The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces

By Adrian M. Altenhoff, Natasha M. Glover, Clément-Marie Train, Klara Kaleb, Alex Warwick Vesztrocy, D. Dylus, Tarcisio Mendes de Farias, Karina Zile, Charles Stevenson, Jiao Long and 3 more. 2017

215 citations recorded by the source corpus.

Abstract The Orthologous Matrix (OMA) is a leading resource to relate genes across many species from all of life. In this update paper, we review the recent algorithmic improvements in the OMA pipeline, describe increases in species coverage (particularly in plants and early-branching eukaryotes) and introduce several new features in the OMA web browser. Notable improvements include: (i) a scalable, interactive viewer for hierarchical orthologous groups; (ii) protein domain annotations and domain-based links between orthologous groups; (iii) functionality to retrieve phylogenetic marker genes for a subset of species of interest; (iv) a new synteny dot plot viewer; and (v) an overhaul of the programmatic access (REST API and semantic web), which will facilitate incorporation of OMA analyses in computational pipelines and integration with other bioinformatic resources. OMA can be freely accessed at https://omabrowser.org.

Subfields: Ecology, Molecular Biology

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Citations in the corpus

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more (2020, methodology): “Finally, genome-centric pages, recognisable by their red theme, provide information on the underlying species, a list of all genes associated with them, a list of closely related genomes in OMA, and access to the pairwise global synteny viewer introduced earlier (6).”
eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses (2018, background): “Hence, several databases have been developed over the years that provide precomputed orthology predictions using different approaches and operational definitions (8–13).”
OMA standalone: orthology inference among public and custom genomes and transcriptomes (2018, unknown): “…et al., 2016) , Ensembl Compara (Zerbino et al., 2018) , Inparanoid (Sonnhammer and Östlund, 2015) , MBGD (Uchiyama et al., 2012) , OrthoDB (Zdobnov et al., 2017) , OrthoMCL (Chen et al., 2006) , Panther (Mi et al., 2017) , PhylomeDB (Huerta-Cepas et al., 2014) , and OMA (Altenhoff et al., 2017) .”
TransmiR v2.0: an updated transcription factor-microRNA regulation database (2018, methodology): “For TFs in non-human species, we tried to map the annotations according to their human orthologs recorded in OMA database (24).”
Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes (2019, methodology): “Within eukaryotes, OMA includes 188 animals, 135 fungi, 57 plants, and 82 protists and has been benchmarked and integrated with other proteomic and genomic resources [16].”
CircAtlas: an integrated resource of one million highly accurate circular RNAs from 1070 vertebrate transcriptomes (2020, methodology): “In brief, a pairwise orthologous gene list was downloaded from the OMA ortholog database [38], and the circRNAs located on these orthologous genes for each species were determined using the genome annotation file.”
COG database update: focus on microbial diversity, model organisms, and widespread pathogens (2020, background): “Although there are several other databases of orthologous proteins in bacteria and archaea, such as eggNOG (49), KEGG Orthology (50,51), OMA (52,53), OrthoDB (54) and MBGD (55), which cover a wider selection of organisms than the COGs and provide comprehensive, automated functional annotation of the”
Advances and Applications in the Quest for Orthologs (2019, methodology): “As of April 2019, the updated, benchmarked ortholog inferences (on the 2018 benchmark) are available for download at the orthology benchmarking service website (https://orthology.benchmarkservice.org; Last accessed April 2019) for nine methods: InParanoid (Sonnhammer and €Ostlund 2015), Hieranoid 2 ”
Genenames.org: the HGNC and VGNC resources in 2021 (2020, background): “This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. nloaded from https://aca”
A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL (2019, background): “…the following major Orthology Databases structure their data in RDF, as well as how they can be queried using SPARQL: the Orthologous MAtrix (OMA) (Altenhoff et al. , 2018), the European Bioinformatics Institute (EBI) RDF platform (Jupp, et al. , 2014), the Database of Orthologous Groups…”
OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs (2018, background): “The large-scale delineation of gene orthology is a popular but challenging task as evidenced by numerous proposed approaches (5–14).”
How to build phylogenetic species trees with OMA (2020, unknown): “Here, we show how to leverage the publicly available orthology data to infer phylogenetic species trees.”
OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species (2019, methodology): “OrthoVenn2 showed accuracy similar to InParanoidCore, OMA Groups 2.0, eggNOG and SonicParanoid (fast) (Supplementary Figure S1).”