# Genetic control of plasticity of oil yield for combined abiotic stresses using a joint approach of crop modeling and genome-wide association

## TL;DR

This study integrates crop modeling and genome-wide association to uncover genetic factors controlling oil yield plasticity in sunflower under multiple abiotic stresses, aiding climate resilience breeding.

## Contribution

It introduces a joint crop modeling and GWAS approach to identify genetic loci associated with yield plasticity across multiple stresses in realistic conditions.

## Key findings

- Identified nine QTL linked to cold stress plasticity in sunflower.
- Stress indicators better explained yield variation than climatic descriptors.
- Genes near QTL are involved in cold stress response mechanisms.

## Abstract

Understanding the genetic basis of phenotypic plasticity is crucial for predicting and managing climate change effects on wild plants and crops. Here, we combined crop modeling and quantitative genetics to study the genetic control of oil yield plasticity for multiple abiotic stresses in sunflower. First we developed stress indicators to characterize 14 environments for three abiotic stresses (cold, drought and nitrogen) using the SUNFLO crop model and phenotypic variations of three commercial varieties. The computed plant stress indicators better explain yield variation than descriptors at the climatic or crop levels. In those environments, we observed oil yield of 317 sunflower hybrids and regressed it with three selected stress indicators. The slopes of cold stress norm reaction were used as plasticity phenotypes in the following genome-wide association study. Among the 65,534 tested SNP, we identified nine QTL controlling oil yield plasticity to cold stress. Associated SNP are localized in genes previously shown to be involved in cold stress responses: oligopeptide transporters, LTP, cystatin, alternative oxidase, or root development. This novel approach opens new perspectives to identify genomic regions involved in genotype-by-environment interaction of a complex traits to multiple stresses in realistic natural or agronomical conditions.