Genomic Surveillance
Genomic Surveillance - Related Videos
09:30
Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
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Cited by 11 •
2018
This protocol provides researchers with a new tool to monitor the fidelity of transcription in multiple model organisms.
05:19
A New Technique for Treating Low-risk Prostate Cancer—Super Active Surveillance
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2025
Overtreatment is often administered to patients with low-risk prostate cancer; super-active surveillance can help avoid such overtreatment.
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
Principles of Disease Surveillance
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2025
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
01:27
Immune Surveillance by NK Cells and Phagocytes
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2026
Immune surveillance is an integral part of the innate immune system, involving the continuous monitoring of peripheral tissues to detect and respond to pathogens, infected cells, or cancerous cells. This surveillance is conducted primarily by natural killer (NK) cells and phagocytes, which employ distinct but complementary mechanisms to identify and eliminate threats. Natural Killer Cells: The Fast Responders NK cells are large granular lymphocytes found in the blood and lymphatic system. These...
FAQs
Sequencing generates genetic information from collected biological samples, while bioinformatics provides the computational analysis needed to compare those sequences. This comparison can identify mutations, distinguish genetic differences among organisms, and organize related genomes into lineages. Together, these steps turn raw genetic data into evidence about how populations change and where particular variants occur.
Mutations provide measurable genetic differences that help distinguish one genome from another. When related genomes share patterns of change, they can be grouped into lineages, which represent connected genetic histories within a population. Tracking mutations and lineages helps investigators recognize emerging variants, follow their distribution, and examine how genetic change contributes to biological evolution or disease spread.
Comparing pathogen genomes from different samples can show which organisms are more closely related genetically and how those relationships are distributed across locations. When combined with information about where samples were collected, the comparisons can reveal patterns of transmission and movement. This evidence supports investigation of outbreaks and helps identify how particular lineages spread through populations.
The meaning of surveillance data depends on the samples available for comparison and the locations and time periods they represent. Organizing genetic findings by place and over time allows researchers to track changing variant distributions and detect shifts in lineages. These comparisons provide the context needed to interpret whether observed genetic patterns reflect local change, broader movement, or both.
A typical workflow begins with collecting biological samples, followed by DNA or RNA sequencing to obtain genetic information. Bioinformatics then compares the resulting genomes to identify mutations, group related sequences, and examine their distribution across locations or lineages. The interpreted results can be used to monitor population change, investigate transmission, or detect emerging genetic variants.
It is especially useful when researchers need to detect emerging strains, monitor how variants spread, or examine genetic changes that may influence disease transmission or treatment. During outbreaks, genomic evidence can clarify transmission patterns and support response decisions. More broadly, the approach provides a way to follow changing pathogen populations rather than relying only on individual observations.
In biology, the same surveillance framework can be applied to questions about evolution, biodiversity, antimicrobial resistance, and the movement of genes through populations. Comparing genetic information over time helps researchers examine how organisms and populations change, while tracking particular genetic patterns can reveal the distribution of traits or lineages across biological populations.