Repository logo
Log in(current)
Repository logoMIT Open ScholarshipDSpace@MIT
  1. Home
  2. MIT Open Access Articles
  3. MIT Open Access Articles
  4. qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells

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

Thumbnail Image
Download
Name

s41598-018-25454-0.pdf

Size

2.41 MB

Format

Adobe PDF

Checksum (MD5)

aecf5deabe6b6a96210cac9a54cc7f43

Download all files submitted through automated deposit
sword-2018-10-11.original.zip (2.08 MB)
Author(s)
Andrews, James Owen
•
Conway, W.
•
Cho, Won-ki
•
Narayanan, Arjun
•
Spille, Jan Hendrik
•
Jayanth, Namrata
•
Inoue, Takuma
•
Thaler, Jesse
•
Cisse, Ibrahim I
•
Mullen, Susan
Date Issued
May 2018
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Andrews, J. O., et al. “QSR: A Quantitative Super-Resolution Analysis Tool Reveals the Cell-Cycle Dependent Organization of RNA Polymerase I in Live Human Cells.” Scientific Reports, vol. 8, no. 1, Dec. 2018. © 2018 The Authors
Version
Final published version
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.
MIT Department
Massachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciences
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution 4.0 International License
http://creativecommons.org/licenses/by/4.0/
Persistent DSpace Link
http://hdl.handle.net/1721.1/118788
DOI of Published Version
https://doi.org/10.1038/s41598-018-25454-0
Repository logo
PrivacyPermissionsAccessibilityContact us
Repository logo
Notify us about copyright concerns.