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

Journal Article · · Database
 [1];  [2];  [3];  [4];  [3]
  1. Swiss-Prot Group, Geneva (Switzerland)
  2. Centre Medical Universitaire, Geneva (Switzerland). SIB Swiss Inst. of Bioinformatics. CALIPHO group
  3. Univ. of Southern California, Los Angeles, CA (United States). Keck School of Medicine of USC. Dept. of Preventive Medicine. Division of Bioinformatics
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Genomics Division

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.

Research Organization:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Grant/Contract Number:
AC02-05CH11231
OSTI ID:
1625307
Journal Information:
Database, Vol. 2016; ISSN 1758-0463
Publisher:
Oxford University PressCopyright Statement
Country of Publication:
United States
Language:
English

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Cited By (4)

Exploring autophagy with Gene Ontology journal February 2018
Rapamycin- and starvation-induced autophagy are associated with miRNA dysregulation in A549 cells journal March 2019
Systematic Identification and Classification of β-Lactamases Based on Sequence Similarity Criteria: β-Lactamase Annotation journal January 2018
The Gene Ontology Resource: 20 years and still GOing strong journal November 2018