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Integration of transcriptomic and proteomic data identifies biological functions in cell populations from human infant lung

Journal Article · · American Journal of Physiology-Lung Cellular and Molecular Physiology
 [1];  [2];  [3];  [4];  [5];  [6];  [7];  [7];  [8];  [7];  [7];  [1];  [2];  [1]
  1. Cincinnati Children's Hospital Medical Center
  2. BATTELLE (PACIFIC NW LAB)
  3. Children's Hospital of Los Angeles
  4. University of Southern California
  5. Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center
  6. Division of Pulmonary Biology, Cincinnati Children's Hospital Medical Center
  7. University of Rochester
  8. Children’s Hospital of Los Angeles

Systems biology uses computational approaches to integrate diverse data types to understand cell and organ behavior. Data derived from complementary technologies, for example transcriptomic and proteomic analyses, are providing new insights into development and disease. We compared mRNA and protein profiles from purified endothelial, epithelial, immune, and mesenchymal cells from normal human lung tissue. Signatures for each cell type were identified and compared at both mRNA and protein levels. Cell specific biological processes and pathways were predicted by analysis of concordant and discordant RNA-protein pairs. Cell clustering and gene set enrichment comparisons identified shared versus unique processes associated with transcriptomic and/or proteomic data. Clear cell-cell correlations between mRNA and protein data were obtained from each cell type. Approximately 40% of RNA-protein pairs were coherently expressed. While the correlation between RNA and their protein products was relatively low (approximately 0.4), cell specific signature genes involved in functional processes characteristic of each cell type, were more highly correlated with their protein products. Consistency of cell specific RNA-protein signatures indicated an essential framework for the function of each cell type. Visualization and reutilization of the protein and RNA profiles are supported by a new web application, "LungProteomics," which is incorporated into the LGEA web portal and freely accessible at (https://research.cchmc.org/pbge/lunggens/lungProteomics/human_sorted_profiles.html).

Research Organization:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
AC05-76RL01830
OSTI ID:
1560147
Report Number(s):
PNNL-SA-142451
Journal Information:
American Journal of Physiology-Lung Cellular and Molecular Physiology, Vol. 317, Issue 3
Country of Publication:
United States
Language:
English

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