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牛的肥育和生长性状的全基因组关联研究。

Genome-wide association studies for feedlot and growth traits in cattle.

机构信息

Cooperative Research Centre for Beef Genetic Technologies, Armidale, New South Wales 2351, Australia.

出版信息

J Anim Sci. 2011 Jun;89(6):1684-97. doi: 10.2527/jas.2010-3079. Epub 2011 Jan 14.

Abstract

A genome wide-association study for production traits in cattle was carried out using genotype data from the 10K Affymetrix (Santa Clara, CA) and the 50K Illumina (San Diego, CA) SNP chips. The results for residual feed intake (RFI), BW, and hip height in 3 beef breed types (Bos indicus, Bos taurus, and B. indicus × B. taurus), and for stature in dairy cattle, are presented. The aims were to discover SNP associated with all traits studied, but especially RFI, and further to test the consistency of SNP effects across different cattle populations and breed types. The data were analyzed within data sets and within breed types by using a mixed model and fitting 1 SNP at a time. In each case, the number of significant SNP was more than expected by chance alone. A total of 75 SNP from the reference population with 50K chip data were significant (P < 0.001) for RFI, with a false discovery rate of 68%. These 75 SNP were mapped on 24 different BTA. Of the 75 SNP, the 9 most significant SNP were detected on BTA 3, 5, 7, and 8, with P ≤ 6.0 × 10(-5). In a population of Angus cattle divergently selected for high and low RFI and 10K chip data, 111 SNP were significantly (P < 0.001) associated with RFI, with a false discovery rate of 7%. Approximately 103 of these SNP were therefore likely to represent true positives. Because of the small number of SNP common to both the 10K and 50K SNP chips, only 27 SNP were significantly (P < 0.05) associated with RFI in the 2 populations. However, other chromosome regions were found that contained SNP significantly associated with RFI in both data sets, although no SNP within the region showed a consistent effect on RFI. The SNP effects were consistent between data sets only when estimated within the same breed type.

摘要

进行了一项全基因组关联研究,使用来自 10K Affymetrix(加利福尼亚州圣克拉拉)和 50K Illumina(加利福尼亚州圣地亚哥)SNP 芯片的基因型数据,研究牛的生产性状。呈现了 3 种肉牛品种(印度野牛、普通牛和印度野牛×普通牛)的剩余饲料摄入量(RFI)、体重和臀部高度以及奶牛的体高的结果。目的是发现与所有研究性状相关的 SNP,特别是 RFI,并进一步测试 SNP 效应在不同牛种群和品种类型中的一致性。数据通过混合模型在数据集内和品种类型内进行分析,一次拟合 1 个 SNP。在每种情况下,显著 SNP 的数量都超过了仅靠机会预测的数量。来自参考群体的 75 个 SNP 与 50K 芯片数据的 RFI 显著相关(P < 0.001),假发现率为 68%。这 75 个 SNP 映射到 24 个不同的 BTA 上。在一个具有高和低 RFI 以及 10K 芯片数据的 Angus 牛群体中,111 个 SNP 与 RFI 显著相关(P < 0.001),假发现率为 7%。因此,大约 103 个 SNP 可能代表真正的阳性。由于两种 10K 和 50K SNP 芯片共有的 SNP 数量较少,因此仅在 2 个群体中发现 27 个 SNP 与 RFI 显著相关(P < 0.05)。然而,在两个数据集之间发现了包含与 RFI 显著相关 SNP 的其他染色体区域,尽管该区域内没有 SNP 对 RFI 表现出一致的影响。仅当在同一品种类型内进行估计时,SNP 效应才在数据集之间保持一致。

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