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Data from: Profiling extracellular long RNA transcriptome in human plasma and extracellular vesicles for biomarker discovery

Citation

Hutchins, Elizabeth; Rodosthenous, Rodosthenis; Van Keuren Jensen, Kendall; Das, Saumya (2020), Data from: Profiling extracellular long RNA transcriptome in human plasma and extracellular vesicles for biomarker discovery, Dryad, Dataset, https://doi.org/10.5061/dryad.kh1893236

Abstract

The recent discovery of extracellular RNAs in blood, including RNAs in extracellular vesicles (EVs), combined with low-input RNA-sequencing advances have enabled scientists to investigate their role in human disease. To date, most studies have been focusing on small RNAs, and methodologies to optimize long RNAs measurement are lacking. We used plasma RNA to assess the performance of six long RNA sequencing methods, at two different sites, and we report their differences in reads (%) mapped to the genome/transcriptome, number of genes detected, long RNA transcript diversity, and reproducibility. Using the best performing method, we further compare the profile of long RNAs in the EV- and no-EV-enriched RNA plasma compartments. These results provide insights on the performance and reproducibility of commercially available kits in assessing the landscape of long RNAs in human plasma and different extracellular RNA carriers that may be exploited for biomarker discovery.

Usage Notes

Tarball with raw counts and transcript TPMs for the library kits tested, and the vesicle isolations tested in the accompanying manuscript:

countTable_libraryKits.csv
tpmTable_libraryKits.csv
countTable_vesicles.csv
tpmTable_vesicles.csv

Funding

National Institutes of Health, Award: UH3TR000901

National Institutes of Health, Award: UH3TR000891

National Institutes of Health, Award: UH3TR000906

National Institutes of Health, Award: UH3TR000906

National Institutes of Health, Award: U01HL126494

National Institutes of Health, Award: HL126497

American Heart Association, Award: 16SFRN31280008

National Institutes of Health, Award: R01HL122547

National Institutes of Health, Award: R01CA218500