OrthoDB: a hierarchical catalog of animal, fungal and bacterial orthologs

By Robert M. Waterhouse, Fredrik Tegenfeldt, Jia Li, E. Zdobnov, Evgenia V. Kriventseva. Nucleic Acids Res., 2012

395 citations recorded by the source corpus.

The concept of orthology provides a foundation for formulating hypotheses on gene and genome evolution, and thus forms the cornerstone of comparative genomics, phylogenomics and metagenomics. We present the update of OrthoDB—the hierarchical catalog of orthologs (http://www.orthodb.org). From its conception, OrthoDB promoted delineation of orthologs at varying resolution by explicitly referring to the hierarchy of species radiations, now also adopted by other resources. The current release provides comprehensive coverage of animals and fungi representing 252 eukaryotic species, and is now extended to prokaryotes with the inclusion of 1115 bacteria. Functional annotations of orthologous groups are provided through mapping to InterPro, GO, OMIM and model organism phenotypes, with cross-references to major resources including UniProt, NCBI and FlyBase. Uniquely, OrthoDB provides computed evolutionary traits of orthologs, such as gene duplicability and loss profiles, divergence rates, sibling groups, and now extended with exon–intron architectures, syntenic orthologs and parent–child trees. The interactive web interface allows navigation along the species phylogenies, complex queries with various identifiers, annotation keywords and phrases, as well as with gene copy-number profiles and sequence homology searches. With the explosive growth of available data, OrthoDB also provides mapping of newly sequenced genomes and transcriptomes to the current orthologous groups.

Subfields: Molecular Biology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/8daec3e38006636b19a9f1b858ee4b1ee426b14c

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Citations in the corpus

BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs (2015, neutral): “0.1 User Guide: Page 1”
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].”
The OMA orthology database in 2015: function predictions, better plant support, synteny view and other improvements (2014, methodology): “We also see potential in sharing computations across different resources and have initiated a joint effort with OrthoDB (10) in that direction.”
Anchored hybrid enrichment provides new insights into the phylogeny and evolution of longhorned beetles (Cerambycidae) (2018, methodology): “OrthoDB7 (Waterhouse et al., 2013; Kriventseva et al., 2015) was used to generate a table of clusters of orthologous groups (COGs) for each of the three chosen OGSs.”
Evolutionary History of the Hymenoptera. (2017, methodology): “We searched the assemblies with the software Orthograph (version beta4) [28] for transcripts of 3,260 protein-coding genes that the OrthoDB v7 database [30] suggested to be single-copy in Hymenoptera and Neuropteroidea (outgroup) by applying the best reciprocal hit criterion.”
Genenames.org: the HGNC resources in 2015 (2014, methodology): “HCOP currently collates orthology assertions from eggNOG (34), Ensembl Compara (2), HGNC, HomoloGene (31), InParanoid (35), OMA (36), OrthoDB (37), OrthoMCL (38), PANTHER (39), PhylomeDB (40), Treefam (41) and ZFIN (18) into a single tool, enabling comparison of these data to identify a consensus or”
The SIB Swiss Institute of Bioinformatics’ resources: focus on curated databases (2015, background): “Delineation of these blocks is based on single-copy orthologous protein markers from OrthoDB (release7) (20).”
FlyBase 102—advanced approaches to interrogating FlyBase (2013, methodology): “For example, most recently, we have improved the ortholog data we provide in collaboration with OrthoDB (2) and have added the modENCODE RNA-Seq data (3).”
SwissTargetPrediction: a web server for target prediction of bioactive small molecules (2014, methodology): “Orthologs and paralogs were retrieved from Ensembl Compara (38), Treefam (39) and orthoDB (40), using the union of all three datasets.”