Korean Journal of Agricultural Science (농업과학연구)

Institute of Agricultural Science, CNU (충남대학교 농업과학연구소)
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A study of the genomic estimated breeding value and accuracy using genotypes in Hanwoo steer (Korean cattle)

  • Eun Ho, Kim (Department of Animal Science, Gyeongsang National University) ;
  • Du Won, Sun (Department of Animal Science and Biotechnology, Gyeongsang National University) ;
  • Ho Chan, Kang (Institute of Agriculture and Life Science, Gyeongsang National University) ;
  • Ji Yeong, Kim (Department of Animal Science, Gyeongsang National University) ;
  • Cheol Hyun, Myung (Department of Animal Science, Gyeongsang National University) ;
  • Doo Ho, Lee (Department of Animal Science and Biotechnology, Chungnam National University) ;
  • Seung Hwan, Lee (Department of Animal Science and Biotechnology, Chungnam National University) ;
  • Hyun Tae, Lim (Department of Animal Science, Gyeongsang National University)
  • Received : 2021.07.19
  • Accepted : 2021.09.02
  • Published : 2021.12.01
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Abstract

The estimated breeding value (EBV) and accuracy of Hanwoo steer (Korean cattle) is an indicator that can predict the slaughter time in the future and carcass performance outcomes. Recently, studies using pedigrees and genotypes are being actively conducted to improve the accuracy of the EBV. In this study, the pedigree and genotype of 46 steers obtained from livestock farm A in Gyeongnam were used for a pedigree best linear unbiased prediction (PBLUP) and a genomic best linear unbiased prediction (GBLUP) to estimate and analyze the breeding value and accuracy of the carcass weight (CWT), eye muscle area (EMA), back-fat thickness (BFT), and marbling score (MS). PBLUP estimated the EBV and accuracy by constructing a numeric relationship matrix (NRM) from the 46 steers and reference population I (545,483 heads) with the pedigree and phenotype. GBLUP estimated genomic EBV (GEBV) and accuracy by constructing a genomic relationship matrix (GRM) from the 46 steers and reference population II (16,972 heads) with the genotype and phenotype. As a result, in the order of CWT, EMA, BFT, and MS, the accuracy levels of PBLUP were 0.531, 0.519, 0.524 and 0.530, while the accuracy outcomes of GBLUP were 0.799, 0.779, 0.768, and 0.810. The accuracy estimated by GBLUP was 50.1 - 53.1% higher than that estimated by PBLUP. GEBV estimated with the genotype is expected to show higher accuracy than the EBV calculated using only the pedigree and is thus expected to be used as basic data for genomic selection in the future.

Keywords

Acknowledgement

본 성과물은(논문, 산업재산권, 품종보호권 등)은 농촌진흥청 연구사업(과제번호: PJ0162182021)의 지원에 의해 이루어진 것임.

References

  1. Cho CI. 2013. Accuracy of breeding value prediction and genetic gain of carcass traits in Hanwoo breeding population through application of genomic selection technology. Ph.D. dissertation, Hankyong National Univ., Anseong, Korea. [in Korean] 
  2. Choi JS, Jeong JT, Lee JK, Choi YS, Jung MO, Choi YI. 2017. Effect of boiled feed on carcass characteristics of Hanwoo steers. Bulletin of the Animal Biotechnology 9:33-37. [in Korean] 
  3. Dekkers JCM, Hospital F. 2002. The use of molecular genetic in the improvement of agricultural population. Nature Review Genetics 3:22-32. 
  4. Do CH, Park BH, Kim SD, Choi TJ, Yang BS, Park SB, Song HJ. 2016. Genetic parameter estimates of carcass traits under national scale breeding scheme for beef cattle. Asian-Australasian Journal of Animal Science 29:1083-1094.  https://doi.org/10.5713/ajas.15.0696
  5. Goddard ME. 2009. Genomic selection: Prediction of accuracy and maximisation of long term response. Genetica 136:245-257.  https://doi.org/10.1007/s10709-008-9308-0
  6. Hayes BJ, Goddard ME. 2008. Prediction of breeding values using marker-derived relationship matrices. Journal of Animal Science 86:2089-2092. 
  7. Heffner EL, Sorrells ME, Jannink JL. 2009. Genomic selection for crop improvement. Crop Science 49:1-12.  https://doi.org/10.2135/cropsci2008.08.0512
  8. Henderson CR. 1975. Best linear unbiased estimation and prediction under a selection model. Biometrics 31:423-447.  https://doi.org/10.2307/2529430
  9. Jang SB, Kim SY, Lee SH, Shin MG, Kang JM, Lee DH, Kim SD, Noh SH, Lee SH, Choi TJ. 2019. The effect of progeny numbers and pedigree depth on the accuracy of the EBV with the BLUP method. Korean Journal of Agricultural Science 46:293-301. [in Korean] 
  10. KIAPQE (Korea Institute for Animal Products Quality Evaluation). 2020. 2019 animal products grading statistical yearbook. KIPQE, Sejong, Korea. [in Korean] 
  11. Kim EH, Kim HK, Sun DW, Kang HC, Lee DH, Lee SH, Lee JB, Lim HT. 2020. The study on estimated breeding value and accuracy for economic traits in Gyoungnam Hanwoo cow (Korean cattle). Journal of Animal Science and Technology 62:429-437. 
  12. Kinghorn B, Kinghorn AJ. 2010. Pedigree viewer. Ver. 6.5. University of New England, Armidale, Australia. 
  13. KMTA (Korea Meat Trade Association). 2021. Consumption status of statistical data room. Accessed in http://www.kmta.or.kr/kr/data/stats_spend.php on 3 August 2021. [in Korean] 
  14. Lee CW, Choi JW, Shin HJ, Kim JB. 2020. Genetic prediction of Hanwoo carcass traits in Kangwon regional Hanwoo cow test farms. Annals of Animal Resources Science 31:1-12. [in Korean]  https://doi.org/10.12718/AARS.2020.31.1.1
  15. Lee JJ. 2012. Genetic evaluation for carcass traits of Hanwoo using pedigree and SNP marker-derived relationship matrix. Ph.D. dissertation, Chungbuk National Univ., Cheongju, Korea. [in Korean] 
  16. Lee SS, Lee SH, Choi TJ, Choy YH, Cho KH, Choi YL, Cho YM, Kim NS, Lee JJ. 2013. Estimation of the accuracy of genomic breeding value in Hanwoo (Korean Cattle). Journal of Animal Science and Technology 55:13-18. [in Korean]  https://doi.org/10.5187/JAST.2013.55.1.13
  17. Mehrban H, Naserkheil M, Lee DH, Ibanez-Escriche N. 2021. Genetic parameters and correlations of related feed efficiency, growth, and carcass traits in Hanwoo beef cattle. Animal Bioscience 34:824-832.  https://doi.org/10.5713/ajas.20.0135
  18. Meuwissen THE, Hayes BJ, Goddard ME. 2001. Prediction of total genetic value using genome-wide dense marker maps. Genetics 157:1819-1829.  https://doi.org/10.1093/genetics/157.4.1819
  19. Miar Y, Plastow GS, Bruce HL, Moore SS, Durunna ON, Nkrumah JD, Wang Z. 2013. Estimation of genetic and phenotypic parameters for ultrasound and carcass merit traits in crossbred beef cattle. Canadian Journal of Animal Science 94:273-280. 
  20. Misztal I, Tsuruta S, Lourenco DAL, Masuda Y, Aguilar I, Legarra A, Vitezica Z. 2018. Manual for BLUPF90 family programs. University of Georgia. Accessed in http://nce.ads.uga.edu/wiki/doku.php?id=documentation on 18 July 2021. 
  21. Park BH, Choi TJ, Park MN, Oh SH. 2020. Estimation of environmental effects and genetic parameters of carcass traits on Chikso (Korean brindle cattle). Asian-Australasian Journal of Animal Science 33:252-530. 
  22. Parnell PF. 1984. Best linear unbiased prediction (BLUP) and the design of breeding programs. Animal Production in Australia 15:513-516. 
  23. Pszczola M, Strabel T, Mulder HA, Calus MP. 2021. Reliability of direct genomic values for animals with different relationships within and to the reference population. Journal of Dairy Science 95:389-400.  https://doi.org/10.3168/jds.2011-4338
  24. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, et al. 2007. PLINK: A toolset for whole-genome association and population-based linkage analysis. American Journal of Human Genetics 81:559-575.  https://doi.org/10.1086/519795
  25. Rolf MM, Taylor JF, Schnabel RD, McKay SD, McClure MC, Northcutt SL, Kerley MS, Weaber RL. 2010. Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle. BMC Genetic 11:1-10.  https://doi.org/10.1186/1471-2156-11-1
  26. Shin CG. 2008. Hanwoo calf selection method based on breeding value. Ph.D. dissertation, Gyeongsang National Univ., Jinju, Korea. [in Korean] 
  27. Shin EG, Lee SH, Yoon DH. 2018. Accuracy of genomic estimated breeding value with Hanwoo cow in the commercial farms. Journal of Agriculture & Life Science 52:91-98. [in Korean]  https://doi.org/10.14397/jals.2018.52.2.91
  28. Su G, Brondum RF, Ma P, Guldbrandtsen B, Aamand GP, Lund MS. 2012. Comparison of genomic predcitions using medium-density (~54,000) and high-density (~777,000) single nucleotide polymorphism marker panels in Nordic Holstein and Red Dairy Cattle population. Journal of Dairy Science 95:4657-4665.  https://doi.org/10.3168/jds.2012-5379
  29. Utrera AR, Van Vleck LD. 2004. Heritability estimates for carcass traits of cattle: A review. Genetics and Molecular Research 3:380-394. 
  30. VanRaden PM, Van Tassell CP, Wiggans GR, Sonstegard TS, Schnabel RD, Taylor JF, Schenkel FS. 2009. Invited review: Reliability of genomic predictions for North American Holstein bulls. Journal of Dairy Science 92:16-24.  https://doi.org/10.3168/jds.2008-1514