Hunting For Disease Markers In ‘Junk’ DNA

An international team has developed a speedy new method to analyze thousands of noncoding variants and their links to diseases like diabetes.

AsianScientist (Aug. 30, 2021) – Genetic analysis has just leveled up with a significant speed boost. A new high-throughput technique described in Nature systematically analyzes hundreds of thousands of noncoding genetic variants, revealing their roles in human disease.

Popularly known as ‘junk’ DNA, regions of the genome that do not carry instructions for building proteins are just as linked to disease as the protein-coding genes. By controlling the binding of transcription factors to the coding genes, the noncoding variants can switch genes on or off, affecting protein synthesis and potentially the emergence of healthy or sick conditions.

While scientists are now aware of these functions, it’s proven a long-lasting challenge to pinpoint these noncoding sequences and uncover how exactly they drive diseases like cancer and diabetes. Studies have typically taken two to three years to complete, shedding light on only a few variants at a time.

Together with international collaborators, Dr. Yan Jian from the City University of Hong Kong and China’s Northwest University developed a high-throughput biological assay to accelerate analysis of these noncoding variants. The technique, called single-nucleotide polymorphism evaluation by systematic evolution of ligands by exponential enrichment (SNP-SELEX), rapidly evaluates the binding between the transcription factors and the noncoding DNA sequences.

By analyzing millions of possible interactions in one test, SNP-SELEX lends insight into the strength of binding and how different noncoding variants affect such binding activity. According to the team, all this data can be used to build better disease models, allowing scientists to dissect the genetic mechanisms underlying diseases and identify biomarkers for better therapies.

To showcase the SNP-SELEX method at work, the researchers studied variants from regions of the genome linked to type II diabetes. Out of 270 transcription factors and nearly 100,000 variants, they found a noncoding variant that impacted the DNA binding of a transcription factor. Moreover, the SNP-SELEX data showed that these were involved in regulatory mechanisms for fat levels in the blood, leading to a higher risk of diabetes.

For the team, this study is but a snapshot of the capabilities of SNP-SELEX, as they only focused on gene regions linked to one disease. By expanding the method to investigate other areas of the genome, they hope to unravel the molecular mysteries of genetic diseases within a much shorter timeframe.

“Understanding the molecular functions of the noncoding variants will help us find out why people carrying these mutations are more susceptible to genetic diseases. This will help us develop methods or strategies to prevent, to detect or to cure the diseases early,” said Yan.

The article can be found at: Yan et al. (2021) Systematic Analysis of Binding of Transcription Factors to Noncoding Variants.


Source: City University of Hong Kong; Photo: Shutterstock.
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