Accurate expression quantification from nanopore direct RNA sequencing with NanoCount

Gleeson, Josie, Leger, Adrien, Prawer, Yair D. J., Lane, Tracy A., Harrison, Paul J., Haerty, Wilfried ORCID: and Clark, Michael B. (2022) Accurate expression quantification from nanopore direct RNA sequencing with NanoCount. Nucleic Acids Research, 50 (4). ISSN 0305-1048

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Accurately quantifying gene and isoform expression changes is essential to understanding cell functions, differentiation and disease. Sequencing full-length native RNAs using long-read direct RNA sequencing (DRS) has the potential to overcome many limitations of short and long-read sequencing methods that require RNA fragmentation, cDNA synthesis or PCR. However, there are a lack of tools specifically designed for DRS and its ability to identify differential expression in complex organisms is poorly characterised. We developed NanoCount for fast, accurate transcript isoform quantification in DRS and demonstrate it outperforms similar methods. Using synthetic controls and human SH-SY5Y cell differentiation into neuron-like cells, we show that DRS accurately quantifies RNA expression and identifies differential expression of genes and isoforms. Differential expression of 231 genes, 333 isoforms, plus 27 isoform switches were detected between undifferentiated and differentiated SH-SY5Y cells and samples clustered by differentiation state at the gene and isoform level. Genes upregulated in neuron-like cells were associated with neurogenesis. NanoCount quantification of thousands of novel isoforms discovered with DRS likewise enabled identification of their differential expression. Our results demonstrate enhanced DRS isoform quantification with NanoCount and establish the ability of DRS to identify biologically relevant differential expression of genes and isoforms.

Item Type: Article
Additional Information: DATA AVAILABILITY: FAST5 and FASTQ files are publicly available to download from ENA: PRJEB39347. All code used to perform the analysis (custom scripts, R workflows for DGE, DTE and DIU) is available on GitHub:; NanoCount is available at: FUNDING: Australian National Health and Medical Research Council Early Career Fellowship [APP1072662]; Investigator Fellowship [APP1196841 to M.B.C.]; Wellcome Trust (Seed Award in Science) [201879/Z/16/Z to M.B.C.]; Strategic Award [102616 to P.J.H.]; UK Medical Research Council [MR/P026028/1 to P.J.H.]; National Institute for Health Research (NIHR) Oxford Health Biomedical Research Centre [BRC-1215-20005 to P.J.H.]; BBSRC, Institute Strategic Programme Grant [BB/J004669/1]; BBSRC Core Strategic Programme Grant [BB/P016774/1 to W.H.]; A.L. was supported by the EMBL Interdisciplinary Postdocs Programme (EIPOD) with co-funding from Marie Skłodowska-Curie actions COFUND [847543]. Funding for open access charge: Lab funds.
Uncontrolled Keywords: genetics,sdg 3 - good health and well-being ,/dk/atira/pure/subjectarea/asjc/1300/1311
Faculty \ School: Faculty of Science > School of Biological Sciences
Faculty of Medicine and Health Sciences > Norwich Medical School
UEA Research Groups: Faculty of Medicine and Health Sciences > Research Centres > Norwich Institute for Healthy Aging
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Depositing User: LivePure Connector
Date Deposited: 03 Dec 2021 01:45
Last Modified: 21 Apr 2023 01:17
DOI: 10.1093/nar/gkab1129


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