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

Autor: Giraldez MD; Department of Internal Medicine, Hematology/Oncology Division, University of Michigan, Ann Arbor, Michigan, USA., Spengler RM; Department of Internal Medicine, Hematology/Oncology Division, University of Michigan, Ann Arbor, Michigan, USA., Etheridge A; Pacific Northwest Research Institute, Seattle, Washington, USA., Godoy PM; Lung Biology Center, Department of Medicine, University of California San Francisco, San Francisco, California, USA., Barczak AJ; Lung Biology Center, Department of Medicine, University of California San Francisco, San Francisco, California, USA., Srinivasan S; Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, California, USA., De Hoff PL; Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, California, USA., Tanriverdi K; Department of Medicine, Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA., Courtright A; Neurogenomics, The Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA., Lu S; Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA., Khoory J; Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA., Rubio R; Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA., Baxter D; Institute for Systems Biology, Seattle, Washington, USA., Driedonks TAP; Department of Biochemistry & Cell Biology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands., Buermans HPJ; Leiden Genome Technology Center, Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands., Nolte-'t Hoen ENM; Department of Biochemistry & Cell Biology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands., Jiang H; Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA., Wang K; Institute for Systems Biology, Seattle, Washington, USA., Ghiran I; Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA., Wang YE; Center for Cancer Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA., Van Keuren-Jensen K; Neurogenomics, The Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA., Freedman JE; Department of Medicine, Division of Cardiovascular Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA., Woodruff PG; 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., Laurent LC; Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, California, USA., Erle DJ; Lung Biology Center, Department of Medicine, University of California San Francisco, San Francisco, California, USA., Galas DJ; Pacific Northwest Research Institute, Seattle, Washington, USA., Tewari M; Department of Internal Medicine, Hematology/Oncology Division, University of Michigan, Ann Arbor, Michigan, USA.; Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA.; Biointerfaces Institute, University of Michigan, Ann Arbor, Michigan, USA.
Jazyk: angličtina
Zdroj: Nature biotechnology [Nat Biotechnol] 2018 Sep; Vol. 36 (8), pp. 746-757. Date of Electronic Publication: 2018 Jul 16.
DOI: 10.1038/nbt.4183
Abstrakt: 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.
Databáze: MEDLINE
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