How Criticality of Gene Regulatory Networks Affects the Resulting Morphogenesis under Genetic Perturbations

Hyobin Kim, Hiroki Sayama

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Whereas the relationship between criticality of gene regulatory networks (GRNs) and dynamics of GRNs at a single-cell level has been vigorously studied, the relationship between the criticality of GRNs and system properties at a higher level has not been fully explored. Here we aim at revealing a potential role of criticality of GRNs in morphogenesis, which is hard to uncover through the single-cell-level studies, especially from an evolutionary viewpoint. Our model simulated the growth of a cell population from a single seed cell. All the cells were assumed to have identical intracellular GRNs. We induced genetic perturbations to the GRN of the seed cell by adding, deleting, or switching a regulatory link between a pair of genes. From numerical simulations, we found that the criticality of GRNs facilitated the formation of nontrivial morphologies when the GRNs were critical in the presence of the evolutionary perturbations. Moreover, the criticality of GRNs produced topologically homogeneous cell clusters by adjusting the spatial arrangements of cells, which led to the formation of nontrivial morphogenetic patterns. Our findings correspond to an epigenetic viewpoint that heterogeneous and complex features emerge from homogeneous and less complex components through the interactions among them. Thus, our results imply that highly structured tissues or organs in morphogenesis of multicellular organisms might stem from the criticality of GRNs.

Original languageEnglish
Pages (from-to)85-105
Number of pages21
JournalArtificial Life
Volume24
Issue number2
DOIs
Publication statusPublished - 2018 May 1
Externally publishedYes

Keywords

  • Criticality
  • Gene regulatory network (GRN)
  • Morphogenetic system
  • Nontrivial morphology
  • Random Boolean network (RBN)

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Artificial Intelligence

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