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Related Concept Videos

RNA-seq03:21

RNA-seq

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
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Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
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RNA-Seq following PCR-based sorting reveals rare cell transcriptional signatures.

Maurizio Pellegrino1, Adam Sciambi1, Jamie L Yates1

  • 1Mission Bio, Inc., 953 Indiana St., San Francisco, California, 94107, USA.

BMC Genomics
|May 19, 2016
PubMed
Summary

PCR-activated cell sorting (PACS) enables high-throughput isolation and transcriptional profiling of rare cell subtypes. This novel cytometry method reveals gene expression profiles previously obscured in bulk analysis, advancing rare cell research.

Keywords:
Cell sortingDropletsGene expressionHeterogeneityMicrofluidicsPCRSingle-cellTranscriptome

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Area of Science:

  • Single-cell biology
  • Molecular profiling
  • Cytometry

Background:

  • Rare cell subtypes significantly impact health and disease but are often missed by bulk analysis.
  • Existing single-cell tools like FACS and FISH-FC have limitations in identifying and characterizing rare cell subpopulations.
  • Cellular heterogeneity requires advanced methods for accurate detection and analysis.

Purpose of the Study:

  • To extend the capabilities of PCR-activated cell sorting (PACS) for high-dimensional molecular profiling.
  • To demonstrate the utility of PACS for transcriptional profiling of rare cell subtypes.
  • To enable deeper biological insight into complex cellular populations.

Main Methods:

  • Utilized PCR-activated cell sorting (PACS) with single-cell TaqMan PCR in microfluidic droplets.
  • Employed a random priming RNA-Seq strategy for transcriptome measurements on PACS-sorted cells.
  • Performed single-cell expression analysis to confirm differentially expressed genes.

Main Results:

  • PACS enabled high-dimensional molecular profiling of targeted cells.
  • High-fidelity transcriptome measurements were obtained from PACS-sorted prostate cancer cells.
  • Revealed previously obscured prostate cancer gene expression profiles and confirmed differentially expressed genes.

Conclusions:

  • PACS requires minimal sample processing and uses readily available TaqMan assays for high-sensitivity isolation.
  • Validated next-generation sequencing of mRNA from PACS-isolated cells.
  • PACS is well-suited for transcriptional profiling of rare cells in complex populations for maximal biological insight.