GWAS and WGCNA uncover hub genes controlling salt tolerance in maize (Zea mays L.) seedlings.
Langlang MaMinyan ZhangJie ChenChunyan QingShijiang HeChaoying ZouGuangsheng YuanCong YangHua PengGuangtang PanThomas LübberstedtYaou ShenPublished in: TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik (2021)
Two hub genes GRMZM2G075104 and GRMZM2G333183 involved in salt tolerance were identified by GWAS and WGCNA. Furthermore, they were verified to affect salt tolerance by candidate gene association analysis. Salt stress influences maize growth and development. To decode the genetic basis and hub genes controlling salt tolerance is a meaningful exploration for cultivating salt-tolerant maize varieties. Herein, we used an association panel consisting of 305 lines to identify the genetic loci responsible for Na+- and K+-related traits in maize seedlings. Under the salt stress, seven significant single nucleotide polymorphisms were identified using a genome-wide association study, and 120 genes were obtained by scanning the linkage disequilibrium regions of these loci. According to the transcriptome data of the above 120 genes under salinity treatment, we conducted a weighted gene co-expression network analysis. Combined the gene annotations, two SNaC/SKC (shoot Na+ content/shoot K+ content)-associated genes GRMZM2G075104 and GRMZM2G333183 were finally identified as the hub genes involved in salt tolerance. Subsequently, these two genes were verified to affect salt tolerance of maize seedlings by candidate gene association analysis. Haplotypes TTGTCCG-CT and CTT were determined as favorable/salt-tolerance haplotypes for GRMZM2G075104 and GRMZM2G333183, respectively. These findings provide novel insights into genetic architectures underlying maize salt tolerance and contribute to the cultivation of salt-tolerant varieties in maize.
Keyphrases
- genome wide
- dna methylation
- genome wide identification
- network analysis
- bioinformatics analysis
- copy number
- genome wide association study
- genome wide analysis
- computed tomography
- high resolution
- gene expression
- positron emission tomography
- machine learning
- arabidopsis thaliana
- deep learning
- binding protein
- contrast enhanced
- smoking cessation
- single cell
- genome wide association