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An update on the Symbiotic Genomes Database (SymGenDB): a collection of metadata, genomic, genetic and protein sequences, orthologs and metabolic networks of symbiotic organisms
Author(s) -
Mariana ReyesPrieto,
Carlos Vargas-Chávez,
Mercè Llabrés,
Pere Palmer-Rodríguez,
Amparo Latorre,
Andrés Moyá
Publication year - 2019
Publication title -
database
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.406
H-Index - 62
ISSN - 1758-0463
DOI - 10.1093/database/baz160
Subject(s) - genome , bacterial genome size , biology , organism , metadata , database , model organism , computational biology , gene , computer science , genetics , world wide web
The Symbiotic Genomes Database (SymGenDB; http://symbiogenomesdb.uv.es/) is a public resource of manually curated associations between organisms involved in symbiotic relationships, maintaining a catalog of completely sequenced/finished bacterial genomes exclusively. It originally consisted of three modules where users could search for the bacteria involved in a specific symbiotic relationship, their genomes and their genes (including their orthologs). In this update, we present an additional module that includes a representation of the metabolic network of each organism included in the database, as Directed Acyclic Graphs (MetaDAGs). This module provides unique opportunities to explore the metabolism of each individual organism and/or to evaluate the shared and joint metabolic capabilities of the organisms of the same genera included in our listing, allowing users to construct predictive analyses of metabolic associations and complementation between systems. We also report a ~25% increase in manually curated content in the database, i.e. bacterial genomes and their associations, with a final count of 2328 bacterial genomes associated to 498 hosts. We describe new querying possibilities for all the modules, as well as new display features for the MetaDAGs module, providing a relevant range of content and utility. This update continues to improve SymGenDB and can help elucidate the mechanisms by which organisms depend on each other.

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