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Gene Regulatory Network inference in long-lived C. elegans reveals modular properties that are predictive of novel ageing genes

ABSTRACT: We design a “wisdom-of-the-crowds” GRN inference pipeline, and couple it to network analyses, to understand the organisational principles governing gene regulation in long-lived glp-1/Notch C. elegans. The GRN has three layers (input, core, output) and is topologically equivalent to bow-tie/hourglass structures prevalent among metabolic networks. To assess functional importance of structural layers, we screened 80% of the regulators and discovered 50 new ageing genes, 86% with human orthologues and 56% further extending the long life of glp-1. Genes essential for longevity—including ones involved in insulin-like signalling (ILS)—are at the core, indicating that GRN’s structure is predictive of functionality. Using in vivo reporters, we found an intricate relationship between fat accumulation, SOD enzymes, and lifespan. We queried 5,497 genetic interactions (https://s-andrews.github.io/wormgrn/qpcr/), and identified modulators that phenocopy ILS genes and share identical targets. We present a framework with predictive power that can accelerate discovery in C. elegans and potentially humans.

ORGANISM(S): Caenorhabditis elegans

PROVIDER: GSE166512 | GEO | 2022/01/20

REPOSITORIES: GEO

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