Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Master Transcription Regulators

Master Transcription Regulators

Master transcription regulators are regulatory proteins that are predominantly responsible for regulating the expression of multiple genes. Often these genes work in concert to drive a complex process. Activation of a master transcription regulator can lead to a cascade of transcriptional activation necessary for that outcome. These regulators can directly bind to the regulatory sequences of the various genes involved, or they can indirectly regulate transcription by binding to regulatory...

DNA Microarrays

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

General Transcription Factors

General Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...

Cis-regulatory Sequences

Cis-regulatory Sequences

Cis-regulatory sequences are short fragments of non-coding DNA that are present on the same chromosomes as the genes that they regulate. These fragments serve as binding sites for transcriptional regulators, proteins that are responsible for controlling gene transcription and differential gene expression across cell types in eukaryotes. Cis-regulatory sequences can be close to the gene of interest or thousands of bases away in the DNA sequence; however, those sequences that are further away are...

Co-activators and Co-repressors

Co-activators and Co-repressors

Gene transcription is regulated by the synergistic action of several proteins that form a complex at a gene regulatory site. This is observed in eukaryotes, where the regulation of gene expression is a complex process. Regulatory proteins in eukaryotes can broadly be classified into two types – regulators that bind directly to specific DNA sequences and co-regulators that associate with regulatory proteins but cannot directly bind to the DNA. These co-regulators are further divided into...

Transcription Factors

Transcription Factors

Tissue-specific transcription factors contribute to diverse cellular functions in mammals. For example, the gene for beta globin, a major component of hemoglobin, is present in all cells of the body. However, it is only expressed in red blood cells because the transcription factors that can bind to the promoter sequences of the beta globin gene are only expressed in these cells. Tissue-specific transcription factors also ensure that mutations in these factors may impair only the function of...

You might also read

Related Articles

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

Sort by

Same author

Regulatory mechanisms driven by functional 3'-UTR variants in alcohol use disorder and related traits.

Genome biology·2026

Same author

Suicidality phenotypes reflect both shared and distinct genetic factors.

medRxiv : the preprint server for health sciences·2026

Same author

Perceived partner substance use, genetic predispositions, and their associations with problematic alcohol use, emotional well-being, and relationship quality.

Psychological medicine·2026

Same author

From Genomes to Conversations: Outreach and Engagement in Psychiatric Genetics.

Behavior genetics·2026

Same author

The Impact of Polygenic Risk, Parental Separation, and Parental Relationship Discord on Heavy Episodic Drinking Across Adolescence and Young Adulthood in a High-Risk Sample.

JAACAP open·2025

Same author

Mapping the genetic landscape across 14 psychiatric disorders.

Nature·2025

Search research articles

Related Experiment Video

Updated: Jul 5, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Mapping of trans-acting regulatory factors from microarray data.

Jeanette N McClintick^1,2, Yunlong Liu^3,2, Howard J Edenberg^1,2

¹Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, 635 Barnhill Drive, MS4063, Indianapolis, Indiana 46202, USA.

BMC Proceedings

|May 10, 2008

Summary

This study mapped gene expression regulators using linkage analysis on individual and composite transcript data. Composite measures effectively identified loci influencing multiple co-expressed genes, with cis linkages showing the highest significance.

More Related Videos

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Published on: February 11, 2019

Related Experiment Videos

Last Updated: Jul 5, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences

Published on: February 11, 2019

Area of Science:

Genetics
Bioinformatics
Systems Biology

Background:

Understanding gene expression regulation is crucial for deciphering complex biological processes.
Identifying genetic factors that control gene expression patterns is a key challenge in genomics.

Purpose of the Study:

To map factors regulating gene expression by analyzing individual and composite transcript data.
To evaluate the utility of composite expression measures for identifying regulatory loci.

Main Methods:

Utilized Affymetrix microarray data and genetic analysis using SOLAR.
Applied quality control measures to remove outlier arrays and noise.
Employed hierarchical clustering to group co-expressed genes and tested composite expression measures.

Main Results:

Probe sets with higher coefficients of variation (CVs) yielded more significant linkages (LOD > 2.0).
While trans-acting linkages were more frequent, cis-linkages exhibited the highest LOD scores (>4).
Composite measures (average signal, normalized signal, first principal component) successfully linked to regions affecting co-expressed genes in 8/19 clusters.

Conclusions:

Composite measures of gene expression are effective for identifying regulatory loci.
This approach can pinpoint genetic regions influencing multiple co-expressed genes simultaneously.
The study highlights the power of integrating gene expression data with genetic linkage analysis.