Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Evidence of non-random mutation rates suggests an evolutionary risk management strategy


A central tenet in evolutionary theory is that mutations occur randomly with respect to their value to an organism; selection then governs whether they are fixed in a population. This principle has been challenged by long-standing theoretical models predicting that selection could modulate the rate of mutation itself1,2. However, our understanding of how the mutation rate varies between different sites within a genome has been hindered by technical difficulties in measuring it. Here we present a study that overcomes previous limitations by combining phylogenetic and population genetic techniques. Upon comparing 34 Escherichia coli genomes, we observe that the neutral mutation rate varies by more than an order of magnitude across 2,659 genes, with mutational hot and cold spots spanning several kilobases. Importantly, the variation is not random: we detect a lower rate in highly expressed genes and in those undergoing stronger purifying selection. Our observations suggest that the mutation rate has been evolutionarily optimized to reduce the risk of deleterious mutations. Current knowledge of factors influencing the mutation rate—including transcription-coupled repair and context-dependent mutagenesis—do not explain these observations, indicating that additional mechanisms must be involved. The findings have important implications for our understanding of evolution and the control of mutations.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Synonymous diversity along the E. coli genome is heterogeneous.
Figure 2: Selective and non-selective factors have only small effects on the variation
Figure 3: Variation in the mutation rate shows functional dependence.

Similar content being viewed by others


  1. Kimura, M. On the evolutionary adjustment of spontaneous mutation rates. Genet. Res. 9, 23–24 (1967)

    Article  ADS  Google Scholar 

  2. Levins, R. Theory of fitness in a heterogeneous environment. VI. The adaptive significance of mutation. Genetics 56, 163–178 (1967)

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Moxon, E. R., Rainey, P. B., Nowak, M. A. & Lenski, R. E. Adaptive evolution of highly mutable loci in pathogenic bacteria. Curr. Biol. 4, 24–33 (1994)

    Article  CAS  Google Scholar 

  4. Sniegowski, P. D., Gerrish, P. J., Johnson, T. & Shaver, A. The evolution of mutation rates: separating causes from consequences. BioEssays 22, 1057–1066 (2000)

    Article  CAS  Google Scholar 

  5. Tenaillon, O., Taddei, F., Radman, M. & Matic, I. Second-order selection in bacterial evolution: selection acting on mutation and recombination rates in the course of adaptation. Res. Microbiol. 152, 11–16 (2001)

    Article  CAS  Google Scholar 

  6. Pal, C., Macia, M. D., Oliver, A., Schachar, I. & Buckling, A. Coevolution with viruses drives the evolution of bacterial mutation rates. Nature 450, 1079–1081 (2007)

    Article  ADS  CAS  Google Scholar 

  7. Hodgkinson, A., Ladoukakis, E. & Eyre-Walker, A. Cryptic variation in the human mutation rate. PLoS Biol. 7, e1000027 (2009)

    Article  Google Scholar 

  8. McVean, G. T. & Hurst, L. D. Evidence for a selectively favourable reduction in the mutation rate of the X chromosome. Nature 386, 388–392 (1997)

    Article  ADS  CAS  Google Scholar 

  9. Chuang, J. H. & Li, H. Functional bias and spatial organization of genes in mutational hot and cold regions in the human genome. PLoS Biol. 2, E29 (2004)

    Article  Google Scholar 

  10. Braverman, J. M., Hudson, R. R., Kaplan, N. L., Langley, C. H. & Stephan, W. The hitchhiking effect on the site frequency spectrum of DNA polymorphisms. Genetics 140, 783–796 (1995)

    CAS  PubMed  PubMed Central  Google Scholar 

  11. O’Fallon, B. D. A method to correct for the effects of purifying selection on genealogical inference. Mol. Biol. Evol. 27, 2406–2416 (2010)

    Article  Google Scholar 

  12. Bustamante, C. D., Nielsen, R. & Hartl, D. L. Maximum likelihood and Bayesian methods for estimating the distribution of selective effects among classes of mutations using DNA polymorphism data. Theor. Popul. Biol. 63, 91–103 (2003)

    Article  Google Scholar 

  13. Drummond, D. A. & Wilke, C. O. Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution. Cell 134, 341–352 (2008)

    Article  CAS  Google Scholar 

  14. McVean, G. A. & Charlesworth, B. A. A population genetic model for the evolution of synonymous codon usage: patterns and predictions. Genet. Res. 74, 145–158 (1999)

    Article  Google Scholar 

  15. Hartl, D. L., Moriyama, E. N. & Sawyer, S. A. Selection intensity for codon bias. Genetics 138, 227–234 (1994)

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Eyre-Walker, A. & Bulmer, M. Reduced synonymous substitution rate at the start of enterobacterial genes. Nucleic Acids Res. 21, 4599–4603 (1993)

    Article  CAS  Google Scholar 

  17. Kudla, G., Murray, A. W., Tollervey, D. & Plotkin, J. B. Coding-sequence determinants of gene expression in Escherichia coli. Science 324, 255–258 (2009)

    Article  ADS  CAS  Google Scholar 

  18. Andolfatto, P. Adaptive hitchhiking effects on genome variability. Curr. Opin. Genet. Dev. 11, 635–641 (2001)

    Article  CAS  Google Scholar 

  19. Touchon, M. et al. Organised genome dynamics in the Escherichia coli species results in highly diverse adaptive paths. PLoS Genet. 5, e1000344 (2009)

    Article  Google Scholar 

  20. Baba, T. et al. Construction of Escherichia coli K-12 in-frame, single-gene knockout mutants: the Keio collection. Mol. Systems Biol. 2, 0008, 10.1038/msb4100050 (2006)

    Article  CAS  Google Scholar 

  21. Eyre-Walker, A. & Bulmer, M. Synonymous substitution rates in enterobacteria. Genetics 140, 1407–1412 (1995)

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Ochman, H. Neutral mutations and neutral substitutions in bacterial genomes. Mol. Biol. Evol. 20, 2091–2096 (2003)

    Article  CAS  Google Scholar 

  23. Beletskii, A. & Bhagwat, A. S. Transcription-induced mutations: increase in C to T mutations in the nontranscribed strand during transcription in Escherichia coli. Proc. Natl Acad. Sci. USA 93, 13919–13924 (1996)

    Article  ADS  CAS  Google Scholar 

  24. Klapacz, J. & Bhagwat, A. S. Transcription-dependent increase in multiple classes of base substitution mutations in Escherichia coli. J. Bacteriol. 184, 6866–6872 (2002)

    Article  CAS  Google Scholar 

  25. Francino, M. P., Chao, L., Riley, M. A. & Ochman, H. Asymmetries generated by transcription-coupled repair in enterobacterial genes. Science 272, 107–109 (1996)

    Article  ADS  CAS  Google Scholar 

  26. Wagner, A. Risk management in biological evolution. J. Theor. Biol. 225, 45–57 (2003)

    Article  MathSciNet  Google Scholar 

  27. Tu, Y., Tornaletti, S. & Pfeifer, G. P. DNA repair domains within a human gene: selective repair of sequences near the transcription initiation site. EMBO J. 15, 675–683 (1996)

    Article  CAS  Google Scholar 

  28. Hoege, C., Pfander, B., Moldovan, G. L., Pyrowolakis, G. & Jentsch, S. RAD6-dependent DNA repair is linked to modification of PCNA by ubiquitin and SUMO. Nature 419, 135–141 (2002)

    Article  ADS  CAS  Google Scholar 

  29. Pleasance, E. D. et al. A comprehensive catalogue of somatic mutations from a human cancer genome. Nature 463, 191–196 (2010)

    Article  ADS  CAS  Google Scholar 

  30. Lee, W. et al. The mutation spectrum revealed by paired genome sequences from a lung cancer patient. Nature 465, 473–477 (2010)

    Article  ADS  CAS  Google Scholar 

Download references


We thank M. Ackermann, S. Brenner, G. Dougan, A. Eyre-Walker, N. Goldman, B. Lenhard, J. Marioni, J. Parkhill, O. Tenaillon, C. Tyler-Smith and F. Ulhmann for their suggestions during the preparation of this manuscript. The work was funded by EMBL, the Spanish Ministry of Science and Innovation and the Caja Madrid Foundation.

Author information

Authors and Affiliations



I.M. and N.M.L. conceived the study; I.M. designed and performed the analyses; A.S.N.S. and N.M.L. provided advice; I.M. and N.M.L. wrote the paper.

Corresponding authors

Correspondence to Iñigo Martincorena or Nicholas M. Luscombe.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Text (see Contents for details), Supplementary Figures 1-25, Supplementary Tables 1-2 and additional references. (PDF 3270 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Martincorena, I., Seshasayee, A. & Luscombe, N. Evidence of non-random mutation rates suggests an evolutionary risk management strategy. Nature 485, 95–98 (2012).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research