Literature DB >> 33204768

Using RNA Sequencing and Spike-in RNAs to Measure Intracellular Abundance of lncRNAs and mRNAs.

Megan D Schertzer1,2, McKenzie M Murvin1,2, J Mauro Calabrese1.   

Abstract

Long noncoding RNAs (lncRNAs) play essential roles in normal physiology and in disease but their mechanisms of action can be challenging to identify. For mechanistic studies, it is often useful to know a lncRNA's intracellular abundance, i.e., approximately how many molecules of the lncRNA are present in a typical cell of a cell-type of interest. At least two approaches have been used to approximate lncRNA intracellular abundance: single-molecule sensitivity RNA fluorescence in situ hybridization (smFISH) and single-gene, calibrated reverse-transcription followed by quantitative PCR (RT-qPCR). However, like all experimental approaches, these methods have their limitations. smFISH, when analyzed using diffraction-limited microscopy, can underestimate intracellular abundance, especially for lncRNAs that accumulate in focused subcellular regions. Calibrated RT-qPCR may return inaccurate estimates of abundance because individual PCR amplicons spaced across the length of a transcript can vary in their efficiency of reverse transcription. Here, we describe a sequencing-based approach that is straightforward, orthogonal to smFISH and RT-qPCR, and can be used to approximate the intracellular abundance for most expressed long RNAs (lncRNAs and mRNAs) in a cell type of interest. Firstly, the average weight of total RNA per cell for the cell type of interest is estimated by replicate rounds of RNA purification from a known number of cells. Secondly, an rRNA-depletion RNA-Seq protocol is performed after adding spike-in control RNAs to a known quantity of total cellular RNA. Lastly, by comparing read counts per transcript to a standard curve derived from the spiked-in RNAs, the intracellular abundance for each transcript is estimated. The sequencing-based approach provides a powerful complement to existing methods, particularly in situations where it is desirable to quantify the abundance of multiple lncRNAs and/or mRNAs simultaneously.

Entities:  

Keywords:  ERCC Spike-In RNAs; RNA FISH; RNA-Seq; Ribosomal RNA depletion; Transcriptome; Xist; lncRNA; smFISH

Year:  2020        PMID: 33204768      PMCID: PMC7668557          DOI: 10.21769/bioprotoc.3772

Source DB:  PubMed          Journal:  Bio Protoc        ISSN: 2331-8325


  32 in total

1.  Synthetic spike-in standards for RNA-seq experiments.

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Review 2.  Illuminating Genomic Dark Matter with RNA Imaging.

Authors:  Arjun Raj; John L Rinn
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Review 3.  RNA-Seq methods for transcriptome analysis.

Authors:  Radmila Hrdlickova; Masoud Toloue; Bin Tian
Journal:  Wiley Interdiscip Rev RNA       Date:  2016-05-19       Impact factor: 9.957

4.  The Sequence Alignment/Map format and SAMtools.

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5.  The evolution of lncRNA repertoires and expression patterns in tetrapods.

Authors:  Anamaria Necsulea; Magali Soumillon; Maria Warnefors; Angélica Liechti; Tasman Daish; Ulrich Zeller; Julie C Baker; Frank Grützner; Henrik Kaessmann
Journal:  Nature       Date:  2014-01-19       Impact factor: 49.962

6.  The sequence read archive.

Authors:  Rasko Leinonen; Hideaki Sugawara; Martin Shumway
Journal:  Nucleic Acids Res       Date:  2010-11-09       Impact factor: 16.971

Review 7.  Nuclear Bodies Built on Architectural Long Noncoding RNAs: Unifying Principles of Their Construction and Function.

Authors:  Takeshi Chujo; Tetsuro Hirose
Journal:  Mol Cells       Date:  2017-12-20       Impact factor: 5.034

8.  Shedding light: The importance of reverse transcription efficiency standards in data interpretation.

Authors:  Jessica Schwaber; Stacey Andersen; Lars Nielsen
Journal:  Biomol Detect Quantif       Date:  2019-02-12

9.  Rapid turnover of long noncoding RNAs and the evolution of gene expression.

Authors:  Claudia Kutter; Stephen Watt; Klara Stefflova; Michael D Wilson; Angela Goncalves; Chris P Ponting; Duncan T Odom; Ana C Marques
Journal:  PLoS Genet       Date:  2012-07-26       Impact factor: 5.917

10.  Comprehensive comparative analysis of strand-specific RNA sequencing methods.

Authors:  Joshua Z Levin; Moran Yassour; Xian Adiconis; Chad Nusbaum; Dawn Anne Thompson; Nir Friedman; Andreas Gnirke; Aviv Regev
Journal:  Nat Methods       Date:  2010-08-15       Impact factor: 28.547

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  1 in total

Review 1.  Significance of lncRNA abundance to function.

Authors:  Ioannis Grammatikakis; Ashish Lal
Journal:  Mamm Genome       Date:  2021-08-18       Impact factor: 2.957

  1 in total

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