Analyses of non-coding somatic drivers in 2,658 cancer whole genomes.

The discovery of drivers of cancer has traditionally focused on protein-coding genes1-4. Here we present analyses of driver point mutations and structural variants in non-coding regions across 2,658 genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium5 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). For point mutations, we developed a statistically rigorous strategy for combining significance levels from multiple methods of driver discovery that overcomes the limitations of individual methods. For structural variants, we present two methods of driver discovery, and identify regions that are significantly affected by recurrent breakpoints and recurrent somatic juxtapositions. Our analyses confirm previously reported drivers6,7, raise doubts about others and identify novel candidates, including point mutations in the 5' region of TP53, in the 3' untranslated regions of NFKBIZ and TOB1, focal deletions in BRD4 and rearrangements in the loci of AKR1C genes. We show that although point mutations and structural variants that drive cancer are less frequent in non-coding genes and regulatory sequences than in protein-coding genes, additional examples of these drivers will be found as more cancer genomes become available.

Interleukin-15 response signature predicts RhCMV/SIV vaccine efficacy.

Simian immunodeficiency virus (SIV) challenge of rhesus macaques (RMs) vaccinated with strain 68-1 Rhesus Cytomegalovirus (RhCMV) vectors expressing SIV proteins (RhCMV/SIV) results in a binary outcome: stringent control and subsequent clearance of highly pathogenic SIV in ~55% of vaccinated RMs with no protection in the remaining 45%. Although previous work indicates that unconventionally restricted, SIV-specific, effector-memory (EM)-biased CD8+ T cell responses are necessary for efficacy, the magnitude of these responses does not predict efficacy, and the basis of protection vs. non-protection in 68-1 RhCMV/SIV vector-vaccinated RMs has not been elucidated. Here, we report that 68-1 RhCMV/SIV vector administration strikingly alters the whole blood transcriptome of vaccinated RMs, with the sustained induction of specific immune-related pathways, including immune cell, toll-like receptor (TLR), inflammasome/cell death, and interleukin-15 (IL-15) signaling, significantly correlating with subsequent vaccine efficacy. Treatment of a separate RM cohort with IL-15 confirmed the central involvement of this cytokine in the protection signature, linking the major innate and adaptive immune gene expression networks that correlate with RhCMV/SIV vaccine efficacy. This change-from-baseline IL-15 response signature was also demonstrated to significantly correlate with vaccine efficacy in an independent validation cohort of vaccinated and challenged RMs. The differential IL-15 gene set response to vaccination strongly correlated with the pre-vaccination activity of this pathway, with reduced baseline expression of IL-15 response genes significantly correlating with higher vaccine-induced induction of IL-15 signaling and subsequent vaccine protection, suggesting that a robust de novo vaccine-induced IL-15 signaling response is needed to program vaccine efficacy. Thus, the RhCMV/SIV vaccine imparts a coordinated and persistent induction of innate and adaptive immune pathways featuring IL-15, a known regulator of CD8+ T cell function, that support the ability of vaccine-elicited unconventionally restricted CD8+ T cells to mediate protection against SIV challenge.

MindReader: Unsupervised Classification of Electroencephalographic Data.

Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process. Automatic detection offers the potential to improve the quality of patient care by shortening the time to diagnosis, managing big data and optimizing the allocation of human resources towards precision medicine. Here, we present MindReader, a novel unsupervised machine-learning method comprised of the interplay between an autoencoder network, a hidden Markov model (HMM), and a generative component: after dividing the signal into overlapping frames and performing a fast Fourier transform, MindReader trains an autoencoder neural network for dimensionality reduction and compact representation of different frequency patterns for each frame. Next, we processed the temporal patterns using a HMM, while a third and generative component hypothesized and characterized the different phases that were then fed back to the HMM. MindReader then automatically generates labels that the physician can interpret as pathological and non-pathological phases, thus effectively reducing the search space for trained personnel. We evaluated MindReader's predictive performance on 686 recordings, encompassing more than 980 h from the publicly available Physionet database. Compared to manual annotations, MindReader identified 197 of 198 epileptic events (99.45%), and is, as such, a highly sensitive method, which is a prerequisite for clinical use.

Nucleolar rDNA folds into condensed foci with a specific combination of epigenetic marks.

Arabidopsis thaliana 45S ribosomal genes (rDNA) are located in tandem arrays called nucleolus organizing regions on the termini of chromosomes 2 and 4 (NOR2 and NOR4) and encode rRNA, a crucial structural element of the ribosome. The current model of rDNA organization suggests that inactive rRNA genes accumulate in the condensed chromocenters in the nucleus and at the nucleolar periphery, while the nucleolus delineates active genes. We challenge the perspective that all intranucleolar rDNA is active by showing that a subset of nucleolar rDNA assembles into condensed foci marked by H3.1 and H3.3 histones that also contain the repressive H3K9me2 histone mark. By using plant lines containing a low number of rDNA copies, we further found that the condensed foci relate to the folding of rDNA, which appears to be a common mechanism of rDNA regulation inside the nucleolus. The H3K9me2 histone mark found in condensed foci represents a typical modification of bulk inactive rDNA, as we show by genome-wide approaches, similar to the H2A.W histone variant. The euchromatin histone marks H3K27me3 and H3K4me3, in contrast, do not colocalize with nucleolar foci and their overall levels in the nucleolus are very low. We further demonstrate that the rDNA promoter is an important regulatory region of the rDNA, where the distribution of histone variants and histone modifications are modulated in response to rDNA activity.

R.ROSETTA: an interpretable machine learning framework.

BACKGROUND: Machine learning involves strategies and algorithms that may assist bioinformatics analyses in terms of data mining and knowledge discovery. In several applications, viz. in Life Sciences, it is often more important to understand how a prediction was obtained rather than knowing what prediction was made. To this end so-called interpretable machine learning has been recently advocated. In this study, we implemented an interpretable machine learning package based on the rough set theory. An important aim of our work was provision of statistical properties of the models and their components. RESULTS: We present the R.ROSETTA package, which is an R wrapper of ROSETTA framework. The original ROSETTA functions have been improved and adapted to the R programming environment. The package allows for building and analyzing non-linear interpretable machine learning models. R.ROSETTA gathers combinatorial statistics via rule-based modelling for accessible and transparent results, well-suited for adoption within the greater scientific community. The package also provides statistics and visualization tools that facilitate minimization of analysis bias and noise. The R.ROSETTA package is freely available at https://github.com/komorowskilab/R.ROSETTA . To illustrate the usage of the package, we applied it to a transcriptome dataset from an autism case-control study. Our tool provided hypotheses for potential co-predictive mechanisms among features that discerned phenotype classes. These co-predictors represented neurodevelopmental and autism-related genes. CONCLUSIONS: R.ROSETTA provides new insights for interpretable machine learning analyses and knowledge-based systems. We demonstrated that our package facilitated detection of dependencies for autism-related genes. Although the sample application of R.ROSETTA illustrates transcriptome data analysis, the package can be used to analyze any data organized in decision tables.

Studies of liver tissue identify functional gene regulatory elements associated to gene expression, type 2 diabetes, and other metabolic diseases.

BACKGROUND: Genome-wide association studies (GWAS) of diseases and traits have found associations to gene regions but not the functional SNP or the gene mediating the effect. Difference in gene regulatory signals can be detected using chromatin immunoprecipitation and next-gen sequencing (ChIP-seq) of transcription factors or histone modifications by aligning reads to known polymorphisms in individual genomes. The aim was to identify such regulatory elements in the human liver to understand the genetics behind type 2 diabetes and metabolic diseases. METHODS: The genome of liver tissue was sequenced using 10X Genomics technology to call polymorphic positions. Using ChIP-seq for two histone modifications, H3K4me3 and H3K27ac, and the transcription factor CTCF, and our established bioinformatics pipeline, we detected sites with significant difference in signal between the alleles. RESULTS: We detected 2329 allele-specific SNPs (AS-SNPs) including 25 associated to GWAS SNPs linked to liver biology, e.g., 4 AS-SNPs at two type 2 diabetes loci. Two hundred ninety-two AS-SNPs were associated to liver gene expression in GTEx, and 134 AS-SNPs were located on 166 candidate functional motifs and most of them in EGR1-binding sites. CONCLUSIONS: This study provides a valuable collection of candidate liver regulatory elements for further experimental validation.

Alteration in the serum concentrations of FGF19, FGFR4 and ßKlotho in patients with thyroid cancer.

INTRODUCTION: ßKlotho (ßKL) is known to act as co-receptor for fibroblast growth factor receptor 4 (FGFR4) which is the main cognate receptor for fibroblast growth factor 19 (FGF19). Dysregulation of this FGF19/FGFR4/ßKL signaling axis has been implicated in the pathogenesis of several cancers. However, its role in the pathogenesis of thyroid cancer has not been determined. MATERIALS AND METHODS: The aim of this study was to assess FGF19, FGFR4 and ßKL concentrations in a group of 36 patients with papillary thyroid cancer (PTC), 11 patients with follicular thyroid cancer (FTC), 9 patients with anaplastic thyroid cancer (ATC) and a group of 19 subjects with multinodular nontoxic goiter (MNG). The control group consisted of 20 healthy volunteers. Serum FGF19, FGFR4 and ßKL concentrations were measured using specific ELISA methods. RESULTS: Significantly lower concentrations of ßKL and higher concentrations of FGF19 were found in patients with PTC, FTC and ATC as compared with MNG group and controls. An elevation of FGFR4 serum concentration was observed in all thyroid cancer groups in comparison to MNG group and controls; however, in FTC group it was statistically insignificant. A positive correlation was found between ßKL and FGFR4 concentrations in PTC patients. The levels of ßKL, FGF19 and FGFR4 did not differ significantly between MNG group and healthy controls. CONCLUSIONS: Our results indicate that a disrupted FGF19/FGFR4/ßKL signaling pathway may play a role in the development of thyroid cancers. However, further studies are needed to elucidate the molecular mechanism of the neoplastic transition of thyroid epithelial cells.

Maps of context-dependent putative regulatory regions and genomic signal interactions.

Gene transcription is regulated mainly by transcription factors (TFs). ENCODE and Roadmap Epigenomics provide global binding profiles of TFs, which can be used to identify regulatory regions. To this end we implemented a method to systematically construct cell-type and species-specific maps of regulatory regions and TF-TF interactions. We illustrated the approach by developing maps for five human cell-lines and two other species. We detected ∼144k putative regulatory regions among the human cell-lines, with the majority of them being ∼300 bp. We found ∼20k putative regulatory elements in the ENCODE heterochromatic domains suggesting a large regulatory potential in the regions presumed transcriptionally silent. Among the most significant TF interactions identified in the heterochromatic regions were CTCF and the cohesin complex, which is in agreement with previous reports. Finally, we investigated the enrichment of the obtained putative regulatory regions in the 3D chromatin domains. More than 90% of the regions were discovered in the 3D contacting domains. We found a significant enrichment of GWAS SNPs in the putative regulatory regions. These significant enrichments provide evidence that the regulatory regions play a crucial role in the genomic structural stability. Additionally, we generated maps of putative regulatory regions for prostate and colorectal cancer human cell-lines.

Estimation of vitamin D status in patients with secondary and primary hypothyroidism of different etiology.

BACKGROUND: Though vitamin D deficiency is a global problem with wide spectrum of severe public health consequences, inadequate vitamin D status still remains one of the most common and untreated medical conditions. Thyroid diseases, including hypothyroidism, also represent the most frequent endocrinopathies in general population. OBJECTIVES: To determine the vitamin D status in hypothyroid patients and to ascertain the status of thyroid hormone replacement. METHODS: The 25(OH)D concentrations (ECLIA) in 71 hypothyroid patients recruited in the Outpatient Clinic of Endocrinology or Department of Clinical Endocrinology were assessed. The examined group was composed of 59 subjects diagnosed with primary hypothyroidism of different etiology and 12 patients with secondary hypothyroidism. The control group included 16 healthy individuals. RESULTS: Mean serum 25(OH)D concentration in healthy volunteers was significantly lower than in hypothyroid subjects (13.09±1.63 vs. 19.92±1.37 ng/mL). Patients with a history of thyroidectomy presented with significantly higher mean 25(OH)D concentration than controls (23.25±2.75 vs. 13.09±1.63 ng/mL). Mean serum 25(OH)D concentration in effectively treated hypothyroidism was significantly higher than in controls (21.90±1.47 vs. 13.09±1.63 ng/mL) or undertreated hypothyroidism (21.90±1.47 vs. 13.52±3.39 ng/mL). Hypothyroid patients aged under 60 years presented with significantly lower mean 25(OH)D concentration than elders (16.46±1.54 vs. 24.39±1.18 ng/mL). The major 25(OH)D deficient (≤10 ng/mL) or deficient (≤20 ng/mL) hypothyroid patients were significantly younger than those with 25(OH)D concentrations exceeding 10 ng/mL or 20 ng/mL respectively. CONCLUSIONS: These findings confirm the necessity for vitamin D status improvement in the general population and more effective healthcare of hypothyroid patients.

[Quality of life in patients with orbitopathy - single center experience]. / Jakosc zycia chorych z orbitopatia tarczycowa.

Thyroid-associated orbitopathy is a syndrome of eye symptoms produced by immunological inflammation of soft tissues of orbit,mostly due to Graves-Basedow disease. This disease is accompanied by proptosis, oedema of lids, double vision, tearing and photophobia. These symptoms lead to significant deterioration of quality of life due to reduction of sharpness of sight and therefore worsen emotional condition of patients. AIM: The aim of study was to assess the impact of Graves orbitopathy on quality of life. Additional aim was assessement of deppression among the subjects. MATERIALS AND METHODS: Study in form of anonymous modified questionnaire EUGOGO grading quality of life of patients with thyroidassociated orbitopathy and the scale of depression by Beck - carried out directly among 30 patients of Clinic od Endocrinology of the Medical Univeristy of Lódz (22 female and 8 male) from November 2011 to April 2012. RESULTS: Patients with thyroid-associated orbitopathy have considerably reduced quality of life - carried out qestionnaires showed they have problems with everyday activity like: riding bicycle (17 patients - 57%), driving car (14 patients - 45%), moving in apartment and outside (9 patients - 30%), watching TV (21 patients - 17%) and reading books (25 patients - 83%). Furthermore, many patients with thyroidassociated orbitopathy have serious emotional disorders - 20 persons have symptoms of depression. CONCLUSIONS: Graves orbitopathy have negative influence on quality of life. Orbitopathy worsens self-evaluation of patients, their interpersonal contacts, making new acquaintances, working and finding new job. Furthermore, many patients with thyroid-associated orbitopathy have serious emotional disorders. It seems reasonable to include psychotherapist in the therapeutic process.

PiiL: visualization of DNA methylation and gene expression data in gene pathways.

BACKGROUND: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels. RESULTS: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas. CONCLUSION: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways. PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git .

Risk stratification in cervical cancer screening by complete screening history: Applying bioinformatics to a general screening population.

Women screened for cervical cancer in Sweden are currently treated under a one-size-fits-all programme, which has been successful in reducing the incidence of cervical cancer but does not use all of the participants' available medical information. This study aimed to use women's complete cervical screening histories to identify diagnostic patterns that may indicate an increased risk of developing cervical cancer. A nationwide case-control study was performed where cervical cancer screening data from 125,476 women with a maximum follow-up of 10 years were evaluated for patterns of SNOMED diagnoses. The cancer development risk was estimated for a number of different screening history patterns and expressed as Odds Ratios (OR), with a history of 4 benign cervical tests as reference, using logistic regression. The overall performance of the model was moderate (64% accuracy, 71% area under curve) with 61-62% of the study population showing no specific patterns associated with risk. However, predictions for high-risk groups as defined by screening history patterns were highly discriminatory with ORs ranging from 8 to 36. The model for computing risk performed consistently across different screening history lengths, and several patterns predicted cancer outcomes. The results show the presence of risk-increasing and risk-decreasing factors in the screening history. Thus it is feasible to identify subgroups based on their complete screening histories. Several high-risk subgroups identified might benefit from an increased screening density. Some low-risk subgroups identified could likely have a moderately reduced screening density without additional risk.

Combinatorial identification of DNA methylation patterns over age in the human brain.

BACKGROUND: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. RESULTS: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. CONCLUSION: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.

A Significant Regulatory Mutation Burden at a High-Affinity Position of the CTCF Motif in Gastrointestinal Cancers.

Somatic mutations drive cancer and there are established ways to study those in coding sequences. It has been shown that some regulatory mutations are over-represented in cancer. We develop a new strategy to find putative regulatory mutations based on experimentally established motifs for transcription factors (TFs). In total, we find 1,552 candidate regulatory mutations predicted to significantly reduce binding affinity of many TFs in hepatocellular carcinoma and affecting binding of CTCF also in esophagus, gastric, and pancreatic cancers. Near mutated motifs, there is a significant enrichment of (1) genes mutated in cancer, (2) tumor-suppressor genes, (3) genes in KEGG cancer pathways, and (4) sets of genes previously associated to cancer. Experimental and functional validations support the findings. The strategy can be applied to identify regulatory mutations in any cell type with established TF motifs and will aid identifications of genes contributing to cancer.

Identification of combinatorial host-specific signatures with a potential to affect host adaptation in influenza A H1N1 and H3N2 subtypes.

BACKGROUND: The underlying strategies used by influenza A viruses (IAVs) to adapt to new hosts while crossing the species barrier are complex and yet to be understood completely. Several studies have been published identifying singular genomic signatures that indicate such a host switch. The complexity of the problem suggested that in addition to the singular signatures, there might be a combinatorial use of such genomic features, in nature, defining adaptation to hosts. RESULTS: We used computational rule-based modeling to identify combinatorial sets of interacting amino acid (aa) residues in 12 proteins of IAVs of H1N1 and H3N2 subtypes. We built highly accurate rule-based models for each protein that could differentiate between viral aa sequences coming from avian and human hosts. We found 68 host-specific combinations of aa residues, potentially associated to host adaptation on HA, M1, M2, NP, NS1, NEP, PA, PA-X, PB1 and PB2 proteins of the H1N1 subtype and 24 on M1, M2, NEP, PB1 and PB2 proteins of the H3N2 subtypes. In addition to these combinations, we found 132 novel singular aa signatures distributed among all proteins, including the newly discovered PA-X protein, of both subtypes. We showed that HA, NA, NP, NS1, NEP, PA-X and PA proteins of the H1N1 subtype carry H1N1-specific and HA, NA, PA-X, PA, PB1-F2 and PB1 of the H3N2 subtype carry H3N2-specific signatures. M1, M2, PB1-F2, PB1 and PB2 of H1N1 subtype, in addition to H1N1 signatures, also carry H3N2 signatures. Similarly M1, M2, NP, NS1, NEP and PB2 of H3N2 subtype were shown to carry both H3N2 and H1N1 host-specific signatures (HSSs). CONCLUSIONS: To sum it up, we computationally constructed simple IF-THEN rule-based models that could distinguish between aa sequences of avian and human IAVs. From the rules we identified HSSs having a potential to affect the adaptation to specific hosts. The identification of combinatorial HSSs suggests that the process of adaptation of IAVs to a new host is more complex than previously suggested. The present study provides a basis for further detailed studies with the aim to elucidate the molecular mechanisms providing the foundation for the adaptation process.

Somatostatin Analogs and Tumor Localization Do Not Influence Vitamin D Concentration in Patients with Neuroendocrine Tumors.

Patients with neuroendocrine tumors (NETs), malignancies of rare but still rising incidence, may be a group at higher risk of vitamin D insufficiency. The gastrointestinal tumor prevalence and somatostatin analog (SSA) therapy may cause vitamin D malabsorption. The aim of this study was to evaluate the serum level of vitamin D in NET patients. A total of 36 NET patients were enrolled into the experimental group and 16 individuals were enrolled into the control group. All patients were further classified into subgroups according to primary tumor localization (gastropancreatic, lung, and other NETs) or therapy (with or without SSA treatment). The concentrations of total 25(OH)D were assayed with Electrochemiluminescence immunoassay (ECLIA). Serum concentration of 25(OH)D in NET patients did not differ significantly from that of the control group. However, the average level of 25(OH)D in both groups met the criteria of vitamin D deficiency. Importantly, SSA therapy did not aggravate vitamin D deficiency. Moreover, the concentration of 25(OH)D in the studied group was not significantly influenced by primary tumor localization, patient age, or season. Vitamin D deficiency is a widespread disorder affecting both NET patients and individuals without other health problems, and SSA and gastrointestinal tumor localization do not exacerbate this condition.

Kcnq1ot1 antisense noncoding RNA mediates lineage-specific transcriptional silencing through chromatin-level regulation.

Recent investigations have implicated long antisense noncoding RNAs in the epigenetic regulation of chromosomal domains. Here we show that Kcnq1ot1 is an RNA polymerase II-encoded, 91 kb-long, moderately stable nuclear transcript and that its stability is important for bidirectional silencing of genes in the Kcnq1 domain. Kcnq1ot1 interacts with chromatin and with the H3K9- and H3K27-specific histone methyltransferases G9a and the PRC2 complex in a lineage-specific manner. This interaction correlates with the presence of extended regions of chromatin enriched with H3K9me3 and H3K27me3 in the Kcnq1 domain in placenta, whereas fetal liver lacks both chromatin interactions and heterochromatin structures. In addition, the Kcnq1 domain is more often found in contact with the nucleolar compartment in placenta than in liver. Taken together, our data describe a mechanism whereby Kcnq1ot1 establishes lineage-specific transcriptional silencing patterns through recruitment of chromatin remodeling complexes and maintenance of these patterns through subsequent cell divisions occurs via targeting the associated regions to the perinucleolar compartment.

Nucleosome regulatory dynamics in response to TGFß.

Nucleosomes play important roles in a cell beyond their basal functionality in chromatin compaction. Their placement affects all steps in transcriptional regulation, from transcription factor (TF) binding to messenger ribonucleic acid (mRNA) synthesis. Careful profiling of their locations and dynamics in response to stimuli is important to further our understanding of transcriptional regulation by the state of chromatin. We measured nucleosome occupancy in human hepatic cells before and after treatment with transforming growth factor beta 1 (TGFß1), using massively parallel sequencing. With a newly developed method, SuMMIt, for precise positioning of nucleosomes we inferred dynamics of the nucleosomal landscape. Distinct nucleosome positioning has previously been described at transcription start site and flanking TF binding sites. We found that the average pattern is present at very few sites and, in case of TF binding, the double peak surrounding the sites is just an artifact of averaging over many loci. We systematically searched for depleted nucleosomes in stimulated cells compared to unstimulated cells and identified 24 318 loci. Depending on genomic annotation, 44-78% of them were over-represented in binding motifs for TFs. Changes in binding affinity were verified for HNF4α by qPCR. Strikingly many of these loci were associated with expression changes, as measured by RNA sequencing.

Integration of genome-wide of Stat3 binding and epigenetic modification mapping with transcriptome reveals novel Stat3 target genes in glioma cells.

BACKGROUND: Signal transducer and activator of transcription 3 (STAT3) is constitutively activated in many human tumors, including gliomas, and regulates the expression of genes implicated in proliferation, survival, apoptosis, angiogenesis and immune regulation. Only a small fraction of those genes has been proven to be direct STAT3 targets. In gliomas, STAT3 can play tumor suppressive or oncogenic roles depending on the tumor genetic background with target genes being largely unknown. RESULTS: We used chromatin immunoprecipitation, promoter microarrays and deep sequencing to assess the genome-wide occupancy of phospho (p)-Stat3 and epigenetic modifications of H3K4me3 and H3ac in C6 glioma cells. This combined assessment identified a list of 1200 genes whose promoters have both Stat3 binding sites and epigenetic marks characteristic for actively transcribed genes. The Stat3 and histone markings data were also intersected with a set of microarray data from C6 glioma cells after inhibition of Jak2/Stat3 signaling. Subsequently, we found 284 genes characterized by p-Stat3 occupancy, activating histone marks and transcriptional changes. Novel genes were screened for their potential involvement in oncogenesis, and the most interesting hits were verified by ChIP-PCR and STAT3 knockdown in human glioma cells. CONCLUSIONS: Non-random association between silent genes, histone marks and p-Stat3 binding near transcription start sites was observed, consistent with its repressive role in transcriptional regulation of target genes in glioma cells with specific genetic background.