Tree2GD: a phylogenomic method to detect large-scale gene duplication events

Duoyuan Chen, Taikui Zhang, Yamao Chen, Hong Ma, Ji Qi

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

MOTIVATION: Whole-genome duplication events have long been discovered throughout the evolution of eukaryotes, contributing to genome complexity and biodiversity and leaving traces in the descending organisms. Therefore, an accurate and rapid phylogenomic method is needed to identify the retained duplicated genes on various lineages across the target taxonomy. RESULTS: Here, we present Tree2GD, an integrated method to identify large-scale gene duplication events by automatically perform multiple procedures, including sequence alignment, recognition of homolog, gene tree/species tree reconciliation, Ks distribution of gene duplicates and synteny analyses. Application of Tree2GD on 2 datasets, 12 metazoan genomes and 68 angiosperms, successfully identifies all reported whole-genome duplication events exhibited by these species, showing effectiveness and efficiency of Tree2GD on phylogenomic analyses of large-scale gene duplications. AVAILABILITY AND IMPLEMENTATION: Tree2GD is written in Python and C++ and is available at https://github.com/Dee-chen/Tree2gd. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Original languageEnglish (US)
Pages (from-to)5317-5321
Number of pages5
JournalBioinformatics (Oxford, England)
Volume38
Issue number23
DOIs
StatePublished - Nov 30 2022

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Biochemistry
  • Molecular Biology
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

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