Dataset Information

TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions.

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/.

SUBMITTER: Leporcq C

PROVIDER: S-EPMC7319436 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions.

Leporcq Clémentine C Spill Yannick Y Balaramane Delphine D Toussaint Christophe C Weber Michaël M Bardet Anaïs Flore AF

Nucleic acids research 20200701 W1

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 moti ...[more]

PMID: 32324215

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Project description:BackgroundClassically, models of DNA-transcription factor binding sites (TFBSs) have been based on relatively few known instances and have treated them as sites of fixed length using position weight matrices (PWMs). Various extensions to this model have been proposed, most of which take account of dependencies between the bases in the binding sites. However, some transcription factors are known to exhibit some flexibility and bind to DNA in more than one possible physical configuration. In some cases this variation is known to affect the function of binding sites. With the increasing volume of ChIP-seq data available it is now possible to investigate models that incorporate this flexibility. Previous work on variable length models has been constrained by: a focus on specific zinc finger proteins in yeast using restrictive models; a reliance on hand-crafted models for just one transcription factor at a time; and a lack of evaluation on realistically sized data sets.ResultsWe re-analysed binding sites from the TRANSFAC database and found motivating examples where our new variable length model provides a better fit. We analysed several ChIP-seq data sets with a novel motif search algorithm and compared the results to one of the best standard PWM finders and a recently developed alternative method for finding motifs of variable structure. All the methods performed comparably in held-out cross validation tests. Known motifs of variable structure were recovered for p53, Stat5a and Stat5b. In addition our method recovered a novel generalised version of an existing PWM for Sp1 that allows for variable length binding. This motif improved classification performance.ConclusionsWe have presented a new gapped PWM model for variable length DNA binding sites that is not too restrictive nor over-parameterised. Our comparison with existing tools shows that on average it does not have better predictive accuracy than existing methods. However, it does provide more interpretable models of motifs of variable structure that are suitable for follow-up structural studies. To our knowledge, we are the first to apply variable length motif models to eukaryotic ChIP-seq data sets and consequently the first to show their value in this domain. The results include a novel motif for the ubiquitous transcription factor Sp1.

Project description:BackgroundNeuroblastoma, a cancer derived from precursor cells of the sympathetic nervous system, is a major cause of childhood cancer related deaths. The single most important prognostic indicator of poor clinical outcome in this disease is genomic amplification of MYCN, a member of a family of oncogenic transcription factors.MethodologyWe applied MYCN chromatin immunoprecipitation to microarrays (ChIP-chip) using MYCN amplified/non-amplified cell lines as well as a conditional knockdown cell line to determine the distribution of MYCN binding sites within all annotated promoter regions.ConclusionAssessment of E-box usage within consistently positive MYCN binding sites revealed a predominance for the CATGTG motif (p<0.0016), with significant enrichment of additional motifs CATTTG, CATCTG, CAACTG in the MYCN amplified state. For cell lines over-expressing MYCN, gene ontology analysis revealed enrichment for the binding of MYCN at promoter regions of numerous molecular functional groups including DNA helicases and mRNA transcriptional regulation. In order to evaluate MYCN binding with respect to other genomic features, we determined the methylation status of all annotated CpG islands and promoter sequences using methylated DNA immunoprecipitation (MeDIP). The integration of MYCN ChIP-chip and MeDIP data revealed a highly significant positive correlation between MYCN binding and DNA hypermethylation. This association was also detected in regions of hemizygous loss, indicating that the observed association occurs on the same homologue. In summary, these findings suggest that MYCN binding occurs more commonly at CATGTG as opposed to the classic CACGTG E-box motif, and that disease associated over expression of MYCN leads to aberrant binding to additional weaker affinity E-box motifs in neuroblastoma. The co-localization of MYCN binding and DNA hypermethylation further supports the dual role of MYCN, namely that of a classical transcription factor affecting the activity of individual genes, and that of a mediator of global chromatin structure.

Dataset Information

TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions.

Publications

TFmotifView: a webserver for the visualization of transcription factor motifs in genomic regions.

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