9 research outputs found

    The Gene Ontology knowledgebase in 2023

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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

    CD8 � T Cell Tolerance to a Tumor-associated Antigen Is Maintained at the Level of Expansion Rather than Effector Function

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    CD8 � T cell tolerance to self-proteins prevents autoimmunity but represents an obstacle to generating T cell responses to tumor-associated antigens. We have made a T cell receptor (TCR) transgenic mouse specific for a tumor antigen and crossed TCR-TG mice to transgenic mice expressing the tumor antigen in hepatocytes (gag-TG). TCRxgag mice showed no signs of autoimmunity despite persistence of high avidity transgenic CD8 � T cells in the periphery. Peripheral CD8 � T cells expressed phenotypic markers consistent with antigen encounter in vivo and had upregulated the antiapoptotic molecule Bcl-2. TCRxgag cells failed to proliferate in response to antigen but demonstrated cytolytic activity and the ability to produce interferon �. This split tolerance was accompanied by inhibition of Ca 2 � flux, ERK1/2, and Jun kinasephosphorylation, and a block in both interleukin 2 production and response to exogenous interleukin 2. The data suggest that proliferation and expression of specific effector functions characteristic of reactive cells are not necessarily linked in CD8 � T cell tolerance. Key words

    The Gene Ontology Knowledgebase in 2023

    No full text
    : The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding 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 Gene Ontology - a computational knowledge structure describing 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, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project

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