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A microfluidic array for parallelized single-cell gene expression profiling

  • H. Sun
  • , T. Olsen
  • , J. Zhu
  • , B. Ponnaiya
  • , S. Amundson
  • , D. Brenner
  • , J. Tao
  • , Q. Lin*
  • *Corresponding author for this work
  • Columbia University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The ability to correlate single-cell genetic information with cellular phenotypes holds the potential to interpret disease pathways that is not attainable from bulk analysis. Microfluidics is attractive for single-cell analysis due to precise handling, low risk of contamination, reduced reagent cost and parallelized operation. We present an integrated microfluidic array for parallelized single-cell messenger RNA (mRNA) transcriptional analysis using quantitative reverse transcription polymerase chain reaction (RT-qPCR). The transcriptional levels of individual human cancer cells (MCF-7) were assayed for the induction of CDKN1A using a Taqman probe/primer set in the array.

Original languageEnglish
Title of host publication18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014
PublisherChemical and Biological Microsystems Society
Pages799-801
Number of pages3
ISBN (Electronic)9780979806476
StatePublished - 2014
Event18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014 - San Antonio, United States
Duration: 26 Oct 201430 Oct 2014

Publication series

Name18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014

Conference

Conference18th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2014
Country/TerritoryUnited States
CitySan Antonio
Period26/10/1430/10/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Microfluidic array
  • RT-qPCR
  • Single-cell genetic analysis

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