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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...

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...

The Eukaryotic Promoter Region

The Eukaryotic Promoter Region

The eukaryotic promoter region is a segment of DNA located upstream of a gene. It contains an RNA polymerase binding site, a transcription start site, and several cis-regulatory sequences. The proximal promoter region is located in the vicinity of the gene and has cis-regulatory sequences and the core promoter. The core promoter is the binding site for RNA polymerase and is usually located between -35 and +35 nucleotides from the transcription start site. The distal promoter regions are...

The Eukaryotic Promoter Region

The Eukaryotic Promoter Region

The eukaryotic promoter region is a segment of DNA located upstream of a gene. It contains an RNA polymerase binding site, a transcription start site, and several cis-regulatory sequences. The proximal promoter region is located in the vicinity of the gene and has cis-regulatory sequences and the core promoter. The core promoter is the binding site for RNA polymerase and is usually located between -35 and +35 nucleotides from the transcription start site. The distal promoter regions are...

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...

RNA Polymerase II Accessory Proteins

RNA Polymerase II Accessory Proteins

Proteins that regulate transcription can do so either via direct contact with RNA Polymerase or through indirect interactions facilitated by adaptors, mediators, histone-modifying proteins, and nucleosome remodelers. Direct interactions to activate transcription is seen in bacteria as well as in some eukaryotic genes. In these cases, upstream activation sequences are adjacent to the promoters, and the activator proteins interact directly with the transcriptional machinery. For example, in...

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Related Experiment Video

Updated: Jun 19, 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

Genomic promoter analysis predicts functional transcription factor binding.

J Sunil Rao¹, Suresh Karanam, Colleen D McCabe

¹Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH 44106, USA.

Advances in Bioinformatics

|September 28, 2011

Summary

Identifying functional transcription factor binding sites (TFBSs) is challenging. This study introduces a new algorithm integrating conserved TFBS analysis and chromatin immunoprecipitation data for accurate prediction of TFBS in vivo.

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Related Experiment Videos

Last Updated: Jun 19, 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

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

Promoter Capture Hi-C: High-resolution, Genome-wide Profiling of Promoter Interactions

Published on: June 28, 2018

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Identifying Transcription Factor Olig2 Genomic Binding Sites in Acutely Purified PDGFRα+ Cells by Low-cell Chromatin Immunoprecipitation Sequencing Analysis

Published on: April 16, 2018

Area of Science:

Computational Biology
Genomics
Bioinformatics

Background:

Accurate identification of functional transcription factor binding sites (TFBSs) is a significant challenge in computational biology.
Understanding TFBSs is crucial for deciphering gene regulation and cellular function.

Purpose of the Study:

To computationally identify conserved transcription factor binding sites (TFBSs) in human genes.
To develop a novel algorithm for predicting in vivo transcription factor binding site occupancy.
To assess the accuracy of integrating conserved TFBS analysis with experimental data for functional site prediction.

Main Methods:

Analysis of conserved promoter sequences for human RefSeq genes using conserved transcription factor binding site (CONFAC) software.
Identification of human-mouse ortholog gene pairs with conserved TFBS in proximal promoter and first intron regions.
Development of a marginal effect isolator algorithm based on Bayesian methods for TFBS filtering and in vivo occupancy prediction.

Main Results:

CONFAC software analyzed 16296 human-mouse ortholog gene pairs, identifying conserved TFBS in 9107 genes.
The novel algorithm predicted in vivo transcription factor binding site occupancy with 84% accuracy for two factors.
Conserved TFBS analysis revealed significant overlap in promoter and intronic regions across orthologous genes.

Conclusions:

Integrating chromatin immunoprecipitation data with conserved TFBS analysis enables accurate prediction of functional TFBS.
TFBS co-occurrence patterns can effectively predict transcription factor binding to promoters in vivo.
This approach enhances the understanding of gene regulatory mechanisms and transcription factor roles.