Mrna Expression Profiling
Mrna Expression Profiling - Related Videos
02:51
mRNA Stability and Gene Expression
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2020
The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity. Cis-acting Elements involved in mRNA stability
02:51
mRNA Stability and Gene Expression
0 Views •
2023
The structure and stability of mRNA molecules regulates gene expression, as mRNAs are a key step in the pathway from gene to protein. In eukaryotes, the half-life of mRNA varies from a few minutes up to several days. mRNA stability is essential in growth and development. The absence of the proteins regulating its stability, such as tristetraprolin in mice, can cause systemic issues, including bone marrow overgrowth, inflammation, and autoimmunity. Cis-acting Elements involved in mRNA stability
07:31
Profiling Voltage-gated Potassium Channel mRNA Expression in Nigral Neurons using Single-cell RT-PCR Techniques
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Cited by 2 •
2011
Neurons are first characterized electrophysiologically. Then the cytoplasm from the recorded neuron is aspirated and subjected to reverse transcription-PCR analysis to detect the expression of mRNAs for neurotransmitter synthesis enzymes, ion channels, and receptors.
08:29
Expression Profiling with Microarrays
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2023
Microarrays are important tools for profiling gene expression, and are based on complementary binding between probes that are attached to glass chips and nucleic acids derived from samples. Using these arrays, scientists can simultaneously evaluate the expression of thousands of genes. In addition, the expression profiles of different cells or tissue types can be compared, allowing researchers to deduce how the expression of different genes change during biological processes, and thus gain...
10:00
Assessment of Selective mRNA Translation in Mammalian Cells by Polysome Profiling
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Cited by 50 •
2014
The ability of cells to adapt to stress is crucial for their survival. Regulation of mRNA translation is one such adaptation strategy, providing for rapid regulation of the proteome. Here, we provide a standardized polysome profiling protocol to identify specific mRNAs that are selectively translated under stress conditions.
FAQs
The key analytical signal is the difference in transcript abundance between cells or tissues. Increased or decreased levels can indicate that gene activity changes with cellular identity, development, synaptic activity, disease, injury, or treatment. Comparing these patterns helps researchers associate molecular changes with particular cellular states rather than examining gene activity in isolation.
After mRNA is isolated, it can be converted into complementary DNA, or cDNA, before measurement. This conversion provides a form of the transcript material that can be quantified using approaches such as microarrays or RNA sequencing. The cDNA step therefore connects the original messenger-RNA population to the technologies used to measure expression levels.
Microarrays and RNA sequencing are measurement approaches used after transcript preparation to quantify mRNA patterns. Applying either method allows researchers to compare which transcripts are present and how their levels differ among samples. Those comparisons can expose coordinated expression patterns associated with biological conditions, including changes linked to nervous-system function or disorder.
A typical workflow begins by isolating RNA from cells or tissues. Researchers then convert the mRNA into complementary DNA and quantify the resulting transcript representation with microarrays or RNA sequencing. The measured profiles can subsequently be compared across conditions to identify differences in gene activity and relate them to cellular or tissue states.
In neuroscience, researchers can use expression profiles to examine molecular patterns associated with neuronal identity, development, and synaptic activity. The same approach can compare nervous-system samples affected by disease, injury, or treatment. These applications help connect changes in transcription with neuronal states and broader processes underlying nervous-system function.
Expression data can reveal patterns that point to altered molecular pathways, candidate biomarkers, or transcriptional changes associated with neurological disorders. Researchers can also use the profiles to connect a cellular state with its gene-expression signature. These outcomes support interpretation of how molecular activity relates to disease, injury responses, treatment effects, and nervous-system behavior.