2. VanRaden PM, Van Tassell CP, Wiggans GR, et al. Invited review: Reliability of genomic predictions for North American Holstein bulls. J Dairy Sci 2009; 92:16–24.
https://doi.org/10.3168/jds.2008-1514
3. Hayes BJ, Bowman PJ, Chamberlain AJ, Goddard ME. Invited review: Genomic selection in dairy cattle: progress and challenges. J Dairy Sci 2009; 92:433–43.
https://doi.org/10.3168/jds.2008-1646
4. Aguilar I, Misztal I, Johnson DL, Legarra A, Tsuruta S, Lawlor TJ. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. J Dairy Sci 2010; 93:743–52.
https://doi.org/10.3168/jds.2009-2730
5. Baloche G, Legarra A, Sallé G, et al. Assessment of accuracy of genomic prediction for French Lacaune dairy sheep. J Dairy Sci 2014; 97:1107–16.
https://doi.org/10.3168/jds.2013-7135
10. Aguilar I, Misztal I, Tsuruta S, Legarra A, Wang H. PREGSF90-POSTGSF90: Computational tools for the implementation of single-step genomic selection and genome-wide association with ungenotyped individuals in BLUPF90 programs. In : Proceedings of the 10th World Congress of Genetics Applied to Livestock Production; 2014; Vancouver, Canada.
https://doi.org/10.13140/2.1.4801.5045
11. Boichard D. PEDIG: A FORTRAN package for pedigree analysis suited for large populations. In : 7th world congress on genetics applied to livestock production; 2002 August 19–23; Montpellier, France.
12. Sargolzaei M, Iwaisaki H, Colleau JJ. CFC: A tool for monitoring genetic diversity. In : Proceedings of the 8th world congress on genetics applied to livestock production; 2006 August 13–18; Belo Horizonte, MG, Brasil. Minas Gerais, Brazil: Instituto Prociência; 2006. p. 27–8.
19. Lee SH, Kim HC, Lim D, et al. Prediction of genomic breeding values of carcass traits using whole genome SNP data in Hanwoo (Korean cattle). CNU J Agric Sci 2012; 39:357–64.
https://doi.org/10.7744/CNUJAS.2012.39.3.357
22. Lee DH. Methods for genetic parameter estimations of carcass weight, longissimus muscle area and marbling score in Korean cattle. J Anim Sci Technol 2004; 46:509–16.
https://doi.org/10.5187/JAST.2004.46.4.509
24. Roh SH, Kim BW, Kim HS, et al. Comparison between REML and Bayesian via Gibbs sampling algorithm with a mixed animal model to estimate genetic parameters for carcass traits in Hanwoo (Korean native cattle). J Anim Sci Technol 2004; 46:719–28.
https://doi.org/10.5187/JAST.2004.46.5.719
25. Roh SH, Kim CY, Won YS, Park CJ, Lee SS, Lee JG. Studies on genetic parameter estimation and sire selection to ultrasound measurement traits of Hanwoo. J Anim Sci Technol 2010; 52:1–8.
https://doi.org/10.5187/JAST.2010.52.1.001
26. Kim JB, Kim DJ, Lee JK, Lee CY. Genetic relationship between carcass traits and carcass price of Korean cattle. Asian-Australas J Anim Sci 2010; 23:848–54.
https://doi.org/10.5713/ajas.2010.90555
27. Lee DH, Kim HC. Genetic relationship between ultrasonic and carcass measurements for meat qualities in Korean steers. Asian-Australas J Anim Sci 2004; 17:7–12.
https://doi.org/10.5713/ajas.2004.7