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

Srinivasan S 1 , Yeri A 2 , Cheah PS 3 , Chung A 4 , Danielson K 2 , De Hoff P 1 Show all authors , Filant J 5 , Laurent CD 6 , Laurent LD 1 , Magee R 7 , Moeller C 1 , Murthy VL 8 , Nejad P 9 , Paul A 9 , Rigoutsos I 7 , Rodosthenous R 2 , Shah RV 2 , Simonson B 2 , To C 1 , Wong D 4 , Yan IK 10 , Zhang X 11 , Balaj L 12 , Breakefield XO 11 , Daaboul G 13 , Gandhi R 9 , Lapidus J 14 , Londin E 7 , Patel T 10 , Raffai RL 4 , Sood AK 15 , Alexander RP 16 , Das S 2 , Laurent LC 17

Affiliations 

  • 1 Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA
  • 2 Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  • 3 Neurology and Radiology Services and Program in Neuroscience, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA; Department of Human Anatomy, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, Malaysia
  • 4 Department of Surgery, University of California, San Francisco and VA Medical Center San Francisco, San Francisco, CA 94121, USA
  • 5 Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
  • 6 Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA; Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
  • 7 Computational Medicine Center, Sidney Kimmel College of Medicine, Thomas Jefferson University, Philadelphia, PA, USA
  • 8 Department of Medicine, Division of Cardiovascular Medicine, Frankel Cardiovascular Center, University of Michigan, Ann Arbor, MI, USA
  • 9 Department of Neurology, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
  • 10 Mayo Clinic Florida, Jacksonville, FL, USA
  • 11 Neurology and Radiology Services and Program in Neuroscience, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
  • 12 Neurology and Radiology Services and Program in Neuroscience, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA; Department of Neurosurgery, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
  • 13 NanoView Biosciences, Boston, MA, USA
  • 14 Oregon Health Sciences University, Portland, OR, USA
  • 15 Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Center for RNA Interference and Non-Coding RNAs, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Department of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
  • 16 Pacific Northwest Research Institute, Seattle, WA 98122, USA
  • 17 Department of Obstetrics, Gynecology, and Reproductive Sciences and Sanford Consortium for Regenerative Medicine, University of California, San Diego, La Jolla, CA, USA. Electronic address: llaurent@ucsd.edu
Cell, 2019 04 04;177(2):446-462.e16.
PMID: 30951671 DOI: 10.1016/j.cell.2019.03.024

Abstract

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 profiles. 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 high-density 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 reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.

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