A Comprehensive In-Silico Analysis of Deleterious Missense SNPs in Human Trehalase Gene: Gaining an Interactome Insights into Type 2 Diabetes Mellitus GC01-GC06
Asura Khanam Lisa,
Lecturer, Department of Biotechnology and Genetic Engineering,
Bangabandhu Sheikh Mujibur Rahman Science and Technology University,
E-mail: firstname.lastname@example.org; email@example.com
Introduction: Trehalase (TREH), a glycoside hydrolase enzyme that catalyses the conversion of trehalose to glucose in sugar metabolism. In spite of severe health threats caused by diabetes worldwide, no systematic and programmed study on human TREH Single Nucleotide Polymorphism (SNPs) and its functional role in Type 2 Diabetes Mellitus (T2DM) has been performed.
Aim: This study aimed to identify pathogenic missense SNPs in the human TREH gene.
Materials and Methods: A series of different bioinformatic tools including SIFT, Polyphen, I-mutant, Variant Effect Predictor, Project Hope and GeneMANNIA were used for this study. At all stages, a p-value of 0.05 was considered as statistically significant.
Results: This study demonstrated 10 potential mutations out of 241 missense human TREH SNPs from the dbSNP database of NCBI, three of which confirmed to have damaging effects on protein function. Out of these three, rs535722007 had the most deleterious effect that altered secondary properties and tertiary structure of the experimental TREH protein and decreased the stability. Further analysis showed a strong connection among TREH, Insulin (INS), and other genes of carbohydrate metabolism associated with T2DM. Gene expression studies found the down-regulation of TREH in all of the experimental studies linked toT2DM.
Conclusion: As the probability of the disease predisposition increases with SNPs in primary or co-expressed gene(s), therefore, characterisation of TREH SNPs from human and its gene networking analysis can aid in better understanding of genetic variations and signalling pathways as well as to elucidate the effective diagnostic and treatment strategies.