Abstract

Transcription factors (TFs) regulate the expression of gene expression. The binding specificities of many TFs have been deciphered and summarized as position-weight matrices, also called TF motifs. Despite the availability of hundreds of known TF motifs in databases, it remains non-trivial to quickly query and visualize the enrichment of known TF motifs in genomic regions of interest. Towards this goal, we developed TFmotifView, a web server that allows to study the distribution of known TF motifs in genomic regions. Based on input genomic regions and selected TF motifs, TFmotifView performs an overlap of the genomic regions with TF motif occurrences identified using a dynamic P-value threshold. TFmotifView generates three different outputs: (i) an enrichment table and scatterplot calculating the significance of TF motif occurrences in genomic regions compared to control regions, (ii) a genomic view of the organisation of TF motifs in each genomic region and (iii) a metaplot summarizing the position of TF motifs relative to the center of the regions. TFmotifView will contribute to the integration of TF motif information with a wide range of genomic datasets towards the goal to better understand the regulation of gene expression by transcription factors. TFmotifView is freely available at http://bardet.u-strasbg.fr/tfmotifview/.

Highlights

  • The regulation of gene expression is mediated by the binding of transcription factors (TFs) to regulatory regions [1]

  • We present TFmotifView, a web server that allows to study the distribution of known TF motifs in genomic regions

  • TFmotifView can analyse genomic regions acquired from different sources such as TF ChIP-seq peaks centered on their peak summits, regions with no define summit such as histone ChIP-seq regions, DNaseseq or ATAC-seq open chromatin regions, gene promoters or any other set of genomic regions of interest

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Summary

Introduction

The regulation of gene expression is mediated by the binding of transcription factors (TFs) to regulatory regions [1]. Hundreds of TF binding motifs have been determined experimentally using in vitro assays such as systematic evolution of ligands by exponential enrichment (SELEX) [2] or high-throughput SELEX [3] and protein-binding microarrays (PBM) [4,5], as well as in vivo approaches such as chromatin immunoprecipitation followed by high throughput sequencing (ChIPseq) [6] They have been summarized as position-weight matrices (PWMs) [7] and are freely available in TF motif databases such as JASPAR [8], cis-BP [4] and HOCOMOCO [9]. Once a motif is identified, it can be compared to known TF motifs found in databases, which is often directly performed by the de novo motif search methods

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