A Bioinformatics Approach to Prioritize Single Nucleotide Polymorphisms in TLRs Signaling Pathway Genes

Document Type : Original Article

Authors
Behnam Alipoor 1
Hamid Ghaedi 2
Mir Davood Omrani 2
Milad Bastami 3
Reza Meshkani 1
Taghi Golmohammadi 1
1 Department of Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
2 Department of Medical Genetics, Faculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3 Department of Medical Genetics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran
Abstract
It has been suggested that single nucleotide polymorphisms (SNPs) in genes involved in Toll-like receptors
(TLRs) pathway may exhibit broad effects on function of this network and might contribute to a range of human
diseases. However, the extent to which these variations affect TLR signaling is not well understood. In this
study, we adopted a bioinformatics approach to predict the consequences of SNPs in TLRs network. The
consequences of non-synonymous coding SNPs (nsSNPs) were predicted by SIFT, PolyPhen, PANTHER,
SNPs&GO, I-Mutant, ConSurf and NetSurf tools. Structural visualization of wild type and mutant protein was
performed using the project HOPE and Swiss PDB viewer. The influence of 5′-UTR and 3′- UTR SNPs were
analyzed by appropriate computational approaches. Nineteen nsSNPs in TLRs pathway genes were found to
have deleterious consequences as predicted by the combination of different algorithms. Moreover, our results
suggested that SNPs located at UTRs of TLRs pathway genes may potentially influence binding of transcription
factors or microRNAs. By applying a pathway-based bioinformatics analysis of genetic variations, we provided
a prioritized list of potentially deleterious variants. These findings may facilitate the selection of proper variants
for future functional and/or association studies.
Keywords
Bioinformatics
in-silico analysis
single nucleotide polymorphisms
toll- like receptors