Comprehensive multi-center assessment of small RNA-seq methods for quantitative miRNA profiling

Maria D Giraldez, Ryan M Spengler, Alton Etheridge, Paula M Godoy, Andrea J Barczak, Srimeenakshi Srinivasan, Peter L De Hoff, Kahraman Tanriverdi, Amanda Courtright, Shulin Lu, Joseph Khoory, Renee Rubio, David Baxter, Tom A P Driedonks, Henk P J Buermans, Esther N M Nolte-'t Hoen, Hui Jiang, Kai Wang, Ionita Ghiran, Yaoyu E WangKendall Van Keuren-Jensen, Jane E Freedman, Prescott G Woodruff, Louise C Laurent, David J Erle, David J Galas, Muneesh Tewari

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

RNA-seq is increasingly used for quantitative profiling of small RNAs (for example, microRNAs, piRNAs and snoRNAs) in diverse sample types, including isolated cells, tissues and cell-free biofluids. The accuracy and reproducibility of the currently used small RNA-seq library preparation methods have not been systematically tested. Here we report results obtained by a consortium of nine labs that independently sequenced reference, 'ground truth' samples of synthetic small RNAs and human plasma-derived RNA. We assessed three commercially available library preparation methods that use adapters of defined sequence and six methods using adapters with degenerate bases. Both protocol- and sequence-specific biases were identified, including biases that reduced the ability of small RNA-seq to accurately measure adenosine-to-inosine editing in microRNAs. We found that these biases were mitigated by library preparation methods that incorporate adapters with degenerate bases. MicroRNA relative quantification between samples using small RNA-seq was accurate and reproducible across laboratories and methods.

Original languageEnglish
Pages (from-to)746-757
Number of pages12
JournalNature Biotechnology
Volume36
Issue number8
DOIs
Publication statusPublished - Sept 2018
Externally publishedYes

Keywords

  • Adenosine/genetics
  • Humans
  • Inosine/genetics
  • MicroRNAs/blood
  • RNA Editing
  • Reference Standards
  • Reproducibility of Results
  • Sequence Analysis, RNA/methods

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