Genomic and environmental determinants and their interplay underlying phenotypic plasticity

Area of Science:

• Genetics
• Plant Biology
• Environmental Science

Background:

• Phenotypic variation arises from complex interactions between genomes and environments.
• Flowering time is a crucial trait influenced by gene-environment interplay, but its plasticity under natural conditions is hard to dissect.
• Identifying specific genetic and environmental factors driving phenotypic plasticity remains a challenge.

Purpose of the Study:

• To reveal the underlying genetic architecture of flowering time plasticity using integrated genomic and environmental analyses.
• To identify specific genes and their interactions contributing to phenotypic variation under natural conditions.
• To establish a genome-wide framework for predicting plant performance by quantitatively linking environmental factors and genomic responses.

Main Methods:

• Analysis of a genetic population with dynamic flowering time changes across diverse natural environments.
• Quantification of environmental gradients using photothermal time (photoperiod and temperature).
• Integrated analysis of genomic responses, including gene-gene interactions, and performance data.

Main Results:

• The effect continuum of key flowering time genes (Ma, Ma, FT, ELF3) varied in magnitude and direction along the environmental gradient.
• Gene-gene interactions were identified as significant contributors to observed phenotypic plasticity.
• A genome-wide performance prediction framework was successfully established using genotype-specific reaction norms and marker-effect continua.

Conclusions:

• Integrated genomic and environmental analyses are powerful for dissecting the genetic architecture of phenotypic plasticity.
• Photothermal time serves as a quantitative index to connect environmental conditions with genetic responses.
• The developed genome-wide prediction framework enables accurate in-season and on-target performance predictions, advancing crop breeding and adaptation strategies.