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eggNOG v7: phylogeny-based orthology predictions and functional annotations.
Ana Hernández-Plaza1, Ziqi Deng1, Fabian Robledo-Yagüe2
1Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid (UPM)-Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA-CSIC), Campus de Montegancedo-UPM, 28223 Madrid, Spain.
Nucleic Acids Research
|December 8, 2025
Summary
The eggNOG v7 database enhances evolutionary gene analysis with a new phylogenetic, domain-centric workflow. This phylogenomic resource improves orthologous group reconstruction and functional annotation accuracy for millions of proteins.
Area of Science:
- Genomics
- Evolutionary Biology
- Bioinformatics
Background:
- The eggNOG database provides orthology inference and functional annotation across diverse species.
- Previous versions faced computational and accuracy limitations in orthologous group reconstruction.
Purpose of the Study:
- To introduce eggNOG v7, featuring a novel phylogenetic, domain-centric workflow.
- To enhance orthologous group (OG) reconstruction, evolutionary dating, and functional annotation accuracy.
Main Methods:
- Implemented a domain-centric pipeline involving sequence pre-clustering, multiple sequence alignment, and phylogenetic tree inference.
- Utilized a noise-tolerant algorithm for speciation and duplication event detection to build hierarchically consistent OGs.
- Applied the workflow to 59.3 million proteins from 12,535 species.
Main Results:
- Generated 3.18 million orthologous groups (OGs) with reduced fragmentation and improved consistency compared to previous versions.
- Demonstrated higher functional consistency against manually curated KEGG OGs.
- Released updated protein functional annotations and a redesigned web interface with enhanced search and visualization tools.
Conclusions:
- eggNOG v7 represents a significant advancement in phylogenomic analysis through its robust phylogenetic, domain-centric approach.
- The new version offers improved accuracy, consistency, and usability for evolutionary and functional genomics research.
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