Using population selection and sequencing to characterize natural variation of starvation resistance in C. elegans
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.
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.
Article and author information
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.
- Oliver Hobert, Columbia University, Howard Hughes Medical Institute, United States
- Received: May 11, 2022
- Accepted: June 20, 2022
- Accepted Manuscript published: June 21, 2022 (version 1)
- Version of Record published: July 7, 2022 (version 2)
© 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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