Integrating multiomics longitudinal data to reconstruct networks underlying lung development.

Autor: Jun Ding, Ahangari, Farida, Espinoza, Celia R., Chhabra, Divya, Nicola, Teodora, Xiting Yan, Lal, Charitharth V., Hagood, James S., Kaminski, Naftali, Bar-Joseph, Ziv, Ambalavanan, Namasivayam
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Zdroj: American Journal of Physiology: Lung Cellular & Molecular Physiology; Nov2019, Vol. 317 Issue 5, pL556-L568, 13p
Abstrakt: A comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. To construct such a model, we profiled mRNA, microRNA, DNA methylation, and proteomics of developing murine alveoli isolated by laser capture microdissection at 14 predetermined time points. We developed a detailed comprehensive and interactive model that provides information about the major expression trajectories, the regulators of specific key events, and the impact of epigenetic changes. Intersecting the model with single-cell RNASeq data led to the identification of active pathways in multiple or individual cell types. We then constructed a similar model for human lung development by profiling time-series human omics data sets. Several key pathways and regulators are shared between the reconstructed models. We experimentally validated the activity of a number of predicted regulators, leading to new insights about the regulation of innate immunity during lung development. [ABSTRACT FROM AUTHOR]
Databáze: Complementary Index