Real-Time Verification of Individual’s Identity by DNA using New Software
Researchers at Columbia University and the New York Genome Center revealed on December 1, 2017, that they have developed a method to accurately identify individual and cell lines from their DNA.
Low cost DNA sequencers could improve research quality-control technology. The technology has multiple applications, which includes identifying victims in a mass disaster and analyzing crime scenes. Most immediate use of low cost sequencing is to detect mislabeled or contaminated cell lines in cancer experiments.
“Our method opens up new ways to use off-the-shelf technology to benefit society. We’re especially excited about the potential to improve cell-authentication in cancer research and potentially speed up the discovery of new treatments,” said the 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.
The software is designed to operate on the MinION, an instrument is small in size and it pulls in strands of DNA through its microscopic pores and analyses sequences of nucleotides. Although using the device researchers can study bacteria and viruses in the field, its high error-rate and large sequencing gaps have limited its use on human cells.
Initially, researchers use the MinION to sequence random strings of DNA from which they select individual variants. In second attempt, 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 with rapidly narrowing the search. Tests show the method can validate an individual’s identity after cross-checking between 60 and 300 variants.
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 in few minutes. While carrying out this, the MinION matched the readout of Zaaijer’s genome gleaned from a sample of cheek cells with a reference profile stored among 31,000 other genomes on the public database, DNA.land. Erlich’s identity was verified the same way, with initial sequencing done by Columbia students in the Ubiquitous Genomics class he and Zaaijer taught in 2015.
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