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

Author

Srinivasan S, Yeri A, Cheah PS, Chung A, Danielson K, De Hoff P, Filant J, Laurent CD, Laurent LD, Magee R, Moeller C, Murthy VL, Nejad P, Paul A, Rigoutsos I, Rodosthenous R, Shah RV, Simonson B, To C, Wong D, Yan IK, Zhang X, Balaj L, Breakefield XO, Daaboul G, Gandhi R, Lapidus J, Londin E, Patel T, Raffai RL, Sood AK, Alexander RP, Das S, and Laurent LC

Subjects
Adult, Body Fluids chemistry, Cell Line, Extracellular Vesicles metabolism, Female, Healthy Volunteers, Humans, Male, MicroRNAs isolation & purification, MicroRNAs metabolism, RNA metabolism, Reproducibility of Results, Sequence Analysis, RNA methods, Cell-Free Nucleic Acids isolation & purification, Circulating MicroRNA isolation & purification, RNA isolation & purification
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., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Published
2019
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2. exRNA Atlas Analysis Reveals Distinct Extracellular RNA Cargo Types and Their Carriers Present across Human Biofluids.

Author

Murillo OD, Thistlethwaite W, Rozowsky J, Subramanian SL, Lucero R, Shah N, Jackson AR, Srinivasan S, Chung A, Laurent CD, Kitchen RR, Galeev T, Warrell J, Diao JA, Welsh JA, Hanspers K, Riutta A, Burgstaller-Muehlbacher S, Shah RV, Yeri A, Jenkins LM, Ahsen ME, Cordon-Cardo C, Dogra N, Gifford SM, Smith JT, Stolovitzky G, Tewari AK, Wunsch BH, Yadav KK, Danielson KM, Filant J, Moeller C, Nejad P, Paul A, Simonson B, Wong DK, Zhang X, Balaj L, Gandhi R, Sood AK, Alexander RP, Wang L, Wu C, Wong DTW, Galas DJ, Van Keuren-Jensen K, Patel T, Jones JC, Das S, Cheung KH, Pico AR, Su AI, Raffai RL, Laurent LC, Roth ME, Gerstein MB, and Milosavljevic A

Subjects
Adult, Body Fluids chemistry, Cell-Free Nucleic Acids metabolism, Circulating MicroRNA metabolism, Extracellular Vesicles metabolism, Female, Humans, Male, Reproducibility of Results, Sequence Analysis, RNA methods, Software, Cell Communication physiology, RNA metabolism
Abstract

To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously. To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Published
2019
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