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

2021 | journal article. A publication with affiliation to the University of Göttingen.

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​Complex small-world regulatory networks emerge from the 3D organisation of the human genome​
Brackley, C. A.; Gilbert, N.; Michieletto, D.; Papantonis, A.; Pereira, M. C. F.; Cook, P. R. & Marenduzzo, D.​ (2021) 
Nature Communications12(1) art. 5756​.​ DOI: https://doi.org/10.1038/s41467-021-25875-y 

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Brackley, C. A.; Gilbert, N.; Michieletto, D.; Papantonis, A.; Pereira, M. C. F.; Cook, P. R.; Marenduzzo, D.
Abstract
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.
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.
Issue Date
2021
Journal
Nature Communications 
eISSN
2041-1723
Language
English

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