The DOI matches its Crossref record; 60 of the 60 references it cites were found in a registry or an index.
Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast
Open accessAbstract
Aneuploidy causes severe developmental defects and is a near universal feature of tumor cells. Despite its profound effects, the cellular processes affected by aneuploidy are not well characterized. Here, we examined the consequences of aneuploidy on the proteome of aneuploid budding yeast strains. We show that although protein levels largely scale with gene copy number, subunits of multi-protein complexes are notable exceptions. Posttranslational mechanisms attenuate their expression when their encoding genes are in excess. Our proteomic analyses further revealed a novel aneuploidy-associated protein expression signature characteristic of altered metabolism and redox homeostasis. Indeed aneuploid cells harbor increased levels of reactive oxygen species (ROS). Interestingly, increased protein turnover attenuates ROS levels and this novel aneuploidy-associated signature and improves the fitness of most aneuploid strains. Our results show that aneuploidy causes alterations in metabolism and redox homeostasis. Cells respond to these alterations through both transcriptional and posttranscriptional mechanisms.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Eng, J. K., McCormack, A. L., & Yates, J. R. (1994) · Journal of the American Society for Mass Spectrometry · doi:10.1016/1044-0305(94)80016-2 · Cited by 6,484
Ong, S.-E., Blagoev, B., Kratchmarova, I., Kristensen, D. B., Steen, H., Pandey, A., & Mann, M. (2002) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m200025-mcp200 · Cited by 5,574
Genomic Expression Programs in the Response of Yeast Cells to Environmental Changes
Gasch, A. P., Spellman, P. T., Kao, C. M., Carmel-Harel, O., Eisen, M. B., Storz, G., Botstein, D., & Brown, P. O. (2000) · Molecular Biology of the Cell · doi:10.1091/mbc.11.12.4241 · Cited by 4,815
Elias, J. E., & Gygi, S. P. (2007) · Nature Methods · doi:10.1038/nmeth1019 · Cited by 3,925
Self-citationModulation of oxidative stress as an anticancer strategy
Gorrini, C., Harris, I. S., & Mak, T. W. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd4002 · Cited by 3,579
ProteomeXchange provides globally coordinated proteomics data submission and dissemination
Vizcaíno, J. A., Deutsch, E. W., Wang, R., Csordas, A., Reisinger, F., Ríos, D., Dianes, J. A., Sun, Z., Farrah, T., Bandeira, N., et al. (2014) · Nature Biotechnology · doi:10.1038/nbt.2839 · Cited by 2,729
Rappsilber, J., Ishihama, Y., & Mann, M. (2003) · Analytical Chemistry · doi:10.1021/ac026117i · Cited by 2,644
Proteome survey reveals modularity of the yeast cell machinery
Gavin, A.-C., Aloy, P., Grandi, P., Krause, R., Boesche, M., Marzioch, M., Rau, C., Jensen, L. J., Bastuck, S., Dümpelfeld, B., et al. (2006) · Nature · doi:10.1038/nature04532 · Cited by 2,575
The economics of ribosome biosynthesis in yeast
Warner, J. R. (1999) · Trends in Biochemical Sciences · doi:10.1016/s0968-0004(99)01460-7 · Cited by 1,933
A tissue-specific atlas of mouse protein phosphorylation and expression
Huttlin, E. L., Jedrychowski, M. P., Elias, J. E., Goswami, T., Rad, R., Beausoleil, S. A., Villén, J., Haas, W., Sowa, M. E., & Gygi, S. P. (2010) · Cell · doi:10.1016/j.cell.2010.12.001 · Cited by 1,778
Self-citation
Cited by
On the Dependency of Cellular Protein Levels on mRNA Abundance
Liu, Y., Beyer, A., & Aebersold, R. (2016) · Cell · doi:10.1016/j.cell.2016.03.014 · Cited by 3,221
mRNAs, proteins and the emerging principles of gene expression control
Buccitelli, C., & Selbach, M. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0258-4 · Cited by 1,243
Quantitative Proteomics of the Cancer Cell Line Encyclopedia
Nusinow, D. P., Szpyt, J., Ghandi, M., Rose, C. M., McDonald, E. R., Kalocsay, M., Jané-Valbuena, J., Gelfand, E., Schweppe, D. K., Jedrychowski, M., et al. (2020) · Cell · doi:10.1016/j.cell.2019.12.023 · Cited by 957
Self-citationMulti-omic measurements of heterogeneity in HeLa cells across laboratories
Liu, Y., Mi, Y., Mueller, T., Kreibich, S., Williams, E. G., Van Drogen, A., Borel, C., Frank, M., Germain, P.-L., Bludau, I., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0037-y · Cited by 338
The Role of Aneuploidy in Cancer Evolution
Sansregret, L., & Swanton, C. (2017) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a028373 · Cited by 266
Metadata
- Authors
- Dephoure, N., Hwang, S., O'Sullivan, C., Dodgson, S. E., Gygi, S. P., Amon, A., & Torres, E. M.
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2014-07-29
- Volume
- 3
- Pages
- e03023-e03023
- ISSN
- 2050-084X (ISSN-L)
- OpenAlex
- W2081278227
- Cited by
- 263
- References
- 60
- FWCI
- 10.30
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast. https://app.cochat.ai/papers/10.7554/elife.03023
- The paper
- Dephoure, N., Hwang, S., O'Sullivan, C., Dodgson, S. E., Gygi, S. P., Amon, A., & Torres, E. M. (2014). Quantitative proteomic analysis reveals posttranslational responses to aneuploidy in yeast. eLife. https://doi.org/10.7554/elife.03023
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.