Systematic assessment of commercially available low-input miRNA library preparation kits. Issue 1 (2nd January 2020)

• Record Type: Journal Article
• Authors: Heinicke, Fatima; Zhong, Xiangfu; Zucknick, Manuela; Breidenbach, Johannes; Sundaram, Arvind Y. M.; T. Flåm, Siri; Leithaug, Magnus; Dalland, Marianne; Farmer, Andrew; Henderson, Jordana M.; Hussong, Melanie A.; Moll, Pamela; Nguyen, Loan; McNulty, Amanda; Shaffer, Jonathan M.; Shore, Sabrina; Yip, Hoichong Karen; Vitkovska, Jana; Rayner, Simon; Lie, Benedicte A; Gilfillan, Gregor D.
• Is Part Of: RNA biology. Volume 17:Issue 1(2020)
• Page Start: 75
• Page End: 86
• Publication Date: 2020-01-02
• Subjects: MicroRNA -- miRNA -- small RNA-seq -- library preparation -- sequencing bias -- low RNA input -- NGS -- next generation sequencing -- UMI; RNA -- Periodicals; Molecular biology -- Periodicals; Molecular biology; RNA; Periodicals; 572.8805
• DOI: 10.1080/15476286.2019.1667741
• Languages: English
• ISSNs: 1547-6286

Abstract

ABSTRACT: High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.