Dissecting genomic regions and candidate genes for root traits at the seedling stage under cold stress in rice

Root system architecture (RSA) is crucial for plant growth under abiotic stress including cold stress (CS) in rice and capturing RSA variation under CS is a key strategy for improving cold tolerance (CT). This study aims to identify the genomic regions associated with RSA traits under CS in 204 diverse rice germplasms. Two growth environments were used: growth chamber (E1; 10°C in 1–2 weeks, followed by 17°C during weeks 3–4) and controlled greenhouse (E2; 28–30°C night/day). A total of 2448 roots were harvested four weeks after planting, and four plant biomasses, along with eight RSA traits, were measured using WinRhizo Pro. Significant phenotypic variations were observed for study traits. 8,54,832 polymorphic SNPs were used for GWAS using the FarmCPU model within the ‘rMVP’ package and 143 QTNs were identified (87 in E1 and 56 in E2) associated with the studied traits. Among the identified QTNs, 49 novel QTNs were multi-trait (≥ two traits), which were further used for candidate genes identification, resulting in 74 putative genes within ± 100 kb genomic regions. Key candidate genes ( OsBRD1/OsDWARF , MHZ11 , and OsSNDP1 ) supporting the rice root adaptation under CS by coordinated brassinosteroid biosynthesis, ethylene signaling, and phospholipid-mediated root hair development, whereas OsPP2C27 , OsNIP1;2 , OsNAR2.1 , OsMYB305 , OsSWEET3a , and OsHMA7 genes play important roles in stress signaling, nutrient uptake, growth regulation, and root development. Overall, this study provides the foundation of novel insights for improving rice CT by RSA.