Genome Analysis
Genome Analysis - Related Videos
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.
10:34
Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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Cited by 28 •
2019
Long-read sequences greatly facilitate the assembly of complex genomes and characterization of structural variation. We describe a method to generate ultra-long sequences by nanopore-based sequencing platforms. The approach adopts an optimized DNA extraction followed by modified library preparations to generate hundreds of kilobase reads with moderate coverage from human cells.
11:19
Genome-wide Analysis using ChIP to Identify Isoform-specific Gene Targets
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Cited by 13 •
2010
Here we are presenting a chromatin immunoprecipitation (ChIP) procedure for genome-wide location analysis of protein isoforms that differ in a histone-binding domain. We are applying it to ChIP-Seq analysis to identify the targets of the KDM5A/JARID1A/RBP2 histone demethylase.
08:56
Combining Analysis of DNA in a Crude Virion Extraction with the Analysis of RNA from Infected Leaves to Discover New Virus Genomes
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2018
Here we present a new approach to identify plant viruses with double-strand DNA genomes. We use standard methods to extract DNA and RNA from infected leaves and carry out next-generation sequencing. Bioinformatic tools assemble sequences into contigs, identify contigs representing virus genomes and assign genomes to taxonomic groups.
02:56
Fluorescence-Based Sorting of Individual Virus Particles for Genomic Analysis
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2026
Source: Zeigler Allen, L., et al. Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'. J. Vis. Exp. (2013).This video demonstrates how flow cytometry enables the isolation of individual, genome-containing viruses from mixed populations through fluorescence-based detection and precise particle sorting, followed by agarose embedding for subsequent genomic characterization.
FAQs
Sequence alignment places DNA sequences in comparable positions so researchers can examine similarities and differences between genomes or genomic regions. This comparison supports the identification of conserved sequence patterns, changes between organisms, and relationships among genetic materials. Its results provide a foundation for studying biological variation, evolution, and possible links between sequence content and cellular traits.
Genome assembly organizes sequence information into a representation of larger genomic structures. This step is important because individual sequence data must be arranged before researchers can examine genome organization or locate features for further interpretation. A well-organized assembly supports downstream processes such as variant detection, gene annotation, genome comparison, and investigation of how genetic information is arranged.
Variant detection identifies differences within or between genome sequences. These differences can be examined across individuals, populations, or organisms to investigate inherited disease, population diversity, and evolutionary change. Interpreting variants requires comparison with genomic context and other analytical results, helping researchers connect genetic differences with biological patterns rather than treating sequence changes as isolated observations.
Gene annotation links regions of a genome with information about their possible biological roles. After sequence organization and comparison, annotation helps researchers interpret where genes occur and how genomic content may relate to function. This step is especially useful for studying gene regulation, cellular traits, and organismal responses because it moves analysis from sequence patterns toward biological interpretation.
A typical workflow begins with DNA sequencing and continues through sequence alignment, genome assembly, variant detection, and gene annotation. Researchers select and combine these computational processes according to the question being studied, such as comparing organisms or examining inherited disease. The resulting analyses provide complementary information about sequence, organization, variation, and potential function.
Comparative genome analysis is useful when researchers need to examine evolutionary relationships, population diversity, or differences associated with biological traits. Comparing sequence content and genomic organization can reveal patterns shared across organisms as well as variation within populations. In biology, these results support studies of evolution and help clarify how genetic differences relate to organismal responses.
Genome analysis supports diverse investigations, including inherited disease, pathogen surveillance, personalized medicine, crop improvement, and the development of experimental models. The same general analytical foundation can therefore address both basic and applied questions. By characterizing sequence variation and genomic function, researchers can connect genetic information with health, agriculture, infectious disease monitoring, and model-organism research.
By examining genome organization, sequence variation, and annotated genes together, researchers can investigate how genetic information may influence cellular traits and organismal responses. Analysis does not rely on sequence alone; integrating computational comparisons with functional interpretation helps place genomic findings in biological context. This approach contributes to understanding gene regulation and the relationship between genomes and cell behavior.