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Related Concept Videos

Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Cooperative Binding of Transcription Regulators02:13

Cooperative Binding of Transcription Regulators

Transcriptional regulators bind to specific cis-regulatory sequences in the DNA to regulate gene transcription. These cis-regulatory sequences are very short, usually less than ten nucleotide pairs in length. The short length means that there is a high probability of the exact same sequence randomly occurring throughout the genome.  Since regulators can also bind to groups of similar sequences, this further increases the chances of random binding. Transcriptional regulators form dimers that...
Cis-regulatory Sequences02:02

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...
Cis-regulatory Sequences02:02

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-repressors02:04

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...
Co-activators and Co-repressors02:04

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...

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Related Experiment Video

Updated: May 29, 2026

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example
12:44

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example

Published on: December 3, 2014

Two covariance models for iron-responsive elements.

Stewart G Stevens1, Paul P Gardner, Chris Brown

  • 1Biochemistry and Genetics Otago, University of Otago, Dunedin, New Zealand.

RNA Biology
|September 2, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces two new computational models for iron-responsive elements (IREs), improving the detection of these RNA regulatory elements. The enhanced models accurately identify known IREs and predict novel ones, aiding research into gene regulation.

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Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
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Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation
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Related Experiment Videos

Last Updated: May 29, 2026

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example
12:44

Electrophoretic Mobility Shift Assay (EMSA) for the Study of RNA-Protein Interactions: The IRE/IRP Example

Published on: December 3, 2014

Enhanced Yeast One-hybrid Screens To Identify Transcription Factor Binding To Human DNA Sequences
11:25

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

Published on: February 11, 2019

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation
09:07

Prediction and Validation of Gene Regulatory Elements Activated During Retinoic Acid Induced Embryonic Stem Cell Differentiation

Published on: June 21, 2016

Area of Science:

  • Molecular Biology
  • Bioinformatics
  • Genomics

Background:

  • Iron-responsive elements (IREs) are cis-acting RNA regulatory elements found in mRNA untranslated regions.
  • IREs modulate gene expression post-transcriptionally through interactions with Iron Regulatory Proteins (IRPs).
  • Known mechanisms involve IRP binding to 5' UTR IREs to decrease translation or 3' UTR IREs to increase RNA stability.

Purpose of the Study:

  • To develop improved computational models for identifying IREs.
  • To create two distinct IRE covariance models to capture sequence and structural diversity.
  • To enhance the accuracy and scope of IRE detection in genomic data.

Main Methods:

  • Development of two new IRE covariance models.
  • Inclusion of these models in the RFAM database as a new IRE clan.
  • Modeling of all experimentally supported IREs.

Main Results:

  • The new models demonstrate increased sensitivity and specificity in detecting known IREs.
  • The models show improved capability in predicting novel IREs.
  • The two-model approach better reflects the experimentally observed diversity of IRE structures.

Conclusions:

  • The developed IRE models offer a more precise and comprehensive tool for identifying these regulatory elements.
  • These models advance the study of iron regulation at the post-transcriptional level.
  • The findings facilitate the discovery of new IREs and the understanding of their roles in gene expression.