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      OrthoDB v10: sampling the diversity of animal, plant, fungal, protist, bacterial and viral genomes for evolutionary and functional annotations of orthologs

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          Abstract

          OrthoDB ( https://www.orthodb.org) provides evolutionary and functional annotations of orthologs. This update features a major scaling up of the resource coverage, sampling the genomic diversity of 1271 eukaryotes, 6013 prokaryotes and 6488 viruses. These include putative orthologs among 448 metazoan, 117 plant, 549 fungal, 148 protist, 5609 bacterial, and 404 archaeal genomes, picking up the best sequenced and annotated representatives for each species or operational taxonomic unit. OrthoDB relies on a concept of hierarchy of levels-of-orthology to enable more finely resolved gene orthologies for more closely related species. Since orthologs are the most likely candidates to retain functions of their ancestor gene, OrthoDB is aimed at narrowing down hypotheses about gene functions and enabling comparative evolutionary studies. Optional registered-user sessions allow on-line BUSCO assessments of gene set completeness and mapping of the uploaded data to OrthoDB to enable further interactive exploration of related annotations and generation of comparative charts. The accelerating expansion of genomics data continues to add valuable information, and OrthoDB strives to provide orthologs from the broadest coverage of species, as well as to extensively collate available functional annotations and to compute evolutionary annotations. The data can be browsed online, downloaded or assessed via REST API or SPARQL RDF compatible with both UniProt and Ensembl.

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          Most cited references15

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          Orthologs, paralogs, and evolutionary genomics.

          Orthologs and paralogs are two fundamentally different types of homologous genes that evolved, respectively, by vertical descent from a single ancestral gene and by duplication. Orthology and paralogy are key concepts of evolutionary genomics. A clear distinction between orthologs and paralogs is critical for the construction of a robust evolutionary classification of genes and reliable functional annotation of newly sequenced genomes. Genome comparisons show that orthologous relationships with genes from taxonomically distant species can be established for the majority of the genes from each sequenced genome. This review examines in depth the definitions and subtypes of orthologs and paralogs, outlines the principal methodological approaches employed for identification of orthology and paralogy, and considers evolutionary and functional implications of these concepts.
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            The genome sequence of taurine cattle: a window to ruminant biology and evolution.

            To understand the biology and evolution of ruminants, the cattle genome was sequenced to about sevenfold coverage. The cattle genome contains a minimum of 22,000 genes, with a core set of 14,345 orthologs shared among seven mammalian species of which 1217 are absent or undetected in noneutherian (marsupial or monotreme) genomes. Cattle-specific evolutionary breakpoint regions in chromosomes have a higher density of segmental duplications, enrichment of repetitive elements, and species-specific variations in genes associated with lactation and immune responsiveness. Genes involved in metabolism are generally highly conserved, although five metabolic genes are deleted or extensively diverged from their human orthologs. The cattle genome sequence thus provides a resource for understanding mammalian evolution and accelerating livestock genetic improvement for milk and meat production.
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              Functional and evolutionary implications of gene orthology.

              Orthologues and paralogues are types of homologous genes that are related by speciation or duplication, respectively. Orthologous genes are generally assumed to retain equivalent functions in different organisms and to share other key properties. Several recent comparative genomic studies have focused on testing these expectations. Here we discuss the complexity of the evolution of gene-phenotype relationships and assess the validity of the key implications of orthology and paralogy relationships as general statistical trends and guiding principles.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                08 January 2019
                05 November 2018
                05 November 2018
                : 47
                : Database issue , Database issue
                : D807-D811
                Affiliations
                [1 ]Department of Genetic Medicine and Development, University of Geneva Medical School, rue Michel-Servet 1, 1211 Geneva, Switzerland
                [2 ]Swiss Institute of Bioinformatics, rue Michel-Servet 1, 1211 Geneva, Switzerland
                Author notes
                To whom correspondence should be addressed. Tel: +41 22 379 54 32; Fax:+41 22 379 57 06; Email: evgenia.kriventseva@ 123456unige.ch . Correspondence may also be addressed to Evgeny Zdobnov. Tel: +41 22 379 59 73; Email: evgeny.zdobnov@ 123456unige.ch
                Article
                gky1053
                10.1093/nar/gky1053
                6323947
                30395283
                fcc6b6e8-5c76-4162-8382-ccd5264cf17b
                © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

                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.

                History
                : 29 October 2018
                : 16 October 2018
                : 15 September 2018
                Page count
                Pages: 5
                Funding
                Funded by: Swiss National Science Foundation 10.13039/501100001711
                Award ID: 31003A_166483
                Funded by: São Paulo Research Foundation 10.13039/501100001807
                Award ID: 17/15195–2
                Categories
                Database Issue

                Genetics
                Genetics

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