JASPAR, the open access database of transcription factor-binding profiles: new content and tools in the 2008 update

Glucocorticoid receptor alpha isoform-selective regulation of antiapoptotic genes in osteosarcoma cells: a new mechanism for glucocorticoid resistance

Glucocorticoids regulate a variety of physiological processes and are commonly used to treat disorders of inflammation, autoimmune diseases, and cancer. Glucocorticoid action is predominantly mediated through the classic glucocorticoid receptor (GR)α isoform. Recent data suggest that the mature GRα mRNA is translated into multiple N-terminal isoforms that have distinct biochemical properties and gene regulatory profiles. Interestingly, osteosarcoma cells stably expressing the GRα-D translational isoform are unique in that they are resistant to glucocorticoid-induced apoptosis. In this study, we investigate whether GRα isoform-specific differences in the regulation of antiapoptotic genes contribute to this resistant phenotype. We now show that GRα-D, unlike the other receptor isoforms, does not inhibit the activity of a nuclear factor κB (NF-κB)-responsive reporter gene and does not efficiently repress either the transcription or protein production of the antiapoptotic genes Bcl-xL, cellular inhibitor of apoptosis protein 1, and survivin. The inability of GRα-D to down-regulate the expression of these genes appears to be associated with a diminished interaction between GRα-D and NF-κB that is observed in cells, but not in vitro, and likely reflects the sequestration of GRα-D in the nucleus. Deletion of the GRα N-terminal amino acids 98-335 also results in a nuclear resident GR, which fails to interact with NF-κB in cells and promote apoptosis in response to glucocorticoids. These data suggest that the N-terminal translational isoforms of GRα selectively regulate antiapoptotic genes and that the GRα-D isoform may contribute to the resistance of certain cancer cells to glucocorticoid-induced apoptosis.

A ChIP-Seq benchmark shows that sequence conservation mainly improves detection of strong transcription factor binding sites

BACKGROUND

Transcription factors are important controllers of gene expression and mapping transcription factor binding sites (TFBS) is key to inferring transcription factor regulatory networks. Several methods for predicting TFBS exist, but there are no standard genome-wide datasets on which to assess the performance of these prediction methods. Also, it is believed that information about sequence conservation across different genomes can generally improve accuracy of motif-based predictors, but it is not clear under what circumstances use of conservation is most beneficial.

RESULTS

Here we use published ChIP-seq data and an improved peak detection method to create comprehensive benchmark datasets for prediction methods which use known descriptors or binding motifs to detect TFBS in genomic sequences. We use this benchmark to assess the performance of five different prediction methods and find that the methods that use information about sequence conservation generally perform better than simpler motif-scanning methods. The difference is greater on high-affinity peaks and when using short and information-poor motifs. However, if the motifs are specific and information-rich, we find that simple motif-scanning methods can perform better than conservation-based methods.

CONCLUSIONS

Our benchmark provides a comprehensive test that can be used to rank the relative performance of transcription factor binding site prediction methods. Moreover, our results show that, contrary to previous reports, sequence conservation is better suited for predicting strong than weak transcription factor binding sites.

Predicting promoter activities of primary human DNA sequences

We developed a computer program that can predict the intrinsic promoter activities of primary human DNA sequences. We observed promoter activity using a quantitative luciferase assay and generated a prediction model using multiple linear regression. Our program achieved a prediction accuracy correlation coefficient of 0.87 between the predicted and observed promoter activities. We evaluated the prediction accuracy of the program using massive sequencing analysis of transcriptional start sites in vivo. We found that it is still difficult to predict transcript levels in a strictly quantitative manner in vivo; however, it was possible to select active promoters in a given cell from the other silent promoters. Using this program, we analyzed the transcriptional landscape of the entire human genome. We demonstrate that many human genomic regions have potential promoter activity, and the expression of some previously uncharacterized putatively non-protein-coding transcripts can be explained by our prediction model. Furthermore, we found that nucleosomes occasionally formed open chromatin structures with RNA polymerase II recruitment where the program predicted significant promoter activities, although no transcripts were observed.

Genome-wide tissue-specific occupancy of the Hox protein Ultrabithorax and Hox cofactor Homothorax in Drosophila

The Hox genes are responsible for generating morphological diversity along the anterior-posterior axis during animal development. The Drosophila Hox gene Ultrabithorax (Ubx), for example, is required for specifying the identity of the third thoracic (T3) segment of the adult, which includes the dorsal haltere, an appendage required for flight, and the ventral T3 leg. Ubx mutants show homeotic transformations of the T3 leg towards the identity of the T2 leg and the haltere towards the wing. All Hox genes, including Ubx, encode homeodomain containing transcription factors, raising the question of what target genes Ubx regulates to generate these adult structures. To address this question, we carried out whole genome ChIP-chip studies to identify all of the Ubx bound regions in the haltere and T3 leg imaginal discs, which are the precursors to these adult structures. In addition, we used ChIP-chip to identify the sites bound by the Hox cofactor, Homothorax (Hth). In contrast to previous ChIP-chip studies carried out in Drosophila embryos, these binding studies reveal that there is a remarkable amount of tissue- and transcription factor-specific binding. Analyses of the putative target genes bound and regulated by these factors suggest that Ubx regulates many downstream transcription factors and developmental pathways in the haltere and T3 leg. Finally, we discovered additional DNA sequence motifs that in some cases are specific for individual data sets, arguing that Ubx and/or Hth work together with many regionally expressed transcription factors to execute their functions. Together, these data provide the first whole-genome analysis of the binding sites and target genes regulated by Ubx to specify the morphologies of the adult T3 segment of the fly.

Hypoxia-inducible factor regulates expression of surfactant protein in alveolar type II cells in vitro

Alveolar type II (ATII) cells cultured at an air-liquid (A/L) interface maintain differentiation, but they lose these properties when they are submerged. Others showed that an oxygen tension gradient develops in the culture medium as ATII cells consume oxygen. Therefore, we wondered whether hypoxia inducible factor (HIF) signaling could explain differences in the phenotypes of ATII cells cultured under A/L interface or submerged conditions. ATII cells were isolated from male Sprague-Dawley rats and cultured on inserts coated with a mixture of rat-tail collagen and Matrigel, in medium including 5% rat serum and 10 ng/ml keratinocyte growth factor, with their apical surfaces either exposed to air or submerged. The A/L interface condition maintained the expression of surfactant proteins, whereas that expression was down-regulated under the submerged condition, and the effect was rapid and reversible. Under submerged conditions, there was an increase in HIF1α and HIF2α in nuclear extracts, mRNA levels of HIF inducible genes, vascular endothelial growth factor, glucose transporter-1 (GLUT1), and the protein level of pyruvate dehydrogenase kinase isozyme-1. The expression of surfactant proteins was suppressed and GLUT1 mRNA levels were induced when cells were cultured with 1 mM dimethyloxalyl glycine. The expression of surfactant proteins was restored under submerged conditions with supplemented 60% oxygen. HIF signaling and oxygen tension at the surface of cells appears to be important in regulating the phenotype of rat ATII cells.

Genome-wide promoter DNA methylation dynamics of human hematopoietic progenitor cells during differentiation and aging

DNA methylation plays an important role in the self-renewal of hematopoietic stem cells and in the commitment to the lymphoid or myeloid lineages. Using purified CD34⁺ hematopoietic progenitor cells and differentiated myeloid cell populations from the same human samples, we obtained detailed methylation profiles at distinct stages of hematopoiesis. We identified a defined set of differentiation-related genes that are methylated in CD34⁺ hematopoietic progenitor cells but show pronounced DNA hypomethylation in monocytes and in granulocytes. In addition, by comparing hematopoietic progenitor cells from umbilical cord blood to hematopoietic progenitor cells from peripheral blood of adult donors we were also able to analyze age-related methylation changes in CD34⁺ cells. Interestingly, the methylation changes observed in older progenitor cells showed a bimodal pattern with hypomethylation of differentiation-associated genes and de novo methylation events resembling epigenetic mutations. Our results thus provide detailed insight into the methylation dynamics during differentiation and suggest that epigenetic changes contribute to hematopoietic progenitor cell aging.

Azacytidine and decitabine induce gene-specific and non-random DNA demethylation in human cancer cell lines

The DNA methyltransferase inhibitors azacytidine and decitabine represent archetypal drugs for epigenetic cancer therapy. To characterize the demethylating activity of azacytidine and decitabine we treated colon cancer and leukemic cells with both drugs and used array-based DNA methylation analysis of more than 14,000 gene promoters. Additionally, drug-induced demethylation was compared to methylation patterns of isogenic colon cancer cells lacking both DNA methyltransferase 1 (DNMT1) and DNMT3B. We show that drug-induced demethylation patterns are highly specific, non-random and reproducible, indicating targeted remethylation of specific loci after replication. Correspondingly, we found that CG dinucleotides within CG islands became preferentially remethylated, indicating a role for DNA sequence context. We also identified a subset of genes that were never demethylated by drug treatment, either in colon cancer or in leukemic cell lines. These demethylation-resistant genes were enriched for Polycomb Repressive Complex 2 components in embryonic stem cells and for transcription factor binding motifs not present in demethylated genes. Our results provide detailed insights into the DNA methylation patterns induced by azacytidine and decitabine and suggest the involvement of complex regulatory mechanisms in drug-induced DNA demethylation.

Regulating Il9 transcription in T helper cells

T helper (Th) cells are crucial for the development of immunity to infections and inflammatory disease. The acquisition of specific cytokine-secreting profiles, primed by the cytokine microenvironment, is required for effector function of Th cells. The most recent addition to the growing list of effector subsets are Th9 cells that secrete IL-9. In this review, we propose a model for the transcriptional regulation of the Il9 gene in IL-9-expressing T cells and the relatedness of this subset to other Th phenotypes. We suggest that transcription factors restricted to certain Th subsets and common among several subsets might play a role in the plasticity of Th9 cells.

Using a structural and logics systems approach to infer bHLH-DNA binding specificity determinants

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein–DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH–DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.

Evolution of promoter affinity for transcription factors in the human lineage

Changes in gene regulation are believed to play an important role in the evolution of animals. It has been suggested that changes in cis-regulatory regions are responsible for many or most of the anatomical and behavioral differences between humans and apes. However, the study of the evolution of cis-regulatory regions is made problematic by the degeneracy of transcription factor (TF) binding sites and the shuffling of their positions. In this work, we use the predicted total affinity of a promoter for a large collection of TFs as the basis for studying the evolution of cis-regulatory regions in mammals. We introduce the human specificity of a promoter, measuring the divergence between the affinity profile of a human promoter and its orthologous promoters in other mammals. The promoters of genes involved in functional categories such as neural processes and signal transduction, among others, have higher human specificity compared with the rest of the genome. Clustering of the human-specific affinities (HSAs) of neural genes reveals patterns of promoter evolution associated with functional categories such as synaptic transmission and brain development and to diseases such as bipolar disorder and autism.

An integrated pipeline for the genome-wide analysis of transcription factor binding sites from ChIP-Seq

ChIP-Seq has become the standard method for genome-wide profiling DNA association of transcription factors. To simplify analyzing and interpreting ChIP-Seq data, which typically involves using multiple applications, we describe an integrated, open source, R-based analysis pipeline. The pipeline addresses data input, peak detection, sequence and motif analysis, visualization, and data export, and can readily be extended via other R and Bioconductor packages. Using a standard multicore computer, it can be used with datasets consisting of tens of thousands of enriched regions. We demonstrate its effectiveness on published human ChIP-Seq datasets for FOXA1, ER, CTCF and STAT1, where it detected co-occurring motifs that were consistent with the literature but not detected by other methods. Our pipeline provides the first complete set of Bioconductor tools for sequence and motif analysis of ChIP-Seq and ChIP-chip data.

Sex hormones in autism: androgens and estrogens differentially and reciprocally regulate RORA, a novel candidate gene for autism

Autism, a pervasive neurodevelopmental disorder manifested by deficits in social behavior and interpersonal communication, and by stereotyped, repetitive behaviors, is inexplicably biased towards males by a ratio of ∼4∶1, with no clear understanding of whether or how the sex hormones may play a role in autism susceptibility. Here, we show that male and female hormones differentially regulate the expression of a novel autism candidate gene, retinoic acid-related orphan receptor-alpha (RORA) in a neuronal cell line, SH-SY5Y. In addition, we demonstrate that RORA transcriptionally regulates aromatase, an enzyme that converts testosterone to estrogen. We further show that aromatase protein is significantly reduced in the frontal cortex of autistic subjects relative to sex- and age-matched controls, and is strongly correlated with RORA protein levels in the brain. These results indicate that RORA has the potential to be under both negative and positive feedback regulation by male and female hormones, respectively, through one of its transcriptional targets, aromatase, and further suggest a mechanism for introducing sex bias in autism.

Systematic search for enhancer elements and somatic allelic imbalance at seven low-penetrance colorectal cancer predisposition loci

BACKGROUND

Common single-nucleotide polymorphisms (SNPs) in ten chromosomal loci have been shown to predispose to colorectal cancer (CRC) in genome-wide association studies. A plausible biological mechanism of CRC susceptibility associated with genetic variation has so far only been proposed for three loci, each pointing to variants that affect gene expression through distant regulatory elements. In this study, we aimed to gain insight into the molecular basis of seven low-penetrance CRC loci tagged by rs4779584 at 15q13, rs10795668 at 10p14, rs3802842 at 11q23, rs4444235 at 14q22, rs9929218 at 16q22, rs10411210 at 19q13, and rs961253 at 20p12.

METHODS

Possible somatic gain of the risk allele or loss of the protective allele was studied by analyzing allelic imbalance in tumour and corresponding normal tissue samples of heterozygous patients. Functional variants were searched from in silico predicted enhancer elements locating inside the CRC-associating linkage-disequilibrium regions.

RESULTS

No allelic imbalance targeting the SNPs was observed at any of the seven loci. Altogether, 12 SNPs that were predicted to disrupt potential transcription factor binding sequences were genotyped in the same population-based case-control series as the seven tagging SNPs originally. None showed association with CRC.

CONCLUSIONS

The results of the allelic imbalance analysis suggest that the seven CRC risk variants are not somatically selected for in the neoplastic progression. The bioinformatic approach was unable to pinpoint cancer-causing variants at any of the seven loci. While it is possible that many of the predisposition loci for CRC are involved in control of gene expression by targeting transcription factor binding sites, also other possibilities, such as regulatory RNAs, should be considered.

Delay in feedback repression by cryptochrome 1 is required for circadian clock function

Direct evidence for the requirement of delay in feedback repression in the mammalian circadian clock has been elusive. Cryptochrome 1 (Cry1), an essential clock component, displays evening-time expression and serves as a strong repressor at morning-time elements (E box/E' box). In this study, we reveal that a combination of day-time elements (D box) within the Cry1-proximal promoter and night-time elements (RREs) within its intronic enhancer gives rise to evening-time expression. A synthetic composite promoter produced evening-time expression, which was further recapitulated by a simple phase-vector model. Of note, coordination of day-time with night-time elements can modulate the extent of phase delay. A genetic complementation assay in Cry1(-/-):Cry2(-/-) cells revealed that substantial delay of Cry1 expression is required to restore circadian rhythmicity, and its prolonged delay slows circadian oscillation. Taken together, our data suggest that phase delay in Cry1 transcription is required for mammalian clock function.

De-novo discovery of differentially abundant transcription factor binding sites including their positional preference

Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom.

Binding of transcription factors to promoters of genes, and subsequent enhancement or repression of transcription, is one of the main steps of transcriptional gene regulation. Direct or indirect wet-lab experiments allow the identification of approximate regions potentially bound or regulated by a transcription factor. Subsequently, de-novo motif discovery tools can be used for detecting the precise positions of binding sites. Many traditional tools focus on motifs over-represented in the target regions, which often turn out to be similarly over-represented in the entire genome. In contrast, several recent tools focus on differentially abundant motifs in target regions compared to a control set. As binding sites are often located at some preferred distance to the transcription start site, it is favorable to include this information into de-novo motif discovery. Here, we present Dispom a novel approach for learning differentially abundant motifs and their positional preferences simultaneously, which predicts binding sites with increased accuracy compared to many popular de-novo motif discovery tools. When applying Dispom to promoters of auxin-responsive genes of Arabidopsis thaliana, we find a binding motif slightly different from the canonical auxin-response element, which exhibits a strong positional preference and which is considerably more specific to auxin-responsive genes.

G = MAT: linking transcription factor expression and DNA binding data

Transcription factors are proteins that bind to motifs on the DNA and thus affect gene expression regulation. The qualitative description of the corresponding processes is therefore important for a better understanding of essential biological mechanisms. However, wet lab experiments targeted at the discovery of the regulatory interplay between transcription factors and binding sites are expensive. We propose a new, purely computational method for finding putative associations between transcription factors and motifs. This method is based on a linear model that combines sequence information with expression data. We present various methods for model parameter estimation and show, via experiments on simulated data, that these methods are reliable. Finally, we examine the performance of this model on biological data and conclude that it can indeed be used to discover meaningful associations. The developed software is available as a web tool and Scilab source code at http://biit.cs.ut.ee/gmat/.

Gene expression analysis of the emergence of epileptiform activity after focal injection of kainic acid into mouse hippocampus

We report gene profiling data on genomic processes underlying the progression towards recurrent seizures after injection of kainic acid (KA) into the mouse hippocampus. Focal injection enabled us to separate the effects of proepileptic stimuli initiated by KA injection. Both the injected and contralateral hippocampus participated in the status epilepticus. However, neuronal death induced by KA treatment was restricted to the injected hippocampus, although there was some contralateral axonal degeneration. We profiled gene expression changes in dorsal and ventral regions of both the injected and contralateral hippocampus. Changes were detected in the expression of 1526 transcripts in samples from three time-points: (i) during the KA-induced status epilepticus, (ii) at 2 weeks, before recurrent seizures emerged, and (iii) at 6 months after seizures emerged. Grouping genes with similar spatio-temporal changes revealed an early transcriptional response, strong immune, cell death and growth responses at 2 weeks and an activation of immune and extracellular matrix genes persisting at 6 months. Immunostaining for proteins coded by genes identified from array studies provided evidence for gliogenesis and suggested that the proteoglycan biglycan is synthesized by astrocytes and contributes to a glial scar. Gene changes at 6 months after KA injection were largely restricted to tissue from the injection site. This suggests that either recurrent seizures might depend on maintained processes including immune responses and changes in extracellular matrix proteins near the injection site or alternatively might result from processes, such as growth, distant from the injection site and terminated while seizures are maintained.

ZFNGenome: a comprehensive resource for locating zinc finger nuclease target sites in model organisms

Background

Zinc Finger Nucleases (ZFNs) have tremendous potential as tools to facilitate genomic modifications, such as precise gene knockouts or gene replacements by homologous recombination. ZFNs can be used to advance both basic research and clinical applications, including gene therapy. Recently, the ability to engineer ZFNs that target any desired genomic DNA sequence with high fidelity has improved significantly with the introduction of rapid, robust, and publicly available techniques for ZFN design such as the Oligomerized Pool ENgineering (OPEN) method. The motivation for this study is to make resources for genome modifications using OPEN-generated ZFNs more accessible to researchers by creating a user-friendly interface that identifies and provides quality scores for all potential ZFN target sites in the complete genomes of several model organisms.

Description

ZFNGenome is a GBrowse-based tool for identifying and visualizing potential target sites for OPEN-generated ZFNs. ZFNGenome currently includes a total of more than 11.6 million potential ZFN target sites, mapped within the fully sequenced genomes of seven model organisms; S. cerevisiae, C. reinhardtii, A. thaliana, D. melanogaster, D. rerio, C. elegans, and H. sapiens and can be visualized within the flexible GBrowse environment. Additional model organisms will be included in future updates. ZFNGenome provides information about each potential ZFN target site, including its chromosomal location and position relative to transcription initiation site(s). Users can query ZFNGenome using several different criteria (e.g., gene ID, transcript ID, target site sequence). Tracks in ZFNGenome also provide "uniqueness" and ZiFOpT (Zinc Finger OPEN Targeter) "confidence" scores that estimate the likelihood that a chosen ZFN target site will function in vivo. ZFNGenome is dynamically linked to ZiFDB, allowing users access to all available information about zinc finger reagents, such as the effectiveness of a given ZFN in creating double-stranded breaks.

Conclusions

ZFNGenome provides a user-friendly interface that allows researchers to access resources and information regarding genomic target sites for engineered ZFNs in seven model organisms. This genome-wide database of potential ZFN target sites should greatly facilitate the utilization of ZFNs in both basic and clinical research.

ZFNGenome is freely available at: http://bindr.gdcb.iastate.edu/ZFNGenome or at the Zinc Finger Consortium website: http://www.zincfingers.org/.

A systems biology model of the regulatory network in Populus leaves reveals interacting regulators and conserved regulation

BACKGROUND

Green plant leaves have always fascinated biologists as hosts for photosynthesis and providers of basic energy to many food webs. Today, comprehensive databases of gene expression data enable us to apply increasingly more advanced computational methods for reverse-engineering the regulatory network of leaves, and to begin to understand the gene interactions underlying complex emergent properties related to stress-response and development. These new systems biology methods are now also being applied to organisms such as Populus, a woody perennial tree, in order to understand the specific characteristics of these species.

RESULTS

We present a systems biology model of the regulatory network of Populus leaves. The network is reverse-engineered from promoter information and expression profiles of leaf-specific genes measured over a large set of conditions related to stress and developmental. The network model incorporates interactions between regulators, such as synergistic and competitive relationships, by evaluating increasingly more complex regulatory mechanisms, and is therefore able to identify new regulators of leaf development not found by traditional genomics methods based on pair-wise expression similarity. The approach is shown to explain available gene function information and to provide robust prediction of expression levels in new data. We also use the predictive capability of the model to identify condition-specific regulation as well as conserved regulation between Populus and Arabidopsis.

CONCLUSIONS

We outline a computationally inferred model of the regulatory network of Populus leaves, and show how treating genes as interacting, rather than individual, entities identifies new regulators compared to traditional genomics analysis. Although systems biology models should be used with care considering the complexity of regulatory programs and the limitations of current genomics data, methods describing interactions can provide hypotheses about the underlying cause of emergent properties and are needed if we are to identify target genes other than those constituting the "low hanging fruit" of genomic analysis.

Methods for Analysis of Transcription Factor DNA-Binding Specificity In Vitro

Transcription of genes during development and in response to environmental stimuli is determined by genomic DNA sequence. The DNA sequences regulating transcription are read by sequence-specific transcription factors (TFs) that recognize relatively short sequences, generally between four and twenty base pairs in length. Transcriptional regulation generally requires binding of multiple TFs in close proximity to each other. Mechanistic understanding of transcription in an organism thus requires detailed knowledge of binding affinities of all its TFs to all possible DNA sequences, and the co-operative interactions between the TFs. However, very little is known about such co-operative binding interactions, and even the simple TF-DNA binding information exists only for a very small proportion of all TFs - for example, mammals have approximately 1,300-2,000 TFs [1, 2], yet the largest public databases for TF binding specificity, Jaspar and Uniprobe [3, 4] currently list only approximately 500 moderate to high resolution profiles for human or mouse. This lack of knowledge is in part due to the fact that analysis of TF DNA binding has been laborious and expensive. In this chapter, we review methods that can be used to determine binding specificity of TFs to DNA, mainly focusing on recently developed assays that allow high-resolution analysis of TF binding specificity in relatively high throughput.

Characterization of the core elements of the NF-κB signaling pathway of the sea anemone Nematostella vectensis

The sea anemone Nematostella vectensis is the leading developmental and genomic model for the phylum Cnidaria, which includes anemones, hydras, jellyfish, and corals. In insects and vertebrates, the NF-κB pathway is required for cellular and organismal responses to various stresses, including pathogens and chemicals, as well as for several developmental processes. Herein, we have characterized proteins that comprise the core NF-κB pathway in Nematostella, including homologs of NF-κB, IκB, Bcl-3, and IκB kinase (IKK). We show that N. vectensis NF-κB (Nv-NF-κB) can bind to κB sites and activate transcription of reporter genes containing multimeric κB sites or the Nv-IκB promoter. Both Nv-IκB and Nv-Bcl-3 interact with Nv-NF-κB and block its ability to activate reporter gene expression. Nv-IKK is most similar to human IKKε/TBK kinases and, in vitro, can phosphorylate Ser47 of Nv-IκB. Nv-NF-κB is expressed in a subset of ectodermal cells in juvenile and adult Nematostella anemones. A bioinformatic analysis suggests that homologs of many mammalian NF-κB target genes are targets for Nv-NF-κB, including genes involved in apoptosis and responses to organic compounds and endogenous stimuli. These results indicate that NF-κB pathway proteins in Nematostella are similar to their vertebrate homologs, and these results also provide a framework for understanding the evolutionary origins of NF-κB signaling.

CompleteMOTIFs: DNA motif discovery platform for transcription factor binding experiments

CompleteMOTIFs (cMOTIFs) is an integrated web tool developed to facilitate systematic discovery of overrepresented transcription factor binding motifs from high-throughput chromatin immunoprecipitation experiments. Comprehensive annotations and Boolean logic operations on multiple peak locations enable users to focus on genomic regions of interest for de novo motif discovery using tools such as MEME, Weeder and ChIPMunk. The pipeline incorporates a scanning tool for known motifs from TRANSFAC and JASPAR databases, and performs an enrichment test using local or precalculated background models that significantly improve the motif scanning result. Furthermore, using the cMOTIFs pipeline, we demonstrated that multiple transcription factors could cooperatively bind to the upstream of important stem cell differentiation regulators.

AVAILABILITY

http://cmotifs.tchlab.org.

Modeling the evolution of regulatory elements by simultaneous detection and alignment with phylogenetic pair HMMs

The computational detection of regulatory elements in DNA is a difficult but important problem impacting our progress in understanding the complex nature of eukaryotic gene regulation. Attempts to utilize cross-species conservation for this task have been hampered both by evolutionary changes of functional sites and poor performance of general-purpose alignment programs when applied to non-coding sequence. We describe a new and flexible framework for modeling binding site evolution in multiple related genomes, based on phylogenetic pair hidden Markov models which explicitly model the gain and loss of binding sites along a phylogeny. We demonstrate the value of this framework for both the alignment of regulatory regions and the inference of precise binding-site locations within those regions. As the underlying formalism is a stochastic, generative model, it can also be used to simulate the evolution of regulatory elements. Our implementation is scalable in terms of numbers of species and sequence lengths and can produce alignments and binding-site predictions with accuracy rivaling or exceeding current systems that specialize in only alignment or only binding-site prediction. We demonstrate the validity and power of various model components on extensive simulations of realistic sequence data and apply a specific model to study Drosophila enhancers in as many as ten related genomes and in the presence of gain and loss of binding sites. Different models and modeling assumptions can be easily specified, thus providing an invaluable tool for the exploration of biological hypotheses that can drive improvements in our understanding of the mechanisms and evolution of gene regulation.

Reconstruction of gene association network reveals a transmembrane protein required for adipogenesis and targeted by PPARγ

We have developed a method for reconstructing gene association networks and have applied this method to gene profiles from 3T3-L1 cells. Priorization of the candidate genes pinpointed a transcript annotated as APMAP (adipocyte plasma membrane-associated protein). Functional studies showed that APMAP is upregulated in murine and human adipogenic cell models as well as in a genetic mouse model of obesity. Silencing APMAP in 3T3-L1 cells strongly impaired the differentiation into adipocytes. Moreover, APMAP expression was strongly induced by the PPARγ ligand rosiglitazone in adipocytes in vitro and in vivo in adipose tissue. Using ChIP-qPCR and luciferase reporter assays, we show a functional PPARγ binding site. In addition, we provide evidence that the extracellular C-terminal domain of APMAP is required for the function of APMAP in adipocyte differentiation. Finally, we demonstrate that APMAP translocates from the endoplasmatic reticulum to the plasma membrane during adipocyte differentiation.

Predicting DNA-binding specificities of eukaryotic transcription factors

Today, annotated amino acid sequences of more and more transcription factors (TFs) are readily available. Quantitative information about their DNA-binding specificities, however, are hard to obtain. Position frequency matrices (PFMs), the most widely used models to represent binding specificities, are experimentally characterized only for a small fraction of all TFs. Even for some of the most intensively studied eukaryotic organisms (i.e., human, rat and mouse), roughly one-sixth of all proteins with annotated DNA-binding domain have been characterized experimentally. Here, we present a new method based on support vector regression for predicting quantitative DNA-binding specificities of TFs in different eukaryotic species. This approach estimates a quantitative measure for the PFM similarity of two proteins, based on various features derived from their protein sequences. The method is trained and tested on a dataset containing 1 239 TFs with known DNA-binding specificity, and used to predict specific DNA target motifs for 645 TFs with high accuracy.

High-resolution genome-wide in vivo footprinting of diverse transcription factors in human cells

Regulation of gene transcription in diverse cell types is determined largely by varied sets of cis-elements where transcription factors bind. Here we demonstrate that data from a single high-throughput DNase I hypersensitivity assay can delineate hundreds of thousands of base-pair resolution in vivo footprints in human cells that precisely mark individual transcription factor-DNA interactions. These annotations provide a unique resource for the investigation of cis-regulatory elements. We find that footprints for specific transcription factors correlate with ChIP-seq enrichment and can accurately identify functional versus nonfunctional transcription factor motifs. We also find that footprints reveal a unique evolutionary conservation pattern that differentiates functional footprinted bases from surrounding DNA. Finally, detailed analysis of CTCF footprints suggests multiple modes of binding and a novel DNA binding motif upstream of the primary binding site.

Conservation of shh cis-regulatory architecture of the coelacanth is consistent with its ancestral phylogenetic position

Background

The modern coelacanth (Latimeria) is the extant taxon of a basal sarcopterygian lineage and sister group to tetrapods. Apart from certain apomorphic traits, its morphology is characterized by a high degree of retention of ancestral vertebrate structures and little morphological change. An insight into the molecular evolution that may explain the unchanged character of Latimeria morphology requires the analysis of the expression patterns of developmental regulator genes and their cis-regulatory modules (CRMs).

Results

We describe the comparative and functional analysis of the sonic hedgehog (shh) genomic region of Latimeria menadoensis. Several putative enhancers in the Latimeria shh locus have been identified by comparisons to sarcopterygian and actinopterygian extant species. Specific sequence conservation with all known actinopterygian enhancer elements has been detected. However, these elements are selectively missing in more recently diverged actinopterygian and sarcopterygian species. The functionality of the putative Latimeria enhancers was confirmed by reporter gene expression analysis in transient transgenic zebrafish and chick embryos.

Conclusions

Latimeria shh CRMs represent the ancestral set of enhancers that have emerged before the split of lobe-finned and ray-finned fishes. In contrast to lineage-specific losses and differentiations in more derived lineages, Latimeria shh enhancers reveal low levels of sequence diversification. High overall sequence conservation of shh conserved noncoding elements (CNE) is consistent with the general trend of high levels of conservation of noncoding DNA in the slowly evolving Latimeria genome.

Unbiased, genome-wide in vivo mapping of transcriptional regulatory elements reveals sex differences in chromatin structure associated with sex-specific liver gene expression

We have used a simple and efficient method to identify condition-specific transcriptional regulatory sites in vivo to help elucidate the molecular basis of sex-related differences in transcription, which are widespread in mammalian tissues and affect normal physiology, drug response, inflammation, and disease. To systematically uncover transcriptional regulators responsible for these differences, we used DNase hypersensitivity analysis coupled with high-throughput sequencing to produce condition-specific maps of regulatory sites in male and female mouse livers and in livers of male mice feminized by continuous infusion of growth hormone (GH). We identified 71,264 hypersensitive sites, with 1,284 showing robust sex-related differences. Continuous GH infusion suppressed the vast majority of male-specific sites and induced a subset of female-specific sites in male livers. We also identified broad genomic regions (up to ∼100 kb) showing sex-dependent hypersensitivity and similar patterns of GH responses. We found a strong association of sex-specific sites with sex-specific transcription; however, a majority of sex-specific sites were >100 kb from sex-specific genes. By analyzing sequence motifs within regulatory regions, we identified two known regulators of liver sexual dimorphism and several new candidates for further investigation. This approach can readily be applied to mapping condition-specific regulatory sites in mammalian tissues under a wide variety of physiological conditions.

Processing and analyzing ChIP-seq data: from short reads to regulatory interactions

Chromatin-immunoprecipitation and sequencing (ChIP-seq) is a rapidly maturing technology that draws on the power of high-throughput short-read sequencing to decipher chromatin states with unprecedented precision and breadth. Although some aspects of the experimental protocol require careful tuning, the bottleneck currently firmly lies with the downstream data analysis. We give an overview of the better-established aspects of genome mapping and data normalization and we describe the more recent progress in peak calling and their statistical analysis and provide a brief overview of popular follow-up analyses such as genomic feature categorization and motif search.

Poly(ADP-ribose) polymerase 1 participates in the phase entrainment of circadian clocks to feeding

Circadian clocks in peripheral organs are tightly coupled to cellular metabolism and are readily entrained by feeding-fasting cycles. However, the molecular mechanisms involved are largely unknown. Here we show that in liver the activity of PARP-1, an NAD(+)-dependent ADP-ribosyltransferase, oscillates in a daily manner and is regulated by feeding. We provide biochemical evidence that PARP-1 binds and poly(ADP-ribosyl)ates CLOCK at the beginning of the light phase. The loss of PARP-1 enhances the binding of CLOCK-BMAL1 to DNA and leads to a phase-shift of the interaction of CLOCK-BMAL1 with PER and CRY repressor proteins. As a consequence, CLOCK-BMAL1-dependent gene expression is altered in PARP-1-deficient mice, in particular in response to changes in feeding times. Our results show that Parp-1 knockout mice exhibit impaired food entrainment of peripheral circadian clocks and support a role for PARP-1 in connecting feeding with the mammalian timing system.

Identification of cis-regulatory elements in the mammalian genome: the cREMaG database

Background

A growing number of gene expression-profiling datasets provides a reliable source of information about gene co-expression. In silico analyses of the properties shared among the promoters of co-expressed genes facilitates the identification of transcription factors (TFs) involved in the co-regulation of those genes. Our previous experience with microarray data led to the development of a database suitable for the examination of regulatory motifs in the promoters of co-expressed genes.

Methodology

We introduce the cREMaG (cis-Regulatory Elements in the Mammalian Genome) system designed for in silico studies of the promoter properties of co-regulated mammalian genes. The cREMaG system offers an analysis of data obtained from human, mouse, rat, bovine and canine gene expression-profiling studies. More than eight analysis parameters can be utilized in user-defined combinations. The selection of alternative transcription start sites and information about CpG islands are also available.

Conclusions

Using the cREMaG system, we successfully identified TFs mediating transcriptional responses in reference gene sets. The cREMaG system facilitates in silico studies of mammalian transcriptional gene regulation. The resource is freely available at http://www.cremag.org.

ChIP-Seq identification of weakly conserved heart enhancers

Accurate control of tissue-specific gene expression plays a pivotal role in heart development, but few cardiac transcriptional enhancers have thus far been identified. Extreme noncoding-sequence conservation has successfully predicted enhancers that are active in many tissues but has failed to identify substantial numbers of heart-specific enhancers. Here, we used ChIP-Seq with the enhancer-associated protein p300 from mouse embryonic day 11.5 heart tissue to identify over 3,000 candidate heart enhancers genome wide. Compared to enhancers active in other tissues we studied at this time point, most candidate heart enhancers were less deeply conserved in vertebrate evolution. Nevertheless, transgenic mouse assays of 130 candidate regions revealed that most function reproducibly as enhancers active in the heart, irrespective of their degree of evolutionary constraint. These results provide evidence for a large population of poorly conserved heart enhancers and suggest that the evolutionary conservation of embryonic enhancers can vary depending on tissue type.

Biological reprogramming in acquired resistance to endocrine therapy of breast cancer

Endocrine therapies targeting the proliferative effect of 17β-estradiol through estrogen receptor α (ERα) are the most effective systemic treatment of ERα-positive breast cancer. However, most breast tumors initially responsive to these therapies develop resistance through molecular mechanisms that are not yet fully understood. The long-term estrogen-deprived (LTED) MCF7 cell model has been proposed to recapitulate acquired resistance to aromatase inhibitors in postmenopausal women. To elucidate this resistance, genomic, transcriptomic and molecular data were integrated into the time course of MCF7-LTED adaptation. Dynamic and widespread genomic changes were observed, including amplification of the ESR1 locus consequently linked to an increase in ERα. Dynamic transcriptomic profiles were also observed that correlated significantly with genomic changes and were predicted to be influenced by transcription factors known to be involved in acquired resistance or cell proliferation (for example, interferon regulatory transcription factor 1 and E2F1, respectively) but, notably, not by canonical ERα transcriptional function. Consistently, at the molecular level, activation of growth factor signaling pathways by EGFR/ERBB/AKT and a switch from phospho-Ser118 (pS118)- to pS167-ERα were observed during MCF7-LTED adaptation. Evaluation of relevant clinical settings identified significant associations between MCF7-LTED and breast tumor transcriptome profiles that characterize ERα-negative status, early response to letrozole and tamoxifen, and recurrence after tamoxifen treatment. In accordance with these profiles, MCF7-LTED cells showed increased sensitivity to inhibition of FGFR-mediated signaling with PD173074. This study provides mechanistic insight into acquired resistance to endocrine therapies of breast cancer and highlights a potential therapeutic strategy.

Common variants in the calcium-sensing receptor gene are associated with total serum calcium levels

Serum calcium levels are tightly regulated. We performed genome-wide association studies (GWAS) in population-based studies participating in the CHARGE Consortium to uncover common genetic variations associated with total serum calcium levels. GWAS of serum calcium concentrations was performed in 20 611 individuals of European ancestry for ∼2.5 million genotyped and imputed single-nucleotide polymorphisms (SNPs). The SNP with the lowest P-value was rs17251221 (P = 2.4 * 10(-22), minor allele frequency 14%) in the calcium-sensing receptor gene (CASR). This lead SNP was associated with higher serum calcium levels [0.06 mg/dl (0.015 mmol/l) per copy of the minor G allele] and accounted for 0.54% of the variance in serum calcium concentrations. The identification of variation in CASR that influences serum calcium concentration confirms the results of earlier candidate gene studies. The G allele of rs17251221 was also associated with higher serum magnesium levels (P = 1.2 * 10(-3)), lower serum phosphate levels (P = 2.8 * 10(-7)) and lower bone mineral density at the lumbar spine (P = 0.038), but not the femoral neck. No additional genomic loci contained SNPs associated at genome-wide significance (P < 5 * 10(-8)). These associations resemble clinical characteristics of patients with familial hypocalciuric hypercalcemia, an autosomal-dominant disease arising from rare inactivating mutations in the CASR gene. We conclude that common genetic variation in the CASR gene is associated with similar but milder features in the general population.

Global Egr1-miRNAs binding analysis in PMA-induced K562 cells using ChIP-Seq

Although much is known about microRNAs' regulation in gene expression and their contributions in cell fate, to date, globally lineage-(cell-) specific identification of the binding events between a transcription factor and its targeting microRNA genes is still waiting for elucidation. In this paper, we performed a ChIP-Seq experiment to find the targeting microRNA genes of a transcription factor, Egr1, in human erythroleukemia cell line K562. We found Egr1 binding sites near the promoters of 124 distinct microRNA genes, accounting for about 42% of the miRNAs which have high-confidence predicted promoters (294). We also found EGR1 bind to another 63 pre-miRNAs. We chose 12 of the 187 microRNAs with Egr1 binding sites to perform ChIP-PCR assays and the positive binding signal from ChIP-PCR confirmed the ChIP-Seq results. Our experiments provide the first global binding profile between Egr1 and its targeting microRNA genes in PMA-treated K562 cells, which may facilitate the understanding of pathways controlling microRNA biology in this specific cell line.

Genome-wide identification of cis-regulatory motifs and modules underlying gene coregulation using statistics and phylogeny

Cell fate determination depends in part on the establishment of specific transcriptional programs of gene expression. These programs result from the interpretation of the genomic cis-regulatory information by sequence-specific factors. Decoding this information in sequenced genomes is an important issue. Here, we developed statistical analysis tools to computationally identify the cis-regulatory elements that control gene expression in a set of coregulated genes. Starting with a small number of validated and/or predicted cis-regulatory modules (CRMs) in a reference species as a training set, but with no a priori knowledge of the factors acting in trans, we computationally predicted transcription factor binding sites (TFBSs) and genomic CRMs underlying coregulation. This method was applied to the gene expression program active in Drosophila melanogaster sensory organ precursor cells (SOPs), a specific type of neural progenitor cells. Mutational analysis showed that four, including one newly characterized, out of the five top-ranked families of predicted TFBSs were required for SOP-specific gene expression. Additionaly, 19 out of the 29 top-ranked predicted CRMs directed gene expression in neural progenitor cells, i.e., SOPs or larval brain neuroblasts, with a notable fraction active in SOPs (11/29). We further identified the lola gene as the target of two SOP-specific CRMs and found that the lola gene contributed to SOP specification. The statistics and phylogeny-based tools described here can be more generally applied to identify the cis-regulatory elements of specific gene regulatory networks in any family of related species with sequenced genomes.

Metamotifs--a generative model for building families of nucleotide position weight matrices

Background

Development of high-throughput methods for measuring DNA interactions of transcription factors together with computational advances in short motif inference algorithms is expanding our understanding of transcription factor binding site motifs. The consequential growth of sequence motif data sets makes it important to systematically group and categorise regulatory motifs. It has been shown that there are familial tendencies in DNA sequence motifs that are predictive of the family of factors that binds them. Further development of methods that detect and describe familial motif trends has the potential to help in measuring the similarity of novel computational motif predictions to previously known data and sensitively detecting regulatory motifs similar to previously known ones from novel sequence.

Results

We propose a probabilistic model for position weight matrix (PWM) sequence motif families. The model, which we call the 'metamotif' describes recurring familial patterns in a set of motifs. The metamotif framework models variation within a family of sequence motifs. It allows for simultaneous estimation of a series of independent metamotifs from input position weight matrix (PWM) motif data and does not assume that all input motif columns contribute to a familial pattern. We describe an algorithm for inferring metamotifs from weight matrix data. We then demonstrate the use of the model in two practical tasks: in the Bayesian NestedMICA model inference algorithm as a PWM prior to enhance motif inference sensitivity, and in a motif classification task where motifs are labelled according to their interacting DNA binding domain.

Conclusions

We show that metamotifs can be used as PWM priors in the NestedMICA motif inference algorithm to dramatically increase the sensitivity to infer motifs. Metamotifs were also successfully applied to a motif classification problem where sequence motif features were used to predict the family of protein DNA binding domains that would interact with it. The metamotif based classifier is shown to compare favourably to previous related methods. The metamotif has great potential for further use in machine learning tasks related to especially de novo computational sequence motif inference. The metamotif methods presented have been incorporated into the NestedMICA suite.

Identification of E74-like factor 1 (ELF1) as a transcriptional regulator of the Hox cofactor MEIS1

OBJECTIVE

Myeloid ectropic viral integration site 1 (MEIS1) is a Hox cofactor known for its role in development and is strongly linked to normal and leukemic hematopoiesis. Although previous studies have focused on identifying protein partners of MEIS1 and its transcriptionally regulated targets, little is known about the upstream transcriptional regulators of this tightly regulated gene. Understanding the regulation of MEIS1 is important to understanding normal hematopoiesis and leukemogenesis.

MATERIALS AND METHODS

Here we describe our studies focusing on the evolutionary conserved putative MEIS1 promoter region. Phylogenetic sequence analysis and reporter assays in MEIS1-expressing (K562) and nonexpressing (HL60) leukemic cell line models were used to identify key regulatory regions and potential transcription factor binding sites within the candidate promoter region followed by functional and expression studies of one identified regulator in both cell lines and primary human cord blood and leukemia samples.

RESULTS

Chromatin status of MEIS1 promoter region is associated with MEIS1 expression. Truncation and mutation studies coupled with reporter assays revealed that a conserved ETS family member binding site located 289 bp upstream of the annotated human MEIS1 transcription start site is required for promoter activity. Of the three ETS family members tested, only ELF1 was enriched on the MEIS1 promoter as assessed by both electrophoretic mobility shift assay and chromatin immunoprecipitation experiments in K562. This finding was confirmed in MEIS1-expressing primary human samples. Moreover, small interfering RNA-mediated knockdown of ELF1 in K562 cells was associated with a decreased MEIS1 expression.

CONCLUSIONS

We conclude that the ETS transcription factor ELF1 is an important positive regulator of MEIS1 expression.

Genome-wide identification of human FOXP3 target genes in natural regulatory T cells

The transcription factor FOXP3 is essential for the formation and function of regulatory T cells (Tregs), and Tregs are essential for maintaining immune homeostasis and tolerance. This is demonstrated by a lethal autoimmune defect in mice lacking Foxp3 and in immunodysregulation polyendocrinopathy enteropathy X-linked syndrome patients. However, little is known about the molecular basis of human FOXP3 function or the relationship between direct and indirect targets of FOXP3 in human Tregs. To investigate this, we have performed a comprehensive genome-wide analysis for human FOXP3 target genes from cord blood Tregs using chromatin immunoprecipitation array profiling and expression profiling. We have identified 5579 human FOXP3 target genes and derived a core Treg gene signature conserved across species using mouse chromatin immunoprecipitation data sets. A total of 739 of the 5579 FOXP3 target genes were differentially regulated in Tregs compared with Th cells, thus allowing the identification of a number of pathways and biological functions overrepresented in Tregs. We have identified gene families including cell surface molecules and microRNAs that are differentially expressed in FOXP3(+) Tregs. In particular, we have identified a novel role for peptidase inhibitor 16, which is expressed on the cell surface of >80% of resting human CD25(+)FOXP3(+) Tregs, suggesting that in conjunction with CD25 peptidase inhibitor 16 may be a surrogate surface marker for Tregs with potential clinical application.

Transcriptional regulation of gene expression clusters in motor neurons following spinal cord injury

Background

Spinal cord injury leads to neurological dysfunctions affecting the motor, sensory as well as the autonomic systems. Increased excitability of motor neurons has been implicated in injury-induced spasticity, where the reappearance of self-sustained plateau potentials in the absence of modulatory inputs from the brain correlates with the development of spasticity.

Results

Here we examine the dynamic transcriptional response of motor neurons to spinal cord injury as it evolves over time to unravel common gene expression patterns and their underlying regulatory mechanisms. For this we use a rat-tail-model with complete spinal cord transection causing injury-induced spasticity, where gene expression profiles are obtained from labeled motor neurons extracted with laser microdissection 0, 2, 7, 21 and 60 days post injury. Consensus clustering identifies 12 gene clusters with distinct time expression profiles. Analysis of these gene clusters identifies early immunological/inflammatory and late developmental responses as well as a regulation of genes relating to neuron excitability that support the development of motor neuron hyper-excitability and the reappearance of plateau potentials in the late phase of the injury response. Transcription factor motif analysis identifies differentially expressed transcription factors involved in the regulation of each gene cluster, shaping the expression of the identified biological processes and their associated genes underlying the changes in motor neuron excitability.

Conclusions

This analysis provides important clues to the underlying mechanisms of transcriptional regulation responsible for the increased excitability observed in motor neurons in the late chronic phase of spinal cord injury suggesting alternative targets for treatment of spinal cord injury. Several transcription factors were identified as potential regulators of gene clusters containing elements related to motor neuron hyper-excitability, the manipulation of which potentially could be used to alter the transcriptional response to prevent the motor neurons from entering a state of hyper-excitability.

Proper differentiation of photoreceptors and amacrine cells depends on a regulatory loop between NeuroD and Six6

Timely generation of distinct neural cell types in appropriate numbers is fundamental for the generation of a functional retina. In vertebrates, the transcription factor Six6 is initially expressed in multipotent retina progenitors and then becomes restricted to differentiated retinal ganglion and amacrine cells. How Six6 expression in the retina is controlled and what are its precise functions are still unclear. To address this issue, we used bioinformatic searches and transgenic approaches in medaka fish (Oryzias latipes) to characterise highly conserved regulatory enhancers responsible for Six6 expression. One of the enhancers drove gene expression in the differentiating and adult retina. A search for transcription factor binding sites, together with luciferase, ChIP assays and gain-of-function studies, indicated that NeuroD, a bHLH transcription factor, directly binds an 'E-box' sequence present in this enhancer and specifically regulates Six6 expression in the retina. NeuroD-induced Six6 overexpression in medaka embryos promoted unorganized retinal progenitor proliferation and, most notably, impaired photoreceptor differentiation, with no apparent changes in other retinal cell types. Conversely, Six6 gain- and loss-of-function changed NeuroD expression levels and altered the expression of the photoreceptor differentiation marker Rhodopsin. In addition, knockdown of Six6 interfered with amacrine cell generation. Together, these results indicate that Six6 and NeuroD control the expression of each other and their functions coordinate amacrine cell generation and photoreceptor terminal differentiation.

Negative regulation of the oncogenic transcription factor FoxM1 by thiazolidinediones and mithramycin

The Forkhead Box transcription factor FoxM1 regulates expression of genes that promote cell cycle progression, and it plays essential roles in the development of liver, lung, prostate and colorectal tumors. Thiazolidinediones (TZDs) activate the peroxisome proliferator-activated receptor gamma (PPARγ), a ligand-activated nuclear receptor transcription factor. We found that treatment of the human hepatoma cell lines HepG2 and PLC/PRF/5 cells with TZDs leads to inhibition of FoxM1 gene expression. No PPARγ/retinoid X receptor (RXR) consensus DNA binding sites were detected in the FoxM1 promoter extending to -10 kb upstream, and knockdown of PPARγ had no impact on TZD mediated downregulation of FoxM1 expression. Previously, others showed that PPARγ agonists inhibit the expression and DNA-binding activity of the Sp1 transcription factor. Here we show that Sp1 binds to the FoxM1 promoter region and positively regulates FoxM1 transcription, while mithramycin, a chemotherapy drug that specifically binds GC rich sequences in the DNA and inhibits activities of Sp1, inhibits expression of FoxM1. Our data suggest that TZD mediated suppression of Sp1 is responsible for downregulation of FoxM1 gene expression. Inhibition of FoxM1 expression by TZDs provides a new mechanism for TZD mediated negative regulation of cancer cell growth. FoxM1 expression and activity in cancer cells can be targeted using PPARγ agonists or the anti-neoplastic antibiotic mithramycin.

Identification of conserved Drosophila-specific euchromatin-restricted non-coding sequence motifs

Non-protein-coding DNA comprises the majority of animal genomes but its functions are largely unknown. We identified over 17,000 different tetranucleotide pairs in the Drosophila melanogaster genome that are over-represented at distances up to 100nt in conserved non-exonic sequences. Those exhibiting the highest information content in surrounding nucleotides were classified into five groups: tRNAs, motifs associated with histone genes, Suppressor-of-Hairy-wing binding sites, and two sets of previously unrecognized motifs (DLM3 and DLM4). There are hundreds to thousands of copies of DLM3 and DLM4, respectively, in the genome, located almost exclusively in non-coding regions. They have similar copy numbers among drosophilids, but are largely absent in other insects. DLM3 is likely a cis-regulatory element, whereas DLM4 sequences are capable of forming a short hairpin structure and are expressed as approximately 80nt RNAs. This work reports the existence of Drosophila genus-specific sequence motifs, and suggests that many more novel functional elements may be discovered in genomes using the general approach outlined herein.

TFM-Explorer: mining cis-regulatory regions in genomes

DNA-binding transcription factors (TFs) play a central role in transcription regulation, and computational approaches that help in elucidating complex mechanisms governing this basic biological process are of great use. In this perspective, we present the TFM-Explorer web server that is a toolbox to identify putative TF binding sites within a set of upstream regulatory sequences of genes sharing some regulatory mechanisms. TFM-Explorer finds local regions showing overrepresentation of binding sites. Accepted organisms are human, mouse, rat, chicken and drosophila. The server employs a number of features to help users to analyze their data: visualization of selected binding sites on genomic sequences, and selection of cis-regulatory modules. TFM-Explorer is available at http://bioinfo.lifl.fr/TFM.

Genome-wide identification of new Wnt/beta-catenin target genes in the human genome using CART method

Background

The importance of in silico predictions for understanding cellular processes is now widely accepted, and a variety of algorithms useful for studying different biological features have been designed. In particular, the prediction of cis regulatory modules in non-coding human genome regions represents a major challenge for understanding gene regulation in several diseases. Recently, studies of the Wnt signaling pathway revealed a connection with neurodegenerative diseases such as Alzheimer's. In this article, we construct a classification tool that uses the transcription factor binding site motifs composition of some gene promoters to identify new Wnt/β-catenin pathway target genes potentially involved in brain diseases.

Results

In this study, we propose 89 new Wnt/β-catenin pathway target genes predicted in silico by using a method based on multiple Classification and Regression Tree (CART) analysis. We used as decision variables the presence of transcription factor binding site motifs in the upstream region of each gene. This prediction was validated by RT-qPCR in a sample of 9 genes. As expected, LEF1, a member of the T-cell factor/lymphoid enhancer-binding factor family (TCF/LEF1), was relevant for the classification algorithm and, remarkably, other factors related directly or indirectly to the inflammatory response and amyloidogenic processes also appeared to be relevant for the classification. Among the 89 new Wnt/β-catenin pathway targets, we found a group expressed in brain tissue that could be involved in diverse responses to neurodegenerative diseases, like Alzheimer's disease (AD). These genes represent new candidates to protect cells against amyloid β toxicity, in agreement with the proposed neuroprotective role of the Wnt signaling pathway.

Conclusions

Our multiple CART strategy proved to be an effective tool to identify new Wnt/β-catenin pathway targets based on the study of their regulatory regions in the human genome. In particular, several of these genes represent a new group of transcriptional dependent targets of the canonical Wnt pathway. The functions of these genes indicate that they are involved in pathophysiology related to Alzheimer's disease or other brain disorders.

Multiplexed massively parallel SELEX for characterization of human transcription factor binding specificities

The genetic code-the binding specificity of all transfer-RNAs--defines how protein primary structure is determined by DNA sequence. DNA also dictates when and where proteins are expressed, and this information is encoded in a pattern of specific sequence motifs that are recognized by transcription factors. However, the DNA-binding specificity is only known for a small fraction of the approximately 1400 human transcription factors (TFs). We describe here a high-throughput method for analyzing transcription factor binding specificity that is based on systematic evolution of ligands by exponential enrichment (SELEX) and massively parallel sequencing. The method is optimized for analysis of large numbers of TFs in parallel through the use of affinity-tagged proteins, barcoded selection oligonucleotides, and multiplexed sequencing. Data are analyzed by a new bioinformatic platform that uses the hundreds of thousands of sequencing reads obtained to control the quality of the experiments and to generate binding motifs for the TFs. The described technology allows higher throughput and identification of much longer binding profiles than current microarray-based methods. In addition, as our method is based on proteins expressed in mammalian cells, it can also be used to characterize DNA-binding preferences of full-length proteins or proteins requiring post-translational modifications. We validate the method by determining binding specificities of 14 different classes of TFs and by confirming the specificities for NFATC1 and RFX3 using ChIP-seq. Our results reveal unexpected dimeric modes of binding for several factors that were thought to preferentially bind DNA as monomers.

Genome-wide analysis of ETS-family DNA-binding in vitro and in vivo

Members of the large ETS family of transcription factors (TFs) have highly similar DNA-binding domains (DBDs)—yet they have diverse functions and activities in physiology and oncogenesis. Some differences in DNA-binding preferences within this family have been described, but they have not been analysed systematically, and their contributions to targeting remain largely uncharacterized. We report here the DNA-binding profiles for all human and mouse ETS factors, which we generated using two different methods: a high-throughput microwell-based TF DNA-binding specificity assay, and protein-binding microarrays (PBMs). Both approaches reveal that the ETS-binding profiles cluster into four distinct classes, and that all ETS factors linked to cancer, ERG, ETV1, ETV4 and FLI1, fall into just one of these classes. We identify amino-acid residues that are critical for the differences in specificity between all the classes, and confirm the specificities in vivo using chromatin immunoprecipitation followed by sequencing (ChIP-seq) for a member of each class. The results indicate that even relatively small differences in in vitro binding specificity of a TF contribute to site selectivity in vivo.

A data integration approach to mapping OCT4 gene regulatory networks operative in embryonic stem cells and embryonal carcinoma cells

It is essential to understand the network of transcription factors controlling self-renewal of human embryonic stem cells (ESCs) and human embryonal carcinoma cells (ECs) if we are to exploit these cells in regenerative medicine regimes. Correlating gene expression levels after RNAi-based ablation of OCT4 function with its downstream targets enables a better prediction of motif-specific driven expression modules pertinent for self-renewal and differentiation of embryonic stem cells and induced pluripotent stem cells.We initially identified putative direct downstream targets of OCT4 by employing CHIP-on-chip analysis. A comparison of three peak analysis programs revealed a refined list of OCT4 targets in the human EC cell line NCCIT, this list was then compared to previously published OCT4 CHIP-on-chip datasets derived from both ES and EC cells. We have verified an enriched POU-motif, discovered by a de novo approach, thus enabling us to define six distinct modules of OCT4 binding and regulation of its target genes.A selection of these targets has been validated, like NANOG, which harbours the evolutionarily conserved OCT4-SOX2 binding motif within its proximal promoter. Other validated targets, which do not harbour the classical HMG motif are USP44 and GADD45G, a key regulator of the cell cycle. Over-expression of GADD45G in NCCIT cells resulted in an enrichment and up-regulation of genes associated with the cell cycle (CDKN1B, CDKN1C, CDK6 and MAPK4) and developmental processes (BMP4, HAND1, EOMES, ID2, GATA4, GATA5, ISL1 and MSX1). A comparison of positively regulated OCT4 targets common to EC and ES cells identified genes such as NANOG, PHC1, USP44, SOX2, PHF17 and OCT4, thus further confirming their universal role in maintaining self-renewal in both cell types. Finally we have created a user-friendly database (http://biit.cs.ut.ee/escd/), integrating all OCT4 and stem cell related datasets in both human and mouse ES and EC cells.In the current era of systems biology driven research, we envisage that our integrated embryonic stem cell database will prove beneficial to the booming field of ES, iPS and cancer research.