Genome-Wide Identification and Expression Analysis of OsbZIP09 Target Genes in Rice Reveal Its Mechanism of Controlling Seed Germination.
Cheng-Chao ZhuChu-Xin WangChen-Ya LuJin-Dong WangYu ZhouMin XiongChang-Quan ZhangQiao Quan LiuQian-Feng LiPublished in: International journal of molecular sciences (2021)
Seed dormancy and germination are key events in plant development and are critical for crop production, and defects in seed germination or the inappropriate release of seed dormancy cause substantial losses in crop yields. Rice is the staple food for more than half of the world's population, and preharvest sprouting (PHS) is one of the most severe problems in rice production, due to a low level of seed dormancy, especially under warm and damp conditions. Therefore, PHS leads to yield loss and a decrease in rice quality and vitality. We reveal that mutation of OsbZIP09 inhibited rice PHS. Analysis of the expression of OsbZIP09 and its encoded protein sequence and structure indicated that OsbZIP09 is a typical bZIP transcription factor that contains conserved bZIP domains, and its expression is induced by ABA. Moreover, RNA sequencing (RNA-seq) and DNA affinity purification sequencing (DAP-seq) analyses were performed and 52 key direct targets of OsbZIP09 were identified, including OsLOX2 and Late Embryogenesis Abundant (LEA) family genes, which are involved in controlling seed germination. Most of these key targets showed consistent changes in expression in response to abscisic acid (ABA) treatment and OsbZIP09 mutation. The data characterize a number of key target genes that are directly regulated by OsbZIP09 and contribute to revealing the molecular mechanism that underlies how OsbZIP09 controls rice seed germination.
Keyphrases
- transcription factor
- genome wide identification
- single cell
- rna seq
- genome wide
- poor prognosis
- dna binding
- plant growth
- climate change
- binding protein
- long non coding rna
- gene expression
- dna methylation
- arabidopsis thaliana
- risk assessment
- early onset
- cell free
- mass spectrometry
- small molecule
- circulating tumor
- big data
- quality improvement
- replacement therapy
- bioinformatics analysis
- deep learning