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Comparative Transcriptomic Analyses by RNA-seq to Elucidate Differentially Expressed Genes in the Muscle of Korean Thoroughbred Horses

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Abstract

The athletic abilities of the horse serve as a valuable model to understand the physiology and molecular mechanisms of adaptive responses to exercise. We analyzed differentially expressed genes in triceps brachii muscle tissues collected from Eonjena Taeyang and Jigusang Seryeok Thoroughbred horses and their co-expression networks in a large-scale RNA-sequence dataset comparing expression before and after exercise. High-quality horse transcriptome data were generated, with over 22 million 90-bp pair-end reads. By comparing the annotations, we found that MYH3, MPZ, and PDE8B genes in Eonjena Taeyang and PDE8B and KIF18A genes in Jigusang Seryeok were upregulated before exercise. Notably further, we observed that PPP1R27, NDUFA3, TNC, and ANK1 in Eonjena Taeyang and HIF1A, BDNF, ADRB2, OBSCN, and PER3 in Jigusang Seryeok have shown upregulation at the postexercise period. This investigation suggested that genes responsible for metabolism and oxidative phosphorylations associated with endurance and resistance exercise were highly expressed, whereas genes encoding structural proteins were generally suppressed. The expression profile of racehorses at pre- and postexercise will provide credible reference for further studies on biological effects such as responses to stress and adaption of other Thoroughbred horse, which might be useful for selective breeding for improvement of traits in commercial production.

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Abbreviations

KRA:

Korea Racing Association

DEGs:

Differentially expressed genes

NGS:

Next-generation sequencing

SNPs:

Single-nucleotide polymorphisms

HCS:

HiSeq control system

RTA:

Real-time analyzer

DAVID:

Database for Annotation, Visualization and Integrated Discovery

EASE:

Expression Analysis Systematic Explorer

GO:

Gene ontology

KEGG:

Kyoto Encyclopedia of Genes and Genomes

RPKM:

Reads per kilobase per million

References

  1. Lee, S. Y., & Cho, G. J. (2006). Parentage testing of Thoroughbred horse in Korea using microsatellite DNA typing. Journal of Veterinary Science, 7, 63–67.

    Article  Google Scholar 

  2. Park, W., Kim, J., Kim, H. J., Choi, J., Park, J. W., Cho, H. W., Kim, B. W., Park, M. H., Shin, T. S., Cho, S. K., Park, J. K., Kim, H., Hwang, J. Y., Lee, C. K., Lee, H. K., Cho, S., & Cho, B. W. (2014). Investigation of de novo unique differentially expressed genes related to evolution in exercise response during domestication in Thoroughbred race horses. PLoS One, 9, e91418.

    Article  Google Scholar 

  3. Capomaccio, S., Vitulo, N., Verini-Supplizi, A., Barcaccia, G., Albiero, A., D’Angelo, M., Campagna, D., Valle, G., Felicetti, M., Silvestrelli, M., & Cappelli, K. (2013). RNA sequencing of the exercise transcriptome in equine athletes. PLoS One, 8, e83504.

    Article  Google Scholar 

  4. Kim, H., Lee, T., Park, W., Lee, J. W., Kim, J., Lee, B. Y., Ahn, Y., Moon, S., Cho, S., Do, K.-T., Kim, K. T., Lee, H. S., Lee, H. K., Kong, C. K., Yang, H. S., Park, Y. M., Kim, J., Kim, H. M., Hwang, B. C., Bhak, S., Burt, J., Park, D., Cho, K. D. B. W., & Kim, H. (2013). Peeling back the evolutionary layers of molecular mechanisms responsive to exercise-stress in the skeletal muscle of the racing horse. DNA Research, 20, 287–298.

    Article  CAS  Google Scholar 

  5. Wade, C. M., Giulotto, E., Sigurdsson, S., et al. (2009). Genome sequence, comparative analysis, and population genetics of the domestic horse. Science, 326, 865–867.

    Article  CAS  Google Scholar 

  6. Morozova, O., & Marra, M. A. (2013). Applications of next-generation sequencing technologies in functional genomics. Genomics, 92, 255–264.

    Article  Google Scholar 

  7. Jacquier, A. (2009). The complex eukaryotic transcriptome: unexpected pervasive transcription and novel small RNAs. Nature Reviews Genetics, 10, 833–844.

    Article  CAS  Google Scholar 

  8. Ghosh, M., Sodhi, S. S., Song, K. D., Kim, J. H., Mongre, R. K., Sharma, N., Singh, N. K., Kim, S. W., Lee, H. K., & Jeong, D. K. (2015). Evaluation of body growth and immunity-related differentially expressed genes through deep RNA sequencing in the piglets of Jeju native pig and Berkshire. Animal Genetics, 46, 255–264.

    Article  CAS  Google Scholar 

  9. Zhang, W., Chen, J., Yang, Y., Tang, Y., Shang, J., & Shen, B. (2011). A practical comparison of de novo genome assembly software tools for next-generation sequencing technologies. PLoS One, 6, e17915.

    Article  CAS  Google Scholar 

  10. Sultan, M., Schulz, M. H., Richard, H., Magen, A., Klingenhoff, A., Scherf, M., Seifert, M., Borodina, T., Soldatov, A., Parkhomchuk, D., Schmidt, D., O’Keeffe, S., Haas, S., Vingron, M., Lehrach, H., & Yaspo, M. L. (2008). A global view of gene activity and alternative splicing by deep sequencing of the human transcriptome. Science, 321, 956–960.

    Article  CAS  Google Scholar 

  11. Alkan, C., Kidd, J. M., Marques-Bonet, T., Aksay, G., Antonacci, F., Hormozdiari, F., Kitzman, J. O., Baker, C., Malig, M., Mutlu, O., Sahinalp, S. C., Gibbs, R. A., & Eichler, E. E. (2009). Personalized copy number and segmental duplication maps using next-generation sequencing. Nature Genetics, 41, 1061–1067.

    Article  CAS  Google Scholar 

  12. Gan, X., Stegle, O., Behr, J., Steffen, J. G., Drewe, P., Hildebrand, K. L., Lyngsoe, R., Schultheiss, S. J., Osborne, E. J., Sreedharan, V. T., Kahles, A., Bohnert, R., Jean, G., Derwent, P., Kersey, P., Belfield, E. J., Harberd, N. P., Kemen, E., Toomajian, C., Kover, P. X., Clark, R. M., Ratsch, G., & Mott, R. (2011). Multiple reference genomes and transcriptomes for Arabidopsis thaliana. Nature, 477, 419–423.

    Article  CAS  Google Scholar 

  13. Hosack, D. A., Dennis, G., Jr., Sherman, B. T., Lane, H. C., & Lempicki, R. A. (2003). Identifying biological themes within lists of genes with EASE. Genome Biology, 4, R70.

    Article  Google Scholar 

  14. Kanduri, C., Kuusi, T., Ahvenainen, M., Philips, A. K., Lahdesmaki, H., & Jarvela, I. (2015). The effect of music performance on the transcriptome of professional musicians. Scientific Reports, 5, 9506.

    Article  CAS  Google Scholar 

  15. Durffee, T. S., & Thate, T. E. (2008). DNASTAR’s next-generation software. In M. Janitz (Ed.), Next generation genome sequencing: towards personalized medicine (Vol. 7, pp. 89–94). Germany: Wiley.

    Chapter  Google Scholar 

  16. Burland, T. G. (2000). DNASTAR’s Lasergene sequence analysis software. Methods in Molecular Biology, 132, 71–91.

    CAS  Google Scholar 

  17. Wagner, G. P., Kin, K., & Lynch, V. J. (2012). Measurement of mRNA abundance using RNA-seq data: RPKM measure is inconsistent among samples. Theory in Biosciences, 131, 281–285.

    Article  CAS  Google Scholar 

  18. Sodhi, S. S., Park, W. C., Ghosh, M., Kim, J. N., Sharma, N., Shin, K. Y., Cho, I. C., Ryu, Y. C., Oh, S. J., Kim, S. H., Song, K. D., Hong, S. P., Cho, S. A., Kim, H. B., & Jeong, D. K. (2014). Comparative transcriptomic analysis to identify differentially expressed genes in fat tissue of adult Berkshire and Jeju native pig using RNA-seq. Molecular Biology Reports, 41, 6305–6315.

    Article  CAS  Google Scholar 

  19. Rozen, S., & Skaletsky, H. (2000). Primer3 on the www for general users and for biologist programmers. In S. Misener & S. A. Krawetz (Eds.), Methods in molecular biology (pp. 365–386). Totowa: Humana.

    Google Scholar 

  20. Wu, C. H., Tsai, M. H., Ho, C. C., Chen, C. Y., & Lee, H. S. (2013). De novo transcriptome sequencing of axolotl blastema for identification of differentially expressed genes during limb regeneration. BMC Genomics, 14, 434.

    Article  CAS  Google Scholar 

  21. McGivney, B. A., McGettigan, P. A., Browne, J. A., Evans, A. C., Fonseca, R. G., Loftus, B. J., Lohan, A., MacHugh, D. E., Murphy, B. A., Katz, L. M., & Hill, E. W. (2010). Characterization of the equine skeletal muscle transcriptome identifies novel functional responses to exercise training. BMC Genomics, 11, 398.

    Article  Google Scholar 

  22. McIntyre, L. M., Lopiano, K. K., Morse, A. M., Amin, V., Oberg, A. L., Young, L. J., & Nuzhdin, S. V. (2011). RNA-seq: technical variability and sampling. BMC Genomics, 12, 293.

    Article  CAS  Google Scholar 

  23. Lopez-Maury, L., Marguerat, S., & Bahler, J. (2008). Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation. Nature Reviews Genetics, 9, 583–593.

    Article  CAS  Google Scholar 

  24. Cong, F., Liu, X., Han, Z., et al. (2013). Transcriptome analysis of chicken kidney tissues following coronavirus avian infectious bronchitis virus infection. BMC Genomics, 14, 743.

    Article  CAS  Google Scholar 

  25. Schrick, K., Bruno, M., Khosla, A., Cox, P. N., Marlatt, S. A., Roque, R. A., Nguyen, H. C., He, C., Snyder, M. P., Singh, D., & Yadav, G. (2014). Shared functions of plant and mammalian StAR-related lipid transfer (START) domains in modulating transcription factor activity. BMC Biology, 12, 70.

    Article  Google Scholar 

  26. Riechman, S. E., Andrews, R. D., Maclean, D. A., & Sheather, S. (2007). Statins and dietary and serum cholesterol are associated with increased lean mass following resistance training. Journal of Gerontology, 62, 1164–1171.

    Google Scholar 

  27. Ness, F., Bourot, S., Regnacq, M., Spagnoli, R., Berges, T., & Karst, F. (2001). SUT1 is a putative Zn[II]2Cys6-transcription factor whose upregulation enhances both sterol uptake and synthesis in aerobically growing Saccharomyces cerevisiae cells. European Journal of Biochemistry, 268, 1585–1595.

    Article  CAS  Google Scholar 

  28. Sodhi, S. S., Ghosh, M., Song, K. D., Sharma, N., Kim, J. H., Kim, N. E., Lee, S. J., Kang, C. W., Oh, S. J., & Jeong, D. K. (2014). An approach to identify SNPs in the gene encoding acetyl-CoA acetyltransferase-2 (ACAT-2) and their proposed role in metabolic processes in pig. PLoS One, 9, e102432.

    Article  Google Scholar 

  29. Smythe, G. M., Eby, J. C., Disatnik, M. H., & Rando, T. A. (2003). A caveolin-3 mutant that causes limb girdle muscular dystrophy type 1C disrupts Src localization and activity and induces apoptosis in skeletal myotubes. Journal of Cell Science, 116, 4739–4749.

    Article  CAS  Google Scholar 

  30. Lucero, H. A., & Robbins, P. W. (2004). Lipid rafts-protein association and the regulation of protein activity. Archives of Biochemistry and Biophysics, 426, 208–224.

    Article  CAS  Google Scholar 

  31. Tochigi, M., Iwamoto, K., Bundo, M., Sasaki, T., Kato, N., & Kato, T. (2008). Gene expression profiling of major depression and suicide in the prefrontal cortex of postmortem brains. Neuroscience Research, 60, 184–191.

    Article  CAS  Google Scholar 

  32. Kirshenbaum, G. S., Saltzman, K., Rose, B., Petersen, J., Vilsen, B., & Roder, J. C. (2011). Decreased neuronal Na+, K+-ATPase activity in Atp1a3 heterozygous mice increases susceptibility to depression-like endophenotypes by chronic variable stress. Genes, Brain, and Behavior, 10, 542–550.

    Article  CAS  Google Scholar 

  33. Li, Y., Roy, B. D., Wang, W., Zhang, L., Zhang, L., Sampson, S. B., Yang, Y., & Lin, D. T. (2012). Identification of two functionally distinct endosomal recycling pathways for dopamine D(2) receptor. Journal of Neuroscience, 32, 7178–7190.

    Article  CAS  Google Scholar 

  34. Willert, K., Brown, J. D., Danenberg, E., et al. (2003). Wnt proteins are lipid-modified and can act as stem cell growth factors. Nature, 423, 448–452.

    Article  CAS  Google Scholar 

  35. Bennett, C. N., Ross, S. E., Longo, K. A., Bajnok, L., Hemati, N., Johnson, K. W., Harrison, S. D., & MacDougald, O. A. (2002). Regulation of Wnt signaling during adipogenesis. Journal of Biological Chemistry, 277, 30998–31004.

    Article  CAS  Google Scholar 

  36. Vertino, A. M., Taylor-Jones, J. M., Longo, K. A., Bearden, E. D., Lane, T. F., McGehee, R. E., Jr., MacDougald, O. A., & Peterson, C. A. (2005). Wnt10b deficiency promotes coexpression of myogenic and adipogenic programs in myoblasts. Molecular Biology of the Cell, 16, 2039–2048.

    Article  CAS  Google Scholar 

  37. Martin, A. M., Elliott, J. A., Duffy, P., Blake, C. M., Ben Attia, S., Katz, L. M., Browne, J. A., Gath, V., McGivney, B. A., Hill, E. W., & Murphy, B. A. (2010). Circadian regulation of locomotor activity and skeletal muscle gene expression in the horse. Journal of Applied Physiology, 109, 1328–1336.

    Article  CAS  Google Scholar 

  38. Doi, K., Noiri, E., Maeda, R., Nakao, A., Kobayashi, S., Tokunaga, K., & Fujita, T. (2007). Functional polymorphism of the myeloperoxidase gene in hypertensive nephrosclerosis dialysis patients. Hypertension Research, 30, 1193–1198.

    Article  CAS  Google Scholar 

  39. Purvis, D., Gonsalves, S., & Deuster, P. A. (2010). Physiological and psychological fatigue in extreme conditions: overtraining and elite athletes. PM & R, 2, 442–450.

    Article  Google Scholar 

  40. Capomaccio, S., Cappelli, K., Spinsanti, G., Mencarelli, M., Muscettola, M., Felicetti, M., Verini Supplizi, A., & Bonifazi, M. (2011). Athletic humans and horses: comparative analysis of interleukin-6 (IL-6) and IL-6 receptor (IL-6R) expression in peripheral blood mononuclear cells in trained and untrained subjects at rest. BMC Physiology, 11, 3.

    Article  CAS  Google Scholar 

  41. Pedersen, B. K., & Edward, F. (2009). Adolph Distinguished Lecture: muscle as an endocrine organ: IL-6 and other myokines. Journal of Applied Physiology, 107, 1006–14.

    Article  CAS  Google Scholar 

  42. Donges, C. E., Duffield, R., & Drinkwater, E. J. (2010). Effects of resistance or aerobic exercise training on interleukin-6, C-reactive protein, and body composition. Medicine and Science in Sports and Exercise, 42, 304–13.

    Article  CAS  Google Scholar 

  43. Pauter, A. M., Olsson, P., Asadi, A., Herslof, B., Csikasz, R. I., Zadravec, D., & Jacobsson, A. (2014). Elovl2 ablation demonstrates that systemic DHA is endogenously produced and is essential for lipid homeostasis in mice. Journal of Lipid Research, 55, 718–728.

    Article  CAS  Google Scholar 

  44. Art, T., Franck, T., Gangl, M., Votion, D., Kohnen, S., Deby-Dupont, G. and Serteyn, D. (2006). Plasma concentrations of myeloperoxidase in endurance and 3-day event horses after a competition. Equine Veterinary Journal. Supplement, 298–302.

  45. Park, K. D., Park, J., Ko, J., Kim, B. C., Kim, H. S., Ahn, K., Do, K. T., Choi, H., Kim, H. M., Song, S., Lee, S., Jho, S., Kong, H. S., Yang, Y. M., Jhun, B. H., Kim, C., Kim, T. H., Hwang, S., Bhak, J., Lee, H. K., & Cho, B. W. (2012). Whole transcriptome analyses of six thoroughbred horses before and after exercise using RNA-Seq. BMC Genomics, 13, 473.

    Article  CAS  Google Scholar 

  46. Rothenbuhler, A., Horvath, A., Libe, R., Faucz, F. R., Fratticci, A., Raffin Sanson, M. L., Vezzosi, D., Azevedo, M., Levy, I., Almeida, M. Q., Lodish, M., Nesterova, M., Bertherat, J., & Stratakis, C. A. (2012). Identification of novel genetic variants in phosphodiesterase 8B (PDE8B), a cAMP-specific phosphodiesterase highly expressed in the adrenal cortex, in a cohort of patients with adrenal tumours. Clinical Endocrinology, 77, 195–199.

    Article  CAS  Google Scholar 

  47. Hidaka, C., Goshi, K. R., Boachie-Adjei, B. O., & Crystal, R. (2003). Enhancement of spine fusion using combined gene therapy and tissue engineering bmp-7-expressing bone marrow cells and allograft bone. Spine, 15, 2049–2057.

    Article  Google Scholar 

  48. Tseng, Y. H., Kokkotou, E., Schulz, T. J., Huang, T. L., Winnay, J. N., Taniguchi, C. M., Tran, T. T., Suzuki, R., Espinoza, D. O., Yamamoto, Y., Ahrens, M. J., Dudley, A. T., Norris, A. W., Kulkarni, R. N., & Kahn, C. R. (2008). New role of bone morphogenetic protein 7 in brown adipogenesis and energy expenditure. Nature, 454, 1000–1004.

    Article  CAS  Google Scholar 

  49. Kontrogianni, K. A., Jones, E. M., van Rossum, D. B., et al. (2003). Obscurin is a ligand for small ankyrin 1 in skeletal muscle. Molecular Biology of the Cell, 14, 1138–1148.

    Article  Google Scholar 

  50. Jarvinen, T. A., Jozsa, L., Kannus, P., Jarvinen, T. L., Hurme, T., Kvist, M., Pelto-Huikko, M., Kalimo, H., & Jarvinen, M. (2003). Mechanical loading regulates the expression of tenascin-C in the myotendinous junction and tendon but does not induce de novo synthesis in the skeletal muscle. Journal of Cell Science, 116, 857–866.

    Article  CAS  Google Scholar 

  51. Watts, L. M., Browne, J. A., & Murphy, B. A. (2012). Investigation of a non-invasive method of assessing the equine circadian clock using hair follicle cells. Journal of Circadian Rhythms, 10, 7.

    Article  CAS  Google Scholar 

  52. Kovac, J., Husse, J., & Oster, H. (2009). A time to fast, a time to feast: the crosstalk between metabolism and the circadian clock. Molecular and Cells, 28, 75–80.

    Article  CAS  Google Scholar 

  53. Ghosh, M., Singh, S. S., Sharma, N., Mongre, R., Kim, N., Singh, A. et al. (2016). An integrated in silico approach for functional and structural impact of non-synonymous SNPs in the MYH1 gene in Jeju Native Pigs. BMC Genetics, 17, 35.

  54. Cannon, B., & Nedergaard, J. (2004). Brown adipose tissue: function and physiological significance. Physiological Reviews, 84, 277–359.

  55. Kelley, D. E., Goodpaster, B. H., & Storlien, L. (2002). Muscle triglyceride and insulin resistance. Annual Review of Nutrition, 22, 325–346.

  56. Huang, Z., Wei, C., Luo, H., Bian, M., Deng, J., & Liu, Y. (2014). The developmental changes of mRNAs expression levels of GHSR gene in sheep. AASRI Procedia, 6, 123–130.

  57. French, M. C., Littlejohn, R. P., Greer, G. J., Bain, W. E., McEwan, J. C., & Tisdall, D. J. (2006). Growth hormone and ghrelin receptor genes are differentially expressed between genetically lean and fat selection lines of sheep. Journal of Animal Science, 84, 324–331.

  58. MacNeil, L. G., Melov, S., Hubbard, A. E., et al. (2010). Eccentric exercise activates novel transcriptional regulation of hypertrophic signaling pathways not affected by hormone changes. PloS One, 5, e10695.

  59. Cho, H. W., Shin, S., Song, K. D., Park, J. W., Choi, J. Y., Lee, H. K. et al. (2015). Molecular characterization and expression analysis of adrenergic receptor beta 2 (ADRB2) gene before and after exercise in the horse. Asian-Australasian Journal of Animal Sciences, 28, 686–690.

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Acknowledgments

This study was supported by grants from the Next Generation BioGreen 21 Program (Nos. PJ011173, PJ01104401, PJ010967), Rural Development Administration, Republic of Korea.

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Authors and Affiliations

  1. Department of Animal Biotechnology, Faculty of Biotechnology, Jeju National University, Jeju, 690-756, Republic of Korea

    Mrinmoy Ghosh, Amit Kumar Singh, Nam Eun Kim, Raj Kumar Mongre, Do Huynh, Zhang Jiao Jiao, Kyoung Tag Do & DongKee Jeong

  2. Department of Animal Science, College of Natural Resources and Life Sciences, Pusan National University, Miryang, 627-702, Republic of Korea

    Hyun-Woo Cho, Jeong-Woong Park, Jae-Young Choi & Byung-Wook Cho

  3. BK21+, Department of Cogno-Mechatronics Engineering, Pusan National University, Busan, 609-735, Republic of Korea

    Young-Hwa Chung

  4. Sher-e-Kashmir University of Agricultural Sciences and Technology, Jammu, Jammu and Kashmir, India

    Neelesh Sharma

  5. Department of Animal Biotechnology, Chonbuk National University, Jeonju, 561-756, Republic of Korea

    Hak-Kyo Lee & Ki-Duk Song

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  1. Mrinmoy Ghosh
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  2. Hyun-Woo Cho
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Ghosh, M., Cho, HW., Park, JW. et al. Comparative Transcriptomic Analyses by RNA-seq to Elucidate Differentially Expressed Genes in the Muscle of Korean Thoroughbred Horses. Appl Biochem Biotechnol 180, 588–608 (2016). https://doi.org/10.1007/s12010-016-2118-4

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