4.8 Article

Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

Journal

CELL
Volume 177, Issue 2, Pages 446-+

Publisher

CELL PRESS
DOI: 10.1016/j.cell.2019.03.024

Keywords

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Funding

  1. NIH Common Fund's exRNA Communication Program
  2. Extracellular RNA Communication Consortium - NIH Common Fund [NIH UH3TR000906, NIH U19179563, NIH UH3TR000901, NIH UH3TR000943, NIH UH3TR000890, NIH UH3TR000884, NIH U19CA179512, NIH U54DA036134]
  3. NIH [P01069246, RO1HL122547, R35CA209904, CA217685, K23 HL127099, R01HL133575, T32 HD007203]
  4. American Cancer Society Research Professor Award
  5. Frank McGraw Memorial Chair in Cancer Research
  6. NIH/NHLBI [HL141424]
  7. NIH/NCI [CA195204]
  8. Thomas Jefferson University

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Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq pro- files. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and highdensity lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and repro ducibility. These results will improve reproducibility and stimulate further progret in exRNA biomarker development. r provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and repro ducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

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