Droplet-Based Microfluidics for Single Molecule/Single Cell Sequencing and Applications
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Cui, Nai Wen
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CitationCui, Nai Wen. 2019. Droplet-Based Microfluidics for Single Molecule/Single Cell Sequencing and Applications. Doctoral dissertation, Harvard University, Graduate School of Arts & Sciences.
AbstractIdentification of rare cells or molecules from a mixture population is important in biology such as identification of rare cancer cells or nucleic acid in early stage cancer diagnosis. Recent advances in droplet-based microfluidics and hydrogel barcoded microsphere to capture all the mRNA molecules in each cell in a single step enables scientists to identify cells based on their whole transcriptome information. However, due to the large number of sequencing reads required to cover the whole transcriptome, this limits the number of cells processed in one sequencing run. We address this problem by using a stepwise approach by first encapsulating single cell and lysis buffer together in a water-in-oil picoliter droplet, then amplifying only the target DNA/RNA molecule of interest in each droplet, pico-inject hydrogel barcoded microsphere into each droplet to tag the amplicons prior to next generation sequencing. We demonstrated the use of this technology by applying it to study how single tumor cells evolves over time at the nuclei RNA level by targeting multiple mutation sites. This will provide doctors a tool to examine multiple mutation information from a large amount of cell population, identify rare cancer cells and can provide unprecedented information to assist doctors in drug administration. In addition, we also demonstrated the broad use of this approach and developed a stepwise workflow to identify single Microsatellite DNA molecules with high fidelity, enabling identification of minor contributors in a mixture DNA sample. We demonstrated the power of this technology by applying this to a five-person mixture DNA sample, with the lowest person contributing less than 0.5% DNA in the mixture. This technology will be a powerful tool for applications that require accurate identification of rare molecules among high background noise, such as in forensics, paternity testing and microsatellite instability in early stage cancer diagnosis.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:42013159
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