Genome-wide association study of Stayability and Heifer Pregnancy in Red Angus cattle

被引:9
作者
Speidel, S. E. [1 ]
Buckley, B. A. [2 ]
Boldt, R. J. [1 ]
Enns, R. M. [1 ]
Lee, J. [3 ]
Spangler, M. L. [3 ]
Thomas, M. G. [1 ]
机构
[1] Colorado State Univ, Dept Anim Sci, Ft Collins, CO 80523 USA
[2] Univ Hawaii Manoa, Dept Human Nutr Food & Anim Sci, Honolulu, HI 96822 USA
[3] Univ Nebraska, Dept Anim Sci, Lincoln, NE 68583 USA
关键词
Heifer Pregnancy; quantitative trait loci; Red Angus; Stayability; ORDERED CATEGORICAL-DATA; 1ST SERVICE CONCEPTION; BRANGUS HEIFERS; MODEL; GENE;
D O I
10.1093/jas/sky041
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
Reproductive performance is the most important component of cattle production from the standpoint of economic sustainability of commercial beef enterprises. Heifer Pregnancy (HPG) and Stayability (STAY) genetic predictions are 2 selection tools published by the Red Angus Association of America (RAAA) to assist with improvements in reproductive performance. Given the importance of HPG and STAY to the profitability of commercial beef enterprises, the objective of this study was to identify QTL associated with both HPG and STAY in Red Angus cattle. A genome-wide association study (GWAS) was performed using deregressed HPG and STAY EBV, calculated using a single-trait animal model and a 3-generation pedigree with data from the Spring 2015 RAAA National Cattle Evaluation. Each individual animal possessed 74,659 SNP genotypes. Individual animals with a deregressed EBV reliability > 0.05 were merged with the genotype file and marker quality control was performed. Criteria for sifting genotypes consisted of removing those markers where any of the following were found: average call rate less than 0.85, minor allele frequency < 0.01, lack of Hardy-Weinberg equilibrium (P < 0.0001), or extreme linkage disequilibrium (r(2) > 0.99). These criteria resulted in 2,664 animals with 62,807 SNP available for GWAS. Association studies were performed using a Bayes C pi model in the BOLT software package. Marker significance was calculated as the posterior probability of inclusion (PPI), or the number of instances a specific marker was sampled divided by the total number of samples retained from the Markov chain Monte Carlo chains. Nine markers, with a PPI >= 3% were identified as QTL associated with HPG on BTA 1, 11, 13, 23, and 29. Twelve markers, with a PPI = 75% were identified as QTL associated with STAY on BTA 6, 8, 9, 12, 15, 18, 22, and 23.
引用
收藏
页码:846 / 853
页数:8
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