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利用全基因组密集标记图谱预测总遗传值。

Prediction of total genetic value using genome-wide dense marker maps.

作者信息

Meuwissen T H, Hayes B J, Goddard M E

机构信息

Research Institute of Animal Science and Health, 8200 AB Lelystad, The Netherlands.

出版信息

Genetics. 2001 Apr;157(4):1819-29. doi: 10.1093/genetics/157.4.1819.

DOI:10.1093/genetics/157.4.1819
PMID:11290733
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC1461589/
Abstract

Recent advances in molecular genetic techniques will make dense marker maps available and genotyping many individuals for these markers feasible. Here we attempted to estimate the effects of approximately 50,000 marker haplotypes simultaneously from a limited number of phenotypic records. A genome of 1000 cM was simulated with a marker spacing of 1 cM. The markers surrounding every 1-cM region were combined into marker haplotypes. Due to finite population size N(e) = 100, the marker haplotypes were in linkage disequilibrium with the QTL located between the markers. Using least squares, all haplotype effects could not be estimated simultaneously. When only the biggest effects were included, they were overestimated and the accuracy of predicting genetic values of the offspring of the recorded animals was only 0.32. Best linear unbiased prediction of haplotype effects assumed equal variances associated to each 1-cM chromosomal segment, which yielded an accuracy of 0.73, although this assumption was far from true. Bayesian methods that assumed a prior distribution of the variance associated with each chromosome segment increased this accuracy to 0.85, even when the prior was not correct. It was concluded that selection on genetic values predicted from markers could substantially increase the rate of genetic gain in animals and plants, especially if combined with reproductive techniques to shorten the generation interval.

摘要

分子遗传技术的最新进展将使密集的标记图谱成为可能,并且对许多个体进行这些标记的基因分型也切实可行。在此,我们试图从有限数量的表型记录中同时估计约50,000个标记单倍型的效应。模拟了一个长度为1000厘摩(cM)的基因组,标记间距为1厘摩。将每1厘摩区域周围的标记组合成标记单倍型。由于有效种群大小N(e)=100,标记单倍型与位于标记之间的数量性状基因座(QTL)处于连锁不平衡状态。使用最小二乘法,无法同时估计所有单倍型效应。当只纳入最大效应时,它们被高估了,并且记录动物后代遗传值预测的准确性仅为0.32。单倍型效应的最佳线性无偏预测假设与每个1厘摩染色体区段相关的方差相等,尽管这一假设远非真实,但预测准确性达到了0.73。即使先验分布不正确,假设与每个染色体区段相关方差的先验分布的贝叶斯方法也将这一准确性提高到了0.85。得出的结论是,基于标记预测的遗传值进行选择可以大幅提高动植物的遗传增益率,特别是如果与生殖技术相结合以缩短世代间隔的话。

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