Scientific Reports (May 2018)

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells

  • J. O. Andrews,
  • W. Conway,
  • W -K. Cho,
  • A. Narayanan,
  • J -H. Spille,
  • N. Jayanth,
  • T. Inoue,
  • S. Mullen,
  • J. Thaler,
  • I. I. Cissé

DOI
https://doi.org/10.1038/s41598-018-25454-0
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 10

Abstract

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Abstract We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.