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Mapping of epistatic quantitative trait loci in four-way crosses
Authors:Xiao-Hong He  Hongde Qin  Zhongli Hu  Tianzhen Zhang  Yuan-Ming Zhang
Institution:(1) Section on Statistical Genomics, State Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, 210095, People’s Republic of China;(2) Chinese National Center for Soybean Improvement, Nanjing Agricultural University, Nanjing, 210095, People’s Republic of China;(3) Cotton Research Institute, State Key Laboratory of Crop Genetics and Germplasm Enhancement, College of Agriculture, Nanjing Agricultural University, Nanjing, 210095, People’s Republic of China;(4) Key Lab of the Ministry of Education for Plant Developmental Biology, College of Life Science, Wuhan University, Wuhan, 430072, People’s Republic of China;
Abstract:Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.
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