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Updated: May 12, 2026
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Using Caenorhabditis elegans to Screen for Tissue-Specific Chaperone Interactions
Published on: June 7, 2020
Integrative analysis of C. elegans modENCODE ChIP-seq data sets to infer gene regulatory interactions.
Eric L Van Nostrand1, Stuart K Kim
1Department of Genetics and Department of Developmental Biology, Stanford University Medical Center, Stanford, California 94305, USA.
Genome Research
|March 28, 2013
Summary
This study uses C. elegans transcription factor binding data to reveal insights into gene regulation. Analyzing transcription factor complexity and dynamic binding uncovers novel regulators of aging and lifespan.
Area of Science:
- Genomics
- Developmental Biology
- Aging Research
Background:
- The C. elegans modENCODE Consortium generated extensive in vivo transcription factor binding site data using ChIP-seq.
- Individual transcription factor analysis has limitations in understanding complex gene regulatory networks.
Purpose of the Study:
- To demonstrate how a compendium of ChIP-seq data can yield biological insights beyond individual factor analysis.
- To explore transcription factor complexity, dynamic binding, and infer regulatory networks.
Main Methods:
- Analysis of transcription factor binding complexity at specific loci.
- Comparison of transcription factor binding profiles across different developmental stages.
- Inference of gene expression regulators using ChIP-seq data and expression profiling.
Main Results:
- Low-complexity binding sites correlate with responsiveness to single transcription factor expression changes.
- Transcription factor UNC-62 exhibits stage-specific binding due to cofactor association and alternative splicing.
- A novel approach identified nine candidate aging regulators, including three known longevity factors, with two experimentally validated to extend lifespan.
Conclusions:
- Integrated analysis of ChIP-seq data provides deeper biological understanding than single-factor studies.
- Dynamic transcription factor binding and complexity are key to understanding gene regulation.
- This approach successfully identifies novel functional regulators of complex biological processes like aging.
