Mingyue Huo, Shanwen Wang, Fan Zhang, Min Li, Ming Yin, Yuxin Lei, Yanfang Wang, Yanjun Chen, Dapu Liu, Xiuqin Zhao, Binying Fu, Fengyi Hu, Jianlong Xu, Zhikang Li, Wensheng Wang

Molecular Plant; 2026; IF: 24.1

DOI:10.1016/j.molp.2026.01.005

Abstract

Great advances have been achieved from the global efforts in rice functional genomics research with thousands of rice genes cloned and characterized, but few of them have been utilized in rice improvement, largely because of the missing link between gene functionalities and their quantitative/population genetic parameters on complex traits. To overcome the challenge, we cloned three related small-effect QTL genes, qPHDF11.2, qPHDF12 and qPHDF10, controlling rice drought tolerance (DT) using an integrated strategy involving QTL identification by GWAS, identification and functional validation/characterization of the QTL genes using molecular, -omic and AlphaFold3 prediction approaches. Strong evidence demonstrated that OsGH18, OsMYB2 and OsCAD3 were three functionally related genes for qPHDF11.2, qPHDF12 and qPHDF10 with OsMYB2 being a drought-induced TF gene regulating OsGH18 and OsCAD3 that act directly in the lignin biosynthesis pathway in rice. Haplotype analyses revealed two and five alleles in the OsMYB2 and OsGH18 promoters plus four alleles in the OsCAD3 CDS region. Comprehensive genetic analyses revealed strong epistatic interactions among alleles at the three loci, leading us to a generalized model, demonstrating how different allelic combinations at OsMYB2, OsGH18 and OsCAD3 functioned as a single module for enhanced lignin biosynthesis/accumulation in cell walls and improved DT traits in rice primarily through specific tri-genic epistatic interactions. This epistatic genetic model fits very well with five DT traits measured at the seedling, vegetative and reproductive stages and provides superior powers (~6-35%) in predicting the field performances of diverse rice accessions of three populations for the DT traits and identifying tri-genic genotypes showing extreme DT phenotypes as potential donors for improving DT in rice. We reached a conclusion that once the functional relationships between or among genes acting in a complex network are determined experimentally, their epistatic relationships among multiple alleles at these genes can be computationally resolved using quantitative genetics models. This strategy will facilitate novel breeding strategies for improving complex traits based on fast-accumulating gene function data and evolving AI technologies.