Genetic basis and adaptive implications of temperature-dependent and temperature-independent effects of drought on chickpea reproductive phenology

Water deficit often hastens flowering of pulses partially because droughted plants are hotter. Separating temperature-independent and temperature-dependent effects of drought is important to understand, model, and manipulate phenology. We define a new trait, drought effect on phenology (DEP), as the difference in flowering time between irrigated and rainfed crops, and use F-ST genome scanning to probe for genomic regions under selection for this trait in chickpea (Cicer arietinum). Owing to the negligible variation in daylength in our dataset, variation in phenology with sowing date was attributed to temperature and water; hence, genomic regions overlapping for early- and late-sown crops would associate with temperature-independent effects and non-overlapping genomic regions would associate with temperature-dependent effects. Thermal-time to flowering was shortened with increasing water stress, as quantified with carbon isotope composition. Genomic regions on chromosomes 4-8 were under selection for DEP. An overlapping region for early and late sowing on chromosome 8 revealed a temperature-independent effect with four candidate genes: BAM1, BAM2, HSL2, and ANT. The non-overlapping regions included six candidate genes: EMF1, EMF2, BRC1/TCP18, BZR1, NPGR1, and ERF1. Modelling showed that DEP reduces the likelihood of drought and heat stress at the expense of increased likelihood of cold stress. Accounting for DEP would improve genetic and phenotypic models of phenology. Predictive and genetic models that overlook drought effects on phenology can return biased predictions of adaptation to future climates. Here we study the genetic causes and model the adaptive consequences of hastened chickpea flowering under drought.

Automated summary

Water deficit accelerates the flowering of pulses due to increased heat in droughted plants. By studying chickpea, researchers have identified genomic regions and candidate genes associated with the effect of drought on phenology. This understanding can enhance genetic and phenotypic models, leading to more accurate predictions of adaptation to future climates.