核糖体RNA基因的九个多变区被用于微生物分类和环境样品的群落结构分析，但多变区和引物选择问题一直困扰着海洋环境微生物研究。本项目将使用数据库中的核糖体RNA基因数据来研究核糖体RNA的多变区在分类效率上的准确度和相关性。利用代表性RNA基因的不同多变区构建的进化树的树型差异，可以计算出这些多变区在分类上的相关性；多组数据统计可以验证这种相关性的可靠性。来自海洋微生物样品公开的宏基因组数据与相应的核糖体RNA测序数据，也可以用于群落结构分析。宏基因组的分析结果可以用于判断核糖体RNA多变区和引物选择在群落结构分析中的准确度。本研究还会使用合成微生物群落，使用不同多变区的引物进行扩增。对比已知的种群构成，可以验证多变区和引物在微生物分类上的可靠度。本项目还就构建海洋微生物核糖体RNA的数据库，运用最新算法实现分类与引物设计的在线服务，以便快速准确定位来自海洋极端环境微生物物种的分类地位。

Hypervariable regions in the ribosomal RNA genes are valuable in taxonomic classification of marine microbes. However, which region should be the best target for pyrosequencing of rRNA amplicons is still a question. This study will use hypervariable regions of rRNA genes from representative species in public databases to uncover the correlation of the regions in taxonomic classification. Similarity between the phylogenetic trees based on these regions will be applied to calculate the correlation; multiple datasets will help to evaluate the probabiltiy of the correlation. Metagenomes and corresponding pyrosequenced rRNA amplicons will be downloaded for such a study too. Accurate community structures based on the analyses of metagenomes will be used to assess the taxonomic classification efficiency of the hypervariable regions and primers used in the same study. A synthetic microbial community will be then designed to test which hypervariable regions and primers can be utilized to more accurately detect the known community structure. This study will also construct an online database enabling to provide taxonomic assignment and primer selection for users with new algorithms. This may help to assign a submitted rRNA sequence to the most closely related species and/or to a possible taxonomic position for rare marine microbial species.