Evidence map›Paper›PMID 40355874›Full record

ArticleBMC infectious diseases2025

Utilizing Nanopore direct RNA sequencing of blood from patients with sepsis for discovery of co- and post-transcriptional disease biomarkers.

Jingni He, Devika Ganesamoorthy, Jessie J-Y Chang, Jianshu Zhang, Sharon L Trevor, Kristen S Gibbons, Stephen J McPherson, Jessica C Kling, Luregn J Schlapbach, Antje Blumenthal and 2 more

Abstract read
In one paragraph

Article in BMC infectious diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Jingni He *Department of Clinical Pathology, The University of Melbourne, Parkville, Australia.
Devika Ganesamoorthy *Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia.
Jessie J-Y Chang *Department of Microbiology and Immunology, The University of Melbourne, Parkville, Australia.
Jianshu ZhangDepartment of Microbiology and Immunology, The University of Melbourne, Parkville, Australia.
Sharon L TrevorDepartment of Microbiology and Immunology, The University of Melbourne, Parkville, Australia.
Kristen S GibbonsChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, Brisbane, Australia.
Stephen J McPhersonFrazer Institute, The University of Queensland, Brisbane, Australia.
Jessica C KlingFrazer Institute, The University of Queensland, Brisbane, Australia.
Luregn J SchlapbachChildren's Intensive Care Research Program, Child Health Research Centre, The University of Queensland, Brisbane, Australia.
Antje BlumenthalFrazer Institute, The University of Queensland, Brisbane, Australia.
Lachlan J M CoinDepartment of Clinical Pathology, The University of Melbourne, Parkville, Australia. lachlan.coin@unimelb.edu.au.
RAPIDS Study Group

Funding

Medical Research Future Fund GHFM76734National Health and Medical Research Council GNT1195743
6 · The paper itself

Abstract

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 sequencing to sequence native mRNA extracted from whole blood from 12 patients with definite 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 Pearson's correlation of 0.927 at the gene level and 0.736 at the transcript isoform level. We identified 2 genes with differential polyadenylation, 9 genes with differential expression and 4 genes with 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 mRNA of genes involved in signaling and short tails in oxidoreductase molecular functions. Additionally, we detected 240 non-artifactual novel transcript isoforms.

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.

Indexed as

BiomarkersNanopore SequencingSepsisSequence Analysis, RNAFemaleGene Expression ProfilingHumansMaleMiddle AgedNanoporesRNA, MessengerTranscriptomeBiomarkersRNA, MessengerDifferential transcript usageDirect RNA-sequencingDisease biomarkersLong-read sequencingNovel isoform detectionOxford Nanopore TechnologiesPolyadenylation

Identifiers

PMID40355874
PMCPMC12070577

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.