Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
권호 표지
DOI QR코드

DOI QR Code

A whole genome sequence association study of muscle fiber traits in a White Duroc×Erhualian F2 resource population

  • Guo, Tianfu (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Gao, Jun (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Yang, Bin (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Yan, Guorong (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Xiao, Shijun (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Zhang, Zhiyan (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University) ;
  • Huang, Lusheng (State Key Laboratory of Pig Genetic Improvement and Production Technology, Jiangxi Agricultural University)
  • Received : 2018.10.13
  • Accepted : 2019.06.17
  • Published : 2020.05.01
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: Muscle fiber types, numbers and area are crucial aspects associated with meat production and quality. However, there are few studies of pig muscle fibre traits in terms of the detection power, false discovery rate and confidence interval precision of whole-genome quantitative trait loci (QTL). We had previously performed genome scanning for muscle fibre traits using 183 microsatellites and detected 8 significant QTLs in a White Duroc×Erhualian F2 population. The confidence intervals of these QTLs ranged between 11 and 127 centimorgan (cM), which contained hundreds of genes and hampered the identification of QTLs. A whole-genome sequence imputation of the population was used for fine mapping in this study. Methods: A whole-genome sequences association study was performed in the F2 population. Genotyping was performed for 1,020 individuals (19 F0, 68 F1, and 933 F2). The whole-genome variants were imputed and 21,624,800 single nucleotide polymorphisms (SNPs) were identified and examined for associations to 11 longissimus dorsi muscle fiber traits. Results: A total of 3,201 significant SNPs comprising 7 novel QTLs showing associations with the relative area of fiber type I (I_RA), the fiber number per square centimeter (FN) and the total fiber number (TFN). Moreover, one QTL on pig chromosome 14 was found to affect both FN and TFN. Furthermore, four plausible candidate genes associated with FN (kinase non-catalytic C-lobe domain containing [KNDC1]), TFN (KNDC1), and I_RA (solute carrier family 36 member 4, contactin associated protein like 5, and glutamate metabotropic receptor 8) were identified. Conclusion: An efficient and powerful imputation-based association approach was utilized to identify genes potentially associated with muscle fiber traits. These identified genes and SNPs could be explored to improve meat production and quality via marker-assisted selection in pigs.

Keywords

References

  1. Brooke MH, Kaiser KK. Muscle fiber types: how many and what kind? Arch Neurol 1970; 23:369-79. https://doi.org/10.1001/archneur.1970.00480280083010
  2. Sosnicki A. Histopathological observation of stress myopathy in M. longissimus in the pig and relationships with meat quality, fattening and slaughter traits. J Anim Sci 1987;65:584-96. https://doi.org/10.2527/jas1987.652584x
  3. Swatland HJ, Cassens RG. Observations on the postmortem histochemistry of myofibers from stress susceptible pigs. J Anim Sci 1973;37:885-91. https://doi.org/10.2527/jas1973.374885x
  4. Franck M, Figwer P, Godfraind C, Poirel MT, Khazzaha A, Ruchoux MM. Could the pale, soft, and exudative condition be explained by distinctive histological characteristics? J Anim Sci 2007;85:746-53. https://doi.org/10.2527/jas.2006-190
  5. Rehfeldt C, Fiedler I, Dietl G, Ender K. Myogenesis and postnatal skeletal muscle cell growth as influenced by selection. Livest Prod Sci 2000;66:177-88. https://doi.org/10.1016/S0301-6226(00)00225-6
  6. Hu ZL, Fritz ER, Reecy JM. Animalqtldb: a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Res 2007;35(Suppl 1):D604-9. https://doi.org/10.1093/nar/gkl946
  7. Nii M, Hayashi T, Mikawa S, et al. Quantitative trait loci mapping for meat quality and muscle fiber traits in a Japanese wild boar $\times$ Large White intercross. J Anim Sci 2005;83:308-15. https://doi.org/10.2527/2005.832308x
  8. Wimmers K, Fiedler I, Hardge T, Murani E, Schellander K, Ponsuksili S. QTL for microstructural and biophysical muscle properties and body composition in pigs. BMC Genet 2006;7:15. https://doi.org/10.1186/1471-2156-7-15
  9. Estelle J, Gil F, Vazquez JM, et al. A quantitative trait locus genome scan for porcine muscle fiber traits reveals overdominance and epistasis. J Anim Sci 2008;86:3290-9. https://doi.org/10.2527/jas.2008-1034
  10. Li WB, Ren J, Zhu WC, et al. Mapping QTL for porcine muscle fibre traits in a White Duroc x Erhualian F2 resource population. J Anim Breed Genet 2009;126:468-74. https://doi.org/10.1111/j.1439-0388.2009.00805.x
  11. Guo YY. Genome-wide association study on muscle fiber and eye muscle area traits in swine [Ph.D. Thesis]. Jizhong, China: Shanxi Agricultural University; 2015.
  12. Li N. Genome-wide association studies for pig meat traits and exploration of major genes [Ph.D. Thesis]. Beijing, China: China Agricultural University; 2016.
  13. Yang GC, Ren J, Li SJ, et al. Genome-wide identification of QTL for age at puberty in gilts using a large intercross $F_{2}$ population between White Duroc $\times$ Erhualian. Genet Sel Evol 2008;40:529-39. https://doi.org/10.1051/gse:2008019
  14. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet 2009;5:e1000529. https://doi.org/10.1371/journal.pgen.1000529
  15. McKenna A, Hanna M, Banks E, et al. The genome analysis toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010;20:1297-303. https://doi.org/10.1101/gr.107524.110
  16. Danecek P, Auton A, Abecasis G, et al. The variant call format and VCFtools. Bioinformatics 2011;27:2156-8. https://doi.org/10.1093/bioinformatics/btr330
  17. Delaneau O, Howie B, Cox AJ, Zagury JF, Marchini J. Haplotype estimation using sequencing reads. Am J Hum Genet 2013;93:687-96. https://doi.org/10.1016/j.ajhg.2013.09.002
  18. Zhou X, Carbonetto P, Stephens M. Polygenic modeling with bayesian sparse linear mixed models. PLoS Genet 2013;9:e1003264. https://doi.org/10.1371/journal.pgen.1003264
  19. Storey JD. The positive false discovery rate: a Bayesian interpretation and the q-value. Ann Statist 2003;31:2013-35. https://doi.org/10.1214/aos/1074290335
  20. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Ann Statist 2001;29:1165-88. https://doi.org/10.1214/aos/1013699998.
  21. Rebai A, Goffinet B, Mangin B. Approximate thresholds of interval mapping tests for QTL detection. Genetics 1994;138:235-40. https://doi.org/10.1093/genetics/138.1.235
  22. Pearson TA, Manolio TA. How to interpret a genome-wide association study. JAMA 2008;299:1335-44. https://doi.org/10.1001/jama.299.11.1335
  23. Nishimura D, Sakai H, Sato T, et al. Roles of ADAM8 in elimination of injured muscle fibers prior to skeletal muscle regeneration. Mech Dev 2015;135:58-67. https://doi.org/10.1016/j.mod.2014.12.001
  24. Liang JJ, Wang W, Sorensen D, et al. Cellular prion protein regulates its own alpha-cleavage through ADAM8 in skeletal muscle. J Biol Chem 2012;287:16510-20. https://doi.org/10.1074/jbc.M112.360891
  25. Wechsler-Reya RJ, Elliott KJ, Prendergast GC. A role for the putative tumor suppressor Bin1 in muscle cell differentiation. Mol Cell Biol 1998;18:566-75. https://doi.org/10.1128/ MCB.18.1.566
  26. Muller AJ, Baker JF, DuHadaway JB, et al. Targeted disruption of the murine Bin1/Amphiphysin II gene does not disable endocytosis but results in embryonic cardiomyopathy with aberrant myofibril formation. Mol Cell Biol 2003;23:4295-306. https://doi.org/10.1128/MCB.23.12.4295-4306.2003
  27. Johann B, Nasim V, Marie M, et al. Altered splicing of the BIN1 muscle-specific exon in humans and dogs with highly progressive centronuclear myopathy. PLoS Genet 2013;9:e1003430. https://doi.org/10.1371/journal.pgen.1003430
  28. Fugier C, Klein AF, Hammer C, et al. Misregulated alternative splicing of BIN1 is associated with T tubule alterations and muscle weakness in myotonic dystrophy. Nat Med 2011;17:720-5. https://doi.org/10.1038/nm.2374
  29. Yuan M, Zhao YH, Wang YS, et al. The apoptosis induced by FAM105A through Bcl-2 family and caspase dependent pathway. J Xiamen Univ 2011;50:1065-9.