New Method to Understand Two levels of Epigenetic Changes in Tissues

More and more people are learning about how an individual’s genetic sequence determines their body’s development and how that also affects their health over a lifetime.  But genes alone are not the only factor contributing to the way an individual’s features emerge and perform. Things like how DNA is exposed—or not exposed—to the cellular machinery that carries it from code to reality are also vital to consider. The field of epigenetics is still rather young, and much effort is needed to go towards developing reliable and accurate techniques that could help to advance research further.

The brain is particularly compelling for epigenetic study because its function is tied not just to physical properties, but reflexes and behaviors as well. Jesse Dixon and Joseph Ecker, along with their respective teams from the Salk Institute, have been working together to combine and overlay two different methods of chromosomal analysis—one focused on chromosomal information, the other on methylation patterns—into a new technique that has the potential to pinpoint some of the gene regulatory elements present in specific cell types. Knowing how genes are regulated naturally leads to understanding what gets misregulated as part of the disease process.

Previously, chromosomal data was examined separately from methylation patterns. Researchers seeking to tie these two together would have to do so manually, which was not only time-consuming but also did not offer any sort of bigger picture understanding beyond the very specific hypotheses being posed by the researcher. In a way then, the scope of any findings was limited to just what the researcher knew to look for and detect. They could be a few loci away from a scientific takeaway and yet have no idea just how close they were.

Seeing this problem, Dixon and Ecker developed their sn-m3C-seq method, short for “single-nucleus methyl-3C sequencing,” which is an automated way to capture chromosomal structure as well as methylation information within the same cell. These two proprietary cell handling techniques are combined with new computational methods for the subsequent analysis.

The fact that this is automated makes it high-throughput, allowing for thousands of cells to be examined in one study. Plus, having the ability to examine both these features within the same cells enhances its validity. In fact, during their testing and development of this method, they applied it to over 4,200 human brain cells and were able to separate out neurons from glial cells.

As Dixon points out, “We know these features can vary a lot between cell types and there’s value in having both types of information together from the same cells. It really opens up our ability to understand what regulatory sequences are affecting which genes across a wide variety of cell types and tissues.”

Changes in these regulatory sequences, whether in the sequences themselves or how they are processed in cells, shed light on what drives diseases, from disorders of the brain—like depression or schizophrenia—all the way to those that may result from nervous dysfunction, such as some heart disease. Understanding what goes wrong and contributes to these conditions can help advise how medicine can intervene and correct individual cases, leading to a higher quality of life and longevity.

One key avenue for applying the results of Ecker and Dixon’s research could potentially be in understanding the factors that contribute to—and ways of intervening against—cancers in all types of cells, starting by first comparing healthy tissues versus cancerous ones.

Reference: September 9, 2019, “Salk scientists develop technique to reveal epigenetic features of cells in the brain.” Salk News, press release.

Source: Lee, Dong-Sung et al.Simultaneous profiling of 3D genome structure and DNA methylation in single human cells. Nature Methods volume 16, pages 999–1006 (2019).