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

Abstract

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.