Viral Genome Assembly
Viral Genome Assembly - Related Videos
06:57
Dot Blot Assay to Quantify Viral Genome
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2025
In this video, we describe the dot blot assay to quantify a viral genome. The signal intensity is directly related to the amount of viral DNA in the sample.
03:36
Genome Annotation and Assembly
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2021
The genome refers to all of the genetic material in an organism. It can range from a few million base pairs in microbial cells to several billion base pairs in many eukaryotic organisms. Genome assembly refers to the process of taking the DNA sequencing data and putting it all back together in a correct order to create a close representation of the original genome. This is followed by the identification of functional elements on the newly assembled genome, a process called genome annotation.
08:31
Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'
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Cited by 2 •
2013
Single Virus Genomics (SVG) is a method to isolate and amplify the genomes of single virons. Viral suspensions of a mixed assemblage are sorted using flow cytometry onto a microscope slide with discrete wells containing agarose, thereby capturing the virion and reducing genome shearing during downstream processing. Whole genome amplification is achieved using multiple displacement amplification (MDA) resulting in genomic material that is suitable for sequencing.
01:26
Size and Structure of Viral Genomes
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2025
Viral genomes exhibit remarkable diversity in size, structure, and composition, influencing their replication strategies and interactions with host cells. These genomes consist of either DNA or RNA and may be linear or circular. Additionally, they can be single-stranded or double-stranded, with each configuration affecting how the virus propagates within a host. RNA viruses, for instance, generally have smaller genomes than DNA viruses, a factor that contributes to their high mutation rates and...
02:17
Visualizing Viral Structural Protein Assembly on Giant Unilamellar Vesicle Membranes
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2026
Source: Olety, B., et. al., Visualization of HIV-1 Gag Binding to Giant Unilamellar Vesicle (GUV) Membranes. J. Vis. Exp. (2016)This study demonstrates a fluorescence-based assay to observe the membrane-binding behavior of human immunodeficiency virus type-1 structural protein. Using synthetic giant unilamellar vesicles as model membranes, the assay visualizes protein recruitment and assembly, mimicking early steps of viral particle formation.
FAQs
The strategy depends on whether a suitable related genome is available. De novo assembly reconstructs sequence by connecting overlapping reads or traversing de Bruijn graphs, whereas reference-guided assembly aligns sequencing reads against a related viral genome. These approaches provide different computational routes to an assembled genome and support downstream identification, mutation tracking, and infection research.
Overlapping reads provide matching sequence segments that algorithms can connect into longer reconstructed regions. De Bruijn graph methods offer another route by representing sequence relationships as graph structures that software traverses. Both approaches address the same assembly challenge, but they organize sequencing information differently, influencing how computational systems reconstruct viral genomic sequence.
Quality filtering removes or limits unreliable sequencing information before it is interpreted, while coverage assessment shows how well the assembled sequence is supported by the available data. These checks help distinguish dependable viral sequence from errors or contamination. The resulting confidence is important when genomes are used for identification, mutation analysis, or outbreak investigation.
Contamination can introduce sequence that does not belong to the virus being studied, making the reconstructed genome less reliable. Quality filtering and coverage assessment help identify sequence that lacks adequate support or appears inconsistent with the intended viral genome. Addressing this issue strengthens conclusions about viral identity and genomic changes relevant to infection research.
A typical workflow begins with DNA or RNA sequencing data, followed by computational reconstruction using either overlapping reads, de Bruijn graphs, or alignment to a related genome. Quality filtering and coverage assessment then support evaluation of the result. The assembled sequence can subsequently inform virus identification, mutation tracking, transmission analysis, and surveillance.
They are especially useful when researchers need to identify infectious agents, compare viral sequences, track variants and mutations, or examine possible transmission patterns. These analyses contribute to genomic epidemiology, which connects genomic information with the spread of infection. The resulting evidence can strengthen surveillance and support public health responses to outbreaks.
Comparing assembled genomes can reveal genomic changes associated with host range, immune escape, or antiviral resistance. These findings provide a genetic perspective on how viruses interact with hosts and respond to pressures during infection or treatment. In immunology and infection studies, the information complements virus identification and transmission analysis by highlighting changes with potential biological significance.