Computational method developed to map chromosome folding in 3D

University of Virginia School of Medicine, US, scientists have developed new resources to analyse chromosomes that could aid the battle against cancer and advance cutting-edge genomics research.

The researchers developed a new computational method to map the folding patterns of chromosomes in three dimensions (3D) from experimental data. This is important because the configuration of genetic material inside chromosomes affects how genes work. In cancer, that configuration can go wrong, so scientists want to understand the genome architecture of both healthy cells and cancerous ones. This will help them develop better ways to treat and prevent cancer, in addition to advancing many other areas of medical research.

The new approach to mapping the folding of the genome is called BART3D. It compares available 3D configuration data about one region of a chromosome with many of its neighbours. It can then extrapolate from this comparison to fill in blanks in the blueprints of genetic material using Binding Analysis for Regulation of Transcription (BART), a novel algorithm. The result is a map that offers unprecedented insights into how genes interact with the transcriptional regulators that control their activity. Identifying these regulators helps scientists understand what turns particular genes on and off – information they can use in the battle against cancer and other diseases.

Using their new approaches, the team have unearthed useful data and they are making their techniques and findings available to their fellow scientists. To advance cancer research, they have built an interactive website that brings together their findings with vast amounts of data from other resources.

“The folding pattern of the genome is highly dynamic; it changes frequently and differs from cell to cell. Our new method aims to link this dynamic pattern to the control of gene activities,” said Dr Chongzhi Zang, the lead researcher. “A better understanding of this link can help unravel the genetic cause of cancer and other diseases and can guide future drug development for precision medicine.”

The team built the database to advance research into 15 different types of cancer, including breast, lung, colorectal and prostate cancer. Scientists can search the interactive database to see which regulators are more active and which are less active in each cancer.

“While a cancer researcher can browse our database to screen potential drug targets, any biomedical scientist can use our web server to analyse their own genetic data,” Zang said. “We hope that the tools and resources we develop can benefit the whole biomedical research community by accelerating scientific discoveries and future therapeutic development.”

The study was published in NAR Cancer.