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上位性数量性状基因座作图效率。

Efficiency of mapping epistatic quantitative trait loci.

机构信息

Department of General Biology, Federal University of Viçosa, 36570-900, Viçosa, MG, Brazil.

出版信息

Heredity (Edinb). 2023 Jul;131(1):25-32. doi: 10.1038/s41437-023-00618-5. Epub 2023 May 8.

Abstract

Most theoretical studies on epistatic QTL mapping have shown that this procedure is powerful, efficient to control the false positive rate (FPR), and precise to localize QTLs. The objective of this simulation-based study was to show that mapping epistatic QTLs is not an almost-perfect process. We simulated 50 samples of 400 F plants/recombinant inbred lines, genotyped for 975 SNPs distributed in 10 chromosomes of 100 cM. The plants were phenotyped for grain yield, assuming 10 epistatic QTLs and 90 minor genes. Adopting basic procedures of r/qtl package, we maximized the power of detection for QTLs (56-74%, on average) but associated with a very high FPR (65%) and a low detection power for the epistatic pairs (7%). Increasing the average detection power for epistatic pairs (14%) highly increased the related FPR. Adopting a procedure to find the best balance between power and FPR, there was a significant decrease in the power of QTL detection (17-31%, on average), associated with a low average detection power for epistatic pairs (8%) and an average FPR of 31% for QTLs and 16% for epistatic pairs. The main reasons for these negative results are a simplified specification of the coefficients of epistatic effects, as theoretically proved, and the effects of minor genes since 2/3 of the FPR for QTLs were due to them. We hope that this study, including the partial derivation of the coefficients of epistatic effects, motivates investigations on how to increase the power of detection for epistatic pairs, effectively controlling the FPR.

摘要

大多数关于上位性 QTL 作图的理论研究表明,该方法具有强大的功能,能够有效地控制假阳性率(FPR),并精确地定位 QTL。本基于模拟的研究旨在表明,定位上位性 QTL 并非几乎完美的过程。我们模拟了 50 个样本,每个样本有 400 个 F1 植物/重组自交系,在 100cM 的 10 条染色体上共 975 个 SNP 进行了基因型分析。对这些植物进行了粒重表型分析,假设存在 10 个上位性 QTL 和 90 个微效基因。采用 r/qtl 包的基本程序,我们最大限度地提高了 QTL 的检测能力(平均 56-74%),但同时 FPR 非常高(65%),对上位性对的检测能力也较低(7%)。提高上位性对的平均检测能力(14%)会极大地增加相关的 FPR。采用一种在能力和 FPR 之间找到最佳平衡的程序,QTL 检测能力显著下降(平均 17-31%),同时,上位性对的平均检测能力较低(8%),QTL 的平均 FPR 为 31%,上位性对的平均 FPR 为 16%。这些负面结果的主要原因是,如理论证明的那样,对上位性效应系数的简化说明以及微效基因的影响,因为 2/3 的 QTL 的 FPR 归因于它们。我们希望本研究,包括对上位性效应系数的部分推导,能够激发对如何提高上位性对检测能力、有效控制 FPR 的研究。

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