Systematic Analysis of Cold Stress Response and Diurnal Rhythm Using Transcriptome Data in Rice Reveals the Molecular Networks Related to Various Biological Processes.
Woo-Jong HongXu JiangHye Ryun AhnJuyoung ChoiSeong-Ryong KimKi-Hong JungPublished in: International journal of molecular sciences (2020)
Rice (Oryza sativa L.), a staple crop plant that is a major source of calories for approximately 50% of the human population, exhibits various physiological responses against temperature stress. These responses are known mechanisms of flexible adaptation through crosstalk with the intrinsic circadian clock. However, the molecular regulatory network underlining this crosstalk remains poorly understood. Therefore, we performed systematic transcriptome data analyses to identify the genes involved in both cold stress responses and diurnal rhythmic patterns. Here, we first identified cold-regulated genes and then identified diurnal rhythmic genes from those (119 cold-upregulated and 346 cold-downregulated genes). We defined cold-responsive diurnal rhythmic genes as CD genes. We further analyzed the functional features of these CD genes through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses and performed a literature search to identify functionally characterized CD genes. Subsequently, we found that light-harvesting complex proteins involved in photosynthesis strongly associate with the crosstalk. Furthermore, we constructed a protein-protein interaction network encompassing four hub genes and analyzed the roles of the Stay-Green (SGR) gene in regulating crosstalk with sgr mutants. We predict that these findings will provide new insights in understanding the environmental stress response of crop plants against climate change.
Keyphrases
- genome wide
- genome wide identification
- bioinformatics analysis
- climate change
- transcription factor
- genome wide analysis
- dna methylation
- copy number
- gene expression
- protein protein
- blood pressure
- endothelial cells
- electronic health record
- single cell
- big data
- risk assessment
- artificial intelligence
- heart rate
- induced pluripotent stem cells
- data analysis
- stress induced