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Viral Recombination

Viral Recombination

Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.

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Related Experiment Video

Updated: Oct 5, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

A mixture model for determining SARS-Cov-2 variant composition in pooled samples.

Renan Valieris¹, Rodrigo D Drummond¹, Alexandre Defelicibus¹

¹Laboratory of Computational Biology and Bioinformatics, CIPE/A.C. Camargo Cancer Center, São Paulo 01508-010, Brazil.

Bioinformatics (Oxford, England)

|February 1, 2022

Summary

This summary is machine-generated.

Genomic surveillance is crucial for tracking Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) variants. A new statistical model accurately estimates variant proportions in pooled samples, including wastewater, aiding disease control efforts.

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Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Related Experiment Videos

Last Updated: Oct 5, 2025

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Large-Scale SARS-CoV-2 Testing Utilizing Saliva and Transposition Sample Pooling

Published on: June 23, 2022

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Quantification and Whole Genome Characterization of SARS-CoV-2 RNA in Wastewater and Air Samples

Published on: June 30, 2023

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Area of Science:

Genomics
Epidemiology
Bioinformatics

Background:

The emergence of SARS-CoV-2 variants necessitates continuous genomic surveillance.
Unequal vaccine distribution and ongoing infections drive viral evolution.
Effective tools are needed to analyze viral composition in complex samples like wastewater.

Purpose of the Study:

To develop a statistical model for estimating SARS-CoV-2 variant frequencies in pooled samples.
To provide an analytical tool for genomic surveillance of viral evolution.
To support the analysis of meta-transcriptomic sequencing data, including environmental samples.

Main Methods:

A statistical model was developed to estimate relative frequencies of SARS-CoV-2 variants.
The model utilizes genomic polymorphisms to identify and quantify variants.
It supports both raw sequencing reads and predefined variant call formats.

Main Results:

The proposed method accurately recovers variant proportions in simulated data.
Analysis of wastewater samples from Switzerland showed good agreement with epidemiological data.
The model is effective for tracking SARS-CoV-2 variants in complex mixtures like wastewater.

Conclusions:

The developed statistical model is a valuable tool for real-time genomic surveillance.
It enhances the ability to monitor SARS-CoV-2 variant spread and evolution.
The method is applicable to environmental surveillance, aiding public health strategies.