iScience (Jan 2022)

Gene regulatory network inference in long-lived C. elegans reveals modular properties that are predictive of novel aging genes

  • Manusnan Suriyalaksh,
  • Celia Raimondi,
  • Abraham Mains,
  • Anne Segonds-Pichon,
  • Shahzabe Mukhtar,
  • Sharlene Murdoch,
  • Rebeca Aldunate,
  • Felix Krueger,
  • Roger Guimerà,
  • Simon Andrews,
  • Marta Sales-Pardo,
  • Olivia Casanueva

Journal volume & issue
Vol. 25, no. 1
p. 103663

Abstract

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Summary: We design a “wisdom-of-the-crowds” GRN inference pipeline and couple it to complex network analysis to understand the organizational principles governing gene regulation in long-lived glp-1/Notch Caenorhabditis elegans. The GRN has three layers (input, core, and output) and is topologically equivalent to bow-tie/hourglass structures prevalent among metabolic networks. To assess the functional importance of structural layers, we screened 80% of regulators and discovered 50 new aging genes, 86% with human orthologues. Genes essential for longevity—including ones involved in insulin-like signaling (ILS)—are at the core, indicating that GRN's structure is predictive of functionality. We used in vivo reporters and a novel functional network covering 5,497 genetic interactions to make mechanistic predictions. We used genetic epistasis to test some of these predictions, uncovering a novel transcriptional regulator, sup-37, that works alongside DAF-16/FOXO. We present a framework with predictive power that can accelerate discovery in C. elegans and potentially humans.

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