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Expression Profiles of the Mouse Lung Identify a Molecular Signature of Time-to-Birth

¹ Childrens Hospital Informatics Program, Children's Hospital Boston and Harvard-MIT Division of Health Sciences and Technology, and ² Pulmonary Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts

Correspondence and requests for reprints should be addressed to Thomas J. Mariani, Ph.D., Division of Neonatology and Center for Pediatric Biomedical Research, University of Rochester, 601 Elmwood Ave., Box 850, Rochester, NY 14642. E-mail: Tom_Mariani{at}urmc.rochester.edu

A greater understanding of the regulatory processes contributing to lung development could help ameliorate morbidity and mortality in premature infants and identify individuals at risk for congenital and/or chronic lung diseases. Genomics technologies have provided rich gene expression datasets for the developing lung that enable systems biology approaches for identifying large-scale molecular signatures within this complex phenomenon. Here, we applied unsupervised principal component analysis on two developing lung datasets and identified common dominant transcriptomic signatures. Of particular interest, we identify an overlying biological program we term "time-to-birth," which describes the distance in age from the day of birth. We identify groups of genes contributing to the time-to-birth molecular signature. Statistically overrepresented are genes involved in oxygen and gas transport activity, as expected for a transition to air breathing, as well as host defense function. In addition, we identify genes with expression patterns associated with the initiation of alveolar formation. Finally, we present validation of gene expression patterns across the two datasets, and independent validation of select genes by qPCR and immunohistochemistry. These data contribute to our understanding of genetic components contributing to large-scale biological processes and may be useful, particularly in animal models of abnormal lung development, to predict the state of organ development or preparation for birth.

Key Words: lung development • microarray • principal component analysis

CLINICAL RELEVANCE Lung development is comprised of a series of interrelated morphogenetic events. We identified a molecular signature for birth, consisting of genes involved in this process, based on expression profiling during lung development. These data may be useful in predicting organ development or preparedness for birth.