Dalland, M. | Search bioRxiv

bioRxiv2020

An extension to: Systematic assessment of commercially available low-input miRNA library preparation kits

High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. To assist researchers choose the most appropriate library preparation kit, we recently compared the performance of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. As before, performance was assessed with respect to sensitivity, reliability, titration response and differential expression. Despite NEXTflex employing partially-randomised adapter sequences to minimise bias, we reaffirm that biases in miRNA abundance are kit-specific, complicating the comparison of miRNA datasets generated using different kits.

molecular biology↗

bioRxiv2019

Systematic assessment of commercially available low-input miRNA library preparation kits

High-throughput sequencing is increasingly favoured to assay the presence and abundance of micro RNAs (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. However, 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 biological 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 sequence (UMI) 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 expected 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 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.

bioinformatics↗