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Comparative analysis of pacbio and oxford nanopore sequencing technologies for transcriptomic landscape identification of penaeus monodon
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Document Title
Comparative analysis of pacbio and oxford nanopore sequencing technologies for transcriptomic landscape identification of penaeus monodon
Author
Udaondo Z., Sittikankaew K., Uengwetwanit T., Wongsurawat T., Sonthirod C., Jenjaroenpun P., Pootakham W., Karoonuthaisiri N., Nookaew I.
Name from Authors Collection
Scopus Author ID
56030033100
Affiliations
Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, United States; National Center for Genetic Engineering and Biotechnology (BIOTEC), National Science and Technology Development Agency, Pathum Thani12120, Thailand; Division of Bioinformatics and Data Management for Research, Department of Research and Development, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, 10700, Thailand; National Omics Center (NOC), National Science and Technology Development Agency (NSTDA), Pathum Thani12120, Thailand
Type
Article
Source Title
Life
ISSN
20751729
Year
2021
Volume
11
Issue
8
Open Access
Gold, Green
Publisher
MDPI AG
DOI
10.3390/life11080862
Abstract
With the advantages that long-read sequencing platforms such as Pacific Biosciences (Menlo Park, CA, USA) (PacBio) and Oxford Nanopore Technologies (Oxford, UK) (ONT) can offer, various research fields such as genomics and transcriptomics can exploit their benefits. Selecting an appropriate sequencing platform is undoubtedly crucial for the success of the research outcome, thus there is a need to compare these long-read sequencing platforms and evaluate them for specific research questions. This study aims to compare the performance of PacBio and ONT platforms for transcriptomic analysis by utilizing transcriptome data from three different tissues (hepatopancreas, intestine, and gonads) of the juvenile black tiger shrimp, Penaeus monodon. We compared three important features: (i) main characteristics of the sequencing libraries and their alignment with the reference genome, (ii) transcript assembly features and isoform identification, and (iii) correlation of the quantification of gene expression levels for both platforms. Our analyses suggest that read-length bias and differences in sequencing throughput are highly influential factors when using long reads in transcriptome studies. These comparisons can provide a guideline when designing a transcriptome study utilizing these two long-read sequencing technologies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Funding Sponsor
National Science Foundation; National Institutes of Health; National Institute of General Medical Sciences; University of Arkansas for Medical Sciences; Horizon 2020 Framework Programme; Arkansas Economic Development Commission; National Science and Technology Development Agency; National Center for Genetic Engineering and Biotechnology
License
CC BY
Rights
Author
Publication Source
Scopus