Literature DB >> 33348360

Dynamics of transcriptional and post-transcriptional regulation.

Mattia Furlan1, Stefano de Pretis1, Mattia Pelizzola1.   

Abstract

Despite gene expression programs being notoriously complex, RNA abundance is usually assumed as a proxy for transcriptional activity. Recently developed approaches, able to disentangle transcriptional and post-transcriptional regulatory processes, have revealed a more complex scenario. It is now possible to work out how synthesis, processing and degradation kinetic rates collectively determine the abundance of each gene's RNA. It has become clear that the same transcriptional output can correspond to different combinations of the kinetic rates. This underscores the fact that markedly different modes of gene expression regulation exist, each with profound effects on a gene's ability to modulate its own expression. This review describes the development of the experimental and computational approaches, including RNA metabolic labeling and mathematical modeling, that have been disclosing the mechanisms underlying complex transcriptional programs. Current limitations and future perspectives in the field are also discussed.
© The Author(s) 2020. Published by Oxford University Press.

Entities:  

Keywords:  RNA degradation; RNA metabolic labeling; RNA processing; RNA synthesis; mathematical modeling; nascent RNA

Year:  2021        PMID: 33348360      PMCID: PMC8294512          DOI: 10.1093/bib/bbaa389

Source DB:  PubMed          Journal:  Brief Bioinform        ISSN: 1467-5463            Impact factor:   11.622


  66 in total

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Journal:  Genome Res       Date:  2003-08       Impact factor: 9.043

2.  Measurement of genome-wide RNA synthesis and decay rates with Dynamic Transcriptome Analysis (DTA).

Authors:  Björn Schwalb; Daniel Schulz; Mai Sun; Benedikt Zacher; Sebastian Dümcke; Dietmar E Martin; Patrick Cramer; Achim Tresch
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Review 3.  Eukaryotic Transcription Turns 50.

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4.  Quantification of experimentally induced nucleotide conversions in high-throughput sequencing datasets.

Authors:  Tobias Neumann; Veronika A Herzog; Matthias Muhar; Arndt von Haeseler; Johannes Zuber; Stefan L Ameres; Philipp Rescheneder
Journal:  BMC Bioinformatics       Date:  2019-05-20       Impact factor: 3.169

5.  m6A-Dependent RNA Dynamics in T Cell Differentiation.

Authors:  Mattia Furlan; Eugenia Galeota; Stefano de Pretis; Michele Caselle; Mattia Pelizzola
Journal:  Genes (Basel)       Date:  2019-01-08       Impact factor: 4.096

6.  Metabolic labeling of RNA using multiple ribonucleoside analogs enables the simultaneous evaluation of RNA synthesis and degradation rates.

Authors:  Kentaro Kawata; Hiroyasu Wakida; Toshimichi Yamada; Kenzui Taniue; Han Han; Masahide Seki; Yutaka Suzuki; Nobuyoshi Akimitsu
Journal:  Genome Res       Date:  2020-08-25       Impact factor: 9.043

7.  Nanopore native RNA sequencing of a human poly(A) transcriptome.

Authors:  Rachael E Workman; Alison D Tang; Paul S Tang; Miten Jain; John R Tyson; Roham Razaghi; Philip C Zuzarte; Timothy Gilpatrick; Alexander Payne; Joshua Quick; Norah Sadowski; Nadine Holmes; Jaqueline Goes de Jesus; Karen L Jones; Cameron M Soulette; Terrance P Snutch; Nicholas Loman; Benedict Paten; Matthew Loose; Jared T Simpson; Hugh E Olsen; Angela N Brooks; Mark Akeson; Winston Timp
Journal:  Nat Methods       Date:  2019-11-18       Impact factor: 28.547

8.  Massively parallel and time-resolved RNA sequencing in single cells with scNT-seq.

Authors:  Qi Qiu; Peng Hu; Xiaojie Qiu; Kiya W Govek; Pablo G Cámara; Hao Wu
Journal:  Nat Methods       Date:  2020-08-31       Impact factor: 28.547

9.  SnapShot-Seq: a method for extracting genome-wide, in vivo mRNA dynamics from a single total RNA sample.

Authors:  Jesse M Gray; David A Harmin; Sarah A Boswell; Nicole Cloonan; Thomas E Mullen; Joseph J Ling; Nimrod Miller; Scott Kuersten; Yong-Chao Ma; Steven A McCarroll; Sean M Grimmond; Michael Springer
Journal:  PLoS One       Date:  2014-02-26       Impact factor: 3.240

10.  A single-molecule view of transcription reveals convoys of RNA polymerases and multi-scale bursting.

Authors:  Katjana Tantale; Florian Mueller; Alja Kozulic-Pirher; Annick Lesne; Jean-Marc Victor; Marie-Cécile Robert; Serena Capozi; Racha Chouaib; Volker Bäcker; Julio Mateos-Langerak; Xavier Darzacq; Christophe Zimmer; Eugenia Basyuk; Edouard Bertrand
Journal:  Nat Commun       Date:  2016-07-27       Impact factor: 14.919

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  5 in total

1.  Estimating RNA dynamics using one time point for one sample in a single-pulse metabolic labeling experiment.

Authors:  Micha Hersch; Adriano Biasini; Ana C Marques; Sven Bergmann
Journal:  BMC Bioinformatics       Date:  2022-04-22       Impact factor: 3.307

Review 2.  New horizons in the stormy sea of multimodal single-cell data integration.

Authors:  Christopher A Jackson; Christine Vogel
Journal:  Mol Cell       Date:  2022-01-20       Impact factor: 17.970

3.  A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them.

Authors:  Jaume Forés-Martos; Anabel Forte; José García-Martínez; José E Pérez-Ortín
Journal:  Cells       Date:  2021-02-05       Impact factor: 6.600

Review 4.  Computational methods for RNA modification detection from nanopore direct RNA sequencing data.

Authors:  Mattia Furlan; Anna Delgado-Tejedor; Logan Mulroney; Mattia Pelizzola; Eva Maria Novoa; Tommaso Leonardi
Journal:  RNA Biol       Date:  2021-09-24       Impact factor: 4.652

5.  Genetic variants associated mRNA stability in lung.

Authors:  Jian-Rong Li; Mabel Tang; Yafang Li; Christopher I Amos; Chao Cheng
Journal:  BMC Genomics       Date:  2022-03-11       Impact factor: 3.969

  5 in total

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