Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Systematic analysis of effects of naturally occurring insertions and deletions that alter transcription factor spacing identifies tolerant and sensitive transcription factor pairs [RNA-seq]

ABSTRACT: Regulation of gene expression requires the combinatorial binding of sequence-specific transcription factors (TFs) at promoters and enhancers. Prior studies showed that alterations in the spacing between TF binding sites can influence promoter and enhancer activity. However, the relative importance of TF spacing alterations resulting from naturally occurring insertions and deletions (InDels) has not been systematically analyzed. To address this question, we first characterized the genome-wide spacing relationships of 75 TFs in K562 cells as determined by ChIP-sequencing. We found a dominant pattern of a relaxed range of spacing between collaborative factors, including forty-six factors exclusively exhibiting relaxed spacing with their binding partners. Next, we exploited millions of InDels provided by genetically diverse mouse strains and human individuals to investigate the effects of altered spacing on TF binding and local histone acetylation. Spacing alterations resulting from naturally occurring InDels are generally tolerated in comparison to genetic variants directly affecting TF binding sites. A remarkable range of tolerance was further established for PU.1 and C/EBPβ, which exhibit relaxed spacing, by introducing synthetic spacing alterations ranging from 5-bp increase to >30-bp decrease using CRISPR/Cas9 mutagenesis. These findings provide implications for understanding mechanisms underlying enhancer selection and for interpretation of non-coding genetic variation.

ORGANISM(S): Mus musculus

PROVIDER: GSE178079 | GEO | 2022/01/28

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Systematic analysis of effects of naturally occurring insertions and deletions that alter transcription factor spacing identifies tolerant and sensitive transcription factor pairs [ChIP-seq]

Project description:Regulation of gene expression requires the combinatorial binding of sequence-specific transcription factors (TFs) at promoters and enhancers. Prior studies showed that alterations in the spacing between TF binding sites can influence promoter and enhancer activity. However, the relative importance of TF spacing alterations resulting from naturally occurring insertions and deletions (InDels) has not been systematically analyzed. To address this question, we first characterized the genome-wide spacing relationships of 75 TFs in K562 cells as determined by ChIP-sequencing. We found a dominant pattern of a relaxed range of spacing between collaborative factors, including forty-six factors exclusively exhibiting relaxed spacing with their binding partners. Next, we exploited millions of InDels provided by genetically diverse mouse strains and human individuals to investigate the effects of altered spacing on TF binding and local histone acetylation. Spacing alterations resulting from naturally occurring InDels are generally tolerated in comparison to genetic variants directly affecting TF binding sites. A remarkable range of tolerance was further established for PU.1 and C/EBPβ, which exhibit relaxed spacing, by introducing synthetic spacing alterations ranging from 5-bp increase to >30-bp decrease using CRISPR/Cas9 mutagenesis. These findings provide implications for understanding mechanisms underlying enhancer selection and for interpretation of non-coding genetic variation.

2022-01-28 | GSE178078 | GEO

Systematic analysis of effects of naturally occurring insertions and deletions that alter transcription factor spacing identifies tolerant and sensitive transcription factor pairs [ATAC-seq]

2022-01-28 | GSE178077 | GEO

Unraveling determinants of transcription factor binding outside the core binding site

Project description:Binding of transcription factors (TFs) to regulatory sequences is a pivotal step in the control of gene expression. Despite many advances in the characterization of sequence motifs recognized by TFs, our ability to quantitatively predict TF binding to different regulatory sequences is still limited. Here, we present a novel experimental assay termed BunDLE-seq that provides quantitative measurements of TF binding to thousands of fully designed sequences of 200 bp in length within a single experiment. Applying this binding assay to two yeast TFs we demonstrate that sequences outside the core TF binding site profoundly affect TF binding. We show that TF-specific models based on the sequence or DNA shape of the regions flanking the core binding site are highly predictive of the measured differential TF binding. We further characterize the dependence of TF binding, accounting for measurements of single and co-occurring binding events, on the number and location of binding sites and on the TF concentration. Finally, by coupling our in vitro TF binding measurements, and another application of our method probing nucleosome formation, to in vivo expression measurements carried out with the same template sequences now serving and promoters, we offer insights into mechanisms that may determine the different expression outcomes observed. Our assay thus paves the way to a more comprehensive understanding of TF binding to regulatory sequences, and allows the characterization of TF binding determinants within and outside of core binding sites.

2015-03-04 | GSE66143 | GEO

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

Pioneer factor-nucleosome binding events during differentiation are motif-encoded

Project description:Though the in vitro structural and in vivo spatial characteristics of transcription factor (TF) binding are well defined, TF interactions with chromatin and other companion TFs during development are poorly understood. To analyze such interactions in vivo, we profiled several TFs across a time course of human embryonic stem cell differentiation via CUT&RUN epigenome profiling, and studied their interactions with nucleosomes and co-occurring TFs by Enhanced Chromatin Occupancy (EChO), a computational strategy for classifying TF binding characteristics across time and space. EChO shows that at different enhancer targets, the same TF can employ either direct DNA binding, or “pioneer” nucleosome binding to access them. Pioneer binding is correlated with local binding of other TFs and enhancer motif character, including degeneracy at key bases in the pioneer factor target motif. Our strategy reveals a dynamic exchange of TFs at enhancers across developmental time that is aided by pioneer nucleosome binding.

2019-06-25 | GSE128499 | GEO

Genomic regions flanking E-box sites influence DNA binding specificity of bHLH transcription factors through DNA shape (validation)

Project description:DNA sequence is a major determinant of the binding specificity of transcription factors (TFs) for their genomic targets. However, eukaryotic cells often express, at the same time, TFs with highly similar DNA binding motifs but distinct in vivo targets. Currently, it is not well understood how TFs with seemingly identical DNA motifs achieve unique specificities in vivo. Here, we used custom protein binding microarrays to analyze TF specificity for putative binding sites in their genomic sequence context. Using yeast TFs Cbf1 and Tye7 as our case study, we found that binding sites of these bHLH TFs (i.e., E-boxes) are bound differently in vitro and in vivo, depending on their genomic context. Computational analyses suggest that nucleotides outside E-box binding sites contribute to specificity by influencing the 3D structure of DNA binding sites. Thus, local shape of target sites might play a widespread role in achieving regulatory specificity within TF families. Two protein binding microarray (PBM) experiments of Saccharomyces cerevisiae transcription factors were performed. Briefly, the PBMs involved binding GST-tagged yeast transcription factors Cbf1 and Tye7 to double-stranded 44K Agilent microarrays in order to determine the accuracy of our regression models for TF-DNA binding specificity. Briefly, this array contains 30-bp genomic sequences from our initial custom array (Gordan et al 2013, submitted), with 0 through 4 mutations designed at various positions in the genomic sequences. Each sequence in represented in 6 replicate spots. We report the PBM signal intensity for each spot. The PBM protocol is described in Berger et al., Nature Biotechnology 2006 (PMID 16998473).

2013-03-29 | E-GEOD-44437 | biostudies-arrayexpress

Transcription Factor Highly Occupied Target (HOT) Regions of 145 Cell Lines

Project description:Purpose: 253 GSM Samples from GSE32970 and GSE29692 was reanalyzed to find the highly occupied target (HOT) regions of 154 cell lines. Methods: 1. We assigned the binding sites of 542 TFs in 154 cell lines as GSE53962 (Our last submission). 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(Candidate region to find HOT regions).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.To define HOT region according to the TF complexity, we required a complexity cutoff for each cell line.To geometrically define the cutoff we first scaled the TF complexity such that the x and y axis were from 0-1. We then found the x axis point for which a line with a slope of 1 was tangent to the curve. We define this point as the cutoff value,TF region whose complexity above this point to be HOT region, and TF region complexity below that point to be lowly occupied target (LOT) regions. Result: Using the binding sites of 542 TFs in 145 cell lines, we assigned a TF complexity score to each TF region corresponding to the number of distinct TFs bound, resulting in HOT regions of 145 cell lines.

2015-01-14 | GSE54296 | GEO

Transcription factors harbor functional RNA-binding domains

Project description:Transcription factors (TFs) orchestrate the gene expression programs that define each cell’s identity, and the canonical TF accomplishes this with two functional domains1–7. The DNA-binding domain interacts with specific genomic sequences, and the effector domain binds coactivators or co-repressors that contribute to transcriptional regulation. We report here that TFs also frequently contain an RNA-binding domain and that this also contributes to gene regulation. Nearly half of TFs in human cells show evidence of RNA-binding and their affinities for RNA are similar to those of well-studied RNA-binding proteins. The RNA-binding sites of TFs have sequence and functional features analogous to the arginine-rich motif of the HIV transcriptional activator Tat8,9. RNA-binding contributes to TF function by promoting the dynamic association of TFs with chromatin. We conclude that the canonical definition of transcription factors is incomplete, and that the ability of many TFs to bind DNA, RNA and protein is fundamental to gene regulation.

2023-07-02 | PXD035484 | Pride

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites [Validation Set]

Project description:During cell division, transcription factors (TFs) are removed from chromatin twice, during DNA synthesis, and during condensation of chromosomes. How TFs can efficiently find their sites following these stages has been unclear. Here, we have analyzed the binding pattern of expressed TFs in human colorectal cancer cells. We find that binding of TFs is highly clustered, and that the clusters are enriched in binding motifs for several major TF classes. Strikingly, almost all clusters are formed around cohesin, and loss of cohesin decreases both DNA accessibility and binding of TFs to clusters. We show that cohesin remains bound in S phase, holding the nascent sister chromatids together at the TF cluster sites. Furthermore, cohesin remains bound to the cluster sites when TFs are evicted in early M-phase. These results suggest that cohesin binding functions as a cellular memory that promotes re- stablishment of TF clusters after DNA replication and chromatin condensation. Examination of TF binding by ChIP-seq in a CRC cell-line.

2013-09-25 | E-GEOD-51142 | biostudies-arrayexpress

Transcription factor binding in human cells occurs in dense clusters formed around cohesin anchor sites

2013-08-15 | E-GEOD-49402 | biostudies-arrayexpress