An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

Gene Ontology Consortium: going forward

The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

Essential role of TM V and VI for binding the C-terminal sequences of Des-Arg-kinins

In the kallikrein-kinin and renin-angiotensin systems the main receptors, B(1) and B(2) (kinin receptors) and AT(1) and AT(2) (angiotensin receptors) respectively, are seven-transmembrane domain G-protein-coupled receptors. Considering that the B(1) agonists Des-Arg(9)-BK (Arg-Pro-Pro-Gly-Phe-Ser-Pro-Phe), Lys-desArg(9)-BK or Des-Arg(10)-KD (Lys-Arg-Pro-Pro-Gly-Phe-Ser-Pro-Phe) and the AT(1) agonist (Asp-Arg-Val-Tyr-Ile-His-Pro-Phe) have the same two residues at the C-terminal region (i.e. Pro-Phe), we hypothesized that TM V and TM VI of the B(1) receptor could play an essential role in agonist binding and activity, being these regions receptor sites for binding the C-terminal sequences of Des-Arg-kinins similarly to that observed to AT(1) receptor. To investigate this hypothesis, we replaced Arg(212) for Ala at the top of the TM V and the sequence 274-282 (CPYHFFAFL) in TM VI of the rat kinin B(1) receptor by the B(2) receptor homologous sequence, 289-297 (FPFQISTFL) and subsequently analyzed the consequences of these mutations by competition binding and functional assays. Despite correct expression, observed at the mRNA and protein level by RT-PCR and confocal microscopy, respectively, no agonist binding and function was verified for the mutated receptors. Therefore, our results suggest an important role for Arg(212) in the TM V and a region of TM VI of rat B(1) receptor in the interaction with the C-terminal residues of Des-Arg-kinins, similar to that observed with AngII

PI4K2β/AP-1-based TGN-endosomal sorting regulates Wnt signaling

Endosomal membrane traffic serves crucial roles in cell physiology, signaling, and development. Sorting between endosomes and the trans-Golgi network (TGN) is regulated among other factors by the adaptor AP-1, an essential component of multicellular organisms. Membrane recruitment of AP-1 requires phosphatidylinositol 4-phosphate [PI(4)P], though the precise mechanisms and PI4 kinase isozyme (or isozymes) involved in generation of this PI(4)P pool remain unclear. The Wnt pathway is a major developmental signaling cascade and depends on endosomal sorting in Wnt-sending cells. Whether TGN/endosomal sorting modulates signaling downstream of Frizzled (Fz) receptors in Wnt-receiving cells is unknown. Here, we identify PI4-kinase type 2{beta} (PI4K2{beta}) as a regulator of TGN/endosomal sorting and Wnt signaling. PI4K2{beta} and AP-1 interact directly and are required for efficient sorting between endosomes and the TGN. Zebrafish embryos depleted of PI4K2{beta} or AP-1 lack pectoral fins due to defective Wnt signaling. Rescue experiments demonstrate requirements for PI4K2{beta}-AP-1 complex formation and PI4K2{beta}-mediated PI(4)P synthesis. Furthermore, PI4K2{beta} binds to the Fz-associated component Dishevelled (Dvl) and regulates endosomal recycling of Fz receptors and Wnt target gene expression. These data reveal an evolutionarily conserved role for PI4K2{beta} and AP-1 in coupling phosphoinositide metabolism to AP-1-mediated sorting and Wnt signaling

An expanded evaluation of protein function prediction methods shows an improvement in accuracy.

BackgroundA major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging.ResultsWe conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2.ConclusionsThe top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent