[A method for reliable detection of genomic point mutations based on single-cell target-sequencing].

Yi Chuan

Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai 200240, China.

Published: July 2020

AI Article Synopsis

  • - The research focuses on analyzing genomic point mutations to understand how tumor cells evolve, specifically using prostate basal cell carcinoma samples.
  • - Traditional methods involve bulk sampling, which can miss important low-frequency mutations since they analyze a mix of different cell types.
  • - The study developed a new single-cell resolution method for identifying mutations, successfully confirming genomic alterations in prostate BCC using optimized genome amplification techniques and targeted sequencing.

Article Abstract

The analysis of genomic point mutations is one of the research strategies to explore the clonal evolution of tumor cells. At present, clonal evolution of tumor cells is mainly determined by bulk sampling and sequencing of different sections of the tumor. Since this approach analyzes a mixture of different cell types, it may not accurately represent the clonal evolution of specific tumor cell populations and likely miss low frequency mutations, especially when the sequencing depths are not sufficient. To address this issue, we have developed a strategy to analyze genomic point mutations from prostate basal cell carcinoma (BCC) tissues at single-cell resolution. Firstly, we optimized the single-cell whole genome amplification procedure with HepG2 cells. Then the single cells from BCC tissue were captured by a microfluidic chip of Fluidigm and processed for whole-genome amplification. Both and genomic mutations were obtained by whole exome sequencing. Finally, we examined the genomic mutations through single-cell targeted amplification and Sanger sequencing. The established method successfully reconfirmed the mutations of and in BCC at single cell level. The strategy established in this study could provide a useful tool for determining the clonal evolution of tumor cells based on genomic mutations at single-cell resolution.

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http://dx.doi.org/10.16288/j.yczz.20-046DOI Listing

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