Divergence of transcription factor binding sites is considered to be an important source of regulatory evolution. The associations between transcription factor binding sites and phenotypic diversity have been investigated in many model organisms. However, the understanding of other factors that contribute to it is still limited. Recent studies have elucidated the effect of chromatin structure on molecular evolution of genomic DNA. Though the profound impact of nucleosome positions on gene regulation has been reported, their influence on transcriptional evolution is still less explored. With the availability of genome-wide nucleosome map in yeast species, it is thus desirable to investigate their impact on transcription factor binding site evolution. Here, we present a comprehensive analysis of the role of nucleosome positioning in the evolution of transcription factor binding sites. We compared the transcription factor binding site frequency in nucleosome occupied regions and nucleosome depleted regions
Didier Picard, January 2015 Current list of HBD fusion proteins_ Protein X a HBD b regulated as c Refs. transcription factor in Arabidopsis transcription factor Arabidopsis transcription factor in tobacco coactivator transcription factor 1 2 3 transcription factor transcription factor, differentiation factor transcription factor putative transcription factor in arabidposis transcription factor oncoprotein transcription factor transcription factor oncoprotein oncoprotein oncoprotein transcription factor oncoprotein, transcription factor 6 7 transcription factor transcription factor in yeast, tissue culture cells and zebra fish transcriptional repressor transcription factor transcription factor in yeast, in tissue culture cells, transgenic mice, Xenopus, Drosophila and plants transcription factor, promoter of proliferation transcription factor transcription factor 19 20, 21, i Transcription factors APETALA3 ATF6α Athb-1 GR ER e GR Bob1/OBF1 ER e CCAT (from calcium ER e 4 5 channel cav1.2) C/EBP ...
Fig 5: regulation of transcription : which evidence code should be used? kct10 negative regulation of sequence-specific DNA binding transcription factor activity GO:0043433 IDA Kctd10 negative regulation of sequence-specific DNA binding transcription factor activity GO:0043433 IDA has_regulation_target(Tbx5a) Kctd10 negative regulation of sequence-specific DNA binding transcription factor activity GO:0043433 IDA tbx5a has_regulation _target(Tbx5a) Kctd10 negative regulation of sequence-specific DNA binding transcription factor activity GO:0043433 IGI tbx5a has_regulation _target(Tbx5a) kctd10 negative regulation of sequence-specific DNA binding transcription factor activity GO:0043433 IMP has_regulation_target: tbx5b ...
The DNA sequence that a transcription factor binds to is called a transcription factor binding site or response element. Chemically, transcription factors usually interact with their binding sites using a combination of hydrogen bonds and Van der Waals forces. Due to the nature of these chemical interactions, most transcription factors bind DNA in a sequence specific manner. However, not all bases in the transcription factor binding site may actually interact with the transcription factor. In addition some of these interactions may be weaker than others. Thus, transcription factors dont bind just one sequence but are capable of binding a subset of closely related sequences, each with a different strength of interaction. For example, although the consensus binding site for the TATA binding protein (TBP) is: TATAAAA the TBP transcription factor can also bind similar sequences such as: TATATAT or TATATAA Because transcription factors can bind a set of related sequences and the sequences dont tend ...
Transcription factors are key proteins in the regulation of gene transcription. An important step in this process is the opening of chromatin in order to make genomic regions available for transcription. Data on DNase I hypersensitivity has previously been used to label a subset of transcription factors as Pioneers, Settlers and Migrants to describe their potential role in this process. These labels represent an interesting hypothesis on gene regulation and possibly a useful approach for data analysis, and therefore we wanted to expand the set of labeled transcription factors to include as many known factors as possible. We have used a well-annotated dataset of 1175 transcription factors as input to supervised machine learning methods, using the subset with previously assigned labels as training set. We then used the final classifier to label the additional transcription factors according to their potential role as Pioneers, Settlers and Migrants. The full set of labeled transcription factors was used
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 ...
The DNA sequence that a transcription factor binds to is called a transcription factor-binding site or response element.[55]. Transcription factors interact with their binding sites using a combination of electrostatic (of which hydrogen bonds are a special case) and Van der Waals forces. Due to the nature of these chemical interactions, most transcription factors bind DNA in a sequence specific manner. However, not all bases in the transcription factor-binding site may actually interact with the transcription factor. In addition, some of these interactions may be weaker than others. Thus, transcription factors do not bind just one sequence but are capable of binding a subset of closely related sequences, each with a different strength of interaction. For example, although the consensus binding site for the TATA-binding protein (TBP) is TATAAAA, the TBP transcription factor can also bind similar sequences such as TATATAT or TATATAA. Because transcription factors can bind a set of related ...
Since the successful isolation of mouse and human embryonic stem cells (ESCs) in the past decades, massive investigations have been conducted to dissect the pluripotency network that governs the ability of these cells to differentiate into all cell types. Beside the core Oct4-Sox2-Nanog circuitry, accumulating regulators, including transcription factors, epigenetic modifiers, microRNA and signaling molecules have also been found to play important roles in preserving pluripotency. Among the various regulations that orchestrate the cellular pluripotency program, transcriptional regulation is situated in the central position and appears to be dominant over other regulatory controls. In this review, we would like to summarize the recent advancements in the accumulating findings of new transcription factors that play a critical role in controlling both pluripotency network and ESC identity.
Silkworm Transcription Factor Database (SilkTF) is a protein database which contains information on transcription factors (TFs) of silkworm.
The Oxidative Stress Responsive Transcription Factor Pap1 Confers DNA Damage Resistance on Checkpoint-Deficient Fission Yeast Cells. . Biblioteca virtual para leer y descargar libros, documentos, trabajos y tesis universitarias en PDF. Material universiario, documentación y tareas realizadas por universitarios en nuestra biblioteca. Para descargar gratis y para leer online.
This unit describes how to use the Transcription Element Search System (TESS). This Web site predicts transcription factor binding sites (TFBS) in DNA sequence using two different kinds of models of sites, strings and positional weight matrices. The binding of transcription factors to DNA is a major part of the control of gene expression. Transcription factors exhibit sequence-specific binding; they form stronger bonds to some DNA sequences than to others. Identification of a good binding site in the promoter for a gene suggests the possibility that the corresponding factor may play a role in the regulation of that gene. However, the sequences transcription factors recognize are typically short and allow for some amount of mismatch. Because of this, binding sites for a factor can typically be found at random every few hundred to a thousand base pairs. TESS has features to help sort through and evaluate the significance of predicted sites. Curr. Protoc. Bioinform. 21:2.6.1-2.6.15. © 2008 by John ...
The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator-1beta (PGC-1beta) has been implicated in important metabolic processes. A mouse lacking PGC-1beta (PGC1betaKO) was generated and phenotyped using physiological, molecular, and bioinformatic approaches. PGC1betaKO mice are generally viable and metabolically healthy. Using systems biology, we identified a general defect in the expression of genes involved in mitochondrial function and, specifically, the electron transport chain. This defect correlated with reduced mitochondrial volume fraction in soleus muscle and heart, but not brown adipose tissue (BAT). Under ambient temperature conditions, PGC-1beta ablation was partially compensated by up-regulation of PGC-1alpha in BAT and white adipose tissue (WAT) that lead to increased thermogenesis, reduced body weight, and reduced fat mass. Despite their decreased fat mass, PGC1betaKO mice had hypertrophic adipocytes in WAT. The thermogenic role of PGC-1beta was
ABSTRACT: One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This ...
ABSTRACT: One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This ...
ABSTRACT: One goal of human genetics is to understand how the information for precise and dynamic gene expression programs is encoded in the genome. The interactions of transcription factors (TFs) with DNA regulatory elements clearly play an important role in determining gene expression outputs, yet the regulatory logic underlying functional transcription factor binding is poorly understood. Many studies have focused on characterizing the genomic locations of TF binding, yet it is unclear to what extent TF binding at any specific locus has functional consequences with respect to gene expression output. To evaluate the context of functional TF binding we knocked down 59 TFs and chromatin modifiers in one HapMap lymphoblastoid cell line. We then identified genes whose expression was affected by the knockdowns. We intersected the gene expression data with transcription factor binding data (based on ChIP-seq and DNase-seq) within 10 kb of the transcription start sites of expressed genes. This ...
Clinical evidence suggests that antiestrogens inhibit the development of androgen-insensitive prostate cancer. Here, we show that the estrogen receptor β (ERβ) mediates inhibition by the antiestrogen ICI 182,780 (ICI) and its enhancement by estrogen. ERβ associated with gene promoters through the tumor-suppressing transcription factor KLF5 (Krüppel-like zinc finger transcription factor 5). ICI treatment increased the recruitment of the transcription coactivator CBP [CREB (adenosine 3′,5′-monophosphate response element-binding protein)-binding protein] to the promoter of FOXO1 through ERβ and KLF5, which enhanced the transcription of FOXO1. The increase in FOXO1 abundance led to anoikis in prostate cancer cells, thereby suppressing tumor growth. In contrast, estrogen induced the formation of complexes containing ERβ, KLF5, and the ubiquitin ligase WWP1 (WW domain containing E3 ubiquitin protein ligase 1), resulting in the ubiquitination and degradation of KLF5. The combined presence of ...
TY - JOUR. T1 - Ablation of PGC-1β results in defective mitochondrial activity, thermogenesis, hepatic function, and cardiac performance. AU - Lelliott, Christopher J.. AU - Medina-Gomez, Gema. AU - Petrovic, Natasa. AU - Kis, Adrienn. AU - Feldmann, Helena M.. AU - Bjursell, Mikael. AU - Parker, Nadeene. AU - Curtis, Keira. AU - Campbell, Mark. AU - Hu, Ping. AU - Zhang, Dongfang. AU - Litwin, Sheldon E.. AU - Zaha, Vlad G.. AU - Fountain, Kimberly T.. AU - Boudina, Sihem. AU - Jimenez-Linan, Mercedes. AU - Blount, Margaret. AU - Lopez, Miguel. AU - Meirhaeghe, Aline. AU - Bohlooly-Y, Mohammad. AU - Storlien, Leonard. AU - Strömstedt, Maria. AU - Snaith, Michael. AU - Orešič, Matej. AU - Abel, E. Dale. AU - Cannon, Barbara. AU - Vidal-Puig, Antonio. PY - 2006/11. Y1 - 2006/11. N2 - The transcriptional coactivator peroxisome proliferator-activated receptor-gamma coactivator-1β (PGC-1β) has been implicated in important metabolic processes. A mouse lacking PGC-1β (PGC1βKO) was generated ...
Isolation of transcriptional activators of CDR1 and CDR2 by mining in the C. albicans genome.In this article, we report the isolation of a transcription factor involved in the regulation of CDR1 and CDR2 by inspection of genome data. We focused on Zn(2)-Cys(6) transcription factors because these factors are able to target 5′-CGG-3′ motifs that are present in the DRE of CDR1 and CDR2 promoters. These transcription factors have in common a Zn(2)-Cys(6) DNA-binding domain which targets sequences with direct, inverted, or everted palindromic repeats containing a 5′-CGG-3′ motif with various numbers of nucleotides in the intervening spacer region. Several examples can be cited from studies performed with S. cerevisiae: Hap1p recognizes the direct repeat 5′-CGGNNNTANCGG-3′; the heterodimer Pip2p/Oaf1p binds to inverted repeats of the consensus sequence 5′-CGGN15-18-CCG-3′; Pdr8p and Yrr1p, which are factors involved in multidrug resistance, target DNA-binding motifs containing the ...
BACKGROUNDIn many approaches to the inference and modeling of regulatory interactions using microarray data, the expression of the gene coding for the transcription factor is considered to be an accurate surrogate for the true activity of the protein it produces. There are many instances where this is inaccurate due to post-translational modifications of the transcription factor protein. Inference of the activity of the transcription factor from the expression of its targets has predominantly involved linear models that do not reflect the nonlinear nature of transcription. We extend a recent approach to inferring the transcription factor activity based on nonlinear Michaelis-Menten kinetics of transcription from maximum likelihood to fully Bayesian inference and give an example of how the model can be further developed.RESULTSWe present results on synthetic and real microarray data. Additionally, we illustrate how gene and replicate specific delays can be incorporated into the model.CONCLUSIONWe ...
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TY - JOUR. T1 - In Vivo mutational analysis of the DNA binding domain of the tissue-specific transcription factor, Pit-1. AU - Liang, Jie. AU - Moye-Rowley, Scott. AU - Maurer, Richard A.. PY - 1995/10/27. Y1 - 1995/10/27. N2 - Pit-1 is a member of the POU family of transcription factors, which contain a bipartite DNA binding domain. The DNA binding domain consists of a POU-specific domain and a POU homeodomain. Each of the subdomains can interact with DNA independently, but both subdomains are required for high affinity, sequence-specific DNA binding. To examine the contributions of individual amino acids to the function of the DNA binding domain of Pit-1, we developed an approach involving random, in vitro mutagenesis followed by functional screening in Saccharomyces cerevisiae. Using this strategy, we identified a number of point mutations that altered the function of the Pit-1 DNA binding domain. Mutations that altered Pit-1 function were found in both the POU-specific and the POU ...
Transcription factors directly control when, where, and the extent to which genes are expressed. Signal transduction pathways are responsible for either activating or inhibiting many of them. Transcription factors are also regulated by cofactors, forming complexes that can activate or inhibit transcriptional activity. Many transcription factors, such as nuclear receptors, reside in the cytoplasm and enter the nucleus upon activation (e.g., ligand binding). Posttranslational modifications and coregulating proteins provide additional layers of regulation. Transcription factors are involved in a wide variety of processes, such as development, stress responses, and immunity. Activation or inhibition of transcription factors is often dysregulated during oncogenesis. Transcription factors can also be dysregulated during developmental processes, promoting or inhibiting cellular differentiation. Analyzing the expression, regulation, activity, and sequence of transcription factor genes can help determine ...
The human transcription enhancer factor-1 (TEF-1) belongs to a family of evolutionarily conserved proteins that have a DNA binding TEA domain. TEF-1 shares a 98% homology with Drosophila scalloped (sd) in the DNA binding domain and a 50% similarity in the activation domain. We have expressed human TEF-1 in Drosophila under the hsp-70 promoter and find that it can substitute for Sd function. The transformants rescue the wingblade defects as well as the lethality of loss-of-function alleles. Observation of reporter activity in the imaginal wing discs of the enhancer-trap alleles suggests that TEF-1 is capable of promoting sd gene regulation. The functional capability of the TEF-1 product was assessed by comparing the extent of rescue by heat shock (hs)-TEF-1 with that of hs-sd. The finding that TEF-1 can function in vivo during wingblade development offers a potent genetic system for the analysis of its function and in the identification of the molecular partners of TEF-1.. ...
Background TF-TFBS-TFT triplets -Transcription factors(TF) regulate transcription factor target(TFT) through binding to transcription factor DNA binding sites(TFBS).
  Gene expression at the level of transcription is regulated by a set of transcription factors (TFs) that recognizes cis elements. We accessed the human promoters from eukaryotic promoter database. These sequences have been run in P-match tool. MEME software has been used for detection of conserved sequences in the promoter region. All the predicted known TFs and their binding sites along with weight matrices were collected from TRANSFAC database under vertebrate TFs category. P-match tool combines pattern matching and weight matrix approaches thus providing higher accuracy of recognition than each of the methods alone. P-Match is closely interconnected with the TRANSFAC® database. Using results of extensive tests of recognition accuracy, we selected three sets of optimized cut-off values that minimize either false negatives or false positives, or the sum of both errors.  In this report, we focus on those polymorphisms of transcription factor binding sites (TFBS) in the
This paper describes a novel approach to constructing Position-Specific Weight Matrices (PWMs) based on the transcription factor binding site (TFBS) data provide by the TRANSFAC database and comparison of the newly generated PWMs with the original TRANSFAC matrices. Multiple local sequence alignment was performed on the TFBSs of each transcription factor. Several different alignment programs were tested and their matrices were compared to the original TRANSFAC matrices. One of the alignment programs, GLAM, produced comparable matrices in terms of the average ranking of true positive sites across the whole test set of sequences. ...
The mechanisms underlying the development and progression of breast cancer are not fully understood, and this is particularly challenging because of its diverse etiologies [20]. However, it is clear that changes in gene expression are essential to drive different processes that occur during tumourigenesis [21]. Transcription factors control gene expression by binding to specific DNA sequences in gene promoters and often regulate multiple target genes. Because of this ability to control different target genes, deregulation of transcription factors can drive events associated with the initiation and progression of diseases such as cancer [22]. Previous studies have shown that the Brn-3b transcription factor is elevated in ,60% of primary breast cancers [1], and when increased, it significantly enhances proliferation and anchorage-independent growth in vitro and tumour growth in vivo [2, 3]. Elevated Brn-3b also confers resistance to growth-inhibitory stimuli and increases the migratory potential ...
ELF4 is a member of the ETS family of transcription factors (TF) with transcription activating properties (Lacorazza and Nimer, 2003). ELF4 binds to DNA sequences containing the consensus 5-WGGA-3 and transactivates promoters of the hematopoietic growth factor genes CSF2, IL3, IL8, and of the bovine lysozyme gene (Miyazaki et al., 1996; Mao et al., 1999; Hedvat et al., 2004; Suico et al., 2004). ELF4 acts synergistically with RUNX1 to transactivate the IL3 promoter (Mao et al., 1999). It also transactivates the PRF1 promoter in natural killer (NK) cells (Lacorazza et al., 2002). ELF4 has important molecular functions, including protein binding, transcription activator activity, sequence-specific DNA binding, transcription factor activity. ELF4 interacts with multiple proteins, including Cyclin A/CDK2 kinase complex, FBXO4, FBXO7, PML, RUNX1, SKP2 and UBB (Miyazaki et al., 1996; Mao et al., 1999; Miyazaki et al., 2001; Liu et al., 2006; Suico et al., 2006). ELF4 has been implicated in widely ...
Recent research has uncovered complex transcription factor networks that control the processes of T-cell development and differentiation. RUNX (runt-related transcription factor) proteins are among the many factors that have crucial roles in these networks. In this Review, we examine the mechanisms …
This function reads in transcription factor information given the selected transcription factor target gene database. The information is downloaded via the AnnotationHub package and merged, if necessary.
Breast cancer is one of the most common malignant diseases in women. Epithelial-mesenchymal transition (EMT) has been documented to play an important role in proliferation, invasion and metastasis of tumor cells as well as drug resistance. Even though the signal transducer and activator of transcription 3 (STAT3) is not a master transcription factor of EMT, STAT3 is involved in the regulation of EMT-related gene expression. However, it remains unclear whether targeted inhibitors of STAT3 affect EMT-mediated proliferation, migration, invasion and drug resistance of tumor cells. In this paper, we investigated the effects of STAT3 and its interaction with Twist, a master transcription factor, in EMT program and subsequent changes in proliferation, migration and invasion of breast cancer cells by interfering STAT3 signaling pathway with different strategies such as STAT3 inactivation and STAT3 silencing. Furthermore, we explored the role of inhibiting STAT3 phosphorylation in the EMT regulation of ...
Post-translational modifications (PTMs) of transcription factors alter interactions with co-regulators and epigenetic modifiers. For example, members of the C/EBP transcription factor family are extensively methylated on arginine and lysine residues in short, conserved, modular domains, implying modification-dependent cofactor docking. Here we describe array peptide screening (APS), a systematic and differential approach to detect PTM-dependent interactions in the human proteome using chemically synthesized, biotinylated peptides coupled to fluorophore-labeled streptavidin. Peptides with and without a modified residue are applied in parallel to bacterial expression libraries in an arrayed format. Interactions are detected and quantified by laser scanning to reveal proteins that differentially bind to nonmodified or modified peptides. We have previously used this method to investigate the effect of arginine methylation of C/EBPβ peptides. The method enables determination of PTM-dependent transcription
The Turner lab has focused on the role of transcription factors in the development of peripheral sensory neurons, the spinal cord, midbrain, and habenula. Transcription factors are proteins which bind to DNA in the nucleus to switch on or off the genes which characterize specific cell types. Without the correct complement of transcription factors, cells undergo an identity crisis and fail to execute their correct developmental programs. Many genetic disorders in the brain and other organ systems have been linked to defective transcription factor function. Most of the Turner Lab studies have been conducted in transgenic mice in which they either knockout the factor of interest, or express a tracer protein in the neurons that express the factor. Studies have focused mainly on the homeodomain transcription factors Brn3a, Islet1, and Hmx1. In recent work, they have shown that without the combinatorial effects of Brn3a and Islet1, developing sensory neurons remain in a ground state in which ...
The analysis of regulatory regions in genome sequences is strongly based on the detection of potential transcription factor binding sites. The preferred models for representation of transcription factor binding specificity have been termed position-specific scoring matrices. JASPAR is an open-access …
Researchers are only beginning to understand how individual variation in gene regulation can have a lasting impact on ones health and susceptibility to certain diseases. Now, an ambitious survey of the human genome has identified differences in the binding of master regulators called transcription factors to DNA that affect how genes are expressed in different people.. The study, which is published in the March 18, 2010, issue of Science, looked at two common transcription factors. HHMI medical research fellow Maya Kasowski and her colleagues in the laboratory of molecular biologist Michael Snyder at Yale University conducted the work with Jan Korbel at the European Molecular Biology Laboratory. Snyder has since joined the faculty at Stanford University.. Transcription factors account for as much as 10 percent of the coding genome in humans and other organisms. When activated, transcription factors switch on or off hundreds or thousands of genes, a cascade that programs cells to grow or divide. ...
While developmental processes such as axon pathfinding and synapse formation have been characterized in detail, comparatively less is known of the intrinsic developmental mechanisms that regulate transcription of ion channel genes in embryonic neurons. Early decisions, including motoneuron axon targeting, are orchestrated by a cohort of transcription factors that act together in a combinatorial manner. These transcription factors include Even-skipped (Eve), islet and Lim3. The perdurance of these factors in late embryonic neurons is, however, indicative that they might also regulate additional aspects of neuron development, including the acquisition of electrical properties. To test the hypothesis that a combinatorial code transcription factor is also able to influence the acquisition of electrical properties in embryonic neurons we utilized the molecular genetics of Drosophila to manipulate the expression of Eve in identified motoneurons. We show that increasing expression of this transcription factor,
While developmental processes such as axon pathfinding and synapse formation have been characterized in detail, comparatively less is known of the intrinsic developmental mechanisms that regulate transcription of ion channel genes in embryonic neurons. Early decisions, including motoneuron axon targeting, are orchestrated by a cohort of transcription factors that act together in a combinatorial manner. These transcription factors include Even-skipped (Eve), islet and Lim3. The perdurance of these factors in late embryonic neurons is, however, indicative that they might also regulate additional aspects of neuron development, including the acquisition of electrical properties. To test the hypothesis that a combinatorial code transcription factor is also able to influence the acquisition of electrical properties in embryonic neurons we utilized the molecular genetics of Drosophila to manipulate the expression of Eve in identified motoneurons. We show that increasing expression of this transcription factor,
Transcriptional coactivator for steroid receptors and nuclear receptors. Greatly increases the transcriptional activity of PPARG and thyroid hormone receptor on the uncoupling protein promoter. Can regulate key mitochondrial genes that contribute to the program of adaptive thermogenesis. Plays an essential role in metabolic reprogramming in response to dietary availability through coordination of the expression of a wide array of genes involved in glucose and fatty acid metabolism. Induces the expression of PERM1 in the skeletal muscle in an ESRRA-dependent manner. Also involved in the integration of the circadian rhythms and energy metabolism. Required for oscillatory expression of clock genes, such as ARNTL/BMAL1 and NR1D1, through the coactivation of RORA and RORC, and metabolic genes, such as PDK4 and PEPCK. Isoform 4 specifically activates the expression of IGF1 and suppresses myostatin expression in skeletal muscle leading to muscle fiber hypertrophy.
Recent development of methods for genome‐wide identification of transcription factor binding sites by chromatin immunoprecipitation (ChIP) has led to novel insights into transcriptional regulation and greater understanding of the function of individual transcription factors
Background: Variants in transcription factor binding sites (TFBSs) may have important regulatory effects, as they have the potential to alter transcription factor (TF) binding affinities and thereby affecting gene expression. With recent advances in sequencing technologies the number of variants identified in TFBSs has increased, hence understanding their role is of significant interest when interpreting next generation sequencing data. Current methods have two major limitations: they are limited to predicting the functional impact of single nucleotide variants (SNVs) and often rely on additional experimental data, laborious and expensive to acquire. We propose a purely bioinformatic method that addresses these two limitations while providing comparable results. Results: Our method uses position weight matrices and a sliding window approach, in order to account for the sequence context of variants, and scores the consequences of both SNVs and INDELs in TFBSs. We tested the accuracy of our method ...
Transcriptional super-enhancers drive expression of oncogenes in many cancers and are being targeted with novel transcriptional and epigenetic therapeutics (1,2,3,4). Super-enhancers are acquired in cancers through multiple mechanisms, including DNA translocation of an extant super-enhancer and focal amplification. We recently discovered a novel mechanism by which super-enhancers are nucleated in T cell acute lymphoblastic leukemias (T-ALLs) (5). In this case, a small, monoallelic insertion creates a DNA binding site for a master transcription factor protein, which binds and recruits additional factors to nucleate the super-enhancer, which in turn drives high levels of the TAL1 transcription factor. We describe here a method for unbiased identification of similar genomic insertions that nucleate potentially oncogenic regulatory elements in cancers. This approach uses data from genome-wide ChIP-Seq studies that map locations of enhancer-binding proteins to identify sequences missing from ...
sequence-specific DNA binding transcription factors;sequence-specific DNA binding; FUNCTIONS IN: sequence-specific DNA binding, sequence-specific DNA binding transcription factor activity; INVOLVED IN: regulation of transcription, DNA-dependent; EXPRESSED IN: 22 plant structures; EXPRESSED DURING: 13 growth stages; CONTAINS InterPro DOMAIN/s: Homeobox (InterPro:IPR001356); BEST Arabidopsis thaliana protein match is: unknown protein (TAIR:AT1G15215.2); Has 91 Blast hits to 88 proteins in 16 species: Archae - 0; Bacteria - 0; Metazoa - 0; Fungi - 0; Plants - 91; Viruses - 0; Other Eukaryotes - 0 (source: NCBI BLink ...
It is important to note that even when all experiments are included, the best results produce clusters with only a 28% true positive rate (see Figure E.1.a in Additional data file 1). That is, most of the genes in a given cluster do not share a common, known transcription factor. There are several possible reasons for this. First, with the present state of knowledge, it is possible that genes in the same cluster do in fact share a common transcription factor that is not (yet) represented in the databases used as gold standards (YPD, SCPD and ChIP data). We note for example, that when one compares ChIP data to YPD, the false-negative rate is approximately 80% using the recommended p-value of 0.001. That is, known gene transcription factor interactions from YPD are identified only about 20% of the time by ChIP (see Table F in Additional data file 1). Hence, it is possible that our evaluation criteria all underestimate the number of co-regulated genes in a cluster. Second, gene regulation is more ...
Aplha, transcription related growth factors and stimulating factors or repressing nuclear factors are complex subunits of proteins involved in cell differentiation. Complex subunit associated factors are involved in hybridoma growth, Eosinohils, eritroid proliferation and derived from promotor binding stimulating subunits on the DNA binding complex. NFKB 105 subunit for example is a polypetide gene enhancer of genes in B cells.The activation of transcription factor subunits is the first step of gene expression, in which a particular segment of DNA is copied into RNA (mRNA) by the enzyme RNA polymerases. Transcription factors, unites and elongations can be RNA and DNA nucleic acids, base pairs of nucleotides . Converting from DNA to RNA is made by enzymatic reactions. During transcription, a DNA sequence is read by an RNA polymerase, which produces a complementary, anti-parallel RNA strand called a primary transcript. Transcriptions are key functions in signal transduction pathways. Signaling ...
T helper 17 (Th17) cells have crucial functions in mucosal immunity and the pathogenesis of several chronic inflammatory diseases. The lineage-specific transcription factor, RORγt, encoded by the RORC gene modulates Th17 polarization and function, as well as thymocyte development. Here we define several regulatory elements at the human RORC locus in thymocytes and peripheral CD4+ T lymphocytes, with CRISPR/Cas9-guided deletion of these genomic segments supporting their role in RORγt expression. Mechanistically, T cell receptor stimulation induces cyclosporine A-sensitive histone modifications and P300/CBP acetylase recruitment at these elements in activated CD4+ T cells. Meanwhile, NFAT proteins bind to these regulatory elements and activate RORγt transcription in cooperation with NF-kB. Our data thus demonstrate that NFAT specifically regulate RORγt expression by binding to the RORC locus and promoting its permissive conformation. The master transcription factor RORγt, encoded by the RORC gene,
Transcription factor and DNA molecule. Molecular model of glucocorticoid receptor (GR) transcription factor protein (purple and blue) complexed with a molecule of DNA (deoxyribonucleic acid, pink and green). Transcription factors regulate the transcription of DNA to RNA (ribonucleic acid) by the enzyme RNA polymerase. RNA is the intermediate product between a gene and its protein. When glucocorticoid binds to GR, GR enters the cells nucleus and binds to the DNA, causing an increase in the production of the apoptosis (programmed cell death) protein bax. - Stock Image A617/0259
Author Summary The main role of transcription factors is to modulate the expression levels of functionally related genes in response to environmental and cellular cues. For this process to be precise, the transcription factor needs to locate and bind specific DNA sequences in the genome and needs to bind these sites with a strength that appropriately adjusts the amount of gene expressed. Both specific protein-DNA interactions and transcription factor activity are intimately coupled, because they are both dependent upon the biochemical properties of the DNA-binding domain. Here we experimentally probe how variable these properties are using a novel in vivo selection assay. We observed that the specific binding preferences for the transcription factor MarA and its transcriptional activity can be altered over a large range with a few mutations and that selection on one function will impact the other. This work helps us to better understand the mechanism of transcriptional regulation and its evolution, and
1. JolmaA, YanJ, WhitingtonT, ToivonenJ, NittaKR, et al. (2013) DNA-binding specificities of human transcription factors. Cell 152: 327-339 doi:10.1016/j.cell.2012.12.009. 2. NobregaMA, OvcharenkoI, AfzalV, RubinEM (2003) Scanning human gene deserts for long-range enhancers. Science 302: 413 doi:10.1126/science.1088328. 3. BernsteinBE, BirneyE, DunhamI, GreenED, GunterC, et al. (2012) An integrated encyclopedia of DNA elements in the human genome. Nature 489: 57-74 doi:10.1038/nature11247. 4. Pique-RegiR, DegnerJF, PaiAA, GaffneyDJ, GiladY, et al. (2011) Accurate inference of transcription factor binding from DNA sequence and chromatin accessibility data. Genome Res 21: 447-455 doi:10.1101/gr.112623.110. 5. SongL, CrawfordGE (2010) DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells. Cold Spring Harb Protoc 2010: pdb.prot5384 doi:10.1101/pdb.prot5384. 6. YanJ, EngeM, WhitingtonT, DaveK, LiuJ, et al. (2013) Transcription factor ...
The oxygen distribution in skin is highly heterogeneous. Oxygen tension at the dermal-epithelial junction where melanocytes reside is about 5%, whereas it is about 0.5% around hair follicles (36). Oxygen availability has important physiological consequences, including the mediation of cellular transformation, especially during the melanocyte-melanoma transition (14). Cellular adaptation to hypoxia is facilitated by the expression of HIFα subunits, mainly HIF1α and HIF2α. HIF proteins are transcription factors that, under hypoxia, enable the activation of target genes involved in metabolism regulation, stress adaptation, growth, migration and invasion, drug resistance, and apoptotic cell death (37).. Protein function is frequently regulated by assembly into complexes. This aspect is particularly important for transcription factors, which interact with co-activators or repressors and with the transcription machinery to regulate gene expression. Indeed, transcription factor functions are ...
Hi: Take a look at TRANSFAC: http://nar.oupjournals.org/cgi/content/full/29/1/281 Good luck! On 8 Jun 2001 12:10:46 +0100, Heather Peto ,hp217 at cam.ac.uk, wrote: ,Hi , ,Does anyone know how I would look up which genes are turned on/off by ,a given transciption factor? Is there a database I can search? I am ,looking to see all the proteins produced / downgraded after CREB and ,a set of other transcription factors are activated. , ,many thanks , ,Heather :) , ...