Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Yang Wu,Jian Yang,Ian J Deary,Naomi R Wray,Jian Zeng,Huanwei Wang,Allan F Mcrae,Jennifer E Phillips-Cremins,Zhili Zheng,Futao Zhang,Ting Qi

doi:10.1038/s41467-020-15587-0

Abstract

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood (n = 1980), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation.

Highlights

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation
We have presented an analytical approach on the basis of the recently developed summary-data–based Mendelian randomisation (SMR) & heterogeneity in dependent instruments (HEIDI) method to predict promoteranchored chromatin interactions using methylation (DNAm) quantitative trait locus (mQTL) summary data
Our method utilises a genetic model to perform a Mendelian randomisation analysis so that the detected associations are not confounded by non-genetic factors, which is distinct from the methods that predict chromatin interactions from the correlations of chromatin accessibility measures[14,16]

Summary

Introduction

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Hi-C is a technique based on chromosome conformation capture (3C)[9] to quantify genome-wide interactions between genomic loci that are close in three-dimensional (3D) space, and ChIA-PET is a method that combines ChIP-based methods[10] and 3C These high-throughput assays are currently not scalable to population-based cohorts with large sample sizes because of the complexity of generating a DNA library and the extremely highsequencing depth needed to achieve high detection resolution[11]. There have been increasing interests in the use of epigenomic data (e.g., DNA methylation (DNAm) and/or histone modification) to infer chromatin interactions[14,15,16,17] These analyses, rely on individual-level chromatin accessibility data often only available in small samples[14,16], and it is not straightforward to use the predicted chromatin interactions to interpret the variant-trait associations identified by GWAS. We propose an analytical approach to predict chromatin interaction by detecting the association between

Methods

Results

Conclusion