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Genomic evaluation of feed efficiency component traits in Duroc pigs using 80K 650K and whole-genome sequence variants

机译:使用80K650K和全基因组序列变异对Duroc猪的饲料效率成分性状进行基因组评估

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摘要

BackgroundIncreasing marker density was proposed to have potential to improve the accuracy of genomic prediction for quantitative traits; whole-sequence data is expected to give the best accuracy of prediction, since all causal mutations that underlie a trait are expected to be included. However, in cattle and chicken, this assumption is not supported by empirical studies. Our objective was to compare the accuracy of genomic prediction of feed efficiency component traits in Duroc pigs using single nucleotide polymorphism (SNP) panels of 80K, imputed 650K, and whole-genome sequence variants using GBLUP, BayesB and BayesRC methods, with the ultimate purpose to determine the optimal method to increase genetic gain for feed efficiency in pigs.
机译:背景技术提出增加标记物密度具有提高定量特征基因组预测准确性的潜力。预计全序列数据将提供最佳的预测准确性,因为预计将包含构成性状的所有因果突变。但是,在牛和鸡中,这一假设不受经验研究的支持。我们的目的是比较使用80K,推算650K的单核苷酸多态性(SNP)面板和使用GBLUP,BayesB和BayesRC方法的全基因组序列变体对Duroc猪的饲料效率成分性状进行基因组预测的准确性,其最终目的是确定增加猪饲料效率遗传增益的最佳方法。

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