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基于遗传算法的无酶 SNP 基因分型中两对引物设计的应对策略。

Confronting two-pair primer design for enzyme-free SNP genotyping based on a genetic algorithm.

机构信息

Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.

出版信息

BMC Bioinformatics. 2010 Oct 13;11:509. doi: 10.1186/1471-2105-11-509.

Abstract

BACKGROUND

Polymerase chain reaction with confronting two-pair primers (PCR-CTPP) method produces allele-specific DNA bands of different lengths by adding four designed primers and it achieves the single nucleotide polymorphism (SNP) genotyping by electrophoresis without further steps. It is a time- and cost-effective SNP genotyping method that has the advantage of simplicity. However, computation of feasible CTPP primers is still challenging.

RESULTS

In this study, we propose a GA (genetic algorithm)-based method to design a feasible CTPP primer set to perform a reliable PCR experiment. The SLC6A4 gene was tested with 288 SNPs for dry dock experiments which indicated that the proposed algorithm provides CTPP primers satisfied most primer constraints. One SNP rs12449783 in the SLC6A4 gene was taken as an example for the genotyping experiments using electrophoresis which validated the GA-based design method as providing reliable CTPP primer sets for SNP genotyping.

CONCLUSIONS

The GA-based CTPP primer design method provides all forms of estimation for the common primer constraints of PCR-CTPP. The GA-CTPP program is implemented in JAVA and a user-friendly input interface is freely available at http://bio.kuas.edu.tw/ga-ctpp/.

摘要

背景

聚合酶链反应与两对引物(PCR-CTPP)方法通过添加四个设计引物产生不同长度的等位基因特异性 DNA 带,通过电泳实现单核苷酸多态性(SNP)基因分型,无需进一步步骤。这是一种省时、省钱的 SNP 基因分型方法,具有简单的优点。然而,可行的 CTPP 引物的计算仍然具有挑战性。

结果

在本研究中,我们提出了一种基于遗传算法(GA)的方法来设计可行的 CTPP 引物组,以进行可靠的 PCR 实验。使用 288 个 SNP 对 SLC6A4 基因进行了干坞实验,结果表明,所提出的算法提供了满足大多数引物约束的 CTPP 引物。SLC6A4 基因中的一个 SNP rs12449783 被用作电泳基因分型实验的示例,验证了基于 GA 的设计方法为 SNP 基因分型提供了可靠的 CTPP 引物组。

结论

基于 GA 的 CTPP 引物设计方法为 PCR-CTPP 的常见引物约束提供了所有形式的估计。GA-CTPP 程序用 JAVA 实现,并在 http://bio.kuas.edu.tw/ga-ctpp/ 上提供了一个用户友好的输入界面。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc0d/2964683/6df65fe9c54d/1471-2105-11-509-1.jpg

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