A database of annotated promoters of genes associated with common respiratory and related diseases

R. Chowdhary, S.L. Tan, G. Pavesi, J. Jin, D. Dong, S.K. Mathur, A. Burkart, V. Narang, I. Glurich, B.A. Raby, S.T. Weiss, L. Wong, J.S. Liu, V.B. Bajic
Am J Respir Cell Mol Biol, 47(1):112-119, (2012)

Keywords

Allergic rhinitis, Asthma, Bronchiectasis, Bronchiolitis, Bronchitis, COPD, Cystic fibrosis, Emphysema, Eczema, Psoriasis, Urticaria, Respiratory/pulmonary disease genes, Promoter analysis, Transcription factor binding sites, Pathways, SNPs, Promoter motifs, Systems/network biology

Abstract

Many genes have been implicated in the pathogenesis of common respiratory and related diseases (RRDs), yet the underlying mechanisms are largely unknown. Differential gene expression patterns in diseased and healthy individuals suggest that RRDs affect or are affected by modified transcription regulation programs. It is thus crucial to characterize implicated genes in terms of transcriptional regulation. For this purpose, we conducted a promoter analysis of genes associated with 11 common RRDs including allergic rhinitis, asthma, bronchiectasis, bronchiolitis, bronchitis, chronic obstructive pulmonary disease, cystic fibrosis, emphysema, eczema, psoriasis, and urticaria, many of which are thought to be genetically related. The objective of the present study was to obtain deeper insight into the transcriptional regulation of these disease-associated genes by annotating their promoter regions with transcription factors (TFs) and TF binding sites (TFBSs). We discovered many TFs that are significantly enriched in the target disease groups including associations that have been documented in the literature. We also identified a number of putative TFs/TFBSs that appear to be novel. The results of our analysis are provided in an online database that is freely accessible to researchers at http://www.respiratorygenomics.com. Promoter-associated TFBS information and related genomic features, such as histone modification sites, microsatellites, CpG islands, and SNPs, are graphically summarized in the database. Users can compare and contrast underlying mechanisms of specific RRDs relative to candidate genes, TFs, gene ontology terms, micro–RNAs, and biological pathways for the conduct of metaanalyses. This database represents a novel, useful resource for RRD researchers.


Code

DOI: 10.1165/rcmb.2011-0419OC

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