Literature DB >> 32197587

Comparison of RNA isolation methods on RNA-Seq: implications for differential expression and meta-analyses.

Amanda N Scholes1,2, Jeffrey A Lewis3.   

Abstract

BACKGROUND: The increasing number of transcriptomic datasets has allowed for meta-analyses, which can be valuable due to their increased statistical power. However, meta-analyses can be confounded by so-called "batch effects," where technical variation across different batches of RNA-seq experiments can clearly produce spurious signals of differential expression and reduce our power to detect true differences. While batch effects can sometimes be accounted for, albeit with caveats, a better strategy is to understand their sources to better avoid them. In this study, we examined the effects of RNA isolation method as a possible source of batch effects in RNA-seq design.
RESULTS: Based on the different chemistries of "classic" hot phenol extraction of RNA compared to common commercial RNA isolation kits, we hypothesized that specific mRNAs may be preferentially extracted depending upon method, which could masquerade as differential expression in downstream RNA-seq analyses. We tested this hypothesis using the Saccharomyces cerevisiae heat shock response as a well-validated environmental response. Comparing technical replicates that only differed in RNA isolation method, we found over one thousand transcripts that appeared "differentially" expressed when comparing hot phenol extraction with the two kits. Strikingly, transcripts with higher abundance in the phenol-extracted samples were enriched for membrane proteins, suggesting that indeed the chemistry of hot phenol extraction better solubilizes those species of mRNA.
CONCLUSIONS: Within a self-contained experimental batch (e.g. control versus treatment), the method of RNA isolation had little effect on the ability to identify differentially expressed transcripts. However, we suggest that researchers performing meta-analyses across different experimental batches strongly consider the RNA isolation methods for each experiment.

Entities:  

Keywords:  Batch effects; Meta-analysis; RNA isolation; RNA-seq; Transcriptomics

Year:  2020        PMID: 32197587     DOI: 10.1186/s12864-020-6673-2

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  9 in total

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2.  Sensitive and accurate analysis of gene expression signatures enabled by oligonucleotide-labelled cDNA.

Authors:  Žana Kapustina; Justina Medžiūnė; Varvara Dubovskaja; Karolis Matjošaitis; Simona Žeimytė; Arvydas Lubys
Journal:  RNA Biol       Date:  2022-01       Impact factor: 4.766

3.  Opportunities and Challenges in Global Quantification of RNA-Protein Interaction via UV Cross-Linking.

Authors:  Carlos H Vieira-Vieira; Matthias Selbach
Journal:  Front Mol Biosci       Date:  2021-05-13

4.  Prime-seq, efficient and powerful bulk RNA sequencing.

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Journal:  Genome Biol       Date:  2022-03-31       Impact factor: 13.583

Review 5.  Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review.

Authors:  Philip A Kocheril; Shepard C Moore; Kiersten D Lenz; Harshini Mukundan; Laura M Lilley
Journal:  Biomark Insights       Date:  2022-06-13

6.  Batch effect detection and correction in RNA-seq data using machine-learning-based automated assessment of quality.

Authors:  Maximilian Sprang; Miguel A Andrade-Navarro; Jean-Fred Fontaine
Journal:  BMC Bioinformatics       Date:  2022-07-14       Impact factor: 3.307

7.  Method of Microglial DNA-RNA Purification from a Single Brain of an Adult Mouse.

Authors:  Md Obayed Raihan; Brett A McGregor; Nathan A Velaris; Afrina Brishti; Junguk Hur; James E Porter
Journal:  Methods Protoc       Date:  2021-12-02

Review 8.  Effects of Mating on Gene Expression in Female Insects: Unifying the Field.

Authors:  Ferdinand Nanfack-Minkeu; Laura King Sirot
Journal:  Insects       Date:  2022-01-07       Impact factor: 3.139

9.  Optimization of RNA extraction methods from human metabolic tissue samples of the COMET biobank.

Authors:  Sandra Rebuffat; Anne-Dominique Lajoix; Agathe Nouvel; Jonas Laget; Flore Duranton; Jérémy Leroy; Caroline Desmetz; Marie-Dominique Servais; Nathalie de Préville; Florence Galtier; David Nocca; Nicolas Builles
Journal:  Sci Rep       Date:  2021-10-25       Impact factor: 4.379

  9 in total

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