Genomic Loci Visualization
Genomic Loci Visualization - Related Videos
08:03
Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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Cited by 2 •
2021
This analytical computational platform provides practical guidance for microbiologists, ecologists, and epidemiologists interested in bacterial population genomics. Specifically, the work presented here demonstrated how to perform: i) phylogeny-guided mapping of hierarchical genotypes; ii) frequency-based analysis of genotypes; iii) kinship and clonality analyses; iv) identification of lineage differentiating accessory loci.
03:44
Isolation and Visualization of Rotavirus Genome via Gel Electrophoresis
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2026
Source: Philip, A. A., et al., Simplified Reverse Genetics Method to Recover Recombinant Rotaviruses Expressing Reporter Proteins. J. Vis. Exp. (2020)This video demonstrates the isolation of rotavirus double-stranded RNA from clarified cell lysates. It further illustrates the separation and visualization of genome segments through polyacrylamide gel electrophoresis.
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.
08:31
Genome Editing
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2023
A well-established technique for modifying specific sequences in the genome is gene targeting by homologous recombination, but this method can be laborious and only works in certain organisms. Recent advances have led to the development of “genome editing”, which works by inducing double-strand breaks in DNA using engineered nuclease enzymes guided to target genomic sites by either proteins or RNAs that recognize specific sequences. When a cell attempts to repair this damage, mutations can be...
13:19
Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
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Cited by 16 •
2013
Human endogenous retroviruses (HERV), which occupy 8% of the human genome, retain scarce coding capacities but a hundred thousand long terminal repeats (LTRs). A custom Affymetrix microarray was designed to identify individual HERV locus expression and was used on prostate cancer tissues as a proof of concept for future clinical studies.
FAQs
A reference assembly provides a common coordinate framework for positioning features consistently. Genomic Loci Visualization can therefore place genes, variants, sequence reads, and regulatory elements at their corresponding coordinates rather than showing them as unrelated records. This shared reference makes it easier to inspect whether a mutation lies within a gene, near a regulatory feature, or in another relevant genomic region.
Annotation tracks make different types of genomic information comparable within the same coordinate system. A researcher can view gene structure alongside variants, sequence reads, conservation scores, or regulatory elements and examine how those features relate spatially. Combining these layers helps reveal patterns that may be difficult to recognize when each dataset is considered separately.
Comparing alleles in the same locus-centered view helps distinguish sequence differences from their genomic context. Researchers can examine where variants fall relative to gene structure and other displayed features, then assess whether a region is a plausible candidate for disease association. The comparison is useful because the allele is considered alongside surrounding organization, not as an isolated sequence change.
To examine a locus, researchers first use genomic coordinates tied to a reference assembly, then select relevant tracks such as annotations, reads, conservation scores, or regulatory elements. Viewing these layers together allows the same region to be inspected from several perspectives. The resulting display can guide focused interpretation of gene structure, variants, and relationships among nearby genomic features.
Genomic Loci Visualization supports variant validation by showing a candidate change alongside sequence reads and the surrounding annotated region. This context lets researchers inspect the relationship between the observed sequence information, the variant's genomic position, and nearby gene features. Such a view can strengthen interpretation of whether the displayed evidence is consistent with the reported locus.
Beyond individual variant review, these displays support genome annotation, comparative genomics, and communication of genomic findings. Conservation scores can add comparative context, while regulatory elements and gene structure help organize functional interpretation. Presenting these data on one locus-centered view gives researchers a concise way to communicate how multiple observations relate within a specific genomic region.