CoChat
Sign Up
Cited by 298Evolution and Genetic DynamicsRNA and protein synthesis mechanismsFungal and yeast genetics research

Synonymous mutations in representative yeast genes are mostly strongly non-neutral

Open access
Shen, Xukang, Song, Siliang, Li, Chuan, Zhang, Jianzhi·2022·Nature
DOI 10.1038/s41586-022-04823-wPMC PMC9650438
Open this paper in CoChat — free account

Abstract

Synonymous mutations in protein-coding genes do not alter protein sequences and are thus generally presumed to be neutral or nearly neutral 1-5. Here, to experimentally verify this presumption, we constructed 8,341 yeast mutants each carrying a synonymous, nonsynonymous or nonsense mutation in one of 21 endogenous genes with diverse functions and expression levels and measured their fitness relative to the wild type in a rich medium. Three-quarters of synonymous mutations resulted in a significant reduction in fitness, and the distribution of fitness effects was overall similar-albeit nonidentical-between synonymous and nonsynonymous mutations. Both synonymous and nonsynonymous mutations frequently disturbed the level of mRNA expression of the mutated gene, and the extent of the disturbance partially predicted the fitness effect. Investigations in additional environments revealed greater across-environment fitness variations for nonsynonymous mutants than for synonymous mutants despite their similar fitness distributions in each environment, suggesting that a smaller proportion of nonsynonymous mutants than synonymous mutants are always non-deleterious in a changing environment to permit fixation, potentially explaining the common observation of substantially lower nonsynonymous than synonymous substitution rates. The strong non-neutrality of most synonymous mutations, if it holds true for other genes and in other organisms, would require re-examination of numerous biological conclusions about mutation, selection, effective population size, divergence time and disease mechanisms that rely on the assumption that synoymous mutations are neutral.

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 · 10.1038/s41586-022-04823-w

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

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

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • There were only three significant gene-level cis-CDS pQTLs in the synonymous collapsing model.

    “Moreover, there were only three significant gene-level cis-CDS pQTLs in the synonymous (syn) collapsing model19,20 (full definitions of collapsing models can be found in Extended Data Table 1).”

    From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [19]

    The Extended Data passages discuss effects of synonymous mutations on yeast fitness and mRNA levels, not gene-level cis-CDS pQTLs. Searches for “cis-CDS pQTLs,” “synonymous collapsing model,” and “pQTL” found no passage reporting three significant associations. (LLM, conf=0.76)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 55

  1. [1]Kimura M Genetic variability maintained in a finite population due to mutational production of neutral and nearly neutral isoalleles. Genet Res 11, 247– 269 (1968). 5713805
  2. [2]King JL & Jukes TH Non-Darwinian evolution. Science 164, 788– 798 (1969). 5767777
  3. [3]Nei M & Kumar S Molecular Evolution and Phylogenetics (Oxford University Press, 2000).
  4. [6]Hershberg R & Petrov DA Selection on codon bias. Annu Rev Genet 42, 287– 299 (2008). 18983258
  5. [7]Chamary JV, Parmley JL & Hurst LD Hearing silence: non-neutral evolution at synonymous sites in mammals. Nat Rev Genet 7, 98– 108 (2006). 16418745
  6. [8]Plotkin JB & Kudla G Synonymous but not the same: the causes and consequences of codon bias. Nat Rev Genet 12, 32– 42 (2011). 21102527 PMC3074964
  7. [9]Stergachis AB Exonic transcription factor binding directs codon choice and affects protein evolution. Science 342, 1367– 1372 (2013). 24337295 PMC3967546
  8. [10]Zhou Z Codon usage is an important determinant of gene expression levels largely through its effects on transcription. Proc Natl Acad Sci U S A 113, E6117– E6125 (2016). 27671647 PMC5068308
  9. [11]Park C, Chen X, Yang JR & Zhang J Differential requirements for mRNA folding partially explain why highly expressed proteins evolve slowly. Proc Natl Acad Sci U S A 110, E678– E686 (2013). 23382244 PMC3581962
  10. [13]Chen S Codon-resolution analysis reveals a direct and context-dependent impact of individual synonymous mutations on mRNA level. Mol Biol Evol 34, 2944– 2958 (2017). 28961875 PMC5850819
  11. [14]Kudla G, Murray AW, Tollervey D & Plotkin JB Coding-sequence determinants of gene expression in Escherichia coli. Science 324, 255– 258 (2009). 19359587 PMC3902468
  12. [15]Qian W, Yang JR, Pearson NM, Maclean C & Zhang J Balanced codon usage optimizes eukaryotic translational efficiency. PLOS Genet 8, e1002603 (2012). 22479199 PMC3315465
  13. [16]Frumkin I Codon usage of highly expressed genes affects proteome-wide translation efficiency. Proc Natl Acad Sci U S A 115, E4940– E4949 (2018). 29735666 PMC6003480
  14. [17]Akashi H Synonymous codon usage in Drosophila melanogaster: natural selection and translational accuracy. Genetics 136, 927– 935 (1994). 8005445 PMC1205897
  15. [18]Sun M & Zhang J Preferred synonymous codons are translated more accurately: Proteomic evidence, among-species variation, and mechanistic basis. bioRxiv doi: 10.1101/2022.02.22.481448 (2022). PMC9258949 35857447 · DOI
  16. [19]Buhr F Synonymous codons direct cotranslational folding toward different protein conformations. Mol Cell 61, 341– 351 (2016). 26849192 PMC4745992
  17. [20]Walsh IM, Bowman MA, Soto Santarriaga IF, Rodriguez A & Clark PL Synonymous codon substitutions perturb cotranslational protein folding in vivo and impair cell fitness. Proc Natl Acad Sci U S A 117, 3528– 3534 (2020). 32015130 PMC7035613
  18. [21]Gilissen C, Hoischen A, Brunner HG & Veltman JA Disease gene identification strategies for exome sequencing. Eur J Hum Genet 20, 490– 497 (2012). 22258526 PMC3330229
  19. [22]Agashe D, Martinez-Gomez NC, Drummond DA & Marx CJ Good codons, bad transcript: large reductions in gene expression and fitness arising from synonymous mutations in a key enzyme. Mol Biol Evol 30, 549– 560 (2013). 23223712 PMC3563975
  20. [23]Kristofich J Synonymous mutations make dramatic contributions to fitness when growth is limited by a weak-link enzyme. PLOS Genet 14, e1007615 (2018). 30148850 PMC6128649
  21. [24]Lebeuf-Taylor E, McCloskey N, Bailey SF, Hinz A & Kassen R The distribution of fitness effects among synonymous mutations in a gene under directional selection. eLife 8, e45952 (2019). 31322500 PMC6692132
  22. [25]Lind PA, Berg OG & Andersson DI Mutational robustness of ribosomal protein genes. Science 330, 825– 827 (2010). 21051637
  23. [26]Sharon E Functional genetic variants revealed by massively parallel precise genome editing. Cell 175, 544– 557 (2018). 30245013 PMC6563827
  24. [27]She R & Jarosz DF Mapping causal variants with single-nucleotide resolution reveals biochemical drivers of phenotypic change. Cell 172, 478– 490 (2018). 29373829 PMC5788306
  25. [28]Qian W, Ma D, Xiao C, Wang Z & Zhang J The genomic landscape and evolutionary resolution of antagonistic pleiotropy in yeast. Cell Rep 2, 1399– 1410 (2012). 23103169 PMC3513580
  26. [29]Li C, Qian W, Maclean M & Zhang J The fitness landscape of a tRNA gene. Science 352, 837– 840 (2016). 27080104 PMC4894649
  27. [30]Chen P & Zhang J Asexual experimental evolution of yeast does not curtail transposable elements. Mol Biol Evol 38, 2831– 2842 (2021). 33720342 PMC8233515
  28. [31]Keren L Massively parallel interrogation of the effects of gene expression levels on fitness. Cell 166, 1282– 1294 (2016). 27545349
  29. [32]Chang YF, Imam JS & Wilkinson MF The nonsense-mediated decay RNA surveillance pathway. Annu Rev Biochem 76, 51– 74 (2007). 17352659
  30. [33]Monteiro PT YEASTRACT+: a portal for cross-species comparative genomics of transcription regulation in yeasts. Nucleic Acids Res 48, D642– D649 (2020). 31586406 PMC6943032
  31. [35]Radhakrishnan A The DEAD-Box protein Dhh1p couples mRNA decay and translation by monitoring codon optimality. Cell 167, 122– 132 (2016). 27641505 PMC5635654
  32. [36]Yang JR, Chen X & Zhang J Codon-by-codon modulation of translational speed and accuracy via mRNA folding. PLOS Biol 12, e1001910 (2014). 25051069 PMC4106722
  33. [37]Faure G, Ogurtsov AY, Shabalina SA & Koonin EV Role of mRNA structure in the control of protein folding. Nucleic Acids Res 44, 10898– 10911 (2016). 27466388 PMC5159526
  34. [38]Goncalves P, Valerio E, Correia C, de Almeida JM & Sampaio JP Evidence for divergent evolution of growth temperature preference in sympatric Saccharomyces species. PLOS One 6, e20739 (2011). 21674061 PMC3107239
  35. [39]Kimura M The Neutral Theory of Molecular Evolution (Cambridge University Press, 1983).
  36. [40]Lewontin RC & Cohen D On population growth in a randomly varying environment. Proc Natl Acad Sci U S A 62, 1056– 1060 (1969). 5256406 PMC223613
  37. [41]Gillespie JH Natural selection for within-generation variance in offspring number II. Discrite haploid models. Genetics 81, 403– 413 (1975). 1205132 PMC1213408
  38. [42]Kimura M & Ohta T The average number of generations until fixation of a mutant gene in a finite population. Genetics 61, 763– 771 (1969). 17248440 PMC1212239
  39. [43]Flynn JM Comprehensive fitness maps of Hsp90 show widespread environmental dependence. eLife 9, e53810 (2020). 32129763 PMC7069724
  40. [44]Dandage R Differential strengths of molecular determinants guide environment specific mutational fates. PLOS Genet 14, e1007419 (2018). 29813059 PMC5993328
  41. [45]Chen P & Zhang J Antagonistic pleiotropy conceals molecular adaptations in changing environments. Nat Ecol Evol 4, 461– 469 (2020). 32042119 PMC7058517
  42. [46]Azizoglu A, Brent R & Rudolf F A precisely adjustable, variation-suppressed eukaryotic transcriptional controller to enable genetic discovery. eLife 10, e69549 (2021). 34342575 PMC8421071
  43. [47]Natsume T & Kanemaki MT Conditional degrons for controlling protein expression at the protein level. Annu Rev Genet 51, 83– 102 (2017). 29178817
  44. [48]Zhang J & Yang JR Determinants of the rate of protein sequence evolution. Nat Rev Genet 16, 409– 420 (2015). 26055156 PMC4523088
  45. [49]Wu Z Expression level is a major modifier of the fitness landscape of a protein coding gene. Nat Ecol Evol 6, 103– 115 (2022). 34795386
  46. [50]Sauna ZE & Kimchi-Sarfaty C Understanding the contribution of synonymous mutations to human disease. Nat Rev Genet 12, 683– 691 (2011). 21878961
  47. [51]Lee TI & Young RA Transcriptional regulation and its misregulation in disease. Cell 152, 1237– 1251 (2013). 23498934 PMC3640494
  48. [52]Chou HJ, Donnard E, Gustafsson HT, Garber M & Rando OJ Transcriptome-wide analysis of roles for tRNA modifications in translational regulation. Mol Cell 68, 978– 992 (2017). 29198561 PMC5728682
  49. [53]Laughery MF New vectors for simple and streamlined CRISPR-Cas9 genome editing in Saccharomyces cerevisiae. Yeast 32, 711– 720 (2015). 26305040 PMC4715497
  50. [54]Warringer J, Ericson E, Fernandez L, Nerman O & Blomberg A High-resolution yeast phenomics resolves different physiological features in the saline response. Proc Natl Acad Sci U S A 100, 15724– 15729 (2003). 14676322 PMC307635
  51. [55]Honlinger A Tom7 modulates the dynamics of the mitochondrial outer membrane translocase and plays a pathway-related role in protein import. EMBO J 15, 2125– 2137 (1996). 8641278 PMC450135
  52. [56]Potapov V & Ong JL Examining sources of error in PCR by single-molecule sequencing. PLOS One 12, e0169774 (2017). 28060945 PMC5218489
  53. [57]Stanke M & Morgenstern B AUGUSTUS: a web server for gene prediction in eukaryotes that allows user-defined constraints. Nucleic Acids Res 33, W465– W467 (2005). 15980513 PMC1160219
  54. [58]Ranwez V, Douzery EJP, Cambon C, Chantret N & Delsuc F MACSE v2: Toolkit for the alignment of coding sequences accounting for frameshifts and stop codons. Mol Biol Evol 35, 2582– 2584 (2018). 30165589 PMC6188553
  55. [60]Zhang J & He X Significant impact of protein dispensability on the instantaneous rate of protein evolution. Mol Biol Evol 22, 1147– 1155 (2005). 15689524

Cited by

Sorted by citations

Authors
Shen, X., Song, S., Li, C., & Zhang, J.
Affiliations
  • University of Michigan (US)
  • Microsoft (United States) (US)
Corresponding author
Zhang, Jianzhi
ORCID
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2022-06-08
Volume
606
Issue
7915
Pages
725-731
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
DOI
10.1038/s41586-022-04823-w
PMC
PMC9650438
OpenAlex
W4281755657
Cited by
298
References
2
Citations by year
2026: 29 · 2025: 52 · 2024: 88 · 2023: 92 · 2022: 37
FWCI
44.04
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
National Institute of General Medical Sciences (R35GM139484)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Fungal and yeast genetics research
Keywords
synonymous mutations, non-synonymous mutations, nonsense mutation, yeast mutants, mRNA levels, substitution rate, molecular evolution
MeSH terms
Silent Mutation, Amino Acid Sequence, Genes, Fungal, RNA, Fungal, RNA, Messenger, Saccharomyces cerevisiae, Selection, Genetic, Codon, Nonsense, Evolution, Molecular, Saccharomyces cerevisiae Proteins, Genetic Fitness, Mutation Rate

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