Observed phenotypic variation in living organisms is shaped by genomes, environment, and their interactions. Flowering time under natural conditions can showcase the diverse outcome of the gene-environment interplay. However, identifying hidden patterns and specific factors underlying phenotypic plasticity under natural field conditions remains challenging. With a genetic population showing dynamic changes in flowering time, here we show that the integrated analyses of genomic responses to diverse environments is powerful to reveal the underlying genetic architecture. Specifically, the effect continuum of individual genes (Ma1 , Ma6 , FT, and ELF3) was found to vary in size and in direction along an environmental gradient that was quantified by photothermal time, a combination of two environmental factors (photoperiod and temperature). Gene-gene interaction was also contributing to the observed phenotypic plasticity. With the identified environmental index to quantitatively connect environments, a systematic genome-wide performance prediction framework was established through either genotype-specific reaction-norm parameters or genome-wide marker-effect continua. These parallel genome-wide approaches were demonstrated for in-season and on-target performance prediction by simultaneously exploiting genomics, environment profiling, and performance information. Improved understanding of mechanisms for phenotypic plasticity enables a concerted exploration that turns challenge into opportunity.
Keywords: flowering time; genomic prediction; genomics; genotype-by-environment interaction; phenotypic plasticity.
Copyright © 2018 the Author(s). Published by PNAS.