Related Concept Videos
02:24Ribosome Profiling
Ribosome profiling or ribo-sequencing is a deep sequencing technique that produces a snapshot of active translation in a cell. It selectively sequences the mRNAs protected by ribosomes to get an insight into a cell’s translation landscape at any given point in time.
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
Applications of ribosome profiling
Ribosome profiling has many applications, including in vivo monitoring of translation inside a particular organ or tissue type and quantifying new protein synthesis levels.
The technique helps...
02:51mRNA Stability and Gene Expression
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
Cis-acting Elements involved in mRNA stability
02:07Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
02:07Improving Translational Accuracy
Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
01:58Cell Specific Gene Expression
Multicellular organisms contain a variety of structurally and functionally distinct cell types, but the DNA in all the cells originated from the same parent cells. The differences in the cells can be attributed to the differential gene expression. Liver cells, whose functions include detoxification of blood, production of bile to metabolize fats, and synthesis of proteins essential for metabolism, must express a specific set of genes to perform their functions. Gene expression also varies with...
01:36What is Gene Expression?
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is comprised of nucleotides and proteins are comprised of amino acids, a mediator is required to convert the information encoded in DNA into proteins. This mediator is the messenger RNA (mRNA). mRNA copies the blueprint from DNA by a process called transcription. In eukaryotes, transcription occurs in the nucleus by complementary base-pairing with the DNA template. The mRNA is then processed and...
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09:58
Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis
Published on: June 27, 2020
Transcript profiling and expression level mapping.
Elena Potokina1, Arnis Druka, Michael J Kearsey
1School of Biosciences, University of Birmingham, Birmingham, UK.
Methods in Molecular Biology (Clifton, N.J.)
|April 7, 2009
Summary
Researchers identified over 4,000 transcript-derived markers (TDMs) from gene expression data. These markers enable high-throughput genotyping and prediction of genotypes in barley populations.
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Area of Science:
- Genomics
- Molecular Biology
- Bioinformatics
Background:
- Transcript abundance data from microarrays offer potential for genetic marker discovery.
- High-throughput genotyping is crucial for genetic studies and breeding.
Purpose of the Study:
- To develop and validate a method for identifying transcript-derived markers (TDMs) from gene expression data.
- To assess the utility of TDMs for high-throughput genotyping and genotype prediction in barley.
Main Methods:
- Utilized Affymetrix expression arrays to analyze transcript abundance data.
- Developed a computational method to identify polymorphic TDMs from two barley varieties and their doubled-haploid progeny.
- Categorized TDMs into single feature polymorphisms (SFPs) and genetic expression markers (GEMs).
Main Results:
- Identified over 4,000 robust TDMs, representing approximately 18% of barley genes on the array.
- Demonstrated that TDMs can accurately predict genotypes in an F(1)-derived, doubled-haploid population.
- Found that 35% of TDMs are SFPs and 65% are GEMs, with GEMs likely acting as cis-acting regulators.
Conclusions:
- Transcript abundance data is a valuable resource for discovering genetic markers.
- TDMs derived from expression arrays are effective for high-throughput genotyping and predicting genotypes.
- GEMs represent a significant class of markers potentially involved in gene regulation.