| 1. |
- Bonn, Stefan, et al.
(author)
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Tissue-specific analysis of chromatin state identifies temporal signatures of enhancer activity during embryonic development.
- 2012
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 44:2
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Journal article (peer-reviewed)abstract
- Chromatin modifications are associated with many aspects of gene expression, yet their role in cellular transitions during development remains elusive. Here, we use a new approach to obtain cell type-specific information on chromatin state and RNA polymerase II (Pol II) occupancy within the multicellular Drosophila melanogaster embryo. We directly assessed the relationship between chromatin modifications and the spatio-temporal activity of enhancers. Rather than having a unique chromatin state, active developmental enhancers show heterogeneous histone modifications and Pol II occupancy. Despite this complexity, combined chromatin signatures and Pol II presence are sufficient to predict enhancer activity de novo. Pol II recruitment is highly predictive of the timing of enhancer activity and seems dependent on the timing and location of transcription factor binding. Chromatin modifications typically demarcate large regulatory regions encompassing multiple enhancers, whereas local changes in nucleosome positioning and Pol II occupancy delineate single active enhancers. This cell type-specific view identifies dynamic enhancer usage, an essential step in deciphering developmental networks.
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| 2. |
- Stepniak, Karolina, et al.
(author)
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Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas
- 2021
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In: Nature Communications. - : Springer Nature. - 2041-1723. ; 12:1
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Journal article (peer-reviewed)abstract
- Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We perform whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we create an atlas of active enhancers and promoters in benign and malignant gliomas. We explore these elements and intersect with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas. Gliomas are tumors often associated with epigenetics-related gene deregulation. Here the authors reveal an atlas of active enhancers and promoters in benign and malignant gliomas by performing whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples.
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| 3. |
- Wilczyński, Bartek, et al.
(author)
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A computer scientist's guide to the regulatory genome
- 2010
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In: Fundamenta Informaticae. - : IOS Press. - 0169-2968 .- 1875-8681. ; 103:1-4, s. 323-332
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Journal article (peer-reviewed)abstract
- Recent years have seen a wealth of computational methods applied to problems stemming from molecular biology. In particular, with the completion of many new full genome sequences, great advances have been made in studying the role of non-protein-coding parts of the genome, reshaping our understanding of the role of DNA sequences. Recent breakthroughs in experimental technologies allowing us to inspect the innards of cells on a genomic scale has provided us with unprecedented amounts of data, posing new computational challenges for scientists working to uncover the secrets of life. Due to the binary-like nature of the DNA code and switch-like behavior of many regulatory mechanisms, many of the questions that are currently in focus in biology are surprisingly related to problems that have been of long-term interest to computer scientists. In this review, we present a glimpse into the current state of research in computational methods applied to modeling the regulatory genome. Our aim is to cover current approaches to selected problems from molecular biology that we consider most interesting from the perspective of computer scientists as well as highlight new challenges that will most likely draw the attention of computational biologists in the coming years.
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| 4. |
- Wilczynski, Bartek, et al.
(author)
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Using local gene expression similarities to discover regulatory binding site modules
- 2006
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 7, s. 505-
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Journal article (peer-reviewed)abstract
- Background: We present an approach designed to identify gene regulation patterns using sequence and expression data collected for Saccharomyces cerevisae. Our main goal is to relate the combinations of transcription factor binding sites (also referred to as binding site modules) identified in gene promoters to the expression of these genes. The novel aspects include local expression similarity clustering and an exact IF-THEN rule inference algorithm. We also provide a method of rule generalization to include genes with unknown expression profiles. Results: We have implemented the proposed framework and tested it on publicly available datasets from yeast S. cerevisae. The testing procedure consists of thorough statistical analyses of the groups of genes matching the rules we infer from expression data against known sets of coregulated genes. For this purpose we have used published ChIP-Chip data and Gene Ontology annotations. In order to make these tests more objective we compare our results with recently published similar studies. Conclusion: Results we obtain show that local expression similarity clustering greatly enhances overall quality of the derived rules, both in terms of enrichment of Gene Ontology functional annotation and coherence with ChIP-Chip binding data. Our approach thus provides reliable hypotheses on co-regulation that can be experimentally verified. An important feature of the method is its reliance only on widely accessible sequence and expression data. The same procedure can be easily applied to other microbial organisms.
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