In the science-fiction movie Gattaca, visitors only clear security if a blood test and readout of their genetic profile matches the sample on file. Now, cheap DNA sequencers and custom software could make real-time DNA-authentication a reality.
Researchers at Columbia University and the New York Genome Center have developed a method to quickly and accurately identify people and cell lines from their DNA. The technology could have multiple applications, from identifying victims in a mass disaster to analyzing crime scenes. But its most immediate use could be to flag mislabeled or contaminated cell lines in cancer experiments, a major reason that studies are later invalidated. The discovery is described in the latest issue of eLife.
“Our method opens up new ways to use off-the-shelf technology to benefit society,” said the study’s senior author Yaniv Erlich, a computer science professor at Columbia Engineering, an adjunct core member at NYGC, and a member of Columbia’s Data Science Institute. “We’re especially excited about the potential to improve cell-authentication in cancer research and potentially speed up the discovery of new treatments.”
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 outline a new way to use the $1,000 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 use the MinION to sequence random strings of DNA, from which they select individual variants, which are nucleotides that vary from person to person and make them unique. Then, they use a Bayesian 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 show the method can validate an individual’s identity after cross-checking between 60 and 300 variants, the researchers report. Within minutes, it verified the identity of the study’s lead author, Sophie Zaaijer, a former member of NYGC and now a postdoctoral researcher at Cornell Tech.
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