A comprehensive in Silico analysis of the functional and structural impact of single nucleotide polymorphisms (SNPs) in the human IL-33 gene |
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Institution: | 1. Ashok and Rita Patel Institute of Integrated Study and Research in Biotechnology and Allied Sciences (ARIBAS), affiliated to Sardar Patel University, Vallabh Vidyanagar, Gujarat 388120, India;2. College of Veterinary Sciences and Animal Husbandary, Anand Agricutural University, India;3. Muljibhai Patel Urological Hospital, Dr. V.V. Desai Road, Nadiad 387 001, Gujarat, India |
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Abstract: | Interleukin 33 (IL-33) is the latest member of the IL-1 cytokine family, which plays both pro - and anti-inflammatory functions. Numerous Single-nucleotide polymorphisms (SNPs) in the IL-33 gene have been recognized to be associated with a vast variety of inflammatory disorders. SNPs associated studies have become a crucial approach in uncovering the genetic background of human diseases. However, distinguishing the functional SNPs in a disease-related gene from a pool of both functional and neutral SNPs is a major challenge and needs multiple experiments of hundreds or thousands of SNPs in candidate genes. This study aimed to identify the possible deleterious SNPs in the IL-33 gene using bioinformatics predictive tools. The nonsynonymous SNPs (nsSNPs) were analyzed by SIFT, PolyPhen, PROVEAN, SNP&GO, MutPred, SNAP, PhD SNP, and I-Mutant tools. The Non-coding SNPs (ncSNPs) were also analyzed by SNPinfo and RegulomeDB tools. In conclusion, our in-silico analysis predicted 5 nsSNPs and 22 ncSNPs as potential candidates in the IL-33 gene for future genetic association studies. |
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Keywords: | Single-nucleotide polymorphisms (SNPs) Interleukin 33 (IL-33) In silico Computational tools |
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