1. Evolutionary Biology
  2. Genetics and Genomics
Download icon

Selfing is the safest sex for Caenorhabditis tropicalis

  1. Luke M Noble  Is a corresponding author
  2. John Yuen
  3. Lewis Stevens
  4. Nicolas D Moya
  5. Riaad Persaud
  6. Marc Moscatelli
  7. Jacqueline L Jackson
  8. Gaotian Zhang
  9. Rojin Chitrakar
  10. L Ryan Baugh
  11. Christian Braendle
  12. Erik C Andersen
  13. Hannah S Seidel
  14. Matthew V Rockman
  1. Ecole Normale Superieure, France
  2. New York University, United States
  3. Northwestern University, United States
  4. Duke University, United States
  5. Université Côte d'Azur, CNRS, Inserm, France
  6. Eastern Michigan University, United States
Research Article
  • Cited 1
  • Views 2,411
  • Annotations
Cite this article as: eLife 2021;10:e62587 doi: 10.7554/eLife.62587

Abstract

Mating systems have profound effects on genetic diversity and compatibility. The convergent evolution of self-fertilization in three Caenorhabditis species provides a powerful lens to examine causes and consequences of mating system transitions. Among the selfers, C. tropicalis is the least genetically diverse and most afflicted by outbreeding depression. We generated a chromosomal-scale genome for C. tropicalis and surveyed global diversity. Population structure is very strong, and islands of extreme divergence punctuate a genomic background that is highly homogeneous around the globe. Outbreeding depression in the laboratory is caused largely by multiple Medea-like elements, genetically consistent with maternal toxin/zygotic antidote systems. Loci with Medea activity harbor novel and duplicated genes, and their activity is modified by mito-nuclear background. Segregating Medea elements dramatically reduce fitness, and simulations show that selfing limits their spread. Frequent selfing in C. tropicalis may therefore be a strategy to avoid Medea-mediated outbreeding depression.

Data availability

All sequencing reads used in this project are available from the NCBI Sequence Read Archive under accession PRJNA662844. Software code is available from https://github.com/lukemn/tropicalis. All data generated or analysed during this study are included in the manuscript and supporting files. Source data and supplementary files have been provided for Figures 1,2,3,4,5,6,7,9,10,11,12.

The following data sets were generated

Article and author information

Author details

  1. Luke M Noble

    Institut de Biologie de l'ENS, Ecole Normale Superieure, Paris, France
    For correspondence
    noble@biologie.ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5161-4059
  2. John Yuen

    Department of Biology and Center for Genomics & Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1569-3298
  3. Lewis Stevens

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6075-8273
  4. Nicolas D Moya

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6817-1784
  5. Riaad Persaud

    Department of Biology and Center for Genomics & Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Marc Moscatelli

    Department of Biology and Center for Genomics & Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Jacqueline L Jackson

    Department of Biology and Center for Genomics & Systems Biology, New York University, Jersey City, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5376-0968
  8. Gaotian Zhang

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Rojin Chitrakar

    Department of Biology, Duke Center for Genomic and Computational Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. L Ryan Baugh

    Department of Biology, Duke Center for Genomic and Computational 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:" 0000-0003-2148-5492
  11. Christian Braendle

    Institut de Biologie Valrose, Université Côte d'Azur, CNRS, Inserm, Nice, France
    Competing interests
    The authors declare that no competing interests exist.
  12. Erik C Andersen

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0229-9651
  13. Hannah S Seidel

    Department of Biology, Eastern Michigan University, Ypsilanti, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. Matthew V Rockman

    Department of Biology and Center for Genomics & Systems Biology, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6492-8906

Funding

National Institute of Environmental Health Sciences (ES029930)

  • Erik C Andersen

National Institute of Environmental Health Sciences (ES029930)

  • Matthew V Rockman

National Institute of General Medical Sciences (GM089972)

  • Matthew V Rockman

National Institute of General Medical Sciences (GM121828)

  • Matthew V Rockman

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

Reviewing Editor

  1. Vincent Castric, Université de Lille, France

Publication history

  1. Received: August 29, 2020
  2. Accepted: January 8, 2021
  3. Accepted Manuscript published: January 11, 2021 (version 1)
  4. Version of Record published: February 1, 2021 (version 2)

Copyright

© 2021, Noble 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

  • 2,411
    Page views
  • 197
    Downloads
  • 1
    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. Evolutionary Biology
    2. Neuroscience
    Jan Clemens et al.
    Research Article Updated

    How neural networks evolved to generate the diversity of species-specific communication signals is unknown. For receivers of the signals, one hypothesis is that novel recognition phenotypes arise from parameter variation in computationally flexible feature detection networks. We test this hypothesis in crickets, where males generate and females recognize the mating songs with a species-specific pulse pattern, by investigating whether the song recognition network in the cricket brain has the computational flexibility to recognize different temporal features. Using electrophysiological recordings from the network that recognizes crucial properties of the pulse pattern on the short timescale in the cricket Gryllus bimaculatus, we built a computational model that reproduces the neuronal and behavioral tuning of that species. An analysis of the model’s parameter space reveals that the network can provide all recognition phenotypes for pulse duration and pause known in crickets and even other insects. Phenotypic diversity in the model is consistent with known preference types in crickets and other insects, and arises from computations that likely evolved to increase energy efficiency and robustness of pattern recognition. The model’s parameter to phenotype mapping is degenerate – different network parameters can create similar changes in the phenotype – which likely supports evolutionary plasticity. Our study suggests that computationally flexible networks underlie the diverse pattern recognition phenotypes, and we reveal network properties that constrain and support behavioral diversity.

    1. Evolutionary Biology
    Lu Chen et al.
    Research Article

    A high portion of the earliest known insect fauna is composed of the so-called ‘lobeattid insects’, whose systematic affinities and role as foliage feeders remain debated. We investigated hundreds of samples of a new lobeattid species from the Xiaheyan locality using a combination of photographic techniques, including reflectance transforming imaging, geometric morphometrics, and biomechanics to document its morphology, and infer its phylogenetic position and ecological role. Ctenoptilus frequens sp. nov. possessed a sword-shaped ovipositor with valves interlocked by two ball-and-socket mechanisms, lacked jumping hind-legs, and certain wing venation features. This combination of characters unambiguously supports lobeattids as stem relatives of all living Orthoptera (crickets, grasshoppers, katydids). Given the herein presented and other remains, it follows that this group experienced an early diversification and, additionally, occurred in high individual numbers. The ovipositor shape indicates that ground was the preferred substrate for eggs. Visible mouthparts made it possible to assess the efficiency of the mandibular food uptake system in comparison to a wide array of extant species. The new species was likely omnivorous which explains the paucity of external damage on contemporaneous plant foliage.