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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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SARS-CoV-2 Genome Sequencing Methods Differ in Their Abilities To Detect Variants from Low-Viral-Load Samples.

C Lam¹, K Gray^1,2, M Gall²

¹Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia.

Journal of Clinical Microbiology

|August 11, 2021

Summary

This summary is machine-generated.

The ARTIC v3 sequencing method is most sensitive for detecting SARS-CoV-2 variants in low-load samples. Choosing the right method is crucial for accurate genomic surveillance and understanding COVID-19 transmission.

Keywords:

SARS-CoV-2 genomics public health variants

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Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

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Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Published on: July 2, 2016

Area of Science:

Virology
Genomics
Epidemiology

Background:

Genomic surveillance of SARS-CoV-2 is essential for tracking COVID-19, identifying variants, and understanding transmission.
Low viral loads in clinical samples challenge the accurate detection of variants and low-frequency mutations.

Purpose of the Study:

To systematically evaluate the sensitivity, specificity, and low-frequency variant detection capabilities of three common SARS-CoV-2 whole-genome sequencing methods.
To determine the optimal sequencing strategy for analyzing samples with low viral loads.

Main Methods:

Comparative analysis of three SARS-CoV-2 whole-genome sequencing protocols: ARTIC v3, Illumina Respiratory Viral Oligo panel, and a pooled long-amplicon method.
Evaluation of sensitivity, specificity, and detection of low-frequency variants using clinical specimens with varying viral loads.

Main Results:

The ARTIC v3 protocol demonstrated superior sensitivity in generating complete SARS-CoV-2 genomes from low-viral-load samples compared to the other two methods.
Significant variability was observed in the number and location of low-frequency variants detected across the three methods.
ARTIC v3 showed higher consistency in detecting variants at low viral loads.

Conclusions:

The ARTIC v3 method is recommended for robust SARS-CoV-2 genomic surveillance, particularly in samples with low viral loads.
Method selection significantly impacts the quality of sequence data and the ability to detect low-frequency variants, crucial for public health.
Optimized sequencing strategies are vital for accurate phylogenetic analyses and uncovering transmission chains.