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Genetic interactions among flowering loci influence phenology, vigour, and yield in chickpea

Aug 2026 · Molecular breeding · Vol 46 · 0 citations · 61 references
Medicine

TL;DR

It is suggested that the primary breeding value of these loci lies in fine-tuning crop development to local stress patterns rather than delivering robust yield gains, and stacking early and late alleles may offer breeders a genetic tool to broaden adaptive flexibility.

Abstract

Flowering time and vegetative vigour are central adaptive traits in chickpea, shaping the balance between stress escape, biomass accumulation, and yield. Major phenology loci have been identified in this species, including ELF3a, CaLG3b and a cluster of FT homologues on chromosome 3 (CaLG3a), but their individual and interactive contributions to field adaptation remain unclear. Here, we developed near-isogenic lines (NILs) to dissect these loci under controlled conditions and across eight field environments in Southern and Western Australia. In a phytotron, NILs revealed strong photoperiod dependence: ELF3a suppressed flowering under short days, while early alleles at CaLG3b and the FT cluster promoted flowering under long days, with additive effects across loci. In the field, allelic substitutions consistently shifted phenology by a few days or nodes but rarely conferred direct yield benefits. Yield responses were variable and environment-dependent, with one NIL pair exhibiting a consistent penalty in environments with yields above 255 g m− 2. In contrast, canopy traits showed clearer divergence between NIL pairs, aligning with pleiotropic effects of the FT cluster. These results highlight the utility of NILs for attributing modest but adaptive phenological shifts to defined genomic regions, and suggest that the primary breeding value of these loci lies in fine-tuning crop development to local stress patterns rather than delivering robust yield gains. Stacking early and late alleles may offer breeders a genetic tool to broaden adaptive flexibility, while yield improvement will likely require integration with physiological traits related to resource capture, efficiency and higher reproductive allocation.

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