Random Priming
Random Priming - Related Videos
06:16
Verbal Priming
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2023
Source: Laboratory of Jonathan Flombaum—Johns Hopkins University Human memory seems to work in two broad ways. Like modern computers, the human mind has explicit, or declarative, memory: ask a question, and a person gives the best answer they can. Input a query, and a computer program returns the contents of the relevant parts of its stored memory. Humans also have a second kind of memory system, one not really typical of computers, one that experimental psychologists call implicit. Implicit...
11:14
Primer-Free Aptamer Selection Using A Random DNA Library
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Cited by 20 •
2010
SELEX protocols comprise multiple rounds of selection, each of which require regeneration of bound ligands, which in turn require fixed primer sequences flanking the random library regions. These fixed primer sequences can interfere with the selection process (false positives and negatives). Here we present a primer-free protocol.
13:54
Tractable Mammalian Cell Infections with Protozoan-primed Bacteria
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Cited by 2 •
2013
This technique provides a method to harvest, normalize and quantify intracellular growth of bacterial pathogens that are pre-cultivated in natural protozoan host cells prior to infections of mammalian cells. This method can be modified to accommodate a wide variety of host cells for the priming stage as well as target cell types.
09:34
Intravital Imaging of Neutrophil Priming Using IL-1β Promoter-driven DsRed Reporter Mice
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Cited by 1 •
2016
This current protocol employs fluorescent reporters, in vivo labeling, and intravital imaging techniques to enable monitoring of the dynamic process of neutrophil priming in living animals.
04:00
A Murine Model of Primed Mycobacterial Uveitis to Study Post-Infectious Uveitis
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2025
This video demonstrates a method to generate a mouse model of primed mycobacterial uveitis (PMU) for studying post-infectious uveitis. Upon induction of PMU by intravitreal injection of heat-killed Mycobacterium tuberculosis in a mouse previously immunized with the same immunogen, the progression of chronic inflammation in the eye is analyzed using imaging and histopathological...
FAQs
Because primers can anneal at complementary sites distributed across RNA molecules, reverse transcriptase can initiate synthesis from more than one location on the available templates. This produces a collection of cDNA fragments representing different parts of the RNA population. The resulting coverage is broader than an approach centered on one transcript-specific starting site, supporting analysis of diverse expressed sequences.
Random Priming is useful when the goal is to represent many RNA molecules rather than selectively copy one known transcript. A transcript-specific primer focuses synthesis on its matching target, whereas multiple random primers can generate cDNA from varied templates in the sample. This distinction makes the technique suitable for broad expression studies and discovery-oriented analyses.
Highly abundant RNA molecules may contribute disproportionately to the resulting cDNA population because more template molecules are available for primer annealing and extension. Consequently, broad priming does not guarantee equal representation of every transcript. When interpreting expression profiles, investigators should consider whether dominant RNA species could influence the apparent distribution of sequences.
Degradation changes the available RNA template into shorter or incomplete molecules, which can alter where primers anneal and which regions become represented in cDNA. Although random priming can initiate synthesis across the remaining template, the resulting fragments may not reflect the original transcript population evenly. This condition is therefore important when assessing coverage and comparing expression results.
The workflow begins with RNA templates and random oligonucleotide primers, allowing the primers to anneal at complementary sites across the molecules. Reverse transcriptase then extends the annealed primers to produce cDNA fragments. That cDNA can subsequently support transcriptome profiling, reverse transcription quantitative PCR, or RNA sequencing, depending on the study’s analytical objective.
Cancer researchers can apply the technique when they need broad gene-expression information from tumors or cancer model systems. The resulting cDNA supports transcriptome profiling, reverse transcription quantitative PCR, and RNA sequencing. These applications can help examine diverse expressed transcripts across cancer-related samples, while interpretation should account for representation changes caused by RNA abundance or degradation.