Utilising Nanopore direct RNA sequencing of blood from patients with sepsis for discovery of co- and post-transcriptional disease biomarkers
He, J.; Ganesamoorthy, D.; Chang, J. J.-Y.; Zhang, J.; Trevor, S. L.; Gibbons, K. S.; McPherson, S. J.; Kling, J. C.; Schlapbach, L. J.; Blumenthal, A.; The RAPIDS Study Group, ; Coin, L. J. M.
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BackgroundRNA sequencing of whole blood has been increasingly employed to find transcriptomic signatures of disease states. These studies traditionally utilize short-read sequencing of cDNA, missing important aspects of RNA expression such as differential isoform abundance and poly(A) tail length variation. MethodsWe used Oxford Nanopore Technologies long-read sequencing to sequence native mRNA extracted from whole blood from 12 patients with suspected bacterial and viral sepsis, and compared with results from matching Illumina short-read cDNA sequencing data. Additionally, we explored poly(A) tail length variation, novel transcript identification and differential transcript usage. ResultsThe correlation of gene count data between Illumina cDNA and Nanopore RNA-sequencing strongly depended on the choice of analysis pipeline; NanoCount for Nanopore and Kallisto for Illumina data yielded the highest mean Pearsons correlation of 0.93 at gene level and 0.74 at transcript isoform level. We identified 18 genes significantly differentially polyadenylated and 4 genes with significant differential transcript usage between bacterial and viral infection. Gene ontology gene set enrichment analysis of poly(A) tail length revealed enrichment of long tails in signal transduction and short tails in oxidoreductase molecular functions. Additionally, we detected 594 non-artifactual novel transcript isoforms, including 9 novel isoforms for Immunoglobulin lambda like polypeptide 5 (IGLL5). ConclusionsNanopore RNA- and Illumina cDNA-gene counts are strongly correlated, indicating that both platforms are suitable for discovery and validation of gene count biomarkers. Nanopore direct RNA-seq provides additional advantages by uncovering additional post- and co-transcriptional biomarkers, such as poly(A) tail length variation and transcript isoform usage.
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