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Construction of a rapid microfluidic-based SNP genotyping (MSG) chip for ancestry inference. | LitMetric

Construction of a rapid microfluidic-based SNP genotyping (MSG) chip for ancestry inference.

Forensic Sci Int Genet

Key Laboratory of Forensic Genetics, National Engineering Laboratory for Forensic Science, Institute of Forensic Science, Beijing 100038, PR China; Shanxi Medical University, Shanxi Taiyuan 036000, PR China. Electronic address:

Published: July 2019


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Article Abstract

In forensics, ancestry inference can provide leads for criminal investigation. Therefore, the time needed to generate results is the first priority. Single nucleotide polymorphisms (SNPs) are widely used genetic markers for ancestry inference. In this study, a rapid microfluidic-based SNP genotyping (MSG) chip was established to detect 72 autosomal SNPs for ancestry inference of East Asian populations. The DNA template was infused into the chip and distributed into reaction chambers with pre-spotted primer pairs under centrifugation. After sealing the inlets/outlets and the connections among adjacent reaction chambers, the chip was placed onto a plate thermocycler for competitive allele-specific PCR. The SNP genotyping results were generated by analyzing the extracted fluorescence signal of each reaction chamber after PCR was completed. The detection process took less time (2.5 h) and was simpler than other SNP genotyping methods, such as SNaPshot and MassArray. To assess the performance of the chip, its accuracy, specificity, and sensitivity were evaluated. A total of 50 samples were genotyped using the chip, and the consistency of all of the typing and sequencing results was 100%. For ancestry inference of unknown individuals, a reference database of 3628 individuals from 57 populations was employed, and the ancestry origin of 110 test samples was inferred, demonstrating that the differentiation of East Asian subpopulations can be achieved through the MSG chip method. Overall, the MSG chip method established in this study can effectively be used for rapid and accurate ancestry inference.

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http://dx.doi.org/10.1016/j.fsigen.2019.04.006DOI Listing

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