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Identification of responsive genes to multiple abiotic stresses in rice (Oryza sativa): a meta-analysis of transcriptomics data
Sunday, 2024/06/16 | 07:13:20

Mahnaz AzadMasoud TohidfarRahele Ghanbari Moheb SerajMohammad MehralianKeyvan Esmaeilzadeh-Salestani

Sci Rep.; 2024 Apr 1;4(1):5463. doi: 10.1038/s41598-024-54623-7.

Abstract

Abiotic stresses limit the quantity and quality of rice grain production, which is considered a strategic crop in many countries. In this study, a meta-analysis of different microarray data at seedling stage was performed to investigate the effects of multiple abiotic stresses (drought, salinity, cold situation, high temperature, alkali condition, iron, aluminum, and heavy metal toxicity, nitrogen, phosphorus, and potassium deficiency) on rice. Comparative analysis between multiple abiotic stress groups and their control groups indicated 561 differentially expressed genes (DEGs), among which 422 and 139 genes were up-regulated and down-regulated, respectively. Gene Ontology analysis showed that the process of responding to stresses and stimuli was significantly enriched. In addition, pathways such as metabolic process and biosynthesis of secondary metabolites were identified by KEGG pathway analysis. Weighted correlation network analysis (WGCNA) uncovered 17 distinct co-expression modules. Six modules were significantly associated with genes involved in response to abiotic stresses. Finally, to validate the results of the meta-analysis, five genes, including TIFY9 (JAZ5), RAB16B, ADF3, Os01g0124650, and Os05g0142900 selected for qRT-PCR analysis. Expression patterns of selected genes confirmed the results of the meta-analysis. The outcome of this study could help introduce candidate genes that may be beneficial for use in genetic engineering programs to produce more tolerant crops or as markers for selection.

 

See https://pubmed.ncbi.nlm.nih.gov/38561340/

 

Figure 2; The top enriched GO terms of DEGs (p-value < 0.05) in the categories of BP: Biological Process, MF: Molecular Function, and CC: Cellular Component.

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