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A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis
Open accessAbstract
Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun) and the other supporting hypothesis-driven (targeted) proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.
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In the citing paper
“Studies in model organisms have shown that variation in mRNA and protein expression levels are often uncorrelated (5-8).”
From Impact of regulatory variation from RNA to protein (2015) · cites this paper as [7]
In the citing paper
“The advance in quantitative proteomics allows a genome-wide map of pQTL model organisms (Foss et al., 2007; Picotti et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Picotti et al. used a nearly complete map of yeast proteome and genetic variation data to identify strong genetic effects of protein abundance, and to demonstrate epistatic interactions affecting protein levels (Picotti et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Using precise MS measurement of peptides over a large number of samples, recent pQTL analyses revealed complex genetic influence on the levels of proteins in yeast (Picotti et al., 2013) and mouse (Holdt et al., 2013).”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Picotti et al., 2013
In the citing paper
“Human biology is tightly linked to proteins, and mass spectrometry-based proteomics has established a strong linkage between phenotype and protein-level biology (1, 2).”
From The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells (2022) · cites this paper as [1]
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Proteomics of lipid accumulation and DGAT inhibition in HepG2 liver carcinoma cells
Bhatt-Wessel, B. (2017) · Open Access Victoria University of Wellington | Te Herenga Waka (Figshare) · doi:10.26686/wgtn.17058194
“generated a spectral library for synthetic peptides generated for all known ORFs of the yeast genome [447].”
BackgroundIdentifying Evolutionarily Conserved Protein Complexes
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064658
Protein Complex Prediction in the Era of Systems Biology
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064659
Introduction to Protein Complex Prediction
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064652
Evaluating Protein Complex Prediction Methods
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064655
Computational Methods for Protein Complex Prediction from PPI Networks
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064654
Open Challenges in Protein Complex Prediction
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064656
Identifying Dynamic Protein Complexes
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064657
Comparison of two proteomic methods for analyses of glaucoma medication effects in vitro
Karisola, N. (2018) · Tampere University Institutional Repository (Tampere University)
Proteomic Responses to Cold Stress
Bhat, T. M., Choudhary, S., & Ramchiary, N. (2018) · Springer eBooks · doi:10.1007/978-3-030-01415-5_7
Gauthier, L., Stynen, B., Serohijos, A. W. R., & Michnick, S. W. (2019) · BioEssays · doi:10.1002/bies.201900169
Robbe, Z. L., Shi, W., Wasson, L. K., Wilczewski, C. M., Sheng, X., Hepperla, A. J., Akerberg, B. N., Pu, W. T., Cristea, I. M., Davis, I. J., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.28.466285
“Using parallel reaction monitoring mass spectrometry (PRM nLC-MS/MS) (Picotti et al. 2013; Federspiel et al. 2019), we confirmed that CHD4 interacts in vivo in mid-gestation hearts with GATA4, NKX2-5 and TBX5.”
MethodSrihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064660
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064661
Srihari, S., Yong, C. H., & Wong, L. (2017) · doi:10.1145/3064650.3064651
Faculty Opinions recommendation of Arabidopsis proteome and the mass spectral assay library.
Heazlewood, J. L. (2020) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.736963194.793572944
Metadata
- Authors
- Picotti, P., Clément-Ziza, M., Lam, H., Campbell, D. S., Schmidt, A., Deutsch, E. W., Röst, H., Sun, Z., Rinner, O., Reiter, L., Shen, Q., Michaelson, J. J., Frei, A., Alberti, S., Kusebauch, U., Wollscheid, B., Moritz, R. L., Beyer, A., & Aebersold, R.
- Affiliations
- ETH Zurich (CH)
- Hong Kong University of Science and Technology (HK)
- Institute for Systems Biology (US)
- University of Basel (CH)
- Chinese Academy of Sciences (CN)
- Biotechnologisches Zentrum (DE)
- Max Planck Institute of Molecular Cell Biology and Genetics (DE)
- University of Zurich (CH)
- Corresponding author
- Picotti, Paola
- Beyer, Andreas
- Aebersold, Ruedi
- ORCID
- Venue
- Nature
- Published
- 2013-01-20
- Volume
- 494
- Issue
- 7436
- Pages
- 266-270
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3951219
- OpenAlex
- W2065096062
- Cited by
- 318
- References
- 73
- Citations by year
- 2026: 2 · 2025: 10 · 2024: 7 · 2023: 10 · 2022: 18 · 2021: 14 · 2020: 10 · 2019: 30 · 2018: 24 · 2017: 44 · 2016: 31 · 2015: 44 · 2014: 40 · 2013: 31
- FWCI
- 21.82
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Max Planck Institute for Plasma Physics (submittedVersion)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Université du Luxembourg
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (133670, 107679)
- National Institutes of Health (n01hv28179-12-0-0)
- National Institute of Standards and Technology
- National Heart, Lung, and Blood Institute (N01 HV028179, N01-HV-28179)
- National Human Genome Research Institute (RC2HG005805)
- National Institute of General Medical Sciences (P50GM076547)
- Topics
- Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
- Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
- Keywords
- proteome reference map, protein abundance, shotgun proteomics, targeted proteomics, genetic polymorphism, protein stoichiometry, selection pressure, yeast strain
- MeSH terms
- Polymorphism, Genetic, Reference Values, Saccharomyces cerevisiae, Selection, Genetic, Mass Spectrometry, Peptide Library, Proteome, Saccharomyces cerevisiae Proteins, Quantitative Trait Loci, Proteomics
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