HAMAP in 2015: updates to the protein family classification and annotation system

Pedruzzi, Ivo; Rivoire, Catherine; Auchincloss, Andrea H.; Coudert, Elisabeth; Keller, Guillaume; Castro, Edouard de; Baratin, Delphine; Cuche, Béatrice A.; Bougueleret, Lydie; Poux, Sylvain; Redaschi, Nicole; Xénarios, Ioannis; Bridge, Alan

doi:10.1093/nar/gku1002

Cited by 142 publications

(115 citation statements)

References 38 publications

(43 reference statements)

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“…These rules share a common syntax that specifies the predicted annotations—including protein nomenclature, function, subcellular location and catalytic residues—and necessary conditions, such as the requirement for conserved functional residues and motifs. InterPro integrates signatures from the HAMAP (19) and PIRSF (20) projects within the UniProt Consortium. Figure 4 illustrates our progress in UniRule generation to date.…”

Section: Progress and New Developmentsmentioning

confidence: 99%

UniProt: the universal protein knowledgebase

2016

Nucleic Acids Res

4,028

2,399

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The UniProt knowledgebase is a large resource of protein sequences and associated detailed annotation. The database contains over 60 million sequences, of which over half a million sequences have been curated by experts who critically review experimental and predicted data for each protein. The remainder are automatically annotated based on rule systems that rely on the expert curated knowledge. Since our last update in 2014, we have more than doubled the number of reference proteomes to 5631, giving a greater coverage of taxonomic diversity. We implemented a pipeline to remove redundant highly similar proteomes that were causing excessive redundancy in UniProt. The initial run of this pipeline reduced the number of sequences in UniProt by 47 million. For our users interested in the accessory proteomes, we have made available sets of pan proteome sequences that cover the diversity of sequences for each species that is found in its strains and sub-strains. To help interpretation of genomic variants, we provide tracks of detailed protein information for the major genome browsers. We provide a SPARQL endpoint that allows complex queries of the more than 22 billion triples of data in UniProt (http://sparql.uniprot.org/). UniProt resources can be accessed via the website at http://www.uniprot.org/.

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Section: Progress and New Developmentsmentioning

confidence: 99%

UniProt: the universal protein knowledgebase

2016

Nucleic Acids Res

4,028

2,399

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“…The mappings described here contain additional annotation including isoform sequences from Swiss-Prot and also sequences and features from the TrEMBL section of UniProtKB. UniProtKB/TrEMBL contains additional isoforms and predicted genes not currently in UniProtKB/Swiss-Prot and automated annotation provided by a combination of automated prediction algorithms with human curated rules (Vasudevan et al 2010;Dimmer et al 2012;Famiglietti et al 2014;Pedruzzi et al 2015). This includes sequence features such as active sites, binding sites and functional domains.…”

Section: Cc-by-nd 40 International License Peer-reviewed) Is the Autmentioning

confidence: 99%

UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants

McGarvey

Nightingale

Luo

et al. 2017

Preprint

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The integration of protein function knowledge in the UniProt Knowledgebase (UniProtKB) with genomic data provides unique opportunities for biomedical research by helping scientists to rapidly comprehend complex processes in biology. UniProtKB provides expert curation of functionally characterized variants reported in the literature, many of them associated with disease.Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of large-scale genomics data. UniProtKB protein sequences and sequence feature annotations such as active sites, modified sites, binding domains and amino acid variation have been mapped to the current build of the human genome (GRCh38). We have also created public track hubs for the Ensembl and UCSC browsers. We examine some specific biological examples in disease-related genes and proteins, illustrating the utility of combining protein and genome annotations for the functional interpretation of variants. We also present a larger comparison of UniProtKB variant and feature curation data that collocates with clinically observed SNP data from ClinVar, illustrating how protein and gene disease annotations currently compare and discuss some additional uses that might follow with combined annotation. The combination of gene and protein annotation can assist medical geneticists with the functional interpretation of variation. The genomic track hubs are downloadable from the UniProt FTP site (http://www.uniprot.org/downloads) and directly discoverable as public track hubs at the USCS and Ensembl genome browsers.

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“…In HAMAP, manually curated family profiles are associated with annotation rules that trigger automatic annotation of proteins belonging to these well-conserved families or subfamilies (http://hamap.expasy.org/) (4). Another automatic annotation approach is InterPro2GO (5), in which GO terms are automatically assigned based on the presence of a protein domain.…”

Section: Introductionmentioning

confidence: 99%

Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

Feuermann¹,

Gaudet²,

Mi³

et al. 2016

Database

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We previously reported a paradigm for large-scale phylogenomic analysis of gene families that takes advantage of the large corpus of experimentally supported Gene Ontology (GO) annotations. This ‘GO Phylogenetic Annotation’ approach integrates GO annotations from evolutionarily related genes across ∼100 different organisms in the context of a gene family tree, in which curators build an explicit model of the evolution of gene functions. GO Phylogenetic Annotation models the gain and loss of functions in a gene family tree, which is used to infer the functions of uncharacterized (or incompletely characterized) gene products, even for human proteins that are relatively well studied. Here, we report our results from applying this paradigm to two well-characterized cellular processes, apoptosis and autophagy. This revealed several important observations with respect to GO annotations and how they can be used for function inference. Notably, we applied only a small fraction of the experimentally supported GO annotations to infer function in other family members. The majority of other annotations describe indirect effects, phenotypes or results from high throughput experiments. In addition, we show here how feedback from phylogenetic annotation leads to significant improvements in the PANTHER trees, the GO annotations and GO itself. Thus GO phylogenetic annotation both increases the quantity and improves the accuracy of the GO annotations provided to the research community. We expect these phylogenetically based annotations to be of broad use in gene enrichment analysis as well as other applications of GO annotations.Database URL: http://amigo.geneontology.org/amigo

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HAMAP in 2015: updates to the protein family classification and annotation system

Cited by 142 publications

References 38 publications

UniProt: the universal protein knowledgebase

UniProt: the universal protein knowledgebase

UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants

Large-scale inference of gene function through phylogenetic annotation of Gene Ontology terms: case study of the apoptosis and autophagy cellular processes

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