids Res 2008 May;36(8):2690-9.
    doi: 10.1093/nar/gkn032pmc: PMC2377434pubmed: 18353861google scholar: lookup
  77. Hudson MB, Woodworth-Hobbs ME, Zheng B, Rahnert JA, Blount MA, Gooch JL, Searles CD, Price SR. miR-23a is decreased during muscle atrophy by a mechanism that includes calcineurin signaling and exosome-mediated export.. Am J Physiol Cell Physiol 2014 Mar 15;306(6):C551-8.
    doi: 10.1152/ajpcell.00266.2013pmc: PMC3948973pubmed: 24336651google scholar: lookup
  78. Okamura T, Hashimoto Y, Osaka T, Senmaru T, Fukuda T, Hamaguchi M, Fukui M. miR-23b-3p acts as a counter-response against skeletal muscle atrophy.. J Endocrinol 2020 Mar;244(3):535-547.
    doi: 10.1530/JOE-19-0425pubmed: 31958315google scholar: lookup
  79. Zhou M, Wang Q, Sun J, Li X, Xu L, Yang H, Shi H, Ning S, Chen L, Li Y, He T, Zheng Y. In silico detection and characteristics of novel microRNA genes in the Equus caballus genome using an integrated ab initio and comparative genomic approach.. Genomics 2009 Aug;94(2):125-31.
    doi: 10.1016/j.ygeno.2009.04.006pubmed: 19406225google scholar: lookup
  80. Ferenčaković M, Sölkner J, Curik I. Estimating autozygosity from high-throughput information: effects of SNP density and genotyping errors.. Genet Sel Evol 2013 Oct 29;45(1):42.
    doi: 10.1186/1297-9686-45-42pmc: PMC4176748pubmed: 24168655google scholar: lookup

Citations

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  1. Dementieva N, Nikitkina E, Shcherbakov Y, Nikolaeva O, Mitrofanova O, Ryabova A, Atroshchenko M, Makhmutova O, Zaitsev A. The Genetic Diversity of Stallions of Different Breeds in Russia.. Genes (Basel) 2023 Jul 24;14(7).
    doi: 10.3390/genes14071511pubmed: 37510415google scholar: lookup
  2. Gmel AI, Brem G, Neuditschko M. New genomic insights into the conformation of Lipizzan horses.. Sci Rep 2023 Jun 2;13(1):8990.
    doi: 10.1038/s41598-023-36272-4pubmed: 37268682google scholar: lookup