4.6 Article

An Insulin-to-Insulin Regulatory Network Orchestrates Phenotypic Specificity in Development and Physiology

Journal

PLOS GENETICS
Volume 10, Issue 3, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.1004225

Keywords

-

Funding

  1. ERC [NeuroAge 242666]
  2. Research Councils UK Fellowship
  3. University of London Central Research Fund
  4. Novartis Research Foundation
  5. Wayne State University
  6. Esther A. and Joseph Klingenstein Fund
  7. March of Dimes Foundation
  8. Alfred P. Sloan Foundation
  9. John Merck Fund
  10. NIH [R01 DC009852, R03 AG032481, R01 AG034994, DP2 OD004402-01, R01AG035317, R21EB012803, R01GM088333]
  11. Max Planck Society
  12. Sybacol/Bundes Ministerium fur Bildung und Forschung
  13. CECAD/Deutch Forschung Gemeinschaft
  14. NSF [CBET 0954578]
  15. Medical Research Council [G0901899] Funding Source: researchfish
  16. Div Of Chem, Bioeng, Env, & Transp Sys
  17. Directorate For Engineering [0954578] Funding Source: National Science Foundation
  18. MRC [G0901899] Funding Source: UKRI

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Insulin-like peptides (ILPs) play highly conserved roles in development and physiology. Most animal genomes encode multiple ILPs. Here we identify mechanisms for how the forty Caenorhabditis elegans ILPs coordinate diverse processes, including development, reproduction, longevity and several specific stress responses. Our systematic studies identify an ILP-based combinatorial code for these phenotypes characterized by substantial functional specificity and diversity rather than global redundancy. Notably, we show that ILPs regulate each other transcriptionally, uncovering an ILP-to-ILP regulatory network that underlies the combinatorial phenotypic coding by the ILP family. Extensive analyses of genetic interactions among ILPs reveal how their signals are integrated. A combined analysis of these functional and regulatory ILP interactions identifies local genetic circuits that act in parallel and interact by crosstalk, feedback and compensation. This organization provides emergent mechanisms for phenotypic specificity and graded regulation for the combinatorial phenotypic coding we observe. Our findings also provide insights into how large hormonal networks regulate diverse traits.

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