10 results for chip-seq drosophila
Contributors: Rich Jones
... Refine.bio survey list generator required CSV, tediously exported manually from GEO web interface. Ex: $ head accessions/Illumina\ HiSeq\ 2000.csv "Experiment Accession","Experiment Title","Organism Name","Instrument","Submitter","Study Accession","Study Title","Sample Accession","Sample Title","Total Size, Mb","Total RUNs","Total Spots","Total Bases","Library Name","Library Strategy","Library Source","Library Selection" "SRX4195895","4","Homo sapiens","Illumina HiSeq 2000","Kolling Institute, The University of Sydney","SRP150290","RET-altered microRNAs in MTC","SRS3406604","","370.5","1","15916120","795806000","4","miRNA-Seq","TRANSCRIPTOMIC","unspecified" "SRX4195894","3","Homo sapiens","Illumina HiSeq 2000","Kolling Institute, The University of Sydney","SRP150290","RET-altered microRNAs in MTC","SRS3406603","","362.43","1","16021366","801068300","3","miRNA-Seq","TRANSCRIPTOMIC","unspecified" "SRX4195893","6","Homo sapiens","Illumina HiSeq 2000","Kolling Institute, The University of Sydney","SRP150290","RET-altered microRNAs in MTC","SRS3406602","","407.58","1","18432342","921617100","6","miRNA-Seq","TRANSCRIPTOMIC","unspecified" "SRX4195892","5","Homo sapiens","Illumina HiSeq 2000","Kolling Institute, The University of Sydney","SRP150290","RET-altered microRNAs in MTC","SRS3406605","","347.33","1","16162471","808123550","5","miRNA-Seq","TRANSCRIPTOMIC","unspecified"
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.
Contributors: Maeda, Robert K., Karch, François
Drosophila third chromosome, the locus became known of as the bithorax...Drosophila ... After nearly 30 years of effort, Ed Lewis published his 1978 landmark paper in which he described the analysis of a series of mutations that affect the identity of the segments that form along the anterior-posterior (AP) axis of the fly (Lewis 1978). The mutations behaved in a non-canonical fashion in complementation tests, forming what Ed Lewis called a "pseudo-allelic" series. Because of this, he never thought that the mutations represented segment-specific genes. As all of these mutations were grouped to a particular area of the Drosophila third chromosome, the locus became known of as the bithorax complex (BX-C). One of the key findings of Lewis' article was that it revealed for the first time, to a wide scientific audience, that there was a remarkable correlation between the order of the segment-specific mutations along the chromosome and the order of the segments they affected along the AP axis. In Ed Lewis' eyes, the mutants he discovered affected "segment-specific functions" that were sequentially activated along the chromosome as one moves from anterior to posterior along the body axis (the colinearity concept now cited in elementary biology textbooks). The nature of the "segment-specific functions" started to become clear when the BX-C was cloned through the pioneering chromosomal walk initiated in the mid 1980s by the Hogness and Bender laboratories (Bender et al. 1983a; Karch et al. 1985). Through this molecular biology effort, and along with genetic characterizations performed by Gines Morata's group in Madrid (Sanchez-Herrero et al. 1985) and Robert Whittle's in Sussex (Tiong et al. 1985), it soon became clear that the whole BX-C encoded only three protein-coding genes (Ubx, abd-A, and Abd-B). Later, immunostaining against the Ubx protein hinted that the segment-specific functions could, in fact, be cis-regulatory elements regulating the expression of the three protein-coding genes. In 1987, Peifer, Karch, and Bender proposed a comprehensive model of the functioning of the BX-C, in which the "segment-specific functions" appear as segment-specific enhancers regulating, Ubx, abd-A, or Abd-B (Peifer et al. 1987). Key to their model was that the segmental address of these enhancers was not an inherent ability of the enhancers themselves, but was determined by the chromosomal location in which they lay. In their view, the sequential activation of the segment-specific functions resulted from the sequential opening of chromatin domains along the chromosome as one moves from anterior to posterior. This model soon became known of as the open for business model. While the open for business model is quite easy to visualize at a conceptual level, molecular evidence to validate this model has been missing for almost 30 years. The recent publication describing the outstanding, joint effort from the Bender and Kingston laboratories now provides the missing proof to support this model (Bowman et al. 2014). The purpose of this article is to review the open for business model and take the reader through the genetic arguments that led to its elaboration.
Contributors: Deplancke, Bart
... This presentation was part of Day 5 of the Open Science in Practice Summer School #osip2017. Additional information can be found on osip2017.epfl.ch.
Unique cistrome defined as CsMBE is strictly required for Nrf2-sMaf heterodimer function in cytoprotection
Contributors: Otsuki, Akihito, Suzuki, Mikiko, Katsuoka, Fumiki, Tsuchida, Kouhei, Suda, Hiromi, Morita, Masanobu, Shimizu, Ritsuko, Yamamoto, Masayuki
... Nrf2-small Maf (sMaf) heterodimer is essential for the inducible expression of cytoprotective genes upon exposure to oxidative and xenobiotic stresses. While the Nrf2-sMaf heterodimer recognizes DNA sequences referred to as the antioxidant/electrophile responsive element (ARE/EpRE), we here define these DNA sequences collectively as CNC-sMaf binding element (CsMBE). In contrast, large and small Maf proteins are able to form homodimers that recognize the Maf recognition element (MARE). CsMBE and MARE share a conserved core sequence but they differ in the 5'-adjacent nucleotide neighboring the core. Because of the high similarity between the CsMBE and MARE sequences, it has been unclear how many target binding sites and target genes are shared by the Nrf2-sMaf heterodimers and Maf homodimers. To address this issue, we introduced a substitution mutation of alanine to tyrosine at position 502 in Nrf2, which rendered the DNA-binding domain structure of Nrf2 similar to Maf, and generated knock-in mice expressing the Nrf2(A502Y) mutant. Our chromatin immunoprecipitation-sequencing analyses showed that binding sites of Nrf2(A502Y)-sMaf were dramatically changed from CsMBE to MARE in vivo. Intriguingly, however, one-quarter of the Nrf2(A502Y)-sMaf binding sites also bound Nrf2-sMaf commonly and vice versa. RNA-sequencing analyses revealed that Nrf2(A502Y)-sMaf failed to induce expression of major cytoprotective genes upon stress stimulation, which increased the sensitivity of Nrf2(A502Y) mutant mice to acute acetaminophen toxicity. These results demonstrate that the unique cistrome defined as CsMBE is strictly required for the Nrf2-sMaf heterodimer function in cytoprotection and that the roles played by CsMBE differ sharply from those of MARE.
Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize
Contributors: Oka, Rurika, Zicola, Johan, Weber, Blaise, Anderson, Sarah N., Hodgman, Charlie, Gent, Jonathan I., Wesselink, Jan-Jaap, Springer, Nathan M., Hoefsloot, Huub C. J., Turck, Franziska
... Background: While most cells in multicellular organisms carry the same genetic information, in each cell type only a subset of genes is being transcribed. Such differentiation in gene expression depends, for a large part, on the activation and repression of regulatory sequences, including transcriptional enhancers. Transcriptional enhancers can be located tens of kilobases from their target genes, but display characteristic chromatin and DNA features, allowing their identification by genome-wide profiling. Here we show that integration of chromatin characteristics can be applied to predict distal enhancer candidates in Zea mays, thereby providing a basis for a better understanding of gene regulation in this important crop plant.Result: To predict transcriptional enhancers in the crop plant maize (Zea mays L. ssp. mays), we integrated available genome-wide DNA methylation data with newly generated maps for chromatin accessibility and histone 3 lysine 9 acetylation (H3K9ac) enrichment in young seedling and husk tissue. Approximately 1500 intergenic regions, displaying low DNA methylation, high chromatin accessibility and H3K9ac enrichment, were classified as enhancer candidates. Based on their chromatin profiles, candidate sequences can be classified into four subcategories. Tissue-specificity of enhancer candidates is defined based on the tissues in which they are identified and putative target genes are assigned based on tissue-specific expression patterns of flanking genes.Conclusions: Our method identifies three previously identified distal enhancers in maize, validating the new set of enhancer candidates and enlarging the toolbox for the functional characterization of gene regulation in the highly repetitive maize genome.
Contributors: Alexander, John, Mantzaris, Dimitris, Georgitsi, Marianthi, Drineas, Petros, Paschou, Peristera
... Background: The increasing volume and complexity of high-throughput genomic data make analysis and prioritization of variants difficult for researchers with limited bioinformatics skills. Variant Ranker allows researchers to rank identified variants and determine the most confident variants for experimental validation.Results: We describe Variant Ranker, a user-friendly simple web-based tool for ranking, filtering and annotation of coding and non-coding variants. Variant Ranker facilitates the identification of causal variants based on novelty, effect and annotation information. The algorithm implements and aggregates multiple prediction algorithm scores, conservation scores, allelic frequencies, clinical information and additional open-source annotations using accessible databases via ANNOVAR. The available information for a variant is transformed into user-specified weights, which are in turn encoded into the ranking algorithm. Through its different modules, users can (i) rank a list of variants (ii) perform genotype filtering for case-control samples (iii) filter large amounts of high-throughput data based on user custom filter requirements and apply different models of inheritance (iv) perform downstream functional enrichment analysis through network visualization. Using networks, users can identify clusters of genes that belong to multiple ontology categories (like pathways, gene ontology, disease categories) and therefore expedite scientific discoveries. We demonstrate the utility of Variant Ranker to identify causal genes using real and synthetic datasets. Our results indicate that Variant Ranker exhibits excellent performance by correctly identifying and ranking the candidate genesConclusions: Variant Ranker is a freely available web server on http://paschou-lab.mbg.duth.gr/Software.html. This tool will enable users to prioritise potentially causal variants and is applicable to a wide range of sequencing data.
The Negative Elongation Factor Complex – a poorly understood multi-faceted transcript-processing complex
Contributors: Byron Baron
... With the advent of whole genome screens, promoter-proximal pausing of RNA polymerase II (RNAPII) has been shown to play a much more significant role in eukaryotic systems than previously thought. This type of transcription inhibition is dependent on the binding of the Negative Elongation Factor (NELF) complex which is composed of four sub-units, presenting unique domains and consequently fulfilling different functions. Numerous questions still surround the mechanism by which NELF is recruited, stabilised and dissociated from the RNAPII complex. Furthermore, not much is known about which other transcription stages the NELF complex is involved in and through which sub-units it carries out such functions. Based on the current knowledge of the role of NELF in transcription pausing, it is hypothesised that different interaction partners are required to direct context-specific functions of the NELF complex. This review covers some of the known roles and contexts in which NELF acts in an attempt to identify key questions for future NELF-dependent transcriptional research.
Contributors: Sablowski, R.
... In spite of the different morphologies of sepal, petals, stamen and carpels, all these floral organs are believed to be modified versions of a ground-state organ similar to the leaf. Modifications of the ground-state developmental program are orchestrated by different combinations of MADS-domain transcription factors encoded by floral organ identity genes. In recent years, much has been revealed about the gene regulatory networks controlled by the floral organ identity genes and about the genetic pathways that control leaf development. Here, I review how floral organ identity is connected with the control of morphogenesis and differentiation of shoot organs, focusing on the model species Arabidopsis thaliana. Direct links have emerged between floral organ identity genes and genes involved in abaxial-adaxial patterning, organ boundary formation, tissue growth and cell differentiation. In parallel, predictive models have been developed to explain how the activity of regulatory genes can be coordinated by intercellular signaling and constrained by tissue mechanics. Combined, these advances provide a unique opportunity to reveal how exactly leaf-like organs have been "metamorphosed" into floral organs during evolution and to reveal crucial regulatory points in the generation of plant form.
Contributors: Percha, Bethany, Altman, Russ B.
... This repository contains labeled, weighted networks of chemical-gene, gene-gene, gene-disease, and chemical-disease relationships based on single sentences in PubMed abstracts. All raw dependency paths are provided in addition to the labeled relationships. PART I: Connects dependency paths to labels, or "themes". Each record contains a dependency path followed by its score for each theme, and indicators of whether or not the path is part of the flagship path set for each theme (meaning that it was manually reviewed and determined to reflect that theme). The themes themselves are listed below and are in our paper (reference below). PART II: Connects sentences to dependency paths. It consists of sentences and associated metadata, entity pairs found in the sentences, and dependency paths connecting those entity pairs. Each record contains the following information: PubMed ID Sentence number (0 = title) First entity name, formatted First entity name, location (characters from start of abstract) Second entity name, formatted Second entity name, location First entity name, raw string Second entity name, raw string First entity name, database ID(s) Second entity name, database ID(s) First entity type (Chemical, Gene, Disease) Second entity type (Chemical, Gene, Disease) Dependency path Sentence, tokenized The "with-themes.txt" files only contain dependency paths with corresponding theme assignments from Part I. The plain ".txt" files contain all dependency paths. This release contains the annotated network for the April 30, 2016 version of PubTator, which is described in our paper (below). We will also be releasing an updated version of the network periodically, as the PubTator community continues to release new versions each month or so. ------------------------------------------------------------------------------------ REFERENCES Percha B, Altman RBA (2017) A global network of biomedical relationships derived from text. (Submitted to Bioinformatics; currently in revision.) Percha B, Altman RBA (2015) Learning the structure of biomedical relationships from unstructured text. PLoS Computational Biology, 11(7): e1004216. This project depends on named entity annotations from the PubTator project: https://www.ncbi.nlm.nih.gov/CBBresearch/Lu/Demo/PubTator/ Reference: Wei CH et. al., PubTator: a Web-based text mining tool for assisting Biocuration, Nucleic acids research, 2013, 41 (W1): W518-W522. doi: 10.1093/nar/gkt44 Dependency parsing was provided by the Stanford CoreNLP toolkit: https://stanfordnlp.github.io/CoreNLP/index.html Reference: Manning, Christopher D., Mihai Surdeanu, John Bauer, Jenny Finkel, Steven J. Bethard, and David McClosky. 2014. The Stanford CoreNLP Natural Language Processing Toolkit In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55-60. ------------------------------------------------------------------------------------ THEMES chemical-gene (A+) agonism, activation (A-) antagonism, blocking (B) binding, ligand (esp. receptors) (E+) increases expression/production (E-) decreases expression/production (E) affects expression/production (neutral) (N) inhibits gene-chemical (O) transport, channels (K) metabolism, pharmacokinetics (Z) enzyme activity chemical-disease (T) treatment/therapy (including investigatory) (C) inhibits cell growth (esp. cancers) (Sa) side effect/adverse event (Pr) prevents, suppresses (Pa) alleviates, reduces (J) role in disease pathogenesis disease-chemical (Mp) biomarkers (of disease progression) gene-disease (U) causal mutations (Ud) mutations affecting disease course (D) drug targets (J) role in pathogenesis (Te) possible therapeutic effect (Y) polymorphisms alter risk (G) promotes progression disease-gene (Md) biomarkers (diagnostic) (X) overexpression in disease (L) improper regulation linked to disease gene-gene (B) binding, ligand (esp. receptors) (W) enhances response (V+) activates, stimulates (E+) increases expression/production (E) affects expression/production (neutral) (I) signaling pathway (H) same protein or complex (Rg) regulation (Q) production by cell population