scholarly journals Identification of Estrogen-responsive Genes Using a Genome-wide Analysis of Promoter Elements for Transcription Factor Binding Sites

2005 ◽  
Vol 280 (22) ◽  
pp. 21491-21497 ◽  
Author(s):  
Sitharthan Kamalakaran ◽  
Senthil K. Radhakrishnan ◽  
William T. Beck
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Promoter Elements ◽  
Genome Wide Analysis ◽  
Factor Binding ◽  
Genome Wide ◽  
A Genome

scholarly journals Estimating the functional impact of INDELs in transcription factor binding sites: a genome-wide landscape

2016 ◽  
Author(s):  
Esben Eickhardt ◽  
Thomas Damm Als ◽  
Jakob Grove ◽  
Anders Dupont Boerglum ◽  
Francesco Lescai
Keyword(s):  
Experimental Data ◽  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Functional Impact ◽  
Additional Tool ◽  
Factor Binding ◽  
Genome Wide ◽  
A Genome

AbstractBackgroundVariants in transcription factor binding sites (TFBSs) may have important regulatory effects, as they have the potential to alter transcription factor (TF) binding affinities and thereby affecting gene expression. With recent advances in sequencing technologies the number of variants identified in TFBSs has increased, hence understanding their role is of significant interest when interpreting next generation sequencing data. Current methods have two major limitations: they are limited to predicting the functional impact of single nucleotide variants (SNVs) and often rely on additional experimental data, laborious and expensive to acquire. We propose a purely bioinformatic method that addresses these two limitations while providing comparable results.ResultsOur method uses position weight matrices and a sliding window approach, in order to account for the sequence context of variants, and scores the consequences of both SNVs and INDELs in TFBSs. We tested the accuracy of our method in two different ways. Firstly, we compared it to a recent method based on DNase I hypersensitive sites sequencing (DHS-seq) data designed to predict the effects of SNVs: we found a significant correlation of our score both with their DHS-seq data and their prediction model. Secondly, we called INDELs on publicly available DHS-seq data from ENCODE, and found our score to represent well the experimental data. We concluded that our method is reliable and we used it to describe the landscape of variation in TFBSs in the human genome, by scoring all variants in the 1000 Genomes Project Phase 3. Surprisingly, we found that most insertions have neutral effects on binding sites, while deletions, as expected, were found to have the most severe TFBS-scores. We identified four categories of variants based on their TFBS-scores and tested them for enrichment of variants classified as pathogenic, benign and protective in ClinVar: we found that the variants with the most negative TFBS-scores have the most significant enrichment for pathogenic variants.ConclusionsOur method addresses key shortcomings of currently available bioinformatic tools in predicting the effects of INDELs in TFBSs, and provides an unprecedented window into the genome-wide landscape of INDELs, their predicted influences on TF binding, and potential relevance for human diseases. We thus offer an additional tool to help prioritising non-coding variants in sequencing studies.

scholarly journals Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data

2008 ◽  
Vol 5 (9) ◽  
pp. 829-834 ◽  
Author(s):  
Anton Valouev ◽  
David S Johnson ◽  
Andreas Sundquist ◽  
Catherine Medina ◽  
Elizabeth Anton ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Genome Wide Analysis ◽  
Factor Binding ◽  
Genome Wide ◽  
On Chip

scholarly journals An Integrated Pipeline for the Genome-Wide Analysis of Transcription Factor Binding Sites from ChIP-Seq

PLoS ONE ◽  
2011 ◽  
Vol 6 (2) ◽  
pp. e16432 ◽  
Author(s):  
Eloi Mercier ◽  
Arnaud Droit ◽  
Leping Li ◽  
Gordon Robertson ◽  
Xuekui Zhang ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Genome Wide Analysis ◽  
Factor Binding ◽  
Genome Wide

scholarly journals Genome-Wide Identification of Transcription Start Sites, Promoters and Transcription Factor Binding Sites in E. coli

PLoS ONE ◽  
2009 ◽  
Vol 4 (10) ◽  
pp. e7526 ◽  
Author(s):  
Alfredo Mendoza-Vargas ◽  
Leticia Olvera ◽  
Maricela Olvera ◽  
Ricardo Grande ◽  
Leticia Vega-Alvarado ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Binding Sites ◽  
Transcription Factor Binding Sites ◽  
Transcription Factor Binding ◽  
Transcription Start ◽  
Transcription Start Sites ◽  
E Coli ◽  
Factor Binding ◽  
Genome Wide
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