title: Statistical method for mapping QTLs for complex traits based on two backcross populations.
abstract: Most important agronomic and quality traits of crops are quantitative in nature. The genetic variations in such traits are usually controlled by sets of genes called quantitative trait loci (QTLs), and the interactions between QTLs and the environment. It is crucial to understand the genetic architecture of complex traits to design efficient strategies for plant breeding. In the present study, a new experimental design and the corresponding statistical method are presented for QTL mapping. The proposed mapping population is composed of double backcross populations derived from backcrossing both homozygous parents to DH (double haploid) or RI (recombinant inbreeding) lines separately. Such 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 population. In 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 estimations. The results showed that the proposed method could estimate the positions and the genetic effects of QTLs with high efficiency.
authors.affiliation: Agronomy Department, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.
authors.forename: Zhu
authors.initials: Z
authors.lastname: Zhihong
authors.affiliation: Department of Mathematics, Statistics and Computer Science, NWFP Agricultural University Peshawar, Peshawar 25130, Pakistan.
authors.forename: Hayart
authors.initials: H
authors.lastname: Yousaf
authors.affiliation: Agronomy Department, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Jian
authors.affiliation: China National Rice Research Institute, National Center for Rice Improvement, State Key Laboratory of Rice Biology, Hangzhou 310006, China.
authors.forename: Cao
authors.initials: C
authors.lastname: Liyong
authors.affiliation: Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA.
authors.forename: Lou
authors.initials: L
authors.lastname: Xiangyang
authors.affiliation: Agronomy Department, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou 310058, China.
authors.forename: Xu
authors.initials: X
authors.lastname: Haiming
keywords: QTL mapping; QTL-by-environment interaction; double backcross populations; epistasis; mixed linear model