Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

VEGFA rSNPs, transcriptional factor binding sites and human disease.

ABSTRACT: Three regulatory SNPs (rSNPs) in the promoter region of the vascular endothelial growth factor-A (VEGFA) gene have been significantly associated with several human diseases or conditions. The rSNP alleles alter the DNA landscape for potential transcriptional factors to attach, resulting in changes in transcriptional factor binding sites (TFBS). These TFBS changes are examined with respect to the human diseases which have been found to be significantly associated with the rSNPs.

SUBMITTER: Buroker NE

PROVIDER: S-EPMC10717560 | biostudies-literature | 2014 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

VEGFA rSNPs, transcriptional factor binding sites and human disease.

Buroker Norman E NE

The journal of physiological sciences : JPS 20131006 1

Three regulatory SNPs (rSNPs) in the promoter region of the vascular endothelial growth factor-A (VEGFA) gene have been significantly associated with several human diseases or conditions. The rSNP alleles alter the DNA landscape for potential transcriptional factors to attach, resulting in changes in transcriptional factor binding sites (TFBS). These TFBS changes are examined with respect to the human diseases which have been found to be significantly associated with the rSNPs. ...[more]

PMID: 24097272

Similar Datasets

Regulatory SNPs and transcriptional factor binding sites in ADRBK1, AKT3, ATF3, DIO2, TBXA2R and VEGFA.

Project description:Abstract Regulatory single nucleotide polymorphisms (rSNPs) which change the transcriptional factor binding sites (TFBS) for transcriptional factors (TFs) to bind DNA were reviewed for the ADRBK1 (GRK2), AKT3, ATF3, DIO2, TBXA2R and VEGFA genes. Changes in the TFBS where TFs attach to regulate these genes may result in human sickness and disease. The highlights of this previous work were reviewed for these genes.

| S-EPMC4581348 | biostudies-literature

VEGFA SNPs and transcriptional factor binding sites associated with high altitude sickness in Han and Tibetan Chinese at the Qinghai-Tibetan Plateau.

Project description:Mountain sickness (MS) occurs among humans visiting or inhabiting high altitude environments. We conducted genetic analyses of seven single nucleotide polymorphisms (SNPs) in the promoter region of VEGFA gene for lowland (Han) and highland (Tibetan) Chinese. The seven SNPs were evaluated in Han and Tibetan patients with acute (A) and chronic (C) MS. We compared 64 patients with AMS with 64 Han unaffected with MS, as well as 48 CMS patients with 32 unaffected Tibetans. The SNPs studied are rs699947, rs34357231, rs79469752, rs13207351, rs28357093, rs1570360, and rs2010963 which are found in the promoter ranging from -2,578 to -634 bp from the transcriptional start site (TSS), respectively. Direct sequencing was used to identify individual genotypes for these SNPs. Arterial oxygen saturation of hemoglobin (SaO2) was found to be significantly associated with the rs699947, rs34357231, rs13207351, and rs1570360 SNPs in Han patients with AMS, while the rs2010963 SNP was found to approach significance in the AMS study group, but found to be significantly associated in the normal Tibetan study group. The Han and Tibetan control groups were found to diverge significantly for the rs28357093 and rs2010963 SNPs, as measured by genetic distances of 0.073 and 0.054, respectively. All the SNPs are found in transcriptional factor binding sites (TFBS), and their possible role in gene regulation was evaluated with regard to MS. MS was found to be significantly associated with these SNPs compared with their Han and Tibetan control groups, indicating that these nucleotide substitutions result in TFBS changes which apparently have a physiological effect on the development of high altitude sickness.

| S-EPMC10717492 | biostudies-literature

Positional distribution of human transcription factor binding sites.

Project description:We developed a method for estimating the positional distribution of transcription factor (TF) binding sites using ChIP-chip data, and applied it to recently published experiments on binding sites of nine TFs: OCT4, SOX2, NANOG, HNF1A, HNF4A, HNF6, FOXA2, USF1 and CREB1. The data were obtained from a genome-wide coverage of promoter regions from 8-kb upstream of the transcription start site (TSS) to 2-kb downstream. The number of target genes of each TF ranges from few hundred to several thousand. We found that for each of the nine TFs the estimated binding site distribution is closely approximated by a mixture of two components: a narrow peak, localized within 300-bp upstream of the TSS, and a distribution of almost uniform density within the tested region. Using Gene Ontology (GO) and Enrichment analysis, we were able to associate (for each of the TFs studied) the target genes of both types of binding with known biological processes. Most GO terms were enriched either among the proximal targets or among those with a uniform distribution of binding sites. For example, the three stemness-related TFs have several hundred target genes that belong to 'development' and 'morphogenesis' whose binding sites belong to the uniform distribution.

| S-EPMC2588498 | biostudies-literature

Functional analysis of transcription factor binding sites in human promoters.

Project description:BackgroundThe binding of transcription factors to specific locations in the genome is integral to the orchestration of transcriptional regulation in cells. To characterize transcription factor binding site function on a large scale, we predicted and mutagenized 455 binding sites in human promoters. We carried out functional tests on these sites in four different immortalized human cell lines using transient transfections with a luciferase reporter assay, primarily for the transcription factors CTCF, GABP, GATA2, E2F, STAT, and YY1.ResultsIn each cell line, between 36% and 49% of binding sites made a functional contribution to the promoter activity; the overall rate for observing function in any of the cell lines was 70%. Transcription factor binding resulted in transcriptional repression in more than a third of functional sites. When compared with predicted binding sites whose function was not experimentally verified, the functional binding sites had higher conservation and were located closer to transcriptional start sites (TSSs). Among functional sites, repressive sites tended to be located further from TSSs than were activating sites. Our data provide significant insight into the functional characteristics of YY1 binding sites, most notably the detection of distinct activating and repressing classes of YY1 binding sites. Repressing sites were located closer to, and often overlapped with, translational start sites and presented a distinctive variation on the canonical YY1 binding motif.ConclusionsThe genomic properties that we found to associate with functional TF binding sites on promoters -- conservation, TSS proximity, motifs and their variations -- point the way to improved accuracy in future TFBS predictions.

| S-EPMC3491394 | biostudies-literature

Long-range transcription factor binding sites clustered regions may mediate transcriptional regulation through phase-separation interactions in early human embryo.

Project description:In mammals, during the post-fertilization pre-implantation phase, the expression of cell type-specific genes is crucial for normal embryonic development, which is regulated by cis-regulatory elements (CREs). TFs control gene expression by interacting with CREs. Research shows that transcription factor binding sites (TFBSs) reflect the general characteristics of the regulatory genome. Here, we identified TFBSs from chromatin accessibility data in five stages of early human embryonic development, and quantified transcription factor binding sites-clustered regions (TFCRs) and their complexity (TC). Assigning TC values to TFCRs has made it possible to assess the functionality of these regulatory elements in a more quantitative way. Our findings reveal a robust correlation between TFCR complexity and gene expression starting from the 8Cell stage, which is when the zygotic genome is activated in humans. Furthermore, we have defined long-range TFCRs (LR-TFCRs) and conjecture that LR-TFCRs may regulate gene expression through phase-separation mechanisms during the early stages of human embryonic development.

| S-EPMC11492133 | biostudies-literature

Serum response factor binding sites differ in three human cell types.

Project description:The serum response factor (SRF) is essential for embryonic development and maintenance of muscle cells and neurons. The mechanism by which this factor controls these divergent pathways is unclear. Here we present a genome-wide view of occupancy of SRF at its binding sites with a focus on those that vary with cell type. We used chromatin immunoprecipitation (ChIP) in combination with human promoter microarrays to identify 216 putative SRF binding sites in the human genome. We performed independent quantitative PCR validation at over half of these sites that resulted in 146 sites we assert to be true binding sites at over 90% confidence. Nearly half of the sites are bound by SRF in only one of the three cell types we tested, providing strong evidence for the diverse roles for SRF in different cell types. We also explore possible mechanisms controlling differential binding of SRF in these cell types by assaying cofactor binding, DNA methylation, histone methylation, and histone acetylation at a subset of sites bound preferentially in smooth muscle cells. Although we did not see a strong correlation between SRF binding and epigenetics modifications, at these sites, we propose that SRF cofactors may play an important role in determining cell-dependent SRF binding sites. ELK4 (previously known as SAP-1 [SRF-associated protein-1]) is ubiquitously expressed. Therefore, we expected it to occupy sites where SRF binding is common in all cell types. Indeed, 90% of SRF sites also bound by ELK4 were common to all three cell types. Together, our data provide a more complete understanding of the regulatory network controlled by SRF.

| S-EPMC1781345 | biostudies-literature

Genome-wide inference of natural selection on human transcription factor binding sites.

Project description:For decades, it has been hypothesized that gene regulation has had a central role in human evolution, yet much remains unknown about the genome-wide impact of regulatory mutations. Here we use whole-genome sequences and genome-wide chromatin immunoprecipitation and sequencing data to demonstrate that natural selection has profoundly influenced human transcription factor binding sites since the divergence of humans from chimpanzees 4-6 million years ago. Our analysis uses a new probabilistic method, called INSIGHT, for measuring the influence of selection on collections of short, interspersed noncoding elements. We find that, on average, transcription factor binding sites have experienced somewhat weaker selection than protein-coding genes. However, the binding sites of several transcription factors show clear evidence of adaptation. Several measures of selection are strongly correlated with predicted binding affinity. Overall, regulatory elements seem to contribute substantially to both adaptive substitutions and deleterious polymorphisms with key implications for human evolution and disease.

| S-EPMC3932982 | biostudies-literature

Pseudocounts for transcription factor binding sites.

Project description:To represent the sequence specificity of transcription factors, the position weight matrix (PWM) is widely used. In most cases, each element is defined as a log likelihood ratio of a base appearing at a certain position, which is estimated from a finite number of known binding sites. To avoid bias due to this small sample size, a certain numeric value, called a pseudocount, is usually allocated for each position, and its fraction according to the background base composition is added to each element. So far, there has been no consensus on the optimal pseudocount value. In this study, we simulated the sampling process by artificially generating binding sites based on observed nucleotide frequencies in a public PWM database, and then the generated matrix with an added pseudocount value was compared to the original frequency matrix using various measures. Although the results were somewhat different between measures, in many cases, we could find an optimal pseudocount value for each matrix. These optimal values are independent of the sample size and are clearly correlated with the entropy of the original matrices, meaning that larger pseudocount vales are preferable for less conserved binding sites. As a simple representative, we suggest the value of 0.8 for practical uses.

| S-EPMC2647310 | biostudies-literature

Assessing the permissiveness of transcriptional activator binding sites.

Project description:Both genetic and biochemical data suggest that transcriptional activators with little sequence homology nevertheless function through interaction with a shared group of coactivators. Here we show that a series of peptidomimetic transcriptional activation domains interact under cell-fiee and cellular conditions with the metazoan coactivator CBP despite differences in the positioning and identity of the constituent functional groups. Taken together, these results suggest that a key activator binding site within CBP is permissive, accepting multiple arrangements of hydrophobic functional groups. Further, this permissiveness is also observed with a coactivator from S. cerevisiae. Thus, the design of small molecule mimics of transcriptional activation domains with broad function may be more straightforward than previously envisioned.

| S-EPMC4322771 | biostudies-literature

Exploiting ancestral mammalian genomes for the prediction of human transcription factor binding sites.

Project description:BackgroundThe computational prediction of Transcription Factor Binding Sites (TFBS) remains a challenge due to their short length and low information content. Comparative genomics approaches that simultaneously consider several related species and favor sites that have been conserved throughout evolution improve the accuracy (specificity) of the predictions but are limited due to a phenomenon called binding site turnover, where sequence evolution causes one TFBS to replace another in the same region. In parallel to this development, an increasing number of mammalian genomes are now sequenced and it is becoming possible to infer, to a surprisingly high degree of accuracy, ancestral mammalian sequences.ResultsWe propose a TFBS prediction approach that makes use of the availability of inferred ancestral mammalian genomes to improve its accuracy. This method aims to identify binding loci, which are regions of a few hundred base pairs that have preserved their potential to bind a given transcription factor over evolutionary time. After proposing a neutral evolutionary model of predicted TFBS counts in a DNA region of a given length, we use it to identify regions that have preserved the number of predicted TFBS they contain to an unexpected degree given their divergence. The approach is applied to human chromosome 1 and shows significant gains in accuracy as compared to both existing single-species and multi-species TFBS prediction approaches, in particular for transcription factors that are subject to high turnover rates.AvailabilityThe source code and predictions made by the program are available at http://www.cs.mcgill.ca/~blanchem/bindingLoci.

| S-EPMC3526440 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data