Integrating multiomics longitudinal data to reconstruct networks underlying lung development

整合多组学纵向数据重建肺发育网络

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作者:Jun Ding, Farida Ahangari, Celia R Espinoza, Divya Chhabra, Teodora Nicola, Xiting Yan, Charitharth V Lal, James S Hagood, Naftali Kaminski, Ziv Bar-Joseph, Namasivayam Ambalavanan

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 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.

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