TY - JOUR
T1 - Computational design and interpretation of single-RNA translation experiments
AU - Aguilera, Luis U.
AU - Raymond, William
AU - Fox, Zachary R.
AU - May, Michael
AU - Djokic, Elliot
AU - Morisaki, Tatsuya
AU - Stasevich, Timothy J.
AU - Munsky, Brian
N1 - Publisher Copyright:
© 2019 Aguilera et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2019/10/16
Y1 - 2019/10/16
N2 - Advances in fluorescence microscopy have introduced new assays to quantify live-cell translation dynamics at single-RNA resolution. We introduce a detailed, yet efficient sequence-based stochastic model that generates realistic synthetic data for several such assays, including Fluorescence Correlation Spectroscopy (FCS), ribosome Run-Off Assays (ROA) after Harringtonine application, and Fluorescence Recovery After Photobleaching (FRAP). We simulate these experiments under multiple imaging conditions and for thousands of human genes, and we evaluate through simulations which experiments are most likely to provide accurate estimates of elongation kinetics. Finding that FCS analyses are optimal for both short and long length genes, we integrate our model with experimental FCS data to capture the nascent protein statistics and temporal dynamics for three human genes: KDM5B, β-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (RSNAPSIM), to easily simulate the single-molecule translation dynamics of any gene sequence for any of these assays and for different assumptions regarding synonymous codon usage, tRNA level modifications, or ribosome pauses. RSNAPSIM is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git.
AB - Advances in fluorescence microscopy have introduced new assays to quantify live-cell translation dynamics at single-RNA resolution. We introduce a detailed, yet efficient sequence-based stochastic model that generates realistic synthetic data for several such assays, including Fluorescence Correlation Spectroscopy (FCS), ribosome Run-Off Assays (ROA) after Harringtonine application, and Fluorescence Recovery After Photobleaching (FRAP). We simulate these experiments under multiple imaging conditions and for thousands of human genes, and we evaluate through simulations which experiments are most likely to provide accurate estimates of elongation kinetics. Finding that FCS analyses are optimal for both short and long length genes, we integrate our model with experimental FCS data to capture the nascent protein statistics and temporal dynamics for three human genes: KDM5B, β-actin, and H2B. Finally, we introduce a new open-source software package, RNA Sequence to NAscent Protein Simulator (RSNAPSIM), to easily simulate the single-molecule translation dynamics of any gene sequence for any of these assays and for different assumptions regarding synonymous codon usage, tRNA level modifications, or ribosome pauses. RSNAPSIM is implemented in Python and is available at: https://github.com/MunskyGroup/rSNAPsim.git.
UR - http://www.scopus.com/inward/record.url?scp=85074242850&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1007425
DO - 10.1371/journal.pcbi.1007425
M3 - Article
C2 - 31618265
AN - SCOPUS:85074242850
SN - 1553-734X
VL - 15
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 10
M1 - e1007425
ER -