Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Personal genomics

A tool to interpret tricky mutations

Subjects

Researchers have developed software to predict whether certain genetic variants are harmful.

The effects of most mutations are unclear, especially for those in the 99% of the genome that does not code for proteins. Chris Tyler-Smith at the Sanger Institute in Hinxton, UK, and Mark Gerstein at Yale University in New Haven, Connecticut, and their colleagues took non-coding regions that had been identified as functional in a large-scale genomics project and used sequencing data from more than 1,000 people to catalogue how these regions varied in healthy individuals.

This revealed likely patterns of harmful mutations, such as those in DNA sequences to which regulatory proteins bind. The scientists incorporated the patterns into a predictive tool and applied it to genomes from cancer biopsies. This found nearly 100 non-coding variants that could contribute to the disease.

Science 342, 84 (2013)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

A tool to interpret tricky mutations. Nature 502, 144 (2013). https://doi.org/10.1038/502144d

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/502144d

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing