Insufficiently complex unique-molecular identifiers (UMIs) distort small RNA sequencing.

The attachment of unique molecular identifiers (UMIs) to RNA molecules prior to PCR amplification and sequencing, makes it possible to amplify libraries to a level that is sufficient to identify rare molecules, whilst simultaneously eliminating PCR bias through the identification of duplicated reads. Accurate de-duplication is dependent upon a sufficiently complex pool of UMIs to allow unique labelling. In applications dealing with complex libraries, such as total RNA-seq, only a limited variety of UMIs are required as the variation in molecules to be sequenced is enormous. However, when sequencing a less complex library, such as small RNAs for which there is a more limited range of possible sequences, we find increased variation in UMIs are required, even beyond that provided in a commercial kit specifically designed for the preparation of small RNA libraries for sequencing. We show that a pool of UMIs randomly varying across eight nucleotides is not of sufficient depth to uniquely tag the microRNAs to be sequenced. This results in over de-duplication of reads and the marked under-estimation of expression of the more abundant microRNAs. Whilst still arguing for the utility of UMIs, this work demonstrates the importance of their considered design to avoid errors in the estimation of gene expression in libraries derived from select regions of the transcriptome or small genomes.

Extensive transcriptional responses are co-ordinated by microRNAs as revealed by Exon-Intron Split Analysis (EISA).

Epithelial-mesenchymal transition (EMT) has been a subject of intense scrutiny as it facilitates metastasis and alters drug sensitivity. Although EMT-regulatory roles for numerous miRNAs and transcription factors are known, their functions can be difficult to disentangle, in part due to the difficulty in identifying direct miRNA targets from complex datasets and in deciding how to incorporate 'indirect' miRNA effects that may, or may not, represent biologically relevant information. To better understand how miRNAs exert effects throughout the transcriptome during EMT, we employed Exon-Intron Split Analysis (EISA), a bioinformatic technique that separates transcriptional and post-transcriptional effects through the separate analysis of RNA-Seq reads mapping to exons and introns. We find that in response to the manipulation of miRNAs, a major effect on gene expression is transcriptional. We also find extensive co-ordination of transcriptional and post-transcriptional regulatory mechanisms during both EMT and mesenchymal to epithelial transition (MET) in response to TGF-ß or miR-200c respectively. The prominent transcriptional influence of miRNAs was also observed in other datasets where miRNA levels were perturbed. This work cautions against a narrow approach that is limited to the analysis of direct targets, and demonstrates the utility of EISA to examine complex regulatory networks involving both transcriptional and post-transcriptional mechanisms.