Washington scientists in a stage of advancement come a new technology that allows them to read and interpret the human genome, which can become of great help in the creation of new drug targets for the treatment of many genetic diseases. The calculation method, called TargetFinder, can predict where non-coding DNA – DNA that does not code for proteins – interacts with genes. This technology helps connect researchers mutations in the genome called ‘dark matter’ genes potentially affecting showing new therapeutic targets for genetic disorders.
Researchers at the Gladstone Institutes in the United States observed fragments of DNA called antisense enhancers. Enhancers act as an instruction manual for a gene, dictating when and where a gene is activated. Genes can be separated from their enhancers for long stretches of DNA containing many genes.
“Most genetic mutations that are associated with the disease occur in enhancers, so a very important area of study,” said Katherine Pollard, a senior researcher at the Gladstone Institutes. “So far, we struggled to understand how distant enhancers find genes that act,” Pollard said.
Scientists originally believed that primarily affect enhancers gene close to them. However, the new study showed that in a DNA chain, enhancers can be millions of letters influence gene away, ignoring the genes in the middle.
When a promoter is far from the gene affects, the two are connected by forming a loop in three dimensions, as a bow in the genome. Using machine learning technology, researchers analyzed hundreds of existing data sets six different cell types to look for patterns in the genome that identify where a gene interact and enhancer.
They discovered several patterns that exist in the ties that bind enhancers genes. This pattern accurately predicted whether an interaction between genes and enhancer produced 85 percent of the time. “It is remarkable that we can predict the complex three-dimensional interactions from relatively simple data,” said Sean Whalen, biostatistician Gladstone.
Conducting laboratory experiments to identify this gene-Enhancer can take millions of dollars and years of research. The new computational approach is a much cheaper and less time to identify connections enhancer genes in the genome.
The technology also offers an idea of how DNA loops form and how they could break into the disease. The study was published in the journal Nature Genetics.