Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published June 21, 2022 | Supplemental Material + Published
Journal Article Open

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

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 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.

Additional Information

© 2022, Webster et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. 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). We thank Oliver Hobert for providing OH16024 daf-16(ot971[daf-16::GFP]), Jon Hibshman for sharing a starvation survival curve-fitting script, Chelsea Shoben for help passaging wild isolates, Clay Dilks for CRISPR advice, Sophia Gomez for genotyping assistance, Seth Taylor for strain organization and maintenance, and Jim Jordan for helpful discussions. Funding was provided by the NIH (R01GM117408 and R01GM143159 to LRB and R01ES029930 to ECA and LRB). AKW was supported by an NSF Graduate Research Fellowship. Some strains were provided by the CGC, which is funded by NIH Office of Research Infrastructure Programs (P40 OD010440). We would also like to thank WormBase. The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication. 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 (copy archived at swh:1:rev:27839dcc9ef1587086be195349310fb70fbfcaf1). A Source Data file for all figures is also included. Author contributions: Amy K Webster, Data curation, Formal analysis, Investigation, Methodology, Supervision, Validation, Visualization, Writing – original draft, Writing – review and editing; Rojin Chitrakar, Data curation, Investigation, Methodology; Maya Powell, Investigation, Validation; Jingxian Chen, Data curation, Formal analysis; Kinsey Fisher, Angela Wei, Validation; Robyn E Tanny, Resources; Lewis Stevens, Kathryn Evans, Formal analysis; Igor Antoshechkin, Data curation, Formal analysis, Investigation, Methodology, Software; Erik C Andersen, Funding acquisition, Resources, Software, Writing – review and editing; L Ryan Baugh, Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Writing – original draft, Writing – review and editing.

Attached Files

Published - elife-80204-v2.pdf

Supplemental Material - elife-80204-supp1-v2.xlsx

Supplemental Material - elife-80204-supp2-v2.xlsx

Supplemental Material - elife-80204-supp3-v2.xlsx

Supplemental Material - elife-80204-transrepform1-v2.docx

Files

elife-80204-v2.pdf
Files (15.7 MB)
Name Size Download all
md5:06386b6330d05903cc3faf83e0d5cb57
1.5 MB Download
md5:bf7213a61c48fcaa64c2d42a2d87f01e
2.1 MB Preview Download
md5:e2e3b3919568755d0754b4f81673bc72
114.7 kB Download
md5:8e8cf3acafdeb661d194e3284bbc4a9d
9.7 MB Download
md5:6a466e95241a8e05e0db6ea524741819
2.2 MB Download

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023