title: Impacts of QTL x environment interactions on genetic response to marker-assisted selection.
abstract: Genotype x environment (GE) interaction is a common characteristic for quantitative traits, and has been a subject of great concern for breeding programs. Simulation studies were conducted to investigate the effects of GE interaction on genetic response to marker-assisted selection (MAS). In our study we demonstrated that MAS is generally more efficient than phenotypic selection in the presence of GE interaction, and this trend is more pronounced for developing broadly adaptable varieties. The utilization of different QTL information dramatically influences MAS efficiency. When MAS is based on QTLs evaluated in a single environment, the causal QTL x environment (QE) interactions usually reduce general response across environments, and the reduction in the cumulative general response is a function of the proportion of QE interactions for the trait studied. However, MAS using QTL information evaluated in multiple environments not only yields higher general response, but the general response obtained is also reasonably robust to QE interactions. The total response achieved by MAS in a specific environment depends largely on the total heritability of traits and is slightly subject to relative changes between general heritability and GE interaction heritability. Two breeding strategies, breeding experiments conducted in one environment throughout and in two environments alternately, were also examined for the implementation of marker-based selection. It was thus concluded that plant breeders should be cautious to utilize QTL information from only one environment and execute breeding studies in another.
authors.affiliation: Institute of Bioinformatics, Zhejiang University, Hangzhou 310029, China.
authors.forename: Peng-Yuan
authors.initials: PY
authors.lastname: Liu
authors.forename: Jun
authors.initials: J
authors.lastname: Zhu
authors.forename: Lu
authors.initials: L
authors.lastname: Yan
mesh_terms: D001947:Breeding; D002874:Chromosome Mapping; D004777:Environment; D005819:Genetic Markers; D005838:Genotype; D008957:Models, Genetic; D009010:Monte Carlo Method; D020412:Multifactorial Inheritance; D063245:Plant Development; D010944:Plants / Q000235:genetics*; D040641:Quantitative Trait Loci; D012641:Selection, Genetic
chemical_list: D005819:Genetic Markers