Target Sites For Transcription Factors Research Articles

FMR1 expression in human granulosa cells and variable ovarian response: control by epigenetic mechanisms.

In humans, FMR1 (fragile X mental retardation 1) is strongly expressed in granulosa cells (GCs) of the female germline and apparently controls efficiency of folliculogenesis. Major control mechanism(s) of the gene transcription rate seem to be based on the rate of CpG-methylation along the CpG island promoter. Conducting CpG-methylation-specific bisulfite-treated PCR assays and subsequent sequence analyses of both gene alleles, revealed three variably methylated CpG domains (FMR1-VMR (variably methylated region) 1, -2, -3) and one completely unmethylated CpG-region (FMR1-UMR) in this extended FMR1-promoter-region. FMR1-UMR in the core promoter was exclusively present only in female GCs, suggesting expression from both gene alleles, i.e., escaping the female-specific X-inactivation mechanism for the second gene allele. Screening for putative target sites of transcription factors binding with CpG methylation dependence, we identified a target site for the transcriptional activator E2F1 in FMR1-VMR3. Using specific electrophoretic mobility shift assays, we found E2F1 binding efficiency to be dependent on CpG-site methylation in its target sequence. Comparative analysis of these CpGs revealed that CpG 94-methylation in primary GCs of women with normal and reduced efficiency of folliculogenesis statistically significant differences. We therefore conclude that E2F1 binding to FMR1-VMR3 in human GCs is part of an epigenetic mechanism regulating the efficiency of human folliculogenesis. Our data indicate that epigenetic mechanisms may control GC FMR1-expression rates.

SU20 - FUNCTIONAL LD CLUMP ENRICHMENT TEST (FLEET) DETECTS ENRICHMENT OF RISK LOCI FOR SCHIZOPHRENIA AND BIPOLAR DISORDER IN REGULATORY ELEMENTS AND PATHWAYS

Background Genome-Wide Association Studies (GWASs) provide a wealth of information that can serve as a backbone for making biological inferences. There are over 160 loci reported with genome-wide significant association with Schizophrenia (SZ) and Bipolar Disorder (BD), and thousands more nominally associated loci that contribute to risk (Purcell et al., 2009; Welter et al., 2014). SNPs with the strongest association to SZ and BD are predominately in non-coding DNA, thus it is often challenging to decipher the function of risk SNPs. Functional and regulatory maps from the ENCODE and Roadmap projects offer detailed annotations of the genome, which can help bridge the gap between GWAS signals and biological mechanisms. We present a new software tool called Functional LD-clump EnrichmEnt Test (FLEET) to decode the underlying biology of GWAS signals via overlaying information from the ENCODE and Roadmap Projects. Possible utilities of this software include: prioritizing risk genes for fine-mapping, illuminating potential regulatory mechanisms that underlie susceptibility, and identifying molecular substrates that are common to psychiatric disorders. Methods FLEET is available for download on Github (https://github.com/hessJ/FLEET). FLEET is currently adapted as a modular script written in R and is under active development. Users must supply a file of genome-wide association summary statistics and modify a few flags in FLEET to run the analysis properly. FLEET performs data reformatting, GWAS pruning, SNP-to-annotation mapping, statistical analyses (i.e., weighted linear regression and permutations), and plotting of results. Results GWAS results of SZ (Ripke et al., 2014) and BD (Hou et al., 2016) revealed widespread associations with histone markers and DNA accessibility in brain, immune and other peripheral tissues. In addition, significant enrichment was detected for gene sets that participate in neurotransmission and neurodevelopment, histone modification enzymes, and target sites of transcription factors, microRNAs, and RNA-binding proteins. Discussion Our software provides unique insight into the underlying biology of SZ and BD risk signals and a framework for hypothesis generation. FLEET is a flexible and efficient pipeline for analyzing biological relationships among GWASs of complex polygenic disorders. FLEET is capable of modeling genome-wide enrichment statistics and performing permutation tests on top GWAS markers; both tests include adjustments for confounding variation (i.e., LD and minor allele frequency). This software is included with a pre-formatted database of >5,800 annotations, and users can provide custom annotations for analysis.

Transcription factor target site search and gene regulation in a background of unspecific binding sites

Response time and transcription level are vital parameters of gene regulation. They depend on how fast transcription factors (TFs) find and how efficient they occupy their specific target sites. It is well known that target site search is accelerated by TF binding to and sliding along unspecific DNA and that unspecific associations alter the occupation frequency of a gene. However, whether target site search time and occupation frequency can be optimized simultaneously is mostly unclear. We developed a transparent and intuitively accessible state-based formalism to calculate search times to target sites on and occupation frequencies of promoters of arbitrary state structure. Our formalism is based on dissociation rate constants experimentally accessible in live cell experiments. To demonstrate our approach, we consider promoters activated by a single TF, by two coactivators or in the presence of a competitive inhibitor. We find that target site search time and promoter occupancy differentially vary with the unspecific dissociation rate constant. Both parameters can be harmonized by adjusting the specific dissociation rate constant of the TF. However, while measured DNA residence times of various eukaryotic TFs correspond to a fast search time, the occupation frequencies of target sites are generally low. Cells might tolerate low target site occupancies as they enable timely gene regulation in response to a changing environment.

Predicting Variation of DNA Shape Preferences in Protein-DNA Interaction in Cancer Cells with a New Biophysical Model.

DNA shape readout is an important mechanism of transcription factor target site recognition, in addition to the sequence readout. Several machine learning-based models of transcription factor–DNA interactions, considering DNA shape features, have been developed in recent years. Here, we present a new biophysical model of protein–DNA interactions by integrating the DNA shape properties. It is based on the neighbor dinucleotide dependency model BayesPI2, where new parameters are restricted to a subspace spanned by the dinucleotide form of DNA shape features. This allows a biophysical interpretation of the new parameters as a position-dependent preference towards specific DNA shape features. Using the new model, we explore the variation of DNA shape preferences in several transcription factors across various cancer cell lines and cellular conditions. The results reveal that there are DNA shape variations at FOXA1 (Forkhead Box Protein A1) binding sites in steroid-treated MCF7 cells. The new biophysical model is useful for elucidating the finer details of transcription factor–DNA interaction, as well as for predicting cancer mutation effects in the future.

Real-time imaging of Huntingtin aggregates diverting target search and gene transcription

The presumptive altered dynamics of transient molecular interactions in vivo contributing to neurodegenerative diseases have remained elusive. Here, using single-molecule localization microscopy, we show that disease-inducing Huntingtin (mHtt) protein fragments display three distinct dynamic states in living cells - 1) fast diffusion, 2) dynamic clustering and 3) stable aggregation. Large, stable aggregates of mHtt exclude chromatin and form 'sticky' decoy traps that impede target search processes of key regulators involved in neurological disorders. Functional domain mapping based on super-resolution imaging reveals an unexpected role of aromatic amino acids in promoting protein-mHtt aggregate interactions. Genome-wide expression analysis and numerical simulation experiments suggest mHtt aggregates reduce transcription factor target site sampling frequency and impair critical gene expression programs in striatal neurons. Together, our results provide insights into how mHtt dynamically forms aggregates and disrupts the finely-balanced gene control mechanisms in neuronal cells.

Landscape of expression profiles in esophageal carcinoma by The Cancer Genome Atlas data.

In this study, we explored the gene and microRNA (miRNA) expressions profile of esophageal carcinoma. The expression data for messenger RNAs and miRNAs in normal and cancerous esophageal tissues were obtained from the Cancer Genome Atlas database and then the differentially expressed genes and miRNAs were identified. As a result, we identified 2962 genes and 45 miRNAs differentially expressed in esophageal carcinoma compared with normal esophageal tissues. Subsequently, the altered gene functions and signaling pathways were investigated using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and these differentially expressed genes were significantly enriched in the cell cycle, cell migration, mitogen-activated protein kinase (MAPK) and toll-like receptor signaling pathway, and so on. Then the regulatory relationships between the differentially expressed miRNAs and genes were examined with Targetscan and Miranda, and the potential target sites of transcription factors (TFs) in the promoter regions of these miRNAs and genes were identified using the TRANSFAC database. Finally the TF-miRNA-gene network in esophageal cancer was established, summarizing the regulatory links among the TFs, differentially expressed miRNAs and differentially expressed genes. Factors such as core promoter-binding protein (CPBP), nuclear factor of activated T-cells 1 (NFAT-1), miR-30c-5p, were located in the central hub of this network, highlighting their vital roles in esophageal tumorigenesis. These findings may extend our understanding of the molecular mechanisms underlying esophageal carcinoma and promote new perspectives for prevention, diagnosis and treatment.

Integrated analysis of differentially expressed genes in breast cancer pathogenesis.

The present study aimed to detect the differences between breast cancer cells and normal breast cells, and investigate the potential pathogenetic mechanisms of breast cancer. The sample GSE9574 series was downloaded, and the microarray data was analyzed to identify differentially expressed genes (DEGs). Gene Ontology (GO) cluster analysis using the GO Enrichment Analysis Software Toolkit platform and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for DEGs was conducted using the Gene Set Analysis Toolkit V2. In addition, a protein-protein interaction (PPI) network was constructed, and target sites of potential transcription factors and potential microRNA (miRNA) molecules were screened. A total of 106 DEGs were identified in the current study. Based on these DEGs, a number of bio-pathways appear to be altered in breast cancer, including a number of signaling pathways and other disease-associated pathways, as indicated by KEGG pathway clustering analysis. ATF3, JUND, FOSB and JUNB were detected in the PPI network. Finally, the most significant potential target sites of transcription factors and miRNAs in breast cancer, which are important in the regulation of gene expression, were identified. The results indicated that miR-93, miR-302A, miR-302B, miR-302C, miR-302D, miR-372, miR-373, miR-520E and miR-520A were closely associated with the occurrence and development of breast cancer. Therefore, changes in the expression of these miRNAs may alter cell metabolism and trigger the development of breast cancer and its complications.

Analysis of gene profiles in glioma cells identifies potential genes, miRNAs, and target sites of migratory cells.

To explore the potential molecular mechanisms involved in migratory glioma cells. The gene expression profiles of GSE28167, employing human malignant glioma U251MG cells cultured on strictly aligned versus randomly oriented electrospun nanofibers of polycaprolactone, were downloaded from the Gene Expression Omnibus database. Gene differential expression analysis was carried out by the package of Gene Expression Omnibus query and limma in R language. The Gene Set Analysis Toolkit V2 was used for pathway analysis. Gene set enrichment analysis was used to screen for target sites of transcription factors, miRNA and small drug molecules. Totally 586 differentially expressed genes were identified and the differentially expressed genes were mainly enriched in the pathway of muscle cell TarBase, MAPK cascade, adipogenesis and epithelium TarBase. Thirty-two significant target sites of transcription factors, such as hsa_RTAAACA_V$FREAC2_01, were screened. The top 20 potential miRNAs including MIR-124A, MIR-34A and MIR-34C were screened for a constructing gene-miRNA interaction network. Small molecules that can inhibit the motility of glioma cells such as diclofenamide and valinomycin were mined. By integrating the regulatory relationships among transcription factors, miRNAs and differentially expressed genes, we found that 7 differentially expressed genes, including SOX4, ANKRD28 and CCND1, might play crucial roles in the migration of glioma cells. The screened migration-associated genes, significant pathways, and small molecules give us new insight for the mechanism of migratory glioma cells. Interest in such genes as potential target genes in the treatment of glioblastoma justifies functional validation studies.

Identification of genes in HepG2 cells that respond to DNA methylation and histone deacetylation inhibitor treatment.

Previous studies have demonstrated that epigenetics has an important role in the regulation of gene expression in cancer. Epigenetics is the study of reversible, heritable changes in gene function, which occur independently from changes in the DNA sequence. DNA methylation and histone deacetylation are the two most important epigenetic modifications. DNA methylation was one of the first discovered epigenetic modifications and it may lead to changes in chromatin structure, DNA conformation and DNA stability, thereby controlling gene expression. Sample data on the HepG2 cell line from the Gene Expression Omnibus database under GSE5230 accession number were obtained and GEOquery and the limma package were then used to analyze the data and identify differentially expressed genes using Gene Otology. This was conducted in order to investigate the effect on gene expression of inhibiting DNA methylation and histone deacetylation, and to explore the potential role of epigenetics in the development and treatment of hepatic carcinoma. It was found that inhibition of DNA methylation and histone deacetylation affected not only substance metabolism, but also the immune activity in HepG2 cells. Furthermore, common target sites for transcription factors were identified in the differentially expressed genes. It may be concluded that the inhibition of DNA methylation and histone deacetylation contributes to the treatment of hepatic carcinoma and may provide a novel therapeutic strategy for the treatment of hepatic cancer.

Increased expression of c-Jun in nonalcoholic fatty liver disease

Overnutrition is the major cause of nonalcoholic fatty liver disease (NAFLD) and its advanced form nonalcoholic steatohepatitis (NASH). We aimed to develop and characterize a murine model, which resembles both the pathology and nutritional situation, of NASH patients in Western societies. Mice were fed with a NASH-inducing diet (ND) containing sucrose, cholesterol and fats rich in saturated fatty acids in a composition, which mimics Western food. After 12 weeks, ND-fed mice revealed obesity and impaired glucose tolerance. In the liver, ND-feeding led to marked steatosis, hepatocellular damage, inflammation and beginning fibrosis. Transcriptome-wide gene expression analysis and search for over-represented transcription factor target sites among the differentially expressed genes identified activator protein-1 (AP-1) as the most likely factor to cause the transcriptional changes in ND livers. Combining differentially expressed gene and protein–protein interaction network analysis identified c-Jun as hub in the largest connected deregulated sub-network in ND livers. Accordingly, ND livers revealed c-Jun-phosphorylation and nuclear translocation. Moreover, hepatic c-Jun expression was enhanced in ND-fed mice. Combined tissue microarray technology and immunohistochemical analysis confirmed enhanced hepatic c-Jun levels in NAFLD patients, which correlated with inflammation, and notably, with the degree of hepatic steatosis. In summary, our new mouse model shows important pathological changes also found in human NASH and indicates c-Jun/AP-1 activation as critical regulator of hepatic alterations. Abundance of c-Jun in NAFLD likely facilitates development and progression of NASH.

Increased expression of c-jun in nonalcoholic fatty liver disease

The lack of animal models which closely mimic the human situation is one main reason why the molecular mechanisms causing progression from nonalcoholic fatty liver to (NASH) still are elusive. In addition to the quantity of consumed calories, certain dietary components, namely saturated fatty acids, fructose, and cholesterol are increasingly recognized as dietary factors affecting NAFLD progression. The aim of this study was to developed and characterize a NASH inducing diet (ND) containing these nutrients in a composition which mimics Western food. Methods and Results: Feeding ND to male C57Bl6/N mice for 12 weeks induced significant body weight gain, an impaired glucose tolerance and elevated fasting blood glucose levels as well as decreased adiponectin and increased leptin serum levels. Furthermore, ND-feeding led to marked hepatic steatosis and distinct signs of hepatic oxidative stress and lipid peroxidation. In line with this, ND-fed mice exhibited more apoptotic hepatocytes and elevated transaminase serum levels as well as hepatic inflammation, activation of hepatic stellate cells, and beginning fibrosis, as assessed by histology and hydroxyprolin analysis. Transcriptome-wide gene expression analysis and classification in Gene Ontology categories revealed main alterations in the categories „lipid metabolic process”, “innate immune response” and “inflammatory response“ in the liver of HD-fed mice, which closely resembled NASH patients. Search for over-represented transcription factor target sites among the differenzially expressed genes identified AP-1 as the most likely factor to cause the transcriptional changes. Interestingly, protein-protein interaction network analysis identified c-JUN (a component if the AP-1 complex) as hub. Westernblot and immunohistochemical analysis confirmed c-jun-phosphorylation and nuclear translocation in murine ND-livers as well as NASH patients. Unexpectedly, also expression of (unphosphorylated) c-jun was significantly enhanced not only in NASH, but also in fatty liver without inflammation. Immunohistochemical analysis of a tissue micro array containing 80 human NAFLD tissues revealed a significant correlation between c-jun expression and the extent of hepatic steatosis. Conclusions: Our novel murine NASH-model induces important pathomechanisms also found in human NASH and led to the identification of increased c-jun already in simple steatosis. It is likely that higher abundance of this crucial pro-inflammatory regulator facilitates NASH upon additional stimuli. The identification of the latter as well as c-jun itself appear as attractive prognostic and therapeutic targets of NAFLD progression.

Genomic Analysis Reveals a Novel Nuclear Factor-κB (NF-κB)-binding Site in Alu-repetitive Elements

The transcription factor NF-κB is a critical regulator of immune responses. To determine how NF-κB builds transcriptional control networks, we need to obtain a topographic map of the factor bound to the genome and correlate it with global gene expression. We used a ChIP cloning technique and identified novel NF-κB target genes in response to virus infection. We discovered that most of the NF-κB-bound genomic sites deviate from the consensus and are located away from conventional promoter regions. Remarkably, we identified a novel abundant NF-κB-binding site residing in specialized Alu-repetitive elements having the potential for long range transcription regulation, thus suggesting that in addition to its known role, NF-κB has a primate-specific function and a role in human evolution. By combining these data with global gene expression profiling of virus-infected cells, we found that most of the sites bound by NF-κB in the human genome do not correlate with changes in gene expression of the nearby genes and they do not appear to function in the context of synthetic promoters. These results demonstrate that repetitive elements interspersed in the human genome function as common target sites for transcription factors and may play an important role in expanding the repertoire of binding sites to engage new genes into regulatory networks.

Flexibility of transcription factor target site position in conserved cis-regulatory modules

Eight Strongylocentrotus purpuratus cis-regulatory modules, in each of which up to three different transcription factor target sites had been previously authenticated in gene transfer and mutagenesis studies, were compared to the orthologous modules in the genome of Lytechinus variegatus. These species diverged about 50 million years ago. The orthologous modules were identified in sequenced Lytechinus BACs, as conserved sequence patches in similar regions of the respective genes. The similar functionality of several of these control modules in the two species was confirmed by cross-species gene transfer experiments. In each case the repertoire of transcription factor target sites was the same in the orthologous modules, but the positions of the individual sites with respect to one another was evolutionarily flexible, even though the intervening sequence was often strongly conserved. The most invariably conserved features, as seen also in other systems, were pairs of target sites that are immediately adjacent to one another. Their conservation is probably due to the necessity for interaction of proximally bound transcription factors, while a facilitated form of sequence conversion might be the mechanism of site position change.

An Integrated Approach to Identifying Cis-Regulatory Modules in the Human Genome

In eukaryotic genomes, it is challenging to accurately determine target sites of transcription factors (TFs) by only using sequence information. Previous efforts were made to tackle this task by considering the fact that TF binding sites tend to be more conserved than other functional sites and the binding sites of several TFs are often clustered. Recently, ChIP-chip and ChIP-sequencing experiments have been accumulated to identify TF binding sites as well as survey the chromatin modification patterns at the regulatory elements such as promoters and enhancers. We propose here a hidden Markov model (HMM) to incorporate sequence motif information, TF-DNA interaction data and chromatin modification patterns to precisely identify cis-regulatory modules (CRMs). We conducted ChIP-chip experiments on four TFs, CREB, E2F1, MAX, and YY1 in 1% of the human genome. We then trained a hidden Markov model (HMM) to identify the labels of the CRMs by incorporating the sequence motifs recognized by these TFs and the ChIP-chip ratio. Chromatin modification data was used to predict the functional sites and to further remove false positives. Cross-validation showed that our integrated HMM had a performance superior to other existing methods on predicting CRMs. Incorporating histone signature information successfully penalized false prediction and improved the whole performance. The dataset we used and the software are available at http://nash.ucsd.edu/CIS/.

ChIPping away at gene regulation

The coordinated regulation of gene expression in higher eukaryotes is complex and poorly understood. Recent technological advances have allowed the first insights into these networks on a genome-wide scale. These investigations have identified transcription factor target sites in the genome and successfully predicted cooperative interactions with other factors. However, a detailed understanding of the processes that coordinate gene expression remains elusive. Here, we highlight the advances that have been made using current methods, and the need for new technologies to address the gaps in our knowledge and to map these complex pathways further.

DASS: efficient discovery andp-value calculation of substructures in unordered data

Pattern identification in biological sequence data is one of the main objectives of bioinformatics research. However, few methods are available for detecting patterns (substructures) in unordered datasets. Data mining algorithms mainly developed outside the realm of bioinformatics have been adapted for that purpose, but typically do not determine the statistical significance of the identified patterns. Moreover, these algorithms do not exploit the often modular structure of biological data. We present the algorithm DASS (Discovery of All Significant Substructures) that first identifies all substructures in unordered data (DASS(Sub)) in a manner that is especially efficient for modular data. In addition, DASS calculates the statistical significance of the identified substructures, for sets with at most one element of each type (DASS(P(set))), or for sets with multiple occurrence of elements (DASS(P(mset))). The power and versatility of DASS is demonstrated by four examples: combinations of protein domains in multi-domain proteins, combinations of proteins in protein complexes (protein subcomplexes), combinations of transcription factor target sites in promoter regions and evolutionarily conserved protein interaction subnetworks. The program code and additional data are available at http://www.fli-leibniz.de/tsb/DASS

An evolutionary constraint: Strongly disfavored class of change in DNA sequence during divergence of cis-regulatory modules

The DNA of functional cis-regulatory modules displays extensive sequence conservation in comparisons of genomes from modestly distant species. Patches of sequence that are several hundred base pairs in length within these modules are often seen to be 80-95% identical, although the flanking sequence cannot even be aligned. However, it is unlikely that base pairs located between the transcription factor target sites of cis-regulatory modules have sequence-dependent function, and the mechanism that constrains evolutionary change within cis-regulatory modules is incompletely understood. We chose five functionally characterized cis-regulatory modules from the Strongylocentrotus purpuratus (sea urchin) genome and obtained orthologous regulatory and flanking sequences from a bacterial artificial chromosome genome library of a congener, Strongylocentrotus franciscanus. As expected, single-nucleotide substitutions and small indels occur freely at many positions within the regulatory modules of these two species, as they do outside the regulatory modules. However, large indels (>20 bp) are statistically almost absent within the regulatory modules, although they are common in flanking intergenic or intronic sequence. The result helps to explain the patterns of evolutionary sequence divergence characteristic of cis-regulatory DNA.

Identification of Cyclin D3 as a Direct Transcriptional Target of E2A Using Damid.

The transcription factor E2A is required for very early B cell development. The exact mechanism by which E2A promotes B cell development is unclear and cannot be explained by the known E2A targets, components of the pre-B cell receptor and cyclin dependent kinase inhibitors, indicating additional pathways and targets remain to be identified. We had previously reported that E2A can promote precursor B cell expansion, promote G1 cell cycle progression, and induce the expressions of multiple G1 phase cyclins including cyclin D3, suggesting that E2A induction of these genes may contribute to early B cell development. To better understand the mechanism by which E2A induces these cyclins, we characterized the relationship between E2A and the cyclin D3 gene promoter. E2A transactivated a luciferase reporter plasmid containing the 1kb promoter of cyclin D3 that contains two consensus E2A binding sites (E-boxes); however, deletion of the E-boxes did not disrupt the transactivation by E2A. We hypothesized three possible mechanisms: 1) indirect activation of cyclin D3 via another transcription factor, 2) binding of E2A to cryptic non-E-boxes, or 3) recruitment of E2A to the promoter via interaction with other DNA binding factor. To test the first possibility, promoter occupancy was examined using the DamID approach. In this approach, a fusion protein consisting of E. coli DNA adenosine methyltransferase (DAM) and a transcription factor of interest is expressed at low levels, resulting in specific methylation of adenosine residues within 2–5 kb of the transcription factor target sites. A fusion construct composed of E2A and DAM (E47Dam), was subcloned in lentiviral vectors, and used to transduce precursor B cell lines. The methylated adenosine residues were detected using a sensitive ligation-mediated PCR (LM-PCR) assay that required only 1 ug of genomic DNA and can detect methylation even if only 3% of the cells express E47Dam; no methylated adenosines were detected in control cells, indicating that all methylated residues resulted from E47Dam. Specific adenosine methylation was identified at the IgH intronic enhancer, a known E2A target site, but not at the non-target sites, CD19, HPRT, and GAPDH promoters. Specific methylation was detected at the cyclin D3 promoter but not 10 kb down-stream, despite similar concentrations of E-boxes at both sites. Chromatin immunoprecipitation analysis confirmed the DamID findings and further localized the binding to within 1 kb of the two E-boxes in the cyclin D3 promoter. To distinguish between the two remaining mechanisms (cryptic non-E-boxes versus recruitment via other DNA binding factors), two point mutations were introduced into E47Dam that disrupted its DNA binding activity. The mutated E47Dam continued to methylate at the cyclin D3 promoter. We conclude that E2A can be recruited to the cyclin D3 promoter, independent of E-boxes or E2A DNA binding activity. Our findings raise the possibility that some direct E2A target genes may lack functional E-boxes. Furthermore, mutated E2A, lacking an E2A DNA binding domain, that is seen in 6% of pediatric ALLs may still activate a subset of E2A target genes. Finally, our application of lentiviral vectors and LM-PCR to the DamID approach should permit analysis of primary human precursor B cells, despite the limitations in cell number and transduction efficiency.

Transcription factor decoy (TFD) in breast cancer research and treatment.

Synthetic oligonucleotides have recently been the object of many investigations aimed to develop sequence-selective compounds able to modulate, either positively or negatively, transcription of eukaryotic and viral genes. Alteration of transcription could be obtained by using synthetic oligonucleotides mimicking target sites of transcription factors (the transcription factor decoy -TFD- approach). This could lead to either inhibition or activation of gene expression, depending on the biological functions of the target transcription factors. Since several transcription factors are involved in tumor onset and progression, this issue is of great interest in order to design anti-tumor compounds. In addition to oligonucleotides, peptide nucleic acids (PNA) can be proposed for the modulation of gene expression. In this respect, double-stranded PNA-DNA chimeras have been shown to be capable to exhibit strong decoy activity. In the case of treatment of breast cancer cells, decoy oligonucleotides mimicking CRE binding sites, promoter region of estrogen receptor alpha gene, NF-kB binding sites have been used with promising results. Therefore, the transcription factor decoy approach could be object of further studies to develop protocols for the treatment of breast cancer. In the future, transcription factors regulating cell cycle, hormone-dependent differentiation, tumor invasion and metastasis are expected to be suitable targets for transcription factor decoy.

Transcript analysis of 1003 novel yeast genes using high-throughput northern hybridizations.

The expression of 1008 open reading frames (ORFs) from the yeast Saccharomyces cerevisiae has been examined under eight different physiological conditions, using classical northern analysis. These northern data have been compared with publicly available data from a microarray analysis of the diauxic transition in S.cerevisiae. The results demonstrate the importance of comparing biologically equivalent situations and of the standardization of data normalization procedures. We have also used our northern data to identify co-regulated gene clusters and define the putative target sites of transcriptional activators responsible for their control. Clusters containing genes of known function identify target sites of known activators. In contrast, clusters comprised solely of genes of unknown function usually define novel putative target sites. Finally, we have examined possible global controls on gene expression. It was discovered that ORFs that are highly expressed following a nutritional upshift tend to employ favoured codons, whereas those overexpressed in starvation conditions do not. These results are interpreted in terms of a model in which competition between mRNA molecules for translational capacity selects for codons translated by abundant tRNAs.