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单倍型中标记数量及单倍型聚类对QTL定位准确性和基因组育种值预测的影响。

Effects of the number of markers per haplotype and clustering of haplotypes on the accuracy of QTL mapping and prediction of genomic breeding values.

作者信息

Calus Mario P L, Meuwissen Theo H E, Windig Jack J, Knol Egbert F, Schrooten Chris, Vereijken Addie L J, Veerkamp Roel F

机构信息

Animal Breeding and Genomics Centre, Animal Sciences Group, Wageningen University and Research Centre, Lelystad, The Netherlands.

出版信息

Genet Sel Evol. 2009 Jan 15;41(1):11. doi: 10.1186/1297-9686-41-11.

DOI:10.1186/1297-9686-41-11
PMID:19284677
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3225874/
Abstract

The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.

摘要

本文旨在比较单倍型定义对QTL定位精度和预测基因组育种值准确性的影响。在一个使用单倍型间同源性(IBD)概率的多QTL模型中,测试了各种单倍型定义,即包括2、6、12或20个标记等位基因,并对与IBD概率>0.55、0.75或0.95相关的基础单倍型进行聚类。模拟数据包含1100只已知基因型和表型的动物以及1000只已知基因型和未知表型的动物。模拟了包含3摩根的基因组,其中包含74个多态性QTL和383个多态性SNP标记,相邻标记之间的平均r2值为0.14。当窗口大小从两个标记增加到20个标记时,单倍型总数减少了50%,当对与IBD概率>0.55而非>0.95相关的单倍型进行聚类时,单倍型总数至少减少了50%。中等窗口大小可实现更精确的QTL定位。窗口大小和聚类对预测总育种值准确性的影响有限,范围为0.79至0.81。我们的结论是,在QTL定位与全基因组育种值预测中应使用不同的最佳窗口大小。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/9f99069eb378/1297-9686-41-11-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/a18eb7fdc516/1297-9686-41-11-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/b382cbc4f388/1297-9686-41-11-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/856db95db782/1297-9686-41-11-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/9f99069eb378/1297-9686-41-11-4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/a18eb7fdc516/1297-9686-41-11-1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/b382cbc4f388/1297-9686-41-11-2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/856db95db782/1297-9686-41-11-3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b16d/3225874/9f99069eb378/1297-9686-41-11-4.jpg

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