CoChat
Sign Up
PreprintCited by 22Evolution and Genetic DynamicsChromosomal and Genetic VariationsMicrotubule and mitosis dynamics

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Comparative modeling reveals the molecular determinants of aneuploidy fitness cost in a wild yeast model

Open access
Rojas, Julie, Hose, James, Dutcher, H. Auguste, Place, Michael, Wolters, John F, Hittinger, Chris Todd, Gasch, Audrey P·2024·Cell Genomics
DOI 10.1101/2024.04.09.588778PMC PMC11602619

Preprint — published as 10.1016/j.xgen.2024.100656 · Paper page

Open this paper in CoChat — free account

Abstract

Although implicated as deleterious in many organisms, aneuploidy can underlie rapid phenotypic evolution. However, aneuploidy will only be maintained if the benefit outweighs the cost, which remains incompletely understood. To quantify this cost and the molecular determinants behind it, we generated a panel of chromosome duplications in Saccharomyces cerevisiae and applied comparative modeling and molecular validation to understand aneuploidy toxicity. We show that 74-94% of the variance in aneuploid strains’ growth rates is explained by the additive cost of genes on each chromosome, measured for single-gene duplications using a genomic library, along with the deleterious contribution of snoRNAs and beneficial effects of tRNAs. Machine learning to identify properties of detrimental gene duplicates provided no support for the balance hypothesis of aneuploidy toxicity and instead identified gene length as the best predictor of toxicity. Our results present a generalized framework for the cost of aneuploidy with implications for disease biology and evolution.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/2024.04.09.588778

Cites

1 of 1 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Flagged first, then by citations

Research works printed but not linked: 131

  1. 10.1038/35066065 · DOI
  2. 10.1534/genetics.108.090878 · DOI
  3. 10.1016/j.devcel.2018.02.002 · DOI
  4. 10.1126/science.1128242 · DOI · Paper page
  5. 2023, The Dynamic Fungal Genome: Polyploidy, Aneuploidy and Copy Number Variation in Response to Stress, Annual Review of Microbiology, 77, 341, 10.1146/annurev-micro-041320-112443 · DOI · Paper page
  6. 10.1002/yea.3427 · DOI
  7. 10.7554/eLife.05462 · DOI
  8. 10.1038/s41586-018-0030-5 · DOI · Paper page
  9. 2021, Genetic variation in aneuploidy prevalence and tolerance across Saccharomyces cerevisiae lineages, Genetics, 217, iyab015, 10.1093/genetics/iyab015 · DOI
  10. 10.1038/nature10795 · DOI · Paper page
  11. 10.1371/journal.pbio.3000069 · DOI
  12. 2017, The Stress-Inducible Peroxidase TSA2 Underlies a Conditionally Beneficial Chromosomal Duplication in Saccharomyces cerevisiae, G3 Genes|Genomes|Genetics, 7, 3177, 10.1534/g3.117.300069 · DOI
  13. 10.1038/ncomms9664 · DOI
  14. 10.1038/nature14187 · DOI
  15. 10.1073/pnas.1211150109 · DOI · Paper page
  16. 2022, Chromosomal instability and aneuploidy as causes of cancer drug resistance, Trends Cancer, 8, 43, 10.1016/j.trecan.2021.09.002 · DOI
  17. 2020, Context is everything: aneuploidy in cancer, Nat Rev Genet, 21, 44, 10.1038/s41576-019-0171-x · DOI
  18. 2023, Oncogene-like addiction to aneuploidy in human cancers, Science, 0, eadg4521
  19. 2023, Chromosome 8p engineering reveals increased metastatic potential targetable by patient-specific synthetic lethality in liver cancer, Sci Adv, 9, eadh1442, 10.1126/sciadv.adh1442 · DOI
  20. 10.1016/j.devcel.2021.07.009 · DOI
  21. 10.1101/gad.345454.120 · DOI
  22. 10.7554/eLife.03023 · DOI
  23. 10.1101/gad.207407.112 · DOI
  24. 10.1126/science.1142210 · DOI · Paper page
  25. 10.1101/gad.261743.115 · DOI
  26. 2023, Consequences of trisomy syndromes – 21 and beyond, Trends in Genetics, 39, 172, 10.1016/j.tig.2022.11.004 · DOI
  27. 2020, Aneuploidy-induced proteotoxic stress can be effectively tolerated without dosage compensation, genetic mutations, or stress responses, BMC Biol, 18, 117, 10.1186/s12915-020-00852-x · DOI
  28. 10.1016/j.tig.2011.07.003 · DOI
  29. 10.1534/g3.116.029397 · DOI
  30. 10.1101/2023.06.08.544269 · DOI
  31. 2020, Down syndrome, Nat Rev Dis Primers, 6, 9, 10.1038/s41572-019-0143-7 · DOI · Paper page
  32. 10.1242/dmm.008078 · DOI
  33. 10.1186/1471-2156-10-36 · DOI
  34. 10.1128/MCB.10.10.5286 · DOI
  35. 10.1016/j.cell.2013.10.011 · DOI · Paper page
  36. 10.1016/j.cell.2018.02.037 · DOI
  37. 10.1126/science.1219580 · DOI
  38. 10.1002/bies.10023 · DOI
  39. 10.1038/nature01771 · DOI · Paper page
  40. 10.1073/pnas.1207726109 · DOI
  41. 2015, Aneuploidy triggers a TFEB-mediated lysosomal stress response, Autophagy, 11, 2383, 10.1080/15548627.2015.1110670 · DOI
  42. 10.1038/s41586-019-1187-2 · DOI
  43. 10.1080/15384101.2015.1006043 · DOI
  44. 10.7554/eLife.52063 · DOI
  45. Hill, A. & Bloom, K . Genetic Manipulation of Centromere Function. MOL. CELL. BIOL. 7, (1987). · DOI
  46. 1992, Construction of a Gal1-Regulated Yeast Cdna Expression Library and Its Application to the Identification of Genes Whose Overexpression Causes Lethality in Yeast, Genetics, 132, 665, 10.1093/genetics/132.3.665 · DOI
  47. 10.1128/MCB.10.10.5295 · DOI
  48. 10.1038/nbt.1534 · DOI
  49. 10.1145/1390156.1390161 · DOI
  50. 10.1016/S0300-9084(02)01402-5 · DOI
  51. 10.1101/2022.10.03.510608 · DOI
  52. 10.1128/MCB.21.15.5031-5040.2001 · DOI
  53. 10.1073/pnas.2014345118 · DOI
  54. 2012, Functional Analysis With a Barcoder Yeast Gene Overexpression System, G3 Genes|Genomes|Genetics, 2, 1279, 10.1534/g3.112.003400 · DOI
  55. 10.1101/gad.1362105 · DOI
  56. 10.1073/pnas.1900437116 · DOI
  57. 10.1016/j.molcel.2005.12.011 · DOI
  58. 2018, The extent of ribosome queuing in budding yeast, PLOS Computational Biology, 14, e1005951, 10.1371/journal.pcbi.1005951 · DOI
  59. 10.7554/eLife.70564 · DOI
  60. 2023, Dissecting aneuploidy phenotypes by constructing Sc2.0 chromosome VII and SCRaMbLEing synthetic disomic yeast, Cell Genomics, 3, 100364, 10.1016/j.xgen.2023.100364 · DOI
  61. Lana-Elola, E. et al. Genetic dissection of Down syndrome-associated congenital heart defects using a new mouse mapping panel. eLife 5, e11614. · DOI
  62. 10.1038/ejhg.2008.214 · DOI · Paper page
  63. 10.1371/journal.pone.0089640 · DOI
  64. 2017, Tuning the ribosome: The influence of rRNA modification on eukaryotic ribosome biogenesis and function, RNA Biology, 14, 1138, 10.1080/15476286.2016.1259781 · DOI · Paper page
  65. 2022, Translational control through ribosome heterogeneity and functional specialization, Trends in Biochemical Sciences, 47, 66, 10.1016/j.tibs.2021.07.001 · DOI · Paper page
  66. 10.1006/jmbi.1997.0942 · DOI
  67. 10.1093/nar/gkp787 · DOI · Paper page
  68. 2023, Transfer RNAs as dynamic and critical regulators of cancer progression, Nature Reviews Cancer, 23, 746, 10.1038/s41568-023-00611-4 · DOI
  69. 2019, tRNA Deregulation and Its Consequences in Cancer, Trends in Molecular Medicine, 25, 853, 10.1016/j.molmed.2019.05.011 · DOI
  70. 10.1016/j.cell.2014.08.011 · DOI
  71. 10.1016/j.cell.2016.05.046 · DOI
  72. Hu, G. , Luo, S. , Rao, H. , Cheng, H. & Gan, X . A Simple PCR-based Strategy for the Introduction of Point Mutations in the Yeast Saccharomyces cerevisiae via CRISPR/Cas9. Biochem Mol biol J 04, (2018). · DOI
  73. 10.1016/j.cub.2009.10.071 · DOI
  74. 10.1371/journal.pone.0085212 · DOI
  75. 2021, Role of SSD1 in Phenotypic Variation of Saccharomyces cerevisiae Strains Lacking DEG1-Dependent Pseudouridylation, Int J Mol Sci, 22, 8753, 10.3390/ijms22168753 · DOI
  76. 2019, SSD1 suppresses phenotypes induced by the lack of Elongator-dependent tRNA modifications, PLoS Genet, 15, e1008117, 10.1371/journal.pgen.1008117 · DOI
  77. Dutcher, H. A. , Hose, J. , Howe, H. , Rojas, J. & Gasch, A. P . Gene duplication fitness cost measurements using MoBy 1.0 plasmid library and used to compute the chromosome cost. bioRxiv (2024).
  78. 2008, A simple principle concerning the robustness of protein complex activity to changes in gene expression, BMC Systems Biology, 2, 1, 10.1186/1752-0509-2-1 · DOI
  79. 10.1016/j.tig.2008.05.005 · DOI
  80. 2019, Overdosage of Balanced Protein Complexes Reduces Proliferation Rate in Aneuploid Cells, Cell Syst, 9, 129, 10.1016/j.cels.2019.06.007 · DOI
  81. 2010, Proteomic Changes Resulting from Gene Copy Number Variations in Cancer Cells, PLOS Genetics, 6, e1001090, 10.1371/journal.pgen.1001090 · DOI
  82. 10.1186/gb-2013-14-11-r133 · DOI
  83. 10.1038/s41467-017-01422-6 · DOI · Paper page
  84. 10.1038/msb.2012.40 · DOI · Paper page
  85. 10.1016/j.cell.2016.09.015 · DOI
  86. 2023, A3D Model Organism Database (A3D-MODB): a database for proteome aggregation predictions in model organisms, Nucleic Acids Res, 52, D360
  87. 10.1101/gad.327494.119 · DOI · Paper page
  88. 2021, Reversible protein aggregation as cytoprotective mechanism against heat stress, Curr Genet, 67, 849, 10.1007/s00294-021-01191-2 · DOI
  89. 10.1101/gr.146662.112 · DOI
  90. 10.1073/pnas.0635171100 · DOI · Paper page
  91. 2004, Gene Expression Analyzed by High-resolution State Array Analysis and Quantitative Proteomics: Response of Yeast to Mating Pheromone *, Molecular & Cellular Proteomics, 3, 478, 10.1074/mcp.M300129-MCP200 · DOI
  92. 10.1126/science.1168978 · DOI · Paper page
  93. 10.1371/journal.pbio.1000238 · DOI · Paper page
  94. 10.1016/j.molbiopara.2011.05.003 · DOI
  95. 10.1038/s41598-017-17618-1 · DOI
  96. 10.1039/C4MB00462K · DOI
  97. 10.1038/nature09322 · DOI
  98. 10.1146/annurev.ge.26.120192.000333 · DOI · Paper page
  99. 10.1093/nar/gkq196 · DOI
  100. 10.1038/nsmb.1554 · DOI
  101. 10.1101/gad.287474.116 · DOI
  102. 10.1016/j.cell.2010.08.038 · DOI
  103. 2023, Gene-by-environment interactions influence the fitness cost of gene copy-number variation in yeast, G3 Genes|Genomes|Genetics, 13, jkad159, 10.1093/g3journal/jkad159 · DOI
  104. 10.1101/gr.215087.116 · DOI
  105. Walker, B. J. et al. Pilon: An integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, (2014). · DOI
  106. 10.1186/gb-2004-5-2-r12 · DOI · Paper page
  107. 2019, BUSCO: Assessing Genome Assembly and Annotation Completeness, Methods Mol Biol, 1962, 227, 10.1007/978-1-4939-9173-0_14 · DOI
  108. 10.1186/s13059-020-02134-9 · DOI · Paper page
  109. 2021, Liftoff: accurate mapping of gene annotations, Bioinformatics, 37, 1639, 10.1093/bioinformatics/btaa1016 · DOI
  110. 10.1093/nar/gkac136 · DOI
  111. 10.1038/nbt.1855 · DOI · Paper page
  112. 10.1007/978-1-4939-2269-7_23 · DOI
  113. 10.1186/gb-2010-11-3-r25 · DOI · Paper page
  114. 10.1093/bioinformatics/btp616 · DOI · Paper page
  115. 10.2307/2346101 · DOI
  116. 10.1093/nar/gkab408 · DOI
  117. 10.1002/PRO.3978 · DOI · Paper page
  118. 2022, The STRING database in 2023: protein–protein association networks and functional enrichment analyses for any sequenced genome of interest, Nucleic Acids Res, 51, D638
  119. 10.1093/nar/gkn1005 · DOI
  120. 10.1093/nar/gkr1029 · DOI
  121. 10.1093/NAR/GKAC1052 · DOI · Paper page
  122. 10.4161/fly.19695 · DOI · Paper page
  123. 10.1093/nar/gkaa931 · DOI
  124. 10.1534/genetics.104.036871 · DOI · Paper page
  125. 10.1038/75556 · DOI · Paper page
  126. 10.1093/genetics/iyad031 · DOI
  127. 10.1371/journal.pbio.0060184 · DOI · Paper page
  128. 10.1093/nar/gkz347 · DOI
  129. 2023, GSEApy: a comprehensive package for performing gene set enrichment analysis in Python, Bioinformatics, 39, btac757, 10.1093/bioinformatics/btac757 · DOI
  130. 10.1016/j.cell.2009.02.044 · DOI
  131. 10.1524/auto.2011.0951 · DOI

Metadata

Authors
Rojas, J., Hose, J., Dutcher, H. A., Place, M., Wolters, J. F., Hittinger, C. T., & Gasch, A. P.
Affiliations
University of Wisconsin–Madison (US)
Corresponding author
Gasch, Audrey P
ORCID
Venue
Cell Genomics
Publisher
openRxiv
Published
2024-04-13
Volume
4
Issue
10
Pages
100656-100656
ISSN
2666-979X (ISSN-L)
DOI
10.1101/2024.04.09.588778
PMC
PMC11602619
OpenAlex
W4402741295
Cited by
22
References
1
Citations by year
2026: 11 · 2025: 4 · 2024: 7
FWCI
5.84
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Cell Genomics (publishedVersion, cc-by-nc-nd)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc)
  • SSRN Electronic Journal (acceptedVersion)
  • PubMed Central (publishedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
  • OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
  • PubMed Central (submittedVersion, cc-by-nc)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • National Science Foundation (DE-SC0018409, 2110403)
  • U.S. Department of Energy (DESC0018409)
  • U.S. Department of Agriculture (7005101)
  • Wisconsin Alumni Research Foundation
  • National Institutes of Health
  • National Institute of Food and Agriculture (DE-SC0018409, 7005101)
  • Office of Science (DESC0018409, DE\u2013SC0018409)
  • Great Lakes Bioenergy Research Center (DE-SC0018409)
  • National Human Genome Research Institute (T32HG002760)
  • National Cancer Institute (R01CA229532)
  • National Institute of General Medical Sciences (T32GM007133, R01GM147271, R01GM148975)
  • Division of Graduate Education
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Microtubule and mitosis dynamics
Keywords
aneuploidy, fitness cost, chromosome duplication, Saccharomyces cerevisiae, gene dosage, small nucleolar RNA, tRNA, gene length, growth rate, phenotypic evolution, homology modeling

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