New Data Filtering Tool Helps Identify Pathogenic Mutations

A new tool designed to assist geneticists to differentiate between pathogenic and harmless mutations is now available on the Internet.

The fraction of the genes that codes for proteins is called the exome, and genome wide analysis has revealed that while the DNA of a patient with a monogenic disease contains about 20,000 variations, only one or two are disease causing. Thus, it is that 58% of rare variants in the protein-coding exome of the general population are located in only 2% of the genes.

To help differentiate between the many harmless variations and the few that are linked to disease, investigators at the Rockefeller Institute (New York, NY, USA) developed the gene damage index (GDI). The GDI is a data analysis tool that weighs how frequently the gene is mutated in the general population and calculates the importance of a given gene in a specific disease group, including Mendelian disorders, cancer, autism, and primary immunodeficiencies.

The investigators compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing).

“To find a needle in the haystack, it helps to get rid of some of the hay,” said first author Dr. Yuval Itan, a researcher in the St. Giles Laboratory of Human Genetics of Infectious Disease at the Rockefeller Institute. “Filtering out the noise, the genes that pollute the data, is crucial. With this method, up to 60% of the irrelevant variants can be removed. The Gene Damage Index will help scientists more easily sort through the large amounts of data produced by next-generation sequencing.”

The GDI study was published in the November 3, 2015, issue of the journal Proceedings of the National Academy of Sciences of the United States of America (PNAS).

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Rockefeller Institute