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Nat Biotechnol. 2018 Sep;36(8):746-757. doi: 10.1038/nbt.4183. Epub 2018 Jul 16.

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

Author information

1
Department of Internal Medicine, Hematology/Oncology Division, University of Michigan, Ann Arbor, Michigan, USA.
2
Pacific Northwest Research Institute, Seattle, Washington, USA.
3
Lung Biology Center, Department of Medicine, University of California San Francisco, San Francisco, California, USA.
4
Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, California, USA.
5
Department of Medicine, Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
6
Neurogenomics, The Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA.
7
Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.
8
Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.
9
Institute for Systems Biology, Seattle, Washington, USA.
10
Department of Biochemistry & Cell Biology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands.
11
Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
12
Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
13
Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.
14
Cardiovascular Research Institute and the Department of Medicine, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of California San Francisco, San Francisco, California, USA.
15
Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.
16
Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.

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.

PMID:
30010675
PMCID:
PMC6078798
[Available on 2019-01-16]
DOI:
10.1038/nbt.4183

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