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Comprehensive maps of transcription factor (TF) binding sites in mouse (RNA-Seq)

ABSTRACT: Comprehensive maps of transcription factor (TF) binding sites in mouse (RNA-Seq)

PROVIDER: PRJNA692432 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR13443433.fastq.gz	Fastqsanger.gz
	SRR13443434.fastq.gz	Fastqsanger.gz
	SRR13443435.fastq.gz	Fastqsanger.gz
	SRR13443436.fastq.gz	Fastqsanger.gz
	SRR13443437.fastq.gz	Fastqsanger.gz

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Comprehensive maps of transcription factor (TF) binding sites in mouse (ATAC-Seq)

Project description:Comprehensive maps of transcription factor (TF) binding sites in mouse (ATAC-Seq)

| PRJNA692431 | ENA

Comprehensive maps of transcription factor (TF) binding sites in mouse (RNA-Seq)

Project description:Mammalian genome encodes approximately 1,700 transcription factors (TFs), 1,300 out of which have sequence specific binding motifs. Transcription in mammalian cells is regulated by the recruitment of TFs to specific cis-regulatory elements. In spite of consistent efforts on the function of individual TF, the question still remains how TFs bind to DNA and form enhancer. Here, we try to solve this problem by investigating the relationship between TF binding pattern and chromatin accessibility (ATAC-Seq). We first systematically acquired ATAC-Seq dataset as well as matched RNA-Seq dataset from different mouse primary tissues. A comprehensive TF binding map was built for each tissue/cell type by genomic approaches.

2022-07-21 | GSE164901 | GEO

Comprehensive maps of transcription factor (TF) binding sites in mouse (ATAC-Seq)

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Synthetic genetic circuit reveals overlapping binding sites underlie TF genomic occupancy

Project description:Synthetic genetic circuit reveals overlapping binding sites underlie TF genomic occupancy

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TF-COMB - Discovering grammar of transcription factor binding sites.

Project description:Cooperativity between transcription factors is important to regulate target gene expression. In particular, the binding grammar of TFs in relation to each other, as well as in the context of other genomic elements, is crucial for TF functionality. However, tools to easily uncover co-occurrence between DNA-binding proteins, and investigate the regulatory modules of TFs, are limited. Here we present TF-COMB (Transcription Factor Co-Occurrence using Market Basket analysis) - a tool to investigate co-occurring TFs and binding grammar within regulatory regions. We found that TF-COMB can accurately identify known co-occurring TFs from ChIP-seq data, as well as uncover preferential localization to other genomic elements. With the use of ATAC-seq footprinting and TF motif locations, we found that TFs exhibit both preferred orientation and distance in relation to each other, and that these are biologically significant. Finally, we extended the analysis to not only investigate individual TF pairs, but also TF pairs in the context of networks, which enabled the investigation of TF complexes and TF hubs. In conclusion, TF-COMB is a flexible tool to investigate various aspects of TF binding grammar.

| S-EPMC9358416 | biostudies-literature

Direct GR binding sites potentiate clusters of TF binding across the human genome

Project description:Direct GR binding sites potentiate clusters of TF binding across the human genome

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Synthetic genetic circuit reveals overlapping binding sites underlie TF genomic occupancy

Project description:Sequence-specific DNA binding by transcription factors (TFs) is required for accurately regulating target gene expression. However, rules governing TF-DNA interactions remain elusive because current high-throughput approaches to map them fail to identify lower-affinity interactions. To address this gap, we have developed PADIT-seq, a novel technology to detect TF-DNA interactions across the entire spectrum of affinities. By profiling the binding preferences of Egr1 and Hoxd13 to all possible 10-mers, we found that nucleotides flanking high-affinity binding sites create additional, overlapping lower-affinity sites that together modulate TF genomic occupancy. The formation of these extended recognition sequences is enabled by an inherent property of TF binding sites to interweave together. Highlighting the importance of lower-affinity binding sites, we provide mechanistic insights into their role in fine-tuning gene regulation.

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Comprehensive discovery of endogenous Argonaute binding sites in C. elegans

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Transcription Factor Binding Sites clustered Regions of 133 Cell Lines

Project description:Purpose: 224 GSM Samples form GSE32970 and GSE29692 was reanalyzed to find the TFBS-clustered regions of 133 cell lines. TFBS-clustered regions were divided into ten classes belong to the TF complexity. Methods: 1. We assigned the binding sites of 542 TFs in 133 cell lines as our record GSE53962 . 2. We performed a Gaussian kernel density estimation across the genome with a bandwidth of 300 bp, using the centers of each of the TF binding peaks as points. Then, we scanned this density for peaks, and denoted each peak a TF region.To determine the complexity of the TF region, we summed the Gaussian kernalized distance from the peak to each TF that contributed at least 0.1 to its strength. The TF region around eat peak was derived by finding the maximum distance (in bp) from the peak to a contributing TF, and then adding 150 bp (one half of the bandwidth). Each TF region is centered on the peak, and have a TF complexity value. 3. According to TFBS complexity, we divided these TFBS-clustered regions into ten classes: from TC0 to TC9 with increasing TFBS complexity. Result: Using the binding sites of 542 TFs in 133 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in ten classes TFBS-clustered regions of 133 cell lines.

2014-10-03 | GSE59016 | GEO

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