EvolClustDB: exploring eukaryotic gene clusters with evolutionarily conserved genomic neighbourhoods
Autor/a
Fecha de publicación
2023ISSN
0022-2836
Resumen
Conservation of gene neighbourhood over evolutionary distances is generally indicative of shared regulation or functional association among genes. This concept has been broadly exploited in prokaryotes but its use on eukaryotic genomes has been limited to specific functional classes, such as biosynthetic gene clusters. We here used an evolutionary-based gene cluster discovery algorithm (EvolClust) to pre-compute evolutionarily conserved gene neighbourhoods, which can be searched, browsed and downloaded in EvolClustDB. We inferred ∼35,000 cluster families in 882 different species in genome comparisons of five taxonomically broad clades: Fungi, Plants, Metazoans, Insects and Protists. EvolClustDB allows browsing through the cluster families, as well as searching by protein, species, identifier or sequence. Visualization allows inspecting gene order per species in a phylogenetic context, so that relevant evolutionary events such as gain, loss or transfer, can be inferred. EvolClustDB is freely available, without registration, at http://evolclustdb.org/.
Tipo de documento
Artículo
Versión del documento
Versión publicada
Lengua
Inglés
Materias (CDU)
57 - Biología
Palabras clave
Páginas
7
Publicado por
Elsevier
Colección
435; 14
Publicado en
Journal of Molecular Biology
Citación
Marcet-Houben, Marina; Collado Cala, Ismael; Fuentes Palacios, Diego [et al.]. EvolClustDB: exploring eukaryotic gene clusters with evolutionarily conserved genomic neighbourhoods. Journal of Molecular Biology, 2023, 435(14), 168013. Disponible en: <https://www.sciencedirect.com/science/article/pii/S0022283623000694?via%3Dihub>. Fecha de acceso; 25 feb. 2025. DOI: 10.1016/j.jmb.2023.168013
Número del acuerdo de la subvención
info:eu-repo/grantAgreement/EC/H2020/724173
info:eu-repo/grantAgreement/EC/H2020/793699
info:eu-repo/grantAgreement/ES/MICINN/IJC2019-039402-I
Nota
We want to acknowledge Joel Moro for his help in the analysis of the protist dataset and Daniel Majer for his help with the web interface. TG group acknowledges support from the Spanish Ministry of Science and Innovation for grant PGC2018-099921-B-I00, cofounded by European Regional Development Fund (ERDF); from the Catalan Research Agency (AGAUR) SGR423; from the European Union’s Horizon 2020 research and innovation programme (ERC-2016-724173); from the Gordon and Betty Moore Foundation (Grant GBMF9742); from the “La Caixa” foundation (Grant LCF/PR/HR21/00737), and from the Instituto de Salud Carlos III (IMPACT Grant IMP/00019 and CIBERINFEC CB21/13/00061- ISCIII-SGEFI/ERDF). UC was funded in part through H2020 Marie Skłodowska-Curie Actions (H2020-MSCA-IF-2017-793699) and MICINN (IJC2019-039402-I).
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Under a Creative Commons license.
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