Bedrock radioactivity influences the rate and spectrum of mutation

  1. Nathanaëlle Saclier  Is a corresponding author
  2. Patrick Chardon
  3. Florian Malard
  4. Lara Konecny-Dupré
  5. David Eme
  6. Arnaud Bellec
  7. Vincent Breton
  8. Laurent Duret
  9. Tristan Lefebure  Is a corresponding author
  10. Christophe J Douady
  1. Université Claude Bernard Lyon 1, France
  2. Université Clermont-Auvergne, France
  3. Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), France
  4. Université de Lyon, Université Claude Bernard, CNRS UMR 5558, France

Abstract

All organisms on Earth are exposed to low doses of natural radioactivity but some habitats are more radioactive than others. Yet, documenting the influence of natural radioactivity on the evolution of biodiversity is challenging. Here, we addressed whether organisms living in naturally more radioactive habitats accumulate more mutations across generations using 14 species of waterlice living in subterranean habitats with contrasted levels of radioactivity. We found that the mitochondrial and nuclear mutation rates across a waterlouse species' genome increased on average by 60 and 30%, respectively, when radioactivity increased by a factor of three. We also found a positive correlation between the level of radioactivity and the probability of G to T (and complementary C to A) mutations, a hallmark of oxidative stress. We conclude that even low doses of natural bedrock radioactivity influence the mutation rate possibly through the accumulation of oxidative damage, in particular in the mitochondrial genome.

Data availability

- 16S sequences have been deposited on the European Nucleotide Archive and are available under the accession numbers from LR214526 to LR214880 (https://www.ebi.ac.uk/ena/data/view/LR214526-LR214880).- Alignments and the list of genes used to compute synonymous substitutionrate have been deposited on Zenodo (https://zenodo.org/deposit/2563829).-Transcriptome reads have been deposited on the European Nucleotide Archive and are available under accession numbers from LR536601 to LR536626 in the study ID PRJEB14193 (https://www.ebi.ac.uk/ena/data/search?query=PRJEB14193).- Number of reads and data used for correlations, namely measures of radionuclides and mutations counts have been deposited on Zenodo (https://doi.org/10.5281/zenodo.4071754).

The following data sets were generated

Article and author information

Author details

  1. Nathanaëlle Saclier

    Laboratoire d'écologie des hydrosystèmes naturels et anthropisés, Université Claude Bernard Lyon 1, Villeurbanne, France
    For correspondence
    nathanaelle.saclier@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1522-9644
  2. Patrick Chardon

    Laboratoire de Physique de Clermont, Université Clermont-Auvergne, Clermont-Ferrand, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Florian Malard

    Laboratoire d'écologie des hydrosystèmes naturels et anthropisés, Université Claude Bernard Lyon 1, Villeurbanne, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Lara Konecny-Dupré

    Laboratoire d'écologie des hydrosystèmes naturels et anthropisés, Université Claude Bernard Lyon 1, Villeurbanne, France
    Competing interests
    The authors declare that no competing interests exist.
  5. David Eme

    Ecologie et Modèles pour l'Halieutique (EMH), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Nantes, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8790-0412
  6. Arnaud Bellec

    Laboratoire d'écologie des hydrosystèmes naturels et anthropisés, Université Claude Bernard Lyon 1, Villeurbanne, France
    Competing interests
    The authors declare that no competing interests exist.
  7. Vincent Breton

    Laboratoire de Physique de Clermont, Université Clermont-Auvergne, Clemront-Ferrand, France
    Competing interests
    The authors declare that no competing interests exist.
  8. Laurent Duret

    Laboratoire de Biométrie et Biologie Evolutive, Université de Lyon, Université Claude Bernard, CNRS UMR 5558, Villeurbanne, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2836-3463
  9. Tristan Lefebure

    LEHNA, Université Claude Bernard Lyon 1, Villeurbanne, France
    For correspondence
    tristan.lefebure@univ-lyon1.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3923-8166
  10. Christophe J Douady

    Laboratoire d'écologie des hydrosystèmes naturels et anthropisés, Université Claude Bernard Lyon 1, Villeurbanne, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4503-8040

Funding

Centre National de la Recherche Scientifique (STYGOMICS - Défi enviromix)

  • Patrick Chardon
  • Florian Malard
  • Lara Konecny-Dupré
  • Tristan Lefebure
  • Christophe J Douady

Agence Nationale de la Recherche (ANR- 15-CE32-0005 Convergenomix)

  • Lara Konecny-Dupré
  • Laurent Duret
  • Tristan Lefebure
  • Christophe J Douady

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Saclier et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,883
    views
  • 151
    downloads
  • 8
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Nathanaëlle Saclier
  2. Patrick Chardon
  3. Florian Malard
  4. Lara Konecny-Dupré
  5. David Eme
  6. Arnaud Bellec
  7. Vincent Breton
  8. Laurent Duret
  9. Tristan Lefebure
  10. Christophe J Douady
(2020)
Bedrock radioactivity influences the rate and spectrum of mutation
eLife 9:e56830.
https://doi.org/10.7554/eLife.56830

Share this article

https://doi.org/10.7554/eLife.56830

Further reading

    1. Evolutionary Biology
    Mattias Siljestam, Claus Rueffler
    Research Article

    The majority of highly polymorphic genes are related to immune functions and with over 100 alleles within a population, genes of the major histocompatibility complex (MHC) are the most polymorphic loci in vertebrates. How such extraordinary polymorphism arose and is maintained is controversial. One possibility is heterozygote advantage (HA), which can in principle maintain any number of alleles, but biologically explicit models based on this mechanism have so far failed to reliably predict the coexistence of significantly more than ten alleles. We here present an eco-evolutionary model showing that evolution can result in the emergence and maintenance of more than 100 alleles under HA if the following two assumptions are fulfilled: first, pathogens are lethal in the absence of an appropriate immune defence; second, the effect of pathogens depends on host condition, with hosts in poorer condition being affected more strongly. Thus, our results show that HA can be a more potent force in explaining the extraordinary polymorphism found at MHC loci than currently recognized.

    1. Evolutionary Biology
    Matthew Osmond, Graham Coop
    Research Article

    Spatial patterns in genetic diversity are shaped by individuals dispersing from their parents and larger-scale population movements. It has long been appreciated that these patterns of movement shape the underlying genealogies along the genome leading to geographic patterns of isolation by distance in contemporary population genetic data. However, extracting the enormous amount of information contained in genealogies along recombining sequences has, until recently, not been computationally feasible. Here we capitalize on important recent advances in genome-wide gene-genealogy reconstruction and develop methods to use thousands of trees to estimate per-generation dispersal rates and to locate the genetic ancestors of a sample back through time. We take a likelihood approach in continuous space using a simple approximate model (branching Brownian motion) as our prior distribution of spatial genealogies. After testing our method with simulations we apply it to Arabidopsis thaliana. We estimate a dispersal rate of roughly 60km2 per generation, slightly higher across latitude than across longitude, potentially reflecting a northward post-glacial expansion. Locating ancestors allows us to visualize major geographic movements, alternative geographic histories, and admixture. Our method highlights the huge amount of information about past dispersal events and population movements contained in genome-wide genealogies.