Evidence map›Paper›PMID 35574625›Full record

ArticleMolecular systems biology2022

The impact of genomic variation on protein phosphorylation states and regulatory networks.

Jan Grossbach, Ludovic Gillet, Mathieu Clément-Ziza, Corinna L Schmalohr, Olga T Schubert, Maximilian Schütter, Julia S P Mawer, Christopher A Barnes, Isabell Bludau, Matthias Weith and 4 more

Open access · goldAbstract read
In one paragraph

Article in Molecular systems biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.8field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Article
  3. Analysis of Limited Proteolysis-Coupled Mass Spectrometry Data.Molecular & cellular proteomics : MCP · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Species-wide quantitative transcriptomes and proteomes reveal distinct genetic control of gene expression variation in yeast.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  8. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 7 institutions in 4 countries.

Jan Grossbach *Excellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.ORCID 0000-0002-9394-5665
Ludovic Gillet *Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.ORCID 0000-0002-1001-3265
Mathieu Clément-Ziza *Center for Molecular Medicine Cologne (CMMC), Medical Faculty, University of Cologne, Cologne, Germany.
Corinna L SchmalohrExcellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.
Olga T SchubertDepartment of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
Maximilian SchütterMax Planck Institute for Biology of Ageing, Cologne, Germany.
Julia S P MawerMax Planck Institute for Biology of Ageing, Cologne, Germany.
Christopher A BarnesNovo Nordisk Research Center Seattle, Inc., Seattle, WA, USA.ORCID 0000-0003-2312-7082
Isabell BludauDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
Matthias WeithExcellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.
Peter TessarzExcellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.ORCID 0000-0002-6953-9835
Martin GraefExcellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.
Ruedi AebersoldDepartment of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.ORCID 0000-0002-9576-3267
Andreas BeyerExcellence Cluster on Cellular Stress Responses in Aging Associated Diseases, University of Cologne, Cologne, Germany.ORCID 0000-0002-3891-2123
University of Cologne · DEETH Zurich · CHMax Planck Institute for Biology of Ageing · DENovo Nordisk (United States) · USTH Köln - University of Applied Sciences · DEUniversity of California, Los Angeles · USUniversity of Zurich · CH

Funding

European Research Council 670821
6 · The paper itself

Abstract

Genomic variation impacts on cellular networks by affecting the abundance (e.g., protein levels) and the functional states (e.g., protein phosphorylation) of their components. Previous work has focused on the former, while in this context, the functional states of proteins have largely remained neglected. Here, we generated high-quality transcriptome, proteome, and phosphoproteome data for a panel of 112 genomically well-defined yeast strains. Genetic effects on transcripts were generally transmitted to the protein layer, but specific gene groups, such as ribosomal proteins, showed diverging effects on protein levels compared with RNA levels. Phosphorylation states proved crucial to unravel genetic effects on signaling networks. Correspondingly, genetic variants that cause phosphorylation changes were mostly different from those causing abundance changes in the respective proteins. Underscoring their relevance for cell physiology, phosphorylation traits were more strongly correlated with cell physiological traits such as chemical compound resistance or cell morphology, compared with transcript or protein abundance. This study demonstrates how molecular networks mediate the effects of genomic variants to cellular traits and highlights the particular importance of protein phosphorylation.

Indexed as

GenomeGenomicsPhosphorylationProteomeSaccharomyces cerevisiaeProteomebudding yeastmulti-omics genetic effectsphosphorylationQTLsystems genetics

Identifiers

PMID35574625
PMCPMC9109056
OpenAlexW4280524101

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.