The Gene Ontology resource: enriching a GOld mine

Abstract

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

Induction of Dopaminergic Neurons for Neuronal Subtype-Specific Modeling of Psychiatric Disease Risk

“…4E ). These findings were corroborated by additional enrichment in a network of Gene Ontology Biological Processes 41,42 related to synaptic structure (e.g., “Synapse Organization” (q = 1.30 × 10 −21 in iDANs; q = 3.54 × 10 −21 in MDNs)) and neurotransmission (e.g., “Dopamine Secretion” (q = 3.16 × 10 −6 in iDANs; q = 0.0060 in MDNs)), whereas non-MDNs were enriched in processes pertaining to glial cells (e.g., “Glial Cell Differentiation”, q = 1.49 × 10 −8 ; “Myelination”, q = 1.71 × 10 −6 ) ( Fig 4F ). in total, these results support a fetal-like midbrain dopaminergic neuron identity for iDANs.…”

“…Gene-set overrepresentation analyses (GSOA) : We used clusterProfiler to perform GSOA on (i) DEGs in the dataset consisting of hiPSCs, iDANs, MDNs, and non-MDNs, and (ii) SEGs with enrichment in psychiatric disorder heritability. Tested gene sets included KEGG pathways 40 and Gene Ontology Biological Processes 41,42 (BP). We used an FDR threshold of < 0.05, and significance values are indicated throughout the text by the corresponding FDR q values.…”

ACE2-lentiviral transduction enables mouse SARS-CoV-2 infection and mapping of receptor interactions

“…The complete Molecular Signatures Database (MSigDB) v7.2 gene set collection (31,120 gene sets) (msigdb.v7.2.symbols.gmt: https://www.gsea-msigdb.org/gsea/msigdb/download_file.jsp?filePath=/msigdb/release/7.2/msigdb.v7.2.symbols.gmt) was used to run GSEAs on pre-ranked gene list for plus versus minus ACE2 at day 2 (Supplementary Table 1B), and day 6 versus day 2 (Supplementary Table 2B). Gene ontology (114, 115) and Enrichr (116, 117) web-tools were also consulted.…”

Investigating the molecular processes behind the cell-specific toxicity response to titanium dioxide nanobelts

“…Toxicity-related processes Within the two human pathway collections used), toxicity-related pathways were identified based on the enrichment of toxicity-related gene sets using the clusterProfiler R package. The gene sets were retrieved from the Gene Ontology (GO, version: release 2020-06) for the following four toxicity-related GO-terms: "apoptotic process" (GO:0006915), "inflammatory response" (GO:0006954), "cellular response to DNA damage stimulus" (GO:0006974) and "cellular response to oxidative stress" (GO:0034599) [69,70]. Associated genes were retrieved using the biomaRt package in R (version 2.42.0, Ensembl Genes 100) [71,72].…”