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

Michael B. Wolfe, Aaron C. Goldstrohm, Peter L. Freddolino

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)88-103
Number of pages16
JournalMethods
Volume155
DOIs
StatePublished - Feb 15 2019

Bibliographical note

Funding Information:
This work was supported in part by the National Institute of General Medical Sciences, National Institutes of Health grant R35 GM128637 to P.L.F. and grant R01 GM105707 to A.C.G. Additionally M.B.W. is supported by an National Science Foundation Graduate Research Fellowship DGE1256260.

Keywords

  • 4sU
  • BrU
  • EU
  • High-throughput sequencing
  • Metabolic labeling
  • RNA decay

Fingerprint Dive into the research topics of 'Global analysis of RNA metabolism using bio-orthogonal labeling coupled with next-generation RNA sequencing'. Together they form a unique fingerprint.

Cite this