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The Chordate Proteome History Database
Author(s) -
Anthony Levasseur,
Julien Paganini,
Jacques Dainat,
Julie Thompson,
Olivier Poch,
Pierre Pontarotti,
Philippe Gouret
Publication year - 2012
Publication title -
evolutionary bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.502
H-Index - 32
ISSN - 1176-9343
DOI - 10.4137/ebo.s9186
Subject(s) - phylogenetic tree , chordate , biology , proteome , phylogenetics , phylogenetic network , lineage (genetic) , protein domain , architecture domain , gene duplication , computational biology , phylogenomics , evolutionary biology , database , genome , gene , bioinformatics , genetics , computer science , clade , software architecture , software , enterprise architecture framework , programming language
The chordate proteome history database (http://ioda.univ-provence.fr) comprises some 20,000 evolutionary analyses of proteins from chordate species. Our main objective was to characterize and study the evolutionary histories of the chordate proteome, and in particular to detect genomic events and automatic functional searches. Firstly, phylogenetic analyses based on high quality multiple sequence alignments and a robust phylogenetic pipeline were performed for the whole protein and for each individual domain. Novel approaches were developed to identify orthologs/paralogs, and predict gene duplication/gain/loss events and the occurrence of new protein architectures (domain gains, losses and shuffling). These important genetic events were localized on the phylogenetic trees and on the genomic sequence. Secondly, the phylogenetic trees were enhanced by the creation of phylogroups, whereby groups of orthologous sequences created using OrthoMCL were corrected based on the phylogenetic trees; gene family size and gene gain/loss in a given lineage could be deduced from the phylogroups. For each ortholog group obtained from the phylogenetic or the phylogroup analysis, functional information and expression data can be retrieved. Database searches can be performed easily using biological objects: protein identifier, keyword or domain, but can also be based on events, eg, domain exchange events can be retrieved. To our knowledge, this is the first database that links group clustering, phylogeny and automatic functional searches along with the detection of important events occurring during genome evolution, such as the appearance of a new domain architecture.

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