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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...

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Updated: Jun 21, 2026

Transcription Start Site Mapping Using Super-low Input Carrier-CAGE

Transcription Start Site Mapping Using Super-low Input Carrier-CAGE

Published on: June 26, 2019

Methods for analyzing deep sequencing expression data: constructing the human and mouse promoterome with deepCAGE

Piotr J Balwierz¹, Piero Carninci, Carsten O Daub

¹Biozentrum, University of Basel, and Swiss Institute of Bioinformatics, Klingelbergstrasse 50/70, 4056-CH, Basel, Switzerland.

|July 24, 2009

Summary

This summary is machine-generated.

Researchers developed new methods for analyzing deep sequencing data in gene expression studies. These techniques were applied to cap analysis of gene expression (CAGE) data to create comprehensive genome-wide promoter maps.

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Area of Science:

Genomics
Bioinformatics
Molecular Biology

Background:

Ultra-high-throughput sequencing technologies are increasingly used for gene expression studies.
Deep sequencing offers powerful insights into gene regulation.

Purpose of the Study:

To present rigorous methods for normalization, noise quantification, and co-expression analysis of deep sequencing data.
To construct genome-wide promoter maps using these methods.

Main Methods:

Development of robust statistical methods for deep sequencing data analysis.
Application of these methods to 122 cap analysis of gene expression (CAGE) samples.
Construction of hierarchical promoter maps in human and mouse.

Main Results:

A comprehensive genome-wide analysis of transcription start sites (TSS) was performed.
A three-tiered hierarchy of TSS, transcription start clusters, and transcription start regions was established.
The developed methods enable accurate quantification of noise and co-expression patterns.

Conclusions:

The presented methods provide a rigorous framework for analyzing deep sequencing data in gene expression studies.
The constructed 'promoteromes' offer a valuable resource for understanding genome-wide transcription regulation.
This work advances the analysis of large-scale gene expression datasets.