IN-SILICO ANALYSIS OF SNPs FROM cAMP-GEFII GENE ASSOCIATED WITH POLYCYSTIC OVARIAN SYNDROME

IN-SILICO ANALYSIS OF SNPs FROM cAMP-GEFII GENE ASSOCIATED WITH POLYCYSTIC OVARIAN SYNDROME

Jeyabaskar Suganya, Mahendran Radha ^*, Sharanya Manoharan and Vasudevan Poornima

Department of Bioinformatics, School of Life Sciences, VISTAS, Pallavaram, Chennai - 600117, Tamil Nadu, India.

ABSTRACT: Polycystic ovary syndrome (PCOS) is one of the most common disorders that occur in women at any age due to the endocrine hormone imbalance. The cause for this disorder is still not identified, but on recent research provided that disorder may be caused by some genetic variation. Predicting and understanding the effects of genetic variation that occurred in the gene are becoming more important for single nucleotide polymorphism to understand the molecular basis of genetic disease. From the literature survey, the candidate gene which is responsible for causing genetic PCOS was identified. In this work using computational methods, this candidate gene was analyzed completely to find out the genetic variation which in charge for altering the expression and the functional of the gene. On analyzing the gene, it was predicted that the protein which was translated from the gene played a key role for causing the major alteration in the gene. Using SNP analysis tool, further investigation were carried out to the disease causing protein and were predicted that the particular mutation occurred in the protein altered the function and structure of the gene. By using bioinformatics tool, an attempt was made to stop the mutation by replacing the original amino acid to the structure and sequence of the protein, which was suggested by the tools. Some clinical studies can be carried out further to confirm that the protein which was responsible for gene alteration in PCOS will function normally after some necessary modification are made in the protein which was suggested by computational methods.

Polycystic ovary syndrome (PCOS), Candidate gene, Protein, SNP, SNP analysis tool

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a mysterious reproductive disorder that causes irregular menstrual periods ¹. An average of 5 to 10 percent of women was found to have this disorder in their endocrine glands ². PCOS women’s of overweight or obese would have higher risk of developing Type 2 diabetes ³ and infertility than the normal women ⁴.

The mode of inheritance and role of genetic factors in PCOS syndrome have not been fully investigated until now ⁵. The genes responsible for  altered expression  in PCOS causes genetic abnormality which  affects signal transduction ruling steroid genesis, steroid hormones action, gonadotropin action and regulation, insulin action and secretion, energy homeostasis, chronic inflammation and others ^{6, 7}.

Several large research groups are actively searching for a genetic cause of this syndrome and noted out the increased level of insulin resistance in PCOS affected woman ⁸. A study was conducted to find out the main candidate gene which causes PCOS to women by collecting 50 candidate genes which are linkage and association with PCOS. That study resulted the cAMP-GEFII were identified as new candidate genes that may be involved in the genetic etiology of PCOS ⁹. The genes cAMP-GEFII, which is an intracellular signaling molecule that is activated by cAMP ¹⁰ and it was the direct target of cAMP in regulated exocytosis ¹¹.

Later genetic causes of this syndrome were identified that if Single nucleotide polymorphisms i.e. mutation occurs in the candidate gene would resulted in PCOS ^{12, 13}. Single nucleotide polymorphisms are single base (A, T, G, C) variations between genomes within a species ¹⁴. SNPs can also be used to track the inheritance of disease genes within families ¹⁵. When SNPs occur within a gene or in a regulatory region, it affects the stability and functions of the protein ¹⁶ due to deleterious amino acid changes occur in the protein sequences would play a very vital role in causing the disease by affecting the candidate gene’s functions ¹⁷. SNP analysis would help to identity the multiple genes associated with such complex diseases like cancer, diabetes, vascular disease and mental illness ^{18, 19}. In this study, the candidate gene of PCOS was analysed using Bioinformatics and step were taken to stop the mutation occurred in the gene which result in normal gene function.

MATERIALS AND METHODS:

Sequence Analysis: The Gene ID, nucleotide sequences and protein sequences of Human cAMP-GEFII gene were retrieved using NCBI and SWISSPROT Database.

The physical and chemical properties of protein sequence can be analyzed using Protparam. The properties include the molecular weight, theoretical pI, amino acid composition, atomic composition, extinction coefficient, estimated half-life, instability index, aliphatic index and grand average of hydropathicity (GRAVY).

The domain and family of protein were identified using Pfam to understand the function of protein.

SNPs Analysis: The list of SNP’S (rs ID) present in the gene was predicted by submitting gene ID using NCBI- dbSNP. The dbSNP database shows the disease-causing clinical mutations as well as neutral polymorphisms which is present in the gene.

The Gene ID of cAMP-GEFII were submitted to database and list of SNPs which observed in the gene were predicted

(http://www.ncbi.nlm.nih.gov/SNP/).NCBI – db SNP database.

The SNP IDs of human cAMP-GEFII were submitted to identify where amino acid substitution occurs in gene and which affect the protein function. (http://siftdna.org/www/SIFT_dbSNP.html).

Sorting Intolerant from Tolerant (SIFT dbSNP) Predicted protein sequence and SNPs of human cAMP-GEFII were submitted to evaluate the effect of single amino acid substitution on protein function (https://www.rostlab.org/services/snap/submit).²⁰

Screening for Non-Acceptable Polymorphisms (SNAP): The FASTA format of protein sequence and amino acid substitution were submitted to predict whether a nonsynonymous single nucleotide polymorphism (nsSNP) having a phenotypic effect or not.

(http://snpanalyzer.uthsc.edu/).

NsSNP Analyzer: The FASTA format of protein sequence and amino acid substitution were submitted to predict the particular nonsynonymous (amino acid changing) SNP which cause a functional impact on the protein.

(http://www.pantherdb.org/tools/csnpScoreForm.jsp).

PANTHER: Evolutionary analysis of coding SNPs^. The Gene ID of cAMP-GEFII was submitted to assign molecular functional effects of non-synonymous SNPs based on structure and sequence analysis (http://www.snps3d.org/).

SNPs3D: Pymol is a potent and interactive molecular visualization software tool and used to view the protein, ligand ²¹. The three dimensional structure of protein and ligand were visualized using Pymol and saved in PDB file format for further analysis ²².

Swiss pdb viewer: Swiss pdb viewer is an interactive molecular graphics program for visualization and analysis of protein structures. Using Mutation ²³ and Energy minimization tool ²⁴ for the protein, mutation has been altered and Energy minimization was performed before and after mutation.

RESULTS AND DISCUSSION:

Sequence Analysis: The FASTA file format of the Nucleotide sequence >gi|568815596:172687774-173100516 Homo sapiens chromosome 2, GRCh38 Primary Assembly and protein sequence. >gi|155030204|ref|NP_008954.2| rap guanine nucleotide exchange factor 4 isoform a [Homo sapiens]. The Nucleotide and protein sequence was retrieved from the NCBI & SWISSPROT database which contains 412225 base-pairs in the mRNA and 1011 amino acid residues

The physiochemical properties of the protein - molecular weight (115521.5), theoretical pI (6.37) and aliphatic index (88.80), Grand average of hydropathicity – GRAVY (0.334), molecular formula (C₅₁₄₀H₈₁₃₁N₁₄₁₉O₁₅₁₁S₄₈) and amino acid composition are shown in the Table 1 were predicted by protparam.

TABLE 1: SHOWS THE AMINO ACID COMPOSITION OF cAMP-GEFII PROTEIN

The five (3 different & 2 same) domain and 1 family of protein were identified and found that all the 5 domain were significant. In the domain, 2 clan were found (CL0542 & CL0072) were predicted using Pfam are shown in the Table 2.

TABLE 2: SHOWS THE FAMILY OF cAMP-GEFII PROTEIN

 SNPs Analysis: From NCBI-Gene  database the  cAMP-GEFII  gene ID  11069 were  identified and  then the gene ID were  submitted to dbSNP database which predicted that  there were 193 SNPs ID (rsID) for this gene, in that some of them are nonsynonymous (ns) and synonymous, which occur in intron region and untranslated region. The non-synonymous (80) SNPs were taken for further analysis because the presence of non-synonymous SNPs can only affect the protein function and structure ^{25, 26.} The list of non-synonymous SNPs was as shown in the Table 3.

TABLE 3: SHOWS THE LIST OF NON-SYNONYMOUS SNPs

Using Sift dbSNP database, nsSNP was analyzed to spot rsID (rs17852173) which was responsible for damaging the function and the structure of cAMP-GEFII were shown in the Table 4.

TABLE 4: SHOWS THE PREDICTION OF SNPs WHICH CAUSES DAMAGE TO cAMP-GEFII PROTEIN

Predicted nsSNP: The SIFT database predicted 6 nsSNP (G54E, P171R, S240F, H358R, H679P, P749) which causes damage to the gene. From SNAP, nsAnalyzer, Panther Database the exact SNP which affect the function of protein and also for the possibility of structural alteration were predicted. In SNAP database SNP of H679P were found to be Non-neutral with high Reliability index 5 when compared with other SNP which are neutral. From nsAnalyzer Database Phenotype of given SNP were analyzed H679P SNP were found to cause disease with siftscore of 0. Result predicted from Panther database show that SNP H679P does not show any multiple sequences position (MSA) when compare with other SNP were shown in the Table 5.

TABLE 5: SHOWS THE RESULT OF SNPs ANALYSIS OF cAMP-GEFII PROTEIN

From 3D SNP database, the 3D structure of cAMP-GEFII Protein was retrieved and viewed using PyMol. On analyzing the sequence and structure of the protein it was confirmed that the amino acid proline was present in the 679^th position of amino acid with the loss of Hydrogen Bond in the structure resulting in the alteration of the gene function. By Swiss Pdb Viewer, the exact amino acid Histidine was placed in proline in the 679^th position of protein structure shown in the Fig. 1, the altered 3D structure of the protein is saved in PDB file format. On analyzing the both structure of the protein, the amino acid histidine present in the 679^th position showed the proper arrangement of atoms and thereby regulating the protein function when compared with the amino acid proline in the 679^th position of protein structure.

FIG. 1: 3D STRUCTURE OF PROTEIN OF cAMPGEFII WITH HISTIDINE IN 679^th POSITION

CONCLUSION: Mutation occurs in the gene affects both the function and structure of the protein which lead to a disease in human. In the current study, the gene which was responsible for causing reproductive disorder of PCOS was identified. On further analyses of cAMP-GEFII gene using bioinformatics tools, it was predicted that mutation (SNP) present in the gene was in charge in causing disease.

From the above obtained result, we can conclude that non-synonymous SNP of rsID (rs17852173) in the cAMP-GEFII gene was not only affects the protein function and structure but also cause serious damage to gene. The investigation of rsID was carried out to identify the exact location of SNP occurred in the protein sequence and structure, resulted that H679P SNP presented in the protein played a vital role for the occurrence of PCOS in many women. The mutations (SNP) in the protein structure were dysfunction by replacing the amino acid Histidine (H) instead of proline (P) in 679^th position of protein structure to make the protein function normally by Swiss PDB Viewer. Some clinical trials are needed in future to confirm that this disease can be treated well by altering the mutation in the gene.

ACKNOWLEDGEMENT: We acknowledge Vels Institute of Science, Technology and Advanced Studies (VISTAS) for providing us with required infrastructure and support system needed.

CONFLICT OF INTEREST: The authors declared no conflicts of interest.

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    How to cite this article:

    Suganya J, Radha M, Manoharan S and Poornima V: In-silico analysis of SNPs from cAMP-GEFII gene associated with polycystic ovarian syndrome. Int J Pharm Sci & Res 2018; 9(12): 5216-20. doi: 10.13040/IJPSR.0975-8232.9(12).5216-20.

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