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    Transcriptome and H3K27 tri-methylation profiling of Ezh2-deficient lung epithelium

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    Author
    Holik, AZ; Galvis, LA; Lun, ATL; Ritchie, ME; Asselin-Labat, M-L
    Date
    2015-09-01
    Source Title
    Genomics Data
    Publisher
    ELSEVIER SCIENCE BV
    University of Melbourne Author/s
    Asselin-Labat, Marie-Liesse; Ritchie, Matthew; HOLIK, ALIAKSEI; Lun, Aaron Tin Long
    Affiliation
    Medical Biology (W.E.H.I.)
    Metadata
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    Document Type
    Journal Article
    Citations
    Holik, A. Z., Galvis, L. A., Lun, A. T. L., Ritchie, M. E. & Asselin-Labat, M. -L. (2015). Transcriptome and H3K27 tri-methylation profiling of Ezh2-deficient lung epithelium. GENOMICS DATA, 5, pp.346-351. https://doi.org/10.1016/j.gdata.2015.07.006.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/257689
    DOI
    10.1016/j.gdata.2015.07.006
    Abstract
    The adaptation of the lungs to air breathing at birth requires the fine orchestration of different processes to control lung morphogenesis and progenitor cell differentiation. However, there is little understanding of the role that epigenetic modifiers play in the control of lung development. We found that the histone methyl transferase Ezh2 plays a critical role in lung lineage specification and survival at birth. We performed a genome-wide transcriptome study combined with a genome-wide analysis of the distribution of H3K27 tri-methylation marks to interrogate the role of Ezh2 in lung epithelial cells. Lung cells isolated from Ezh2-deficient and control mice at embryonic day E16.5 were sorted into epithelial and mesenchymal populations based on EpCAM expression. This enabled us to dissect the transcriptional and epigenetic changes induced by the loss of Ezh2 specifically in the lung epithelium. Here we provide a detailed description of the analysis of the RNA-seq and ChIP-seq data, including quality control, read mapping, differential expression and differential binding analyses, as well as visualisation methods used to present the data. These data can be accessed from the Gene Expression Omnibus database (super-series accession number GSE57393).

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