Submit Data |  Help |  Video Tutorials |  News |  Publications |  FTP Download |  REST API |  Citing RGD |  Contact   
Search RGD Grant Resources Citing RGD About Us Contact Us
Genes QTLs Strains Markers Genome Information Ontologies Cell Lines References FTP Download Submit Data
OntoMate (Literature Search) JBrowse (Genome Browser) Variant Visualizer Multi-Ontology Enrichment (MOET) Gene-Ortholog Location Finder (GOLF) InterViewer (Protein-Protein Interactions) PhenoMiner (Quatitative Phenotypes) Gene Annotator OLGA (Gene List Generator) RatMine GViewer (Genome Viewer) Overgo Probe Designer ACP Haplotyper Genome Scanner
Aging & Age-Related Disease Cancer Cardiovascular Disease COVID-19 Developmental Disease Diabetes Hematologic Disease Immune & Inflammatory Disease Liver Disease Neurological Disease Obesity & Metabolic Syndrome Renal Disease Respiratory Disease Sensory Organ Disease
Find Models   new Genetic Models Autism Models PhenoMiner (Quantitative Phenotypes) Expected Ranges (Quantitative Phenotype) PhenoMiner Term Comparison Hybrid Rat Diversity Panel Phenotypes GERRC (Gene Editing Rat Resource Center) Phenotypes in Other Animal Models Animal Husbandry Strain Medical Records Phylogenetics Strain Availability Calendar Rats 101 Submissions Photo Archive
Pathways
Rat Community Forum Directory of Rat Laboratories Video Tutorials News RGD Publications RGD Poster Archive Nomenclature Guidelines Resource Links Laboratory Resources Employment Resources

Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium.

Authors: Gaudet, Pascale  Livstone, Michael S  Lewis, Suzanna E  Thomas, Paul D 
Citation: Gaudet P, etal., Brief Bioinform. 2011 Sep;12(5):449-62. doi: 10.1093/bib/bbr042. Epub 2011 Aug 27.
Pubmed: (View Article at PubMed) PMID:21873635
DOI: Full-text: DOI:10.1093/bib/bbr042

The goal of the Gene Ontology (GO) project is to provide a uniform way to describe the functions of gene products from organisms across all kingdoms of life and thereby enable analysis of genomic data. Protein annotations are either based on experiments or predicted from protein sequences. Since most sequences have not been experimentally characterized, most available annotations need to be based on predictions. To make as accurate inferences as possible, the GO Consortium's Reference Genome Project is using an explicit evolutionary framework to infer annotations of proteins from a broad set of genomes from experimental annotations in a semi-automated manner. Most components in the pipeline, such as selection of sequences, building multiple sequence alignments and phylogenetic trees, retrieving experimental annotations and depositing inferred annotations, are fully automated. However, the most crucial step in our pipeline relies on software-assisted curation by an expert biologist. This curation tool, Phylogenetic Annotation and INference Tool (PAINT) helps curators to infer annotations among members of a protein family. PAINT allows curators to make precise assertions as to when functions were gained and lost during evolution and record the evidence (e.g. experimentally supported GO annotations and phylogenetic information including orthology) for those assertions. In this article, we describe how we use PAINT to infer protein function in a phylogenetic context with emphasis on its strengths, limitations and guidelines. We also discuss specific examples showing how PAINT annotations compare with those generated by other highly used homology-based methods.

Annotation

Gene Ontology Annotations