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Bow-tie architecture of gene regulatory networks in species of varying complexity

journal contribution
posted on 2024-11-02, 20:10 authored by Gourab Roy, Shan He, Nicholas Geard, Cornelia VerspoorCornelia Verspoor
The gene regulatory network (GRN) architecture plays a key role in explaining the biological differences between species. We aim to understand species differences in terms of some universally present dynamical properties of their gene regulatory systems. A network architectural feature associated with controlling system-level dynamical properties is the bow-tie, identified by a strongly connected subnetwork, the core layer, between two sets of nodes, the in and the out layers. Though a bow-tie architecture has been observed in many networks, its existence has not been extensively investigated in GRNs of species of widely varying biological complexity. We analyse publicly available GRNs of several well-studied species from prokaryotes to unicellular eukaryotes to multicellular organisms. In their GRNs, we find the existence of a bow-tie architecture with a distinct largest strongly connected core layer. We show that the bow-tie architecture is a characteristic feature of GRNs. We observe an increasing trend in the relative core size with species complexity. Using studied relationships of the core size with dynamical properties like robustness and fragility, flexibility, criticality, controllability and evolvability, we hypothesize how these regulatory system properties have emerged differently with biological complexity, based on the observed differences of the GRN bow-tie architectures.

History

Related Materials

  1. 1.
    DOI - Is published in 10.1098/rsif.2021.0069
  2. 2.
    ISSN - Is published in 17425689

Journal

Journal of the Royal Society Interface

Volume

18

Number

20210069

Issue

179

Start page

1

End page

11

Total pages

11

Publisher

The Royal Society Publishing

Place published

United Kingdom

Language

English

Copyright

© 2021 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original author and source are credited.

Former Identifier

2006114653

Esploro creation date

2022-07-06

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