CHARACTERISATION OF TETRA AMELIA SYNDROME BY SNP BASED ON COMPUTATIONAL GENOTYPING ANALYSIS
Abstract
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 Objective: Tetra Amelia syndrome is a congenital disorder, which is mainly caused by the presence of mutation in the WNT3 region. Being an embryonic developmental disorder, earlier warning of its onset can be predicted by subjecting there single nucleotide polymorphisms (SNPs) to further studies.
Methods: For the identification of the list of mutant WNT3 proteins with the specified (G83X) position, we predicted it through reverse genetics method. This region was further used to determine the SNPs involved in them using the Chi-square test. Finally, we have validated the existence of these SNPs in the WNT3 gene by multifactor dimensionality reduction analysis.
Results: In Tetra Amelia syndrome, we determined that among the six frames of WNT3 gene, only the 2nd frame has more identity with WNT3 protein (98%). The mutant amino acid residue was found only at the 83rd position (G83X). Sequence analysis techniques helped to determine 16 SNPs: rs147030694, rs9908452, rs1062339, rs193268056, rs190245126, rs185051815, rs71375364, rs188212517, rs185848450, rs151309556, rs148810526, rs142400306, rs118086135, rs77768380, rs75398055, and rs34608985. These SNPs where validated further and this lead to 3 SNP s, which can be used to genotype Tetra Amelia syndrome.
Conclusion: The present studies of genotyping Tetra Amelia syndrome can help determine congenital disease at earlier stages itself. In future, larger dataset is needed and as well similar methodology can be used on late onset diseases (like Parkinson's) can also be predicted by subjecting there SNPs genotype.
Keywords: Tetra Amelia syndrome, WNT3, Hap map, Multifactor dimensionality reduction, Single, Nucleotide polymorphisms
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