Forecasting rice latitude adaptation through a daylength-sensing-based environment adaptation simulator

Global climate change necessitates crop varieties with good environmental adaptability. As a proxy for climate adaptation, crop breeders could select for adaptability to different latitudes, but the lengthy procedures for that slow development. Here, we combined molecular technologies with a streamlined in-house screening method to facilitate rapid selection for latitude adaptation. We established the daylength-sensing-based environment adaptation simulator (DEAS) to assess rice latitude adaptation status via the transcriptional dynamics of florigen genes at different latitudes. The DEAS predicted the florigen expression profiles in rice varieties with high accuracy. Furthermore, the DEAS showed potential for application in different crops. Incorporating the DEAS into conventional breeding programmes would help to develop cultivars for climate adaptation. Breeding crop cultivars with better environmental adaptability could support crop yield stability to mitigate the effects of climate change. Combining transcriptional dynamics of florigen genes and statistical models, the daylength-sensing-based environment adaptation simulator can forecast the latitude adaptability of rice cultivars and has application potential in other crops.

Automated summary

Global climate change requires crop varieties with good environmental adaptability. By combining molecular technologies and streamlined screening methods, breeders can select for adaptability to different latitudes efficiently. The daylength-sensing-based environment adaptation simulator (DEAS) accurately assesses rice latitude adaptation and shows potential for application in other crops. Forecasting the adaptability of crop cultivars to different latitudes using DEAS could aid in developing cultivars for climate adaptation and supporting crop yield stability.