Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders

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Abstract

Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.

Introduction

When measured linearly, the approximately 3 billion DNA base pairs comprising the human genome extend 2 m in length. Despite the relatively large size as compared to other organisms, it contains a similar number of protein coding genes which account for just 2% of its total content. Traditionally, it was thought the other 98% of DNA sequences were “junk DNA”. However, it has become increasingly understood that many of these non-coding regions orchestrate gene regulation via functioning as enhancers, silencers, insulators, and/or non-coding RNAs. It is now estimated that these non-coding regions harbor ~90% of genetic variants associated with human diseases [1], and therefore, detailed characterization of the non-coding genome is imperative for advancing our understanding of disease biology. While large-scale efforts to characterize the non-coding genome such as ENCODE are actively underway [2], deciphering the functional consequences of non-coding variation has been challenging due to its vast size, limited conservation across species, and lack of a generalizable rubric to predict effects from sequence variation. The advent of next generation sequencing technologies and adaptations of genome engineering tools have enabled development of various multi-omic approaches that can be used to decode the regulatory grammar of the genome, or “regulome” [3]. One key approach for better interpreting the non-coding genome is generation of three-dimensional (3-D) contact maps of chromatin conformation, as the coordinated manner in which 2 m-sized DNA is compacted into a nucleus approximately 200,000 times smaller in size is reflective of gene regulatory principles.

In this review, we highlight recent advances in available techniques for assaying chromosome conformation, which provides a roadmap to interrogate the functional consequences of non-coding genetic variants. We also introduce perturbation assays that complement chromatin architecture by experimentally validating variant effects on gene regulation. We conclude by describing key gaps in our knowledge of the dynamic gene regulatory landscape and how filling these gaps can provide a path forward for gleaning mechanistic understanding of disease pathogenesis.

Section snippets

Mapping three-dimensional chromatin configuration

Decoding the chromatin configuration remains a fundamental question in molecular biology. To date, one of the most popular genomic approaches to identify chromatin configuration is to use chromosome conformation capture (3C)-based techniques [4]. Hi-C is one such technique which profiles chromosome conformation at a genome-wide scale [5], and relies on fixation of DNA to preserve chromosome configuration, followed by restriction enzyme mediated digestion and proximity ligation to link points of

Gene regulatory architecture functions as a blueprint for inferring SNP-gene relationships

Genome-wide association studies (GWAS) and whole genome sequencing (WGS) studies have identified hundreds to thousands of genetic variants associated with various human traits and diseases [41], [42]. The vast majority of these variants are located in the non-coding genome, and high-resolution maps of chromatin architecture may function as a reference atlas to decipher the functional consequences of these risk variants. The basic assumption is that risk variants can regulate distal genes when

Experimental validation to elucidate functional impact of SNPs

Despite tremendous strides in predictive methodologies for inferring SNP-gene relationships, a gap remains in experimentally validating the functional outcome of these relationships. Therefore, the next fundamental step is to functionally characterize the variant effects on gene regulation. However, traditional approaches such as luciferase assays and single gene knock-out experiments are no longer suitable for systematic characterization of thousands of genetic variants associated with human

Toward a more complete map of gene regulatory architecture in the human brain

Chromatin configuration of the human brain has been profiled across key developmental epochs and cell types (Table 1). These rich datasets of 3-D chromatin architecture generated from the human brain provided a cornerstone for predicting the functional impact of non-coding variants and elucidating biological underpinnings of various psychiatric and neurodegenerative disorders [48], [67], [68], [69], [70]. Despite these resources, we are far from understanding the comprehensive landscape of gene

Declaration of Competing Interest

Authors declare no conflict of interest.

Acknowledgements

This review was supported by the National Institute of Mental Health (R00MH113823, DP2MH122403, H.W.), the National Institute on Drug Abuse (R21DA051921, H.W.), the Pharmacological Sciences T32 Training Program (T32GM135095, B.M.P.), and the NARSAD Young Investigator Award from the Brain and Behavior Research Foundation (H.W.).

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