Algorithm pinpoints potential disease-causing variants in non-coding regions of human genome

Researchers from Children's Hospital of Philadelphia (CHOP) and the Perelman School of Medicine at the University of Pennsylvania (Penn Medicine) have successfully employed an algorithm to identify potential mutations which increase disease risk in the noncoding regions of our DNA, which make up the vast majority of the human genome.

The findings could serve as the basis for detecting disease-associated variants in a range of common diseases. The findings were published online by the American Journal of Human Genetics in a paper titled “Characterization of non-coding variants associated with transcription factor binding through ATAC-seq-defined footprint QTLs in liver.”

While certain sections of the human genome code for proteins to carry out a variety of essential biological functions, more than 98% of the genome does not code for proteins. However, disease-associated variants can also be found in these noncoding regions of the genome, which often control when proteins are made or “expressed.”

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