一种多元聚合酶链反应的引物集选择算法  

An Algorithm for Multiplex PCR Primer Set Selection

作　　者：吴璟莉[1] 陈建二[1] 王建新[1] 

机构地区：[1]中南大学信息科学与工程学院

出　　处：《小型微型计算机系统》2008年第8期1520-1524,共5页Journal of Chinese Computer Systems

基　　金：国家自然科学基金项目(60433020)资助;新世纪优秀人才支持计划项目(NCET-05-0683)资助;长江学者和创新团队发展计划项目(IRT0661)资助

摘　　要：多元聚合酶链反应(multiplex PCR,MP-PCR)是一种运用多对引物同时扩增多条DNA序列或一条DNA序列上多个区域的生物学实验方法.引物集设计对于实验的成功至关重要.由于引物合成是实验成本的主要来源,且引物需要满足许多约束条件,因此设计满足多约束条件的最小引物集是保证实验成功、降低实验成本的有效手段.首先给出多约束最小引物集选择问题(minimum primer set selection problem with multiple constraints,MPSSPMC)的数学模型,通过引入新颖的遗传算子,提出一种求解该问题的单亲遗传算法MG-PGA.实验结果表明MG-PGA在满足多约束条件下能获得较小的引物集,为MP-PCR引物设计提供了一种有效的解决方法.Multiplex polymerase chain reaction （MP-PCR） is a biological experimental technique to amplify multiple DNA sequences or multiple regions of a DNA sequence simultaneously by using different primer pairs. The choice of primers is very important for successful PCR experiment. The expense of PCR experiment comes mainly from synthesizing PCR primers, and there are many constraints need to be satisfied by primers, therefore, it is an effective way for successful and economical experiment to design the minimum primer set with multiple constraints. In this paper, firstly, a mathematical model of minimum primer set selection problem with multiple constraints （MPSSPMC） is presented. Secondly, a parthenogenetic algorithm named MG-PGA for solving this problem is proposed by introducing a novel genetic operator. Experimental results show that MG-PGA is able to find a small primer set on the premise of satisfying multiple constraints. Hence, it is an effective solution for MP-PCR primer design.

关 键 词：多元聚合酶链反应 引物集 引物设计 贪心算法 单亲遗传算法 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]