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

Journal Article (Journal Article)

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 Caenorhabditis 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, although 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 .

Full Text

Duke Authors

Cited Authors

  • Webster, AK; Chitrakar, R; Powell, M; Chen, J; Fisher, K; Tanny, RE; Stevens, L; Evans, K; Wei, A; Antoshechkin, I; Andersen, EC; Baugh, LR

Published Date

  • June 2022

Published In

Volume / Issue

  • 11 /

Start / End Page

  • e80204 -

PubMed ID

  • 35727141

Pubmed Central ID

  • PMC9262388

Electronic International Standard Serial Number (EISSN)

  • 2050-084X

International Standard Serial Number (ISSN)

  • 2050-084X

Digital Object Identifier (DOI)

  • 10.7554/elife.80204


  • eng