Testing ecological theories with sequence similarity networks: marine ciliates exhibit similar geographic dispersal patterns as multicellular organisms (file : Novel_diversity_V4_BIOM_DNA.fasta)

file : Novel_diversity_V4_BIOM_DNA.fasta see details in 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：Novel_diversity_V4_BIOM_DNA.fasta，详细信息请参阅《利用序列相似性网络验证生态学理论：海洋纤毛虫展现出与多细胞生物相似的地理扩散模式》（配套文件：readme_Forster_et_al_BMC），访问链接：http://dx.doi.org/10.6084/m9.figshare.1264013。

**背景**：高通量测序技术破除了真核微生物多样性分子生态学研究的主要限制瓶颈，但针对由此产生的数百万条短扩增子的计算机模拟（in silico）分析仍是该研究路径的核心障碍。本研究将进化生物学与图论领域中日益广泛应用的序列相似性网络（sequence similarity networks）分析与统计框架引入生态学研究，结合已有研究数据集（包括培养纤毛虫的小亚基核糖体DNA（SSU-rDNA）桑格测序数据及既往环境多样性调查数据），对新获得的焦磷酸测序V4区SSU-rDNA序列数据集开展分析。

**结果**：本研究开发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的解析进展，识别出此类调查中存在的根本性历史偏倚——即优先获取已有类群的倾向，并揭示了大量未被发掘的微生物多样性。此外，网络分析指标显示，纤毛虫并非全球随机扩散，而是在中等地理尺度上呈现出显著的局部分布模式，这与细菌、植物及动物的分布特征一致。

**结论**：尽管当前用于局域深度测序调查的通用引物几乎无法完全覆盖纤毛虫（极大概率也包括其他微生物）远超此前认知的多样性，但序列相似性网络可通过识别具有显著相似性的分化序列类群，为设计新型引物、进一步探索这种庞大且具有结构特征的微生物多样性提供了极具前景的研究路径。