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Related Experiment Video

Updated: May 10, 2026

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Published on: July 2, 2016

Viral categorization and discovery in human circulation by transcriptome sequencing.

Weihua Wang¹, Xiaoan Zhang, Yanjuan Xu

¹Division of Gastroenterology and Hepatology, Department of Internal Medicine, Saint Louis University School of Medicine, St. Louis, MO 63104, USA.

Biochemical and Biophysical Research Communications

|June 15, 2013

Summary

This summary is machine-generated.

Researchers explored human serum RNA for viral discovery, overcoming concerns about RNA degradation. This method uses transcriptome sequencing and bioinformatics for potential clinical applications in identifying viral causes of disease.

Keywords:

Multiple displacement amplification Next-generation sequencing Viral discovery

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Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

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High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Area of Science:

Biochemistry
Virology
Bioinformatics

Background:

Serum is an accessible patient specimen.
RNA in serum is underexplored due to degradation concerns.

Purpose of the Study:

To document the use of human serum RNA for viral categorization and discovery.
To demonstrate the utility of an integrated bioinformatic approach for viral identification.

Main Methods:

Transcriptome sequencing of human serum RNA.
Analysis using curated databases and advanced bioinformatic tools.

Main Results:

Successfully utilized human serum RNA for viral categorization.
Demonstrated the feasibility of viral discovery using this approach.

Conclusions:

Human serum RNA can be effectively used for viral identification.
This integrated approach has potential clinical applications for diagnosing viral diseases.