Modeling plant phenotypic plasticity and its underlying genetic architecture: a comparative study.

Abstract

Phenotypic plasticity can contribute to crop adaptation to challenging environments. Plasticity indices are potentially useful to identify the genetic basis of crop phenotypic plasticity. Numerous methods exist to measure phenotypic plasticity. However, their ability to capture QTL with environmental effects remains elusive. Here, we analyzed a published multi-trial maize phenotyping dataset that examined the water stress response of leaf area, shoot biomass and water use efficiency, calculating phenotypic plasticity for these traits using seven different plasticity indices. A comprehensive genetic analysis of phenotypic plasticity for these traits was further performed and the ability of these methods to detect genetic regions capturing variance due to genotype-by-environment (G x E) interaction was evaluated. Our results suggest that not all plasticity indices are amenable to identify genomic regions associated with phenotypic plasticity. We observed that plasticity indices based on calculation of a ratio between environments or the slope of the Finlay-Wilkinson model were particularly useful in uncovering the genetic architecture underlying phenotypic plasticity when studying responses to treatments within and across trials. Ultimately, a deeper understanding of phenotypic plasticity should provide opportunities for breeding plants better able to adapt to climate uncertainty.