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Statistical method for mapping QTLs for complex traits based on two backcross populations

Chinese Science Bulletin 2012年第21期57卷 2645-2654页

作者： ZHU ZhiHong hayart yousaf YANG Jian CAO LiYong LOU XiangYang XU HaiMing Agronomy Department College of Agriculture and BioteehnologyZhejiang UniversityHangzhou 310058China Department of Mathematics Statistics and Computer ScienceNWFP Agricultural University PeshawarPeshawar 25130Pakistan China National Rice Research Institute National Center for Rice ImprovementState Key Laboratory of Rice BiologyHangzhou 310006China Department of Biostatistics School of Public HealthUniversity of Alabama at BirminghamBirminghamAlabama 35294USA

Most important agronomic and quality traits of crops are quantitative in *** genetic variations in such traits are usually controlled by sets of genes called quantitative trait loci (QTLs),and the interactions between QTLs and the *** is crucial to understand the genetic architecture of complex traits to design efficient strategies for plant *** the present study,a new experimental design and the corresponding statistical method are presented for QTL *** proposed mapping population is composed of double backcross populations derived from backcrossing both homozygous parents to DH (double haploid) or RI (recombinant inbreeding) lines *** an immortal mapping population allows for across-environment replications,and can be used to estimate dominance effects,epistatic effects,and QTL-environment interactions,remedying the drawbacks of a single backcross *** this method,the mixed linear model approach is used to estimate the positions of QTLs and their various effects including the QTL additive,dominance,and epistatic effects,and QTL-environment interaction effects (QE).Monte Carlo simulations were conducted to investigate the performance of the proposed method and to assess the accuracy and efficiency of its *** results showed that the proposed method could estimate the positions and the genetic effects of QTLs with high efficiency.

关键词：回交群体品质性状基因定位统计方法数量性状位点上位性效应基础相互作用

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