期刊
EMBO JOURNAL
卷 33, 期 6, 页码 648-664出版社
WILEY
DOI: 10.1002/embj.201387614
关键词
Cdk regulation; chromatin; machine learning; organelle; proteomics
资金
- Wellcome Trust [084229, 077707, 092076, 091020]
- FEBS Long-Term fellowship
- CRUK senior research fellowship [C28206/A14499]
- Cancer Research UK [14499] Funding Source: researchfish
Chromatin proteins mediate replication, regulate expression, and ensure integrity of the genome. So far, a comprehensive inventory of interphase chromatin has not been determined. This is largely due to its heterogeneous and dynamic composition, which makes conclusive biochemical purification difficult, if not impossible. As a fuzzy organelle, it defies classical organellar proteomics and cannot be described by a single and ultimate list of protein components. Instead, we propose a new approach that provides a quantitative assessment of a protein's probability to function in chromatin. We integrate chromatin composition over a range of different biochemical and biological conditions. This resulted in interphase chromatin probabilities for 7635 human proteins, including 1840 previously uncharacterized proteins. We demonstrate the power of our large-scale data-driven annotation during the analysis of cyclin-dependent kinase (CDK) regulation in chromatin. Quantitative protein ontologies may provide a general alternative to list-based investigations of organelles and complement Gene Ontology.
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