MIT researchers generate the highest-resolution maps of the 3D genome

The researchers have developed a new technique called Region Capture Micro-C (RCMC), which uses targeted sequencing to generate ultra-high-resolution 3D genome structure maps.
Kavita Verma
MIT researchers use RCMC to study enhancer-gene interactions in five regions, find clusters of multiple interactions
MIT researchers use RCMC to study enhancer-gene interactions in five regions, find clusters of multiple interactions


Region Capture Micro-C (RCMC), a new technique created by MIT researchers to map the 3D organization of the human genome, provides unparalleled resolution at a far cheaper cost. The MIT researchers used Micro-C, which fragments the genome using the enzyme micrococcal nuclease, to acquire the high resolution required to map particular connections between genes and regulatory regions. 

The number of potential genomic locations is reduced by a factor of 1,000 by concentrating on regions of the genome that contain genes of interest, and the cost of sequencing is reduced by a factor of 100,000, or around $1,000. In a recent study, the scientists employed RCMC to investigate five locations with sizes ranging from a few hundred thousand to nearly 2 million base pairs. 

They discovered numerous enhancers that interact with Sox2 as well as previously unknown relationships between neighboring genes and enhancers after collecting and sequencing the DNA regions of interest. The method used by the researchers, however, conceals neither the timing nor simultaneity of any of these interactions – nor does it indicate which contact is most crucial. 

The MIT team intends to collaborate with scientists at Harvard Medical School to investigate variants linked to metabolic disorders and with scientists at Boston Children's Hospital to apply this type of analysis to genomic regions that have been connected with blood disorders in genome-wide association studies.

RCMC offers unprecedented resolution at a much lower cost

For a quarter of the price of other published techniques, RCMC produces maps that are 100 times more information-rich by concentrating on regions spanning a few million base pairs. Prior to this, obtaining high resolution would have cost millions, if not billions, of dollars. With RCMC, this approach is more reasonably priced at around $1,000.

New tool to study genomic regions linked to blood disorders and metabolic disorders

In order to apply RCMC to genomic areas connected with blood diseases in genome-wide association studies, the MIT team intends to collaborate with scientists at Boston Children's Hospital. Additionally, they are working with Harvard Medical School experts to investigate variations related to metabolic illnesses. With the help of the new method, it will be possible to analyze the ultrafine chromatin looping architecture and gain new knowledge about the connections between regulatory elements and gene regulation.

The study was published in the journal Nature Genetics.

Study Abstract

Although enhancers are central regulators of mammalian gene expression, the mechanisms underlying enhancer–promoter (E-P) interactions remain unclear. Chromosome conformation capture (3C) methods effectively capture large-scale three-dimensional (3D) genome structure but struggle to achieve the depth necessary to resolve fine-scale E-P interactions. Here, we develop Region Capture Micro-C (RCMC) by combining micrococcal nuclease (MNase)-based 3C with a tiling region-capture approach and generate the deepest 3D genome maps reported with only modest sequencing. By applying RCMC in mouse embryonic stem cells and reaching the genome-wide equivalent of ~317 billion unique contacts, RCMC reveals previously unresolvable patterns of highly nested and focal 3D interactions, which we term microcompartments. Microcompartments frequently connect enhancers and promoters, and although loss of loop extrusion and inhibition of transcription disrupts some microcompartments, most are largely unaffected. We therefore propose that many E-P interactions form through a compartmentalization mechanism, which may partially explain why acute cohesin depletion only modestly affects global gene expression.

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