Genome-wide landscape of liver X receptor chromatin binding and gene regulation in human macrophages

<p>Abstract</p> <p>Background</p> <p>The liver X receptors (LXRs) are oxysterol sensing nuclear receptors with multiple effects on metabolism and immune cells. However, the complete genome-wide cistrome of LXR in cells of human origin has not yet been provided.</p> <p>Results</p> <p>We performed ChIP-seq in phorbol myristate acetate-differentiated THP-1 cells (macrophage-type) after stimulation with the potent synthetic LXR ligand T0901317 (T09). Microarray gene expression analysis was performed in the same cellular model. We identified 1357 genome-wide LXR locations (FDR < 1%), of which 526 were observed after T09 treatment. <it>De novo </it>analysis of LXR binding sequences identified a DR4-type element as the major motif. On mRNA level T09 up-regulated 1258 genes and repressed 455 genes. Our results show that LXR actions are focused on 112 genomic regions that contain up to 11 T09 target genes per region under the control of highly stringent LXR binding sites with individual constellations for each region. We could confirm that LXR controls lipid metabolism and transport and observed a strong association with apoptosis-related functions.</p> <p>Conclusions</p> <p>This first report on genome-wide binding of LXR in a human cell line provides new insights into the transcriptional network of LXR and its target genes with their link to physiological processes, such as apoptosis.</p> <p>The gene expression microarray and sequence data have been submitted collectively to the NCBI Gene Expression Omnibus <url>http://www.ncbi.nlm.nih.gov/geo</url> under accession number GSE28319.</p

Characterization and diversity of 243 complete human papillomavirus genomes in cervical swabs using next generation sequencing

In recent years, next generation sequencing (NGS) technology has been widely used for the discovery of novel human papillomavirus (HPV) genotypes, variant characterization and genotyping. Here, we compared the analytical performance of NGS with a commercial PCR-based assay (Anyplex II HPV28) in cervical samples of 744 women. Overall, HPV positivity was 50.2% by the Anyplex and 45.5% by the NGS. With the NGS, we detected 25 genotypes covered by Anyplex and 41 additional genotypes. Agreement between the two methods for HPV positivity was 80.8% (kappa = 0.616) and 84.8% (kappa = 0.652) for 28 HPV genotypes and 14 high-risk genotypes, respectively. We recovered and characterized 243 complete HPV genomes from 153 samples spanning 40 different genotypes. According to phylogenetic analysis and pairwise distance, we identified novel lineages and sublineages of four high-risk and 16 low-risk genotypes. In total, 17 novel lineages and 14 novel sublineages were proposed, including novel lineages of HPV45, HPV52, HPV66 and a novel sublineage of HPV59. Our study provides important genomic insights on HPV types and lineages, where few complete genomes were publicly available

Aberrant splicing of the tumor suppressor CYLD promotes the development of chronic lymphocytic leukemia via sustained NF-kappaB signaling.

The pathogenesis of chronic lymphocytic leukemia (CLL) has been linked to constitutive NF-kappaB activation but the underlying mechanisms are poorly understood. Here we show that alternative splicing of the negative regulator of NF-kappaB and tumor suppressor gene CYLD regulates the pool of CD5(+) B cells through sustained canonical NF-kappaB signaling. Reinforced canonical NF-kappaB activity leads to the development of B1 cell-associated tumor formation in aging mice by promoting survival and proliferation of CD5(+) B cells, highly reminiscent of human B-CLL. We show that a substantial number of CLL patient samples express sCYLD, strongly implicating a role for it in human B-CLL. We propose that our new CLL-like mouse model represents an appropriate tool for studying ubiquitination-driven canonical NF-kappaB activation in CLL. Thus, inhibition of alternative splicing of this negative regulator is essential for preventing NF-kappaB-driven clonal CD5(+) B-cell expansion and ultimately CLL-like disease

Dataset integration identifies transcriptional regulation of microRNA genes by PPARγ in differentiating mouse 3T3-L1 adipocytes

Peroxisome proliferator-activated receptor γ (PPARγ) is a key transcription factor in mammalian adipogenesis. Genome-wide approaches have identified thousands of PPARγ binding sites in mouse adipocytes and PPARγ upregulates hundreds of protein-coding genes during adipogenesis. However, no microRNA (miRNA) genes have been identified as primary PPARγ-targets. By integration of four separate datasets of genome-wide PPARγ binding sites in 3T3-L1 adipocytes we identified 98 miRNA clusters with PPARγ binding within 50 kb from miRNA transcription start sites. Nineteen mature miRNAs were upregulated ≥2-fold during adipogenesis and for six of these miRNA loci the PPARγ binding sites were confirmed by at least three datasets. The upregulation of five miRNA genes miR-103-1 (host gene Pank3), miR-148b (Copz1), miR-182/96/183, miR-205 and miR-378 (Ppargc1b) followed that of Pparg. The PPARγ-dependence of four of these miRNA loci was demonstrated by PPARγ knock-down and the loci of miR-103-1 (Pank3), miR-205 and miR-378 (Ppargc1b) were also responsive to the PPARγ ligand rosiglitazone. Finally, chromatin immunoprecipitation analysis validated in silico predicted PPARγ binding sites at all three loci and H3K27 acetylation was analyzed to confirm the activity of these enhancers. In conclusion, we identified 22 putative PPARγ target miRNA genes, showed the PPARγ dependence of four of these genes and demonstrated three as direct PPARγ target genes in mouse adipogenesis

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three genomic nomenclature systems to all sequence data from the World Health Organization European Region available until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation, compare the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2

In Silico prediction of transcription factor binding sites by probabilistic models

The characterization of in silico detected transcription factor binding sites represents a fundamental problem in the field of regulatory gene expression analysis. Several approaches have been proposed to model DNA-protein-interactions, composed by two main classes: qualitative models considering a consensus sequence and quantitative models providing a measure of binding affinity. The latter can be further subdivided in models assuming an independent contribution of the nucleotides forming a potential binding site and more flexible ones implicating a positional interdependence. In this work the applicability of three probabilistic models to predict transcription factor binding sites has been investigated: (i) the simple position weight matrix (PWM), assuming independence, and two flexible models capturing positional interdependencies represented by a (ii) Chow-Liu Tree and (iii) Ensemble of Trees model. The training and validation of the models on the Mus musculus subset of the UniPROBE database revealed that complex models provide a better predictive power suggesting a high amount of transcription factors binding motifs being affected by positional interdependencies. Additionally, numerous transcription factors were detected, for which the Ensemble of Trees model outperformed both, the Chow-Liu Tree and PWM model. The UniPROBE-based trained models have been applied in a biological context - the prediction of differential binding profiles in five different ChIP-seq samples, followed by the detection of causative regulatory SNPs. The chosen set-up involved family trio data, meaning genotype data from a family composed of father, mother and daughter, providing internal validation. The models provide strong power to correctly classify true negatives in an independent biological sample, represented by a high specificity. The applied approach to detect causative regulatory SNPs, resulted in a candidate list of 20 SNPs. Those gain strong support by epigenetic markers and both, model-based predicted binding affinity of the comprising binding site and significant p-values, describing the effect of the nucleotide exchange

Dataset integration identifies transcriptional regulation of microRNA genes by PPARgamma in differentiating mouse 3T3-L1 adipocytes

Peroxisome proliferator-activated receptor gamma (PPARgamma) is a key transcription factor in mammalian adipogenesis. Genome-wide approaches have identified thousands of PPARgamma binding sites in mouse adipocytes and PPARgamma upregulates hundreds of protein-coding genes during adipogenesis. However, no microRNA (miRNA) genes have been identified as primary PPARgamma-targets. By integration of four separate datasets of genome-wide PPARgamma binding sites in 3T3-L1 adipocytes we identified 98 miRNA clusters with PPARgamma binding within 50 kb from miRNA transcription start sites. Nineteen mature miRNAs were upregulated >/=2-fold during adipogenesis and for six of these miRNA loci the PPARgamma binding sites were confirmed by at least three datasets. The upregulation of five miRNA genes miR-103-1 (host gene Pank3), miR-148b (Copz1), miR-182/96/183, miR-205 and miR-378 (Ppargc1b) followed that of Pparg. The PPARgamma-dependence of four of these miRNA loci was demonstrated by PPARgamma knock-down and the loci of miR-103-1 (Pank3), miR-205 and miR-378 (Ppargc1b) were also responsive to the PPARgamma ligand rosiglitazone. Finally, chromatin immunoprecipitation analysis validated in silico predicted PPARgamma binding sites at all three loci and H3K27 acetylation was analyzed to confirm the activity of these enhancers. In conclusion, we identified 22 putative PPARgamma target miRNA genes, showed the PPARgamma dependence of four of these genes and demonstrated three as direct PPARgamma target genes in mouse adipogenesis

Bioinformatics as a driver, not a passenger, of translational biomedical research: Perspectives from the 6th Benelux bioinformatics conference.

The 6th Benelux Bioinformatics Conference (BBC11) held in Luxembourg on 12 and 13 December 2011 attracted around 200 participants, including internationally-renowned guest speakers and more than 100 peer-reviewed submissions from 3 continents. Researchers from the public and private sectors convened at BBC11 to discuss advances and challenges in a wide spectrum of application areas. A key theme of the conference was the contribution of bioinformatics to enable and accelerate translational and clinical research. The BBC11 stressed the need for stronger collaborating efforts across disciplines and institutions. The demonstration of the clinical relevance of systems approaches and of next-generation sequencing-based measurement technologies are among the existing opportunities for increasing impact in translational research. Translational bioinformatics will benefit from research models that strike a balance between the importance of protecting intellectual property and the need to openly access scientific and technological advances. The full conference proceedings are freely available at http://www.bbc11.lu

Interferon-γ-induced activation of Signal Transducer and Activator of Transcription 1 (STAT1) up-regulates the tumor suppressing microRNA-29 family in melanoma cells

Background: The type-II-cytokine IFN-γ is a pivotal player in innate immune responses but also assumes functions in controlling tumor cell growth by orchestrating cellular responses against neoplastic cells. The role of IFN-γ in melanoma is not fully understood: it is a well-known growth inhibitor of melanoma cells in vitro. On the other hand, IFN-γ may also facilitate melanoma progression. While interferon-regulated genes encoding proteins have been intensively studied since decades, the contribution of miRNAs to effects mediated by interferons is an emerging area of research.We recently described a distinct and dynamic regulation of a whole panel of microRNAs (miRNAs) after IFN-γ-stimulation. The aim of this study was to analyze the transcriptional regulation of miR-29 family members in detail, identify potential interesting target genes and thus further elucidate a potential signaling pathway IFN-γ → Jak→ P-STAT1 → miR-29 → miR-29 target genes and its implication for melanoma growth. Results: Here we show that IFN-γ induces STAT1-dependently a profound up-regulation of the miR-29 primary cluster pri-29a∼b-1 in melanoma cell lines. Furthermore, expression levels of pri-29a∼b-1 and mature miR-29a and miR-29b were elevated while the pri-29b-2∼c cluster was almost undetectable. We observed an inverse correlation between miR-29a/b expression and the proliferation rate of various melanoma cell lines. This finding could be corroborated in cells transfected with either miR-29 mimics or inhibitors. The IFN-γ-induced G1-arrest of melanoma cells involves down-regulation of CDK6, which we proved to be a direct target of miR-29 in these cells. Compared to nevi and normal skin, and metastatic melanoma samples, miR-29a and miR-29b levels were found strikingly elevated in certain patient samples derived from primary melanoma. Conclusions: Our findings reveal that the miR-29a/b1 cluster is to be included in the group of IFN- and STAT-regulated genes. The up-regulated miR-29 family members may act as effectors of cytokine signalling in melanoma and other cancer cells as well as in the immune system. © 2012 Schmitt et al.; licensee BioMed Central Ltd