scholarly journals Positional specificity of different transcription factor classes within enhancers

2018 ◽  
Vol 115 (30) ◽  
pp. E7222-E7230 ◽  
Author(s):  
Sharon R. Grossman ◽  
Jesse Engreitz ◽  
John P. Ray ◽  
Tung H. Nguyen ◽  
Nir Hacohen ◽  
...  

Gene expression is controlled by sequence-specific transcription factors (TFs), which bind to regulatory sequences in DNA. TF binding occurs in nucleosome-depleted regions of DNA (NDRs), which generally encompass regions with lengths similar to those protected by nucleosomes. However, less is known about where within these regions specific TFs tend to be found. Here, we characterize the positional bias of inferred binding sites for 103 TFs within ∼500,000 NDRs across 47 cell types. We find that distinct classes of TFs display different binding preferences: Some tend to have binding sites toward the edges, some toward the center, and some at other positions within the NDR. These patterns are highly consistent across cell types, suggesting that they may reflect TF-specific intrinsic structural or functional characteristics. In particular, TF classes with binding sites at NDR edges are enriched for those known to interact with histones and chromatin remodelers, whereas TFs with central enrichment interact with other TFs and cofactors such as p300. Our results suggest distinct regiospecific binding patterns and functions of TF classes within enhancers.

2017 ◽  
Author(s):  
Katarzyna Wreczycka ◽  
Vedran Franke ◽  
Bora Uyar ◽  
Ricardo Wurmus ◽  
Altuna Akalin

AbstractHigh-occupancy target (HOT) regions are the segments of the genome with unusually high number of transcription factor binding sites. These regions are observed in multiple species and thought to have biological importance due to high transcription factor occupancy. Furthermore, they coincide with house-keeping gene promoters and the associated genes are stably expressed across multiple cell types. Despite these features, HOT regions are solemnly defined using ChIP-seq experiments and shown to lack canonical motifs for transcription factors that are thought to be bound there. Although, ChIP-seq experiments are the golden standard for finding genome-wide binding sites of a protein, they are not noise free. Here, we show that HOT regions are likely to be ChIP-seq artifacts and they are similar to previously proposed “hyper-ChIPable” regions. Using ChIP-seq data sets for knocked-out transcription factors, we demonstrate presence of false positive signals on HOT regions. We observe sequence characteristics and genomic features that are discriminatory of HOT regions, such as GC/CpG-rich k-mers and enrichment of RNA-DNA hybrids (R-loops) and DNA tertiary structures (G-quadruplex DNA). The artificial ChIP-seq enrichment on HOT regions could be associated to these discriminatory features. Furthermore, we propose strategies to deal with such artifacts for the future ChIP-seq studies.


2018 ◽  
Author(s):  
Mehran Karimzadeh ◽  
Michael M. Hoffman

AbstractMotivationIdentifying transcription factor binding sites is the first step in pinpointing non-coding mutations that disrupt the regulatory function of transcription factors and promote disease. ChIP-seq is the most common method for identifying binding sites, but performing it on patient samples is hampered by the amount of available biological material and the cost of the experiment. Existing methods for computational prediction of regulatory elements primarily predict binding in genomic regions with sequence similarity to known transcription factor sequence preferences. This has limited efficacy since most binding sites do not resemble known transcription factor sequence motifs, and many transcription factors are not even sequence-specific.ResultsWe developed Virtual ChIP-seq, which predicts binding of individual transcription factors in new cell types using an artificial neural network that integrates ChIP-seq results from other cell types and chromatin accessibility data in the new cell type. Virtual ChIP-seq also uses learned associations between gene expression and transcription factor binding at specific genomic regions. This approach outperforms methods that predict TF binding solely based on sequence preference, pre-dicting binding for 36 transcription factors (Matthews correlation coefficient > 0.3).AvailabilityThe datasets we used for training and validation are available at https://virchip.hoffmanlab.org. We have deposited in Zenodo the current version of our software (http://doi.org/10.5281/zenodo.1066928), datasets (http://doi.org/10.5281/zenodo.823297), predictions for 36 transcription factors on Roadmap Epigenomics cell types (http://doi.org/10.5281/zenodo.1455759), and predictions in Cistrome as well as ENCODE-DREAM in vivo TF Binding Site Prediction Challenge (http://doi.org/10.5281/zenodo.1209308).


2007 ◽  
Vol 4 (2) ◽  
pp. 1-23
Author(s):  
Amitava Karmaker ◽  
Kihoon Yoon ◽  
Mark Doderer ◽  
Russell Kruzelock ◽  
Stephen Kwek

Summary Revealing the complex interaction between trans- and cis-regulatory elements and identifying these potential binding sites are fundamental problems in understanding gene expression. The progresses in ChIP-chip technology facilitate identifying DNA sequences that are recognized by a specific transcription factor. However, protein-DNA binding is a necessary, but not sufficient, condition for transcription regulation. We need to demonstrate that their gene expression levels are correlated to further confirm regulatory relationship. Here, instead of using a linear correlation coefficient, we used a non-linear function that seems to better capture possible regulatory relationships. By analyzing tissue-specific gene expression profiles of human and mouse, we delineate a list of pairs of transcription factor and gene with highly correlated expression levels, which may have regulatory relationships. Using two closely-related species (human and mouse), we perform comparative genome analysis to cross-validate the quality of our prediction. Our findings are confirmed by matching publicly available TFBS databases (like TRANFAC and ConSite) and by reviewing biological literature. For example, according to our analysis, 80% and 85.71% of the targets genes associated with E2F5 and RELB transcription factors have the corresponding known binding sites. We also substantiated our results on some oncogenes with the biomedical literature. Moreover, we performed further analysis on them and found that BCR and DEK may be regulated by some common transcription factors. Similar results for BTG1, FCGR2B and LCK genes were also reported.


2019 ◽  
Author(s):  
Arnav Moudgil ◽  
Michael N. Wilkinson ◽  
Xuhua Chen ◽  
June He ◽  
Alex J. Cammack ◽  
...  

AbstractIn situ measurements of transcription factor (TF) binding are confounded by cellular heterogeneity and represent averaged profiles in complex tissues. Single cell RNA-seq (scRNA-seq) is capable of resolving different cell types based on gene expression profiles, but no technology exists to directly link specific cell types to the binding pattern of TFs in those cell types. Here, we present self-reporting transposons (SRTs) and their use in single cell calling cards (scCC), a novel assay for simultaneously capturing gene expression profiles and mapping TF binding sites in single cells. First, we show how the genomic locations of SRTs can be recovered from mRNA. Next, we demonstrate that SRTs deposited by the piggyBac transposase can be used to map the genome-wide localization of the TFs SP1, through a direct fusion of the two proteins, and BRD4, through its native affinity for piggyBac. We then present the scCC method, which maps SRTs from scRNA-seq libraries, thus enabling concomitant identification of cell types and TF binding sites in those same cells. As a proof-of-concept, we show recovery of cell type-specific BRD4 and SP1 binding sites from cultured cells. Finally, we map Brd4 binding sites in the mouse cortex at single cell resolution, thus establishing a new technique for studying TF biology in situ.


F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 344
Author(s):  
Mahmoud Ahmed ◽  
Deok Ryong Kim

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the factor ChIP experiment and the signed statistics from gene expression profiling with factor perturbation. We further extend BETA to integrate two sets of data from two factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two factors, which were found to be, on average, more cooperatively regulated.


Cells ◽  
2019 ◽  
Vol 8 (11) ◽  
pp. 1321 ◽  
Author(s):  
Mahmoud Ahmed ◽  
Trang Huyen Lai ◽  
Jin Seok Hwang ◽  
Sahib Zada ◽  
Trang Minh Pham ◽  
...  

Autophagy is the cell self-eating mechanism to maintain cell homeostasis by removing damaged intracellular proteins or organelles. It has also been implicated in the development and differentiation of various cell types including the adipocyte. Several links between adipogenic transcription factors and key autophagy genes has been suggested. In this study, we tried to model the gene expression and their transcriptional regulation during the adipocyte differentiation using high-throughput sequencing datasets of the 3T3-L1 cell model. We applied the gene expression and co-expression analysis to all and the subset of autophagy genes to study the binding, and occupancy patterns of adipogenic factors, co-factors and histone modifications on key autophagy genes. We also analyzed the gene expression of key autophagy genes under different transcription factor knockdown adipocyte cells. We found that a significant percent of the variance in the autophagy gene expression is explained by the differentiation stage of the cell. Adipogenic master regulators, such as CEBPB and PPARG target key autophagy genes directly. In addition, the same factor may also control autophagy gene expression indirectly through autophagy transcription factors such as FOXO1, TFEB or XBP1. Finally, the binding of adipogenic factors is associated with certain patterns of co-factors binding that might modulate the functions. Some of the findings were further confirmed under the knockdown of the adipogenic factors in the differentiating adipocytes. In conclusion, autophagy genes are regulated as part of the transcriptional programs through adipogenic factors either directly or indirectly through autophagy transcription factors during adipogenesis.


Development ◽  
2002 ◽  
Vol 129 (19) ◽  
pp. 4387-4397
Author(s):  
Fiona C. Wardle ◽  
Daniel H. Wainstock ◽  
Hazel L. Sive

The cement gland marks the extreme anterior ectoderm of the Xenopus embryo, and is determined through the overlap of several positional domains. In order to understand how these positional cues activate cement gland differentiation, the promoter of Xag1, a marker of cement gland differentiation, was analyzed. Previous studies have shown that Xag1 expression can be activated by the anterior-specific transcription factor Otx2, but that this activation is indirect. 102 bp of upstream genomic Xag1 sequence restricts reporter gene expression specifically to the cement gland. Within this region, putative binding sites for Ets and ATF/CREB transcription factors are both necessary and sufficient to drive cement gland-specific expression, and cooperate to do so. Furthermore, while the putative ATF/CREB factor is activated by Otx2, a factor acting through the putative Ets-binding site is not. These results suggest that Ets-like and ATF/CREB-like family members play a role in regulating Xag1 expression in the cement gland, through integration of Otx2 dependent and independent pathways.


Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 3875-3875
Author(s):  
Thu-Hang Pham ◽  
Monika Lichtinger ◽  
Chris Benner ◽  
Sabine Pape ◽  
Lucia Schwarzfischer ◽  
...  

Abstract Abstract 3875 The differentiation of human macrophages is accompanied by distinctive phenotypical changes and generally proceeds in the absence of proliferation. The molecular events governing this process are still poorly understood. Using ChIP-Seq technology we studied epigenetic changes as well as alterations in transcription factor occupancy during human monocyte differentiation and correlated these events with gene expression levels in hematopoietic cell types. We show that putative enhancer regions marked by histone H3 lysine4 monomethylation (H3K4me1) at different developmental stages (human progenitor cells, peripheral blood monocytes and in vitro differentiated macrophages) are enriched in distinct sets of transcription factor motifs corresponding to lineage-determining factors. Cell stage-specific histone methylation at promoter-distal sites corresponds with increased mRNA expression levels of neighboring genes. We generated global DNA-binding maps in monocytes and macrophages for two transcription factors (PU.1 and C/EBPβ) with a well established role in monocyte/macrophage differentiation. Comparison of human binding sites with corresponding mouse data revealed a surprisingly low level of conservation (∼10-15%) of PU.1-or C/EBPβ -bound sites between man and mouse, despite a highly conserved binding preference for both transcription factors. During monocytic differentiation, human macrophages primarily gained additional binding sites for both transcription factors (as well as promoter-distal H3K4me1). Interestingly, only neighboring genes with multiple binding events showed significantly increased, macrophage-specific mRNA expression as compared to monocytic as well as lymphocytic cell types. Human macrophage-specific H3K4me1-marked regions as well as macrophage-specific PU.1- and C/EBP-bound sites were characterized by overlapping sets of novel sequence motifs, suggesting that the combinatorial interaction of corresponding DNA-binding factors with PU.1 and C/EBPβ may be required for the establishment of human macrophage-specific enhancers. These data provide novel insights into PU.1 and C/EBPβ mediated gene regulation during human macrophage differentiation. Disclosures: No relevant conflicts of interest to declare.


2003 ◽  
Vol 75 (11-12) ◽  
pp. 1757-1769 ◽  
Author(s):  
P. J. Kushner ◽  
P. Webb ◽  
R. M. Uht ◽  
M.-M. Liu ◽  
R. H. Price

The estrogen receptors alpha and beta (ERα and ERβ) mediate the changes in gene expression from physiological and environmental estrogens. Early studies identified classical estrogen response elements (EREs) in the promoter region of target genes whose expression is regulated by estrogen and to which the ERs bind via their DNA-binding domain (DBD). EREs in the pituitary prolactin promoter, for example, mediate an activation by both ERα and ERβ albeit with different affinities for different ligands. Full activation in most cell types requires the integrity of the activation function 2 (AF-2) in the receptors ligand binding domain (LBD), which is engaged by estrogens and disengaged by tamoxifen, raloxifene, and other antiestrogens. However, in some cells and ERE contexts, the AF-1 in the ERα amino terminal domain (NTD) is sufficient. We now know that ERs also regulate expression of target genes that do not have EREs, but instead have various kinds of alternative response elements that bind heterologous transcription factors whose activity is regulated by interactions with ERs. Thus, ERα activates genes, including collagenase and cyclin D1, an important mediator of cellular proliferation, by AP-1 and CRE sites, which bind Jun/Fos or Jun/ATF-2 transcription factors. ERα also activates gene expression through GC-rich elements that bind the SP1 transcription factor. Finally, we also know that ERs mediate inhibition of the expression of many genes. In one well-studied instance, ERs counterexpression of genes involved in the inflammatory response by inhibiting the action at tumor necrosis factor response elements (TNF-REs) that bind the NFkappaB transcription factor. ERβ is especially efficient at this inhibition. ERα activation of AP-1/CRE target genes is of special interest because of the putative role of these target genes in mediating proliferation. The AF-1 and AF-2 functions of ERα are both needed for this activation in most cell types. However, in uterine cells, the AF-1 function is sufficient. Thus, the antiestrogen tamoxifen, which allows AF-1, mimics estrogen and drives activation of AP-1/CRE target genes and proliferation of uterine cells. This estrogen-like action, which can increase the risk of uterine cancer, complicates the use of tamoxifen to prevent breast cancer. Surprisingly, ERβ inhibits AP-1/CRE target genes in the presence of estrogen. When both receptors are present, ERβ efficiently opposes activation by ERα. Moreover, ERβ activates the AP-1/CRE target genes in the presence of antiestrogens especially so-called "complete" antiestrogens raloxifene, and ICI 182, 780. We here review the evidence for different kinds of promoter elements that mediate ER action, for the differential ligand preferences of ERα and ERβ at these different elements, and the potential mechanisms by which they are mediated. One attractive strategy for the investigation and comparison of potential environmental estrogens is to assay their activity in cell culture systems using reporter genes with simplified promoter elements. Thus, the findings of complexity in ERα and ERβ activation at different types of response elements needs to be taken into account in the development and interpretation of assays using simplified promoter elements systems.


F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 344
Author(s):  
Mahmoud Ahmed ◽  
Deok Ryong Kim

Researchers use ChIP binding data to identify potential transcription factor binding sites. Similarly, they use gene expression data from sequencing or microarrays to quantify the effect of the transcription factor overexpression or knockdown on its targets. Therefore, the integration of the binding and expression data can be used to improve the understanding of a transcription factor function. Here, we implemented the binding and expression target analysis (BETA) in an R/Bioconductor package. This algorithm ranks the targets based on the distances of their assigned peaks from the transcription factor ChIP experiment and the signed statistics from gene expression profiling with transcription factor perturbation. We further extend BETA to integrate two sets of data from two transcription factors to predict their targets and their combined functions. In this article, we briefly describe the workings of the algorithm and provide a workflow with a real dataset for using it. The gene targets and the aggregate functions of transcription factors YY1 and YY2 in HeLa cells were identified. Using the same datasets, we identified the shared targets of the two transcription factors, which were found to be, on average, more cooperatively regulated.


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