scholarly journals iDamIDseq and iDEAR: An improved method and a computational pipeline to profile chromatin-binding proteins of developing organisms

2016 ◽  
Author(s):  
Jose Arturo Gutierrez-Triana ◽  
Juan L. Mateo ◽  
David Ibberson ◽  
Joachim Wittbrodt
Keyword(s):  
Enrichment Analysis ◽  
Analysis Tool ◽  
Chromatin Binding ◽  
Dna Interactions ◽  
Aberrant Splicing ◽  
Specific Expression ◽  
Genome Wide ◽  
Protein Dna Interactions ◽  
Critical Issues ◽  
Dna Adenine Methyltransferase

AbstractDNA adenine methyltransferase identification (DamID) has emerged as an alternative for profiling protein-DNA interactions, however critical issues in the method limit its applicability. Here we present iDamlDseq, a protocol that improves specificity and robustness making its use compatible with developing organisms. In addition, we present the analysis tool iDEAR (iDamlDseq Enrichment Analysis with R) to determine protein-DNA interactions genome wide. The combination of both allows establishing highly reliable transcription factor profiles, even in transient assays. For tissue specific expression we improved the Dam coding sequence to overcome predominant aberrant splicing of Dam fusions we discovered with the commonly used sequence.

scholarly journals High similarity among ChEC-seq datasets

2021 ◽  
Author(s):  
Chitvan Mittal ◽  
Matthew J. Rossi ◽  
B. Franklin Pugh
Keyword(s):  
Rna Polymerase Ii ◽  
Transcriptional Regulators ◽  
Micrococcal Nuclease ◽  
High Similarity ◽  
Dna Interactions ◽  
Promoter Regions ◽  
Genome Wide ◽  
A Genome ◽  
Protein Dna Interactions ◽  
Negative Controls

AbstractChEC-seq is a method used to identify protein-DNA interactions across a genome. It involves fusing micrococcal nuclease (MNase) to a protein of interest. In principle, specific genome-wide interactions of the fusion protein with chromatin result in local DNA cleavages that can be mapped by DNA sequencing. ChEC-seq has been used to draw conclusions about broad gene-specificities of certain protein-DNA interactions. In particular, the transcriptional regulators SAGA, TFIID, and Mediator are reported to generally occupy the promoter/UAS of genes transcribed by RNA polymerase II in yeast. Here we compare published yeast ChEC-seq data performed with a variety of protein fusions across essentially all genes, and find high similarities with negative controls. We conclude that ChEC-seq patterning for SAGA, TFIID, and Mediator differ little from background at most promoter regions, and thus cannot be used to draw conclusions about broad gene specificity of these factors.

scholarly journals EAT-UpTF: Enrichment Analysis Tool for Upstream Transcription Fctors of a gene group

2020 ◽  
Author(s):  
Sangrea Shim ◽  
Pil Joon Seo
Keyword(s):  
Transcription Factors ◽  
Open Source ◽  
Chromatin Immunoprecipitation ◽  
Target Genes ◽  
Affinity Purification ◽  
Enrichment Analysis ◽  
Analysis Tool ◽  
Gene Group ◽  
Genome Wide ◽  
One Step

SummaryEAT-UpTF (Enrichment Analysis Tool for Upstream Transcription Factors of a gene group) is an open-source Python script that analyzes the enrichment of upstream transcription factors (TFs) in a group of genes-of-interest (GOIs). EAT-UpTF utilizes genome-wide lists of TF-target genes generated by DNA affinity purification followed by sequencing (DAP-seq) or chromatin immunoprecipitation followed by sequencing (ChIP-seq). Unlike previous methods based on the two-step prediction of cis-motifs and DNA-element-binding TFs, our EAT-UpTF analysis enabled a one-step identification of enriched upstream TFs in a set of GOIs using lists of empirically determined TF-target [email protected] or [email protected]://github.com/sangreashim/EAT-UpTF

scholarly journals Integrative analysis of public ChIP-seq experiments reveals a complex multi-cell regulatory landscape

2014 ◽  
Vol 43 (4) ◽  
pp. e27-e27 ◽  
Author(s):  
Aurélien Griffon ◽  
Quentin Barbier ◽  
Jordi Dalino ◽  
Jacques van Helden ◽  
Salvatore Spicuglia ◽  
...  
Keyword(s):  
Human Genome ◽  
Enrichment Analysis ◽  
Search Space ◽  
Regulatory Elements ◽  
Data Sets ◽  
Analysis Tool ◽  
Coding Regions ◽  
Genome Wide ◽  
Public Data ◽  
Cancer Genomes

Abstract The large collections of ChIP-seq data rapidly accumulating in public data warehouses provide genome-wide binding site maps for hundreds of transcription factors (TFs). However, the extent of the regulatory occupancy space in the human genome has not yet been fully apprehended by integrating public ChIP-seq data sets and combining it with ENCODE TFs map. To enable genome-wide identification of regulatory elements we have collected, analysed and retained 395 available ChIP-seq data sets merged with ENCODE peaks covering a total of 237 TFs. This enhanced repertoire complements and refines current genome-wide occupancy maps by increasing the human genome regulatory search space by 14% compared to ENCODE alone, and also increases the complexity of the regulatory dictionary. As a direct application we used this unified binding repertoire to annotate variant enhancer loci (VELs) from H3K4me1 mark in two cancer cell lines (MCF-7, CRC) and observed enrichments of specific TFs involved in biological key functions to cancer development and proliferation. Those enrichments of TFs within VELs provide a direct annotation of non-coding regions detected in cancer genomes. Finally, full access to this catalogue is available online together with the TFs enrichment analysis tool (http://tagc.univ-mrs.fr/remap/).

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