Cited by 492Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic NetworksProtein Tyrosine Phosphatases

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The functional landscape of the human phosphoproteome

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Ochoa, David, Jarnuczak, Andrew F., Viéitez, Cristina, Gehre, Maja, Soucheray, Margaret, Mateus, André, Kleefeldt, Askar A., Hill, Anthony, Garcia-Alonso, Luz, Stein, Frank, Krogan, Nevan J., Savitski, Mikhail M., Swaney, Danielle L., Vizcaíno, Juan A., Noh, Kyung-Min, Beltrao, Pedro·2020·Nature Biotechnology

DOI 10.1038/s41587-019-0344-3PMC PMC7100915

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Abstract

Protein phosphorylation is a key post-translational modification regulating protein function in almost all cellular processes. Although tens of thousands of phosphorylation sites have been identified in human cells, approaches to determine the functional importance of each phosphosite are lacking. Here, we manually curated 112 datasets of phospho-enriched proteins, generated from 104 different human cell types or tissues. We re-analyzed the 6,801 proteomics experiments that passed our quality control criteria, creating a reference phosphoproteome containing 119,809 human phosphosites. To prioritize functional sites, we used machine learning to identify 59 features indicative of proteomic, structural, regulatory or evolutionary relevance and integrate them into a single functional score. Our approach identifies regulatory phosphosites across different molecular mechanisms, processes and diseases, and reveals genetic susceptibilities at a genomic scale. Several regulatory phosphosites were experimentally validated, including identifying a role in neuronal differentiation for phosphosites in SMARCC2, a member of the SWI/SNF chromatin-remodeling complex.

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Self-citation

Authors: Ochoa, D., Jarnuczak, A. F., Viéitez, C., Gehre, M., Soucheray, M., Mateus, A., Kleefeldt, A. A., Hill, A., Garcia-Alonso, L., Stein, F., Krogan, N. J., Savitski, M. M., Swaney, D. L., Vizcaíno, J. A., Noh, K.-M., & Beltrao, P.
Affiliations: European Bioinformatics Institute (GB)
European Molecular Biology Laboratory (DE)
Gladstone Institutes (US)
Corresponding author: Ochoa, David
ORCID: Ochoa, David
Jarnuczak, Andrew F.
Viéitez, Cristina
Gehre, Maja
Soucheray, Margaret
Mateus, André
Kleefeldt, Askar A.
Hill, Anthony
Stein, Frank
Krogan, Nevan J.
Savitski, Mikhail M.
Swaney, Danielle L.
Vizcaíno, Juan A.
Noh, Kyung-Min
Beltrao, Pedro
Venue: Nature Biotechnology
Publisher: Springer Science and Business Media LLC
Published: 2019-12-09
Volume: 38
Issue: 3
Pages: 365-373
ISSN: 0733-222X (ISSN-L)
1087-0156
1546-1696
DOI: 10.1038/s41587-019-0344-3
PMC: PMC7100915
OpenAlex: W2994464657
Cited by: 491
References: 106
Citations by year: 2026: 83 · 2025: 85 · 2024: 80 · 2023: 74 · 2022: 83 · 2021: 54 · 2020: 25 · 2019: 6
FWCI: 16.77
Type: journal article
Language: en
Open access: green
doi.org
Licence: cc-by
www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Nature Biotechnology (publishedVersion)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: Wellcome Trust (WT101477MA, 101477, 208391/Z/17/Z, Z/17/Z, 208391)
Topics: Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Tyrosine Phosphatases
Keywords: protein phosphorylation, phosphosites, post-translational modification, machine learning feature selection, genetic susceptibility, SMARCC2, SWI/SNF chromatin remodeling, neuronal differentiation
MeSH terms: Machine Learning, Binding Sites, Cell Line, DNA-Binding Proteins, HeLa Cells, Humans, Phosphoproteins, Protein Processing, Post-Translational, Mass Spectrometry, Transcription Factors, Computational Biology, Databases, Protein, Proteomics, Neurogenesis, Data Curation

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