Whole-Genome Resequencing Analysis of Athletic Traits in Grassland-Thoroughbred.
Abstract: Speed is not only the primary objective of racehorse breeding but also a crucial indicator for evaluating racehorse performance. This study investigates a newly developed racehorse breed in China. Through whole-genome resequencing, we selected 60 offspring obtained from the crossbreeding of Thoroughbred horses and Xilingol horses for this study. This breed is tentatively named "Grassland-Thoroughbred", and the samples were divided into two groups based on racing ability: 30 racehorses and 30 non-racehorses. Based on whole-genome sequencing data, the study achieved an average sequencing depth of 25.63×. The analysis revealed strong selection pressure on chromosomes (Chr) 1 and 3. Selection signals were detected using methods such as the nucleotide diversity ratio (π ratio), integrated haplotype score (iHS), fixation index (Fst), and cross-population extended haplotype homozygosity (XP-EHH). Regions ranked in the top 5% by at least three methods were designated as candidate regions. This approach detected 215 candidate genes. Additionally, the Fst method was employed to detect Indels, and the top 1% regions detected were considered candidate regions, covering 661 candidate genes. Functional enrichment analysis of the candidate genes suggests that pathways related to immune regulation, neural signal transmission, muscle contraction, and energy metabolism may significantly influence differences in performance. Among these identified genes, , , , , , , , and play crucial roles in muscle function, metabolism, sensory perception, and neurobiology, indicating their key significance in shaping racehorse phenotypes. This study not only enhances understanding of the molecular mechanisms underlying racehorse speed but also provides essential theoretical and practical references for the molecular breeding of Grassland-Thoroughbreds.
Publication Date: 2025-08-07 PubMed ID: 40805113PubMed Central: PMC12346297DOI: 10.3390/ani15152323Google 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 research analyzed the genetic basis of athletic performance in a newly developed Chinese racehorse breed called the Grassland-Thoroughbred by comparing whole-genome data from racehorses and non-racehorses.
- The study identified specific genomic regions and genes related to traits such as muscle function, energy metabolism, neural signaling, and immune regulation that may influence racehorse speed and performance.
Introduction and Research Purpose
- The primary goal of racehorse breeding is to enhance speed, a key measure of racehorse performance.
- This study focused on a newly developed breed in China, the Grassland-Thoroughbred, derived from crossing Thoroughbred and Xilingol horses.
- Understanding the genetic basis of speed and athletic traits in this breed can assist in molecular breeding to improve racehorse performance.
Sample Collection and Grouping
- A total of 60 offspring from Grassland-Thoroughbred crosses were selected.
- These samples were divided into two equal groups based on racing ability: 30 racehorses and 30 non-racehorses.
Whole-Genome Resequencing Methodology
- Whole-genome resequencing was performed on all 60 horses, achieving an average sequencing depth of 25.63×, which ensures detailed and reliable genetic information.
- Genome-wide analyses were conducted to identify signals of selection and genetic variants associated with athletic traits.
Genomic Regions Under Selection
- Strong selection pressure was detected particularly on chromosomes 1 and 3.
- Four statistical methods were used to identify selection signals:
- π ratio (nucleotide diversity ratio)
- Integrated haplotype score (iHS)
- Fixation index (Fst)
- Cross-population extended haplotype homozygosity (XP-EHH)
- Regions identified in the top 5% by at least three of these methods were considered candidate regions related to racing ability, leading to the identification of 215 candidate genes.
- Insertions and deletions (Indels) were also analyzed using the Fst method, and the top 1% regions were designated candidate regions, revealing 661 candidate genes.
Functional Enrichment and Candidate Genes
- Candidate genes were functionally enriched to understand their biological roles and pathways.
- Key pathways identified include:
- Immune regulation
- Neural signal transmission
- Muscle contraction
- Energy metabolism
- The involvement of these pathways suggests they significantly influence racing performance differences.
- Several specific genes were highlighted for their importance in muscle function, metabolism, sensory perception, and neurobiology, underscoring their role in shaping the athletic phenotype of the Grassland-Thoroughbred (the abstract noted several gene names but they were missing—these would typically include genes related to these physiological processes).
Significance of the Study
- This research provides insights into the molecular mechanisms of horse speed and athletic ability, aiding in the understanding of performance variation at the genetic level.
- The findings offer a valuable foundation for molecular breeding strategies aimed at improving racehorse performance in the Grassland-Thoroughbred breed.
- Identifying candidate genes and pathways allows breeders to focus on genetic markers associated with desirable traits, facilitating precision breeding.
Conclusion
- The whole-genome resequencing approach effectively revealed genomic regions and genes under selection related to racing ability in Grassland-Thoroughbreds.
- The integration of multiple methods strengthened the reliability of candidate gene identification.
- Pathways related to muscle, metabolism, neural function, and immunity appear central to the differences in racing performance, highlighting complex biological underpinnings of speed.
- Overall, this study advances the molecular understanding of athletic traits in racehorses and supports breeding programs targeting enhanced racing capabilities.
Cite This Article
APA
Ding W, Gong W, Bou T, Shi L, Lin Y, Shi X, Li Z, Wu H, Dugarjaviin M, Bai D.
(2025).
Whole-Genome Resequencing Analysis of Athletic Traits in Grassland-Thoroughbred.
Animals (Basel), 15(15), 2323.
https://doi.org/10.3390/ani15152323 Publication
Researcher Affiliations
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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 / Inner Mongolia Autonomous Region Science and Technology Program Project
- 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 98 references
- DuBois C, Nakonechny L, Derisoud E, Merkies K. Examining Canadian Equine Industry Participants’ Perceptions of Horses and Their Welfare. Animals 2018;8:201.
- Authorities IFoHR. IFHRA Annual Report 2019. International Federation of Horse Racing Authorities; Boulogne, France: 2019.
- Chien P.M., Council for Australasian Tourism and Hospitality Education. CAUTHE 2014: Tourism and Hospitality in the Contemporary World: Trends, Changes and Complexity. The University of Queensland; Brisbane, Australia: 2014.
- 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.
- Narayan P.K., Smyth R. The race that stops a nation: The demand for the Melbourne Cup. Econ. Rec. 2004;80:193–207.
- Cassidy R. The Sport of Kings: Kinship, Class and Thoroughbred Breeding in Newmarket. Cambridge University Press; Cambridge, UK: 2002.
- Kay J., Vamplew W. Encyclopedia of British horse Racing. Routledge; London, UK: 2012.
- Davis M. When Things Get Dark: A Mongolian Winter’s Tale. Macmillan; London, UK: 2010.
- Qi B. Xilin Gol League Animal Husbandry Chronicle. Inner Mongolia People’s Publishing House; Hohhot, China: 2002.
- Sackton T.B.. Studying Natural Selection in the Era of Ubiquitous Genomes. Trends Genet. 2020;36:792–803.
- Orlando L., Ginolhac A., Zhang G., Froese D., Albrechtsen A., Stiller M., Schubert M., Cappellini E., Petersen B., Moltke I.. Recalibrating Equus evolution using the genome sequence of an early Middle Pleistocene horse. Nature 2013;499:74–78.
- Otey C.A., Rachlin A., Moza M., Arneman D., Carpen O. The palladin/myotilin/myopalladin family of actin-associated scaffolds. Int. Rev. Cytol. 2005;246:31–58.
- Hill E.W., McGivney B.A., Gu J., Whiston R., Machugh D.E.. A genome-wide SNP-association study confirms a sequence variant (g.66493737C>T) in the equine myostatin (MSTN) gene as the most powerful predictor of optimum racing distance for Thoroughbred racehorses. BMC Genom. 2010;11:552.
- Negro Rama S., Valera M., Membrillo A., Gómez M.D., Solé M., Menendez-Buxadera A., Anaya G., Molina A. Quantitative analysis of short- and long-distance racing performance in young and adult horses and association analysis with functional candidate genes in Spanish Trotter horses. J. Anim. Breed. Genet. 2016;133:347–356.
- Jäderkvist Fegraeus K., Velie B.D., Axelsson J., Ang R., Hamilton N.A., Andersson L., Meadows J.R.S., Lindgren G. 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.
- Thomas JC, Khoury R, Neeley CK, Akroush AM, Davies EC. A fast CTAB method of human DNA isolation for polymerase chain reaction applications.. Biochem. Educ. 1997;25:233–235.
- Mazuet C, Legeay C, Sautereau J, Bouchier C, Criscuolo A, Bouvet P, Trehard H, Jourdan Da Silva N, Popoff M. Characterization of Clostridium Baratii Type F Strains Responsible for an Outbreak of Botulism Linked to Beef Meat Consumption in France.. PLoS Curr. 2017;9.
- Chen S, Zhou Y, Chen Y, Gu J. Fastp: An ultra-fast all-in-one FASTQ preprocessor.. Bioinformatics 2018;34:i884–i890.
- Wingett SW, Andrews S. FastQ Screen: A tool for multi-genome mapping and quality control.. F1000Res. 2018;7:1338.
- Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform.. Bioinformatics 2009;25:1754–1760.
- McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M. The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data.. Genome Res. 2010;20:1297–1303.
- Foll M, Gaggiotti O. A genome-scan method to identify selected loci appropriate for both dominant and codominant markers: A Bayesian perspective.. Genetics 2008;180:977–993.
- Wright S. The genetical structure of populations.. Ann. Eugen. 1950;15:323–354.
- Ma Y, Ding X, Qanbari S, Weigend S, Zhang Q, Simianer H. Properties of different selection signature statistics and a new strategy for combining them.. Heredity 2015;115:426–436.
- Weir BS, Cockerham CC. Estimating F-statistics for the analysis of population structure.. Evolution 1984;38:1358–1370.
- Sabeti PC, Schaffner SF, Fry B, Lohmueller J, Varilly P, Shamovsky O, Palma A, Mikkelsen TS, Altshuler D, Lander ES. Positive natural selection in the human lineage.. Science 2006;312:1614–1620.
- Danecek P, Auton A, Abecasis G, Albers CA, Banks E, DePristo MA, Handsaker RE, Lunter G, Marth GT, Sherry ST. The variant call format and VCFtools.. Bioinformatics 2011;27:2156–2158.
- Yang J, Li WR, Lv FH, He SG, Tian SL, Peng WF, Sun YW, Zhao YX, Tu XL, Zhang M. Whole-Genome Sequencing of Native Sheep Provides Insights into Rapid Adaptations to Extreme Environments.. Mol. Biol. Evol. 2016;33:2576–2592.
- Qanbari S, Pausch H, Jansen S, Somel M, Strom TM, Fries R, Nielsen R, Simianer H. Classic selective sweeps revealed by massive sequencing in cattle.. PLoS Genet. 2014;10:e1004148.
- Randhawa IA, Khatkar MS, Thomson PC, Raadsma HW. A meta-assembly of selection signatures in cattle.. PLoS ONE 2016;11:e0153013.
- Voight BF, Kudaravalli S, Wen X, Pritchard JK. A map of recent positive selection in the human genome.. PLoS Biol. 2006;4:e72.
- Browning SR, Browning BL. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering.. Am. J. Hum. Genet. 2007;81:1084–1097.
- Liu Y, Xu L, Yang L, Zhao G, Li J, Liu D, Li Y. Discovery of genomic characteristics and selection signatures in southern Chinese local cattle.. Front. Genet. 2020;11:533052.
- Szpiech ZA, Hernandez RD. Selscan: An efficient multithreaded program to perform EHH-based scans for positive selection.. Mol. Biol. Evol. 2014;31:2824–2827.
- Dennis G, Sherman BT, Jr, Hosack DA, Yang J, Gao W, Lane HC, Lempicki RA. DAVID: Database for Annotation, Visualization, and Integrated Discovery.. Genome Biol. 2003;4:P3.
- Choi JW, Liao X, Stothard P, Chung WH, Jeon HJ, Miller SP, Choi SY, Lee JK, Yang B, Lee KT. Whole-genome analyses of Korean native and Holstein cattle breeds by massively parallel sequencing.. PLoS ONE 2014;9:e101127.
- Choi JW, Liao X, Park S, Jeon HJ, Chung WH, Stothard P, Park YS, Lee JK, Lee KT, Kim SH. Massively parallel sequencing of Chikso (Korean brindle cattle) to discover genome-wide SNPs and InDels.. Mol. Cells. 2013;36:203–211.
- Hill EW, Gu J, McGivney BA, MacHugh DE. Targets of selection in the Thoroughbred genome contain exercise-relevant gene SNPs associated with elite racecourse performance.. Anim. Genet. 2010;41((Suppl. S2)):56–63.
- Han H, McGivney BA, Allen L, Bai D, Corduff LR, Davaakhuu G, Davaasambuu J, Dorjgotov D, Hall TJ, Hemmings AJ. Common protein-coding variants influence the racing phenotype in galloping racehorse breeds.. Commun. Biol. 2022;5:1320.
- Santos WB, Pereira CB, Maiorano AM, Arce CDS, Baldassini WA, Pereira GL, Chardulo LAL, Neto ORM, Oliveira HN, Curi RA. Genomic inbreeding estimation, runs of homozygosity, and heterozygosity-enriched regions uncover signals of selection in the Quarter Horse racing line.. J. Anim. Breed. Genet. 2023;140:583–595.
- 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.
- Eivers SS, McGivney BA, Fonseca RG, MacHugh DE, Menson K, Park SD, Rivero JL, Taylor CT, Katz LM, Hill EW. Alterations in oxidative gene expression in equine skeletal muscle following exercise and training.. Physiol. Genom. 2010;40:83–93.
- Scarpulla RC. Transcriptional paradigms in mammalian mitochondrial biogenesis and function.. Physiol. Rev. 2008;88:611–638.
- Lira VA, Benton CR, Yan Z, Bonen A. PGC-1alpha regulation by exercise training and its influences on muscle function and insulin sensitivity.. Am. J. Physiol. Endocrinol. Metab. 2010;299:E145–E161.
- Lin J, Handschin C, Spiegelman BM. Metabolic control through the PGC-1 family of transcription coactivators.. Cell Metab. 2005;1:361–370.
- Kupr B, Handschin C. Complex Coordination of Cell Plasticity by a PGC-1α-controlled Transcriptional Network in Skeletal Muscle.. Front. Physiol. 2015;6:325.
- Wright DC, Han DH, Garcia-Roves PM, Geiger PC, Jones TE, Holloszy JO. Exercise-induced mitochondrial biogenesis begins before the increase in muscle PGC-1alpha expression.. J. Biol. Chem. 2007;282:194–199.
- Ikeda S, Kizaki T, Haga S, Ohno H, Takemasa T. Acute exercise induces biphasic increase in respiratory mRNA in skeletal muscle.. Biochem. Biophys. Res. Commun. 2008;368:323–328.
- Popov DV, Lysenko EA, Makhnovskii PA, Kurochkina NS, Vinogradova OL. Regulation of PPARGC1A gene expression in trained and untrained human skeletal muscle.. Physiol. Rep. 2017;5:e13339.
- Hashimoto T, Hussien R, Oommen S, Gohil K, Brooks GA. Lactate sensitive transcription factor network in L6 cells: Activation of MCT1 and mitochondrial biogenesis.. Faseb. J. 2007;21:2602–2612.
- Kitaoka Y, Takeda K, Tamura Y, Hatta H. Lactate administration increases mRNA expression of PGC-1α and UCP3 in mouse skeletal muscle.. Appl. Physiol. Nutr. Metab. 2016;41:695–698.
- Zhang SL, Lu WS, Yan L, Wu MC, Xu MT, Chen LH, Cheng H. Association between peroxisome proliferator-activated receptor-gamma coactivator-1alpha gene polymorphisms type 2 diabetes in southern Chinese population: Role of altered interaction with myocyte enhancer factor, 2.C.. Chin. Med. J. 2007;120:1878–1885.
- Lucia A, Gómez-Gallego F, Barroso I, Rabadán M, Bandrés F, San Juan AF, Chicharro JL, Ekelund U, Brage S, Earnest CP. PPARGC1A genotype (Gly482Ser) predicts exceptional endurance capacity in European men.. J. Appl. Physiol. 2005;99:344–348.
- Eynon N, Meckel Y, Sagiv M, Yamin C, Amir R, Sagiv M, Goldhammer E, Duarte JA, Oliveira J. Do PPARGC1A and PPARalpha polymorphisms influence sprint or endurance phenotypes?. Scand. J. Med. Sci. Sports. 2010;20:e145–e150.
- Gineviciene V, Jakaitiene A, Aksenov MO, Aksenova AV, Druzhevskaya AM, Astratenkova IV, Egorova ES, Gabdrakhmanova LJ, Tubelis L, Kucinskas V. Association analysis of ACE, ACTN3 and PPARGC1A gene polymorphisms in two cohorts of European strength and power athletes.. Biol. Sport. 2016;33:199–206.
- Jin HJ, Hwang IW, Kim KC, Cho HI, Park TH, Shin YA, Lee HS, Hwang JH, Kim AR, Lee KH. Is there a relationship between PPARD T294C/PPARGC1A Gly482Ser variations and physical endurance performance in the Korean population?. Genes. Genom. 2016;38:389–395.
- Maciejewska A, Sawczuk M, Cieszczyk P, Mozhayskaya IA, Ahmetov II. The PPARGC1Agene Gly482Ser in Polish Russian athletes.. J. Sports Sci. 2012;30:101–113.
- Cheng Z. FoxOtranscription factors in mitochondrial homeostasis.. Biochem. J. 2022;479:525–536.
- Cheng Z. The FoxO–autophagy axis in health and disease.. Trends Endocrinol. Metab. 2019;30:658–671.
- Cheng Z. FOXO1: Mute for a tuned metabolism?. Trends Endocrinol. Metab. 2015;26:402–403.
- Sedding DG. FoxO transcription factors in oxidative stress response and ageing--a new fork on the way to longevity?. Biol. Chem. 2008;389:279–283.
- Essers MA, de Vries-Smits LM, Barker N, Polderman PE, Burgering BM, Korswagen HC. Functional interaction between beta-catenin and FOXO in oxidative stress signaling.. Science 2005;308:1181–1184.
- Sanchez AM, Candau RB, Bernardi H. FoxO transcription factors: Their roles in the maintenance of skeletal muscle homeostasis.. Cell. Mol. Life Sci. 2014;71:1657–1671.
- Weeks KL, Tham YK, Yildiz SG, Alexander Y, Donner DG, Kiriazis H, Harmawan CA, Hsu A, Bernardo BC, Matsumoto A. FOXO1 is required for physiological cardiac hypertrophy induced by exercise but not by constitutively active, P.I.3.K.. Am. J. Physiol. Heart Circ. Physiol. 2021;320:H1470–H1485.
- Sanchez AM, Bernardi H, Py G, Candau RB. Autophagy is essential to support skeletal muscle plasticity in response to endurance exercise.. Am. J. Physiol.-Regul. Integr. Comp. Physiol. 2014;307:R956–R969.
- Koltai E, Bori Z, Osvath P, Ihasz F, Peter S, Toth G, Degens H, Rittweger J, Boldogh I, Radak Z. Master athletes have higher miR-7, SIRT3 and SOD2 expression in skeletal muscle than age-matched sedentary controls.. Redox Biol. 2018;19:46–51.
- 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. 2012;43:153–162.
- Marín-García J. Cardiomyopathies: A Comparative Analysis of Phenotypes and Genotypes.. Elsevier; Amsterdam, The Netherlands: 2014. pp. 363–426.
- Sabharwal R, Chapleau MW. Autonomic, locomotor and cardiac abnormalities in a mouse model of muscular dystrophy: Targeting the renin–angiotensin system.. Exp. Physiol. 2014;99:627–631.
- Palma-Flores C, Cano-Martínez LJ, Fernández-Valverde F, Torres-Pérez I, de Los Santos S, Hernández-Hernández JM, Hernández-Herrera AF, García S, Canto P, Zentella-Dehesa A. Differential histological features myogenic protein levels in distinct muscles of d-sarcoglycan null muscular dystrophy mouse model.. J. Mol. Histol. 2023;54:405–413.
- Goldstein JA, Kelly SM, LoPresti PP, Heydemann A, Earley JU, Ferguson EL, Wolf MJ, McNally EM. SMAD signaling drives heart and muscle dysfunction in a Drosophila model of muscular dystrophy.. Hum. Mol. Genet. 2011;20:894–904.
- Bround MJ, Havens JR, York AJ, Sargent MA, Karch J, Molkentin JD. ANT-dependent MPTP underlies necrotic myofiber death in muscular dystrophy.. Sci. Adv. 2023;9:eadi2767.
- Bessho C, Yamada S, Tanida T, Tanaka M. FoxP2 protein decreases at a specific region in the chick midbrain after hatching.. Neurosci. Lett. 2023;800:137119.
- Fisher SE, Scharff C. FOXP2 as a molecular window into speech and language.. Trends Genet. 2009;25:166–177.
- Rodríguez-Urgellés E, Casas-Torremocha D, Sancho-Balsells A, Ballasch I, García-García E, Miquel-Rio L, Manasanch A, Del Castillo I, Chen W, Pupak A. Thalamic Foxp2 regulates output connectivity and sensory-motor impairments in a model of Huntington’s Disease.. Cell Mol. Life Sci. 2023;80:367.
- Feil R, Hofmann F, Kleppisch T. Function of cGMP-dependent protein kinases in the nervous system.. Rev. Neurosci. 2005;16:23–41.
- 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.
- Woodhead JST, Merry TL. Mitochondrial-derived peptides and exercise.. Biochim. Biophys. Acta Gen. Subj. 2021;1865:130011.
- Many GM, Sanford JA, Sagendorf TJ, Hou Z, Nigro P, Whytock KL, Amar D, Caputo T, Gay NR, Gaul DA. Sexual dimorphism and the multi-omic response to exercise training in rat subcutaneous white adipose tissue.. Nat. Metab. 2024;6:963–979.
- Tan B, Li X, Yin Y, Wu Z, Liu C, Tekwe CD, Wu G. Regulatory roles for L-arginine in reducing white adipose tissue.. Front. Biosci. 2012;17:2237–2246.
- Viegas CM, Zanatta A, Knebel LA, Schuck PF, Tonin AM, Ferreira Gda C, Amaral AU, Dutra Filho CS, Wannmacher CM, Wajner M. Experimental evidence that ornithine and homocitrulline disrupt energy metabolism in brain of young rats.. Brain Res. 2009;1291:102–112.
- Lee YM, Choi DH, Cheon MW, Kim JG, Kim JS, Shin MG, Kim HR, Youn D. Changes in Mitochondria-Related Gene Expression upon Acupuncture at LR3 in the D-Galactosamine-Induced Liver Damage Rat Model.. Evid. Based Complement. Alternat. Med. 2022;2022:3294273.
- Kay L, Nicolay K, Wieringa B, Saks V, Wallimann T. Direct evidence for the control of mitochondrial respiration by mitochondrial creatine kinase in oxidative muscle cells in situ.. J. Biol. Chem. 2000;275:6937–6944.
- Touron J, Perrault H, Maisonnave L, Patrac V, Walrand S, Malpuech-Brugere C, Pereira B, Burelle Y, Costes F, Richard R. Effects of exercise-induced metabolic and mechanical loading on skeletal muscle mitochondrial function in male rats.. J. Appl. Physiol. 2022;133:611–621.
- Kang S, Kang BH. Structure Function Inhibitors of the Mitochondrial Chaperone TRAP1.. J. Med. Chem. 2022;65:16155–16172.
- Lisanti S, Tavecchio M, Chae YC, Liu Q, Brice AK, Thakur ML, Languino LR, Altieri DC. Deletion of the mitochondrial chaperone TRAP-1 uncovers global reprogramming of metabolic networks.. Cell Rep. 2014;8:671–677.
- Schmidt JF, Andersen TR, Andersen LJ, Randers MB, Hornstrup T, Hansen PR, Bangsbo J, Krustrup P. Cardiovascular function is better in veteran football players than age-matched untrained elderly healthy men. Scand. J. Med. Sci. Sports. 2015;25:61–69.
- Mancini A, Vitucci D, Randers MB, Schmidt JF, Hagman M, Andersen TR, Imperlini E, Mandola A, Orrù S, Krustrup P. Lifelong Football Training: Effects on Autophagy and Healthy Longevity Promotion.. Front. Physiol. 2019;10:132.
- Mills RE, Pittard WS, Mullaney JM, Farooq U, Creasy TH, Mahurkar AA, Kemeza DM, Strassler DS, Ponting CP, Webber C. Natural genetic variation caused by small insertions and deletions in the human genome.. Genome Res. 2011;21:830–839.
- Chen X, Nie S, Hu L, Fang Y, Cui W, Xu H, Zhao C, Zhu BF. Forensic efficacy evaluation and genetic structure exploration of the Yunnan Miao group by a multiplex InDel panel.. Electrophoresis. 2022;43:1765–1773.
- Huang Y, Liu C, Xiao C, Chen X, Han X, Yi S, Huang D. Mutation analysis of 28 autosomal short tandem repeats in the Chinese Han population.. Mol. Biol. Rep. 2021;48:5363–5369.
- Chen CH, Chuang TJ, Liao BY, Chen FC. Scanning for the signatures of positive selection for human-specific insertions and deletions.. Genome Biol. Evol. 2009;1:415–419.
- Boschiero C, Moreira GCM, Gheyas AA, Godoy TF, Gasparin G, Mariani P, Paduan M, Cesar ASM, Ledur MC, Coutinho LL. Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines.. BMC Genom. 2018;19:83.
- Rooney MF, Hill EW, Kelly VP, Porter RK. The “speed gene” effect of myostatin arises in Thoroughbred horses due to a promoter proximal SINE insertion.. PLoS ONE. 2018;13:e0205664.
- Petersen JL, Valberg SJ, Mickelson JR, McCue ME. Haplotype diversity in the equine myostatin gene with focus on variants associated with race distance propensity and muscle fiber type proportions.. Anim. Genet. 2014;45:827–835.
- 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;12:450–455.
- Biglari S, Afousi AG, Mafi F, Shabkhiz F. High-intensity interval training-induced hypertrophy in gastrocnemius muscle via improved IGF-I/Akt/FoxO and myostatin/Smad signaling pathways in rats.. Physiol. Int. 2020;107:220–230.
- Korge P. Factors limiting adenosine triphosphatase function during high intensity exercise. Thermodynamic and regulatory considerations.. Sports Med. 1995;20:215–225.
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