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Related Concept Videos

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...
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...
Combinatorial Gene Control02:33

Combinatorial Gene Control

Combinatorial gene control is the synergistic action of several transcriptional factors to regulate the expression of a single gene. The absence of one or more of these factors may lead to a significant difference in the level of gene expression or repression.
The expression of more than 30,000 genes is controlled by approximately 2000-3000 transcription factors. This is possible because a single transcription factor can recognize more than one regulatory sequence. The specificity in gene...
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

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
07:55

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

Computational methods for the detection of cis-regulatory modules.

Peter Van Loo1, Peter Marynen

  • 1Department of Human Genetics, VIB and University of Leuven, B-3000 Leuven, Belgium. peter.vanloo@med.kuleuven.be

Briefings in Bioinformatics
|June 6, 2009
PubMed
Summary

Identifying cis-regulatory modules (CRMs) is crucial for understanding metazoan gene regulation. This study reviews computational methods for detecting CRMs, highlighting their current limitations and future potential for genome annotation.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Metazoan transcription relies on cis-regulatory modules (CRMs) bound by transcription factors.
  • Annotation of CRMs lags significantly behind transcriptome annotation.
  • Accurate CRM identification is essential for understanding gene regulation.

Purpose of the Study:

  • To provide an overview of computational methods for detecting CRMs in metazoan genomes.
  • To categorize existing CRM detection approaches.
  • To discuss the strengths, limitations, and future prospects of these methods.

Main Methods:

  • Categorization of computational CRM detection methods into three classes: CRM scanners, CRM builders, and CRM genome screeners.
  • Description of CRM scanners utilizing predefined models, often based on multiple position weight matrices (PWMs).
  • Explanation of CRM builders that construct models for CRMs regulating co-expressed genes and CRM genome screeners identifying clusters of transcription factor binding sites.

Main Results:

  • CRM scanners are currently the most advanced but have limited applicability.
  • CRM builders show promise for future advancements, especially when utilizing PWM libraries.
  • The study categorizes and evaluates diverse computational strategies for CRM identification.

Conclusions:

  • CRM builders, enhanced by PWM libraries, are poised to be instrumental in annotating metazoan regulatory regions.
  • Further development of computational tools is needed to overcome current limitations in CRM detection.
  • This review aids researchers in selecting appropriate methods for CRM identification and genome annotation.