Combined GWAS and Transcriptome Analyses Provide New Insights Into the Response Mechanisms of Sunflower Against Drought Stress

Abstract

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 genome-wide association studies (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. Subsequent analysis of linkage disequilibrium (LD) and population structure in the 226 accessions was carried out based on the 94,162 high-quality SNPs. The average 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 the 8 traits (p < 1.062 × 10−6). Next, a total of 118 candidate genes were found. To obtain more reliable candidate genes, RNA-seq analysis was subsequently performed. 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 the branched-chain amino acid catabolic process, while the down-regulated genes were mainly enriched in the 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 of 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. Our findings provide new insights into the response mechanisms of sunflowers against drought stress and contribute to further genetic breeding.

Analysis of QTL mapping for germination and seedling response to drought stress in sunflower (Helianthus annuus L.)

“…5 and 17 under two water conditions, respectively, located on the same chromosome as this study. Interestingly, Wu et al (2022a) found that the SNP locus S5_195713371 was located on chromosome 5 and closely associated with the relative water content of leaves, and this was coincidentally located in the qRLWC-5-1 region in our study. However, it was not at the same loci as this study, which may have been caused by the different densities of the mapping.…”

“…Drought stress was initiated when the seedlings grew to the stage of six leaves. The water stress was carried out according to the method of Wu et al (2022a) . The drought stress (DS) soil moisture content was set to 10 ± 2%, and 30 ± 2% in the control group (CK) ( Wu et al, 2022a ).…”

“…The water stress was carried out according to the method of Wu et al (2022a) . The drought stress (DS) soil moisture content was set to 10 ± 2%, and 30 ± 2% in the control group (CK) ( Wu et al, 2022a ). We measured the soil water content at 8:00 am every two days using a weight method ( Soni & Abdin, 2017 ).…”

“…However, the differences between different stresses still need to be further investigated ( Barnhart et al, 2022 ). Wu et al (2022a) identified 14 candidate genes through the integration of a genome-wide association study and RNA-sequencing.…”

Genome-wide association scan and transcriptome analysis reveal candidate genes for waterlogging tolerance in cultivated barley

“…A genome-wide association study (GWAS) is an effective approach to identify genomic regions associated with specific variants of complex traits, which could dissect more alleles compared with linkage analysis. Recently, GWAS has been widely used to detect important candidate genes associated with yield, quality, salt stress, and drought stress ( Reig-Valiente et al., 2018 ; Luo et al., 2021 ; Hao et al., 2022 ; Wu et al., 2022 ). In barley, many functional loci associated with agronomic traits ( Xu et al., 2018 ), salt stress tolerance ( Mwando et al., 2020 ), drought stress tolerance ( Tarawneh et al., 2020 ), grain quality ( Jia et al., 2021 ) and disease resistance ( Pan et al., 2022 ) have been identified by GWAS.…”