TY - JOUR T1 - Comprehensive assessment of multiple biases in small RNA sequencing reveals significant differences in the performance of widely used methods JF - bioRxiv DO - 10.1101/445437 SP - 445437 AU - Carrie Wright AU - Anandita Rajpurohit AU - Emily E. Burke AU - Courtney Williams AU - Leonardo Collado-Torres AU - Martha Kimos AU - Nicholas J. Brandon AU - Alan J. Cross AU - Andrew E. Jaffe AU - Daniel R. Weinberger AU - Joo Heon Shin Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/01/17/445437.abstract N2 - Background High-throughput sequencing offers advantages over other quantification methods for microRNA (miRNA), yet numerous biases make reliable quantification challenging. Previous comparisons of library preparation methods have focused on adapter ligation bias and none have evaluated the influence of reverse transcription or amplification biases in small RNA sequencing. In addition, only one prior study has compared randomized adapter methods and adapter-free ligation methods, two methods known to mitigate adapter ligation bias. Furthermore, comparisons of the quantifications of isomiRs (miRNA isoforms) or the influence of starting amount on performance have been very limited. Only one prior study evaluated method differences in edited miRNA quantifications and no study had yet evaluated differences in the quantification of isomiRs of altered length. In addition, no studies had yet compared the consistency of results derived from multiple moderate starting inputs. We therefore evaluated quantifications of canonical miRNA and isomiRs using four library preparation kits, with various starting amounts (100ng to 2000ng), as well as quantifications following removal of duplicate reads using unique molecular identifiers (UMIs) to mitigate reverse transcription and amplification biases.Results Randomized adapter and adapter-free methods mitigated adapter ligation bias similarly; however, the adapter-free method was especially prone to false isomiR detection. We demonstrate that using UMIs improves accuracy and we provide a guide for input amounts to improve consistency.Conclusion Our data show differences and limitations of current methods, thus raising concerns about the validity of quantification of miRNA and isomiRs. Our work suggests that the use of UMIs may improve miRNA quantifications. ER -