Global Chromatin Domain Organization of the Drosophila Genome

In eukaryotes, neighboring genes can be packaged together in specific chromatin structures that ensure their coordinated expression. Examples of such multi-gene chromatin domains are well-documented, but a global view of the chromatin organization of eukaryotic genomes is lacking. To systematically identify multi-gene chromatin domains, we constructed a compendium of genome-scale binding maps for a broad panel of chromatin-associated proteins in Drosophila melanogaster. Next, we computationally analyzed this compendium for evidence of multi-gene chromatin domains using a novel statistical segmentation algorithm. We find that at least 50% of all fly genes are organized into chromatin domains, which often consist of dozens of genes. The domains are characterized by various known and novel combinations of chromatin proteins. The genes in many of the domains are coregulated during development and tend to have similar biological functions. Furthermore, during evolution fewer chromosomal rearrangements occur inside chromatin domains than outside domains. Our results indicate that a substantial portion of the Drosophila genome is packaged into functionally coherent, multi-gene chromatin domains. This has broad mechanistic implications for gene regulation and genome evolution

The Epstein–Barr virus nuclear antigen-1 promotes telomere dysfunction via induction of oxidative stress

The Epstein–Barr virus (EBV) nuclear antigen (EBNA)-1 promotes the accumulation of chromosomal aberrations in malignant B cells by inducing oxidative stress. Here we report that this phenotype is associated with telomere dysfunction. Stable or conditional expression of EBNA1 induced telomere abnormalities including loss or gain of telomere signals, telomere fusion and heterogeneous length of telomeres. This was accompanied by the accumulation of extrachromosomal telomeres, telomere dysfunction-induced foci (TIFs) containing phosphorylated histone H2AX and the DNA damage response protein 53BP1, telomere-associated promyelocytic leukemia nuclear bodies (APBs), telomeric-sister chromatid exchanges and displacement of the shelterin protein TRF2. The induction of TIFs and APBs was inhibited by treatment with scavengers of reactive oxygen species (ROS) that also promoted the relocalization of TRF2 at telomeres. These findings highlight a novel mechanism by which EBNA1 may promote malignant transformation and tumor progression

Immunohistochemical analysis of the mechanistic target of rapamycin and hypoxia signalling pathways in basal cell carcinoma and trichoepithelioma

Background: Basal cell carcinoma (BCC) is the most common cancer in Caucasians. Trichoepithelioma (TE) is a benign neoplasm that strongly resembles BCC. Both are hair follicle (HF) tumours. HFs are hypoxic microenvironments, therefore we hypothesized that hypoxia-induced signalling pathways could be involved in BCC and TE as they are in other human malignancies. Hypoxia-inducible factor 1 (HIF1) and mechanistic/mammalian target of rapamycin (mTOR) are key players in these pathways. Objectives: To determine whether HIF1/mTOR signalling is involved in BCC and TE. Methods: We used immunohistochemical staining of formalin-fixed paraffin-embedded BCC (n = 45) and TE (n = 35) samples to assess activity of HIF1, mTORC1 and their most important target genes. The percentage positive tumour cells was assessed manually in a semi-quantitative manner and categorized (0%, 80%). Results: Among 45 BCC and 35 TE examined, expression levels were respectively 81% and 57% (BNIP3), 73% and 75% (CAIX), 79% and 86% (GLUT1), 50% and 19% (HIF1 alpha), 89% and 88% (pAKT), 55% and 61% (pS6), 15% and 25% (pMTOR), 44% and 63% (PHD2) and 44% and 49% (VEGF-A). CAIX, Glut1 and PHD2 expression levels were significantly higher in TE when only samples with at least 80% expression were included. Conclusions: HIF and mTORC1 signalling seems active in both BCC and TE. There are no appreciable differences between the two with respect to pathway activity. At this moment immunohistochemical analyses of HIF, mTORC1 and their target genes does not provide a reliable diagnostic tool for the discrimination of BCC and TE

siRNA Silencing of Proteasome Maturation Protein (POMP) Activates the Unfolded Protein Response and Constitutes a Model for KLICK Genodermatosis

Keratosis linearis with ichthyosis congenita and keratoderma (KLICK) is an autosomal recessive skin disorder associated with a single-nucleotide deletion in the 5′untranslated region of the proteasome maturation protein (POMP) gene. The deletion causes a relative switch in transcription start sites for POMP, predicted to decrease levels of POMP protein in terminally differentiated keratinocytes. To investigate the pathophysiology behind KLICK we created an in vitro model of the disease using siRNA silencing of POMP in epidermal air-liquid cultures. Immunohistochemical analysis of the tissue constructs revealed aberrant staining of POMP, proteasome subunits and the skin differentiation marker filaggrin when compared to control tissue constructs. The staining patterns of POMP siRNA tissue constructs showed strong resemblance to those observed in skin biopsies from KLICK patients. Western blot analysis of lysates from the organotypic tissue constructs revealed an aberrant processing of profilaggrin to filaggrin in samples transfected with siRNA against POMP. Knock-down of POMP expression in regular cell cultures resulted in decreased amounts of proteasome subunits. Prolonged silencing of POMP in cultured cells induced C/EBP homologous protein (CHOP) expression consistent with an activation of the unfolded protein response and increased endoplasmic reticulum (ER) stress. The combined results indicate that KLICK is caused by reduced levels of POMP, leading to proteasome insufficiency in differentiating keratinocytes. Proteasome insufficiency disturbs terminal epidermal differentiation, presumably by increased ER stress, and leads to perturbed processing of profilaggrin. Our findings underline a critical role for the proteasome in human epidermal differentiation

CATCHprofiles: Clustering and Alignment Tool for ChIP Profiles

Chromatin Immuno Precipitation (ChIP) profiling detects in vivo protein-DNA binding, and has revealed a large combinatorial complexity in the binding of chromatin associated proteins and their post-translational modifications. To fully explore the spatial and combinatorial patterns in ChIP-profiling data and detect potentially meaningful patterns, the areas of enrichment must be aligned and clustered, which is an algorithmically and computationally challenging task. We have developed CATCHprofiles, a novel tool for exhaustive pattern detection in ChIP profiling data. CATCHprofiles is built upon a computationally efficient implementation for the exhaustive alignment and hierarchical clustering of ChIP profiling data. The tool features a graphical interface for examination and browsing of the clustering results. CATCHprofiles requires no prior knowledge about functional sites, detects known binding patterns “ab initio”, and enables the detection of new patterns from ChIP data at a high resolution, exemplified by the detection of asymmetric histone and histone modification patterns around H2A.Z-enriched sites. CATCHprofiles' capability for exhaustive analysis combined with its ease-of-use makes it an invaluable tool for explorative research based on ChIP profiling data

Integrative bioinformatics analysis of transcriptional regulatory programs in breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Microarray technology has unveiled transcriptomic differences among tumors of various phenotypes, and, especially, brought great progress in molecular understanding of phenotypic diversity of breast tumors. However, compared with the massive knowledge about the transcriptome, we have surprisingly little knowledge about regulatory mechanisms underling transcriptomic diversity.</p> <p>Results</p> <p>To gain insights into the transcriptional programs that drive tumor progression, we integrated regulatory sequence data and expression profiles of breast cancer into a Bayesian Network, and searched for <it>cis</it>-regulatory motifs statistically associated with given histological grades and prognosis. Our analysis found that motifs bound by ELK1, E2F, NRF1 and NFY are potential regulatory motifs that positively correlate with malignant progression of breast cancer.</p> <p>Conclusion</p> <p>The results suggest that these 4 motifs are principal regulatory motifs driving malignant progression of breast cancer. Our method offers a more concise description about transcriptome diversity among breast tumors with different clinical phenotypes.</p