Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/129728
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Type: Journal article
Title: Insufficiently complex unique-molecular identifiers (UMIs) distort small RNA sequencing
Author: Saunders, K.
Bert, A.G.
Dredge, B.K.
Toubia, J.
Gregory, P.A.
Pillman, K.A.
Goodall, G.J.
Bracken, C.P.
Citation: Scientific Reports, 2020; 10(1):1-9
Publisher: Springer Nature
Issue Date: 2020
ISSN: 2045-2322
2045-2322
Statement of
Responsibility: 
Klay Saunders, Andrew G. Bert, B. Kate Dredge, John Toubia, Philip A. Gregory, Katherine A. Pillman, Gregory J. Goodall, Cameron P. Bracken
Abstract: 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.
Keywords: Epithelial Cells
Mesenchymal Stem Cells
Humans
MicroRNAs
RNA
Sequence Analysis, DNA
Sequence Analysis, RNA
Algorithms
Rights: © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
DOI: 10.1038/s41598-020-71323-0
Grant ID: http://purl.org/au-research/grants/arc/DP190103333
http://purl.org/au-research/grants/nhmrc/1129353
http://purl.org/au-research/grants/nhmrc/1118170
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