Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry
Bahrudeen, Mohamed N.M.; Chauhan, Vatsala; Palma, Cristina S.D.; Oliveira, Samuel M.D.; Kandavalli, Vinodh K.; Ribeiro, Andre S. (2019)
Bahrudeen, Mohamed N.M.
Chauhan, Vatsala
Palma, Cristina S.D.
Oliveira, Samuel M.D.
Kandavalli, Vinodh K.
Ribeiro, Andre S.
2019
105745
Julkaisun pysyvä osoite on
https://urn.fi/urn:nbn:fi:tuni-201910294177
https://urn.fi/urn:nbn:fi:tuni-201910294177
Kuvaus
Peer reviewed
Tiivistelmä
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.
Kokoelmat
- TUNICRIS-julkaisut [15313]