International Journal of Genetic Engineering 2020, 8(1): 1-6 DOI: 10.5923/j.ijge.20200801.01 Computational Analysis of Single Nucleotide Polymorphism (SNPs) in Human MYOC Gene Amged Mohammed Ibrahim, Afra M. Albakry, Nuha Widat Alla, Mona A. M. Khaeir, Hind. A. Elnasri * Department of Molecular Biology and Bioinformatics, College of Veterinary Medicine, University of Bahri, Khartoum, Sudan Abstract Glaucoma is a disease that damages the eye’s optic nerve. It usually occurs when fluid builds up in the front part of the eye thus increasing the pressure within the eye and damaging the optic nerve. Among the causes of glaucoma is genetic polymorphisms of MYOC gene which can alter the myocilin protein and thus disrupting the regulation of the intraocular pressure which may lead to the disease. This study aimed to analyze nsSNPS in the Myocilin (MYOC) gene and the effect they may have on the protein function and structure. SNPs were obtained from the NCBI dbSNP database. The nsSNPs were further analyzed using 8 prediction tools namely GeneMANIA, SIFT, Polyphen-2, PROVEAN, SNPs & GO, PHD SNP, I-Mutant 3.0 and Project Hope. GeneMANIA results showed the association of MYOC gene with 20 other genes and mainly genes sharing the same protein domain. A total of 16 SNPs were predicted to be disease-associated using all software. Three SNPs were found to increase protein stability while 13 SNPs decreased the stability of the protein. In the current study, some SNPs that were previously reported to be associated with glaucoma were also found to be disease related using different software, while other new SNPs were predicted for the first time. In the future, these SNPs can clinically be tested to investigate their association with the disease. Keywords In silico analysis, MYOC gene, Glaucoma, Bioinformatics 1. Introduction Glaucoma is a complex, heterogeneous ocular disorder with multi factorial etiology characterized by structural damage to the optic nerve, and commonly associated with relatively high intraocular pressure (IOP) [1-2]. It is a leading cause of irreversible blindness worldwide with ~20% of cases occurring secondary to other ocular or systemic diseases [2-4]. Based on anatomical changes in the anterior chamber angle, primary glaucoma may be classified as primary angle closure glaucoma (PACG) or primary open-angle glaucoma (POAG), which may be further subdivided into juvenile open-angle glaucoma (JOAG) and adult onset POAG [1,5]. Glaucoma is a treatable disease if detected early; however, many patients are diagnosed during routine examinations or only following advanced field loss, as glaucoma is typically asymptomatic in the early stages. Therefore, the development of an accurate test for the detection of presymptomatic carriers at risk is important for the management of glaucoma. * Corresponding author: hindnasri2017@gmail.com (Hind. A. Elnasri) Published online at http://journal.sapub.org/ijge Copyright © 2020 The Author(s). Published by Scientific & Academic Publishing This work is licensed under the Creative Commons Attribution International License (CC BY). http://creativecommons.org/licenses/by/4.0/ A family history of glaucoma is a well-known risk factor and hence genetic background is considered an important factor for the development of the disease [6-8]. Several genes have been reported to be associated with primary glaucoma including myocilin (MYOC), WD repeat domain, neurotrophin 1, cytochrome P450 family 1 subtype [9-10]. To date, mutations in these genes account for only ~5% of patients with POAG, and the influence of mutations in these genes on patients with PACG remain controversial [11-12]. The MYOC gene, is located on chromosome 1q24.3-q25.2. Mutations in the gene are commonly found in juvenile or early adult patients with high IOP although mutation frequencies vary between ethnic groups [13]. Bioinformatics is now playing a key role in different scientific areas. It involves computer sciences, mathematics, and statistics in order to analyze biological data that is being produced through the different sequencing techniques. Bio computing plays a key role in understanding the implication of genomic variations, especially single-nucleotide polymorphisms (SNPs), which represent the most frequent genetic variations in the human genome [14]. SNPs are the single base change in coding or non-coding DNA sequence and are present in every 200-300 bp in human genome [15]. The nonsynonymous SNPs (nsSNPs) are the single nucleotide variations that affect the coding region of the protein and modify the mutated site-encoded amino acid, which may lead to a structural modification of