基于组合探针识别的大规模细菌分类16 S rRNA基因芯片设计(英文)

Design of 16 S rRNA-based Oligonucleotide Array Using Group-specific Non-unique Probes in Large Scale Bacteria Detection

随着16SrRNA序列资源的不断丰富,以及寡核苷酸微阵列基因芯片技术的不断进步,检测复杂微生物菌落中的微生物种群构成成为可能.现有的序列特异性探针设计算法缺乏足够的覆盖度、灵活性以及效率,不能满足大规模细菌检测基因芯片的设计要求.很多组特异性探针设计算法的思路多局限于针对某个目标序列组设计唯一的组特异性探针.在很多应用场合,设计单个探针检测组内所有目标序列的目标是很难达到的.因此,设计多个探针通过组合方式进行检测是很有必要的.每个探针能特异性地检测组内一部分目标序列,通过组合就能提高覆盖率.然而,在所有可能的探针组合中找到一个优化的探针组合是很耗时的.提出了一个可行的基于相对熵和遗传算法的组合探针设计算法.

With thousands of sequenced 16 S rRNA genes available, and advancements in oligonucleotide microarray technology, the detection of microorganisms in microbial communities consisting of hundreds of species may be possible. The existing algorithms developed for sequence-specific probe design are not suitable for applications in large-scale bacteria detection due to the lack of coverage, flexibility and efficiency. Many other strategies developed for group-specific probe design focus on how to find a unique group-specific probe that can specifically detect all target sequences of a group. Unique group-specific probe for each group can not always be found. Hence, it is necessary to design non-unique probes. Each probe can specifically detect target sequences of a different subgroup. Combination of multiple probes can achieve higher coverage. However, it is a time-consuming task to evaluate all possible combinations. A feasible algorithm using relative entropy and genetic algorithm （GA） to design group-specific non-unique probes was presented.