UMMS Affiliation
Program in Bioinformatics and Integrative Biology; RNA Therapeutics Institute; Department of Biochemistry and Molecular Pharmacology
Publication Date
2018-07-13
Document Type
Article
Disciplines
Bioinformatics | Computational Biology | Genomics | Molecular Biology
Abstract
BACKGROUND: RNA-seq and small RNA-seq are powerful, quantitative tools to study gene regulation and function. Common high-throughput sequencing methods rely on polymerase chain reaction (PCR) to expand the starting material, but not every molecule amplifies equally, causing some to be overrepresented. Unique molecular identifiers (UMIs) can be used to distinguish undesirable PCR duplicates derived from a single molecule and identical but biologically meaningful reads from different molecules.
RESULTS: We have incorporated UMIs into RNA-seq and small RNA-seq protocols and developed tools to analyze the resulting data. Our UMIs contain stretches of random nucleotides whose lengths sufficiently capture diverse molecule species in both RNA-seq and small RNA-seq libraries generated from mouse testis. Our approach yields high-quality data while allowing unique tagging of all molecules in high-depth libraries.
CONCLUSIONS: Using simulated and real datasets, we demonstrate that our methods increase the reproducibility of RNA-seq and small RNA-seq data. Notably, we find that the amount of starting material and sequencing depth, but not the number of PCR cycles, determine PCR duplicate frequency. Finally, we show that computational removal of PCR duplicates based only on their mapping coordinates introduces substantial bias into data analysis.
Keywords
PCR cycle, PCR duplicates, RNA-seq, Ribognome, Sequencing depth, Small RNA-seq, Starting material, Transcriptome, UMI, Unique molecular identifier
Rights and Permissions
© The Author(s). 2018 Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
DOI of Published Version
10.1186/s12864-018-4933-1
Source
BMC Genomics. 2018 Jul 13;19(1):531. doi: 10.1186/s12864-018-4933-1. Link to article on publisher's site
Journal/Book/Conference Title
BMC genomics
Related Resources
PubMed ID
30001700
Repository Citation
Fu, Yu; Pei-Hsuan Wu; Beane, Timothy J.; Zamore, Phillip D.; and Weng, Zhiping, "Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers" (2018). Open Access Articles. 3552.
https://escholarship.umassmed.edu/oapubs/3552
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Included in
Bioinformatics Commons, Computational Biology Commons, Genomics Commons, Molecular Biology Commons