Zhitao Li1, Bo Wang,  Wei Luo, Yunyuan Xu, Jinjuan Wang, Zhihui Xue, Yuda Niu,  Zhukuan Cheng, Song Ge, Wei Zhang, Jingyu Zhang, Qizhai Li, Kang Chong

Science Advances; January 6 2023; Vol.9, Issue 1.

Abstract

Abnormal temperature caused by global climate change threatens the rice production. Defense signaling network for chilling has been uncovered in plants. However, less is known about repairing DNA damage produced from overwhelmed defense and its evolution during domestication. Here, we genetically identified a major QTL, COLD11, using the data-merging genome-wide association study based on an algorithm combining polarized data from two subspecies, indica and japonica, into one system. Rice loss-of-function mutations of COLD11 caused reduced chilling tolerance. Genome evolution analysis of representative rice germplasms suggested that numbers of GCG sequence repeats in the first exon of COLD11 were subjected to strong domestication selection during the northern expansion of rice planting. The repeat numbers affected the biochemical activity of DNA repair protein COLD11/RAD51A1 in renovating DNA damage under chilling stress. Our findings highlight a potential way to finely manipulate key genes in rice genome and effectively improve chilling tolerance through molecular designing.

See https://www.science.org/doi/10.1126/sciadv.abq5506

Fig. 1. Data-merging GWAS for rice chilling tolerance with separate analysis for indica and japonica as control. (A) Schematic diagram showing the merging of survival rate data for indica and japonica. Blue and red stars stand for random samples in japonica (Jap) and indica (Ind), respectively. The line connecting these two stars stands for interpoint distance, which is preserved before  and after data merging. (B) Manhattan plots of the Bayes factor result of data-merging GWAS for chilling tol-erance. Horizontal axis indicates chromosomes, and vertical axis indicates log10 (Bayes factor). Dashed line represents significance threshold (log10 BF = 6.77). Arrows indicate the positions of strong peaks (qCTS1-1, qCTS1-2, qCTS3-1, qCTS4-1, qCTS5-1, qCTS7-1, qCTS9-1, and qCTS11-1), which were confirmed by chilling tolerance analysis of chromosome segment substitution lines (CSSLs; CSSL1-1, CSSL1-2, CSSL3-1, CSSL5-1, CSSL7-1, CSSL11-1, CSSL11-2, and CSSL11-3) or contained reported chilling tolerance–related genes (OsDREB1B for qCTS9-1 and OsDREB1E for qCTS4-1). (C) Manhattan plots of the Bayes factor results of GWAS for chilling tolerance of indica (top) and japonica (bottom). Dashed line represents significance threshold (indica: log10 BF = 7.32 and japonica: log10 BF = 7.32). Arrow indicates the position of strong peak, qCTS11-1, which was confirmed by analysis of CSSL11-1, CSSL11-2, and CSSL11-3. (D) Statistical data for data-merging GWAS and GWAS performed separately for indica and japonica. MD, merged data; Ind, indica data; Jap, japonica data; No. loci, number of loci exceeding significance threshold; Reported, the number of loci with chilling tolerance–related genes reported previously; Identified CSSLs, the number of loci confirmed by CSSLs.