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Genomic-polygenic evaluation for ultrasound and weight traits in Angus–Brahman multibreed cattle with the Illumina3k chip

, , , , , , , , и .
Livestock Science, 153 (1–3): 39 - 49 (2013)
DOI: http://dx.doi.org/10.1016/j.livsci.2013.02.002

Аннотация

The objectives of this study were to estimate the proportion of additive genetic and phenotypic variances explained by the \SNP\ markers in the Illumina3K chip for 4 postweaning ultrasound carcass and weight traits, to compare rankings of calf predicted additive genetic values with 3 models, and to evaluate trends of calf predictions as Brahman fraction increased from 0 to 1. Traits were postweaning ultrasound measures of ribeye area (UREA), backfat thickness (UFAT), intramuscular fat (UPIMF), and body weight at time of ultrasound (UW). Models were genomic-polygenic, genomic, and polygenic. Phenotypes and genotypes were from 623 bulls, heifers, and steers ranging in breed composition from 100% Angus to 100% Brahman fed for 90 d at a GrowSafe automated feeding facility from 2006 to 2010. Variance components were estimated with Markov Chain Monte Carlo procedures (option VCE, program GS3) using a single-trait genomic-polygenic model. Fixed effects were contemporary group (year-pen), age of dam, sex of calf, age of calf, Brahman fraction of calf, and heterozygosity of calf. Random effects were additive SNP, animal polygenic, and residual effects. Models without polygenic effects were used for genomic predictions, and without additive \SNP\ effects for polygenic predictions. Fractions of additive genetic variances explained by the \SNP\ in the Illumina3K chip were 9% for UREA, 38% for UBF, 6% for UPIMF, and 8% for UW. Phenotypic variance fractions explained by Illumina3K \SNP\ were 3.7% for UREA, 9.7% for UBF, 3.2% for UPIMF, and 4.6% for UW. Substantially higher rank correlations existed between genomic-polygenic and polygenic models (0.89 to 0.99) than between genomic-polygenic and genomic (0.64 to 0.79), and genomic and polygenic (0.51 to 0.65) models. Genomic-polygenic, genomic, and polygenic predicted values tended to decrease as Brahman fraction of calf increased suggesting that calves with higher percentage Brahman grew more slowly and had less desirable ultrasound carcass traits. However, there were calves with high, medium, and low predicted genetic values across the Angus–Brahman spectrum, suggesting that selection of animals with desirable postweaning ultrasound carcass and growth traits using a genomic-polygenic strategy would be effective in this multibreed population. Insofar as this multibreed herd represents commercial operations in Florida and the Southern region of the US, selection of commercial calves for these postweaning traits would likely increase their rate of improvement in Brahman and Brahman crossbred populations.

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