Integrating multi-omics longitudinal data to reconstruct networks underlying lung development.

Integrating multi-omics longitudinal data to reconstruct networks underlying lung development.
Am J Physiol Lung Cell Mol Physiol. 2019 Aug 21;:
Authors: Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N
Abstract
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 (scRNA-Seq) 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 datasets. 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.
PMID: 31432713 [PubMed - as supplied by publisher]

Source: American Journal of Physiology. Lung Cellular and Molecular Physiology - August 20, 2019 Category: Cytology Authors: Ding J, Ahangari F, Espinoza CR, Chhabra D, Nicola T, Yan X, Lal CV, Hagood JS, Kaminski N, Bar-Joseph Z, Ambalavanan N Tags: Am J Physiol Lung Cell Mol Physiol Source Type: research