Transient power-law behaviour following induction distinguishes between competing models of stochastic gene expression DOI Creative Commons
Andrew G. Nicoll, Juraj Szavits-Nossan, M. R. Evans

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 22, 2025

Abstract What features of transcription can be learnt by fitting mathematical models gene expression to mRNA count data? Given a suite models, data selects an optimal one, thus identifying probable transcriptional mechanism. Whilst attractive, the utility this methodology remains unclear. Here, we sample steady-state, single-cell distributions from parameters in physiological range, and show they cannot used confidently estimate number inactive states, i.e. rate-limiting steps initiation. Distributions over 99% parameter space generated using with 2, 3, or 4 states well fit one single state. However, that for many minutes following induction, eukaryotic cells increase mean obeys power law whose exponent equals sum visited initial active state post-transcriptional processing steps. Our study shows estimation sufficient determine lower bound on total regulatory initiation, splicing, nuclear export.

Language: Английский

Direct Comparative Analyses of 10X Genomics Chromium and Smart-Seq2 DOI Creative Commons
Xiliang Wang, Yao He, Qiming Zhang

et al.

Genomics Proteomics & Bioinformatics, Journal Year: 2021, Volume and Issue: 19(2), P. 253 - 266

Published: March 2, 2021

Abstract Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently scRNA-seq platforms, yet there only a few thorough systematic comparisons their advantages limitations. Here, by directly comparing data generated these platforms from same samples CD45− cells, we systematically evaluated features using wide spectrum analyses. detected more genes in cell, especially low abundance transcripts as well alternatively spliced transcripts, but captured higher proportion mitochondrial genes. composite also resembled bulk RNA-seq more. For 10X-based data, observed noise mRNAs with expression levels. Approximately 10%−30% all both were non-coding genes, long RNAs (lncRNAs) accounting 10X. displayed severe dropout problem, lower However, 10X-data can detect rare cell types given its ability to cover large number In addition, each platform distinct groups differentially expressed between clusters, indicating different characteristics technologies. Our study promotes better understanding offers basis an informed choice widely

Language: Английский

Citations

246
Intrinsic Dynamics of a Human Gene Reveal the Basis of Expression Heterogeneity DOI Creative Commons
Joseph Rodriguez, Gang Ren, Christopher R. Day

et al.

Cell, Journal Year: 2018, Volume and Issue: 176(1-2), P. 213 - 226.e18

Published: Dec. 13, 2018

Language: Английский

Citations

227
What’s Luck Got to Do with It: Single Cells, Multiple Fates, and Biological Nondeterminism DOI Creative Commons
Orsolya Symmons, Arjun Raj

Molecular Cell, Journal Year: 2016, Volume and Issue: 62(5), P. 788 - 802

Published: June 1, 2016

Language: Английский

Citations

197
Cycling through developmental decisions: how cell cycle dynamics control pluripotency, differentiation and reprogramming DOI Open Access
Abdenour Soufi, Stephen Dalton

Development, Journal Year: 2016, Volume and Issue: 143(23), P. 4301 - 4311

Published: Nov. 29, 2016

A strong connection exists between the cell cycle and mechanisms required for executing fate decisions in a wide-range of developmental contexts. Terminal differentiation is often associated with exit, whereas switches are frequently linked to transitions dividing cells. These phenomena have been investigated context reprogramming, trans-differentiation but underpinning molecular remain unclear. Most progress address has made pluripotent stem cells, which transition through mitosis G1 phase crucial establishing window opportunity pluripotency exit initiation differentiation. This Review will summarize recent developments this area place them broader that implications wide range scenarios.

Language: Английский

Citations

188
Analytical distributions for detailed models of stochastic gene expression in eukaryotic cells DOI Creative Commons
Zhixing Cao, Ramon Grima

Proceedings of the National Academy of Sciences, Journal Year: 2020, Volume and Issue: 117(9), P. 4682 - 4692

Published: Feb. 18, 2020

Significance The random nature of gene expression is well established experimentally. Mathematical modeling provides a means understanding the factors leading to observed stochasticity. In this article, we extend classical two-state model stochastic mRNA dynamics include considerable number salient features single-cell biology, such as cell division, replication, maturation, dosage compensation, and growth-dependent transcription. By biologically relevant approximations, obtain expressions for time-dependent distributions protein numbers. These provide insight into how fluctuations are modified controlled by complex intracellular processes.

Language: Английский

Citations

168
RNA velocity unraveled DOI Creative Commons
Gennady Gorin, Meichen Fang, Tara Chari

et al.

PLoS Computational Biology, Journal Year: 2022, Volume and Issue: 18(9), P. e1010492 - e1010492

Published: Sept. 12, 2022

We perform a thorough analysis of RNA velocity methods, with view towards understanding the suitability various assumptions underlying popular implementations. In addition to providing self-contained exposition mathematics, we undertake simulations and controlled experiments on biological datasets assess workflow sensitivity parameter choices biology. Finally, argue for more rigorous approach velocity, present framework Markovian that points directions improvement mitigation current problems.

Language: Английский

Citations

117
Cell cycle proliferation decisions: the impact of single cell analyses DOI Creative Commons
Jacob P. Matson, Jeanette Gowen Cook

FEBS Journal, Journal Year: 2016, Volume and Issue: 284(3), P. 362 - 375

Published: Sept. 16, 2016

Cell proliferation is a fundamental requirement for organismal development and homeostasis. The mammalian cell division cycle tightly controlled to ensure complete precise genome duplication segregation of replicated chromosomes daughter cells. onset DNA replication marks an irreversible commitment division, the accumulated efforts many decades molecular cellular studies have probed this decision, commonly called restriction point. Despite long‐standing conceptual framework point progression through G1 phase into S or exit from quiescence (G0), recent technical advances in quantitative single analysis cells provided new insights. Significant intercellular heterogeneity revealed by discovery discrete subpopulations proliferating cultures suggests need even more nuanced understanding decisions. In review, we describe some developments field made possible experimental approaches.

Language: Английский

Citations

166
Modulation of transcriptional burst frequency by histone acetylation DOI Creative Commons

Damien Nicolas,

Benjamin Zoller, David M. Suter

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2018, Volume and Issue: 115(27), P. 7153 - 7158

Published: June 18, 2018

Many mammalian genes are transcribed during short bursts of variable frequencies and sizes that substantially contribute to cell-to-cell variability. However, which molecular mechanisms determine bursting properties remains unclear. To probe putative mechanisms, we combined temporal analysis transcription along the circadian cycle with multiple genomic reporter integrations, using both short-lived luciferase live microscopy single-molecule RNA-FISH. Using Bmal1 promoter as our model, observed rhythmic resulted predominantly from variations in burst frequency, while position changed size. Thus, frequency size independently modulated transcription. We then found histone-acetylation level covaried being greatest at peak expression lowest trough expression, remaining unaffected by location. In addition, specific deletions ROR-responsive elements led constitutively elevated histone acetylation frequency. investigated suggested link between dCas9p300-targeted modulation acetylation, revealing levels influence more than The correlation was also endogenous embryonic stem cell fate genes. data suggest acetylation-mediated control is a common mechanism gene expression.

Language: Английский

Citations

150
What shapes eukaryotic transcriptional bursting? DOI

Damien Nicolas,

Nick E. Phillips,

Félix Naef

et al.

Molecular BioSystems, Journal Year: 2017, Volume and Issue: 13(7), P. 1280 - 1290

Published: Jan. 1, 2017

Isogenic cells in a common environment present large degree of heterogeneity gene expression. Part this variability is attributed to transcriptional bursting: the stochastic activation and inactivation promoters that leads discontinuous production mRNA. The diversity bursting patterns displayed by different genes suggests existence connection between regulation. Experimental strategies such as single-molecule RNA FISH, MS2-GFP or short-lived protein reporters allow quantification comparison kinetics conditions, allowing therefore identification molecular mechanisms modulating bursting. In review we recapitulate impact on aspects transcription chromatin environment, nucleosome occupancy, histone modifications, number affinity regulatory elements, DNA looping factor availability. More specifically, examine their role tuning burst size frequency. While some involved marks can affect every aspect bursting, others predominantly influence (e.g. cis-regulatory elements) frequency availability).

Language: Английский

Citations

131
Simulating multiple faceted variability in single cell RNA sequencing DOI Creative Commons
Xiuwei Zhang, Chenling Xu, Nir Yosef

et al.

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: June 13, 2019

The abundance of new computational methods for processing and interpreting transcriptomes at a single cell level raises the need in silico platforms evaluation validation. Here, we present SymSim, simulator that explicitly models processes give rise to data observed RNA-Seq experiments. components SymSim pipeline pertain three primary sources variation data: noise intrinsic process transcription, extrinsic indicative different states (both discrete continuous), technical due low sensitivity measurement bias. We demonstrate how can be used benchmarking clustering, differential expression trajectory inference, examining effects various parameters on their performance. also show evaluate number cells required detect rare population under scenarios.

Language: Английский

Citations

125