Medical College of Wisconsin
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Impacts of QTL x environment interactions on genetic response to marker-assisted selection. Yi Chuan Xue Bao 2006 Jan;33(1):63-71



Pubmed ID




Scopus ID

2-s2.0-31344451887   7 Citations


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.

Author List

Liu PY, Zhu J, Yan L


Pengyuan Liu PhD Adjunct Professor in the Physiology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Chromosome Mapping
Genetic Markers
Models, Genetic
Monte Carlo Method
Multifactorial Inheritance
Plant Development
Quantitative Trait Loci
Selection, Genetic
jenkins-FCD Prod-484 8aa07fc50b7f6d102f3dda2f4c7056ff84294d1d