Publication: The Identification of Functional Non-Synonymous SNP in Human ATP Binding Cassette (ABC), Subfamily Member 7 Gene: Application of Bioinformatics Tools in Biomedicine.
Issued Date
2011
Resource Type
Language
eng
ISSN
1948-593X
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Mahidol University
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J Bioanal Biomed
Bibliographic Citation
J Bioanal Biomed. Vol.3, No.1 (2011), 26-31
Suggested Citation
Pornlada Nuchnoi, Duangdao Nantakomol, Vasunun Chumchua, Chotiros Plabplueng, Chartchalerm Isarankura-Na-Ayudhya, Virapong Prachayasittikul The Identification of Functional Non-Synonymous SNP in Human ATP Binding Cassette (ABC), Subfamily Member 7 Gene: Application of Bioinformatics Tools in Biomedicine.. J Bioanal Biomed. Vol.3, No.1 (2011), 26-31. Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/2097
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Title
The Identification of Functional Non-Synonymous SNP in Human ATP Binding Cassette (ABC), Subfamily Member 7 Gene: Application of Bioinformatics Tools in Biomedicine.
Abstract
The prediction of functional single nucleotide polymorphism (SNP) is promising in modern genetics analysis.
Computational biology technology has facilitated an increase in the successful rate of genetic association study and
reduced the cost of genotyping. In the present study, we applied various bioinformatics tools for the selection of high
potentially functional nsSNP and determined the linkage disequilibrium (LD) structure of ATP-binding cassette transporter
member 7 (ABCA7) genes in HapMap populations. Two functional polymorphisms (rs3752233 and rs3752246) were
identified on the basis of less protein stability, a low likelihood of mutability, a changing of protein structure and function.
Interestingly, a completed LD between rs3752233 (R463H) and rs4147918 (Q1686R) was detected in Utah residents
with ancestry from northern and western Europe (CEU) populations. In addition, the difference of the LD pattern between
the populations observed highlighted the essential role of the construction of an LD map for designing and interpreting
genetic association study. Studies herein convey the empirical guidelines for conduction of ABCA7 genetic association
study via bioinformatics and computational application.