In silico analysis of single nucleotide polymorphisms (SNPs) in human FOXC2 gene [version 2; referees: 2 approved]

• Main Authors: Mohammed Nimir, Mohanad Abdelrahim, Mohamed Abdelrahim, Mahil Abdalla, Wala eldin Ahmed, Muhanned Abdullah, Muzamil Mahdi Abdel Hamid
• Format: Article
• Language: English
• Published: F1000 Research Ltd 2017-10-01
• Series: F1000Research
• Subjects: Bioinformatics; Genetics of the Immune System; Genomics
• Online Access: https://f1000research.com/articles/6-243/v2

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.