A combinatorial strategy to identify various types of QTLs for quantitative traits using extreme phenotype individuals in an F-2 population

文献类型： 外文期刊

第一作者： Li, Pei

作者： Li, Pei;Li, Guo;Zhang, Ya-Wen;Zuo, Jian-Fang;Liu, Jin-Yang;Zhang, Yuan-Ming;Liu, Jin-Yang

作者机构：

关键词： F-2; bulked segregant analysis; dQTG-seq; extremely over-dominant gene; small-effect gene; rice

期刊名称：PLANT COMMUNICATIONS （ 影响因子：8.625； 五年影响因子：8.625 ）

ISSN： 2590-3462

年卷期： 2022 年 3 卷 3 期

页码：

收录情况： SCI

摘要： Theoretical and applied studies demonstrate the difficulty of detecting extremely over-dominant and small-effect genes for quantitative traits via bulked segregant analysis (BSA) in an F-2 population. To address this issue, we proposed an integrated strategy for mapping various types of quantitative trait loci (QTLs) for quantitative traits via a combination of BSA and whole-genome sequencing. In this strategy, the numbers of read counts of marker alleles in two extreme pools were used to predict the numbers of read counts of marker genotypes. These observed and predicted numbers were used to construct a new statistic, G(w), for detecting quantitative trait genes (QTGs), and the method was named dQTG-seq1. This method was significantly better than existing BSA methods. If the goal was to identify extremely over-dominant and small-effect genes, another reserved DNA/RNA sample from each extreme phenotype F-2 plant was sequenced, and the observed numbers of marker alleles and genotypes were used to calculate G(w) to detect QTGs; this method was named dQTG-seq2. In simulated and real rice dataset analyses, dQTG-seq2 could identify many more extremely over-dominant and small-effect genes than BSA and QTL mapping methods. dQTG-seq2 may be extended to other heterogeneous mapping populations. The significance threshold of G(w) in this study was determined by permutation experiments. In addition, a handbook for the R software dQTG.seq, which is available at https://cran.r-project.org/web/packages/dQTG.seq/index.html, has been provided in the supplemental materials for the users' convenience. This study provides a new strategy for identifying all types of QTLs for quantitative traits in an F-2 population.

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