The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements

By Adrian M. Altenhoff, Nives Skunca, Natasha M. Glover, Clément-Marie Train, Anna Sueki, Ivana Pilizota, Kevin Gori, Bartlomiej Tomiczek, Steven Müller, Henning Redestig and 2 more. 2014

216 citations recorded by the source corpus.

The Orthologous Matrix (OMA) project is a method and associated database inferring evolutionary relationships amongst currently 1706 complete proteomes (i.e. the protein sequence associated for every protein-coding gene in all genomes). In this update article, we present six major new developments in OMA: (i) a new web interface; (ii) Gene Ontology function predictions as part of the OMA pipeline; (iii) better support for plant genomes and in particular homeologs in the wheat genome; (iv) a new synteny viewer providing the genomic context of orthologs; (v) statically computed hierarchical orthologous groups subsets downloadable in OrthoXML format; and (vi) possibility to export parts of the all-against-all computations and to combine them with custom data for ‘client-side’ orthology prediction. OMA can be accessed through the OMA Browser and various programmatic interfaces at http://omabrowser.org.

Subfields: Biomedical Engineering, Molecular Biology, Plant Science

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Citations in the corpus

The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases (2015, background): “org) (69) is a resource for identifying orthologs among complete genomes.”
Protein Ontology (PRO): enhancing and scaling up the representation of protein entities (2016, methodology): “For example, PRO imports information from UniProtKB to create terms for selected species (2), and integrates information from the OMA (9) and PANTHER (10) databases to find connections between such terms.”
Crystal structures of eukaryote glycosyltransferases reveal biologically relevant enzyme homooligomers (2018, methodology): “Briefly, multiple sequence alignments were generated by querying the sequence of each studied GTase against the OMA orthology database [76], using the InterEvolAlign server.”
Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors (2019, methodology): “To determinate sequence relationships of receptor-ligand families across different organisms, we collected phylogenetic relationships and orthologous sequences through the REST API from the Orthologous MAtrix (OMA) database (version December 2017) (Altenhoff et al., 2015) using R and Python scripts ”
OMA standalone: orthology inference among public and custom genomes and transcriptomes (2018, background): “input sequences with Gene Ontology annotations by propagating high-quality annotations across orthologs (Altenhoff et al. 2015).”
Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome. (2017, unknown): “…(Koonin et al., 2004) https://www.ncbi.nlm.nih.gov/COG/new/ shokog.cgi; ftp://ftp.ncbi.nih.gov/pub/ COG/KOG OrthoMCL (Chen et al., 2006; Li et al., 2003) http://orthomcl.org/orthomcl/ OMA (Altenhoff et al., 2015) http://omabrowser.org/oma/home/ MUSCLE v3.”
The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces (2017, unknown): “One of the outputs of the OMA database are ‘OMA Groups,’ or sets of genes which are all orthologous to each other.”
Homoeologs: What Are They and How Do We Infer Them? (2016, methodology): “Computational biology Homoeologs: ‘orthologs between subgenomes’ [35]”