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Genetic legacy effects in a mungbean-wheat rotation reveal potential to breed for system-level yield gains
Shanice Van Haeften1, Stephanie M Brunner1, Eric Dinglasan1
1Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, Australia.
Abstract:
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.
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