Dissecting the genetic basis of yield stability in faba bean by multi-environment analysis

Abstract

Faba bean is a globally adapted legume protein crop with a high yield potential. Currently, yield variation across environments limits more widespread cultivation, and the underlying genetics remain poorly understood. Here, we identify major QTL for faba bean yield and yield stability. We genotype the ProFaba diversity panel with high resolution and carry out coordinated multi-year/location trials across Europe. Based on these data, we identify more than one hundred loci associated with mean performance and stability for 14 complex traits, including yield. Experimental validation supports the involvement of the candidate gene Vfaba.Hedin2.R2.1g002122 in plant architecture, with gene expression significantly associated with first pod position and plant height. Furthermore, we introduce a method for integrating environmental data in the analysis of trait stability based on a random regression mixed model, which enables prediction of performance in untested environments. Our study provides insights into the genetic architecture of yield, yield stability, and genotype-by-environment interaction in faba bean. The genomic resources, candidate loci, and weather-informed analytical framework provide practical tools for predicting performance across environments and accelerating breeding of resilient, high-yielding protein crops.