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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...
Conserved Binding Sites01:49

Conserved Binding Sites

Many proteins’ biological role depends on their interactions with their ligands, small molecules that bind to specific locations on the protein known as ligand-binding sites. Ligand-binding sites are often conserved among homologous proteins as these sites are critical for protein function.
Binding sites are often located in large pockets, and if their location on a protein’s surface is unknown, it can be predicted using various approaches. The energetic method computationally analyses the...
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...
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...

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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

Assessing computational methods of cis-regulatory module prediction.

Jing Su1, Sarah A Teichmann, Thomas A Down

  • 1MRC Laboratory of Molecular Biology, Cambridge, United Kingdom.

Plos Computational Biology
|December 15, 2010
PubMed
Summary
This summary is machine-generated.

Identifying cis-regulatory modules (CRMs) computationally is challenging. This study compares CRM prediction tools, finding that methods using evolutionary conservation perform best and tool choice depends on species and genomic context.

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Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes
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Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Identifying cis-regulatory modules (CRMs) is crucial for understanding gene regulation.
  • Computational tools for CRM prediction face challenges due to limited knowledge of transcription factor interactions.
  • A comprehensive comparison of existing CRM prediction tools is lacking.

Purpose of the Study:

  • To categorize and compare the performance of computational methods for predicting cis-regulatory modules (CRMs).
  • To identify factors influencing the accuracy of CRM prediction tools across different species and genomic regions.

Main Methods:

  • Twelve representative CRM prediction methods were selected and categorized based on search strategy and input data.
  • Methods were applied to predict CRMs from the Drosophila REDfly database and human ENCODE regions.
  • Performance was evaluated based on prediction accuracy and ability to discriminate CRMs from non-coding regions.

Main Results:

  • Methods incorporating evolutionary conservation showed superior predictive power compared to single-genome approaches.
  • Optimal tool selection is species-dependent and influenced by sequence composition.
  • Different CRM representations and search strategies highlight complementary strengths of various methods.

Conclusions:

  • No single CRM prediction method is universally optimal; choice depends on specific genomic context and species.
  • Evolutionary conservation is a key feature for improving CRM prediction accuracy.
  • Future CRM prediction tool development should consider cross-species applicability and genomic features.