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Home / Equine Research Bank / BMC Genet / Transcriptome profiling of Arabian horse blood during traini...
BMC genetics2017; 18(1); 31; doi: 10.1186/s12863-017-0499-1

Transcriptome profiling of Arabian horse blood during training regimens.

Abstract: Arabian horses are believed to be one of the oldest and most influential horse breeds in the world. Blood is the main tissue involved in maintaining body homeostasis, and it is considered a marker of the processes taking place in the other tissues. Thus, the aim of our study was to identify the genetic basis of changes occurring in the blood of Arabian horses subjected to a training regimen and to compare the global gene expression profiles between different training periods (T: after a slow canter phase that is considered a conditioning phase, T: after an intense gallop phase, and T: at the end of the racing season) and between trained and untrained horses (T). RNA sequencing was performed on 37 samples with a 75-bp single-end run on a HiScanSQ platform (Illumina), and differentially expressed genes (DEGs) were identified based on DESeq2 (v1.11.25) software. An increase in the number of DEGs between subsequent training periods was observed, and the highest amount of DEGs (440) was detected between untrained horses (T) and horses at the end of the racing season (T). The comparisons of the T vs. T transcriptomes and the T vs. T transcriptomes showed a significant gain of up-regulated genes during long-term exercise (up-regulation of 266 and 389 DEGs in the T period compared to T and T, respectively). Forty differentially expressed genes were detected between the T and T periods, and 296 between T and T. Functional annotation showed that the most abundant genes up-regulated in exercise were involved in pathways regulating cell cycle (PI3K-Akt signalling pathway), cell communication (cAMP-dependent pathway), proliferation, differentiation and apoptosis, as well as immunity processes (Jak-STAT signalling pathway). We investigated whether training causes permanent transcriptome changes in horse blood as a reflection of adaptation to conditioning and the maintenance of fitness to compete in flat races. The present study identified the overrepresented molecular pathways and genes that are essential for maintaining body homeostasis during long-term exercise in Arabian horses. Selected DEGs should be further investigated as markers that are potentially associated with racing performance in Arabian horses.
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Publication Date: 2017-04-05 PubMed ID: 28381206PubMed Central: PMC5382464DOI: 10.1186/s12863-017-0499-1Google Scholar: Lookup
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  • Journal Article
  • Research Support
  • Non-U.S. Gov't

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 explores the genetic changes in the blood of Arabian horses subjected to different training regimens, revealing specific genes and pathways that may be relevant to racing performance.

Objective of the Research

The study aimed to understand the genetic changes that occur in the blood of Arabian horses when they undergo different periods and intensities of training.

Methods and Procedures Used

  • The investigators carried out RNA sequencing on 37 horse blood samples striving to identify Differentially Expressed Genes (DEGs) using DESeq2 software.
  • The samples were obtained from various training phases such as after a slow canter phase, after an intense gallop phase, and at the end of the racing season, as well as from untrained horses.

Key Findings of the Study

  • The number of DEGs increased between subsequent training phases, thus indicating a significant change in gene expression driven by exercise.
  • The study identified the highest number of DEGs (440) between untrained horses and horses at the end of the racing season.
  • There was a significant up-regulation of genes during long-term exercise as shown by comparing the transcriptomes of untrained horses versus horses in various training periods.
  • The researchers detected 40 DEGs between two different periods, and 296 between two others, demonstrating how degrees of training intensity can alter gene expression.

Interpretation of the Results

  • The functional analysis revealed that the most abundant genes up-regulated during exercise were involved in various biological processes, notably cell cycle regulation, cellular communication, proliferation, differentiation, apoptosis, and immunity processes.
  • The findings suggest that the adaptive changes in gene expression during exercise are important for maintaining homeostasis in the horses’ bodies.

Implications and Conclusions

  • This research sheds light on the genes that potentially play a crucial role in maintaining body homeostasis during long-term exercise in Arabian horses.
  • The study opens up the possibility of further exploring these DEGs as potential markers associated with racing performance in Arabian horses.

Cite This Article

APA
Ropka-Molik K, Stefaniuk-Szmukier M, Żukowski K, Piórkowska K, Gurgul A, Bugno-Poniewierska M. (2017). Transcriptome profiling of Arabian horse blood during training regimens. BMC Genet, 18(1), 31. https://doi.org/10.1186/s12863-017-0499-1

Publication

BMC genetics
ISSN: 1471-2156
NlmUniqueID: 100966978
Country: England
Language: English
Volume: 18
Issue: 1
Pages: 31
PII: 31

Researcher Affiliations

Ropka-Molik, Katarzyna
  • Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production, Balice, Poland. katarzyna.ropka@izoo.krakow.pl.
Stefaniuk-Szmukier, Monika
  • Department of Horse Breeding, Institute of Animal Science, University of Agriculture in Cracow, Kracow, Poland.
Żukowski, Kacper
  • Department of Animal Genetics and Breeding, National Research Institute of Animal Production, Balice, Poland.
Piórkowska, Katarzyna
  • Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production, Balice, Poland.
Gurgul, Artur
  • Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production, Balice, Poland.
Bugno-Poniewierska, Monika
  • Department of Genomics and Animal Molecular Biology, National Research Institute of Animal Production, Balice, Poland.

MeSH Terms

  • Animals
  • Cell Cycle
  • DNA / blood
  • Gene Expression Profiling / veterinary
  • Gene Expression Regulation
  • Gene Regulatory Networks
  • Horses / classification
  • Horses / genetics
  • Physical Conditioning, Animal
  • Sequence Analysis, RNA / veterinary
  • Software

References

This article includes 46 references
  1. Holloszy JO, Coyle EF. Adaptations of skeletal muscle to endurance exercise and their metabolic consequences.. J Appl Physiol Respir Environ Exerc Physiol 1984 Apr;56(4):831-8.
    pubmed: 6373687doi: 10.1152/jappl.1984.56.4.831google scholar: lookup
  2. Jacobs RA, Rasmussen P, Siebenmann C, Díaz V, Gassmann M, Pesta D, Gnaiger E, Nordsborg NB, Robach P, Lundby C. Determinants of time trial performance and maximal incremental exercise in highly trained endurance athletes.. J Appl Physiol (1985) 2011 Nov;111(5):1422-30.
    doi: 10.1152/japplphysiol.00625.2011pubmed: 21885805google scholar: lookup
  3. Budgett R. Fatigue and underperformance in athletes: the overtraining syndrome.. Br J Sports Med 1998 Jun;32(2):107-10.
    doi: 10.1136/bjsm.32.2.107pmc: PMC1756078pubmed: 9631215google scholar: lookup
  4. Purvis D, Gonsalves S, Deuster PA. Physiological and psychological fatigue in extreme conditions: overtraining and elite athletes.. PM R 2010 May;2(5):442-50.
    doi: 10.1016/j.pmrj.2010.03.025pubmed: 20656626google scholar: lookup
  5. Bouwman FG, van Ginneken MM, Noben JP, Royackers E, de Graaf-Roelfsema E, Wijnberg ID, van der Kolk JH, Mariman EC, van Breda E. Differential expression of equine muscle biopsy proteins during normal training and intensified training in young standardbred horses using proteomics technology.. Comp Biochem Physiol Part D Genomics Proteomics 2010 Mar;5(1):55-64.
    doi: 10.1016/j.cbd.2009.11.001pubmed: 20374942google scholar: lookup
  6. McGivney BA, Eivers SS, MacHugh DE, MacLeod JN, O'Gorman GM, Park SD, Katz LM, Hill EW. Transcriptional adaptations following exercise in thoroughbred horse skeletal muscle highlights molecular mechanisms that lead to muscle hypertrophy.. BMC Genomics 2009 Dec 30;10:638.
    doi: 10.1186/1471-2164-10-638pmc: PMC2812474pubmed: 20042072google scholar: lookup
  7. McGivney BA, McGettigan PA, Browne JA, Evans AC, Fonseca RG, Loftus BJ, Lohan A, MacHugh DE, Murphy BA, Katz LM, Hill EW. Characterization of the equine skeletal muscle transcriptome identifies novel functional responses to exercise training.. BMC Genomics 2010 Jun 23;11:398.
    doi: 10.1186/1471-2164-11-398pmc: PMC2900271pubmed: 20573200google scholar: lookup
  8. 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 Jan 20;5(1):e8645.
    pmc: PMC2808334pubmed: 20098749doi: 10.1371/journal.pone.0008645google scholar: lookup
  9. Hill EW, McGivney BA, Gu J, Whiston R, Machugh DE. 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 Genomics 2010 Oct 11;11:552.
    pmc: PMC3091701pubmed: 20932346doi: 10.1186/1471-2164-11-552google scholar: lookup
  10. Park KD, Park J, Ko J, Kim BC, Kim HS, Ahn K, Do KT, Choi H, Kim HM, Song S, Lee S, Jho S, Kong HS, Yang YM, Jhun BH, Kim C, Kim TH, Hwang S, Bhak J, Lee HK, Cho BW. Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq.. BMC Genomics 2012 Sep 12;13:473.
    doi: 10.1186/1471-2164-13-473pmc: PMC3472166pubmed: 22971240google scholar: lookup
  11. Capomaccio S, Vitulo N, Verini-Supplizi A, Barcaccia G, Albiero A, D'Angelo M, Campagna D, Valle G, Felicetti M, Silvestrelli M, Cappelli K. RNA sequencing of the exercise transcriptome in equine athletes.. PLoS One 2013;8(12):e83504.
    doi: 10.1371/journal.pone.0083504pmc: PMC3877044pubmed: 24391776google scholar: lookup
  12. Capomaccio S, Cappelli K, Barrey E, Felicetti M, Silvestrelli M, Verini-Supplizi A. Microarray analysis after strenuous exercise in peripheral blood mononuclear cells of endurance horses.. Anim Genet 2010 Dec;41 Suppl 2:166-75.
    doi: 10.1111/j.1365-2052.2010.02129.xpubmed: 21070292google scholar: lookup
  13. Bickel CS, Slade J, Mahoney E, Haddad F, Dudley GA, Adams GR. Time course of molecular responses of human skeletal muscle to acute bouts of resistance exercise.. J Appl Physiol (1985) 2005 Feb;98(2):482-8.
    pubmed: 15465884doi: 10.1152/japplphysiol.00895.2004google scholar: lookup
  14. Dodt M, Roehr JT, Ahmed R, Dieterich C. FLEXBAR-Flexible Barcode and Adapter Processing for Next-Generation Sequencing Platforms.. Biology (Basel) 2012 Dec 14;1(3):895-905.
    doi: 10.3390/biology1030895pmc: PMC4009805pubmed: 24832523google scholar: lookup
  15. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.. BMC Bioinformatics 2011 Aug 4;12:323.
    doi: 10.1186/1471-2105-12-323pmc: PMC3163565pubmed: 21816040google scholar: lookup
  16. Dobin A, Davis CA, Schlesinger F, Drenkow J, Zaleski C, Jha S, Batut P, Chaisson M, Gingeras TR. STAR: ultrafast universal RNA-seq aligner.. Bioinformatics 2013 Jan 1;29(1):15-21.
    doi: 10.1093/bioinformatics/bts635pmc: PMC3530905pubmed: 23104886google scholar: lookup
  17. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.. Genome Biol 2014;15(12):550.
    doi: 10.1186/s13059-014-0550-8pmc: PMC4302049pubmed: 25516281google scholar: lookup
  18. Mi H, Poudel S, Muruganujan A, Casagrande JT, Thomas PD. PANTHER version 10: expanded protein families and functions, and analysis tools.. Nucleic Acids Res 2016 Jan 4;44(D1):D336-42.
    doi: 10.1093/nar/gkv1194pmc: PMC4702852pubmed: 26578592google scholar: lookup
  19. Mutch DM, Berger A, Mansourian R, Rytz A, Roberts MA. The limit fold change model: a practical approach for selecting differentially expressed genes from microarray data.. BMC Bioinformatics 2002 Jun 21;3:17.
    doi: 10.1186/1471-2105-3-17pmc: PMC117238pubmed: 12095422google scholar: lookup
  20. Cappelli K, Felicetti M, Capomaccio S, Spinsanti G, Silvestrelli M, Supplizi AV. Exercise induced stress in horses: selection of the most stable reference genes for quantitative RT-PCR normalization.. BMC Mol Biol 2008 May 19;9:49.
    doi: 10.1186/1471-2199-9-49pmc: PMC2412902pubmed: 18489742google scholar: lookup
  21. Zechner P, Sölknera J, Bodob I, Drumla T, Baumunga R, Achmannc R, Martid E, Habee F, Bremc G. Analysis of diversity and population structure in the Lipizzan horse breed based on pedigree information. Livest Prod Sci 2002;77(2–3):137–46.
    doi: 10.1016/S0301-6226(02)00079-9google scholar: lookup
  22. Prince A, Geor R, Harris P, Hoekstra K, Gardner S, Hudson C, Pagan J. Comparison of the metabolic responses of trained Arabians and Thoroughbreds during high- and low-intensity exercise.. Equine Vet J Suppl 2002 Sep;(34):95-9.
    doi: 10.1111/j.2042-3306.2002.tb05398.xpubmed: 12405666google scholar: lookup
  23. JL L–R, Agüera E, Monterde JG, Rodríguez-Barbudo MV, Miró F. Comparative study of muscle fiber type compositions in the middle gluteal muscle of andalusioan, Thoroughbred and Arabian horses. JEquine VetSci 1989;9:337–340.
  24. Snow DH, Valberg SJ. Muscle anatomy: Adaptations to exercise and training. In: The Athletic Horse: Principles and Practice of Equine Sports Medicine, Sanders, 1994; New York. Rose et al. (eds.) pp 145–179.
  25. Lopez-Rivero L, Letelier A. Skeletal muscle profile of show jumpers: Physiological and pathological considerations in the elite show jumper. In: The Elite Showjumper: Proceedings of the Conference on Equine Sports Medicine and Science, 2000; Ed: A. Lindner. pp 57–76.
  26. Bodine SC, Stitt TN, Gonzalez M, Kline WO, Stover GL, Bauerlein R, Zlotchenko E, Scrimgeour A, Lawrence JC, Glass DJ, Yancopoulos GD. Akt/mTOR pathway is a crucial regulator of skeletal muscle hypertrophy and can prevent muscle atrophy in vivo.. Nat Cell Biol 2001 Nov;3(11):1014-9.
    doi: 10.1038/ncb1101-1014pubmed: 11715023google scholar: lookup
  27. Camera DM, Edge J, Short MJ, Hawley JA, Coffey VG. Early time course of Akt phosphorylation after endurance and resistance exercise.. Med Sci Sports Exerc 2010 Oct;42(10):1843-52.
    doi: 10.1249/MSS.0b013e3181d964e4pubmed: 20195183google scholar: lookup
  28. Sandri M, Sandri C, Gilbert A, Skurk C, Calabria E, Picard A, Walsh K, Schiaffino S, Lecker SH, Goldberg AL. Foxo transcription factors induce the atrophy-related ubiquitin ligase atrogin-1 and cause skeletal muscle atrophy.. Cell 2004 Apr 30;117(3):399-412.
    doi: 10.1016/S0092-8674(04)00400-3pmc: PMC3619734pubmed: 15109499google scholar: lookup
  29. Trenerry MK, Della Gatta PA, Larsen AE, Garnham AP, Cameron-Smith D. Impact of resistance exercise training on interleukin-6 and JAK/STAT in young men.. Muscle Nerve 2011 Mar;43(3):385-92.
    doi: 10.1002/mus.21875pubmed: 21321954google scholar: lookup
  30. Chen M, Feng HZ, Gupta D, Kelleher J, Dickerson KE, Wang J, Hunt D, Jou W, Gavrilova O, Jin JP, Weinstein LS. G(s)alpha deficiency in skeletal muscle leads to reduced muscle mass, fiber-type switching, and glucose intolerance without insulin resistance or deficiency.. Am J Physiol Cell Physiol 2009 Apr;296(4):C930-40.
    doi: 10.1152/ajpcell.00443.2008pmc: PMC2670650pubmed: 19158402google scholar: lookup
  31. Minetti GC, Feige JN, Rosenstiel A, Bombard F, Meier V, Werner A, Bassilana F, Sailer AW, Kahle P, Lambert C, Glass DJ, Fornaro M. Gαi2 signaling promotes skeletal muscle hypertrophy, myoblast differentiation, and muscle regeneration.. Sci Signal 2011 Nov 29;4(201):ra80.
    doi: 10.1126/scisignal.2002038pubmed: 22126963google scholar: lookup
  32. Berdeaux R, Stewart R. cAMP signaling in skeletal muscle adaptation: hypertrophy, metabolism, and regeneration.. Am J Physiol Endocrinol Metab 2012 Jul 1;303(1):E1-17.
    doi: 10.1152/ajpendo.00555.2011pmc: PMC3404564pubmed: 22354781google scholar: lookup
  33. Lopez-Rivero JL, Morales-Lopez JL, Galisteo AM, Aguera E. Muscle fibre type composition in untrained and endurance-trained Andalusian and Arab horses.. Equine Vet J 1991 Mar;23(2):91-3.
    doi: 10.1111/j.2042-3306.1991.tb02727.xpubmed: 2044515google scholar: lookup
  34. Cheng SM, Ho TJ, Yang AL, Chen IJ, Kao CL, Wu FN, Lin JA, Kuo CH, Ou HC, Huang CY, Lee SD. Exercise training enhances cardiac IGFI-R/PI3K/Akt and Bcl-2 family associated pro-survival pathways in streptozotocin-induced diabetic rats.. Int J Cardiol 2013 Jul 31;167(2):478-85.
    doi: 10.1016/j.ijcard.2012.01.031pubmed: 22341695google scholar: lookup
  35. Chelh I, Meunier B, Picard B, Reecy MJ, Chevalier C, Hocquette JF, Cassar-Malek I. Molecular profiles of Quadriceps muscle in myostatin-null mice reveal PI3K and apoptotic pathways as myostatin targets.. BMC Genomics 2009 Apr 27;10:196.
    doi: 10.1186/1471-2164-10-196pmc: PMC2684550pubmed: 19397818google scholar: lookup
  36. Sanchez AM, Candau RB, Bernardi H. FoxO transcription factors: their roles in the maintenance of skeletal muscle homeostasis.. Cell Mol Life Sci 2014 May;71(9):1657-71.
    pubmed: 24232446doi: 10.1007/s00018-013-1513-zgoogle scholar: lookup
  37. 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 Oct 15;307(8):R956-69.
    pubmed: 25121614doi: 10.1152/ajpregu.00187.2014google scholar: lookup
  38. Sanchez AM. FoxO transcription factors and endurance training: a role for FoxO1 and FoxO3 in exercise-induced angiogenesis.. J Physiol 2015 Jan 15;593(2):363-4.
    doi: 10.1113/jphysiol.2014.285999pmc: PMC4303382pubmed: 25630258google scholar: lookup
  39. Takeuchi K, Reue K. Biochemistry, physiology, and genetics of GPAT, AGPAT, and lipin enzymes in triglyceride synthesis.. Am J Physiol Endocrinol Metab 2009 Jun;296(6):E1195-209.
    doi: 10.1152/ajpendo.90958.2008pmc: PMC2692402pubmed: 19336658google scholar: lookup
  40. Geertman JM, van Maris AJ, van Dijken JP, Pronk JT. Physiological and genetic engineering of cytosolic redox metabolism in Saccharomyces cerevisiae for improved glycerol production.. Metab Eng 2006 Nov;8(6):532-42.
    doi: 10.1016/j.ymben.2006.06.004pubmed: 16891140google scholar: lookup
  41. Yang Y, Cao J, Shi Y. Identification and characterization of a gene encoding human LPGAT1, an endoplasmic reticulum-associated lysophosphatidylglycerol acyltransferase.. J Biol Chem 2004 Dec 31;279(53):55866-74.
    doi: 10.1074/jbc.M406710200pubmed: 15485873google scholar: lookup
  42. Nakao R, Hirasaka K, Goto J, Ishidoh K, Yamada C, Ohno A, Okumura Y, Nonaka I, Yasutomo K, Baldwin KM, Kominami E, Higashibata A, Nagano K, Tanaka K, Yasui N, Mills EM, Takeda S, Nikawa T. Ubiquitin ligase Cbl-b is a negative regulator for insulin-like growth factor 1 signaling during muscle atrophy caused by unloading.. Mol Cell Biol 2009 Sep;29(17):4798-811.
    doi: 10.1128/MCB.01347-08pmc: PMC2725709pubmed: 19546233google scholar: lookup
  43. Kim YB, Inoue T, Nakajima R, Shirai-Morishita Y, Tokuyama K, Suzuki M. Effect of long-term exercise on gene expression of insulin signaling pathway intermediates in skeletal muscle.. Biochem Biophys Res Commun 1999 Jan 27;254(3):720-7.
    doi: 10.1006/bbrc.1998.9940pubmed: 9920808google scholar: lookup
  44. Howlett KF, Sakamoto K, Hirshman MF, Aschenbach WG, Dow M, White MF, Goodyear LJ. Insulin signaling after exercise in insulin receptor substrate-2-deficient mice.. Diabetes 2002 Feb;51(2):479-83.
    doi: 10.2337/diabetes.51.2.479pubmed: 11812758google scholar: lookup
  45. Hawley JA, Lessard SJ. Exercise training-induced improvements in insulin action.. Acta Physiol (Oxf) 2008 Jan;192(1):127-35.
    doi: 10.1111/j.1748-1716.2007.01783.xpubmed: 18171435google scholar: lookup
  46. Ennezat PV, Malendowicz SL, Testa M, Colombo PC, Cohen-Solal A, Evans T, LeJemtel TH. Physical training in patients with chronic heart failure enhances the expression of genes encoding antioxidative enzymes.. J Am Coll Cardiol 2001 Jul;38(1):194-8.
    doi: 10.1016/S0735-1097(01)01321-3pubmed: 11451274google scholar: lookup

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  1. Wilson J, De Donato M, Appelbaum B, Garcia CT, Peters S. Differential Expression of Innate and Adaptive Immune Genes during Acute Physical Exercise in American Quarter Horses. Animals (Basel) 2023 Jan 16;13(2).
    doi: 10.3390/ani13020308pubmed: 36670847google scholar: lookup
  2. Polani S, Dean M, Lichter-Peled A, Hendrickson S, Tsang S, Fang X, Feng Y, Qiao W, Avni G, Kahila Bar-Gal G. Sequence Variant in the TRIM39-RPP21 Gene Readthrough is Shared Across a Cohort of Arabian Foals Diagnosed with Juvenile Idiopathic Epilepsy. J Genet Mutat Disord 2022 Jan;1(1).
    pubmed: 35465405
  3. Gabay O, Shoshan Y, Kopel E, Ben-Zvi U, Mann TD, Bressler N, Cohen-Fultheim R, Schaffer AA, Roth SH, Tzur Z, Levanon EY, Eisenberg E. Landscape of adenosine-to-inosine RNA recoding across human tissues. Nat Commun 2022 Mar 4;13(1):1184.
    doi: 10.1038/s41467-022-28841-4pubmed: 35246538google scholar: lookup
  4. Mach N, Moroldo M, Rau A, Lecardonnel J, Le Moyec L, Robert C, Barrey E. Understanding the Holobiont: Crosstalk Between Gut Microbiota and Mitochondria During Long Exercise in Horse. Front Mol Biosci 2021;8:656204.
    doi: 10.3389/fmolb.2021.656204pubmed: 33898524google scholar: lookup
  5. Lee HY, Kim JY, Kim KH, Jeong S, Cho Y, Kim N. Gene Expression Profile in Similar Tissues Using Transcriptome Sequencing Data of Whole-Body Horse Skeletal Muscle. Genes (Basel) 2020 Nov 17;11(11).
    doi: 10.3390/genes11111359pubmed: 33213000google scholar: lookup
  6. Ropka-Molik K, Stefaniuk-Szmukier M, Musiał AD, Velie BD. The Genetics of Racing Performance in Arabian Horses. Int J Genomics 2019;2019:9013239.
    doi: 10.1155/2019/9013239pubmed: 31565654google scholar: lookup
  7. Ropka-Molik K, Stefaniuk-Szmukier M, Szmatoła T, Piórkowska K, Bugno-Poniewierska M. The use of the SLC16A1 gene as a potential marker to predict race performance in Arabian horses. BMC Genet 2019 Sep 11;20(1):73.
    doi: 10.1186/s12863-019-0774-4pubmed: 31510920google scholar: lookup
  8. Stefaniuk-Szmukier M, Szmatoła T, Łątka J, Długosz B, Ropka-Molik K. The Blood and Muscle Expression Pattern of the Equine TCAP Gene during the Race Track Training of Arabian Horses. Animals (Basel) 2019 Aug 18;9(8).
    doi: 10.3390/ani9080574pubmed: 31426609google scholar: lookup
  9. Gurgul A, Jasielczuk I, Semik-Gurgul E, Pawlina-Tyszko K, Stefaniuk-Szmukier M, Szmatoła T, Polak G, Tomczyk-Wrona I, Bugno-Poniewierska M. A genome-wide scan for diversifying selection signatures in selected horse breeds. PLoS One 2019;14(1):e0210751.
    doi: 10.1371/journal.pone.0210751pubmed: 30699152google scholar: lookup
  10. Correia CN, McLoughlin KE, Nalpas NC, Magee DA, Browne JA, Rue-Albrecht K, Gordon SV, MacHugh DE. RNA Sequencing (RNA-Seq) Reveals Extremely Low Levels of Reticulocyte-Derived Globin Gene Transcripts in Peripheral Blood From Horses (Equus caballus) and Cattle (Bos taurus). Front Genet 2018;9:278.
    doi: 10.3389/fgene.2018.00278pubmed: 30154823google scholar: lookup
  11. Ropka-Molik K, Pawlina-Tyszko K, Żukowski K, Piórkowska K, Żak G, Gurgul A, Derebecka N, Wesoły J. Examining the Genetic Background of Porcine Muscle Growth and Development Based on Transcriptome and miRNAome Data. Int J Mol Sci 2018 Apr 16;19(4).
    doi: 10.3390/ijms19041208pubmed: 29659518google scholar: lookup
  12. Mecocci S, Porzio E, Chiaradia E, Pepe M, Paris A, Bergagna S, Pietrucci D, Chillemi G, Beccati F, Cappelli K. Omic technology to monitoring resilience and adaptation to exercise and heat stress in endurance horses. Front Vet Sci 2025;12:1734969.
    doi: 10.3389/fvets.2025.1734969pubmed: 41585523google scholar: lookup
  13. Stefaniuk-Szmukier M, Szmatoła T, Ropka-Molik K. Molecular Signatures of Exercise Adaptation in Arabian Racing Horses: Transcriptomic Insights from Blood and Muscle. Genes (Basel) 2025 Apr 4;16(4).
    doi: 10.3390/genes16040431pubmed: 40282391google scholar: lookup
  14. Wang J, Ren W, Li Z, Li L, Wang R, Ma S, Zeng Y, Meng J, Yao X. Regulatory Mechanisms of Yili Horses During an 80 km Race Based on Transcriptomics and Metabolomics Analyses. Int J Mol Sci 2025 Mar 8;26(6).
    doi: 10.3390/ijms26062426pubmed: 40141070google scholar: lookup
  15. Gmel AI, Mikko S, Ricard A, Velie BD, Gerber V, Hamilton NA, Neuditschko M. Using high-density SNP data to unravel the origin of the Franches-Montagnes horse breed. Genet Sel Evol 2024 Jul 10;56(1):53.
    doi: 10.1186/s12711-024-00922-6pubmed: 38987703google scholar: lookup
  16. Reißmann M, Rajavel A, Kokov ZA, Schmitt AO. Identification of Differentially Expressed Genes after Endurance Runs in Karbadian Horses to Determine Candidates for Stress Indicators and Performance Capability. Genes (Basel) 2023 Oct 24;14(11).
    doi: 10.3390/genes14111982pubmed: 38002925google scholar: lookup
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