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2024-07-08

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cc-by (c) Pisarenco, Vadim A. et al., 2024
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/218646

GALEON: a comprehensive bioinformatic tool to analyse and visualize gene clusters in complete genomes

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https://doi.org/10.1093/bioinformatics/btae439

Abstract

Motivation: 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. Results: To facilitate the identification, analysis, and visualization 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.

Subject

Bioinformàtica, Anàlisi de conglomerats, Genomes

Subject (English)

Bioinformatics, Cluster analysis, Genomes

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Articles publicats en revistes (Genètica, Microbiologia i Estadística)
Articles publicats en revistes (Institut de Recerca de la Biodiversitat (IRBio))

Citation

PISARENCO, Vadim A., VIZUETA, Joel and ROZAS LIRAS, Julio A. GALEON: a comprehensive bioinformatic tool to analyse and visualize gene clusters in complete genomes. Bioinformatics. 2024. Vol. 40, num. 7, pags. 1-4. ISSN 1367-4803. [consulted: 9 of June of 2026]. Available at: https://hdl.handle.net/2445/218646

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