title: Dissecting genetic architecture underlying seed traits in multiple environments.
abstract: The seeds of flowering plants develop from double fertilization and play a vital role in reproduction and supplying human and animal food. The genetic variation of seed traits is influenced by multiple genetic systems, e.g., maternal, embryo, and/or endosperm genomes. Understanding the genetic architecture of seed traits is a major challenge because of this complex mechanism of multiple genetic systems, especially the epistasis within or between different genomes and their interactions with the environment. In this study, a statistical model was proposed for mapping QTL with epistasis and QTL-by-environment (QE) interactions underlying endosperm and embryo traits. Our model integrates the maternal and the offspring genomes into one mapping framework and can accurately analyze maternal additive and dominant effects, endosperm/embryo additive and dominant effects, and epistatic effects of two loci in the same or two different genomes, as well as interaction effects of each genetic component of QTL with environment. Intensive simulations under different sampling strategies, heritabilities, and model parameters were performed to investigate the statistical properties of the model. A set of real cottonseed data was analyzed to demonstrate our methods. A software package, QTLNetwork-Seed-1.0.exe, was developed for QTL analysis of seed traits.
authors.affiliation: Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, People's Republic of China.
authors.forename: Ting
authors.initials: T
authors.lastname: Qi
authors.affiliation: Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, People's Republic of China.
authors.forename: Yujie
authors.initials: Y
authors.lastname: Cao
authors.affiliation: State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou, 311402, People's Republic of China.
authors.forename: Liyong
authors.initials: L
authors.lastname: Cao
authors.affiliation: Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing, 100081, People's Republic of China.
authors.forename: Yongming
authors.initials: Y
authors.lastname: Gao
authors.affiliation: Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, People's Republic of China.
authors.forename: Shuijin
authors.initials: S
authors.lastname: Zhu
authors.affiliation: Department of Biostatistics, University of Alabama, Birmingham, Alabama 35294.
authors.forename: Xiangyang
authors.initials: X
authors.lastname: Lou
authors.affiliation: Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, 310058, People's Republic of China hmxu@zju.edu.cn.
authors.forename: Haiming
authors.initials: H
authors.lastname: Xu
mesh_terms: D004777:Environment; D059647:Gene-Environment Interaction; D018745:Genome, Plant; D003368:Gossypium / Q000235:genetics; D008957:Models, Genetic; D040641:Quantitative Trait Loci; D019655:Quantitative Trait, Heritable; D012639:Seeds / Q000235:genetics*; D012984:Software
keywords: crop seed traits; epistasis; gene-by-environment interaction; genetic effect; mixed linear model