scholarly journals Flipping between Polycomb repressed and active transcriptional states introduces noise in gene expression

2017 ◽  
Author(s):  
Gozde Kar ◽  
Jong Kyoung Kim ◽  
Aleksandra A. Kolodziejczyk ◽  
Kedar Nath Natarajan ◽  
Elena Torlai Triglia ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Burst Size ◽  
Three Dimensions ◽  
Sequencing Data ◽  
Gene Expression Noise ◽  
Histone Modifiers ◽  
Transcriptional Bursting ◽  
Noise In Gene Expression ◽  
Active Genes

AbstractPolycomb repressive complexes (PRCs) are important histone modifiers, which silence gene expression, yet there exists a subset of PRC-bound genes actively transcribed by RNA polymerase II (RNAPII). It is likely that the role of PRC is to dampen expression of these PRC-active genes. However, it is unclear how this flipping between chromatin states alters the kinetics of transcriptional burst size and frequency relative to genes with exclusively activating marks. To investigate this, we integrate histone modifications and RNAPII states derived from bulk ChIP-seq data with single-cell RNA-sequencing data. We find that PRC-active genes have a greater cell-to-cell variation in expression than active genes with the same mean expression levels, and validate these results by knockout experiments. We also show that PRC-active genes are clustered on chromosomes in both two and three dimensions, and interactions with active enhancers promote a stabilization of gene expression noise. These findings provide new insights into how chromatin regulation modulates stochastic gene expression and transcriptional bursting, with implications for regulation of pluripotency and development.

scholarly journals Chromosome-wide co-fluctuation of stochastic gene expression in mammalian cells

2019 ◽  
Author(s):  
Mengyi Sun ◽  
Jianzhi Zhang
Keyword(s):  
Gene Expression ◽  
Mammalian Cells ◽  
Three Dimensional ◽  
Sequencing Data ◽  
Chromatin Dynamics ◽  
Gene Expression Noise ◽  
Genes Encoding ◽  
The Face ◽  
Allele Specific ◽  
Genomic Scale

ABSTRACTGene expression is subject to stochastic noise, but to what extent and by which means such stochastic variations are coordinated among different genes are unclear. We hypothesize that neighboring genes on the same chromosome co-fluctuate in expression because of their common chromatin dynamics, and verify it at the genomic scale using allele-specific single-cell RNA-sequencing data of mouse cells. Unexpectedly, the co-fluctuation extends to genes that are over 60 million bases apart. We provide evidence that this long-range effect arises in part from chromatin co-accessibilities of linked loci attributable to three-dimensional proximity, which is much closer intra-chromosomally than inter-chromosomally. We further show that genes encoding components of the same protein complex tend to be chromosomally linked, likely resulting from natural selection for intracellular among-component dosage balance. These findings have implications for both the evolution of genome organization and optimal design of synthetic genomes in the face of gene expression noise.

scholarly journals Kinetic foundation of the zero-inflated negative binomial model for single-cell RNA sequencing data

2019 ◽  
Author(s):  
Chen Jia
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Negative Binomial ◽  
Burst Size ◽  
Dropout Rate ◽  
Quantitative Relation ◽  
Sequencing Data ◽  
Single Cell Rna Sequencing ◽  
Transcriptional Bursting ◽  
Over Dispersion

AbstractSingle-cell RNA sequencing data have complex features such as dropout events, over-dispersion, and high-magnitude outliers, resulting in complicated probability distributions of mRNA abundances that are statistically characterized in terms of a zero-inflated negative binomial (ZINB) model. Here we provide a mesoscopic kinetic foundation of the widely used ZINB model based on the biochemical reaction kinetics underlying transcription. Using multiscale modeling and simplification techniques, we show that the ZINB distribution of mRNA abundance and the phenomenon of transcriptional bursting naturally emerge from a three-state stochastic transcription model. We further reveal a nontrivial quantitative relation between dropout events and transcriptional bursting, which provides novel insights into how and to what extent the burst size and burst frequency could reduce the dropout rate. Three different biophysical origins of over-dispersion are also clarified at the single-cell level.

scholarly journals Single cell transcriptomes reveal characteristics of miRNA in gene expression noise reduction

2018 ◽  
Author(s):  
Tao Hu ◽  
Lei Wei ◽  
Shuailin Li ◽  
Tianrun Cheng ◽  
Xuegong Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Mirna Expression ◽  
Transcriptional Activation ◽  
Expression Profiles ◽  
Mrna Level ◽  
Interaction Strength ◽  
Sequencing Data ◽  
Gene Expression Noise ◽  
Expression Noise

AbstractIsogenic cells growing in identical environments show cell-to-cell variations because of stochastic gene expression. The high level of variation or noise could disrupt robust gene expression and result in tremendous consequences on cell behaviors. In this work, we showed evidence that microRNAs (miRNAs) could reduce gene expression noise in mRNA level of mouse cells based on single-cell RNA-sequencing data analysis. We identified that miRNA expression level, number of targets, targets pool abundance and interaction strength of miRNA with its targets are the key features contributing to noise repression. MiRNAs tend to work together as cooperative sub-networks to repress target noise synergistically in a cell type specific manner. Using a physical model of post-transcriptional regulation, we demonstrated that the accelerated degradation with elevated transcriptional activation of miRNA target provides resistance to extrinsic fluctuations. Together, through the integration analysis of single-cell RNA and miRNA expression profiles. We demonstrated that miRNAs are important post-transcriptional regulators for reducing gene expression noise and conferring robustness to biological processes.

scholarly journals Origins and impacts of new exons

2014 ◽  
Author(s):  
Jason Merkin* ◽  
Ping Chen* ◽  
Maria Alexis ◽  
Sampsa Hautaniemi ◽  
Christopher Burge
Keyword(s):  
Gene Expression ◽  
Rna Polymerase Ii ◽  
Nucleosome Occupancy ◽  
Mrna Levels ◽  
Sequencing Data ◽  
Protein Coding ◽  
Evolutionary Origins ◽  
Alternatively Spliced ◽  
Mammalian Genes ◽  
Species Specific

Mammalian genes are typically broken into several protein-coding and non-coding exons, but the evolutionary origins and functions of new exons are not well understood. Here, we analyzed patterns of exon gain using deep cDNA sequencing data from several mammals and one bird, identifying thousands of species- and lineage-specific exons. While exons conserved across mammals are mostly protein-coding and constitutively spliced, species-specific exons were mostly located in 5' untranslated regions and alternatively spliced. New exons most often derived from unique intronic sequence rather than repetitive elements, and were associated with upstream intronic deletions, increased nucleosome occupancy and RNA polymerase II pausing. Surprisingly, exon gain was associated with increased gene expression, but only in tissues where the exon was included, suggesting that splicing enhances steady-state mRNA levels and that changes in splicing represent a major contributor to the evolution of gene expression.

scholarly journals Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

2020 ◽  
Vol 48 (16) ◽  
pp. 9406-9413 ◽  
Author(s):  
Tyler Quarton ◽  
Taek Kang ◽  
Vasileios Papakis ◽  
Khai Nguyen ◽  
Chance Nowak ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Synthesis ◽  
Reporter System ◽  
Extrinsic Noise ◽  
Cell Content ◽  
Gene Expression Noise ◽  
Central Dogma ◽  
Expression Noise ◽  
Global Correlation ◽  
Noise In Gene Expression

Abstract Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.

scholarly journals TNF stimulation primarily modulates transcriptional burst size of NF-κB-regulated genes

2020 ◽  
Author(s):  
Victor L. Bass ◽  
Victor C. Wong ◽  
M. Elise Bullock ◽  
Suzanne Gaudet ◽  
Kathryn Miller-Jensen
Keyword(s):  
Inflammatory Response ◽  
Rna Polymerase Ii ◽  
Computational Models ◽  
Target Genes ◽  
Burst Size ◽  
Inverse Correlation ◽  
Burst Frequency ◽  
Gene Expression Noise ◽  
Molecule Inhibitor ◽  
Single Transcript

AbstractCell-to-cell heterogeneity is a characteristic feature of the tumor necrosis factor (TNF)-stimulated inflammatory response mediated by the transcription factor NF-κB, motivating an exploration of the underlying sources of this noise. Here we combined single-transcript measurements with computational models to study transcriptional noise at six NF-κB-regulated inflammatory genes. In the basal state, NF-κB-target genes displayed an inverse correlation between mean and noise. TNF stimulation increased transcription while maintaining noise, except for the most repressed genes. By fitting transcript distributions to a two-state model of promoter activity, we found that TNF primarily stimulated transcription by increasing burst size while maintaining burst frequency. Burst size increases were associated with enrichment of initiated-but-paused RNA polymerase II at the promoter, and blocking the release of paused RNAPII with a small molecule inhibitor decreased TNF-stimulated burst size. Finally, we used a mathematical model to show that TNF positive feedback further amplified gene expression noise resulting from burst-size mediated transcription, leading to diverse TNF functional outputs. Our results reveal potential sources of noise underlying intercellular heterogeneity in the TNF-mediated inflammatory response.

scholarly journals High cooperativity in negative feedback can amplify noisy gene expression

2017 ◽  
Author(s):  
Pavol Bokes ◽  
Yen Ting Lin ◽  
Abhyudai Singh
Keyword(s):  
Gene Expression ◽  
Negative Feedback ◽  
Coefficient Of Variation ◽  
Burst Size ◽  
Burst Frequency ◽  
Gene Expression Noise ◽  
Protein Levels ◽  
Feedback Strength ◽  
Cell To Cell Variability ◽  
The Impact

AbstractBurst-like synthesis of protein is a significant source of cell-to-cell variability in protein levels. Negative feedback is a common example of a regulatory mechanism by which such stochasticity can be controlled. Here we consider a specific kind of negative feedback, which makes bursts smaller in the excess of protein. Increasing the strength of the feedback may lead to dramatically different outcomes depending on a key parameter, the noise load, which is defined as the squared coefficient of variation the protein exhibits in the absence of feedback. Combining stochastic simulation with asymptotic analysis, we identify a critical value of noise load: for noise loads smaller than critical, the coefficient of variation remains bounded with increasing feedback strength; contrastingly, if the noise load is larger than critical, the coefficient of variation diverges to infinity in the limit of ever greater feedback strengths. Interestingly, high-cooperativity feedbacks have lower critical noise loads, implying that low-cooperativity feedbacks in burst size can be preferable for noisy proteins. Finally, we discuss our findings in the context of previous results on the impact of negative feedback in burst size and burst frequency on gene-expression noise.

scholarly journals Phase separation provides a mechanism to reduce noise in cells

2019 ◽  
Author(s):  
Florian Oltsch ◽  
Adam Klosin ◽  
Frank Julicher ◽  
Anthony A. Hyman ◽  
Christoph Zechner
Keyword(s):  
Gene Expression ◽  
Phase Separation ◽  
Mammalian Cells ◽  
Biological Information ◽  
Liquid Droplets ◽  
Gene Expression Noise ◽  
Noise In Gene Expression ◽  
Biological Information Processing ◽  
Cellular Control

A central problem in cellular control is how cells cope with the inherent noise in gene expression. Although transcriptional and posttranscriptional feedback mechanisms can suppress noise, they are often slow, and cannot explain how cells buffer acute fluctuations. Here, by using a physical model that links fluctuations in protein concentration to the theory of phase separation, we show that liquid droplets can act as fast and effective buffers for gene expression noise. We confirm our theory experimentally using an engineered phase separating protein that forms liquid-like compartments in mammalian cells. These data suggest a novel role of phase separation in biological information processing.

Linking transcription, RNA polymerase II elongation and alternative splicing

2020 ◽  
Vol 477 (16) ◽  
pp. 3091-3104 ◽  
Author(s):  
Luciana E. Giono ◽  
Alberto R. Kornblihtt
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Rna Polymerase Ii ◽  
Environmental Changes ◽  
Transcription Elongation ◽  
Single Gene ◽  
Regulation Of Gene Expression ◽  
Regulation Of Transcription ◽  
Stepping Stones ◽  
Eukaryotic Transcription

Gene expression is an intricately regulated process that is at the basis of cell differentiation, the maintenance of cell identity and the cellular responses to environmental changes. Alternative splicing, the process by which multiple functionally distinct transcripts are generated from a single gene, is one of the main mechanisms that contribute to expand the coding capacity of genomes and help explain the level of complexity achieved by higher organisms. Eukaryotic transcription is subject to multiple layers of regulation both intrinsic — such as promoter structure — and dynamic, allowing the cell to respond to internal and external signals. Similarly, alternative splicing choices are affected by all of these aspects, mainly through the regulation of transcription elongation, making it a regulatory knob on a par with the regulation of gene expression levels. This review aims to recapitulate some of the history and stepping-stones that led to the paradigms held today about transcription and splicing regulation, with major focus on transcription elongation and its effect on alternative splicing.

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