Asian-Australasian Journal of Animal Sciences

Asian Australasian Association of Animal Production Societies (아세아태평양축산학회)
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A whole genome association study to detect additive and dominant single nucleotide polymorphisms for growth and carcass traits in Korean native cattle, Hanwoo

  • Li, Yi (School of Statistics, Shanxi University of Finance & Economics) ;
  • Gao, Yuxuan (School of Statistics, Shanxi University of Finance & Economics) ;
  • Kim, You-Sam (School of Biotechnology, Yeungnam University) ;
  • Iqbal, Asif (School of Biotechnology, Yeungnam University) ;
  • Kim, Jong-Joo (School of Biotechnology, Yeungnam University)
  • Received : 2016.03.02
  • Accepted : 2016.05.20
  • Published : 2017.01.01
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Abstract

Objective: A whole genome association study was conducted to identify single nucleotide polymorphisms (SNPs) with additive and dominant effects for growth and carcass traits in Korean native cattle, Hanwoo. Methods: The data set comprised 61 sires and their 486 Hanwoo steers that were born between spring of 2005 and fall of 2007. The steers were genotyped with the 35,968 SNPs that were embedded in the Illumina bovine SNP 50K beadchip and six growth and carcass quality traits were measured for the steers. A series of lack-of-fit tests between the models was applied to classify gene expression pattern as additive or dominant. Results: A total of 18 (0), 15 (3), 12 (8), 15 (18), 11 (7), and 21 (1) SNPs were detected at the 5% chromosome (genome) - wise level for weaning weight (WWT), yearling weight (YWT), carcass weight (CWT), backfat thickness (BFT), longissimus dorsi muscle area (LMA) and marbling score, respectively. Among the significant 129 SNPs, 56 SNPs had additive effects, 20 SNPs dominance effects, and 53 SNPs both additive and dominance effects, suggesting that dominance inheritance mode be considered in genetic improvement for growth and carcass quality in Hanwoo. The significant SNPs were located at 33 quantitative trait locus (QTL) regions on 18 Bos Taurus chromosomes (i.e. BTA 3, 4, 5, 6, 7, 9, 11, 12, 13, 14, 16, 17, 18, 20, 23, 26, 28, and 29) were detected. There is strong evidence that BTA14 is the key chromosome affecting CWT. Also, BTA20 is the key chromosome for almost all traits measured (WWT, YWT, LMA). Conclusion: The application of various additive and dominance SNP models enabled better characterization of SNP inheritance mode for growth and carcass quality traits in Hanwoo, and many of the detected SNPs or QTL had dominance effects, suggesting that dominance be considered for the whole-genome SNPs data and implementation of successive molecular breeding schemes in Hanwoo.

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References

  1. MacLeod IM, Hayes BJ, Savin KW, et al. Power of a genome scan to detect and locate quantitative trait loci in cattle using dense single nucleotide polymorphisms. J Anim Breed Genet 2010;127:133-42. https://doi.org/10.1111/j.1439-0388.2009.00831.x
  2. Lee YM, Han CM, Li Y, et al. A Whole Genome Association Study to Detect Single Nucleotide Polymorphisms for Carcass Traits in Hanwoo Populations. Asian-Australas J Anim Sci 2010;23:417-24. https://doi.org/10.5713/ajas.2010.10019
  3. Pausch H, Flisikowski K, Jung S, et al. Genome-wide association study identifies two major loci affecting calving ease and growthrelated traits in cattle. Genetics 2011;187:289-97. https://doi.org/10.1534/genetics.110.124057
  4. Nishimura S, Watanabe T, Mizoshita K, et al. Genome-wide association study identified three major QTL for carcass weight including the PLAG1-CHCHD7 QTN for stature in Japanese Black cattle. BMC Genet 2012;13.
  5. Kim JB, Lee C. Historical look at the genetic improvement in Korean cattle - Review. Asian-Australas J Anim Sci 2000;13:1467-81. https://doi.org/10.5713/ajas.2000.1467
  6. Venkata Reddy B, Sivakumar AS, Jeong DW, et al. Beef quality traits of heifer in comparison with steer, bull and cow at various feeding environments. Anim Sci J 2015;86:1-16. https://doi.org/10.1111/asj.12266
  7. Rowe SJ, Pong-Wong R, Haley CS, Knott SA, De Koning DJ. Detecting dominant QTL with variance component analysis in simulated pedigrees. Genet Res 2008;90:363-74. https://doi.org/10.1017/S0016672308009336
  8. Kim JJ, Farnir F, Savell J, Taylor JF. Detection of quantitative trait loci for growth and beef carcass fatness traits in a cross between Bos taurus (Angus) and Bos indicus (Brahman) cattle. J Anim Sci 2003;81:1933-42. https://doi.org/10.2527/2003.8181933x
  9. Lee SH, van der Werf JHJ, Hayes BJ, Goddard ME, Visscher PM. Predicting unobserved phenotypes for complex traits from wholegenome SNP data. Plos Genet 2008;4.
  10. Su GS, Christensen OF, Ostersen T, Henryon M, Lund MS. Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. Plos One 2012;7:e45293. https://doi.org/10.1371/journal.pone.0045293
  11. Druet T, Schrooten C, de Roos APW. Imputation of genotypes from different single nucleotide polymorphism panels in dairy cattle. J Dairy Sci 2010;93:5443-54. https://doi.org/10.3168/jds.2010-3255
  12. Sun YV, Jacobsen DM, Kardia SLR. ChromoScan: a scan statistic application for identifying chromosomal regions in genomic studies. Bioinformatics 2006;22:2945-7. https://doi.org/10.1093/bioinformatics/btl503
  13. McClure MC, Morsci NS, Schnabel RD, et al. A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle. Anim Genet 2010; 41:597-607. https://doi.org/10.1111/j.1365-2052.2010.02063.x
  14. Casas E, Shackelford SD, Keele JW, et al. Detection of quantitative trait loci for growth and carcass composition in cattle. J Anim Sci 2003;81:2976-83. https://doi.org/10.2527/2003.81122976x
  15. Mizoshita K, Takano A, Watanabe T, Takasuga A, Sugimoto Y. Identification of a 1.1-Mb region for a carcass weight QTL onbovine Chromosome 14. Mamm Genome 2005;16:532-7. https://doi.org/10.1007/s00335-005-0024-0
  16. Choi IS, Kong HS, Oh JD, et al. Analysis of microsatellite markers on bovine chromosomes 1 and 14 for potential allelic association with carcass traits in Hanwoo (Korean cattle). Asian-Australas J Anim Sci 2006;19:927-30. https://doi.org/10.5713/ajas.2006.927
  17. Takasuga A, Watanabe T, Mizoguchi Y, et al. Identification of bovine QTL for growth and carcass traits in Japanese Black cattle by replication and identical-by-descent mapping. Mamm Genome 2007; 18:125-36. https://doi.org/10.1007/s00335-006-0096-5
  18. Casas E, Keele JW, Shackelford SD, Koohmaraie M, Stone RT. Identification of quantitative trait loci for growth and carcass composition in cattle. Anim Genet 2004;35:2-6. https://doi.org/10.1046/j.1365-2052.2003.01067.x
  19. Lee YM, Lee YS, Han CM, et al. Detection of quantitative trait loci for growth and carcass traits on BTA6 in a Hanwoo population. Asian-Australas J Anim Sci 2010;23:287-91. https://doi.org/10.5713/ajas.2010.90586
  20. Sukegawa S, Miyake T, Takahagi Y, et al. Replicated association of the single nucleotide polymorphism in EDG1 with marbling in three general populations of Japanese Black beef cattle. BMC Res Notes 2010;3:66. https://doi.org/10.1186/1756-0500-3-66
  21. Boysen TJ, Heuer C, Tetens J, Reinhardt F, Thaller G. Novel use of derived genotype probabilities to discover significant dominance effects for milk production traits in dairy cattle. Genetics 2013; 193:431-42. https://doi.org/10.1534/genetics.112.144535
  22. Lippman ZB, Zamir D. Heterosis: revisiting the magic. Trends Genet 2007;23:60-6. https://doi.org/10.1016/j.tig.2006.12.006
  23. Hayes BJ, Miller SP. Mate selection strategies to exploit across- and within-breed dominance variation. J Anim Breed Genet-Zeitschrift Fur Tierzuchtung Und Zuchtungsbiologie 2000;117:347-59. https://doi.org/10.1046/j.1439-0388.2000.00252.x
  24. Dekkers JCM, Chakraborty R. Optimizing purebred selection for crossbred performance using QTL with different degrees of dominance. Genet Sel Evol 2004;36:297-324. https://doi.org/10.1186/1297-9686-36-3-297
  25. Beavis WD. QTL analyses: power precision and accuracy. In: A. H. Paterson, editor. Molecular dissection of complex traits. New York: CRC Press; 1998. p. 145-62.
  26. Ashwell MS, Heyen DW, Sonstegard TS, et al. Detection of quantitative trait loci affecting milk production, health, and reproductive traits in Holstein cattle. J Dairy Sci 2004;87:468-75. https://doi.org/10.3168/jds.S0022-0302(04)73186-0
  27. Wibowo TA, Gaskins CT, Newberry RC, et al. Genome assembly anchored QTL map of bovine chromosome 14. Int J Biol Sci 2008; 4:406-14.
  28. Karim L, Takeda H, Lin L, et al. Variants modulating the expression of a chromosome domain encompassing PLAG1 influence bovine stature. Nat Genet 2011;43:405-13. https://doi.org/10.1038/ng.814
  29. Blott S, Kim JJ, Moisio S, et al. Molecular dissection of a quantitative trait locus: a phenylalanine-to-tyrosine substitution in the transmembrane domain of the bovine growth hormone receptor is associated with a major effect on milk yield and composition. Genetics 2003;163:253-66.
  30. Garcia MD, Matukumalli L, Wheeler TL, et al. Markers on bovine chromosome 20 associated with carcass quality and composition traits and incidence of contracting infectious bovine keratoconjunctivitis. Anim Biotechnol 2010;21:188-202. https://doi.org/10.1080/10495398.2010.495012

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