EvolClust
EvolClust identifies evolutionarily conserved gene clusters by detecting groups of homologous proteins with conserved gene order across multiple eukaryotic genomes.
Key Features:
- Pairwise genome comparisons: Predicts conserved gene clusters by identifying groups of homologous proteins that are consistently co-located in at least two genomes.
- All-versus-all genome comparisons: Infers multi-species cluster families by comparing genomes across a dataset to find related clusters present in multiple species.
- Conservation significance: Detects clusters that are conserved beyond the level expected for the compared genomes.
- Broad taxonomic application: Applied to eukaryotic genomes across five major clades: Fungi, Plants, Metazoans, Insects, and Protists.
- EvolClustDB: Provides pre-computed evolutionarily conserved gene neighborhoods and links gene order information to phylogenetic context to support inference of evolutionary events.
Scientific Applications:
- Evolutionary genomics: Identification of conserved gene clusters to infer potential regulatory or functional associations among genes.
- Inference of evolutionary events: Mapping conserved gene order within phylogenetic contexts to infer gene gain, loss, or transfer.
- Comparative eukaryotic genomics: Discovery and analysis of conserved gene clusters across Fungi, Plants, Metazoans, Insects, and Protists.
Methodology:
Uses pairwise genome comparisons to detect groups of homologous proteins co-located in at least two genomes, employs all-versus-all genome comparisons to infer families of related clusters across species, and pre-computes conserved gene neighborhoods in EvolClustDB for phylogenetic mapping of gene order to infer gain, loss, or transfer.
Topics
Collections
Details
- Tool Type:
- web application
- Programming Languages:
- Python
- Added:
- 11/14/2019
- Last Updated:
- 11/24/2024
Operations
Publications
Marcet-Houben M, Gabaldón T. EvolClust: automated inference of evolutionary conserved gene clusters in eukaryotes. Bioinformatics. 2019;36(4):1265-1266. doi:10.1093/bioinformatics/btz706. PMID:31560365. PMCID:PMC7703780.
Marcet-Houben M, Collado-Cala I, Fuentes-Palacios D, Gómez AD, Molina M, Garisoain-Zafra A, Chorostecki U, Gabaldón T. EvolClustDB: Exploring Eukaryotic Gene Clusters with Evolutionarily Conserved Genomic Neighbourhoods. Journal of Molecular Biology. 2023;435(14):168013. doi:10.1016/j.jmb.2023.168013. PMID:36806474.