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PASPA: a web server for mRNA poly(A) site predictions in plants and algae
Guoli Ji1, Lei Li2, Qingshun Q Li3
1Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China Department of Automation, Innovation Center for Cell Biology and Key Laboratory of the Ministry of Education on Costal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Xiamen, Fujian, China, Department of Biology, Miami University, Oxford, OH, USA and Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou, Fujian, China.
Predicting poly(A) sites in plants and algae is crucial for gene annotation. The PASPA web server offers accurate polyadenylation site prediction for ten species, aiding research in gene regulation.
Area of Science:
- Molecular Biology
- Bioinformatics
- Genomics
Background:
- Polyadenylation is a vital eukaryotic gene expression step.
- Accurate poly(A) site prediction is essential for gene annotation and understanding gene regulation.
- Predicting poly(A) sites in plants and algae remains challenging due to limited poly(A) signal knowledge.
Purpose of the Study:
- To develop and present PASPA, a web server for poly(A) site prediction in plants and algae.
- To facilitate poly(A) site prediction, visualization, and data mining.
Main Methods:
- PASPA integrates multiple in-house tools for poly(A) site prediction.
- The server supports prediction for ten plant and algae species.
- Performance metrics include sensitivity and specificity.
Main Results:
- PASPA demonstrates high predictive performance with sensitivity and specificity ranging from 0.80 to 0.95.
- The server enables prediction for seven species lacking prior poly(A) signal characterization.
- Integrated tools enhance poly(A) site analysis capabilities.
Conclusions:
- PASPA provides a valuable resource for poly(A) site prediction in plants and algae.
- The tool aids in gene annotation and regulatory mechanism studies.
- PASPA improves the efficiency and accuracy of polyadenylation site analysis.
