Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry

Mohamed N.M. Bahrudeen, Vatsala Chauhan, Cristina S.D. Palma, Samuel M.D. Oliveira, Vinodh K. Kandavalli, Andre S. Ribeiro

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
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Abstract

Estimating the statistics of single-cell RNA numbers has become a key source of information on gene expression dynamics. One of the most informative methods of in vivo single-RNA detection is MS2d-GFP tagging. So far, it requires microscopy and laborious semi-manual image analysis, which hampers the amount of collectable data. To overcome this limitation, we present a new methodology for quantifying the mean, standard deviation, and skewness of single-cell distributions of RNA numbers, from flow cytometry data on cells expressing RNA tagged with MS2d-GFP. The quantification method, based on scaling flow-cytometry data from microscopy single-cell data on integer-valued RNA numbers, is shown to readily produce precise, big data on in vivo single-cell distributions of RNA numbers and, thus, can assist in studies of transcription dynamics.

Original languageEnglish
Article number105745
JournalJournal of Microbiological Methods
Volume166
DOIs
Publication statusPublished - 2019
Publication typeA1 Journal article-refereed

Keywords

  • Flow cytometry
  • MS2d-GFP RNA tagging
  • Single-cell RNA numbers
  • Time-lapse microscopy

Publication forum classification

  • Publication forum level 1

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