4.7 Article

Genome-wide association study and genomic predictions for exterior traits in Yorkshire pigs

期刊

JOURNAL OF ANIMAL SCIENCE
卷 97, 期 7, 页码 2793-2802

出版社

OXFORD UNIV PRESS INC
DOI: 10.1093/jas/skz158

关键词

Bayesian method; exterior traits; genomic prediction; GWAS; Yorkshire pigs

资金

  1. Ministry of Education of the Republic of Korea [NRF-2019R1A6A1A03025159]
  2. National Research Foundation of Korea [NRF-2019R1A6A1A03025159]
  3. Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries through the Golden Seed Project, Ministry of Agriculture, Food, and Rural Affairs [213010-05-3-SB510]
  4. Cooperative Research Program for Agriculture Science and Technology Development of the Rural Development Administration, Republic of Korea [PJ012817012019]
  5. Rural Development Administration (RDA), Republic of Korea [PJ012817012019] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

The objectives of this study were to identify informative genomic regions that affect the exterior traits of purebred Korean Yorkshire pigs and to investigate and compare the accuracy of genomic prediction for response variables. Phenotypic data on body height (BH), body length (BL), and total teat number (TTN) from 2,432 Yorkshire pigs were used to obtain breeding values including as response variable the estimated breeding value (EBV) and 2 types of deregressed EBVs-one including the parent average (DEBVincPA) and the other excluding it (DEBVexcPA). A final genotype panel comprising 46,199 SNP markers was retained for analysis after quality control for common SNPs. The BayesB and BayesC methods-with various p and weighted response variables (EBV, DEBVincPA, or DEBVexcPA)-were used to estimate SNP effects, through the genome-wide association study. The significance of genomic windows (1 Mb) was obtained at 1.0% additive genetic variance and was subsequently used to identify informative genomic regions. Furthermore, SNPs with a high model frequency (>= 0.90) were considered informative. The accuracy of genomic prediction was estimated using a 5-fold cross-validation with the K-means clustering method. Genomic accuracy was measured as the genomic correlation between the molecular breeding value and the individual weighted response variables (EBV, DEBVincPA, or DEBVexcPA). The number of identified informative windows (1 Mb) for BH, BL, and TTN was 4, 3, and 4, respectively. The number of significant SNPs for BH, BL, and TTN was 6, 4, and 5, respectively. Diversity p did not influence the accuracy of genomic prediction. The BayesB method showed slightly higher genomic accuracy for exterior traits than BayesC method in this study. In addition, the genomic accuracy using DEBVincPA as response variable was higher than that using other response variables. Therefore, the genomic accuracy using BayesB (pi = 0.90) with DEBVinPA as a response variable was the most effective in this study. The genomic accuracy values for BH, BL, and TTN were calculated to be 0.52, 0.60, and 0.51, respectively.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据