Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

What is Gene Expression?01:42

What is Gene Expression?

195.3K
Overview
Gene expression is the process in which DNA directs the synthesis of functional products, that is, proteins. Cells can regulate gene expression at various stages. It allows organisms to generate different cell types and enables cells to adapt to internal and external factors.
Genetic Information Flows from DNA to RNA to Protein
A gene is a stretch of DNA that serves as the blueprint for functional RNAs and proteins. Since DNA is made up of nucleotides and proteins consist of amino...
195.3K
What is Gene Expression?01:36

What is Gene Expression?

11.2K
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...
11.2K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

16.3K
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...
16.3K
Cell Specific Gene Expression01:58

Cell Specific Gene Expression

5.4K
5.4K
Chromatin Position Affects Gene Expression02:35

Chromatin Position Affects Gene Expression

24.7K
Chromatin is the massive complex of DNA and proteins packaged inside the nucleus. The complexity of chromatin folding and how it is packaged inside the nucleus greatly influences  access to genetic information. Generally, the nucleus' periphery is considered transcriptionally repressive, while the cell's interior is considered a transcriptionally active area. 
Topologically Associated Domains (TADs)
The 3-dimensional positioning of chromatin in the nucleus influences the...
24.7K
mRNA Stability and Gene Expression02:51

mRNA Stability and Gene Expression

6.6K
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
6.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Exploring the feasibility of modeling next-day fatigue and sleepiness using digital sleep tracker data in neurodegenerative and immune-mediated inflammatory diseases.

Frontiers in digital health·2026
Same author

An integrated human immunoglobulin germline resource linking allele diversity to expressed repertoire structure.

bioRxiv : the preprint server for biology·2026
Same author

Using objective measures of physical activity, sleep, and breathing for disease profiling of patients with systemic lupus erythematosus and Sjögren's disease.

Frontiers in digital health·2026
Same author

Circulating tumor DNA at baseline as a prognostic marker in untreated follicular lymphoma.

Haematologica·2026
Same author

IDEA-FAST clinical study protocol: Identifying digital end-points of fatigue, sleep quality and daytime sleepiness in N = 2000.

Digital health·2026
Same author

Enhancement of LuxS/AI-2 quorum sensing promotes biofilm formation and cryotolerance in Lactiplantibacillus plantarum.

Journal of the science of food and agriculture·2026
Same journal

Another 10 years of PLOS Computational Biology: A data-driven reflection on trends in genomics research.

PLoS computational biology·2026
Same journal

Mobility data resolution needed to inform predictive models of spatial epidemic spread from mobile phone data.

PLoS computational biology·2026
Same journal

DeepMethylation: A deep learning framework for tissue-specific DNA methylation prediction and functional variant annotation.

PLoS computational biology·2026
Same journal

Redefining and estimating the early-phase reproduction ratio for epidemic outbreaks in spatially structured populations.

PLoS computational biology·2026
Same journal

Optimized phenotype definitions boost GWAS power.

PLoS computational biology·2026
Same journal

Detection, communication, and individual identification with deep audio embeddings: A case study with North Atlantic right whales.

PLoS computational biology·2026
See all related articles

Related Experiment Video

Updated: Jan 26, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.3K

Gene set meta-analysis with Quantitative Set Analysis for Gene Expression (QuSAGE).

Hailong Meng1, Gur Yaari2, Christopher R Bolen3

  • 1Department of Pathology, Yale School of Medicine, New Haven, Connecticut, United States of America.

Plos Computational Biology
|April 3, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces QuSAGE meta-analysis, a powerful framework for detecting subtle gene expression changes. It enhances the ability to find significant biological signals by combining gene set analysis with meta-analysis of multiple studies.

More Related Videos

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
10:34

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Published on: April 14, 2010

16.0K
Analysis of Gene Expression in Emerald Ash Borer Agrilus planipennis Using Quantitative Real Time-PCR
11:22

Analysis of Gene Expression in Emerald Ash Borer Agrilus planipennis Using Quantitative Real Time-PCR

Published on: May 4, 2010

11.1K

Related Experiment Videos

Last Updated: Jan 26, 2026

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research
09:35

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research

Published on: August 16, 2017

18.3K
Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells
10:34

Using an Automated Cell Counter to Simplify Gene Expression Studies: siRNA Knockdown of IL-4 Dependent Gene Expression in Namalwa Cells

Published on: April 14, 2010

16.0K
Analysis of Gene Expression in Emerald Ash Borer Agrilus planipennis Using Quantitative Real Time-PCR
11:22

Analysis of Gene Expression in Emerald Ash Borer Agrilus planipennis Using Quantitative Real Time-PCR

Published on: May 4, 2010

11.1K

Area of Science:

  • Bioinformatics
  • Genomics
  • Statistical Genetics

Background:

  • Detecting subtle gene expression changes is challenging due to small sample sizes and high inter-individual variability.
  • Gene set analysis and meta-analysis are existing methods to improve the detection power in transcriptional profiling studies.

Purpose of the Study:

  • To present a novel framework, QuSAGE meta-analysis, for the meta-analysis of gene sets.
  • To enhance the detection of biologically relevant gene expression changes by integrating data from multiple studies.

Main Methods:

  • Developed QuSAGE meta-analysis, extending the existing QuSAGE framework.
  • The framework accounts for gene-gene correlations and quantifies gene set activity using a probability density function.

Main Results:

  • QuSAGE meta-analysis successfully identified significant gene set activity in influenza vaccination response data.
  • Detected significant biological signals that were not apparent in individual studies.

Conclusions:

  • QuSAGE meta-analysis provides a robust approach for integrating multiple gene expression studies.
  • This framework increases statistical power to detect subtle, coordinated gene expression changes, improving biological discovery.