| First Author | Ding J | Year | 2019 |
| Journal | Am J Physiol Lung Cell Mol Physiol | Volume | 317 |
| Issue | 5 | Pages | L556-L568 |
| PubMed ID | 31432713 | Mgi Jnum | J:281586 |
| Mgi Id | MGI:6369778 | Doi | 10.1152/ajplung.00554.2018 |
| Citation | Ding J, et al. (2019) Integrating multiomics longitudinal data to reconstruct networks underlying lung development. Am J Physiol Lung Cell Mol Physiol 317(5):L556-L568 |
| abstractText | 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 RNA-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 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. |
