OrthoDB v9.1: cataloging evolutionary and functional annotations for animal, fungal, plant, archaeal, bacterial and viral orthologs

By E. Zdobnov, Fredrik Tegenfeldt, D. Kuznetsov, Robert M. Waterhouse, Felipe A. Simão, Panagiotis Ioannidis, Mathieu Seppey, Alexis Loetscher, Evgenia V. Kriventseva. 2016

430 citations recorded by the source corpus.

OrthoDB is a comprehensive catalog of orthologs, genes inherited by extant species from a single gene in their last common ancestor. In 2016 OrthoDB reached its 9th release, growing to over 22 million genes from over 5000 species, now adding plants, archaea and viruses. In this update we focused on usability of this fast-growing wealth of data: updating the user and programmatic interfaces to browse and query the data, and further enhancing the already extensive integration of available gene functional annotations. Collating functional annotations from over 100 resources, and enabled us to propose descriptive titles for 87% of ortholog groups. Additionally, OrthoDB continues to provide computed evolutionary annotations and to allow user queries by sequence homology. The OrthoDB resource now enables users to generate publication-quality comparative genomics charts, as well as to upload, analyze and interactively explore their own private data. OrthoDB is available from http://orthodb.org.

Subfields: Insect Science, Molecular Biology, Plant Science

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Citations in the corpus

OMA orthology in 2021: website overhaul, conserved isoforms, ancestral gene order and more (2020, methodology): “In the SwissOrthology portal (https://swissorthology.ch), we provide consensus orthology calls from OMA and OrthoDB (39) using federated SPARQL queries in the backend.”
OrthoDB v11: annotation of orthologs in the widest sampling of organismal diversity (2022, background): “As in previous releases, the abundance of gene annotations within each orthologous group (OG) is condensed into a one-line text description as previously described (29).”
OMA standalone: orthology inference among public and custom genomes and transcriptomes (2018, neutral): “…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.,…”
OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species (2019, methodology): “The second is graphbased, and this methodology is found in tools including PanOCT (8), OrthoFinder (9), OrthoMCL (10), COCOCL (11), OrthoDB (12), OMA (13) and Roary (14).”
FlyBase 2.0: the next generation (2018, positive): “This has included orthology data from OrthoDB (https://www.orthodb.org/, PMID:27899580) (9) and meta-analysis from DIOPT (https://www.flyrnai.org/ cgi-bin/DRSC orthologs.pl) (10).”
A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL (2019, methodology): “OrthoDB (Zdobnov et al. , 2017) contains orthologous genes along with evolutionary and functional annotations. et al. , 2016), they use different ORTH versions.”
Scalable phylogenetic profiling using MinHash uncovers likely eukaryotic sexual reproduction genes (2019, background): “As a result, most mainstream phylogenomic databases, such as Ensembl [12] , EggNOG [13] , OrthoDB [14] , or OMA [15] do not provide phylogenetic profiles.”