Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms (file : details_V4ciliates_Biomarks.tab)

file : details_V4ciliates_Biomarks.tab Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms (file : readme_Forster_et_al_BMC) http://dx.doi.org/10.6084/m9.figshare.1264013 Background: High-throughput sequencing technologies are lifting major limitations to molecular-based ecological studies of eukaryotic microbial diversity, but in silico analyses of the resulting millions of short amplicons remain a major bottleneck for these approaches. Here, we introduced the analytical and statistical framework of sequence similarity networks, increasingly used in evolutionary studies and graph theory, into the field of ecology to analyze novel pyrosequenced V4 SSU-rDNA sequence data sets in the context of previous studies, including SSU-rDNA Sanger sequence data from cultured ciliates and from previous environmental diversity inventories.Results: Our broadly applicable protocol quantified progress in the description of genetic diversity of ciliates by environmental rRNA amplicons studies, detected a fundamental historical bias, the tendency to recover already known groups, in these surveys, and revealed substantial amounts of hidden microbial diversity. Moreover, network measures demonstrated that ciliates are not globally dispersed, but present strong local patterns at intermediate geographical scale, as observed for bacteria, plants, and animals.Conclusions: Although currently available ‘universal’ primers used for local in-depth sequencing surveys provide little hope to exhaust the significantly higher ciliate (and most likely microbial) diversity than previously thought, sequence similarity networks, since they identify groups of divergence sequences sharing distinctive similarities, offer a promising way to guide the design of novel primers and to further explore such a vast and structured microbial diversity.数据集文件：details_V4ciliates_Biomarks.tab，研究主题为「利用序列相似性网络（sequence similarity networks）验证生态学理论：海洋纤毛虫展现出与多细胞生物相似的地理扩散模式」，配套说明文件为readme_Forster_et_al_BMC，数据DOI链接：http://dx.doi.org/10.6084/m9.figshare.1264013 背景：高通量测序技术（high-throughput sequencing technologies）破除了真核微生物多样性分子生态学研究的主要限制，但针对由此产生的数百万条短扩增子（amplicons）的计算机模拟（in silico）分析仍是该研究方法的一大瓶颈。本研究将进化生物学与图论领域中日益普及的序列相似性网络分析与统计框架引入生态学领域，结合既往研究数据——包括已培养纤毛虫的桑格测序（Sanger sequence）SSU-rDNA数据，以及既往环境多样性调查库数据——对新获得的焦磷酸测序（pyrosequencing）V4区小亚基核糖体RNA基因（SSU-rDNA）序列数据集展开分析。 结果：本研究提出的普适性分析流程量化了环境rRNA扩增子研究对纤毛虫遗传多样性描述的进展，在这类调查中检测到一项基础性历史偏倚：即研究人员倾向于回收已被报道的类群，并揭示了大量隐匿的微生物多样性。此外，网络度量指标分析显示，纤毛虫并非全球扩散，而是在中等地理尺度下呈现显著的局部分布模式，这与细菌、植物和动物的观测结果一致。 结论：尽管当前用于局域深度测序调查的通用引物（universal primers）几乎无法穷尽纤毛虫（以及极大概率下的其他微生物）远超此前认知的多样性，但序列相似性网络可识别具有显著相似性的差异序列类群，因此为设计新型引物、进一步探索这一庞大且具有结构化特征的微生物多样性提供了极具前景的路径。