Genome-Wide DNA Methylation Analysis of Performance Variation in the 5000-m Speed Race of Yili Horses.
Abstract: Whole-genome bisulfite sequencing (WGBS) was employed in this article to map blood DNA methylation profiles at single-base resolution in Yili horses before a 5000 m speed race, with comparative analysis of epigenetic differences between the 'elite group' and 'ordinary group' across six four-year-old stallions. The overall methylation level in the elite group was generally higher than that in the ordinary groups, with a minority of regions showing hypomethylation. For instance, the promoter regions of key metabolic and neuro-related genes exhibited significant hypomethylation. The article identified over 10,000 CG differential methylation regions (DMRs), predominantly enriched in promoter and CpG island regions, anchoring 7221 differentially methylated genes (DMGs). These DMGs were significantly enriched in key biological processes including oxidative phosphorylation, protein binding, axon guidance, glutamatergic synapses, and the Hedgehog signalling pathway. Among these, six genes-ACTN3, MSTN, FOXO1, PPARGC1A, ND1, and ND2-were selected as core candidate genes closely associated with muscle strength, energy metabolism, and stress adaptation. The study confirms that the differences in athletic ability among Yili horses have a significant epigenetic basis, with DNA methylation participating in the epigenetic regulation of athletic traits by modulating the expression of genes related to energy metabolism and neuroplasticity. The constructed "promoter hypomethylated DMR panel" holds promise for translation into non-invasive blood-based epigenetic markers for early performance evaluation and targeted breeding in racehorses. This provides a theoretical basis and molecular targets for improving equine athletic phenotypes and optimising training strategies.
Publication Date: 2026-01-19 PubMed ID: 41594492PubMed Central: PMC12838019DOI: 10.3390/ani16020302Google 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.
Overview
- This study investigated DNA methylation differences in Yili horses to understand how epigenetic factors influence their performance in 5000-meter speed races.
- Researchers compared the blood DNA methylation profiles of elite and ordinary horses to identify epigenetic markers associated with athletic ability.
Background and Objectives
- Yili horses are a breed used in competitive racing, with some individuals displaying superior athletic performance.
- The study aimed to explore epigenetic mechanisms, specifically DNA methylation, underlying performance variability.
- DNA methylation involves adding methyl groups to DNA, potentially regulating gene expression without altering the genetic code.
- Understanding these epigenetic changes could help identify biomarkers for breeding and training strategies.
Methods
- Whole-genome bisulfite sequencing (WGBS) was used to map DNA methylation at single-base resolution.
- Blood samples were taken from six four-year-old Yili stallions categorized into ‘elite’ and ‘ordinary’ groups based on race performance.
- Comparisons were made to detect differences in methylation patterns, particularly in promoter regions and CpG islands.
- Differentially methylated regions (DMRs) and genes (DMGs) were identified and analyzed for biological relevance.
Key Findings
- The overall DNA methylation level was higher in elite horses compared to ordinary ones, indicating a general epigenetic distinction.
- A subset of regions, particularly promoters of genes involved in metabolism and neurological functions, were hypomethylated in elite horses, suggesting increased gene activity in these areas.
- More than 10,000 CG DMRs were found, mainly located within promoter and CpG island regions.
- 7221 differentially methylated genes were linked to biological processes such as:
- Oxidative phosphorylation (energy production in cells)
- Protein binding (cellular interactions)
- Axon guidance (nerve development)
- Glutamatergic synapses (neurotransmission)
- Hedgehog signaling pathway (cell growth and differentiation)
- Six candidate genes were highlighted for their association with physical performance:
- ACTN3: muscle fiber function and strength
- MSTN: regulation of muscle growth
- FOXO1: stress response and metabolism
- PPARGC1A: energy metabolism and mitochondrial function
- ND1 and ND2: components of mitochondrial respiratory chain linked to energy production
Implications
- The study demonstrated a clear epigenetic basis for differences in athletic performance among Yili horses.
- DNA methylation changes appear to regulate genes critical for muscle strength, energy use, and nervous system function, all important for racing success.
- The identified “promoter hypomethylated DMR panel” could be used to develop blood-based tests to evaluate horse performance potential non-invasively.
- This offers promising molecular targets for selective breeding programs aiming to enhance racehorse athleticism.
- It also provides a foundation for optimizing training by understanding the epigenetic regulation of key physiological traits.
Conclusion
- This research bridges genomics and performance by linking epigenetic modifications to athletic traits in horses.
- It pioneers use of whole-genome methylation profiling to reveal how gene regulation differences correspond to variations in speed race performance.
- The findings support further exploration of epigenetic biomarkers for improving equine sports performance and personalized training regimens.
Cite This Article
APA
Shan D, Yao X, Ren W, Huang Q, Su Y, Li Z, Li L, Wang R, Ma S, Wang J.
(2026).
Genome-Wide DNA Methylation Analysis of Performance Variation in the 5000-m Speed Race of Yili Horses.
Animals (Basel), 16(2), 302.
https://doi.org/10.3390/ani16020302 Publication
Researcher Affiliations
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- College of Animal Science, Xinjiang Agricultural University, Urumqi 830052, China.
- Xinjiang Key Laboratory of Equine Breeding and Exercise Physiology, Urumqi 830052, China.
Conflict of Interest Statement
The authors declare no conflicts of interest.
References
This article includes 36 references
- Goldberg AD, Allis CD, Bernstein E. Epigenetics: A landscape takes shape.. Cell 2007;128:635–638.
- Raun SH, Ali MS, Han X, Henríquez-Olguín C, Pham TCP, Meneses-Valdés R, Knudsen JR, Willemsen ACH, Larsen S, Jensen TE. Adenosine monophosphate-activated protein kinase is elevated in human cachectic muscle and prevents cancer-induced metabolic dysfunction in mice.. J. Cachexia Sarcopenia Muscle 2023;14:1631–1647.
- Eivers SS, McGivney BA, Gu J, MacHugh DE, Katz LM, Hill EW. PGC-1α encoded by the PPARGC1A gene regulates oxidative energy metabolism in equine skeletal muscle during exercise.. Anim. Genet. 2011;43:153–162.
- Han H, McGivney BA, Farries G, Katz LM, MacHugh DE, Randhawa IAS, Hill EW. Selection in Australian Thoroughbred horses acts on a locus associated with early two-year old speed.. PLoS ONE 2020;15:e0227212.
- Barrès R, Yan J, Egan B, Treebak JT, Rasmussen M, Fritz T, Caidahl K, Krook A, O’Gorman DJ, Zierath JR. Acute exercise remodels promoter methylation in human skeletal muscle.. Cell Metab. 2012;15:405–411.
- Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA. Circos: An information aesthetic for comparative genomics.. Genome Res. 2009;19:1639–1645.
- Doi A, Park IH, Wen B, Murakami P, Aryee MJ, Irizarry R, Herb B, Ladd-Acosta C, Rho J, Loewer S. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts.. Nat. Genet. 2009;41:1350–1353.
- Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2.. Nat. Methods 2012;9:357–359.
- Krueger F, Andrews SR. Bismark: A flexible aligner and methylation caller for Bisulfite-Seq applications.. Bioinformatics 2011;27:1571–1572.
- Robinson JT, Thorvaldsdóttir H, Winckler W, Guttman M, Lander ES, Getz G, Mesirov JP. Integrative genomics viewer.. Nat. Biotechnol. 2011;29:24–26.
- Wu H, Xu T, Feng H, Chen L, Li B, Yao B, Qin Z, Jin P, Conneely KN. Detection of differentially methylated regions from whole-genome bisulfite sequencing data without replicates.. Nucleic Acids Res. 2015;43:e141.
- Feng H, Conneely KN, Wu H. A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data.. Nucleic Acids Res. 2014;42:e69.
- Park Y, Wu H. Differential methylation analysis for BS-seq data under general experimental design.. Bioinformatics 2016;32:1446–1453.
- Young MD, Wakefield MJ, Smyth GK, Oshlack A. Gene ontology analysis for RNA-seq: Accounting for selection bias.. Genome Biol. 2010;11:R14.
- Kanehisa M, Araki M, Goto S, Hattori M, Hirakawa M, Itoh M, Katayama T, Kawashima S, Okuda S, Tokimatsu T. KEGG for linking genomes to life and the environment.. Nucleic Acids Res. 2008;36:D480–D484.
- Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, Nery JR, Lee L, Ye Z, Ngo QM. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 2009;462:315–322.
- Habibi E, Brinkman AB, Arand J, Kroeze LI, Kerstens HH, Matarese F, Lepikhov K, Gut M, Brun-Heath I, Hubner NC. Whole-genome bisulfite sequencing of two distinct interconvertible DNA methylomes of mouse embryonic stem cells. Cell Stem Cell 2013;13:360–369.
- Irizarry RA, Ladd-Acosta C, Wen B, Wu Z, Montano C, Onyango P, Cui H, Gabo K, Rongione M, Webster M. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat. Genet. 2009;41:178–186.
- Sun D, Xi Y, Rodriguez B, Park HJ, Tong P, Meong M, Goodell MA, Li W. MOABS: Model based analysis of bisulfite sequencing data. Genome Biol. 2014;15:R38.
- Ziller MJ, Gu H, Müller F, Donaghey J, Tsai LT-Y, Kohlbacher O, De Jager PL, Rosen ED, Bennett DA, Bernstein BE. Charting a Dynamic DNA Methylation Landscape of the Human Genome. Nature 2013;500:477–481.
- Chen X, Duan X, Chong Q, Li C, Xiao H, Chen S. Genome-Wide DNA Methylation Differences between Bos indicus and Bos taurus. Animals 2023;13:203.
- Yang N, MacArthur DG, Gulbin JP, Hahn AG, Beggs AH, Easteal S, North K. ACTN3 genotype is associated with human elite athletic performance. Am. J. Hum. Genet. 2003;73:627–631.
- The Gene Ontology Consortium. The Gene Ontology resource: Enriching a gold mine. Nucleic Acids Res. 2021;49:D325–D334.
- Gim JA, Hong CP, Kim DS, Moon JW, Choi Y, Eo J, Kwon YJ, Lee JR, Jung YD, Bae JH. Genome-wide analysis of DNA methylation before-and after exercise in the thoroughbred horse with MeDIP-Seq. Mol. Cells 2015;38:210–220.
- Hill EW, Gu J, Eivers SS, Fonseca RG, McGivney BA, Govindarajan P, Orr N, Katz LM, MacHugh DE. A sequence polymorphism in MSTN predicts sprinting ability and racing stamina in Thoroughbred horses. PLoS ONE 2010;5:e8645.
- Wang J, Ren W, Li Z, Ma S, Li L, Wang R, Zeng Y, Meng J, Yao X. Blood-Based Whole-Genome Methylation Analysis of Yili Horses Pre- and Post-Racing. Animals 2025;15:326.
- Ruas JL, White JP, Rao RR, Kleiner S, Brannan KT, Harrison BC, Greene NP, Wu J, Estall JL, Irving BA. A PGC-1α isoform induced by resistance training regulates skeletal muscle hypertrophy. Cell 2012;151:1319–1331.
- Reik W, Dean W, Walter J. Epigenetic reprogramming in mammalian development. Science 2001;293:1089–1093.
- Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Zhang X, Bernstein BE, Nusbaum C, Jaffe DB. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 2008;45:766–770.
- Mahfouz MM. RNA-directed DNA methylation: Mechanisms and functions. Plant Signal. Behav. 2010;5:956–961.
- Kulis M, Heath S, Bibikova M, Queirós AC, Navarro A, Clot G, Martínez-Trillos A, Castellano G, Brun-Heath I, Pinyol M. Epigenomic analysis detects widespread gene-body DNA hypomethylation in chronic lymphocytic leukemia.. Nat. Genet. 2012;44:1236–1242.
- Roberts LD, Boström P, O’Sullivan JF, Schinzel RT, Lewis GD, Dejam A, Lee YK, Palma MJ, Calhoun S, Georgiadi A. β-Aminoisobutyric acid induces browning of white fat and hepatic β-oxidation and is inversely correlated with cardiometabolic risk factors.. Cell Metab. 2014;19:96–108.
- Wu L, Jiao Y, Li Y, Jiang J, Zhao L, Li M, Li B, Yan Z, Chen X, Li X. Hepatic Gadd45β promotes hyperglycemia and glucose intolerance through DNA demethylation of PGC-1α.. J. Exp. Med. 2021;218:e20201475.
- Murach KA, Dimet-Wiley AL, Wen Y, Brightwell CR, Latham CM, Dungan CM, Fry CS, Watowich SJ. Late-life exercise mitigates skeletal muscle epigenetic aging.. Aging Cell. 2022;21:e13527.
- Vivian CJ, Brinker AE, Koestler DC. Mitochondrial genomic backgrounds affect nuclear DNA methylation and gene expression.. Cancer Res. 2017;77:6202–6214.
- Zhong S, Fei Z, Chen YR, Zheng Y, Huang M, Vrebalov J, McQuinn R, Gapper N, Liu B, Xiang J. Single-base resolution methylomes of tomato fruit development reveal epigenome modifications associated with ripening.. Nat. Biotechnol. 2013;31:154–159.
Citations
This article has been cited 0 times.Use Nutrition Calculator
Check if your horse's diet meets their nutrition requirements with our easy-to-use tool Check your horse's diet with our easy-to-use tool
Talk to a Nutritionist
Discuss your horse's feeding plan with our experts over a free phone consultation Discuss your horse's diet over a phone consultation
Submit Diet Evaluation
Get a customized feeding plan for your horse formulated by our equine nutritionists Get a custom feeding plan formulated by our nutritionists
