New system can identity people from their DNA in minutes

Researchers have developed a software system to accurately identify people and cell lines from their DNA in a matter of minutes.

The technology has a wide range of applications, but its most immediate use could be to flag mislabelled or contaminated cell lines in cancer experiments, according to the study published in the journal eLife.

"Our method opens up new ways to use off-the-shelf technology to benefit society," said Yaniv Erlich, from the Columbia University in the US.

"We're especially excited about the potential to improve cell-authentication in cancer research and potentially speed up the discovery of new treatments," he said.

The software is designed to run on the MinION, an instrument the size of a credit card that pulls in strands of DNA through its microscopic pores and reads out sequences of nucleotides, or the DNA letters A, T, C, G.

The device has made it possible for researchers to study bacteria and viruses in the field, but its high error-rate and large sequencing gaps have, until now, limited its use on human cells with their billions of nucleotides.

In an innovative two-step process, the researchers outlined a new way to use the MinION and the abundance of human genetic data now online to validate the identity of people and cells by their DNA with near-perfect accuracy.

First, they used the MinION to sequence random strings of DNA, from which they selected individual variants, which are nucleotides that vary from person to person and make them unique.

Then, they used an algorithm to randomly compare this mix of variants with corresponding variants in other genetic profiles on file.

With each cross-check, the algorithm updates the likelihood of finding a match, rapidly narrowing the search.

Tests showed that the method can validate an individual's identity after cross-checking between 60 and 300 variants.

"Using our method, one needs only a few DNA reads to infer a match to an individual in the database," said Sophie Zaaijer, from the New York Genome Center in the US.