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Systems Biology Approaches for Elucidation of the Transcriptional Regulation of Pulmonary Maturation

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Part of the book series: Translational Bioinformatics ((TRBIO,volume 10))

Abstract

Surfactant deficiency associated with lung immaturity is a major cause of morbidity and mortality in preterm infants resulting in acute respiratory failure (termed “respiratory distress syndrome” or RDS) and chronic respiratory dysfunction (bronchopulmonary dysplasia or BPD). The lack of surfactant lipids and proteins needed to reduce surface tension at the air-liquid interface in the peripheral lung saccules, causes atelectasis and respiratory insufficiency after preterm birth. Lung “maturation” is a complex process involving diverse structural, cellular, and biochemical changes in lung architecture and function that are precisely coordinated by genetic and environmental factors that synchronize the length of gestation with lung maturation. We developed computational tools utilizing systems biology and single cell genomics strategies to analyze large-scale mRNA expression data from distinct technical platforms and biological contexts to: (1) identify signature genes, (2) predict transcriptional regulators driving epithelial cell differentiation, and (3) model transcriptional regulatory networks (TRN) controlling perinatal lung maturation. The signaling and transcriptional mechanisms controlling lung growth and maturation required for the abrupt adaptation to airbreathing at birth are of considerable clinical interest, with the hope of preventing and treating neonatal pulmonary disease. This chapter provides practical analytic strategies to utilize bioinformatics tools to integrate large-scale lung gene expression data with independent genomic information to predict transcriptional networks controlling lung maturation and surfactant homeostasis.

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Xu, Y., Whitsett, J.A. (2016). Systems Biology Approaches for Elucidation of the Transcriptional Regulation of Pulmonary Maturation. In: Hutton, J. (eds) Pediatric Biomedical Informatics. Translational Bioinformatics, vol 10. Springer, Singapore. https://doi.org/10.1007/978-981-10-1104-7_19

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