Genetic characterisation of the Connemara pony and the Warmblood horse using a within-breed clustering approach.
Abstract: The Connemara pony (CP) is an Irish breed that has experienced varied selection by breeders over the last fifty years, with objectives ranging from the traditional hardy pony to an agile athlete. We compared these ponies with well-studied Warmblood (WB) horses, which are also selectively bred for athletic performance but with a much larger census population. Using genome-wide single nucleotide polymorphism (SNP) and whole-genome sequencing data from 116 WB (94 UK WB and 22 European WB) and 36 CP (33 UK CP and 3 US CP), we studied the genomic diversity, inbreeding and population structure of these breeds. Results: The k-means clustering approach divided both the CP and WB populations into four genetic groups, among which the CP genetic group 1 (C1) associated with non-registered CP, C4 with US CP, WB genetic group 1 (W1) with Holsteiners, and W3 with Anglo European and British WB. Maximum and mean linkage disequilibrium (LD) varied significantly between the two breeds (mean from 0.077 to 0.130 for CP and from 0.016 to 0.370 for WB), but the rate of LD decay was generally slower in CP than WB. The LD block size distribution peaked at 225 kb for all genetic groups, with most of the LD blocks not exceeding 1 Mb. The top 0.5% harmonic mean pairwise fixation index (FST) values identified ontology terms related to cancer risk when the four CP genetic groups were compared. The four CP genetic groups were less inbred than the WB genetic groups, but C2, C3 and C4 had a lower proportion of shorter runs of homozygosity (ROH) (74 to 76% < 4 Mb) than the four WB genetic groups (80 to 85% < 4 Mb), indicating more recent inbreeding. The CP and WB genetic groups had a similar ratio of effective number of breeders (Neb) to effective population size (Ne). Conclusions: Distinct genetic groups of individuals were revealed within each breed, and in WB these genetic groups reflected population substructure better than studbook or country of origin. Ontology terms associated with immune and inflammatory responses were identified from the signatures of selection between CP genetic groups, and while CP were less inbred than WB, the evidence pointed to a greater degree of recent inbreeding. The ratio of Neb to Ne was similar in CP and WB, indicating the influence of popular sires is similar in CP and WB.
© 2023. ’Institut National de Recherche en Agriculture, Alimentation et Environnement (INRAE).
Publication Date: 2023-08-17 PubMed ID: 37592264PubMed Central: PMC10436415DOI: 10.1186/s12711-023-00827-wGoogle 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.
The study investigates the genetic differences between the Connemara pony (CP) and the Warmblood horse (WB) using comprehensive genetic screening and analysis methods. The aim is to provide insights into the genetic diversity, characteristics and potential health risks associated with both breeds.
Genomic Diversity and Breed Classification
- Researchers used whole-genome sequencing data of 116 WB and 36 CP breeds, combining both UK and European versions to analyze their genomic diversity and population structure.
- The k-means clustering approach was used to categorize both CP and WB populations into four distinct genetic groups. These groups reflected certain characteristics such as place of origin (US or UK) and specific breed types (e.g., Holsteiners).
Linkage Disequilibrium (LD) and Inbreeding
- Next, they evaluated linkage disequilibrium (LD), a measure of the non-random association of alleles at different loci in a given population. They found significant differences in LD between the two breeds, with LD decay generally slower in CP than in WB, which means there is less genetic variation within the CP breed.
- Inbreeding levels were evaluated using a measure called runs of homozygosity (ROH), where higher ROH values indicate more inbreeding. The research found that CP was less inbred overall than WB, but there were indications of recent inbreeding in specific CP genetic groups (C2, C3, C4).
Disease Risk and Other Findings
- The study revealed possible health risks tied to certain genetic groups within the CP breed. The highest ranking pairwise fixation index (F) values indicated an association with cancer-related ontology terms when comparing the four CP genetic groups.
- In regards to the ratio of the effective number of breeders (N) to effective population size (N), both CP and WB had similar ratios, indicating that the influence of popular sires, sires that are frequently used for breeding, is similar in both breeds.
Conclusions
- The study successfully highlighted distinct genetic groups within each breed, and showed that WB genetic groups more accurately reflected population substructure than places of origin or studbook classifications.
- The study also identified genetic markers associated with immune and inflammatory responses within CP genetic groups and revealed higher levels of recent inbreeding within the breed, even though overall inbreeding was less in CP than in WB.
- The research provides valuable insight that could be used in the future for making informed breeding decisions and better managing the health risks of both breeds.
Cite This Article
APA
Lindsay-McGee V, Sanchez-Molano E, Banos G, Clark EL, Piercy RJ, Psifidi A.
(2023).
Genetic characterisation of the Connemara pony and the Warmblood horse using a within-breed clustering approach.
Genet Sel Evol, 55(1), 60.
https://doi.org/10.1186/s12711-023-00827-w Publication
Researcher Affiliations
- Royal Veterinary College, London, UK.
- Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
- The Roslin Institute, University of Edinburgh, Edinburgh, UK.
- Scotland's Rural College (SRUC), Edinburgh, UK.
- The Roslin Institute, University of Edinburgh, Edinburgh, UK.
- Royal Veterinary College, London, UK.
- Royal Veterinary College, London, UK. apsifidi@rvc.ac.uk.
MeSH Terms
- Animals
- Horses / genetics
- Inbreeding
- Cluster Analysis
- Genomics
- Homozygote
- Linkage Disequilibrium
Conflict of Interest Statement
The authors declare that they have no competing interests.
References
This article includes 120 references
- Charlesworth D, Willis JH. The genetics of inbreeding depression.. Nat Rev Genet 2009;10:783–796.
- Khadka R. Global horse population with respect to breeds and risk status. Master thesis, Swedish University of Agricultural Sciences; 2010.
- Petersen JL, Mickelson JR, Cothran EG, Andersson LS, Axelsson J, Bailey E. Genetic diversity in the modern horse illustrated from genome-wide SNP data.. PLoS One 2013;8:e54997.
- Westemeier RL, Brawn JD, Simpson SA, Esker TL, Jansen RW, Walk JW. Tracking the long-term decline and recovery of an isolated population.. Science 1998;282:1695–1698.
- Mac Lochlainn T. The Connemara pony: a history.. Loughrea: Loughrea Printing Works; 2021.
- Lyne P. Shrouded in mist: the Connemara pony.. Presteigne: Combe Cottage; 1984.
- Petch E. Connemara pony breeders' society, 1923–1998.. Clifden: Connemara Pony Breeders' Society; 1998.
- Brown CJ. From working to winning: the shifting symbolic value of Connemara ponies in the West of Ireland.. In: Davis DL, Maurstad A, editors. The meaning of horses Biosocial Encounters. London: Routledge, Taylor & Francis Group; 2016. pp. 69–84.
- O'Hare N. Great Connemara Stalions.. Harkaway, Co. Meath Ireland; 2008.
- British Connemara Pony Society. British Connemara Pony Society Stud Book.. 2019.
- Rare Breeds Survival Trust. Watchlist 2021–22: Rare Breeds Survival Trust.. 2021.
- Finno CJ, Stevens C, Young A, Affolter V, Joshi NA, Ramsay S. SERPINB11 frameshift variant associated with novel hoof specific phenotype in Connemara ponies.. PLoS Genet 2015;11:e1005122.
- Connemara Pony Breeders' Society. The Connemara Pony Breeders’ Society Breeding Programme.. 2020.
- British Connemara Pony Society. Hoof wall separation disease.. 2023.
- McGahern A, Edwards CJ, Bower M, Heffernan A, Park S, Brophy P. Mitochondrial DNA sequence diversity in extant Irish horse populations and in ancient horses.. Anim Genet 2006;37:498–502.
- Winton CL, Hegarty MJ, McMahon R, Slavov GT, McEwan NR, Davies-Morel MC. Genetic diversity and phylogenetic analysis of native mountain ponies of Britain and Ireland reveals a novel rare population.. Ecol Evol 2013;3:934–947.
- Khanshour AM, Hempsey EK, Juras R, Cothran E. Genetic characterization of Cleveland bay horse breed.. Diversity 2019;11:174.
- Winton CL, McMahon R, Hegarty MJ, McEwan NR, Davies-Morel MC, Morgan C. Genetic diversity within and between British and Irish breeds: the maternal and paternal history of native ponies.. Ecol Evol 2020;10:1352–1367.
- Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data.. Genetics 2000;155:945–959.
- Bower MA, Campana MG, Whitten M, Edwards CJ, Jones H, Barrett E. The cosmopolitan maternal heritage of the Thoroughbred racehorse breed shows a significant contribution from British and Irish native mares.. Biol Lett 2011;7:316–320.
- Wallin D, Kidd J, Clarke C. The International Warmblood horse: a worldwide guide to breeding and bloodlines.. 2. Buckingham: Kenilworth Press Ltd; 1995.
- Ablondi M, Eriksson S, Tetu S, Sabbioni A, Viklund Å, Mikko S. Genomic divergence in Swedish Warmblood horses selected for equestrian disciplines.. Genes (Basel) 2019;10:976.
- Koenen EPC, Aldridge LI, Philipsson J. An overview of breeding objectives for warmblood sport horses.. Livest Prod Sci 2004;88:77–84.
- Stock K, Distl O. Genetic correlations between performance traits and radiographic findings in the limbs of German Warmblood riding horses.. J Anim Sci 2007;85:31–41.
- Viklund Å, Braam Å, Näsholm A, Strandberg E, Philipsson J. Genetic variation in competition traits at different ages and time periods and correlations with traits at field tests of 4-year-old Swedish Warmblood horses.. Animal 2010;4:682–691.
- Borowska A, Wolc A, Szwaczkowski T. Genetic variability of traits recorded during 100-day stationary performance test and inbreeding level in Polish warmblood stallions.. Arch Anim Breed 2011;54:327–337.
- Schröder W, Klostermann A, Stock KF, Distl O. A genome-wide association study for quantitative trait loci of show-jumping in Hanoverian warmblood horses.. Anim Genet 2012;43:392–400.
- Stewart ID, White IMS, Gilmour AR, Thompson R, Woolliams JA, Brotherstone S. Estimating variance components and predicting breeding values for eventing disciplines and grades in sport horses.. Animal 2012;6:1377–1388.
- Nolte W, Thaller G, Kuehn C. Selection signatures in four German warmblood horse breeds: Tracing breeding history in the modern sport horse.. PLoS One 2019;14:e0215913.
- Eurodressage. German Equestrian Federation Discloses Breeding Statistics for 2018.. 2018.
- Deutsche Reiterliche Vereinigung (FN). Jahresbericht 2022 Bereich Zucht.. 2022.
- Deutsche Reiterliche Vereinigung (FN), Deutches Olympiade-Komitee für Reiterei. Jahresbericht 2021.. 2021.
- Slater J. National Equine Health Survey; Blue Cross.. 2016.
- Slater J. National Equine Health Survey; Blue Cross.. 2017.
- Taylor G, Slater J. National Equine Health Survey; Blue Cross.. 2018.
- Heuer C, Scheel C, Tetens J, Kühn C, Thaller G. Genomic prediction of unordered categorical traits: an application to subpopulation assignment in German Warmblood horses.. Genet Sel Evol 2016;48:13.
- Wright S. Evolution in Mendelian populations.. Genetics 1931;16:97–159.
- Barbato M, Orozco-terWengel P, Tapio M, Bruford MW. SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data.. Front Genet 2015;6:109.
- Jorde PE, Ryman N. Temporal allele frequency change and estimation of effective size in populations with overlapping generations.. Genetics 1995;139:1077–1090.
- Nomura T. Estimation of effective number of breeders from molecular coancestry of single cohort sample.. Evol Appl 2008;1:462–474.
- Alemu SW, Kadri NK, Harland C, Faux P, Charlier C, Caballero A. An evaluation of inbreeding measures using a whole-genome sequenced cattle pedigree.. Heredity (Edinb) 2021;126:410–423.
- Howrigan DP, Simonson MA, Keller MC. Detecting autozygosity through runs of homozygosity: a comparison of three autozygosity detection algorithms.. BMC Genomics 2011;12:460.
- Keller MC, Visscher PM, Goddard ME. Quantification of inbreeding due to distant ancestors and its detection using dense single nucleotide polymorphism data.. Genetics 2011;189:237–249.
- McQuillan R, Leutenegger A-L, Abdel-Rahman R, Franklin CS, Pericic M, Barac-Lauc L. Runs of homozygosity in European populations.. Am J Hum Genet 2008;83:359–372.
- Schaefer RJ, Schubert M, Bailey E, Bannasch DL, Barrey E, Bar-Gal GK. Developing a 670k genotyping array to tag~ 2M SNPs across 24 horse breeds.. BMC Genomics 2017;18:565.
- Van der Auwera GA, O'Connor BD. Genomics in the Cloud: Using Docker, GATK, and WDL in Terra.. Sebastopol: O'Reilly Media; 2020.
- DePristo MA, Banks E, Poplin R, Garimella KV, Maguire JR, Hartl C. A framework for variation discovery and genotyping using next-generation DNA sequencing data.. Nat Genet 2011;43:491–498.
- Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D. PLINK: a tool set for whole-genome association and population-based linkage analyses.. Am J Hum Genet 2007;81:559–575.
- Zhou X, Stephens M. Genome-wide efficient mixed-model analysis for association studies.. Nat Genet 2012;44:821–824.
- Waskom ML. seaborn: statistical data visualization.. J Open Source Softw 2021;6:3021.
- Hunter JD. Matplotlib: A 2D graphics environment.. Comput Sci Eng 2007;9:90–95.
- Kassambra A, Mundt F. factoextra: Extract and visualize the results of multivariate data analyses.. R package version 1.0.7. 2020.
- Seabold S, Perktold J. Statsmodels: Econometric and statistical modeling with python.. In: Proceedings of the 9th Python in Science Conference: 28 June-3 July 2010; Austin; 2010.
- Howey R, Cordell HJ. Mapthin.. 2011.
- Wickham H, François R, Henry L, Müller K. dplyr: A Grammar of Data Manipulation.. R package version 1.0.7 ed. 2021.
- Wickham H. stringr: Simple, consistent wrappers for common string operations.. R package version 1.4.0. 2019.
- Wickham H. ggplot2: Elegant graphics for data analysis.. Dordrecht: Springer-Verlag; 2016.
- Sved JA, Feldman MW. Correlation and probability methods for one and two loci.. Theor Pop Biol 1973;4:129–132.
- Corbin LJ, Liu A, Bishop SC, Woolliams JA. Estimation of historical effective population size using linkage disequilibria with marker data.. J Anim Breed Genet 2012;129:257–270.
- Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O. Scikit-learn: Machine Learning in Python.. J Mach Learn Res 2011;12:2825–2830.
- Lischer HE, Excoffier L. PGDSpider: an automated data conversion tool for connecting population genetics and genomics programs.. Bioinformatics 2012;28:298–299.
- Do C, Waples RS, Peel D, Macbeth G, Tillett BJ, Ovenden JR. NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne) from genetic data.. Mol Ecol Resour 2014;14:209–214.
- Goudet J. Hierfstat, a package for R to compute and test hierarchical F-statistics.. Mol Ecol Notes 2005;5:184–186.
- Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets.. Gigascience 2015;4:7.
- Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D. SciPy 10: Fundamental algorithms for scientific computing in Python.. Nat Methods 2020;17:261–272.
- Turner SD. qqman: an R package for visualizing GWAS results using Q-Q and manhattan plots.. J Open Source Softw 2018;3:731.
- Durinck S, Moreau Y, Kasprzyk A, Davis S, De Moor B, Brazma A. BioMart and Bioconductor: a powerful link between biological databases and microarray data analysis.. Bioinformatics 2005;21:3439–3440.
- Durinck S, Spellman PT, Birney E, Huber W. Mapping identifiers for the integration of genomic datasets with the R/Bioconductor package biomaRt.. Nat Protoc 2009;4:1184–1191.
- Dennis G Jr, Sherman BT, Hosack DA, Yang J, Gao W, Lane HC. DAVID: database for annotation, visualization, and integrated discovery.. Genome Biol 2003;4:R60.
- Ashburner M, Ball CA, Blake JA, Botstein D, Butler H, Cherry JM. Gene ontology: tool for the unification of biology.. Nat Genet 2000;25:25–29.
- Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes.. Nucleic Acids Res 2000;28:27–30.
- Kanehisa M. Toward understanding the origin and evolution of cellular organisms.. Protein Sci 2019;28:1947–1951.
- Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms.. Nucleic Acids Res 2021;49:D545–D551.
- Gene Ontology Consortium The. The Gene Ontology resource: enriching a GOld mine.. Nucleic Acids Res 2021;49:D325–D334.
- Biscarini F, Cozzi P, Gaspa G, Marras G. detectRUNS: Detect runs of homozygosity and runs of heterozygosity in diploid genomes.. R package version 0.9.6. 2019.
- Meyermans R, Gorssen W, Buys N, Janssens S. How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species.. BMC Genomics 2020;21:94.
- Nothnagel M, Lu TT, Kayser M, Krawczak M. Genomic and geographic distribution of SNP-defined runs of homozygosity in Europeans.. Hum Mol Genet 2010;19:2927–2935.
- Quinlan AR, Hall IM. BEDTools: a flexible suite of utilities for comparing genomic features.. Bioinformatics 2010;26:841–842.
- Quinlan AR. BEDTools: the Swiss-army tool for genome feature analysis.. Curr Protoc Bioinformatics .
- Smedley D, Haider S, Ballester B, Holland R, London D, Thorisson G. BioMart—biological queries made easy.. BMC Genomics 2009;10:22.
- Schiavo G, Bovo S, Bertolini F, Tinarelli S, DallOlio S, Costa LN. Comparative evaluation of genomic inbreeding parameters in seven commercial and autochthonous pig breeds.. Animal 2020;14:910–920.
- Jones AT, Ovenden JR, Wang YG. Improved confidence intervals for the linkage disequilibrium method for estimating effective population size.. Heredity (Edinb) 2016;117:217–223.
- Waples RS. Testing for Hardy-Weinberg proportions: Have we lost the plot?. J Hered 2015;106:1–19.
- Nei M. Analysis of gene diversity in subdivided populations.. Proc Natl Acad Sci USA 1973;70:3321–3323.
- SalekArdestani S, Aminafshar M, ZandiBaghcheMaryam MB, Banabazi MH, Sargolzaei M, Miar Y. Whole-genome signatures of selection in sport horses revealed selection footprints related to musculoskeletal system development processes.. Animals (Basel) 2020;10:53.
- Metzger J, Karwath M, Tonda R, Beltran S, Águeda L, Gut M. Runs of homozygosity reveal signatures of positive selection for reproduction traits in breed and non-breed horses.. BMC Genomics 2015;16:764.
- Aurich JE. Artificial insemination in horses—more than a century of practice and research.. J Eq Vet Sci 2012;32:458–463.
- Langlois B, Blouin C. Statistical analysis of some factors affecting the number of horse births in France.. Reprod Nutr Dev 2004;44:583–595.
- Feely D, Brophy P, Quinn K. Characterisation of several Connemara Pony populations.. In: Bodó I, Alderson L, Langlois B, editors. Conservation genetics of endangered horse breeds The European Association for Animal Production Scientific Series. Wageningen: Wageningen Academic; 2005.
- Glowatzki-Mullis M, Muntwyler J, Pfister W, Marti E, Rieder S, Poncet P. Genetic diversity among horse populations with a special focus on the Franches-Montagnes breed.. Anim Genet 2006;37:33–39.
- Grilz-Seger G, Neuditschko M, Ricard A, Velie B, Lindgren G, Mesarič M. Genome-wide homozygosity patterns and evidence for selection in a set of European and near eastern horse breeds.. Genes (Basel) 2019;10:491.
- Schurink A, Shrestha M, Eriksson S, Bosse M, Bovenhuis H, Back W. The gGenomic makeup of nine horse populations smpled in the Netherlands.. Genes (Basel) 2019;10:480.
- Dyson S. Lameness and poor performance in the sport horse: dressage, show jumping and horse trials.. J Eq Vet Sci 2002;22:145–150.
- Anglo European Studbook. Grading Procedures 2023.. .
- The Warmblood Breeders' Studbook UK. Stallion Grading 2023.. .
- The Warmblood Breeders' Studbook UK. Mare Grading 2023.. .
- Holsteiner Verband. Stallions 2023.. .
- Holsteiner Verband. Holsteiner Mares 2023.. .
- Corbin LJ, Blott S, Swinburne J, Vaudin M, Bishop SC, Woolliams JA. Linkage disequilibrium and historical effective population size in the Thoroughbred horse.. Anim Genet 2010;41:8–15.
- Wade C, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F. Genome sequence, comparative analysis, and population genetics of the domestic horse.. Science 2009;326:865–867.
- Próchniak T, Kasperek K, Knaga S, Rozempolska-Rucińska I, Batkowska J, Drabik K. Pedigree analysis of warmblood horses participating in competitions for young horses.. Front Genet 2021;12:658403.
- Feely D, Brophy P, Quinn K. Characterisation of the Connemara pony population in Ireland.. Dublin: University College Dublin; 2003.
- VanRaden PM, Olson KM, Wiggans GR, Cole JB, Tooker ME. Genomic inbreeding and relationships among Holsteins, Jerseys, and Brown Swiss.. J Dairy Sci 2011;94:5673–5682.
- Mancin E, Ablondi M, Mantovani R, Pigozzi G, Sabbioni A, Sartori C. Genetic variability in the Italian heavy draught horse from pedigree data and genomic information.. Animals (Basel) 2020;10:1310.
- Velie BD, Solé M, Fegraeus KJ, Rosengren MK, Røed KH, Ihler C-F. Genomic measures of inbreeding in the Norwegian-Swedish Coldblooded Trotter and their associations with known QTL for reproduction and health traits.. Genet Sel Evol 2019;51:22.
- 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;12:429.
- Saastamoinen M, Maenpaa M. Rare horse breeds in Northern Europe.. In: Bodó I, Alderson L, Langlois B, editors. Conservation genetics of endangered horse breeds. The European Association for Animal Production Scientific Series. Wageningen: Wageningen Academic; 2005.
- McMahon R, Debbonaire A, McEwan N, Nash D, Davies-Morel M, Winton C. Report prepared for the WPCS-2015: a preliminary examination of the genetic variation within and between the improvement society herds of Welsh Mountain ponies.. Felinfach: Welsh Pony and Cob Society; 2015.
- Park W, Kim J, Kim HJ, Choi J, Park J-W, Cho H-W. Investigation of de novo unique differentially expressed genes related to evolution in exercise response during domestication in Thoroughbred race horses.. PLoS One 2014;9:e91418.
- Gourlay CW, Ayscough KR. The actin cytoskeleton: a key regulator of apoptosis and ageing?. Nat Rev Mol Cell Biol 2005;6:583–589.
- Saleem A, Adhihetty PJ, Hood DA. Role of p53 in mitochondrial biogenesis and apoptosis in skeletal muscle.. Physiol Genomics 2009;37:58–66.
- Niess A, Dickhuth H, Northoff H, Fehrenbach E. Free radicals and oxidative stress in exercise–immunological aspects.. Exerc Immunol Rev 1999;5:22–56.
- Dousset E, Avela J, Ishikawa M, Kallio J, Kuitunen S, Kyrolainen H. Bimodal recovery pattern in human skeletal muscle induced by exhaustive stretch-shortening cycle exercise.. Med Sci Sports Exerc 2007;39:453–460.
- Andersson L. How selective sweeps in domestic animals provide new insight into biological mechanisms.. J Intern Med 2012;271:1–14.
- Kim H, Lee T, Park W, Lee JW, Kim J, Lee B-Y. Peeling back the evolutionary layers of molecular mechanisms responsive to exercise-stress in the skeletal muscle of the racing horse.. DNA Res 2013;20:287–298.
- Kingston SG, Hoffman-Goetz L. Effect of environmental enrichment and housing density on immune system reactivity to acute exercise stress.. Physiol Behav 1996;60:145–150.
- Gurgul A, Jasielczuk I, Semik-Gurgul E, Pawlina-Tyszko K, Stefaniuk-Szmukier M, Szmatoła T. A genome-wide scan for diversifying selection signatures in selected horse breeds.. PLoS One 2019;14:e0210751.
- Cannon JG, St Pierre BA. Cytokines in exertion-induced skeletal muscle injury.. Mol Cell Biochem 1998;179:159–168.
- Clarkson PM, Sayers SP. Etiology of exercise-induced muscle damage.. Can J Appl Physiol 1999;24:234–248.
- Kwok AJ, Mentzer A, Knight JC. Host genetics and infectious disease: new tools, insights and translational opportunities.. Nat Rev Genet 2021;22:137–153.
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