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RNA-seq

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases.
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...

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Updated: Jun 25, 2025

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

High-Throughput Transcriptome Analysis for Investigating Host-Pathogen Interactions

Published on: March 5, 2022

Unveiling Inter- and Intra-Patient Sequence Variability with a Multi-Sample Coronavirus Target Enrichment Approach.

Sara Lado¹, Jakob Thannesberger¹, Kathrin Spettel^2,3

¹Division of Infectious Diseases and Tropical Medicine, Department of Medicine 1, Medical University of Vienna, 1090 Vienna, Austria.

|May 25, 2024

Summary

This summary is machine-generated.

This study used next-generation sequencing (NGS) to track SARS-CoV-2 evolution, identifying key mutations in viral genes like Spike and Nucleocapsid. The findings highlight the importance of genomic surveillance for understanding emerging variants.

Keywords:

COVID-19 frequency high throughput metagenomics pandemic target enrichment variants virus

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Last Updated: Jun 25, 2025

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Area of Science:

Genomics
Virology
Molecular Biology

Background:

The COVID-19 pandemic necessitated rapid understanding of SARS-CoV-2 evolution.
Genomic surveillance is critical for tracking viral dynamics and host-virus interactions.

Purpose of the Study:

To explore SARS-CoV-2 evolution using a high-throughput next-generation sequencing (NGS) approach.
To identify specific viral genes and mutations indicative of viral evolution and selection pressures.

Main Methods:

Utilized nasal swab and mouthwash samples from COVID-19 patients across diverse geographical regions and infection waves.
Applied a targeted enrichment protocol and pooling strategy to enhance detection sensitivity in NGS.
Analyzed mutations across 10 distinct viral gene regions.

Main Results:

The NGS approach yielded a high number of reads and mutations.
Envelope, Nucleocapsid, and Open Reading Frame 8 genes exhibited the highest mutation rates.
Spike and Nucleocapsid genes showed evidence of positive selection, indicating adaptive evolution.
The pooling strategy successfully detected subtle sequence variability.

Conclusions:

SARS-CoV-2 evolution is dynamic, influenced by virus-host interplay.
Continuous genomic surveillance is essential for understanding viral dynamics and emerging variants.
The described NGS approach is a versatile, fast, and cost-efficient tool for variant screening.