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Rice (Oryza sativa L.) is a chilling-sensitive staple food crop, and thus, low temperature significantly affects rice growth and yield. Many studies have focused on the cold shock of rice although chilling acclimation is more likely to happen in the field. In this paper, a genome-wide association study (GWAS) was used to identify the genes that participated in cold stress and chilling accumulation. A total of 235 significantly associated single-nucleotide polymorphisms (SNPs) were identified. Among them, we detected 120 and 88 SNPs for the relative shoot fresh weight under cold stress and chilling acclimation, respectively. Furthermore, 11 and 12 quantitative trait loci (QTLs) were identified for cold stress and chilling acclimation, respectively, by integrating the co-localized SNPs. Interestingly, we identified 10 and 15 candidate genes in 11 and 12 QTLs involved in cold stress and chilling acclimation, respectively, and two new candidate genes (LOC_Os01g62410, LOC_Os12g24490) were obviously up-regulated under chilling acclimation. Furthermore, OsMYB3R-2 (LOC_Os01g62410) that encodes a R1R2R3 MYB gene was associated with cold tolerance, while a new C3HC4-type zinc finger protein-encoding gene LOC_Os12g24490 was found to function as a putative E3 ubiquitin-protein ligase in rice. Moreover, haplotype, distribution, and Wright’s fixation index (FST) of both genes showed that haplotype 3 of LOC_Os12g24490 is more stable in chilling acclimation, and the SNP (A > T) showed a difference in latitudinal distribution. FST analysis of SNPs in OsMYB3R-2 (LOC_Os01g62410) and LOC_Os12g24490 indicated that several SNPs were under selection in rice indica and japonica subspecies. This study provided new candidate genes in genetic improvement of chilling acclimation response in rice.
Pubmed ID: 36361995
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Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
View all literature mentionsAn efficient software tool to utilize update-to-date information to functionally annotate genetic variants detected from diverse genomes (including human genome hg18, hg19, as well as mouse, worm, fly, yeast and many others). Given a list of variants with chromosome, start position, end position, reference nucleotide and observed nucleotides, ANNOVAR can perform: 1. gene-based annotation. 2. region-based annotation. 3. filter-based annotation. 4. other functionalities. (entry from Genetic Analysis Software)
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