Estimation of genetic parameters and accuracy of genomic prediction for production traits in Duroc pigs

Lopez B.I., Viterbo V., Song C.W., Seo K.S., (2019): Estimation of genetic parameters and accuracy of genomic prediction for production traits in Duroc pigs. Czech J. Anim. Sci., 64: 160-165.

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Abstract: Genetic parameters and accuracy of genomic prediction for production traits in a Duroc population were estimated. Data were on 24 828 purebred Duroc pigs born in 2000–2016. After quality control procedures, 30 263 single nucleotide polymorphism markers and 560 animals remained that were used to predict the genomic breeding values of individuals. Accuracies of predicted breeding values for average daily gain (ADG), backfat thickness (BF), loin muscle area (LMA), lean percentage (LP) and age at 90 kg (D90) between pedigree-based and single-step methods were compared. Analyses were carried out with a multivariate animal model to estimate genetic parameters for production traits while univariate analyses were performed to predict the genomic breeding values of individuals. Heritability estimates from pedigree analysis were moderate to high. Heritability estimates and standard error for ADG, BF, LMA, LP and D90 were 0.35 ± 0.01, 0.35 ± 0.11, 0.24 ± 0.04, 0.42 ± 0.11 and 0.37 ± 0.03, respectively. Genetic correlations of ADG with BF and LP were low and negative. Genetic correlations of LMA with ADG, BF, LP and D90 were –0.37, –0.27, 0.48 and 0.31, respectively. High correlations were observed between ADG and D90 (–0.98), and also between BF and LP (–0.93). Accuracies of genomic breeding values for ADG, BF, LMA, LP and D90 were 0.30, 0.33, 0.38, 0.40 and 0.28, respectively. Corresponding accuracies using pedigree-based method were 0.29, 0.32, 0.38, 0.39 and 0.27, respectively. The results showed that the single-step method did not show significant advantage compared to the pedigree-based method.

Aguilar I., Misztal I., Johnson D.L., Legarra A., Tsuruta S., Lawlor T.J. (2010): Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 93, 743-752
Akanno E.C., Schenkel F.S., Quinton V.M., Friendship R.M., Robinson J.A.B. (2013): Meta-analysis of genetic parameter estimates for reproduction, growth and carcass traits of pigs in the tropics. Livestock Science, 152, 101-113
Akanno E.C., Schenkel F.S., Sargolzaei M., Friendship R.M., Robinson J.A.B. (2014): Persistency of accuracy of genomic breeding values for different simulated pig breeding programs in developing countries. Journal of Animal Breeding and Genetics, 131, 367-378
Boichard Didier, Ducrocq Vincent, Croiseau Pascal, Fritz Sébastien (2016): Genomic selection in domestic animals: Principles, applications and perspectives. Comptes Rendus Biologies, 339, 274-277
Cabling M. M., Kang H. S., Lopez B. M., Jang M., Kim H. S., Nam K. C., Choi J. G., Seo K. S. (2015): Estimation of Genetic Associations between Production and Meat Quality Traits in Duroc Pigs. Asian-Australasian Journal of Animal Sciences, 28, 1061-1065
Chang Hsiu-Luan, Lai Yung-Yu, Wu Ming-Che, Sasaki Osamu (2017): Genetic correlations between male reproductive traits and growth traits in growth performance tested Duroc, Landrace and Yorkshire breed boars. Animal Science Journal, 88, 1258-1268
Chen P., Baas T.J., Mabry J.W., Dekkers J.C.M., Koehler K.J. (2002): Genetic parameters and trends for lean growth rate and its components in U.S. Yorkshire, Duroc, Hampshire, and Landrace pigs. Journal of Animal Science,
80, 2062–2070.
Choi Jae Gwan, Cho Chung Il, Choi Im Soo, Lee Seung Soo, Choi Tae Jeong, Cho Kwang Hyun, Park Byoung Ho, Choy Yun Ho (2013): Genetic Parameter Estimation in Seedstock Swine Population for Growth Performances. Asian-Australasian Journal of Animal Sciences, 26, 470-475
Choy Yun Ho, Mahboob Alam, Cho Chung Il, Choi Jae Gwan, Choi Im Soo, Choi Tae Jeong, Cho Kwang Hyun, Park Byoung Ho (2015): Genetic Parameters of Pre-adjusted Body Weight Growth and Ultrasound Measures of Body Tissue Development in Three Seedstock Pig Breed Populations in Korea. Asian-Australasian Journal of Animal Sciences, 28, 1696-1702
Christensen O. F., Madsen P., Nielsen B., Ostersen T., Su G. (2012): Single-step methods for genomic evaluation in pigs. animal, 6, 1565-1571
Do D. N., Strathe A. B., Jensen J., Mark T., Kadarmideen H. N. (2013): Genetic parameters for different measures of feed efficiency and related traits in boars of three pig breeds1. Journal of Animal Science, 91, 4069-4079
Dube B., Mulugeta S.D., Dzama K. (2014): Investigating maternal effects on production traits in Duroc pigs using animal and sire models. Journal of Animal Breeding and Genetics, 131, 279-293
Gianola Daniel, de los Campos Gustavo, Hill William G., Manfredi Eduardo, Fernando Rohan (2009): Additive Genetic Variability and the Bayesian Alphabet. Genetics, 183, 347-363
Guo Xiangyu, Christensen Ole Fredslund, Ostersen Tage, Wang Yachun, Lund Mogens Sandø, Su Guosheng (2016): Genomic prediction using models with dominance and imprinting effects for backfat thickness and average daily gain in Danish Duroc pigs. Genetics Selection Evolution, 48, -
Habier D., Fernando R. L., Dekkers J. C. M. (2007): The Impact of Genetic Relationship Information on Genome-Assisted Breeding Values. Genetics, 177, 2389-2397
Hoque M.A., Kadowaki H., Shibata T., Oikawa T., Suzuki K. (2009): Genetic parameters for measures of residual feed intake and growth traits in seven generations of Duroc pigs. Livestock Science, 121, 45-49
Imboonta N., Rydhmer L., Tumwasorn S. (2007): Genetic parameters and trends for production and reproduction traits in Thai Landrace sows. Livestock Science,
111, 70–79.
Jiao S., Maltecca C., Gray K. A., Cassady J. P. (2014): Feed intake, average daily gain, feed efficiency, and real-time ultrasound traits in Duroc pigs: II. Genomewide association. Journal of Animal Science, 92, 2846-2860
Kapell D. N. R. G., Ashworth C. J., Walling G. A., Lawrence A. B., Edwards S. A., Roehe R. (2009): Estimation of genetic associations between reproduction and production traits based on a sire and dam line with common ancestry. animal, 3, 1354-1362
Kim J. I., Sohn Y. G., Jung J. H., Park Y. I. (2004): Genetic Parameter Estimates for Backfat Thickness at Three Different Sites and Growth Rate in Swine. Asian-Australasian Journal of Animal Sciences, 17, 305-308
Legarra Andrés, Robert-Granié Christèle, Manfredi Eduardo, Elsen Jean-Michel (2008): Performance of Genomic Selection in Mice. Genetics, 180, 611-618
Lourenco D. A. L., Tsuruta S., Fragomeni B. O., Chen C. Y., Herring W. O., Misztal I. (2016): Crossbreed evaluations in single-step genomic best linear unbiased predictor using adjusted realized relationship matrices1. Journal of Animal Science, 94, 909-919
Misztal I., Tsuruta S., Lourenco D., Aguilar I., Legarra A., Vitezica Z. (2014): Manual for BLUPF90 Family of Programs. University of Georgia, Athens, USA.
Rothschild M.F., Ruvinsky A. (2011) The Genetics of the Pig. CABI, Wallingford, UK.
Samorè Antonia Bianca, Fontanesi Luca (2016): Genomic selection in pigs: state of the art and perspectives. Italian Journal of Animal Science, 15, 211-232
Simianer H. (2009): The potential of genomic selection to improve litter size in pig breeding programmes. In: Proc. 60th Annu. Mtg., European Association for Animal Production (EAAP), Barcelona, Spain, 210.
Su G., Christensen O.F., Ostersen T., Henryon M., Lund M.S. (2012): Estimating additive and non-additive genetic variances and predicting genetic merits using genome-wide dense single nucleotide polymorphism markers. PLoS ONE, 7, e45293.
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