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    Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics

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    Type
    Article
    Authors
    Roy, S.
    Schmeier, S.
    Arner, E.
    Alam, Tanvir cc
    Parihar, S. P.
    Ozturk, M.
    Tamgue, O.
    Kawaji, H.
    de Hoon, M. J. L.
    Itoh, M.
    Lassmann, T.
    Carninci, P.
    Hayashizaki, Y.
    Forrest, A. R. R.
    Bajic, Vladimir B. cc
    Guler, R.
    Consortium, F.
    Brombacher, F.
    Suzuki, H.
    KAUST Department
    Computational Bioscience Research Center (CBRC)
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Computer Science Program
    Applied Mathematics and Computational Science Program
    Date
    2015-06-27
    Online Publication Date
    2015-06-27
    Print Publication Date
    2015-08-18
    Permanent link to this record
    http://hdl.handle.net/10754/558766
    
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    Abstract
    Classically or alternatively activated macrophages (M1 and M2, respectively) play distinct and important roles for microbiocidal activity, regulation of inflammation and tissue homeostasis. Despite this, their transcriptional regulatory dynamics are poorly understood. Using promoter-level expression profiling by non-biased deepCAGE we have studied the transcriptional dynamics of classically and alternatively activated macrophages. Transcription factor (TF) binding motif activity analysis revealed four motifs, NFKB1_REL_RELA, IRF1,2, IRF7 and TBP that are commonly activated but have distinct activity dynamics in M1 and M2 activation. We observe matching changes in the expression profiles of the corresponding TFs and show that only a restricted set of TFs change expression. There is an overall drastic and transient up-regulation in M1 and a weaker and more sustainable up-regulation in M2. Novel TFs, such as Thap6, Maff, (M1) and Hivep1, Nfil3, Prdm1, (M2) among others, were suggested to be involved in the activation processes. Additionally, 52 (M1) and 67 (M2) novel differentially expressed genes and, for the first time, several differentially expressed long non-coding RNA (lncRNA) transcriptome markers were identified. In conclusion, the finding of novel motifs, TFs and protein-coding and lncRNA genes is an important step forward to fully understand the transcriptional machinery of macrophage activation.
    Citation
    Redefining the transcriptional regulatory dynamics of classically and alternatively activated macrophages by deepCAGE transcriptomics 2015 Nucleic Acids Research
    Publisher
    Oxford University Press (OUP)
    Journal
    Nucleic Acids Research
    DOI
    10.1093/nar/gkv646
    PubMed ID
    26117544
    Additional Links
    http://nar.oxfordjournals.org/lookup/doi/10.1093/nar/gkv646
    ae974a485f413a2113503eed53cd6c53
    10.1093/nar/gkv646
    Scopus Count
    Collections
    Articles; Applied Mathematics and Computational Science Program; Computer Science Program; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

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