Highly Polygenic Control of Photosynthetic Responses to Nighttime Temperature Studied by Genomic Prediction

Rising nighttime temperature (T_night) can reduce crop yields while low T_night may restrict plant growth and development. Despite quantifiable effects of T_night, genetic basis underlying plant responses to T_night remains unclear. We investigated natural variation in long-term response of effective photosynthetic efficiency (F_q'/F_m') to T_night among Arabidopsis accessions. Genome-wide association study (GWAS) was conducted for F_q'/F_m' of the plants grown under 15°C or 20°C T_night. GWAS revealed highly polygenic architecture of F_q'/F_m', with associated single nucleotide polymorphisms (SNPs) varying across T_night conditions and measurement days. Notably, 15°C T_night stabilised the contributions of a subset of SNPs, whereas 20°C T_night enhanced day-to-day variations in SNP-trait associations. We then incorporated the associated SNPs in genomic prediction (GP) models to assess the improvement of prediction accuracy. The GWAS-derived SNPs significantly improved the prediction ability of GP models, indicating collective influence of numerous small-effect SNPs. Finally, the model predictions were experimentally validated in an independent, genetically diverse population, which confirmed the correct identification of low-F_q'/F_m' accessions in 15°C T_night. These results uncover the genetic underpinnings of long-term F_q'/F_m' response to cool vs warm nights and establish a framework for leveraging GWAS and GP to explore complex traits, such as photosynthesis, toward breeding climate-resilient crops.