10 results for chip-seq drosophila
Contributors: Chang, Ching-Ho, Chanvan, Ankita, Palladino, Jason, Wei, Xiaolu, Martins, Nuno M. C., Santinello, Bryce, Chen, Chin-Chi, Erceg, Jelena, Beliveau, Brian J., Wu, Chao-Ting
Drosophila centromeres...Drosophila simulans, revealing an unexpected conservation despite the ...ChIP-seq to 100x coverage using BBnorm (v37.54) with the parameters "threads...R2 ChIP-seq to 100x coverage using BBnorm (v37.54) with the parameters...ChIP-seq...satellite DNAs from Drosophila melanogaster....Drosophila simulans...Drosophila melanogaster...created a custom Drosophila-specific consensus repeat library modified...Drosophila melanogaster by combining long-read sequencing, chromatin immunoprecipitation...Drosophila...Drosophila-specific consensus repeat library modified from RepBase v20150807...Drosophila melanogaster. ... Centromeres are essential chromosomal regions that mediate kinetochore assembly and spindle attachments during cell division. Despite their functional conservation, centromeres are amongst the most rapidly evolving genomic regions and can shape karyotype evolution and speciation across taxa. Although significant progress has been made in identifying centromere-associated proteins, the highly repetitive centromeres of metazoans have been refractory to DNA sequencing and assembly, leaving large gaps in our understanding of their functional organization and evolution. Here, we identify the sequence composition and organization of the centromeres of Drosophila melanogaster by combining long-read sequencing, chromatin immunoprecipitation for the centromeric histone CENP-A, and high-resolution chromatin fiber imaging. Contrary to previous models that heralded satellite repeats as the major functional components, we demonstrate that functional centromeres form on islands of complex DNA sequences enriched in retroelements that are flanked by large arrays of satellite repeats. Each centromere displays distinct size and arrangement of its DNA elements but is similar in composition overall. We discover that a specific retroelement, G2/Jockey-3, is the most highly enriched sequence in CENP-A chromatin and is the only element shared among all centromeres. G2/Jockey-3 is also associated with CENP-A in the sister species Drosophila simulans, revealing an unexpected conservation despite the reported turnover of centromeric satellite DNA. Our work reveals the DNA sequence identity of the active centromeres of a premier model organism and implicates retroelements as conserved features of centromeric DNA.
Contributors: Kok, Kurtulus, Ay, Ahmet, Li, Li M., Arnosti, David N.
C...command....Drosophila melanogaster...ChIP-Seq experiments were visualized as custom tracks using Integrative...ChIP-Seq experiments were visualized as custom tracks using Integrative...Customized Drosophila Genome Oligo Microarrays (Agilent). Slide image ...Drosophila embryos. This long-range repressor mediates histone acetylation...Drosophila Genome Oligo Microarrays (Agilent). Slide image data was quantified ... Metazoan transcriptional repressors regulate chromatin through diverse histone modifications. Contributions of individual factors to the chromatin landscape in development is difficult to establish, as global surveys reflect multiple changes in regulators. Therefore, we studied the conserved Hairy/Enhancer of Split family repressor Hairy, analyzing histone marks and gene expression in Drosophila embryos. This long-range repressor mediates histone acetylation and methylation in large blocks, with highly context-specific effects on target genes. Most strikingly, Hairy exhibits biochemical activity on many loci that are uncoupled to changes in gene expression. Rather than representing inert binding sites, as suggested for many eukaryotic factors, many regions are targeted errantly by Hairy to modify the chromatin landscape. Our findings emphasize that identification of active cis-regulatory elements must extend beyond the survey of prototypical chromatin marks. We speculate that this errant activity may provide a path for creation of new regulatory elements, facilitating the evolution of novel transcriptional circuits.
Contributors: Duffy, David J., Krstic, Aleksandar, Halasz, Melinda, Schwarzl, Thomas, Konietzny, Anja, Iljin, Kristiina, Higgins, Desmond G., Kolch, Walter
ChIP-seq) ... Background: Retinoid therapy is widely employed in clinical oncology to differentiate malignant cells into their more benign counterparts. However, certain high-risk cohorts, such as patients with MYCN-amplified neuroblastoma, are innately resistant to retinoid therapy. Therefore, we employed a precision medicine approach to globally profile the retinoid signalling response and to determine how an excess of cellular MYCN antagonises these signalling events to prevent differentiation and confer resistance. Methods: We applied RNA sequencing (RNA-seq) and interaction proteomics coupled with network-based systems level analysis to identify targetable vulnerabilities of MYCN-mediated retinoid resistance. We altered MYCN expression levels in a MYCN-inducible neuroblastoma cell line to facilitate or block retinoic acid (RA)-mediated neuronal differentiation. The relevance of differentially expressed genes and transcriptional regulators for neuroblastoma outcome were then confirmed using existing patient microarray datasets. Results: We determined the signalling networks through which RA mediates neuroblastoma differentiation and the inhibitory perturbations to these networks upon MYCN overexpression. We revealed opposing regulation of RA and MYCN on a number of differentiation-relevant genes, including LMO4, CYP26A1, ASCL1, RET, FZD7 and DKK1. Furthermore, we revealed a broad network of transcriptional regulators involved in regulating retinoid responsiveness, such as Neurotrophin, PI3K, Wnt and MAPK, and epigenetic signalling. Of these regulators, we functionally confirmed that MYCN-driven inhibition of transforming growth factor beta (TGF-β) signalling is a vulnerable node of the MYCN network and that multiple levels of cross-talk exist between MYCN and TGF-β. Co-targeting of the retinoic acid and TGF-β pathways, through RA and kartogenin (KGN; a TGF-β signalling activating small molecule) combination treatment, induced the loss of viability of MYCN-amplified retinoid-resistant neuroblastoma cells. Conclusions: Our approach provides a powerful precision oncology tool for identifying the driving signalling networks for malignancies not primarily driven by somatic mutations, such as paediatric cancers. By applying global omics approaches to the signalling networks regulating neuroblastoma differentiation and stemness, we have determined the pathways involved in the MYCN-mediated retinoid resistance, with TGF-β signalling being a key regulator. These findings revealed a number of combination treatments likely to improve clinical response to retinoid therapy, including co-treatment with retinoids and KGN, which may prove valuable in the treatment of high-risk MYCN-amplified neuroblastoma.
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Contributors: Conesa, Ana, Madrigal, Pedro, Tarazona, Sonia, Gomez-Cabrero, David, Cervera, Alejandra, McPherson, Andrew, Szcześniak, Michał Wojciech, Gaffney, Daniel J., Elo, Laura L., Zhang, Xuegong
... RNA-sequencing (RNA-seq) has a wide variety of applications, but no single analysis pipeline can be used in all cases. We review all of the major steps in RNA-seq data analysis, including experimental design, quality control, read alignment, quantification of gene and transcript levels, visualization, differential gene expression, alternative splicing, functional analysis, gene fusion detection and eQTL mapping. We highlight the challenges associated with each step. We discuss the analysis of small RNAs and the integration of RNA-seq with other functional genomics techniques. Finally, we discuss the outlook for novel technologies that are changing the state of the art in transcriptomics.
Contributors: Moretti, Charlotte, Vaiman, Daniel, Tores, Frederic, Cocquet, Julie
ChIP-Seq datasets performed on mouse round spermatids and four RNA-seq ... Background: During meiosis, the X and Y chromosomes are transcriptionally silenced. The persistence of repressive chromatin marks on the sex chromatin after meiosis initially led to the assumption that XY gene silencing persists to some extent in spermatids. Considering the many reports of XY-linked genes expressed and needed in the post-meiotic phase of mouse spermatogenesis, it is still unclear whether or not the mouse sex chromatin is a repressive or permissive environment, after meiosis. Results: To determine the transcriptional and chromatin state of the sex chromosomes after meiosis, we re-analyzed ten ChIP-Seq datasets performed on mouse round spermatids and four RNA-seq datasets from male germ cells purified at different stages of spermatogenesis. For this, we used the last version of the genome (mm10/GRCm38) and included reads that map to several genomic locations in order to properly interpret the high proportion of sex chromosome-encoded multicopy genes. Our study shows that coverage of active epigenetic marks H3K4me3 and Kcr is similar on the sex chromosomes and on autosomes. The post-meiotic sex chromatin nevertheless differs from autosomal chromatin in its enrichment in H3K9me3 and its depletion in H3K27me3 and H4 acetylation. We also identified a posttranslational modification, H3K27ac, which specifically accumulates on the Y chromosome. In parallel, we found that the X and Y chromosomes are enriched in genes expressed post-meiotically and display a higher proportion of spermatid-specific genes compared to autosomes. Finally, we observed that portions of chromosome 14 and of the sex chromosomes share specific features, such as enrichment in H3K9me3 and the presence of multicopy genes that are specifically expressed in round spermatids, suggesting that parts of chromosome 14 are under the same evolutionary constraints than the sex chromosomes. Conclusions: Based on our expression and epigenomic studies, we conclude that, after meiosis, the mouse sex chromosomes are no longer silenced but are nevertheless regulated differently than autosomes and accumulate different chromatin marks. We propose that post-meiotic selective constraints are at the basis of the enrichment of spermatid-specific genes and of the peculiar chromatin composition of the sex chromosomes and of parts of chromosome 14.
Contributors: García-Molinero, Varinia, García-Martínez, José, Reja, Rohit, Furió-Tarí, Pedro, Antúnez, Oreto, Vinayachandran, Vinesh, Conesa, Ana, Pugh, B. Franklin, Pérez-Ortín, José E., Rodríguez-Navarro, Susana
... Background: Eukaryotic transcription is regulated through two complexes, the general transcription factor IID (TFIID) and the coactivator Spt–Ada–Gcn5 acetyltransferase (SAGA). Recent findings confirm that both TFIID and SAGA contribute to the synthesis of nearly all transcripts and are recruited genome-wide in yeast. However, how this broad recruitment confers selectivity under specific conditions remains an open question.Results: Here we find that the SAGA/TREX-2 subunit Sus1 associates with upstream regulatory regions of many yeast genes and that heat shock drastically changes Sus1 binding. While Sus1 binding to TFIID-dominated genes is not affected by temperature, its recruitment to SAGA-dominated genes and RP genes is significantly disturbed under heat shock, with Sus1 relocated to environmental stress-responsive genes in these conditions. Moreover, in contrast to recent results showing that SAGA deubiquitinating enzyme Ubp8 is dispensable for RNA synthesis, genomic run-on experiments demonstrate that Sus1 contributes to synthesis and stability of a wide range of transcripts.Conclusions: Our study provides support for a model in which SAGA/TREX-2 factor Sus1 acts as a global transcriptional regulator in yeast but has differential activity at yeast genes as a function of their transcription rate or during stress conditions.
Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare
Contributors: Suravajhala, Prashanth, Kogelman, Lisette J. A., Kadarmideen, Haja N.
... In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.
Contributors: Zhou, Yue, Romero-Campero, Francisco J., Gómez-Zambrano, Ángeles, Turck, Franziska, Calonje, Myriam
... Background: Polycomb group complexes PRC1 and PRC2 repress gene expression at the chromatin level in eukaryotes. The classic recruitment model of Polycomb group complexes in which PRC2-mediated H3K27 trimethylation recruits PRC1 for H2A monoubiquitination was recently challenged by data showing that PRC1 activity can also recruit PRC2. However, the prevalence of these two mechanisms is unknown, especially in plants as H2AK121ub marks were examined at only a handful of Polycomb group targets. Results: By using genome-wide analyses, we show that H2AK121ub marks are surprisingly widespread in Arabidopsis thaliana, often co-localizing with H3K27me3 but also occupying a set of transcriptionally active genes devoid of H3K27me3. Furthermore, by profiling H2AK121ub and H3K27me3 marks in atbmi1a/b/c, clf/swn, and lhp1 mutants we found that PRC2 activity is not required for H2AK121ub marking at most genes. In contrast, loss of AtBMI1 function impacts the incorporation of H3K27me3 marks at most Polycomb group targets. Conclusions: Our findings show the relationship between H2AK121ub and H3K27me3 marks across the A. thaliana genome and unveil that ubiquitination by PRC1 is largely independent of PRC2 activity in plants, while the inverse is true for H3K27 trimethylation.
Contributors: Piwowar, Heather A., Vision, Todd J.
... Background: Attribution to the original contributor upon reuse of published data is important both as a reward for data creators and to document the provenance of research findings. Previous studies have found that papers with publicly available datasets receive a higher number of citations than similar studies without available data. However, few previous analyses have had the statistical power to control for the many variables known to predict citation rate, which has led to uncertain estimates of the "citation benefit". Furthermore, little is known about patterns in data reuse over time and across datasets. Method and Results: Here, we look at citation rates while controlling for many known citation predictors, and investigate the variability of data reuse. In a multivariate regression on 10,555 studies that created gene expression microarray data, we found that studies that made data available in a public repository received 9% (95% confidence interval: 5% to 13%) more citations than similar studies for which the data was not made available. Date of publication, journal impact factor, open access status, number of authors, first and last author publication history, corresponding author country, institution citation history, and study topic were included as covariates. The citation benefit varied with date of dataset deposition: a citation benefit was most clear for papers published in 2004 and 2005, at about 30%. Authors published most papers using their own datasets within two years of their first publication on the dataset, whereas data reuse papers published by third-party investigators continued to accumulate for at least six years. To study patterns of data reuse directly, we compiled 9,724 instances of third party data reuse via mention of GEO or ArrayExpress accession numbers in the full text of papers. The level of third-party data use was high: for 100 datasets deposited in year 0, we estimated that 40 papers in PubMed reused a dataset by year 2, 100 by year 4, and more than 150 data reuse papers had been published by year 5. Data reuse was distributed across a broad base of datasets: a very conservative estimate found that 20% of the datasets deposited between 2003 and 2007 had been reused at least once by third parties. Conclusion: After accounting for other factors affecting citation rate, we find a robust citation benefit from open data, although a smaller one than previously reported. We conclude there is a direct effect of third-party data reuse that persists for years beyond the time when researchers have published most of the papers reusing their own data. Other factors that may also contribute to the citation benefit are considered.We further conclude that, at least for gene expression microarray data, a substantial fraction of archived datasets are reused, and that the intensity of dataset reuse has been steadily increasing since 2003.
Contributors: Jessica Cox, Corey Harper
... This dataset contains 4 files: 1. A .csv containing 29,105 sentences from CC-BY papers that contain citations ("pygothamCleanDataset.csv"). 2. A community edition databricks notebook to process and explore the data as .dbc 3. A community edition databricks notebook to view in HTML. 3. Pygotham slides in PDF format.