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

Biomolecular Detection and Quantification
Jessica SchwaberLars Nielsen

Abstract

The RNA-to-cDNA conversion step in transcriptomics experiments is widely recognised as inefficient and variable, casting doubt on the ability to do quantitative transcriptomics analyses. Multiple studies have focused on ways to optimise this process, resulting in contradictory recommendations. Here we explore the problem of reverse transcription efficiency using digital PCR and the RT method's impact on subsequent data analysis. Using synthetic RNA standards, an example experiment is presented, outlining a method to (1) determine relevant efficiency and variability values and then to (2) incorporate this information into downstream analyses as a way to improve the accuracy of quantitative transcriptomics experiments.

Citations

Nov 9, 2019·Clinical Chemistry·Daniel ZuchaLukas Valihrach
Oct 12, 2019·Cytometry. Part a : the Journal of the International Society for Analytical Cytology·Diana Ordoñez-RuedaMalte Paulsen
Jul 14, 2020·Bioinformatics·Qiuyu LianKong Chen
Dec 18, 2019·The Journal of General Virology·Valentina D'ArienzoJane A McKeating
Jul 30, 2020·Methods : a Companion to Methods in Enzymology·Loic LindnerGuillaume Pavlovic
Feb 9, 2021·Computational and Structural Biotechnology Journal·Arnt EbingerDirk Höper
Mar 12, 2021·Frontiers in Microbiology·Amy H FitzpatrickPaul Cotter
Nov 6, 2020·Journal of Virological Methods·Sofia PerssonPatrik Ellström
Jun 2, 2021·The Journal of Molecular Diagnostics : JMD·Natalie N KinlochZabrina L Brumme
Jan 23, 2022·Genome Biology·Ruochen JiangJingyi Jessica Li

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Methods Mentioned

BETA
PCR
single cell sequencing
single-cell sequencing
RNA
chip
RNA Assay
Assay

Software Mentioned

QuantaSoft [UNK] Analysis Pro
EvaGreen

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