Using population selection and sequencing to characterize natural variation of starvation resistance in C. elegans

  1. Amy K Webster
  2. Rojin Chitrakar
  3. Maya Powell
  4. Jingxian Chen
  5. Kinsey Fisher
  6. Robyn E Tanny
  7. Lewis Stevens
  8. Kathryn Evans
  9. Angela Wei
  10. Igor Antoshechkin
  11. Erik C Andersen
  12. L Ryan Baugh  Is a corresponding author
  1. Duke University, United States
  2. Northwestern University, United States
  3. California Institute of Technology, United States

Abstract

Starvation resistance is important to disease and fitness, but the genetic basis of its natural variation is unknown. Uncovering the genetic basis of complex, quantitative traits such as starvation resistance is technically challenging. We developed a synthetic-population (re)sequencing approach using molecular inversion probes (MIP-seq) to measure relative fitness during and after larval starvation in C. elegans. We applied this competitive assay to 100 genetically diverse, sequenced, wild strains, revealing natural variation in starvation resistance. We confirmed that the most starvation-resistant strains survive and recover from starvation better than the most starvation-sensitive strains using standard assays. We performed genome-wide association (GWA) with the MIP-seq trait data and identified three quantitative trait loci (QTL) for starvation resistance, and we created near isogenic lines (NILs) to validate the effect of these QTL on the trait. These QTL contain numerous candidate genes including several members of the Insulin/EGF Receptor-L Domain (irld) family. We used genome editing to show that four different irld genes have modest effects on starvation resistance. Natural variants of irld-39 and irld-52 affect starvation resistance, and increased resistance of the irld-39; irld-52 double mutant depends on daf-16/FoxO. DAF-16/FoxO is a widely conserved transcriptional effector of insulin/IGF signaling (IIS), and these results suggest that IRLD proteins modify IIS, though they may act through other mechanisms as well. This work demonstrates efficacy of using MIP-seq to dissect a complex trait and it suggests that irld genes are natural modifiers of starvation resistance in C. elegans.

Data availability

Raw MIP-seq data for the starvation-resistance experiment and the pilot experiments to test individual MIPs is available as part of NCBI BioProject PRJNA730178. Code for processing MIP-seq data is available at github.com/amykwebster/MIPseq_2021.A Source Data file for all figures is also included.

The following data sets were generated

Article and author information

Author details

  1. Amy K Webster

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Rojin Chitrakar

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Maya Powell

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Jingxian Chen

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Kinsey Fisher

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Robyn E Tanny

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Lewis Stevens

    Department of Molecular Biosciences, Northwestern University, Evanston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Kathryn Evans

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

    Department of Biology, Duke University, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Igor Antoshechkin

    Division of Biology, California Institute of Technology, Pasadena, United States
    Competing interests
    The authors declare that no competing interests exist.
  11. 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
  12. L Ryan Baugh

    Department of Biology, Duke University, Durham, United States
    For correspondence
    ryan.baugh@duke.edu
    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

Funding

National Institute of General Medical Sciences (R01GM117408)

  • L Ryan Baugh

National Institute of General Medical Sciences (R01GM143159)

  • L Ryan Baugh

National Institute of Environmental Health Sciences (R01ES02993)

  • Erik C Andersen
  • L Ryan Baugh

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

Reviewing Editor

  1. Oliver Hobert, Columbia University, Howard Hughes Medical Institute, United States

Publication history

  1. Received: May 11, 2022
  2. Accepted: June 20, 2022
  3. Accepted Manuscript published: June 21, 2022 (version 1)

Copyright

© 2022, Webster 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.

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  1. Amy K Webster
  2. Rojin Chitrakar
  3. Maya Powell
  4. Jingxian Chen
  5. Kinsey Fisher
  6. Robyn E Tanny
  7. Lewis Stevens
  8. Kathryn Evans
  9. Angela Wei
  10. Igor Antoshechkin
  11. Erik C Andersen
  12. L Ryan Baugh
(2022)
Using population selection and sequencing to characterize natural variation of starvation resistance in C. elegans
eLife 11:e80204.
https://doi.org/10.7554/eLife.80204

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