Literature DB >> 30529548

Global analysis of RNA metabolism using bio-orthogonal labeling coupled with next-generation RNA sequencing.

Michael B Wolfe1, Aaron C Goldstrohm2, Peter L Freddolino3.   

Abstract

Many open questions in RNA biology relate to the kinetics of gene expression and the impact of RNA binding regulatory factors on processing or decay rates of particular transcripts. Steady state measurements of RNA abundance obtained from RNA-seq approaches are not able to separate the effects of transcription from those of RNA decay in the overall abundance of any given transcript, instead only giving information on the (presumed steady-state) abundances of transcripts. Through the combination of metabolic labeling and high-throughput sequencing, several groups have been able to measure both transcription rates and decay rates of the entire transcriptome of an organism in a single experiment. This review focuses on the methodology used to specifically measure RNA decay at a global level. By comparing and contrasting approaches and describing the experimental protocols in a modular manner, we intend to provide both experienced and new researchers to the field the ability to combine aspects of various protocols to fit the unique needs of biological questions not addressed by current methods.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  4sU; BrU; EU; High-throughput sequencing; Metabolic labeling; RNA decay

Mesh:

Substances:

Year:  2018        PMID: 30529548      PMCID: PMC6387853          DOI: 10.1016/j.ymeth.2018.12.001

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


  3 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

2.  Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets.

Authors:  Hanna Alalam; Jorge A Zepeda-Martínez; Per Sunnerhagen
Journal:  RNA       Date:  2022-03-16       Impact factor: 5.636

3.  Principles of mRNA control by human PUM proteins elucidated from multimodal experiments and integrative data analysis.

Authors:  Michael B Wolfe; Trista L Schagat; Michelle T Paulsen; Brian Magnuson; Mats Ljungman; Daeyoon Park; Chi Zhang; Zachary T Campbell; Aaron C Goldstrohm; Peter L Freddolino
Journal:  RNA       Date:  2020-08-04       Impact factor: 4.942

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.