Letter | Published:

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

Nature volume 485, pages 9598 (03 May 2012) | Download Citation

Abstract

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.

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Acknowledgements

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

Author notes

    • Aswin S. N. Seshasayee

    Present address: National Centre for Biological Sciences, TIFR, GKVK, Bellary Road, Bangalore 560065, India.

Affiliations

  1. EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge CB10 1SD, UK

    • Iñigo Martincorena
    • , Aswin S. N. Seshasayee
    •  & Nicholas M. Luscombe
  2. Okinawa Institute of Science & Technology, 1919-1 Tancha, Onna-son, Kunigami-gun, Okinawa 904-0495, Japan

    • Nicholas M. Luscombe
  3. UCL Genetics Institute, Department of Genetics, Environment and Evolution, University College London, Gower Street, London WC1E 6BT, UK

    • Nicholas M. Luscombe
  4. Cancer Research UK London Research Institute, 44 Lincoln’s Inn Fields, London WC2A 3LY, UK

    • Nicholas M. Luscombe

Authors

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Contributions

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.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Iñigo Martincorena or Nicholas M. Luscombe.

Supplementary information

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    Supplementary Information

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

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DOI

https://doi.org/10.1038/nature10995

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