Asian-Australasian Journal of Animal Sciences

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

DOI QR Code

Effect of errors in pedigree on the accuracy of estimated breeding value for carcass traits in Korean Hanwoo cattle

  • Nwogwugwu, Chiemela Peter (Division of Animal and Dairy Science, Chungnam National University) ;
  • Kim, Yeongkuk (Division of Animal and Dairy Science, Chungnam National University) ;
  • Chung, Yun Ji (Division of Animal and Dairy Science, Chungnam National University) ;
  • Jang, Sung Bong (Division of Animal and Dairy Science, Chungnam National University) ;
  • Roh, Seung Hee (Hanwoo Improvement Center, National Agricultural Cooperative Federation) ;
  • Kim, Sidong (National Institute of Animal Science) ;
  • Lee, Jun Heon (Division of Animal and Dairy Science, Chungnam National University) ;
  • Choi, Tae Jeong (National Institute of Animal Science) ;
  • Lee, Seung-Hwan (Division of Animal and Dairy Science, Chungnam National University)
  • Received : 2019.01.09
  • Accepted : 2019.09.02
  • Published : 2020.07.01
Download PDF
⟨ Previous Next ⟩

Abstract

Objective: This study evaluated the effect of pedigree errors (PEs) on the accuracy of estimated breeding value (EBV) and genetic gain for carcass traits in Korean Hanwoo cattle. Methods: The raw data set was based on the pedigree records of Korean Hanwoo cattle. The animals' information was obtained using Hanwoo registration records from Korean animal improvement association database. The record comprised of 46,704 animals, where the number of the sires used was 1,298 and the dams were 38,366 animals. The traits considered were carcass weight (CWT), eye muscle area (EMA), back fat thickness (BFT), and marbling score (MS). Errors were introduced in the pedigree dataset through randomly assigning sires to all progenies. The error rates substituted were 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, and 80%, respectively. A simulation was performed to produce a population of 1,650 animals from the pedigree data. A restricted maximum likelihood based animal model was applied to estimate the EBV, accuracy of the EBV, expected genetic gain, variance components, and heritability (h2) estimates for carcass traits. Correlation of the simulated data under PEs was also estimated using Pearson's method. Results: The results showed that the carcass traits per slaughter year were not consistent. The average CWT, EMA, BFT, and MS were 342.60 kg, 78.76 ㎠, 8.63 mm, and 3.31, respectively. When errors were introduced in the pedigree, the accuracy of EBV, genetic gain and h2 of carcass traits was reduced in this study. In addition, the correlation of the simulation was slightly affected under PEs. Conclusion: This study reveals the effect of PEs on the accuracy of EBV and genetic parameters for carcass traits, which provides valuable information for further study in Korean Hanwoo cattle.

Keywords

References

  1. Annual report, directory and career opportunities 2019-2020 [Internet]. San Marcos, TX, USA: National Pedigreed Livestock Council; 2019 [2019 Nov 11]. Available from: http://www.nplc.net
  2. Carmen LB. Pedigree analysis. Tufts' Canine and Feline Breeding and Genetics Conference, 2007; Sturbridge, MA, USA.
  3. Meuwissen THE. Maximizing the response of selection with a predefined rate of inbreeding. J Anim Sci 1997;75:934-40. https://doi.org/10.2527/1997.754934x
  4. Steyn JW, Neser FWC, Hunlun C, Lubout PC. Preliminary report: Pedigree analysis of the Brangus cattle in South Africa. S Afr J Anim Sci 2012;42:511-4. https://doi.org/10.4314/sajas. v42i5.14
  5. Lee SH, Park BH, Sharma A, et al. Hanwoo cattle: origin, domestication, breeding strategies and genomic selection. J Anim Sci Technol 2014;56:2. https://doi.org/10.1186/2055-0391-56-2
  6. Lee SH, Choi BH, Cho SH, et al. Genome-wide association study identifies three loci for intramuscular fat in Hanwoo (Korean cattle). Livest Sci 2014;165:27-32. https://doi.org/10.1016/j.livsci.2014.04.006
  7. Lee SH, Choi BH, et al. Genome-wide association study identifies major loci for carcass weight on BTA14 in Hanwoo (Korean cattle). PLoS ONE 2013;8:e74677. https://doi.org/10.1371/journal.pone.0074677
  8. Long TE, Johnson RK, Keele JW. Effects of errors in pedigree on three methods of estimating breeding value for litter size, backfat and average daily gain in swine. J Anim Sci 1990;68:4069-78. https://doi.org/10.2527/1990.68124069x
  9. Harder B, Bennewitz J, Reinsch N, Mayer M, Kalm E. Effect of missing sire information on genetic evaluation. Arch Anim Breed 2005;48:219-32. https://doi.org/10.5194/aab-48-219- 2005
  10. Israel C, Weller JI. Effect of misidentification on genetic gain and estimation of breeding value in dairy cattle populations. J Dairy Sci 2000;83:181-7. https://doi.org/10.3168/jds.S0022- 0302(00)74869-7
  11. Christensen LG, Madsen P, Petersen J. The influence of incorrect sire identification on the estimates of genetic parameters and breeding values. In: Proceedings of the World Congress on Genetics Applied to Livestock Production; 1982: Madrid, Spain. pp. 200-8.
  12. Gelderman H, Pieper U, Weber WE. Effect of misidentification on the estimation of breeding value and heritability in cattle. J Anim Sci 1986;63:1759-68. https://doi.org/10.2527/jas1986. 6361759x
  13. Ron M, Blanc Y, Band M, Ezra E, Weller JI. Misidentification rate in the Israeli dairy cattle population and its implications for genetic improvement. J Dairy Sci 1996;79:676-81. https://doi.org/10.3168/jds.S0022-0302(96)76413-5
  14. Van Vleck LD. Misidentification in estimating the paternal sib correlation. J Dairy Sci 1970;53:1469-74. https://doi.org/10.3168/jds.S0022-0302(70)86416-5
  15. Van Vleck LD. Misidentification and sire evaluation. J Dairy Sci 1970;53:1697-702. https://doi.org/10.3168/jds.S0022-0302 (70)86465-7
  16. Korean Animal Improvement Association database [Internet]. Korean Animal Improvement Association; 2014. Available from: https://www.aiak.or.kr/ka_index.jsp
  17. Korea Institute for Animal Product Quality Evaluation (KAPQE). The report of livestock product marketing in Korea. Anyang, Korea: KAPQE; 2012.
  18. Kim HC, Lee SH, Cho YM et al. Genomic information and its application in Hanwoo (Korean native cattle) breeding program - a mini review. Ann Anim Resour Sci 2011;22:125- 33.
  19. Oliehoek PA, Bijma P. Effects of pedigree errors on the efficiency of conservation decisions. Genet Select Evol 2009;41:9. https://doi.org/10.1186/1297-9686-41-9
  20. Sargolzaei M, Schenkel FS. QMSim: A large-scale genome simulator for livestock. Bioinformatics 2009;25:680-1. https://doi.org/10.1093/bioinformatics/btp045
  21. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2013, URL http://www.R-project.org
  22. Henderson CR. Sire evaluation and genetic trends. J Anim Sci 1973;(Issue Symposium, 1973):10-41. https://doi.org/10.1093/ansci/1973.Symposium.10
  23. Park B, Choi T, Kim S, Oh SH. National genetic evaluation (system) of Hanwoo (Korean native cattle). Asian-Australas J Anim Sci 2013;26:151-6. https://doi.org/10.5713/ajas.2012.12439
  24. Yoon HB, Kim SD, Na SH, et al. Estimation of genetic parameters for carcass traits in Hanwoo steers. J Anim Sci Technol 2002;44:383-90. https://doi.org/10.5187/JAST.2002.44.4.383
  25. Do C, Park B, Kim S, et al. Genetic parameter estimates of carcass traits under national scale breeding scheme for beef cattle. Asian-Australas J Anim Sci 2016;29:1083-94. https://doi.org/10.5713/ajas.15.0696
  26. Oikawa T, Sanehira T, Sato K, Mizoguchi Y, Yamamoto H, Baba M. Genetic parameters for growth and carcass traits of Japanese Black (Wagyu) cattle. Anim Sci 2000;71:59-64. https://doi.org/10.1017/S1357729800054898
  27. Fabrizio A, Alberto MB, Jean-Luc G, et al. Genotype by environment interaction on growth and carcass traits in beef cattle in the tropics. Adv Anim Biosci 2010;1:372-3. https://doi.org/10.1017/S2040470010000026
  28. Bovenhuis H, Van Arendonk JAM. Estimation of milk protein gene frequencies in crossbred cattle by maximum likelihood. J Dairy Sci 1991;74:2728-36. https://doi.org/10.3168/jds. S0022-0302(91)78452-X
  29. Banos G, Wiggans GR, Powell RL. Impact of paternity errors in cow identification on genetic evaluations and international comparisons. J Dairy Sci 2001;84:2523-9. https://doi.org/10.3168/jds.S0022-0302(01)74703-0
  30. Van Arendonk JAM, Spelman RS, van der Waaij EH, Bijma P, Bovenhuis H. Livestock breeding schemes: challenges and opportunities. In: Proceedings of the 6th World Congress on Genetics Applied to Livestock Production; 1998: Armidale, Australia. pp. 407-14.
  31. Sanders K, Bennewitz J, Kalm E. Wrong and missing sire information affects genetic gain in the Angeln dairy cattle population. J Dairy Sci 2006;89:315-21. https://doi.org/10.3168/jds.S0022-0302(06)72096-3
  32. Richard MB. Understanding animal breeding. 2nd ed. London, UK: Pearson New International Edition; 2013.
  33. Senneke SL, MacNeil MD, Van Vleck LD. Effects of sire misidentification on estimates of genetic parameters for birth and weaning weights in Hereford cattle. J Anim Sci 2004;82:2307-12. https://doi.org/10.2527/2004.8282307x
  34. Parlato E, Van Vleck LD. Effect of parentage misidentification on estimates of genetic parameters for milk yield in the Mediterranean Italian buffalo population. J Dairy Sci 2012;95:4059-64. https://doi.org/10.3168/jds.2011-4855

Cited by

  1. Assessment of genomic prediction accuracy using different selection and evaluation approaches in a simulated Korean beef cattle population vol.33, pp.12, 2020, https://doi.org/10.5713/ajas.20.0217
  2. Accounting for Genetic Differences Among Unknown Parents in Bubalus bubalis: A Case Study From the Italian Mediterranean Buffalo vol.12, 2020, https://doi.org/10.3389/fgene.2021.625335