![]() ![]() ![]() Gene expression analysis of individual cells enables characterization of heterogeneous and rare cell populations, yet widespread implementation of existing single-cell gene analysis techniques has been hindered due to limitations in scale, ease, and cost. Here, we present a novel microdroplet-based, one-step reverse-transcriptase polymerase chain reaction (RT-PCR) platform and demonstrate the detection of three targets simultaneously in over 100,000 single cells in a single experiment with a rapid read-out. Our customized reagent cocktail incorporates the bacteriophage T7 gene 2.5 protein to overcome cell lysate-mediated inhibition and allows for one-step RT-PCR of single cells encapsulated in nanoliter droplets. The specificity of primers and probes was verified using the. Ralph Lauren Outlet Online Nike Vapormax Michael Kors Outlet Coach Factory Outlet Nike Lebron 15 Kate Spade. Fluorescent signals indicative of gene expressions are analyzed using a probabilistic deconvolution method to account for ambient RNA and cell doublets and produce single-cell gene signature profiles, as well as predict cell frequencies within heterogeneous samples. The sequences of the primers and probes for expression analysis of the candidate genes were designed using Beacon designer 7.0 software (Premier Biosoft, San Francisco, CA, USA), and the nucleotide sequences of the Hcn1, Dnmt1, and Th genes, and the reference genes Sars and Psmd6. premier biosoft beacon designer 8.02 versions. We also developed a simulation model to guide experimental design and optimize the accuracy and precision of the assay. Using mixtures of in vitro transcripts and murine cell lines, we demonstrated the detection of single RNA molecules and rare cell populations at a frequency of 0.1%. This low cost, sensitive, and adaptable technique will provide an accessible platform for high throughput single-cell analysis and enable a wide range of research and clinical applications. ![]() Single-cell analysis techniques are critical to distinguish differences between individual cells within seemingly homogeneous populations, such as divergent cell cycle status, cell lineage bias, or other cellular processes. ![]()
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