Reverse transcriptase enzyme and priming strategy affect quantification and diversity of environmental transcripts

• Published in: Environmental microbiology Vol. 22; no. 6; pp. 2383 - 2402
• Main Authors: Cholet, Fabien, Ijaz, Umer Z., Smith, Cindy J.
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01-06-2020; Wiley Subscription Services, Inc
• Subjects: Bacterial Proteins - genetics; DNA; Enzymes; Gene expression; Gene sequencing; Marine sediments; Microbiology; Nucleic acids; Nucleotide sequence; Oxidoreductases - genetics; PCR; Priming; Reproducibility; Reproducibility of Results; Reverse Transcriptase Polymerase Chain Reaction; Reverse transcription; RNA; RNA, Ribosomal, 16S - genetics; RNA-directed DNA polymerase; RNA-Directed DNA Polymerase - genetics; rRNA 16S; Sediments; Sequencing; Strategy; Transcription
• ISSN: 1462-2912; 1462-2920
• DOI: 10.1111/1462-2920.15017

Summary
Reverse‐transcriptase‐quantitative PCR (RT‐Q‐PCR) and RT‐PCR amplicon sequencing, provide a convenient, target‐specific, high‐sensitivity approach for gene expression studies and are widely used in environmental microbiology. Yet, the effectiveness and reproducibility of the reverse transcription step has not been evaluated. Therefore, we tested a combination of four commercial reverse transcriptases with two priming techniques to faithfully transcribe 16S rRNA and amoA transcripts from marine sediments. Both enzyme and priming strategy greatly affected quantification of the exact same target with differences of up to 600‐fold. Furthermore, the choice of RT system significantly changed the communities recovered. For 16S rRNA, both enzyme and priming had a significant effect with enzyme having a stronger impact than priming. Inversely, for amoA only the change in priming strategy resulted in significant differences between the same samples. Specifically, more OTUs and better coverage of amoA transcripts diversity were obtained with GS priming indicating this approach was better at recovering the diversity of amoA transcripts. Moreover, sequencing of RNA mock communities revealed that, even though transcript α diversities (i.e., OTU counts within a sample) can be biased by the RT, the comparison of β diversities (i.e., differences in OTU counts between samples) is reliable as those biases are reproducible between environments.