Optimization of small RNA library preparation protocol from human urinary exosomes

Autor: Dolores Olivares, Javier Perez-Hernandez, Daniel Perez-Gil, Felipe J. Chaves, Josep Redon, Raquel Cortes
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Journal of Translational Medicine, Vol 18, Iss 1, Pp 1-9 (2020)
Druh dokumentu: article
ISSN: 1479-5876
DOI: 10.1186/s12967-020-02298-9
Popis: Abstract Background Sequencing of miRNAs isolated from exosomes has great potential to identify novel disease biomarkers, but exosomes have low amount of RNA, hindering adequate analysis and quantification. Here, we have assessed several steps in developing an optimized small RNA (sRNA) library preparation protocol for next-generation sequencing (NGS) miRNA analysis from urinary exosomes. Methods A total of 24 urinary exosome samples from donors were included in this study. RNA was extracted by column-based methods. The quality of extracted RNA was assessed by spectrophotometric quantification and Bioanalyzer software analysis. All libraries were prepared using the CleanTag small RNA library preparation protocol and the effect of our additional modifications on adapter-dimer presence, sequencing data and tagged small RNA library population was also analyzed. Results Our results show that good quality sequencing libraries can be prepared following our optimized small RNA library preparation protocol from urinary exosomes. When the size selection by gel purification step was included within the workflow, adapter-dimer was totally removed from cDNA libraries. Furthermore, the inclusion of this modification step within small RNA library protocol augmented the small RNA mapped reads, with an especially significant 37% increase in miRNA reads, and the gel purification step made no difference to the tagged miRNA population. Conclusions This study provides researchers with an optimized small RNA library preparation workflow for next generation sequencing based exosome-associated miRNA analysis that yields a high amount of miRNA mapped reads without skewing the tagged miRNA population significantly.
Databáze: Directory of Open Access Journals
Externí odkaz:
Nepřihlášeným uživatelům se plný text nezobrazuje