Quantifying how post-transcriptional noise and gene copy number variation bias transcriptional parameter inference from mRNA distributions

X Fu, HP Patel, S Coppola, L Xu, Z Cao, TL Lenstra… - Elife, 2022 - elifesciences.org
Transcriptional rates are often estimated by fitting the distribution of mature mRNA numbers
measured using smFISH (single molecule fluorescence in situ hybridization) with the …

[HTML][HTML] Quantifying and correcting bias in transcriptional parameter inference from single-cell data

R Grima, PM Esmenjaud - Biophysical Journal, 2024 - cell.com
The snapshot distribution of mRNA counts per cell can be measured using single-molecule
fluorescence in situ hybridization or single-cell RNA sequencing. These distributions are …

[HTML][HTML] Cell-cycle dependence of transcription dominates noise in gene expression

CJ Zopf, K Quinn, J Zeidman… - PLoS computational …, 2013 - journals.plos.org
The large variability in mRNA and protein levels found from both static and dynamic
measurements in single cells has been largely attributed to random periods of transcription …

Effects of cell cycle variability on lineage and population measurements of messenger RNA abundance

R Perez-Carrasco, C Beentjes… - Journal of the Royal …, 2020 - royalsocietypublishing.org
Many models of gene expression do not explicitly incorporate a cell cycle description. Here,
we derive a theory describing how messenger RNA (mRNA) fluctuations for constitutive and …

[HTML][HTML] Quantifying intrinsic and extrinsic variability in stochastic gene expression models

A Singh, M Soltani - Plos one, 2013 - journals.plos.org
Genetically identical cell populations exhibit considerable intercellular variation in the level
of a given protein or mRNA. Both intrinsic and extrinsic sources of noise drive this variability …

[HTML][HTML] Using a single fluorescent reporter gene to infer half-life of extrinsic noise and other parameters of gene expression

M Komorowski, B Finkenstädt, D Rand - Biophysical journal, 2010 - cell.com
Fluorescent and luminescent proteins are often used as reporters of transcriptional activity.
Given the prevalence of noise in biochemical systems, the time-series data arising from …

[HTML][HTML] BayFish: Bayesian inference of transcription dynamics from population snapshots of single-molecule RNA FISH in single cells

M Gómez-Schiavon, LF Chen, AE West, NE Buchler - Genome biology, 2017 - Springer
Single-molecule RNA fluorescence in situ hybridization (smFISH) provides unparalleled
resolution in the measurement of the abundance and localization of nascent and mature …

[HTML][HTML] A stochastic model of the yeast cell cycle reveals roles for feedback regulation in limiting cellular variability

D Barik, DA Ball, J Peccoud… - PLoS computational …, 2016 - journals.plos.org
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent
protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system …

LTMG: a novel statistical modeling of transcriptional expression states in single-cell RNA-Seq data

C Wan, W Chang, Y Zhang, F Shah, X Lu… - Nucleic acids …, 2019 - academic.oup.com
A key challenge in modeling single-cell RNA-seq data is to capture the diversity of gene
expression states regulated by different transcriptional regulatory inputs across individual …

[HTML][HTML] Accounting for experimental noise reveals that mRNA levels, amplified by post-transcriptional processes, largely determine steady-state protein levels in yeast

G Csárdi, A Franks, DS Choi, EM Airoldi… - PLoS …, 2015 - journals.plos.org
Cells respond to their environment by modulating protein levels through mRNA transcription
and post-transcriptional control. Modest observed correlations between global steady-state …