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Published on: May 27, 2021
Improved orthologous databases to ease protozoan targets inference.
Nelson Kotowski1, Rodrigo Jardim2, Alberto M R Dávila3
1Computational and Systems Biology Laboratory, Oswaldo Cruz Institute, FIOCRUZ, Avenida Brasil, 4365, 21040-360, Rio de Janeiro, RJ, Brazil. nelson.peixoto@fiocruz.br.
This study introduces an improved method for building orthologous databases using comparative genomics. The enhanced databases aid in identifying potential protozoan targets through homology inference.
Area of Science:
- Comparative genomics
- Bioinformatics
- Parasitology
Background:
- Homology inference is crucial for understanding evolutionary relationships between organisms.
- Comparative genomics pipelines, utilizing various bioinformatics tools, are essential for such analyses.
- Identifying protozoan targets benefits significantly from advanced comparative genomics approaches.
Purpose of the Study:
- To propose a novel methodology for constructing improved orthologous databases.
- To leverage these databases for enhanced protozoan target identification.
- To refine comparative genomics pipelines for broader biological applications.
Main Methods:
- Utilized the OrthoSearch comparative genomics pipeline, based on HMM and reciprocal best hits.
- Developed a method to merge and compare existing orthologous databases (EggNOG KOG, ProtozoaDB, Kegg Orthology).
- Performed similarity analysis against the human genome to identify potential protozoan targets.
Main Results:
- Created two comprehensive orthologous databases: "KO + EggNOG KOG" (16,938 groups) and "KO + EggNOG KOG + ProtozoaDB" (27,701 groups).
- Achieved significant coverage of protozoan genomes (e.g., up to 19% for Entamoeba histolytica).
- Identified 13 potential protozoan targets using a distant homology approach with the enhanced databases.
Conclusions:
- The HMM-based methodology generates broader orthologous datasets compared to original databases.
- These improved databases enhance homology inference, annotation tasks, and protozoan target discovery.
- The approach offers a valuable tool for advancing research in protozoan biology and drug development.

