Computational analysis of glycogenes from mouse RNA-SEQ data

Abstract

Glycogenes regulate a wide array of biological processes in the development of organisms as well as different diseases such as cancer, primary open-angle glaucoma, and renal dysfunction. The objective of this study was to explore the role of differentially expressed glycogenes (DEGGs) in three major tissues such as brain, muscle, and liver using mouse RNA-seq data, and we identified 579, 501, and 442 DEGGs for brain versus liver (BvL579), brain versus muscle (BvM501), and liver versus muscle (LvM442) groups. DAVID functional analysis suggested inflammatory response, glycosaminoglycan metabolic process, and protein maturation as the enriched biological processes in BvL579, BvM501, and LvM442, respectively. These DEGGs were then used to construct three interaction networks by using GeneMANIA, from which we detected potential hub genes such as PEMT and HPXN (BvL579), IGF2 and NID2 (BvM501), and STAT6 and FLT1 (LvM442), having the highest degree. Community analysis of DEGGs suggests the significance of immune system related processes in liver, glycosphingolipid metabolic processes in the development of brain, and the processes such as cell proliferation, adhesion, and growth are important for muscle development. Additionally, an interaction network of non-redundant list of 923 glycogenes was also created by combining all identified glycogenes of brain, muscle and liver tissues, to detect potential hubs from different mouse tissues. SLC2A4, TNFRSF1B, TRFR2, and UCHL1 were identified as hub genes by calculating the node degree distribution using Network Analyzer plugin of Cytoscape. We also explored nsSNPs that may modify the expression and function of identified hubs using computational methods. We observe that the number of nsSNPs predicted by any two methods to affect protein function is 4, 7 and 2 for FLT1, NID2 and TNFRSF1B. Residues in the iv native and mutant proteins were analyzed for solvent accessibility and secondary structure change. Analysis of hubs can help in determining their degree of conservation and understanding their functions in biological processes. Further studies are required to confirm the role of these predicted hub genes as well as the significance of biological processes. The nsSNPs proposed in this work may also be further targeted through experimental methods for understanding structural and functional relationships of hub mutants.