Modulation of nuclear and cytoplasmic mRNA fluctuations by time-dependent stimuli: Analytical distributions

Филатова, Т. С.; Popović, Nikola; Grima, Ramon

doi:10.1016/j.mbs.2022.108828

Cited by 8 publications

(4 citation statements)

References 57 publications

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“…One contributing factor to noisy expression is toggling between an inactive and active transcription state, so that mRNAs are produced in "bursts", leading to large variation in mRNA abundance (25). The large noise created by bursty expression can be modulated downstream of mRNA synthesis (26,27). For example, slow mRNA export from the nucleus may buffer bursty mRNA synthesis and thereby lower noise in the cytoplasm relative to noise in the nucleus (11,(28)(29)(30).…”

Section: Introductionmentioning

confidence: 99%

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Weidemann

Singh

Grima

et al. 2023

Preprint

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Stochastic variation in gene products (“noise”) is an inescapable by-product of gene expression and can have profound consequences on cellular physiology. The least variation is seen for constitutively expressed genes, whose mRNA numbers in the population are commonly assumed to be Poisson-distributed, i.e. showing a variance equal to the mean. Here, we show that specific constitutively expressed cell division genes inS. pombeshow considerably lower variance in mRNA numbers, classifying them as sub-Poissonian. Importantly, the sub-Poissonian nature is more pronounced in the cytoplasm than the nucleus. Modeling indicates that the dynamics of cytoplasmic mRNA degradation and nuclear export are key in reducing the variance-to-mean ratio in the cytoplasm. Our findings suggest that constitutively expressed genes are not a homogenous group with respect to expression noise. Instead, they can differ in gene expression dynamics to create a range of mRNA distributions, whose lower limit is sub-Poissonian.

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Section: Introductionmentioning

confidence: 99%

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Weidemann

Singh

Grima

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

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“…

stands for the geodesic (that is, the shortest arc) between

and

in the manifold

, and

is the included angle between

and

. Unlike the Kullback–Leibler divergence, the geodesic

is symmetric and satisfies the triangle inequality, so it can be treated as a true distance [ 41 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 ].…”

Section: Methods Of Information Geometrymentioning

confidence: 99%

Quantifying Information of Dynamical Biochemical Reaction Networks

Jiang

Yin

2023

Entropy

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A large number of complex biochemical reaction networks are included in the gene expression, cell development, and cell differentiation of in vivo cells, among other processes. Biochemical reaction-underlying processes are the ones transmitting information from cellular internal or external signaling. However, how this information is measured remains an open question. In this paper, we apply the method of information length, based on the combination of Fisher information and information geometry, to study linear and nonlinear biochemical reaction chains, respectively. Through a lot of random simulations, we find that the amount of information does not always increase with the length of the linear reaction chain; instead, the amount of information varies significantly when this length is not very large. When the length of the linear reaction chain reaches a certain value, the amount of information hardly changes. For nonlinear reaction chains, the amount of information changes not only with the length of this chain, but also with reaction coefficients and rates, and this amount also increases with the length of the nonlinear reaction chain. Our results will help to understand the role of the biochemical reaction networks in cells.

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“…It is not a priori obvious that this export process should be Markovian. Previous theoretical studies have adopted this assumption (Filatova et al, 2022, Singh and Bokes, 2012), and some experimental studies involving synthetic fluorescent reporter constructs (Hansen et al, 2018, Munsky et al, 2018) have not observed gross discrepancies with the Markovian hypothesis. However, in previous work (Gorin and Pachter, 2022a), we observed that scRNA-seq data were largely consistent with the simple CME model of bursty transcription, Markovian splicing, and Markovian removal of spliced molecules, but snRNA-seq data exhibited a high rate of apparent model misspecification according to a goodness-of-fit criterion.…”

Section: Introductionmentioning

confidence: 99%

Transient and delay chemical master equations

Gorin

Yoshida

Pachter

2022

Preprint

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The serial nature of reactions involved in the RNA life-cycle motivates the incorporation of delays in models of transcriptional dynamics. The models couple a bursty or switching promoter to a fairly general set of Markovian or deterministically delayed monomolecular RNA interconversion reactions with no feedback. We provide numerical solutions for the RNA copy number distributions the models induce, and solve several systems with splicing and degradation. An analysis of single-cell and single-nucleus RNA sequencing data using these models reveals that the kinetics of nuclear export do not appear to require invocation of a non-Markovian waiting time.

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Modulation of nuclear and cytoplasmic mRNA fluctuations by time-dependent stimuli: Analytical distributions

Cited by 8 publications

References 57 publications

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Quantifying Information of Dynamical Biochemical Reaction Networks

Transient and delay chemical master equations

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