Complex small-world regulatory networks emerge from the 3D organisation of the human genome

Dataset

Abstract

The discovery that overexpressing one or a few critical transcription factors can switch cell state suggests that gene regulatory networks are relatively simple. In contrast, genome-wide association studies (GWAS) point to complex phenotypes being determined by hundreds of loci that rarely encode transcription factors and which individually have small effects. Here, we use computer simulations and a simple fitting-free polymer model of chromosomes to show that spatial correlations arising from 3D genome organisation naturally lead to stochastic and bursty transcription as well as complex small-world regulatory networks (where the transcriptional activity of each genomic region subtly affects almost all others). These effects require factors to be present at sub-saturating levels; increasing levels dramatically simplifies networks as more transcription units are pressed into use. Consequently, results from GWAS can be reconciled with those involving overexpression. We apply this pan-genomic model to predict patterns of transcriptional activity in whole human chromosomes, and, as an example, the effects of the deletion causing the diGeorge syndrome. javascript:void(0);

## Software ##
For information on the LAMMPS see https://www.lammps.org .

Data Citation

Brackley, CA; Gilbert, N; Michieletto, D; Papantonis, A; Pereira, MCF; Cook, PR; Marenduzzo, D. (2021). Complex small-world regulatory networks emerge from the 3D organisation of the human genome, [dataset]. University of Edinburgh. School of Physics and Astronomy. https://doi.org/10.7488/ds/3110.
Date made available9 Aug 2021
PublisherEdinburgh DataShare
Geographical coverageUK,UNITED KINGDOM

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