OrthoMCL-DB: querying a comprehensive multi-species collection of ortholog groups

By F. Chen, Aaron J. Mackey, Christian J. Stoeckert Jr., David S. Roos. Nucleic Acids Res., 2005

902 citations recorded by the source corpus.

The OrthoMCL database () houses ortholog group predictions for 55 species, including 16 bacterial and 4 archaeal genomes representing phylogenetically diverse lineages, and most currently available complete eukaryotic genomes: 24 unikonts (12 animals, 9 fungi, microsporidium, Dictyostelium, Entamoeba), 4 plants/algae and 7 apicomplexan parasites. OrthoMCL software was used to cluster proteins based on sequence similarity, using an all-against-all BLAST search of each species' proteome, followed by normalization of inter-species differences, and Markov clustering. A total of 511 797 proteins (81.6% of the total dataset) were clustered into 70 388 ortholog groups. The ortholog database may be queried based on protein or group accession numbers, keyword descriptions or BLAST similarity. Ortholog groups exhibiting specific phyletic patterns may also be identified, using either a graphical interface or a text-based Phyletic Pattern Expression grammar. Information for ortholog groups includes the phyletic profile, the list of member proteins and a multiple sequence alignment, a statistical summary and graphical view of similarities, and a graphical representation of domain architecture. OrthoMCL software, the entire FASTA dataset employed and clustering results are available for download. OrthoMCL-DB provides a centralized warehouse for orthology prediction among multiple species, and will be updated and expanded as additional genome sequence data become available.

Subfields: Ecology, Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/d746e9ac3ef08397cef89feebc08fa66e6729edf

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Citations in the corpus

OMA standalone: orthology inference among public and custom genomes and transcriptomes (2018, neutral): “The OrthoMCL trees had the most issues, with the lowest support values.”
Annotation Error in Public Databases: Misannotation of Molecular Function in Enzyme Superfamilies (2009, background): “Databases of motifs [28–30], sequence profiles [31,32], and ortholog sets [33,34], are available for use in computational annotation.”
ToxoDB: an integrated Toxoplasma gondii database resource (2007, background): “gondii with orthologous genes from 86 other eukaryotic and prokaryotic genomes (10).”
Assessing Performance of Orthology Detection Strategies Applied to Eukaryotic Genomes (2007, background): “Analysis of independently assigned EC number annotations suggests a high degree of reliability [18], and orthology predictions for 55 genomes are available at OrthoMCL-DB [20].”
Using OrthoMCL to assign proteins to OrthoMCL-DB groups or to cluster proteomes into new ortholog groups (2011, background): “OrthoMCL-DB (Chen et al., 2006) contains ortholog groups for most completely sequenced and annotated eukaryotes and for a number of completely sequenced and annotated prokaryotes.”
Reactome knowledgebase of human biological pathways and processes (2008, neutral): “The OrthoMCL clustering procedure (1,2) (http:// reactome.”
The OMA orthology database in 2018: retrieving evolutionary relationships among all domains of life through richer web and programmatic interfaces (2017, neutral): “Because orthologs are so important, a large number of methods and resources for their inference have been developed over the years, such as the COGs database (4), Inparanoid (5), OrthoMCL (6), En-sembl Compara (7), KEGG Orthology (8), PhylomeDb (9), OrthoDB (10), EggNOG (11), MBGD (12), PLAZA (13) o”
VEuPathDB: the eukaryotic pathogen, vector and host bioinformatics resource center (2021, background): “org (38) as well as the orthology relationships in the VEuPathDB sites.”
The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements (2014, methodology): “The need for orthology inference has led to the development of numerous methods (reviewed in 5) and databases, notably including EggNOG (6), Ensembl Compara (7), Inparanoid (8), MBGD (9), OrthoDB (10), OrthoMCL (11), Panther (12), PhylomeDB (13), Plaza (14) and OMA (15).”
TreeFam: 2008 Update (2007, methodology): “Tree-based inference of orthologues is more robust to rate diﬀerences than BLAST -based orthologue inference, which has been used in other databases such as InParanoid (5), KOGs (6), HomoloGene (7) and OrthoMCL-DB (8).”
A Phylogeny-Based Benchmarking Test for Orthology Inference Reveals the Limitations of Function-Based Validation (2014, background): “In addition to the mostly manually curated, and thus irregularly updated, COG database [11], there are other orthology resources that have adapted this definition of orthologous groups (i.e. eggNOG [12], OrthoDB, [13], OrthoMCL [14]).”
MODBASE: a database of annotated comparative protein structure models and associated resources (2005, methodology): “The sequences were retrieved from ENSEMBL (36), TIGR (50), NCBI-Genbank (6), OrthoMCL-DB (51), TubercuList (52), CryptoDB (53), GeneDB (54), ToxoDB (55), SFLD (56) and UniProt (34).”
Reactome: a database of reactions, pathways and biological processes (2010, methodology): “Curated human reactions were used previously to electronically infer reactions by orthology in 20 evolutionary divergent species, with the assistance of the OrthoMCL (25).”
ModBase, a database of annotated comparative protein structure models and associated resources (2013, methodology): “The sequences were retrieved from ENSEMBL (36), TIGR (50), NCBI-Genbank (6), OrthoMCL-DB ( 51 ), TubercuList (52), CryptoDB (53), GeneDB (54), ToxoDB (55), SFLD (56) and UniProt (34).”
Insights into Land Plant Evolution Garnered from the Marchantia polymorpha Genome. (2017, background): “…(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.”
PlasmoDB: a functional genomic database for malaria parasites (2008, background): “OrthoMCL analyses provide ortholog determinations between the different species facilitating discovery of shared genes between lineages (26).”
OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy (2015, background): “orthogroups; an orthogroup is the set of genes that are descended from a single gene in the last common ancestor of all the species being considered [2, 5–9].”