Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

<jats:title>Abstract</jats:title><jats:p>Accurately quantifying gene and isoform expression changes is essential to understanding cell functions, differentiation and disease. Therefore, a crucial requirement of RNA sequencing is identifying differential expression. The recent development of long-read direct RNA (dRNA) sequencing has the potential to overcome many limitations of short and long-read sequencing methods that require RNA fragmentation, cDNA synthesis or PCR. dRNA sequences native RNA and can encompass an entire RNA in a single read. However, its ability to identify differential gene and isoform expression in complex organisms is poorly characterised. Using a mixture of synthetic controls and human SH-SY5Y cell differentiation into neuron-like cells, we show that dRNA sequencing accurately quantifies RNA expression and identifies differential expression of genes and isoforms. We generated ∼4 million dRNA reads with a median length of 991 nt. On average, reads covered 74% of SH-SY5Y transcripts and 29% were full-length. Measurement of expression and fold changes between synthetic control RNAs confirmed accurate quantification of genes and isoforms. Differential expression of 231 genes, 291 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. We further identified &gt;30,000 expressed transcripts including thousands of novel splice isoforms and transcriptional units. Our results establish the ability of dRNA sequencing to identify biologically relevant differences in gene and isoform expression and perform the key capabilities of expression profiling methodologies.</jats:p>

Original publication

DOI

10.1101/2020.08.02.232785

Type

Journal article

Publisher

Cold Spring Harbor Laboratory

Publication Date

04/08/2020