Identifying Variable Chromatin Modules using single-cell epigenomics

Most common disease-associated genetic variants are thought to fall into gene regulatory regions, where they affect the interaction between transcription factors (TFs) and DNA and induce transcriptional changes.

To understand the extent of, and the mechanisms underlying variation in binding of TFs to DNA, genome-wide TF and chromatin state profiling studies were performed which revealed that non-coding variants frequently mediate coordinated changes in TF binding and chromatin mark enrichment over regions that span more than 100 kb.

These regions were termed “variable chromatin modules” (VCMs), providing a conceptual framework of how regulatory variation might shape complex traits. However, little is known about the formation, function, or plasticity of VCMs.

This is because vast amounts of epigenomics data have so far been required for identifying VCMs, making their identification costly, labour-intensive, and only applicable to easy-to-culture cell types.

Recent work has demonstrated the value of ATAC-seq for defining regulatory element hierarchies that conceptually resemble VCMs.

Here, I propose to extend these principles by developing an experimental and computational workflow for VCM identification using single-cell ATAC-seq.

This will allow sample multiplexing for sequencing followed by genotype-based demultiplexing, thereby increasing throughput, minimizing sample input, and mitigating variation between samples (Aim 1). I will apply this workflow to study VCM plasticity during human mesenchymal stromal cell differentiation (Aim 2).

The resulting data will be used to identify VCM-linked metabolic disease-relevant genetic variants, whose role in VCM formation will be validated using CRISPR-Cas9 (Aim 3).