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Published on: July 12, 2022
EPGD: a comprehensive web resource for integrating and displaying eukaryotic paralog/paralogon information
Guohui Ding1, Yan Sun, Hong Li
1Bioinformatics Center, Key Lab of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, P. R. China.
This study introduces a method to identify duplicated genes (paralogs) and their evolutionary patterns in eukaryotic genomes. A new database, Eukaryotic Paralog Group Database (EPGD), is now available for research on gene duplication events.
Area of Science:
- Genomics
- Evolutionary Biology
- Bioinformatics
Background:
- Gene duplication is a frequent evolutionary mechanism across all domains of life, particularly in eukaryotes.
- Duplicated genes (paralogs) serve as raw material for evolutionary processes like selection and genetic drift.
- Understanding gene duplication is crucial for deciphering genome evolution and organismal complexity.
Purpose of the Study:
- To develop a robust procedure for extracting paralogs from eukaryotic genomes.
- To calculate key evolutionary indices for paralog families.
- To construct a publicly accessible database for gene duplication research.
Main Methods:
- Extraction of duplicated genes (paralogs) from 26 eukaryotic genomes.
- Pre-calculation of evolutionary indices including evolutionary rate and synonymous distance.
- Identification of block or segmental duplications (paralogons).
Main Results:
- A sophisticated procedure for identifying and analyzing paralogs and paralogons was established.
- Several evolutionary indices were computed for paralog families.
- The Eukaryotic Paralog Group Database (EPGD) was created and made accessible online.
Conclusions:
- The developed methods and the EPGD provide valuable resources for studying gene duplication events.
- The database facilitates research for both experimentalists and bioinformaticians.
- This work enhances the understanding of evolutionary dynamics driven by gene duplication in eukaryotes.
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