Scientists have identified nearly 100 genetic variants implicated in the development of deadly
cancers such as breast cancer and prostate cancer.
The new method designed by the team, identified these variants in the under-explored regions of DNA that do not code for proteins, but instead influence activity of other genes.
As even more whole genome sequences become available, this approach can be applied to find any potential disease-causing variant in the non-coding regions of the genome, researchers said.
Researchers can now identify DNA regions within non-coding DNA, the major part of the genome that is not translated into a protein, where mutations can cause diseases
such as cancer.
Their approach reveals many potential genetic variants within non-coding DNA that drive the development of a variety of different cancers. This approach has great potential to
find other disease-causing variants.
Recent studies have emphasised the biological value of the non-coding regions, previously considered ‘junk’ DNA, in the regulation of proteins.
“Our technique allows scientists to focus in on the most functionally important parts of the non-coding regions of the genome,” said Professor Mark Gerstein, senior author from the
University of Yale.
Protein-coding genes play a crucial role in human survival and fitness, and are under strong ‘purifying’ selection, which removes variation, researchers said.
The team found that some non-coding DNA regions showed almost the same low levels of variation as protein-coding genes, and called these ‘ultrasensitive’ regions.
Within the ultrasensitive regions, they looked at specific single DNA letters that, when altered, caused the greatest disturbance to the genetic region.
If this non-coding, ultrasensitive region is central to a network of many related genes, variation can cause a greater knock-on effect, resulting in disease, researchers said.
They integrated all this information to develop a computer workflow known as FunSeq. This system prioritises genetic variants in the non-coding regions based on their predicted impact on human disease.
The team applied FunSeq to 90 cancer genomes including breast cancer, prostate cancer and brain tumours, and found nearly 100 potential non-coding cancer driving variants.
In the breast cancer genomes, for example, they found a single DNA letter change that seems to have great impact on the development of breast cancer.
The study was published in the journal Science.