Center for Computational Biology, Beijing Forestry University, Beijing, 100083, China.
The Nurturing Station for the State Key Laboratory of Subtropical Silviculture, Zhejiang Agricultural and Forestry University, Lin'an, Zhejiang, 311300, China.
New Phytol. 2014 Jan;201(1):357-365. doi: 10.1111/nph.12458. Epub 2013 Sep 13.
The phenotype of an individual is controlled not only by its genes, but also by the environment in which it grows. A growing body of evidence shows that the extent to which phenotypic changes are driven by the environment, known as phenotypic plasticity, is also under genetic control, but an overall picture of genetic variation for phenotypic plasticity remains elusive. Here, we develop a model for mapping quantitative trait loci (QTLs) that regulate environment-induced plastic response. This model enables geneticists to test whether there exist actual QTLs that determine phenotypic plasticity and, if there are, further test how plasticity QTLs control the costs of plastic response by dissecting the genetic correlation of phenotypic plasticity and trait value. The model was used to analyze real data for grain yield of winter wheat (Triticum aestivum), leading to the detection of pleiotropic QTLs and epistatic QTLs that affect phenotypic plasticity and its cost in this crop.
个体的表型不仅受其基因控制,还受其生长环境的影响。越来越多的证据表明,表型变化受环境驱动的程度,即表型可塑性,也受到遗传控制,但表型可塑性的遗传变异全貌仍然难以捉摸。在这里,我们开发了一种用于映射调节环境诱导的可塑性反应的数量性状基因座 (QTL) 的模型。该模型使遗传学家能够测试是否存在实际的 QTL 来决定表型可塑性,如果有,通过剖析表型可塑性和性状值的遗传相关性,进一步测试可塑性 QTL 如何控制可塑性反应的成本。该模型用于分析冬小麦(Triticum aestivum)的谷物产量的真实数据,导致检测到影响该作物表型可塑性及其成本的多效性 QTL 和上位性 QTL。