Literature DB >> 24710662

Post-transcriptional regulation in the nucleus and cytoplasm: study of mean time to threshold (MTT) and narrow escape problem.

D Holcman1, K Dao Duc, A Jones, H Byrne, K Burrage.   

Abstract

Messenger RNAs (mRNAs) can be repressed and degraded by small non-coding RNA molecules. In this paper, we formulate a coarsegrained Markov-chain description of the post-transcriptional regulation of mRNAs by either small interfering RNAs (siRNAs) or microRNAs (miRNAs). We calculate the probability of an mRNA escaping from its domain before it is repressed by siRNAs/miRNAs via calculation of the mean time to threshold: when the number of bound siRNAs/miRNAs exceeds a certain threshold value, the mRNA is irreversibly repressed. In some cases, the analysis can be reduced to counting certain paths in a reduced Markov model. We obtain explicit expressions when the small RNA bind irreversibly to the mRNA and we also discuss the reversible binding case. We apply our models to the study of RNA interference in the nucleus, examining the probability of mRNAs escaping via small nuclear pores before being degraded by siRNAs. Using the same modelling framework, we further investigate the effect of small, decoy RNAs (decoys) on the process of post-transcriptional regulation, by studying regulation of the tumor suppressor gene, PTEN: decoys are able to block binding sites on PTEN mRNAs, thereby reducing the number of sites available to siRNAs/miRNAs and helping to protect it from repression. We calculate the probability of a cytoplasmic PTEN mRNA translocating to the endoplasmic reticulum before being repressed by miRNAs. We support our results with stochastic simulations.

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Year:  2014        PMID: 24710662     DOI: 10.1007/s00285-014-0782-y

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  21 in total

1.  Threshold activation for stochastic chemical reactions in microdomains.

Authors:  K Dao Duc; D Holcman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2010-04-12

2.  Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs.

Authors:  Yvonne Tay; Lev Kats; Leonardo Salmena; Dror Weiss; Shen Mynn Tan; Ugo Ala; Florian Karreth; Laura Poliseno; Paolo Provero; Ferdinando Di Cunto; Judy Lieberman; Isidore Rigoutsos; Pier Paolo Pandolfi
Journal:  Cell       Date:  2011-10-14       Impact factor: 41.582

3.  An extensive microRNA-mediated network of RNA-RNA interactions regulates established oncogenic pathways in glioblastoma.

Authors:  Pavel Sumazin; Xuerui Yang; Hua-Sheng Chiu; Wei-Jen Chung; Archana Iyer; David Llobet-Navas; Presha Rajbhandari; Mukesh Bansal; Paolo Guarnieri; Jose Silva; Andrea Califano
Journal:  Cell       Date:  2011-10-14       Impact factor: 41.582

4.  Mechanism of mRNA transport in the nucleus.

Authors:  Diana Y Vargas; Arjun Raj; Salvatore A E Marras; Fred Russell Kramer; Sanjay Tyagi
Journal:  Proc Natl Acad Sci U S A       Date:  2005-11-11       Impact factor: 11.205

Review 5.  How do microRNAs regulate gene expression?

Authors:  Richard J Jackson; Nancy Standart
Journal:  Sci STKE       Date:  2007-01-02

6.  MicroRNA sponges: competitive inhibitors of small RNAs in mammalian cells.

Authors:  Margaret S Ebert; Joel R Neilson; Phillip A Sharp
Journal:  Nat Methods       Date:  2007-08-12       Impact factor: 28.547

7.  Narrow escape and leakage of Brownian particles.

Authors:  A Singer; Z Schuss; D Holcman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-11-14

8.  Kinetic signatures of microRNA modes of action.

Authors:  Nadya Morozova; Andrei Zinovyev; Nora Nonne; Linda-Louise Pritchard; Alexander N Gorban; Annick Harel-Bellan
Journal:  RNA       Date:  2012-07-31       Impact factor: 4.942

9.  The tumor suppressor PTEN is exported in exosomes and has phosphatase activity in recipient cells.

Authors:  Ulrich Putz; Jason Howitt; Anh Doan; Choo-Peng Goh; Ley-Hian Low; John Silke; Seong-Seng Tan
Journal:  Sci Signal       Date:  2012-09-25       Impact factor: 8.192

10.  Argonaute protein identity and pairing geometry determine cooperativity in mammalian RNA silencing.

Authors:  Jennifer A Broderick; William E Salomon; Sean P Ryder; Neil Aronin; Phillip D Zamore
Journal:  RNA       Date:  2011-08-30       Impact factor: 4.942

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