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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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相关实验视频

Updated: Jun 5, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Published on: July 2, 2016

多音:检测病毒基因组测序数据中的样本间污染.

Lydia A Krasilnikova^1,2,3, Christopher H Tomkins-Tinch², Alton C Gayton⁴

¹Howard Hughes Medical Institute, Chevy Chase, MD 20815, United States.

Bioinformatics (Oxford, England)

|December 14, 2024

概括

在病毒测序数据中,Polyphonia使用现有的基因组信息检测到样本间的污染,从而消除了对额外控制的需求. 该工具通过在任何阶段识别污染来提高病毒基因组研究和监测的准确性.

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Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

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Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

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Published on: March 11, 2020

相关实验视频

Last Updated: Jun 5, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples

Published on: July 2, 2016

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'

Published on: May 26, 2013

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Validating Whole Genome Nanopore Sequencing, using Usutu Virus as an Example

Published on: March 11, 2020

科学领域:

基因组学就是基因组学.
生物信息学是一种生物信息学.
病毒学病毒学

背景情况:

样本间污染在病毒基因组研究中构成了重大挑战,影响了变种检测,进化分析和疫情重建.
现有的方法,如样本条形码,具有局限性,因为在实验管道中实施之前,它们无法检测污染.

研究的目的:

推出Polyphonia,这是一种新的计算工具,旨在直接从深度测序数据中检测样本间污染.
提供一种识别污染的方法,而不需要额外的实验控制.

主要方法:

波利福尼亚在测序数据中分析了宿主内部变异频率,以推断污染的存在.
该工具处理原始测序数据,利用固有的基因组信息来识别可能存在污染的异常.

主要成果:

多声波被应用于1102个SARS-CoV-2样本,证明了其检测样本间污染的能力.
该工具的性能与以前使用分子条形码跟踪的样本进行了验证,证实了它的准确性.

结论:

在病毒测序数据集中,Polyphonia提供了一种强大且无控制的方法,用于检测病毒测序数据集中的样本间污染.
该工具有可能提高病毒基因组研究,监测和疫情调查的可靠性.