Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress - Wu, Yang; Shi, Huimin; Yu, Haifeng; Ma, Yu; Hu, Haibo; Han, Zhigang; Zhang, Yonghu; Zhen, Zilong; Yi, Liuxi; Hou, Jianhua (Frontiers in Plant Science, 2022)
Sunflower is one of the most important oil crops in the world, and drought stress can severely limit its production and quality. To understand the underlying mechanism of drought tolerance, and identify candidate genes for drought tolerance breeding, we conducted a combined GWAS and RNA-seq analysis. A total of 226 sunflower inbred lines were collected from different regions of China and other countries. Eight phenotypic traits were evaluated under control and drought stress conditions. Genotyping was performed using a Specific-Locus Amplified Fragment Sequencing (SLAF-seq) approach. A total of 934.08 M paired-end reads were generated, with an average Q30 of 91.97%. Based on the 243,291 polymorphic SLAF tags, a total of 94,162 high-quality SNPs were identified. The average linkage disequilibrium (LD) decay across the genome was 20 kb. Admixture analysis indicated that the entire population most likely originated from 11 ancestors. GWAS was performed using three methods (MLM, FarmCPU, and BLINK) simultaneously. A total of 80 SNPs showed significant associations with (p<1.062 ×10-6) with the 8 traits. Next, a total of 118 candidate genes were found. To obtain a more accurate candidate gene set, an RNA-sequencing (RNA-seq) analysis was performed in the next year. An inbred line with the highest drought tolerance was selected according to phenotypic traits. RNA was extracted from leaves at 0, 7, and 14 days of drought treatment. A total of 18,922 differentially expressed genes were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed up-regulated genes were mainly enriched in branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in photosynthesis-related process. Six DEGs were randomly selected from all DEGs for validation, these genes showed similar patterns in RNA-seq and RT-qPCR analysis, with a correlation coefficient was 0.8167. Through the integration of the genome-wide association study and the RNA-sequencing, 14 candidate genes were identified. Four of them (LOC110885273, LOC110872899, LOC110891369, LOC110920644) were abscisic acid related protein kinases and transcription factors. These genes may play an important role in sunflower drought response and will be used for further study.