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  • 1
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    Reprogramming of T cells to natural killer-like cells upon Bcl11b deletion (2010)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2010-06-12
    Description: T cells develop in the thymus and are critical for adaptive immunity. Natural killer (NK) lymphocytes constitute an essential component of the innate immune system in tumor surveillance, reproduction, and defense against microbes and viruses. Here, we show that the transcription factor Bcl11b was expressed in all T cell compartments and was indispensable for T lineage development. When Bcl11b was deleted, T cells from all developmental stages acquired NK cell properties and concomitantly lost or decreased T cell-associated gene expression. These induced T-to-natural killer (ITNK) cells, which were morphologically and genetically similar to conventional NK cells, killed tumor cells in vitro, and effectively prevented tumor metastasis in vivo. Therefore, ITNKs may represent a new cell source for cell-based therapies.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628452/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3628452/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Li, Peng -- Burke, Shannon -- Wang, Juexuan -- Chen, Xiongfeng -- Ortiz, Mariaestela -- Lee, Song-Choon -- Lu, Dong -- Campos, Lia -- Goulding, David -- Ng, Bee Ling -- Dougan, Gordon -- Huntly, Brian -- Gottgens, Bertie -- Jenkins, Nancy A -- Copeland, Neal G -- Colucci, Francesco -- Liu, Pentao -- 076962/Wellcome Trust/United Kingdom -- 077186/Wellcome Trust/United Kingdom -- G0501150/Medical Research Council/United Kingdom -- G0800784/Medical Research Council/United Kingdom -- G116/187/Medical Research Council/United Kingdom -- Biotechnology and Biological Sciences Research Council/United Kingdom -- Wellcome Trust/United Kingdom -- Medical Research Council/United Kingdom -- New York, N.Y. -- Science. 2010 Jul 2;329(5987):85-9. doi: 10.1126/science.1188063. Epub 2010 Jun 10.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Sanger Institute, Hinxton, Cambridge CB10 1HH, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/20538915" target="_blank"〉PubMed〈/a〉
    Keywords: Animals ; Cell Line, Tumor ; *Cell Lineage ; Cells, Cultured ; Coculture Techniques ; Cytotoxicity, Immunologic ; Gene Deletion ; Gene Expression Profiling ; Gene Expression Regulation, Developmental ; Gene Knock-In Techniques ; Genes, T-Cell Receptor beta ; Killer Cells, Natural/cytology/immunology/*physiology ; *Lymphopoiesis/genetics ; Melanoma, Experimental/immunology/therapy ; Mice ; Mice, Inbred C57BL ; Mice, Knockout ; Oligonucleotide Array Sequence Analysis ; Precursor Cells, T-Lymphoid/cytology/physiology ; Receptors, Antigen, T-Cell, alpha-beta/metabolism ; Repressor Proteins/*genetics/*metabolism ; Signal Transduction ; Stromal Cells/cytology/physiology ; T-Lymphocytes/cytology/immunology/*physiology/transplantation ; Tamoxifen/analogs & derivatives/pharmacology ; Tumor Suppressor Proteins/*genetics/*metabolism
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Constrained transcription factor spacing is prevalent and important for transcriptional control of mouse blood cells (2014)
    Oxford University Press
    Details
    Publication Date: 2014-12-17
    Description: Combinatorial transcription factor (TF) binding is essential for cell-type-specific gene regulation. However, much remains to be learned about the mechanisms of TF interactions, including to what extent constrained spacing and orientation of interacting TFs are critical for regulatory element activity. To examine the relative prevalence of the ‘enhanceosome’ versus the ‘TF collective’ model of combinatorial TF binding, a comprehensive analysis of TF binding site sequences in large scale datasets is necessary. We developed a motif-pair discovery pipeline to identify motif co-occurrences with preferential distance(s) between motifs in TF-bound regions. Utilizing a compendium of 289 mouse haematopoietic TF ChIP-seq datasets, we demonstrate that haematopoietic-related motif-pairs commonly occur with highly conserved constrained spacing and orientation between motifs. Furthermore, motif clustering revealed specific associations for both heterotypic and homotypic motif-pairs with particular haematopoietic cell types. We also showed that disrupting the spacing between motif-pairs significantly affects transcriptional activity in a well-known motif-pair—E-box and GATA, and in two previously unknown motif-pairs with constrained spacing—Ets and Homeobox as well as Ets and E-box. In this study, we provide evidence for widespread sequence-specific TF pair interaction with DNA that conforms to the ‘enhanceosome’ model, and furthermore identify associations between specific haematopoietic cell-types and motif-pairs.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 3
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    TRES predicts transcription control in embryonic stem cells (2014)
    Oxford University Press
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    Publication Date: 2014-10-04
    Description: : Unraveling transcriptional circuits controlling embryonic stem cell maintenance and fate has great potential for improving our understanding of normal development as well as disease. To facilitate this, we have developed a novel web tool called ‘TRES’ that predicts the likely upstream regulators for a given gene list. This is achieved by integrating transcription factor (TF) binding events from 187 ChIP-sequencing and ChIP-on-chip datasets in murine and human embryonic stem (ES) cells with over 1000 mammalian TF sequence motifs. Using 114 TF perturbation gene sets, as well as 115 co-expression clusters in ES cells, we validate the utility of this approach. Availability and implementation: TRES is freely available at http://www.tres.roslin.ed.ac.uk . Contact: Anagha.Joshi@roslin.ed.ac.uk or bg200@cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 4
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    Probabilistic PCA of censored data: accounting for uncertainties in the visualization of high-throughput single-cell qPCR data (2014)
    Oxford University Press
    Details
    Publication Date: 2014-06-27
    Description: Motivation: High-throughput single-cell quantitative real-time polymerase chain reaction (qPCR) is a promising technique allowing for new insights in complex cellular processes. However, the PCR reaction can be detected only up to a certain detection limit, whereas failed reactions could be due to low or absent expression, and the true expression level is unknown. Because this censoring can occur for high proportions of the data, it is one of the main challenges when dealing with single-cell qPCR data. Principal component analysis (PCA) is an important tool for visualizing the structure of high-dimensional data as well as for identifying subpopulations of cells. However, to date it is not clear how to perform a PCA of censored data. We present a probabilistic approach that accounts for the censoring and evaluate it for two typical datasets containing single-cell qPCR data. Results: We use the Gaussian process latent variable model framework to account for censoring by introducing an appropriate noise model and allowing a different kernel for each dimension. We evaluate this new approach for two typical qPCR datasets (of mouse embryonic stem cells and blood stem/progenitor cells, respectively) by performing linear and non-linear probabilistic PCA. Taking the censoring into account results in a 2D representation of the data, which better reflects its known structure: in both datasets, our new approach results in a better separation of known cell types and is able to reveal subpopulations in one dataset that could not be resolved using standard PCA. Availability and implementation: The implementation was based on the existing Gaussian process latent variable model toolbox ( https://github.com/SheffieldML/GPmat ); extensions for noise models and kernels accounting for censoring are available at http://icb.helmholtz-muenchen.de/censgplvm . Contact: fbuettner.phys@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 5
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    Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model (2013)
    Oxford University Press
    Details
    Publication Date: 2013-06-24
    Description: Motivation: Combinatorial interactions of transcription factors with cis -regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis -regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis -regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis -regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. Results: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as ‘stepping stones’ for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or ‘trigger’ is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis -regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. Contact: j.heringa@vu.nl or ioannis.xenarios@isb-sib.ch or bg200@cam.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
    Print ISSN: 1367-4803
    Electronic ISSN: 1460-2059
    Topics: Biology , Computer Science , Medicine
    Published by Oxford University Press
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  • 6
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    Key regulators control distinct transcriptional programmes in blood progenitor and mast cells (2014)
    EMBO Press
    Details
    Publication Date: 2014-04-23
    Print ISSN: 0261-4189
    Electronic ISSN: 1460-2075
    Topics: Biology , Medicine
    Published by EMBO Press on behalf of European Molecular Biology Organization.
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