Abstract
The 3-dimensional (3D) conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases like schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs and schizophrenia heritability compared to equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared to promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally.
Summary Blurb Genes and their regulatory elements are organized within 3D networks in neurons which model functional structures and explain schizophrenia genetic etiology.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Title and abstract were shortened Section 1 on CRH characteristics and links to 3D features updated. Additional analyses on validation in post-mortem brain tissues. New section 6 added Figures revised : New Figure 1, Figure 3, Figure 4, New panel in Figure 5 Supplemental files updated Minor corrections provided : two-sided tests instead of right-tailed to consider alternative hypotheses contrary to expectation (e.g. depletion instead of enrichment); p-values were recomputed accordingly. It is worth noting that some effect measures are slightly changed to the second decimal point. Then, in the chromatin (Section 2) state analysis, we adjusted definitions of overlapping patterns to obtain a more intuitive interpretation. Indeed, in the original submission, only distal elements were considered while in this revision we integrated both distal elements and promoters, adjusting the subsequent figure (Fig 3A). Finally, regarding the logistic regression performed in the section on page 16 and the subsequent Fig4D, we found duplicated entries in the dataset. Removing duplicates led to slightly different results (confidence intervals and estimates) without changing substantially the interpretation of the variable effects.
