Analyze Diet
Animals : an open access journal from MDPI2025; 15(10); doi: 10.3390/ani15101462

Preliminary Study on the Genetic Structure and Functional Candidate Genes of Grassland-Thoroughbreds Based on Whole-Genome Resequencing.

Abstract: Speed and endurance are the primary goals in racehorse breeding. The Grassland-Thoroughbred is a newly developed breed in northern China that combines speed, endurance, and environmental adaptability. However, current research on the genetic background of this breed and the genes associated with athletic performance remains limited. We conducted whole-genome resequencing on Mongolian (MG), Thoroughbred (TB), Xilingol (XL), and Grassland-Thoroughbred (CY) horses, generating 3813.74 Gb of clean data after quality control. The number of transitions was significantly higher than that of transversions. The SNPs were mainly located in intergenic regions, followed by intronic regions. Principal component analysis, population structure analysis, and phylogenetic tree results indicated that the CYs had a distinct genetic background from MGs, TBs, and XLs, but based on PCA and phylogenetic clustering, they showed greater genetic similarity to Thoroughbreds. Using fixation index (Fst) and nucleotide diversity ratio (π ratio) analyses between CYs and the other three horse populations, 70, 76, and 80 candidate genes were identified from the intersection of the two methods, respectively. A total of 179 candidate genes were obtained from the union of the three groups. Candidate genes associated with athletic performance (ATF2, NDUFS7, PRKG1, IGFN1, MTOR, TTN) and growth and development (MTOR, IGFN1, COL21A1, NEDD4, PIEZO1) were screened. These genes are related to athletic ability and developmental processes in the CY population. Our study reveals genomic information associated with important traits in Grassland-Thoroughbreds and identifies valuable candidate genes, laying a foundation for future breeding and trait association studies.
Publication Date: 2025-05-19 PubMed ID: 40427339PubMed Central: PMC12108167DOI: 10.3390/ani15101462Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
  • Journal Article

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.

This research was focused on studying an emerging horse breed in northern China, named the Grassland-Thoroughbred. This breed is gaining popularity for its speed, stamina, and ability to adapt to various environments. The researchers undertook genome sequencing studies on this breed along with three other established horse breeds to identify unique genetic characteristics associated with performance and development. They also identified specific candidate genes linked with these traits, providing a basis for future genetics-based breeding programs.

Background

  • The study, focused on the Grassland-Thoroughbred horse breed in northern China, analyzed its genetic structure with the goal of understanding its traits of speed, endurance, and environmental adaptability. Along with the Grassland-Thoroughbred (CY), three other horse breeds – the Mongolian (MG), Thoroughbred (TB), and Xilingol (XL) were also studied.
  • Existing, pertinent research on this breed is reportedly limited in scope, deepening the relevance of this study to breeders interested in understanding the genetic bases of athletic performance and adaptability.

Methodology

  • The researchers conducted whole-genome resequencing on representatives of four horse breeds. From the collected data, they filtered out the clean data totaling 3813.74 Gb after running quality control measures.
  • Genes of interest or “candidate genes” were identified, and the locations of these genes were tracked chiefly in intergenic regions, followed by intronic zones. These regions define the presence, type, and operation of genes in an organism.

Findings

  • The Grassland-Thoroughbred horses had a unique genetic makeup distinct from the other three breeds, but they showed some similarity with Thoroughbreds according to tests like principal component analysis, population structure analysis, and the construction of a phylogenetic tree.
  • Applying the fixation index (Fst) and nucleotide diversity ratio (π ratio) analyses, the researchers identified groups of candidate genes linked with athletic performance and growth development that could potentially be attributed to the Grassland-Thoroughbreds’ desirable traits.
  • A total of 179 candidate genes were isolated, helping to provide a possible genetic explanation for athleticism and adaptability in the Grassland-Thoroughbred breed.

Conclusion

  • This study generated valuable information on the genetic structure of the Grassland-Thoroughbreds, specifically identifying genes that could be associated with desirable athletic performance and adaptability.
  • The accomplished research sets a solid groundwork for future examination of trait association and can influence directions taken in breeding programs, thereby optimizing the exceptional traits of this breed.

Cite This Article

APA
Ding W, Gong W, Bou T, Shi L, Lin Y, Shi X, Li Z, Wu H, Dugarjaviin M, Bai D, Zhao Y. (2025). Preliminary Study on the Genetic Structure and Functional Candidate Genes of Grassland-Thoroughbreds Based on Whole-Genome Resequencing. Animals (Basel), 15(10). https://doi.org/10.3390/ani15101462

Publication

ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 15
Issue: 10

Researcher Affiliations

Ding, Wenqi
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Gong, Wendian
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Bou, Tugeqin
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Shi, Lin
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Lin, Yanan
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Shi, Xiaoyuan
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Li, Zheng
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Wu, Huize
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Dugarjaviin, Manglai
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Bai, Dongyi
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.
Zhao, Yiping
  • Key Laboratory of Equus Germplasm Innovation (Co-Construction by Ministry and Province), Ministry of Agriculture and Rural Affairs, Hohhot 010018, China.
  • Inner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, Inner Mongolia Agricultural University, Hohhot 010018, China.
  • Equus Research Center, College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China.

Grant Funding

  • U23A20224 / the National Natural Science Foundation of China
  • BR22-11-03 / the Basic Research Operating Expenses of Colleges and Universities Project of the Department of Education of the Inner Mongolia Autonomous Region
  • 2020ZD0004 / construction projects of the Inner Mongolia Science and Technology Department
  • RK2400002235 / the Agricultural and Animal Husbandry Characteristic Seed Industry Project

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 44 references
  1. Moazemi I, Mohammadabadi M, Mostafavi A, Esmailizadeh A, Babenko O, Bushtruk M, Tkachenko S, Stavetska R, Klopenko N. Polymorphism of DMRT3 gene and its association with body measurements in horse breeds.. Russ. J. Genet. 2020;56:1232–1240.
    doi: 10.1134/S1022795420100087google scholar: lookup
  2. International Federation of Horse Racing Authorities. IFHRA Annual Report 2019. International Federation of Horse Racing Authorities; Boulogne, France: 2019.
  3. Chien P.M., Council for Australian University Tourism and Hospitality Education. CAUTHE 2014: Tourism and Hospitality in the Contemporary World: Trends, Changes and Complexity: Trends, Changes and Complexity. School of Tourism, The University of Queensland; Brisbane, Australia: 2014.
  4. Worthington A.C.. National exuberance: A note on the Melbourne Cup effect in Australian stock returns.. Econ. Pap. A J. Appl. Econ. Policy 2007;26:170–179.
  5. Narayan P.K., Smyth R.. The race that stops a nation: The demand for the Melbourne Cup.. Econ. Rec. 2004;80:193–207.
  6. Davis M.. When Things Get Dark: A Mongolian Winter’s Tale. Macmillan; New York, NY, USA: 2010.
  7. Qi B.. Xilin Gol League Animal Husbandry Chronicle. Inner Mongolia People’s Publishing House; Hohhot, China: 2002.
  8. Cassidy R.. The Sport of Kings: Kinship, Class and Thoroughbred Breeding in Newmarket. Cambridge University Press; Cambridge, UK: 2002.
  9. Kay J., Vamplew W.. Encyclopedia of British Horse Racing. Routledge; London, UK: 2012.
  10. Porto-Neto L., Lee S., Sonstegard T., Van Tassell C., Lee H., Gibson J., Gondro C.. Genome-wide detection of signatures of selection in K orean H anwoo cattle.. Anim. Genet. 2014;45:180–190.
    doi: 10.1111/age.12119pubmed: 24494817google scholar: lookup
  11. Zhong X., Hao S., Zhang Z., Zhao Q.-B., Olasege B.S., Qiu-Meng L., Yang Y., Zhang X.-Z., Wang Q.-S., Pan Y.-C.. Genome-wide detection of selective signatures in a Jinhua pig population.. J. Integr. Agric. 2020;19:1314–1322.
  12. Bordbar F., Mohammadabadi M., Jensen J., Xu L., Li J., Zhang L.. Identification of candidate genes regulating carcass depth and hind leg circumference in simmental beef cattle using Illumina Bovine Beadchip and next-generation sequencing analyses.. Animals 2022;12:1103.
    doi: 10.3390/ani12091103pmc: PMC9102740pubmed: 35565529google scholar: lookup
  13. Consortium I.H.. Integrating common and rare genetic variation in diverse human populations.. Nature 2010;467:52.
    doi: 10.1038/nature09298pmc: PMC3173859pubmed: 20811451google scholar: lookup
  14. Consortium G.P.. A map of human genome variation from population scale sequencing.. Nature 2010;467:1061.
    doi: 10.1038/nature09534pmc: PMC3042601pubmed: 20981092google scholar: lookup
  15. Bs W.. Estimating F-statistics for the analysis of population structure.. Evolution 1984;38:1358–1370.
    pubmed: 28563791
  16. Chen S., Zhou Y., Chen Y., Gu J.. Fastp: An ultra-fast all-in-one FASTQ preprocessor.. Bioinformatics 2018;34:i884–i890.
  17. Wingett S.W., Andrews S.. FastQ Screen: A tool for multi-genome mapping and quality control.. F1000Research 2018;7:1338.
  18. Li H., Durbin R.. Fast and accurate short read alignment with Burrows-Wheeler transform.. Bioinformatics 2009;25:1754–1760.
  19. Yurchenko A.A., Deniskova T.E., Yudin N.S., Dotsev A.V., Khamiruev T.N., Selionova M.I., Egorov S.V., Reyer H., Wimmers K., Brem G.. High-density genotyping reveals signatures of selection related to acclimation and economically important traits in 15 local sheep breeds from Russia.. BMC Genom. 2019;20:294.
    doi: 10.1186/s12864-019-5537-0pmc: PMC7227232pubmed: 32039702google scholar: lookup
  20. Wei C., Wang H., Liu G., Zhao F., Kijas J.W., Ma Y., Lu J., Zhang L., Cao J., Wu M.. Genome-wide analysis reveals adaptation to high altitudes in Tibetan sheep.. Sci. Rep. 2016;6:26770.
    doi: 10.1038/srep26770pmc: PMC4882523pubmed: 27230812google scholar: lookup
  21. Purcell S., Neale B., Todd-Brown K., Thomas L., Ferreira M.A., Bender D., Maller J., Sklar P., De Bakker P.I., Daly M.J.. PLINK: A tool set for whole-genome association and population-based linkage analyses.. Am. J. Hum. Genet. 2007;81:559–575.
    doi: 10.1086/519795pmc: PMC1950838pubmed: 17701901google scholar: lookup
  22. Danecek P., Auton A., Abecasis G., Albers C.A., Banks E., DePristo M.A., Handsaker R.E., Lunter G., Marth G.T., Sherry S.T.. The variant call format and VCFtools.. Bioinformatics 2011;27:2156–2158.
  23. Hendricks B.L.. International Encyclopedia of Horse Breeds. University of Oklahoma Press; Norman, OK, USA: 2007.
  24. Wadley G.D., McConell G.K.. High-dose antioxidant vitamin C supplementation does not prevent acute exercise-induced increases in markers of skeletal muscle mitochondrial biogenesis in rats.. J. Appl. Physiol. 2010;108:1719–1726.
  25. Akimoto T., Pohnert S.C., Li P., Zhang M., Gumbs C., Rosenberg P.B., Williams R.S., Yan Z.. Exercise stimulates Pgc-1alpha transcription in skeletal muscle through activation of the p38 MAPK pathway.. J. Biol. Chem. 2005;280:19587–19593.
    doi: 10.1074/jbc.M408862200pubmed: 15767263google scholar: lookup
  26. Chou T.-J., Lu C.-W., Lin L.-Y., Hsu Y.-J., Huang C.-C., Huang K.-C.. Proteomic analysis of skeletal muscle and white adipose tissue after aerobic exercise training in high fat diet induced obese mice.. Int. J. Mol. Sci. 2023;24:5743.
    doi: 10.3390/ijms24065743pmc: PMC10052314pubmed: 36982812google scholar: lookup
  27. Alizadeh R., Salehi O., Rezaeinezhad N., Hosseini S.A.. The effect of high intensity interval training with genistein supplementation on mitochondrial function in the heart tissue of elderly rats.. Exp. Gerontol. 2023;171:112039.
    doi: 10.1016/j.exger.2022.112039pubmed: 36442700google scholar: lookup
  28. Feil R., Hofmann F., Kleppisch T.. Function of cGMP-dependent protein kinases in the nervous system.. Rev. Neurosci. 2005;16:23–41.
    doi: 10.1515/REVNEURO.2005.16.1.23pubmed: 15810652google scholar: lookup
  29. Gao S., Yao W., Zhou R., Pei Z.. Exercise training affects calcium ion transport by downregulating the CACNA2D1 protein to reduce hypertension-induced myocardial injury in mice.. iScience 2024;27:109351.
    doi: 10.1016/j.isci.2024.109351pmc: PMC10940998pubmed: 38495825google scholar: lookup
  30. Lee W., Park K.-D., Taye M., Lee C., Kim H., Lee H.-K., Shin D.. Analysis of cross-population differentiation between Thoroughbred and Jeju horses.. Asian-Australas. J. Anim. Sci. 2017;31:1110.
    doi: 10.5713/ajas.17.0460pmc: PMC6043458pubmed: 29268585google scholar: lookup
  31. Perez K., Ciotlos S., McGirr J., Limbad C., Doi R., Nederveen J.P., Nilsson M.I., Winer D.A., Evans W., Tarnopolsky M.. Single nuclei profiling identifies cell specific markers of skeletal muscle aging, frailty, and senescence.. Aging 2022;14:9393–9422.
    doi: 10.18632/aging.204435pmc: PMC9792217pubmed: 36516485google scholar: lookup
  32. Riedl I., Yoshioka M., Nishida Y., Tobina T., Paradis R., Shono N., Tanaka H., St-Amand J.. Regulation of skeletal muscle transcriptome in elderly men after 6 weeks of endurance training at lactate threshold intensity.. Exp. Gerontol. 2010;45:896–903.
    doi: 10.1016/j.exger.2010.08.014pubmed: 20813182google scholar: lookup
  33. Mascher H., Andersson H., Nilsson P.A., Ekblom B., Blomstrand E.. Changes in signalling pathways regulating protein synthesis in human muscle in the recovery period after endurance exercise.. Acta Physiol. 2007;191:67–75.
  34. Léger B., Cartoni R., Praz M., Lamon S., Dériaz O., Crettenand A., Gobelet C., Rohmer P., Konzelmann M., Luthi F.. Akt signalling through GSK-3β, mTOR and Foxo1 is involved in human skeletal muscle hypertrophy and atrophy.. J. Physiol. 2006;576:923–933.
  35. Stebbings G., Williams A., Herbert A.J., Lockey S., Heffernan S., Erskine R., Morse C., Day S.. TTN genotype is associated with fascicle length and marathon running performance.. Scand. J. Med. Sci. Sports. 2018;28:400–406.
    doi: 10.1111/sms.12927pubmed: 28581678google scholar: lookup
  36. Ding W., Gong W., Bou T., Shi L., Lin Y., Wu H., Dugarjaviin M., Bai D.. Pilot Study on the Profiling and Functional Analysis of mRNA, miRNA, and lncRNA in the Skeletal Muscle of Mongolian Horses, Xilingol Horses, and Grassland-Thoroughbreds.. Animals 2025;15:1123.
    doi: 10.3390/ani15081123pmc: PMC12024394pubmed: 40281957google scholar: lookup
  37. Bodine S.C., Stitt T.N., Gonzalez M., Kline W.O., Stover G.L., Bauerlein R., Zlotchenko E., Scrimgeour A., Lawrence J.C., Glass D.J.. Akt/mTOR pathway is a crucial regulator of skeletal muscle hypertrophy and can prevent muscle atrophy in vivo.. Nat. Cell Biol. 2001;3:1014–1019.
    doi: 10.1038/ncb1101-1014pubmed: 11715023google scholar: lookup
  38. Bentzinger C.F., von Maltzahn J., Dumont N.A., Stark D.A., Wang Y.X., Nhan K., Frenette J., Cornelison D., Rudnicki M.A.. Wnt7a stimulates myogenic stem cell motility and engraftment resulting in improved muscle strength.. J. Cell Biol. 2014;205:97–111.
    doi: 10.1083/jcb.201310035pmc: PMC3987134pubmed: 24711502google scholar: lookup
  39. Li X., Baker J., Cracknell T., Haynes A.R., Blanco G.. IGFN1_v1 is required for myoblast fusion and differentiation.. PLoS ONE 2017;12:e0180217.
  40. Kilpinen S., Ojala K., Kallioniemi O.. Analysis of kinase gene expression patterns across 5681 human tissue samples reveals functional genomic taxonomy of the kinome.. PLoS ONE 2010;5:e15068.
  41. Cracknell T.R.. Revealing the Role of IGFN1 in Skeletal Muscle. University of York; York, UK: 2019.
  42. Wang W., Olson D., Liang G., Franceschi R.T., Li C., Wang B., Wang S.S., Yang S.. Collagen XXIV (Col24α1) promotes osteoblastic differentiation and mineralization through TGF-β/Smads signaling pathway.. Int. J. Biol. Sci. 2012;8:1310.
    doi: 10.7150/ijbs.5136pmc: PMC3492790pubmed: 23139630google scholar: lookup
  43. Bustos F., de la Vega E., Cabezas F., Thompson J., Cornelison D.D., Olwin B.B., Yates J.R. 3rd, Olguín H.C.. NEDD4 Regulates PAX7 Levels Promoting Activation of the Differentiation Program in Skeletal Muscle Precursors.. Stem Cells 2015;33:3138–3151.
    doi: 10.1002/stem.2125pmc: PMC4579044pubmed: 26304770google scholar: lookup
  44. Wang T., Feng S., Zhou H., Mao W., Bai R., Xia Y., Huang J., Zhang R., Lin F.. PIEZO1 activation enhances myogenesis and mitigates muscle degeneration in rotator cuff tear.. Regen. Ther. 2025;28:143–152.
    doi: 10.1016/j.reth.2024.12.002pmc: PMC11699464pubmed: 39759799google scholar: lookup