PlaASDB

PlaASDB catalogs alternative splicing (AS) events in Arabidopsis thaliana and Oryza sativa under biotic and abiotic stresses to enable comparative analyses of stress-responsive splicing and associated gene expression changes.


Key Features:

  • Extensive Data Collection: Integration of 3,255 publicly available RNA-seq datasets from Arabidopsis thaliana and Oryza sativa covering diverse stress conditions.
  • Alternative Splicing Event Detection: Computational detection of AS events and identification of differentially spliced genes (DSGs) with correlation to gene expression data.
  • Comparative Analysis Capabilities: Cross-species comparison of AS patterns between Arabidopsis and rice under abiotic and biotic stress, revealing conservation of AS patterns relative to gene expression changes.
  • Independent Roles of AS and Gene Expression: Characterization of limited overlap between DSGs and differentially expressed genes (DEGs) under stress, supporting independent regulatory roles.

Scientific Applications:

  • Regulatory Mechanism Studies: Investigation of AS-mediated regulation of stress responses in plants at the transcriptomic level.
  • Comparative Transcriptomics: Large-scale comparison of splicing patterns and gene expression between Arabidopsis thaliana and Oryza sativa under biotic and abiotic stresses.
  • Crop Stress Research: Informing studies aimed at understanding and potentially improving stress resilience in crop species through AS analysis.

Methodology:

Collection of publicly available RNA-seq datasets followed by computational analyses to detect alternative splicing events, identify differentially spliced genes (DSGs), and assess differential gene expression (DEGs).

Topics

Details

Cost:
Free of charge
Tool Type:
web application
Operating Systems:
Mac, Linux, Windows
Added:
9/4/2023
Last Updated:
9/4/2023

Operations

Publications

Guo X, Wang T, Jiang L, Qi H, Zhang Z. PlaASDB: a comprehensive database of plant alternative splicing events in response to stress. BMC Plant Biology. 2023;23(1). doi:10.1186/s12870-023-04234-7. PMID:37106367. PMCID:PMC10134664.

PMID: 37106367
Funding: - National Natural Science Foundation of China: 31970645

Documentation

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