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Home / Equine Research Bank / J Appl Genet / RNA sequencing as a powerful tool in searching for genes inf...
Journal of applied genetics2015; 57(2); 199-206; doi: 10.1007/s13353-015-0320-7

RNA sequencing as a powerful tool in searching for genes influencing health and performance traits of horses.

Abstract: RNA sequencing (RNA-seq) by next-generation technology is a powerful tool which creates new possibilities in whole-transcriptome analysis. In recent years, with the use of the RNA-seq method, several studies expanded transcriptional gene profiles to understand interactions between genotype and phenotype, supremely contributing to the field of equine biology. To date, in horses, massive parallel sequencing of cDNA has been successfully used to identify and quantify mRNA levels in several normal tissues, as well as to annotate genes. Moreover, the RNA-seq method has been applied to identify the genetic basis of several diseases or to investigate organism adaptation processes to the training conditions. The use of the RNA-seq approach has also confirmed that horses can be useful as a large animal model for human disease, especially in the field of immune response. The presented review summarizes the achievements of profiling gene expression in horses (Equus caballus).
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Publication Date: 2015-10-07 PubMed ID: 26446669DOI: 10.1007/s13353-015-0320-7Google Scholar: Lookup
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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 study discusses the use of RNA sequencing, a modern technology, in identifying genes that impact health and performance traits in horses. This tool has widened the horizons in transcriptome analysis, providing new insights into the interactions between genotype and phenotype, and largely contributing to equine biology.

Understanding Next-Generation RNA Sequencing in Studying Horses

  • The main focus of this research is the utilization of RNA sequencing (RNA-seq), a next-generation technology, for analyzing whole transcriptomes. A transcriptome represents the set of all RNA molecules, including mRNA, rRNA, tRNA, and other non-coding RNA transcribed in one cell or a population of cells.
  • This method offers a deep understanding of the genetic make-up and functioning of horses and their health and performance traits. It is a fundamental tool to analyze horse genetics, genome annotation, and gene expression profiling.

Applications of RNA-Sequencing in Equine Studies

  • The researchers have employed RNA-seq to examine horse genomics at the transcriptome level. This method has been successfully used to identify and quantify mRNA levels in several normal tissues of horses, and to annotate genes, enhancing the existing knowledge about equine genetics.
  • RNA-seq has also proven useful in identifying genetic causes of various diseases affecting horses. Moreover, it has been implemented to investigate organism adaptation processes in response to training conditions, hence contributing significantly to understanding horses’ performance characteristics.

Horses as a Large Animal Model for Human Disease

  • One of the key findings of the study is the applicability of the RNA-seq approach to consider horses as a valuable large animal model for human diseases, particularly in immune response studies.
  • This finding reveals two significant aspects: firstly, the commonality between horse and human immune responses, and secondly, further potential for sequencing technologies like RNA-seq in translational research. This leads to better understanding and treatment of human diseases.

Overall Achievements of RNA-Sequencing in Equine Research

  • The article overall provides a review summarizing the achievements of profiling gene expression in horses utilizing RNA-seq. It highlights how this revolutionary technology has been a game-changer in equine biology and related studies, opening up new research opportunities and applications for genetic analysis and disease identification.

Cite This Article

APA
Stefaniuk M, Ropka-Molik K. (2015). RNA sequencing as a powerful tool in searching for genes influencing health and performance traits of horses. J Appl Genet, 57(2), 199-206. https://doi.org/10.1007/s13353-015-0320-7

Publication

Journal of applied genetics
ISSN: 2190-3883
NlmUniqueID: 9514582
Country: England
Language: English
Volume: 57
Issue: 2
Pages: 199-206

Researcher Affiliations

Stefaniuk, Monika
  • Department of Horse Breeding, Institute of Animal Science, University of Agriculture in Cracow, al. Mickiewicza 24/28, 30-059, Cracow, Poland. m.k.stefaniuk@gmail.com.
Ropka-Molik, Katarzyna
  • Laboratory of Genomics, National Research Institute of Animal Production, Krakowska 1, 32-083, Balice, Poland.

MeSH Terms

  • Animals
  • Disease Models, Animal
  • Gene Expression Profiling
  • High-Throughput Nucleotide Sequencing
  • Horses / genetics
  • Phenotype
  • Sequence Analysis, RNA / veterinary
  • Transcriptome

References

This article includes 57 references
  1. Coleman SJ, Zeng Z, Wang K, Luo S, Khrebtukova I, Mienaltowski MJ, Schroth GP, Liu J, MacLeod JN. Structural annotation of equine protein-coding genes determined by mRNA sequencing.. Anim Genet 2010 Dec;41 Suppl 2:121-30.
    pubmed: 21070285doi: 10.1111/j.1365-2052.2010.02118.xgoogle scholar: lookup
  2. Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics.. Nat Rev Genet 2009 Jan;10(1):57-63.
    pubmed: 19015660doi: 10.1038/nrg2484google scholar: lookup
  3. Switonski M, Mankowska M, Salamon S. Family of melanocortin receptor (MCR) genes in mammals-mutations, polymorphisms and phenotypic effects.. J Appl Genet 2013 Nov;54(4):461-72.
    pubmed: 23996627doi: 10.1007/s13353-013-0163-zgoogle scholar: lookup
  4. 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.
    pubmed: 20098749doi: 10.1371/journal.pone.0008645google scholar: lookup
  5. Horohov DW. The equine immune responses to infectious and allergic disease: a model for humans?. Mol Immunol 2015 Jul;66(1):89-96.
    pubmed: 25457878doi: 10.1016/j.molimm.2014.09.020google scholar: lookup
  6. Haase B, Signer-Hasler H, Binns MM, Obexer-Ruff G, Hauswirth R, Bellone RR, Burger D, Rieder S, Wade CM, Leeb T. Accumulating mutations in series of haplotypes at the KIT and MITF loci are major determinants of white markings in Franches-Montagnes horses.. PLoS One 2013;8(9):e75071.
    pubmed: 24098679doi: 10.1371/journal.pone.0075071google scholar: lookup
  7. Kim MC, Lee SW, Ryu DY, Cui FJ, Bhak J, Kim Y. Identification and characterization of microRNAs in normal equine tissues by Next Generation Sequencing.. PLoS One 2014;9(4):e93662.
    pubmed: 24695583doi: 10.1371/journal.pone.0093662google scholar: lookup
  8. Vilà C, Leonard JA, Gotherstrom A, Marklund S, Sandberg K, Liden K, Wayne RK, Ellegren H. Widespread origins of domestic horse lineages.. Science 2001 Jan 19;291(5503):474-7.
    pubmed: 11161199doi: 10.1126/science.291.5503.474google scholar: lookup
  9. Desjardin C, Vaiman A, Mata X, Legendre R, Laubier J, Kennedy SP, Laloe D, Barrey E, Jacques C, Cribiu EP, Schibler L. Next-generation sequencing identifies equine cartilage and subchondral bone miRNAs and suggests their involvement in osteochondrosis physiopathology.. BMC Genomics 2014 Sep 17;15(1):798.
    pubmed: 25227120doi: 10.1186/1471-2164-15-798google scholar: lookup
  10. Brehm W, Burk J, Delling U. Application of stem cells for the treatment of joint disease in horses.. Methods Mol Biol 2014;1213:215-28.
    pubmed: 25173386doi: 10.1007/978-1-4939-1453-1_18google scholar: lookup
  11. Dirschl DR, Marsh JL, Buckwalter JA, Gelberman R, Olson SA, Brown TD, Llinias A. Articular fractures.. J Am Acad Orthop Surg 2004 Nov-Dec;12(6):416-23.
    pubmed: 15615507doi: 10.5435/00124635-200411000-00006google scholar: lookup
  12. Brommer H, Laasanen MS, Brama PA, van Weeren PR, Helminen HJ, Jurvelin JS. Functional consequences of cartilage degeneration in the equine metacarpophalangeal joint: quantitative assessment of cartilage stiffness.. Equine Vet J 2005 Sep;37(5):462-7.
    pubmed: 16163950doi: 10.2746/042516405774480012google scholar: lookup
  13. McIlwraith CW, Frisbie DD, Kawcak CE. The horse as a model of naturally occurring osteoarthritis.. Bone Joint Res 2012 Nov;1(11):297-309.
    pubmed: 23610661doi: 10.1302/2046-3758.111.2000132google scholar: lookup
  14. Giese A, Jude R, Kuiper H, Raudsepp T, Piumi F, Schambony A, Guérin G, Chowdhary BP, Distl O, Töpfer-Petersen E, Leeb T. Molecular characterization of the equine testis-specific protein 1 (TPX1) and acidic epididymal glycoprotein 2 (AEG2) genes encoding members of the cysteine-rich secretory protein (CRISP) family.. Gene 2002 Oct 16;299(1-2):101-9.
    pubmed: 12459257doi: 10.1016/s0378-1119(02)01018-1google scholar: lookup
  15. Sarrafian TL, Garcia TC, Dienes EE, Murphy B, Stover SM, Galuppo LD. A nonterminal equine mandibular model of bone healing.. Vet Surg 2015 Apr;44(3):314-21.
    pubmed: 25258299doi: 10.1111/j.1532-950X.2014.12279.xgoogle scholar: lookup
  16. Tozaki T, Miyake T, Kakoi H, Gawahara H, Sugita S, Hasegawa T, Ishida N, Hirota K, Nakano Y. A genome-wide association study for racing performances in Thoroughbreds clarifies a candidate region near the MSTN gene.. Anim Genet 2010 Dec;41 Suppl 2:28-35.
    pubmed: 21070273doi: 10.1111/j.1365-2052.2010.02095.xgoogle scholar: lookup
  17. Li Z, Sergouniotis PI, Michaelides M, Mackay DS, Wright GA, Devery S, Moore AT, Holder GE, Robson AG, Webster AR. Recessive mutations of the gene TRPM1 abrogate ON bipolar cell function and cause complete congenital stationary night blindness in humans.. Am J Hum Genet 2009 Nov;85(5):711-9.
    pubmed: 19878917doi: 10.1016/j.ajhg.2009.10.003google scholar: lookup
  18. Liew CC, Ma J, Tang HC, Zheng R, Dempsey AA. The peripheral blood transcriptome dynamically reflects system wide biology: a potential diagnostic tool.. J Lab Clin Med 2006 Mar;147(3):126-32.
    pubmed: 16503242doi: 10.1016/j.lab.2005.10.005google scholar: lookup
  19. Neundorf RH, Lowerison MB, Cruz AM, Thomason JJ, McEwen BJ, Hurtig MB. Determination of the prevalence and severity of metacarpophalangeal joint osteoarthritis in Thoroughbred racehorses via quantitative macroscopic evaluation.. Am J Vet Res 2010 Nov;71(11):1284-93.
    pubmed: 21034319doi: 10.2460/ajvr.71.11.1284google scholar: lookup
  20. Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq.. Bioinformatics 2009 May 1;25(9):1105-11.
    pubmed: 19289445doi: 10.1093/bioinformatics/btp120google scholar: lookup
  21. Coleman SJ, Zeng Z, Hestand MS, Liu J, Macleod JN. Analysis of unannotated equine transcripts identified by mRNA sequencing.. PLoS One 2013;8(7):e70125.
    pubmed: 23922931doi: 10.1371/journal.pone.0070125google scholar: lookup
  22. Tryon RC, White SD, Bannasch DL. Homozygosity mapping approach identifies a missense mutation in equine cyclophilin B (PPIB) associated with HERDA in the American Quarter Horse.. Genomics 2007 Jul;90(1):93-102.
    pubmed: 17498917doi: 10.1016/j.ygeno.2007.03.009google scholar: lookup
  23. 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.
    pubmed: 20932346doi: 10.1186/1471-2164-11-552google scholar: lookup
  24. Bryant CE, Ouellette A, Lohmann K, Vandenplas M, Moore JN, Maskell DJ, Farnfield BA. The cellular Toll-like receptor 4 antagonist E5531 can act as an agonist in horse whole blood.. Vet Immunol Immunopathol 2007 Apr 15;116(3-4):182-9.
    pubmed: 17320193doi: 10.1016/j.vetimm.2007.01.013google scholar: lookup
  25. Chitwood JL, Rincon G, Kaiser GG, Medrano JF, Ross PJ. RNA-seq analysis of single bovine blastocysts.. BMC Genomics 2013 May 25;14:350.
    pubmed: 23705625doi: 10.1186/1471-2164-14-350google scholar: lookup
  26. Johnson PJ, Wiedmeyer CE, Messer NT, Ganjam VK. Medical implications of obesity in horses--lessons for human obesity.. J Diabetes Sci Technol 2009 Jan;3(1):163-74.
    pubmed: 20046661doi: 10.1177/193229680900300119google scholar: lookup
  27. Grabherr MG, Haas BJ, Yassour M, Levin JZ, Thompson DA, Amit I, Adiconis X, Fan L, Raychowdhury R, Zeng Q, Chen Z, Mauceli E, Hacohen N, Gnirke A, Rhind N, di Palma F, Birren BW, Nusbaum C, Lindblad-Toh K, Friedman N, Regev A. Full-length transcriptome assembly from RNA-Seq data without a reference genome.. Nat Biotechnol 2011 May 15;29(7):644-52.
    pubmed: 21572440doi: 10.1038/nbt.1883google scholar: lookup
  28. Sabeur K, Ball BA, Corbin CJ, Conley A. Characterization of a novel, testis-specific equine serine/threonine kinase.. Mol Reprod Dev 2008 May;75(5):867-73.
    pubmed: 18246530doi: 10.1002/mrd.20792google scholar: lookup
  29. Kempisty B, Antosik P, Bukowska D, Jackowska M, Lianeri M, Jaśkowski JM, Jagodziński PP. Analysis of selected transcript levels in porcine spermatozoa, oocytes, zygotes and two-cell stage embryos.. Reprod Fertil Dev 2008;20(4):513-8.
    pubmed: 18462614doi: 10.1071/rd07211google scholar: lookup
  30. Ropka-Molik K, Zukowski K, Eckert R, Gurgul A, Piórkowska K, Oczkowicz M. Comprehensive analysis of the whole transcriptomes from two different pig breeds using RNA-Seq method.. Anim Genet 2014 Oct;45(5):674-84.
    pubmed: 24961663doi: 10.1111/age.12184google scholar: lookup
  31. Oancea E, Vriens J, Brauchi S, Jun J, Splawski I, Clapham DE. TRPM1 forms ion channels associated with melanin content in melanocytes.. Sci Signal 2009 May 12;2(70):ra21.
    pubmed: 19436059doi: 10.1126/scisignal.2000146google scholar: lookup
  32. Binns MM, Boehler DA, Lambert DH. Identification of the myostatin locus (MSTN) as having a major effect on optimum racing distance in the Thoroughbred horse in the USA.. Anim Genet 2010 Dec;41 Suppl 2:154-8.
    pubmed: 21070290doi: 10.1111/j.1365-2052.2010.02126.xgoogle scholar: lookup
  33. Hoang TV, Kumar PK, Sutharzan S, Tsonis PA, Liang C, Robinson ML. Comparative transcriptome analysis of epithelial and fiber cells in newborn mouse lenses with RNA sequencing.. Mol Vis 2014;20:1491-517.
    pubmed: 25489224
  34. Mao S, Sendler E, Goodrich RJ, Hauser R, Krawetz SA. A comparison of sperm RNA-seq methods.. Syst Biol Reprod Med 2014 Oct;60(5):308-15.
    pubmed: 25077492doi: 10.3109/19396368.2014.944318google scholar: lookup
  35. Moreton J, Malla S, Aboobaker AA, Tarlinton RE, Emes RD. Characterisation of the horse transcriptome from immunologically active tissues.. PeerJ 2014;2:e382.
    pubmed: 24860704doi: 10.7717/peerj.382google scholar: lookup
  36. Rudolph JA, Spier SJ, Byrns G, Rojas CV, Bernoco D, Hoffman EP. Periodic paralysis in quarter horses: a sodium channel mutation disseminated by selective breeding.. Nat Genet 1992 Oct;2(2):144-7.
    pubmed: 1338908doi: 10.1038/ng1092-144google scholar: lookup
  37. Smith RK, Garvican ER, Fortier LA. The current 'state of play' of regenerative medicine in horses: what the horse can tell the human.. Regen Med 2014;9(5):673-85.
    pubmed: 25372081doi: 10.2217/rme.14.42google scholar: lookup
  38. Peffers M, Liu X, Clegg P. Transcriptomic signatures in cartilage ageing.. Arthritis Res Ther 2013 Aug 23;15(4):R98.
    pubmed: 23971731doi: 10.1186/ar4278google scholar: lookup
  39. Bellone RR, Holl H, Setaluri V, Devi S, Maddodi N, Archer S, Sandmeyer L, Ludwig A, Foerster D, Pruvost M, Reissmann M, Bortfeldt R, Adelson DL, Lim SL, Nelson J, Haase B, Engensteiner M, Leeb T, Forsyth G, Mienaltowski MJ, Mahadevan P, Hofreiter M, Paijmans JL, Gonzalez-Fortes G, Grahn B, Brooks SA. Evidence for a retroviral insertion in TRPM1 as the cause of congenital stationary night blindness and leopard complex spotting in the horse.. PLoS One 2013;8(10):e78280.
    pubmed: 24167615doi: 10.1371/journal.pone.0078280google scholar: lookup
  40. Brooks SA, Gabreski N, Miller D, Brisbin A, Brown HE, Streeter C, Mezey J, Cook D, Antczak DF. Whole-genome SNP association in the horse: identification of a deletion in myosin Va responsible for Lavender Foal Syndrome.. PLoS Genet 2010 Apr 15;6(4):e1000909.
    pubmed: 20419149doi: 10.1371/journal.pgen.1000909google scholar: lookup
  41. Iqbal K, Chitwood JL, Meyers-Brown GA, Roser JF, Ross PJ. RNA-seq transcriptome profiling of equine inner cell mass and trophectoderm.. Biol Reprod 2014 Mar;90(3):61.
    pubmed: 24478389doi: 10.1095/biolreprod.113.113928google scholar: lookup
  42. Wade CM, Giulotto E, Sigurdsson S, Zoli M, Gnerre S, Imsland F, Lear TL, Adelson DL, Bailey E, Bellone RR, Blöcker H, Distl O, Edgar RC, Garber M, Leeb T, Mauceli E, MacLeod JN, Penedo MC, Raison JM, Sharpe T, Vogel J, Andersson L, Antczak DF, Biagi T, Binns MM, Chowdhary BP, Coleman SJ, Della Valle G, Fryc S, Guérin G, Hasegawa T, Hill EW, Jurka J, Kiialainen A, Lindgren G, Liu J, Magnani E, Mickelson JR, Murray J, Nergadze SG, Onofrio R, Pedroni S, Piras MF, Raudsepp T, Rocchi M, Røed KH, Ryder OA, Searle S, Skow L, Swinburne JE, Syvänen AC, Tozaki T, Valberg SJ, Vaudin M, White JR, Zody MC, Lander ES, Lindblad-Toh K. Genome sequence, comparative analysis, and population genetics of the domestic horse.. Science 2009 Nov 6;326(5954):865-7.
    pubmed: 19892987doi: 10.1126/science.1178158google scholar: lookup
  43. Bonache S, Mata A, Ramos MD, Bassas L, Larriba S. Sperm gene expression profile is related to pregnancy rate after insemination and is predictive of low fecundity in normozoospermic men.. Hum Reprod 2012 Jun;27(6):1556-67.
    pubmed: 22447625doi: 10.1093/humrep/des074google scholar: lookup
  44. Das PJ, McCarthy F, Vishnoi M, Paria N, Gresham C, Li G, Kachroo P, Sudderth AK, Teague S, Love CC, Varner DD, Chowdhary BP, Raudsepp T. Stallion sperm transcriptome comprises functionally coherent coding and regulatory RNAs as revealed by microarray analysis and RNA-seq.. PLoS One 2013;8(2):e56535.
    pubmed: 23409192doi: 10.1371/journal.pone.0056535google scholar: lookup
  45. Betteridge KJ. Equine embryology: an inventory of unanswered questions.. Theriogenology 2007 Sep 1;68 Suppl 1:S9-21.
    pubmed: 17532037doi: 10.1016/j.theriogenology.2007.04.037google scholar: lookup
  46. Zhou M, Wang Q, Sun J, Li X, Xu L, Yang H, Shi H, Ning S, Chen L, Li Y, He T, Zheng Y. In silico detection and characteristics of novel microRNA genes in the Equus caballus genome using an integrated ab initio and comparative genomic approach.. Genomics 2009 Aug;94(2):125-31.
    pubmed: 19406225doi: 10.1016/j.ygeno.2009.04.006google scholar: lookup
  47. Cheng WS, Tao H, Hu EP, Liu S, Cai HR, Tao XL, Zhang L, Mao JJ, Yan DL. Both genes and lncRNAs can be used as biomarkers of prostate cancer by using high throughput sequencing data.. Eur Rev Med Pharmacol Sci 2014 Nov;18(22):3504-10.
    pubmed: 25491628
  48. Ferraz AL, Ojeda A, López-Béjar M, Fernandes LT, Castelló A, Folch JM, Pérez-Enciso M. Transcriptome architecture across tissues in the pig.. BMC Genomics 2008 Apr 16;9:173.
    pubmed: 18416811doi: 10.1186/1471-2164-9-173google scholar: lookup
  49. Hamatani T. Human spermatozoal RNAs.. Fertil Steril 2012 Feb;97(2):275-81.
    pubmed: 22289287doi: 10.1016/j.fertnstert.2011.12.035google scholar: lookup
  50. Bellone RR. Pleiotropic effects of pigmentation genes in horses.. Anim Genet 2010 Dec;41 Suppl 2:100-10.
    pubmed: 21070283doi: 10.1111/j.1365-2052.2010.02116.xgoogle scholar: lookup
  51. Bissonnette N, Lévesque-Sergerie JP, Thibault C, Boissonneault G. Spermatozoal transcriptome profiling for bull sperm motility: a potential tool to evaluate semen quality.. Reproduction 2009 Jul;138(1):65-80.
    pubmed: 19423662doi: 10.1530/REP-08-0503google scholar: lookup
  52. 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.
    pubmed: 24391776doi: 10.1371/journal.pone.0083504google scholar: lookup
  53. Pacholewska A, Drögemüller M, Klukowska-Rötzler J, Lanz S, Hamza E, Dermitzakis ET, Marti E, Gerber V, Leeb T, Jagannathan V. The transcriptome of equine peripheral blood mononuclear cells.. PLoS One 2015;10(3):e0122011.
    pubmed: 25790166doi: 10.1371/journal.pone.0122011google scholar: lookup
  54. 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.
    pubmed: 22971240doi: 10.1186/1471-2164-13-473google scholar: lookup
  55. 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.
    pubmed: 20573200doi: 10.1186/1471-2164-11-398google scholar: lookup
  56. McLoughlin KE, Nalpas NC, Rue-Albrecht K, Browne JA, Magee DA, Killick KE, Park SD, Hokamp K, Meade KG, O'Farrelly C, Gormley E, Gordon SV, MacHugh DE. RNA-seq Transcriptional Profiling of Peripheral Blood Leukocytes from Cattle Infected with Mycobacterium bovis.. Front Immunol 2014;5:396.
    pubmed: 25206354doi: 10.3389/fimmu.2014.00396google scholar: lookup
  57. Davis BW, Ostrander EA. Domestic dogs and cancer research: a breed-based genomics approach.. ILAR J 2014;55(1):59-68.
    pubmed: 24936030doi: 10.1093/ilar/ilu017google scholar: lookup

Citations

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  1. Hsu TH, Chiu YT, Lee HT, Gong HY, Huang CW. Development of EST-Molecular Markers from RNA Sequencing for Genetic Management and Identification of Growth Traits in Potato Grouper (Epinephelus tukula). Biology (Basel) 2021 Jan 7;10(1).
    doi: 10.3390/biology10010036pubmed: 33430356google scholar: lookup
  2. Lu PJ, Wang G, Cai XD, Zhang P, Wang HK. Sequencing analysis of matrix metalloproteinase 7-induced genetic changes in Schwann cells. Neural Regen Res 2020 Nov;15(11):2116-2122.
    doi: 10.4103/1673-5374.282263pubmed: 32394970google scholar: lookup
  3. 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
  4. Hekman JP, Johnson JL, Kukekova AV. Transcriptome Analysis in Domesticated Species: Challenges and Strategies. Bioinform Biol Insights 2015;9(Suppl 4):21-31.
    doi: 10.4137/BBI.S29334pubmed: 26917953google scholar: lookup
  5. Jafari H, Abebe BK, Cong L, Ahmed Z, Zhaofei W, Sun M, Muhatai G, Chuzhao L, Dang R. Review: Genomic insights into the adaptive traits and stress resistance in modern horses. Stress Biol 2026 Jan 12;6(1):5.
    doi: 10.1007/s44154-025-00274-1pubmed: 41521281google scholar: lookup
  6. Austin MMP, Ivey JLZ, Shepherd EA, Myer PR. Methodologies to Identify Metabolic Pathway Differences Between Emaciated and Moderately Conditioned Horses: A Review of Multiple Gene Expression Techniques. Animals (Basel) 2025 Oct 10;15(20).
    doi: 10.3390/ani15202933pubmed: 41153862google scholar: lookup
  7. Hasan MS, Wang Y, Feugang JM, Zhou H, Liao SF. RNA sequencing analysis revealed differentially expressed genes and their functional annotation in porcine longissimus dorsi muscle affected by dietary lysine restriction. Front Vet Sci 2023;10:1233292.
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