Issue 8, 2017, Issue in Progress

Automated melting curve analysis in droplet microfluidics for single nucleotide polymorphisms (SNP) genotyping

Abstract

An integrated microchip platform with automated analysis capability for DNA melting curves is developed for Single Nucleotide Polymorphism (SNP) genotyping applications. The microchip contains fluidic channels where genomic DNA samples are encapsulated into a series of droplets and transported through a detection region with a stable temperature gradient. As the temperature is elevated from 60 °C to 85 °C, the DNA strains denature and the associated fluorescence signals decay with this relationship being acquired as the melting curve. The droplets serve as discrete reactors to conduct DNA melting curve analysis in the liquid phase, eliminating the need for immobilization of reagents. They provide the advantage of signal homogeneity, which reduces the signal fluctuations, and thus the signal-to-noise ratio is improved. In addition, a droplet detection and tracking software system which can identify the droplets, records the fluorescence intensities, plots the melting curves, and finds the melting temperatures, is developed making automated SNP genotyping possible. The platform has been verified with genomic DNA from Landrace sows and shown successful SNP discrimination from homozygotes and heterozygotes which demonstrates its potential to conduct on-site SNP genotyping for disease research, medical diagnostics, agriculture, and farm animal reproduction.

Graphical abstract: Automated melting curve analysis in droplet microfluidics for single nucleotide polymorphisms (SNP) genotyping

Article information

Article type
Paper
Submitted
08 Nov 2016
Accepted
19 Dec 2016
First published
16 Jan 2017
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2017,7, 4646-4655

Automated melting curve analysis in droplet microfluidics for single nucleotide polymorphisms (SNP) genotyping

F.-W. Liu, S.-T. Ding, E.-C. Lin, Y.-W. Lu and J.-S. R. Jang, RSC Adv., 2017, 7, 4646 DOI: 10.1039/C6RA26484K

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