BMC Biology · 2015 · 51 citations · 62 references
Life SciencesEcologyEvolutionary BiologyMicrobial EcologyMolecular EvolutionSequence AnalysisMicrobial DiversityMicrobial PhylogenomicsMolecular PhylogenyPhylogenetic Network AnalysisPhylogenetic Sequence AnalysisPhylogenomic AnalysisEcological StudiesMarine Microbial PhylogenomicsMicrobial Diversity AnalysisMicrobial Ecological NetworksPhylogenomic InferenceReference Data SetsSequence Similarity
BACKGROUND: High-throughput sequencing technologies are lifting major limitations to molecular-based ecological studies of eukaryotic microbial diversity, but analyses of the resulting millions of short sequences remain a major bottleneck for these approaches. Here, we introduce 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 small subunit rDNA (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 the progress in the description of genetic diversity of ciliates by environmental SSU-rDNA surveys, detected a fundamental historical bias in 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 are structured by habitat and geographical location at intermediate geographical scale, as observed for bacteria, plants, and animals. CONCLUSIONS: 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. Network analyses such as presented in this study offer a promising way to guide the design of novel primers and to further explore this vast and structured microbial diversity.
62
Edward Simpson · Nature · 1949 · 14K citations · Full text
The igraph software package for complex network research
Gábor Csárdi, Tamás Nepusz · Medical Entomology and Zoology · 2006 · 10.4K citations
Conrad L. Schoch, Keith A. Seifert, Sabine M. Huhndorf et al. · Proceedings of the National Academy of Sciences · 2012 · 5.1K citations · Full text