By Todd Dickinson, PhD
Like it or not, scientists are often at the mercy of their instrumentation and the outputs those instruments produce. Next-generation sequencing (NGS) is a perfect example.
High-throughput genomic studies produce incredible data, enriching our understanding of biology. But the readouts can be a little too neat and tidy—linear arrays of genetic code. This makes it easier to read the raw data, but it doesn’t capture the three-dimensional complexity found in actual cells.
This has real-world consequences. The spatial relationships between a gene and its distal regulatory elements (such as the gene’s promoter and enhancer/silencer) can modulate that gene’s expression. Accordingly, these relationships are critically important to fully understand cellular function. In essence, we have been trying to solve a three-dimensional (3D) problem with two-dimensional (2D) analysis.
Biology in 3D
Genome-wide association studies (GWASs) are a great way to understand how essential three-dimensional information is to cellular biology. The single-nucleotide variants (SNVs) found in these studies often do not map to genes with known functions. Instead, they fall in non-annotated regulatory regions, such as enhancers. Mapping these regions to specific genes can be very challenging, as they can be quite far from each other on a linear genomic map.
But that’s only if we assess this relationship in 2D. In cells, the chromatin is looping around, bringing promoters much closer to their enhancers. This 3D structure brings all the necessary elements together to drive gene expression.
These loops are both structural and mechanistic. By examining chromosomes in 3D, we can better see the relationships between these regulatory elements and gene promoters. Moreover, clarifying these relationships has a massive impact on our understanding of the biology.
Improved tools for 3D analysis
The key to gaining a more complete, 3D understanding is chromatin—the mixture of DNA and proteins that make up chromosomes.
One of the best emerging tools is Hi-C, which uses proximity ligation to capture a more complete picture of chromatin’s dimensionality. Using the word “emerging” may seem tongue-in-cheek, as Hi-C has been around for more than 10 years, but new refinements have tremendously improved throughput, making the technique much more scalable. Initially, Hi-C analyses took around five days. That has been trimmed back to two days, and we can foresee this being accelerated further in the near future.
Hi-C is also more user friendly than experimental imaging techniques, which are labor intensive, requiring thousands of images and enormous computational power.
Not only has Hi-C become faster and easier, but updates have improved data quality, delivering far more uniform genome coverage and higher data resolution, as well as enabling pairing with chromatin-immunoprecipitation (ChIP), or hybrid capture, for more focused data. With these advances, Hi-C has become a far more accessible, flexible, and useful lab tool.
These improvements mean that Hi-C is now a go-to approach to understand genome function. On the discovery side, Hi-C can illuminate many of the underlying mechanisms that drive disease. At a recent conference, University of Michigan researcher Abhijit Parolia, MD, PhD, discussed how dissecting these structural realities improves our understanding of cancer cells and opens new treatment modalities.
Parolia and colleagues are focused on the SWItch/Sucrose Non-Fermentable (SWI/SNF) chromatin remodeling complex1, which modulates transcription factors’ access to chromatin, and the enhancer elements contained within, a prerequisite to promoting gene expression.
In cancers, this mechanism can become dysregulated, causing oncogene overexpression. Parolia and his team observed that disrupting this chromatin remodeling complex shifts chromatin to a closed state, denying transcription machinery access to the chromatin.
The researchers used HiChIP, a flavor of Hi-C that focuses the viewpoint on protein binding positions. Specifically, HiChIP technology developed by Dovetail Genomics allowed the researchers to clearly see the change in chromatin topology that occurs when the complex is disrupted, a change that can alleviate aberrant gene expression and prevent tumor growth. Seeing these chromatin changes in 3D helped the researchers visualize these mechanisms in greater detail.
Arul Chinnaiyan, MD, PhD, director of the Michigan Center for Translational Pathology and Parolia’s principal investigator, recently noted that “it would have been quite difficult for us to make these findings without the ability to fully visualize chromatin’s 3D configuration.”
The translational impact may be even greater. Consider a drug that works in some patients but not others. This happens all the time, but scientists and clinicians often don’t fully understand the mechanisms behind this delta. As a result, people are receiving medicines that may not be helping them.
If we can go back to the source, chromatin topology can act as a biomarker to help us understand why certain patients respond while others do not, offering a new approach to pharmacogenomics and, ultimately, personalized medicine.
As the scientific community tackles more complex diseases, visualizing the genome in 3D will become increasingly important to fully understand mechanisms, identify effective treatments, and deliver them to the right patients. Since altered gene expression is a common component in many diseases, seeing these disruptions in 3D has enormous potential. Current approaches are only scratching the surface. Biology happens in 3D and so should our analyses.
1. Xiao, L., Parolia, A., Qiao, Y. et al. Targeting SWI/SNF ATPases in enhancer-addicted prostate cancer. Nature (2021).