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Network Biology, 2021, 11(3): 137-153
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Article

In silico search for regulatory genes associated with lung and liver disease in Cystic Fibrosis

Rafat Ali, Safia Tazyeen, Mohd Murshad Ahmed, Aftab Alam, Nikhat Imam, Shahnawaz Ali, Md Zubbair Malik, Romana Ishrat
Computational Biology Lab, Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia (A Central University), New Delhi 110025, India

Received 6 March 2021;Accepted 15 April 2021;Published 1 September 2021
IAEES

Abstract
The pathogenesis of Cystic Fibrosis (CF) airway disease is not well understood. CF is an autosomal recessive monogenic genetic disease. It affects the exocrine glands, which normally produce thin secretions such as mucus, sweat and tears. In CF, the mucus is thick and sticky which interferes with certain normal organs. A broad knowledge of the genes which are involved in the regulation or co-regulation of affected organs in the CF is required to get a better understanding of its pathophysiological mechanisms. DNA microarray approaches have made it possible to get an insight on gene expression across the genome. In the current study, microarray data related to CF and CF-associated affected organs were retrieved from the NCBS Gene Expression Omnibus database and were subjected to gene regulatory network analysis. We constructed two separated networks of up and down regulated genes from six microarray datasets. The power-law obeying topological properties showed scale-free hierarchical nature of the both networks. Density and compactness of both networks at each level was calculated by modularity and Hamiltonian energy. From all the leading hubs we found four key genes namely GSTT1, ANKRD7, PBX1, and TGFB2 deeply rooted in up and down regulated networks respectively. Conclusively these genes may have prognostic significance.

Keywords Cystic Fibrosis;microarray;modularity;Hamiltonian Energy;GSTT1;ANKRD7;PBX1;TGFB2.

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