4.6 Article

Integrated Transcriptomic and Epigenomic Analysis of Primary Human Lung Epithelial Cell Differentiation

Journal

PLOS GENETICS
Volume 9, Issue 6, Pages -

Publisher

PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pgen.1003513

Keywords

-

Funding

  1. NIH [1 R01 P30 H10125, 81 HL114094, R37HL062569-13]
  2. Whittier Foundation
  3. Hastings Foundation
  4. Ralph Edgington Chair in Medicine
  5. ACS/Canary postdoctoral fellowship [PFTED-10-207-01-SIED]
  6. National Institute of Health Fellowship [T32 CA009320]
  7. Norris Comprehensive Cancer Center from the National Cancer Institute [P30CA014089]

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Elucidation of the epigenetic basis for cell-type specific gene regulation is key to gaining a full understanding of how the distinct phenotypes of differentiated cells are achieved and maintained. Here we examined how epigenetic changes are integrated with transcriptional activation to determine cell phenotype during differentiation. We performed epigenomic profiling in conjunction with transcriptomic profiling using in vitro differentiation of human primary alveolar epithelial cells (AEC). This model recapitulates an in vivo process in which AEC transition from one differentiated cell type to another during regeneration following lung injury. Interrogation of histone marks over time revealed enrichment of specific transcription factor binding motifs within regions of changing chromatin structure. Cross-referencing of these motifs with pathways showing transcriptional changes revealed known regulatory pathways of distal alveolar differentiation, such as the WNT and transforming growth factor beta (TGFB) pathways, and putative novel regulators of adult AEC differentiation including hepatocyte nuclear factor 4 alpha (HNF4A), and the retinoid X receptor (RXR) signaling pathways. Inhibition of the RXR pathway confirmed its functional relevance for alveolar differentiation. Our incorporation of epigenetic data allowed specific identification of transcription factors that are potential direct upstream regulators of the differentiation process, demonstrating the power of this approach. Integration of epigenomic data with transcriptomic profiling has broad application for the identification of regulatory pathways in other models of differentiation.

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