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The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO—a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations—evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)—mechanistic models of molecular “pathways” (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Understanding the protein interaction and functional signalling networks that define a cells’ endogenous environment is key to understanding the internal mechanics of cellular homeostasis, development of disease, treatment, and drug resistance. The use of controlled experimental models allow the accurate analysis of the consequences of a single perturbation to a protein network, with the aim of characterizing the role of that protein within the wider cellular environment. Presented here are four different models for controlled perturbation of a cells’ signalling network, centred on proteins involved in the canonical Wnt signalling pathway in a colorectal cancer model. CRISPR Cas9 was utilized in tandem with lentiviral transduction of the F-box protein TIR-1, in an attempt to create a CRC-derived cell line with an inducible degration mechanism of Dnmt1, which would facilitate study of the cell signalling and functional consequences of Dnmt1. Although TIR-1 was successfully inserted and expressed by the cells, issues with Cas9 guide specificity prevented the integration of an inducible degradation tag into Dnmt1. An alternative method of Dnmt1 knockdown is utilised to investigate the changes to the nuclear-enriched proteome. 5-Azacitidine, a nucleoside analog able to trap and induce DNA-repair mediated degradation of Dnmt1, was utilized to degrade the protein over two time points. Nuclear-enriched proteomics analysis indicated that Dnmt1 degradation by this method resulted in the reduction in protein abundance of its interaction partner Uhrf1. Further analysis suggested that loss of Dnmt1 protein abundance on its own is not sufficient to result in Uhrf1 protein abundance decrease, therefore 5-Azacitidine treatment or the endogenous cellular mechanism of Dnmt1 degradation may result in Uhrf1 protein loss. Nuclear-enriched proteomics analysis was used to investigate the changes to the functional proteome of a well characterized and frequently researched hypomorphic cell line, HCT116-Dnmt1∆3-5. Although this cell line is a well studied model of investigation for genomic methylation changes in the presence of minimal Dnmt1 protein levels, this is the first proteomic characterization of this model. Results indicate that key markers of the epithelial to mesenchymal transition process are dysregulated within this cell line, and these changes could not be rescued upon the reintroduction of the wild type Dnmt1 protein in these cells. In addition changes in the cellular localization of Dnmt1 and its interaction partner Beta-Catenin were evident, this suggests that the loss of exons 3 to 5 in this protein results in functional changes that impact the cellular proteome, and interaction partners of this crucial DNA methyltransferase. Finally, the functional proteome of GSK3β, a protein that plays a key role in the canonical Wnt signalling destruction complex and a promiscuous kinase, is investigated in a novel CRC knockout cell line. Findings show that in a constituatively Wnt activated cell model, loss of GSK3β does not impact levels of its interactors in the Wnt signalling cascade, however changes within the wider cellular proteome were present. A key finding is dysregulation of proteins involved in desmosomes, specialized cell-cell adhesion junctions, changes in protein abundance of these junctional proteins resulted in weaken cell-cell adhesion capability of the cells. Therefore, indicates a role for GSK3β in cell-cell junction strength and potentially in processes related to metastatic spread of cancerous cells.