Single-Cell Epigenomics Uncovers Non-Coding Disease-Associated Genetic Variants

Single-Cell Epigenomics Uncovers Non-Coding Disease-Associated Genetic Variants

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Untangling the complex web of interactions that regulate gene expression and function requires effective tools to examine coding and non-coding regions of the genome, as well as the presence of genetic variants and epigenetic modifications. Historically, non-coding genomic regions and epigenetic elements have been difficult to characterize. New tools, like a single-cell epigenomics method recently published for non-coding disease-associated variants, are helping identify missing pieces in the puzzle of the genome.

Non-Coding Elements and Epigenetic Profiling

Genome-wide association studies have linked thousands of genetic variants to human diseases. However, most of these disease-associated variants occur within regions of the genome that do not encode proteins (non-coding regions), limiting our understanding of their functional significance. Often these variants can affect sequences known as cis-regulatory elements (CREs), which control the expression of target genes in specific cell types and in context-dependent manners.

Activation of CREs is accompanied by epigenetic changes, such as DNA hypomethylation or certain modifications to proteins involved in the packaging and organization of DNA. Epigenetics is a blanket term for describing elements that affect the genome and gene expression but aren’t encoded in the genetic sequence itself. Thus, epigenetic profiling has emerged as a valuable approach to understanding the impact of genetic variants in CREs. 

A recent review published in Nature Reviews Genetics provides an overview of the use of single-cell epigenomic analyses for the interpretation of disease-associated variants in non-coding regions of the genome, with exciting applications for mapping out the yet-unknown genetic basis of common traits.

Linking CREs to Their Functions

A major step toward increasing the interpretation of these variants has been the generation of atlases of candidate CREs for many primary human cells, tissues, organoids, and cell lines using single-cell epigenomic assays. These atlases comprise maps of chromatin accessibility, DNA methylation, and 3D chromatin conformation and interactions. The assays used include single-cell transposase-accessible chromatin using sequencing (scATAC-seq), single-cell transposome hypersensitive site sequencing (scTHS-seq), single-cell Hi-C, single-cell methyl-Hi-C, or single-nucleus methyl-3C sequencing (sn-m3C-seq).

Many of these assays are now available with high-throughput methodology allowing epigenomic profiling in thousands to millions of cells. They are also being offered as part of multi-omic workflows with single-cell gene expression (transcriptome) profiling to link gene regulatory networks and molecular mechanisms to disease pathologies.

Epigenomics and Disease

With the ability to link CREs to their functions comes the ability to better predict how alterations to gene regulation can contribute to disease phenotypes. Typical disease-associated variants are identified because they are in a coding gene, making it relatively easier to trace the affected gene product back to its origin.

Variants in non-coding regions, however, are harder to trace to their downstream effects. That’s why these breakthroughs in epigenomics and the creation of cell type-specific CRE candidate atlases are so exciting. They enable researchers to locate the elusive effects of regulatory element variation as they relate to disease, opening up avenues for new drug targets and a better understanding of underlying disease mechanisms.

Outsourcing Bioinformatics Analysis: How Bridge Informatics Can Help

With technological advances in fields like epigenomics, biological data generation, storage, and analysis is faster and more accessible than ever before. From pipeline development and software engineering to deploying existing bioinformatics tools, Bridge Informatics can help you on every step of your research journey.

As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing, and interpreting genomic and transcriptomic data. Bridge Informatics’ bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis. Click here to schedule a free introductory call with a member of our team.

Lauren Dembeck, Ph.D., Geneticist & Science Writer, Bridge Informatics

Lauren Dembeck, Ph.D., is an experienced science and medical writer. During her doctoral research at North Carolina State University, she conducted genome-wide association studies to identify genetic variants contributing to natural variation in complex traits and used a combination of classical and molecular genetics approaches in validation studies. Lauren was a postdoctoral fellow at the Okinawa Institute of Science and Technology in Japan. During her postdoc, she used fluorescence-activated cell sorting paired with high-throughput sequencing approaches to study the formation and regulation of neuronal circuits. 

She is part of our team of expert content writers at Bridge Informatics, bringing our readers and customers everything they need to know at the cutting edge of bioinformatics research. If you’re interested in reaching out, please email [email protected] or [email protected].

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