Integrative transcriptogenomic analyses reveal the regulatory network underlying rice eating and cooking quality and identify a role for alpha-globulin in modulating starch and sucrose metabolism

Abstract

Rice eating and cooking quality (ECQ) is significantly influenced by the physicochemical properties of rice starch. This study integrates whole-genome resequencing, transcriptomic data, and phenotypic analysis to identify the genetic factors that regulate transcript expression levels and contribute to phenotypic variation in rice ECQ traits. A TWAS (transcriptome-wide association study) identified 285 transcripts linked to 6 ECQ traits. Genome-wide mapping of these transcripts revealed 21 747 local eQTLs (expression quantitative trait loci) and 45 158 distal eQTLs. TWAS and eQTL analysis detected several known and novel genes, including starch synthesis-related genes, heat shock proteins, transcription factors, genes related to ATP accumulation, and UDP-glucosyltransferases, showcasing the complex genetic regulation of rice ECQ. WGCNA (weighted gene co-expression network analysis) uncovered key co-expression networks, including a module that links alpha-globulin1 (GLB1) to starch and sucrose metabolism. Genetic diversity analysis of the GLB1 gene across a Korean rice collection identified 26 haplotypes, with indica and aus forming 7 and 3 haplotypes, respectively, which showed significant phenotypic effects on ECQ traits. CRISPR-Cas9-created knockout lines validated these findings, demonstrating that loss of GLB1 function caused significant changes in seed storage proteins, reduced amylose content, altered starch granules, and modified pasting properties without affecting plant phenotypes. By integrating TWAS, eQTL mapping, haplotype analysis, gene expression networks, and CRISPR validation, this study establishes GLB1 as a regulator of ECQ, linking starch biosynthesis and protein accumulation pathways. This transcriptogenomic convergence approach provides novel insights into the genetic regulation of ECQ in rice, demonstrating its effectiveness for characterizing complex traits and enabling precision breeding. © 2025 The Authors