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10-Plex Digital Polymerase Chain Reaction with Four-Color Melting Curve Analysis for Simultaneous KRAS and BRAF Genotyping.

Tatsuo NakagawaJunko TanakaKunio HaradaAkiko ShiratoriYuzuru ShimazakiTakahide YokoiChihiro UematsuYoshinobu Kohara
Published in: Analytical chemistry (2020)
Digital PCR (dPCR) is a promising method for performing liquid biopsies that quantifies nucleic acids more sensitively than real-time PCR. However, dPCR shows large fluctuations in the fluorescence intensity of droplets or wells due to insufficient PCR amplification in the small partitions, limiting the multiplexing capability of using the fluorescence intensity. In this study, we propose a measurement method that combines dPCR with melting curve analysis for highly multiplexed genotyping. A sample was digitized into a silicon chip with up to 2 × 104 wells in which asymmetric PCR was performed to obtain more single-stranded amplicons that were complementary to molecular beacon probes. Fluorescence images were captured while controlling the temperature of the chip, and the melting curve was measured for each well. Then, genotyping was performed by using the fluorescence intensity, the dye color of the probe, and the melting temperature (Tm). Because the Tm of the PCR products is not highly dependent on the amplification efficiency of PCR, genotyping accuracy is improved by using Tm values, enabling highly multiplexed genotyping. The concept was confirmed by simultaneously identifying wild-type KRAS, BRAF, and eight mutants of these genes (G12D, G12R, G12V, G13D, G12A, G12C, G12S, and V600E) through four-color melting curve analysis. To the best of our knowledge, this is the first demonstration of the genotyping of 10 DNA groups including single mutations of cancer-related genes by combining dPCR with four-color melting curve analysis.
Keyphrases
  • high resolution
  • wild type
  • high throughput
  • genome wide
  • single molecule
  • real time pcr
  • healthcare
  • dna methylation
  • high intensity
  • living cells
  • young adults
  • papillary thyroid
  • metastatic colorectal cancer
  • data analysis