GALEON: A Comprehensive Bioinformatic Tool to Analyse and Visualise Gene Clusters in Complete Genomes.


Journal

Bioinformatics (Oxford, England)
ISSN: 1367-4811
Titre abrégé: Bioinformatics
Pays: England
ID NLM: 9808944

Informations de publication

Date de publication:
08 Jul 2024
Historique:
received: 16 04 2024
revised: 12 06 2024
accepted: 05 07 2024
medline: 8 7 2024
pubmed: 8 7 2024
entrez: 8 7 2024
Statut: aheadofprint

Résumé

Gene clusters, defined as a set of genes encoding functionally-related proteins, are abundant in eukaryotic genomes. Despite the increasing availability of chromosome-level genomes, the comprehensive analysis of gene family evolution remains largely unexplored, particularly for large and highly dynamic gene families or those including very recent family members. These challenges stem from limitations in genome assembly contiguity, particularly in repetitive regions such as large gene clusters. Recent advancements in sequencing technology, such as long reads and chromatin contact mapping, hold promise in addressing these challenges. To facilitate the identification, analysis, and visualisation of physically clustered gene family members within chromosome-level genomes, we introduce GALEON, a user-friendly bioinformatic tool. GALEON identifies gene clusters by studying the spatial distribution of pairwise physical distances among gene family members along with the genome-wide gene density. The pipeline also enables the simultaneous analysis and comparison of two gene families and allows the exploration of the relationship between physical and evolutionary distances. This tool offers a novel approach for studying the origin and evolution of gene families. GALEON is freely available from https://www.ub.edu/softevol/galeon, and from https://github.com/molevol-ub/galeon.

Identifiants

pubmed: 38976642
pii: 7709405
doi: 10.1093/bioinformatics/btae439
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Vadim A Pisarenco (VA)

Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain.
Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain.

Joel Vizueta (J)

Villum Centre for Biodiversity Genomics, Section for Ecology and Evolution, Department of Biology, University of Copenhagen, Copenhagen, Denmark.

Julio Rozas (J)

Departament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona, Spain.
Institut de Recerca de la Biodiversitat (IRBio), Universitat de Barcelona, Barcelona, Spain.

Classifications MeSH