scholarly journals In silico analysis of single nucleotide polymorphisms (SNPs) in human FOXC2 gene

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 243 ◽  
Author(s):  
Mohammed Nimir ◽  
Mohanad Abdelrahim ◽  
Mohamed Abdelrahim ◽  
Mahil Abdalla ◽  
Wala eldin Ahmed ◽  
...  

Introduction: Lymphedema is abnormal accumulation of interstitial fluid, due to inefficient uptake and reduced flow, leading to swelling and disability, mostly in the extremities. Hereditary lymphedema usually occurs as an autosomal dominant trait with allelic heterogeneity. Methods: We identified single nucleotide polymorphisms (SNPs) in the FOXC2 gene using dbSNP, analyzed their effect on the resulting protein using VEP and Biomart, modelled the resulting protein using Project HOPE, identified gene – gene interactions using GeneMANIA and predicted miRNAs affected and the resulting effects of SNPs in the 5’ and 3’ regions using PolymiRTS. Results: We identified 448 SNPs - 429 were nsSNPs and 44 SNPs were in the 5’ and 3’ UTRs. In total, 2 SNPs have deleterious effects on the resulting protein, and a 3D model confirmed those effects. The gene – gene interaction network showed the involvement of FOXC2 protein in the development of the lymphatic system. hsa-miR-6886-5p, hsa-miRS-6886-5p , hsa-miR-6720-3p, which were affected by the SNPs rs201118690, rs6413505, rs201914560, respectively, were the most important miRNAs affected, due to their high conservation score. Conclusions: rs121909106 and rs121909107 were predicted to have the most harmful effects, while hsa-miR-6886-5p, hsa-miR-6886-5p and hsa-miR-6720-3p were predicted to be the most important miRNAs affected. Computational biology tools have advantages and disadvantages, and the results they provide are predictions that require confirmation.

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 243
Author(s):  
Mohammed Nimir ◽  
Mohanad Abdelrahim ◽  
Mohamed Abdelrahim ◽  
Mahil Abdalla ◽  
Wala eldin Ahmed ◽  
...  

Introduction: Lymphedema is an abnormal accumulation of interstitial fluid, due to inefficient uptake and reduced flow, leading to swelling and disability, mostly in the extremities. Hereditary lymphedema usually occurs as an autosomal dominant trait with allelic heterogeneity. Methods: We identified single nucleotide polymorphisms (SNPs) in the FOXC2 gene using dbSNP, analyzed their effect on the resulting protein using VEP and Biomart, modelled the resulting protein using Project HOPE, identified gene – gene interactions using GeneMANIA and predicted miRNAs affected and the resulting effects of SNPs in the 5’ and 3’ regions using PolymiRTS. Results: We identified 473 SNPs - 429 were nsSNPs and 44 SNPs were in the 5’ and 3’ UTRs. In total, 2 SNPs - rs121909106 and rs121909107 - have deleterious effects on the resulting protein, and a 3D model confirmed those effects. The gene – gene interaction network showed the involvement of FOXC2 protein in the development of the lymphatic system. hsa-miR-6886-5p, hsa-miRS-6886-5p, hsa-miR-6720-3p, which were affected by the SNPs rs201118690, rs6413505, rs201914560, respectively, were the most important miRNAs affected, due to their high conservation score. Conclusions: rs121909106 and rs121909107 were predicted to have the most harmful effects, while hsa-miR-6886-5p, hsa-miR-6886-5p and hsa-miR-6720-3p were predicted to be the most important miRNAs affected. Computational biology tools have advantages and disadvantages, and the results they provide are predictions that require confirmation using methods such as functional studies.


2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Harini Venkata Subbiah ◽  
Polani Ramesh Babu ◽  
Usha Subbiah

Abstract Background Single nucleotide polymorphisms (SNPs) play a significant role in differences in individual’s susceptibility to diseases, and it is imperative to differentiate potentially harmful SNPs from neutral ones. Defensins are small cationic antimicrobial peptides that serve as antimicrobial and immunomodulatory molecules, and SNPs in β-defensin 1 (DEFB1 gene) have been associated with several diseases. In this study, we have determined deleterious SNPs of the DEFB1 gene that can affect the susceptibility to diseases by using different computational methods. Non-synonymous SNPs (nsSNPs) of the DEFB1 gene that have the ability to affect protein structure and functions were determined by several in silico tools—SIFT, PolyPhen v2, PROVEAN, SNAP, PhD-SNP, and SNPs&GO. Then, nsSNPs identified to be potentially deleterious were further analyzed by I-Mutant and ConSurf. Post-translational modifications mediated by nsSNPs were predicted by ModPred, and gene-gene interaction was studied by GeneMANIA. Finally, nsSNPs were submitted to Project HOPE analysis. Results Ten nsSNPs of the DEFB1 gene were found to be potentially deleterious: rs1800968, rs55874920, rs56270143, rs140503947, rs145468425, rs146603349, rs199581284, rs201260899, rs371897938, rs376876621. I-Mutant server showed that nsSNPs rs140503947 and rs146603349 decreased stability of the protein, and ConSurf analysis revealed that SNPs were located in conserved regions. The physiochemical properties of the polymorphic amino acid residues and their effect on structure were determined by Project HOPE. Conclusion This study has determined high-risk deleterious nsSNPs of β-defensin 1 and could increase the knowledge of nsSNPs towards the impact of mutations on structure and functions mediated by β-defensin 1 protein.


2018 ◽  
Author(s):  
Md. Arifuzzaman ◽  
Sarmistha Mitra ◽  
Amir Hamza ◽  
Raju Das ◽  
Nurul Absar ◽  
...  

ABSTRACTBackgroundMutations in SMPX gene can disrupt the normal activity of the SMPX protein which is involved in hearing process.ObjectiveIn this study, deleterious non-synonymous single nucleotide polymorphisms were isolated from the neutral variants by using several bioinformatics tools.MethodFirstly, dbSNP database hosted by NCBI was used to retrieve the SNPs of SMPX gene, secondly, SIFT was used primarily to screen the damaging SNPs. Further, for validation PROVEAN, PredictSNP and PolyPhen 2 were used. I-Mutant 3 was utilized to analyze the protein stability change and MutPred predicted the molecular mechanism of protein stability change. Finally evolutionary conservation was done to study their conservancy by using ConSurf server.ResultsA total of 26 missense (0.6517%) and 3 nonsense variants (0.075%) were retrieved and among them 4 mutations were found deleterious by all the tools of this experiment and are also highly conserved according to ConSurf server. rs772775896, rs759552778, rs200892029 and rs1016314772 are the reference IDs of deleterious mutations where the substitutions are S71L, N19D, A29T and K54N. Loss of Ubiquitination, loss of methylation, loss of glycosylation, and loss of MoRF binding motifs are the root causes of protein stability change.ConclusionThis is the first study regarding nsSNPs of SMPX gene where the most damaging SNPs were screened that are associated with the SMPX gene and can be used for further research to study their effect on protein structure and function, their dynamic behavior and how they actually affect protein’s flexibility.


BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chaoxiong Shen ◽  
Daofeng Fan ◽  
Huajun Fu ◽  
Chong Zheng ◽  
Yinjuan Chen ◽  
...  

Abstract Objectives The purpose of this study was to investigate the impact of single nucleotide polymorphisms (SNPs) in the ANGPTL4 gene and the SNP–SNP interactions on atherosclerotic ischemic stroke (IS) risk. Patients and methods A case-control study was conducted. A total of 360 patients with atherosclerotic IS and 342 controls between December 2018 and December 2019 from Longyan First Hospital affiliated to Fujian Medical University were included. A logistic regression model was used to examine the association between SNPs and atherosclerotic IS risk. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the SNP-SNP interaction. Results Logistic regression analysis showed that atherosclerotic IS risk was significantly lower in carriers with the rs11672433-T allele than those with the CC genotype (CT+ TT vs. CC); adjusted OR, 0.005; 95% CI, 0.02–0.11. We found a significant 2-locus model (P = 0.0010) involving rs11672433 and rs4076317; the cross-validation consistency of this model was 10 of 10, and the testing accuracy was 57.96%. Participants with the CT or TT of rs11672433 and CC of rs4076317 genotype have the lowest atherosclerotic IS risk, compared to subjects with CC of rs11672433 and the CC of rs4076317 genotype, OR (95%CI) was 0.06(0.02–0.22), after covariates adjustment for gender, age, smoking and alcohol status, hypertension, Diabetes mellitus, TG, TC, HDL-C, LDL-C, Uric acid. Conclusions We found that rs11672433 was associated with decreased atherosclerotic IS risk; we also found that gene–gene interaction between rs11672433 and rs4076317 was associated with decreased atherosclerotic IS risk.


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