1. Evolutionary Biology
  2. Genetics and Genomics
Download icon

The mutationathon highlights the importance of reaching standardization in estimates of pedigree-based germline mutation rates

  1. Lucie A Bergeron  Is a corresponding author
  2. Søren Besenbacher
  3. Tychele Turner
  4. Cyril J Versoza
  5. Richard J Wang
  6. Alivia Lee Price
  7. Ellie Armstrong
  8. Meritxell Riera
  9. Jedidiah Carlson
  10. Hwei-yen Chen
  11. Matthew W Hahn
  12. Kelley Harris
  13. April Snøfrid Kleppe
  14. Elora H López-Nandam
  15. Priya Moorjani
  16. Susanne P Pfeifer
  17. George P Tiley
  18. Anne D Yoder
  19. Guojie Zhang
  20. Mikkel H Schierup  Is a corresponding author
  1. University of Copenhagen, Denmark
  2. Aarhus University, Denmark
  3. Washington University in St. Louis, United States
  4. Arizona State University, United States
  5. Indiana University, United States
  6. Stanford University, United States
  7. University of Washington, United States
  8. California Academy of Sciences, United States
  9. University of California, Berkeley, United States
  10. Duke University, United States
Tools and Resources
  • Cited 0
  • Views 91
  • Annotations
Cite this article as: eLife 2022;11:e73577 doi: 10.7554/eLife.73577

Abstract

In the past decade, several studies have estimated the human per-generation germline mutation rate using large pedigrees. More recently, estimates for various non-human species have been published. However, methodological differences among studies in detecting germline mutations and estimating mutation rates make direct comparisons difficult. Here, we describe the many different steps involved in estimating pedigree-based mutation rates, including sampling, sequencing, mapping, variant calling, filtering, and how to appropriately account for false-positive and false-negative rates. For each step, we review the different methods and parameter choices that have been used in the recent literature. Additionally, we present the results from a 'Mutationathon', a competition organized among five research labs to compare germline mutation rate estimates for a single pedigree of rhesus macaques. We report almost a two-fold variation in the final estimated rate among groups using different post-alignment processing, calling, and filtering criteria and provide details into the sources of variation across studies. Though the difference among estimates is not statistically significant, this discrepancy emphasizes the need for standardized methods in mutation rate estimations and the difficulty in comparing rates from different studies. Finally, this work aims to provide guidelines for computational and statistical benchmarks for future studies interested in identifying germline mutations from pedigrees.

Data availability

The sequences of the pedigree analyzed are available on NCBI under the accession numbers:SRR10426295;SRR10426294;SRR10426275;SRR10426264;SRR10426253;SRR10426291;SRR10426290;SRR10426256;SRR10426255.The PCR experiment and Sanger resequencing produced for this work are deposited on Genbank under the accession number MZ661796 - MZ662076. Supplementary table 4 describe the data.The scripts used by the participants of the Mutationathon are publically available on different github described in the manuscript.Figure 3, 4 and 5 can be reproduced with the data in Figure 3 - source data 1, Figure 4 - source data 1, and Figure 5 - source data 1 .

The following data sets were generated

Article and author information

Author details

  1. Lucie A Bergeron

    Department of Biology, University of Copenhagen, Copenhagen, Denmark
    For correspondence
    lucie.a.bergeron@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1877-1690
  2. Søren Besenbacher

    Department of Molecular Medicine (MOMA), Aarhus University, Aarhus N, Denmark
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1455-1738
  3. Tychele Turner

    Department of Genetics, Washington University in St. Louis, Saint Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Cyril J Versoza

    Center for Evolution and Medicine, Arizona State University, Tempe, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Richard J Wang

    Department of Biology, Indiana University, Bloomington, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Alivia Lee Price

    Department of Biology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  7. Ellie Armstrong

    Department of Biology, Stanford University, Stanford, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7107-6318
  8. Meritxell Riera

    Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  9. Jedidiah Carlson

    Department of Genome Sciences, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Hwei-yen Chen

    Department of Biology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  11. Matthew W Hahn

    Department of Biology, Indiana University, Bloomington, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5731-8808
  12. Kelley Harris

    Department of Genome Sciences, University of Washington, Seattle, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0302-2523
  13. April Snøfrid Kleppe

    Department of Molecular Medicine, Aarhus University, Aarhus, Denmark
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7866-3056
  14. Elora H López-Nandam

    California Academy of Sciences, San Francisco, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Priya Moorjani

    Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Susanne P Pfeifer

    School of Life Sciences, Arizona State University, Tempe, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1378-2913
  17. George P Tiley

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0053-0207
  18. Anne D Yoder

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  19. Guojie Zhang

    Department of Biology, University of Copenhagen, Copenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  20. Mikkel H Schierup

    Bioinformatics Research Center, Aarhus University, Aarhus, Denmark
    For correspondence
    mheide@birc.au.dk
    Competing interests
    The authors declare that no competing interests exist.

Funding

Carlsbergfondet (CF16-0663)

  • Guojie Zhang

US national science foundation CAREER (DEB-2045343)

  • Susanne P Pfeifer

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

Reviewing Editor

  1. Virginie Courtier-Orgogozo, Université Paris-Diderot CNRS, France

Publication history

  1. Received: September 2, 2021
  2. Accepted: January 11, 2022
  3. Accepted Manuscript published: January 12, 2022 (version 1)

Copyright

© 2022, Bergeron 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

  • 91
    Page views
  • 21
    Downloads
  • 0
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

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)

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

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

Further reading

    1. Cell Biology
    2. Evolutionary Biology
    Chirine Toufaily et al.
    Research Article Updated

    Gonadotropin-releasing hormone (GnRH) is the primary neuropeptide controlling reproduction in vertebrates. GnRH stimulates follicle-stimulating hormone (FSH) and luteinizing hormone (LH) synthesis via a G-protein-coupled receptor, GnRHR, in the pituitary gland. In mammals, GnRHR lacks a C-terminal cytosolic tail (Ctail) and does not exhibit homologous desensitization. This might be an evolutionary adaptation that enables LH surge generation and ovulation. To test this idea, we fused the chicken GnRHR Ctail to the endogenous murine GnRHR in a transgenic model. The LH surge was blunted, but not blocked in these mice. In contrast, they showed reductions in FSH production, ovarian follicle development, and fertility. Addition of the Ctail altered the nature of agonist-induced calcium signaling required for normal FSH production. The loss of the GnRHR Ctail during mammalian evolution is unlikely to have conferred a selective advantage by enabling the LH surge. The adaptive significance of this specialization remains to be determined.

    1. Evolutionary Biology
    Eva Wolf et al.
    Research Article Updated

    With accelerating global warming, understanding the evolutionary dynamics of plant adaptation to environmental change is increasingly urgent. Here, we reveal the enigmatic history of the genus Cochlearia (Brassicaceae), a Pleistocene relic that originated from a drought-adapted Mediterranean sister genus during the Miocene. Cochlearia rapidly diversified and adapted to circum-Arctic regions and other cold-characterized habitat types during the Pleistocene. This sudden change in ecological preferences was accompanied by a highly complex, reticulate polyploid evolution, which was apparently triggered by the impact of repeated Pleistocene glaciation cycles. Our results illustrate that two early diversified Arctic-alpine diploid gene pools contributed differently to the evolution of this young polyploid genus now captured in a cold-adapted niche. Metabolomics revealed central carbon metabolism responses to cold in diverse species and ecotypes, likely due to continuous connections to cold habitats that may have facilitated widespread adaptation to alpine and subalpine habitats, and which we speculate were coopted from existing drought adaptations. Given the growing scientific interest in the adaptive evolution of temperature-related traits, our results provide much-needed taxonomic and phylogenomic resolution of a model system as well as first insights into the origins of its adaptation to cold.