ALBERT

All Library Books, journals and Electronic Records Telegrafenberg

feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Publication Date: 2014-07-22
    Description: Developmental enhancers initiate transcription and are fundamental to our understanding of developmental networks, evolution and disease. Despite their importance, the properties governing enhancer-promoter interactions and their dynamics during embryogenesis remain unclear. At the beta-globin locus, enhancer-promoter interactions appear dynamic and cell-type specific, whereas at the HoxD locus they are stable and ubiquitous, being present in tissues where the target genes are not expressed. The extent to which preformed enhancer-promoter conformations exist at other, more typical, loci and how transcription is eventually triggered is unclear. Here we generated a high-resolution map of enhancer three-dimensional contacts during Drosophila embryogenesis, covering two developmental stages and tissue contexts, at unprecedented resolution. Although local regulatory interactions are common, long-range interactions are highly prevalent within the compact Drosophila genome. Each enhancer contacts multiple enhancers, and promoters with similar expression, suggesting a role in their co-regulation. Notably, most interactions appear unchanged between tissue context and across development, arising before gene activation, and are frequently associated with paused RNA polymerase. Our results indicate that the general topology governing enhancer contacts is conserved from flies to humans and suggest that transcription initiates from preformed enhancer-promoter loops through release of paused polymerase.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Ghavi-Helm, Yad -- Klein, Felix A -- Pakozdi, Tibor -- Ciglar, Lucia -- Noordermeer, Daan -- Huber, Wolfgang -- Furlong, Eileen E M -- England -- Nature. 2014 Aug 7;512(7512):96-100. doi: 10.1038/nature13417. Epub 2014 Jul 2.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉European Molecular Biology Laboratory, Genome Biology Unit, D-69117 Heidelberg, Germany. ; 1] European Molecular Biology Laboratory, Genome Biology Unit, D-69117 Heidelberg, Germany [2]. ; Swiss Federal Institute of Technology, School of Life Sciences, CH-1015 Lausanne, Switzerland.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25043061" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Binding Sites ; Chromosomes, Insect/genetics/metabolism ; DNA-Directed RNA Polymerases/*metabolism ; Drosophila melanogaster/embryology/*enzymology/*genetics ; Embryonic Development/*genetics ; Enhancer Elements, Genetic/*genetics ; Gene Expression Regulation, Developmental/genetics ; Genetic Loci/genetics ; Genome, Insect/genetics ; Humans ; Promoter Regions, Genetic/*genetics ; Transcription Initiation, Genetic ; Transcriptional Activation
    Print ISSN: 0028-0836
    Electronic ISSN: 1476-4687
    Topics: Biology , Chemistry and Pharmacology , Medicine , Natural Sciences in General , Physics
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
  • 2
    Publication Date: 2015-09-22
    Description: Motivation: Circularized Chromosome Conformation Capture (4C) is a powerful technique for studying the spatial interactions of a specific genomic region called the ‘viewpoint’ with the rest of the genome, both in a single condition or comparing different experimental conditions or cell types. Observed ligation frequencies typically show a strong, regular dependence on genomic distance from the viewpoint, on top of which specific interaction peaks are superimposed. Here, we address the computational task to find these specific peaks and to detect changes between different biological conditions. Results: We model the overall trend of decreasing interaction frequency with genomic distance by fitting a smooth monotonically decreasing function to suitably transformed count data. Based on the fit, z -scores are calculated from the residuals, and high z -scores are interpreted as peaks providing evidence for specific interactions. To compare different conditions, we normalize fragment counts between samples, and call for differential contact frequencies using the statistical method DESeq2 adapted from RNA-Seq analysis. Availability and implementation: A full end-to-end analysis pipeline is implemented in the R package FourCSeq available at www.bioconductor.org . Contact: felix.klein@embl.de or whuber@embl.de Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Location Call Number Expected Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...