Ben J Hayes | PubMed Health

PubMed2026

Genetic legacy effects in a mungbean-wheat rotation reveal potential to breed for system-level yield gains.

Legume crops provide protein-rich food, serve as critical disease breaks in cereal rotations, and contribute to soil fertility through symbiotic nitrogen fixation. However, crop improvement programs typically focus on within-crop performance rather than system-level benefits. We hypothesize that legacy effects (the influence of one crop's genotype on subsequent crop performance) are under genetic control and could be targeted in breeding programs. To test this, we evaluated how 309 genetically diverse mungbean genotypes influenced subsequent wheat performance. The mungbean panel was grown, followed by a single wheat cultivar sown in the same plots. Remarkably, wheat yield varied by nearly 1 t ha-1 (2.52-3.49 t ha-1), depending solely on the preceding mungbean genotype. Legacy effects showed moderate heritability (H2: 0.43-0.65), suggesting untapped genetic potential for breeding. However, these estimates were derived from a single site and season and require validation across environments. Analyses of mungbean traits, soil properties, and volatile organic compounds identified root architecture, symbiotic nitrogen fixation, and the soil microbiome as potential contributors to legacy effects, although these mechanisms remain to be tested directly. Haplotype mapping identified genomic regions in mungbean associated with wheat yield and, to a lesser extent, grain protein, revealing trade-offs between within-crop performance and legacy effects. Genetic simulations based on empirically derived marker effects compared genomic selection strategies targeting mungbean yield, wheat yield, or both simultaneously. A selection strategy placing equal weight on mungbean yield and subsequent wheat yield (50:50 weighting) achieved simultaneous gains in both crops (19.5% and 7.6%), highlighting the potential to breed for system-level productivity with reduced input requirements.

crop rotations↗

PubMed2025

Haplotype stacking to improve stability of stripe rust resistance in wheat.

Genotype-by-environment interaction analysis and haplotype-level characterisation provide novel insights into the stability of stripe rust resistance. Breeding selection strategies are proposed to achieve rapid and stable genetic gains across environments. This study investigated stripe/yellow rust (YR) responses in the Vavilov wheat diversity panel evaluated across 11 field experiments conducted in Australia and Ethiopia during 2014-2021. Genotype-by-environment interaction (GEI) was analysed using a factor analytic (FA) model. Genotype-level selection was performed with overall performance (OP) and root-mean-square deviation (RMSD), which reflected average performance and stability of YR resistance across environments, respectively. Genomic estimated breeding values (GEBV) for these traits were calculated and compared with those from a multi-trait GBLUP model with average performance represented by the mean GEBV across environments and stability by the standard deviation of GEBV across environments. The FA-based and multi-trait GBLUP GEBV had high correlations. Haplotypes with large effects on OP and RMSD were identified using the local GEBV method. Favourable haplotypes were then used for stacking in breeding simulations, using the Vavilov collection as a base. Compared to truncation selection, optimal haplotype selection (OHS) using an artificial intelligence (AI)-based algorithm achieved longer-term genetic gains for both OP and RMSD (after many generations) by initially selecting founder parents that maximised favourable haplotypes. Simulations using YR responses from diverse environments that mimicked fluctuating environmental conditions across seasons were conducted to evaluate strategies for selection of YR resistance that is stable across years. Strategies which gave most weight to OP, but some weight to RMSD were optimal in these conditions, and substantially reduced variation of performance across years. This study provides useful information for breeding cultivars with both high YR resistance and high stability of resistance across environments.

Triticum↗