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Mathematics and Computer Science Division
"Combining molecular and computational tools for targeted explorations of taxonomic novelty."

DATE: June 18, 2012 to June 18, 2012
TIME: 2:00 PM - 3:00 PM
SPEAKER: Josh D. Neufeld, Associate Professor University of Waterloo Department of Biology
LOCATION: Building 240/Conference Room 1406-1407, Argonne National Laboratory
HOST: Jack Gilbert

Description:
Next-generation sequencing technologies have led to recognition of a so-called “rare biosphere”. These microbial species are defined by low relative abundance and may be specifically adapted to maintaining low population sizes. We hypothesized that mining of low-abundance next-generation 16S rRNA gene data would lead to the discovery of novel phylogenetic diversity, reflecting microorganisms not yet discovered by previous sampling efforts. Here we test this hypothesis by combining molecular and bioinformatic approaches for targeted retrieval of phylogenetic novelty within rare biosphere species. Using our Illumina 16S rRNA gene sequencing approach and two in-house applications (AutoQIIME and SSUnique), we combined BLASTN network analysis, phylogenetics and targeted primer design to amplify 16S rRNA gene sequences from unique potential bacterial lineages, comprising part of the rare biosphere from a multi-million sequence dataset from an Arctic tundra soil sample. Demonstrating the feasibility of the protocol developed here, three of seven recovered phylogenetic lineages represented extremely divergent taxonomic entities. These divergent target sequences correspond to a) a previously unknown lineage within the BRC1 candidate phylum, b) a sister group to the early diverging and currently recognized monospecific Cyanobacteria Gloeobacter, a genus containing multiple plesiomorphic traits and c) a highly divergent lineage, phylogenetically resolved within mitochondria. A comparison to twelve next-generation datasets from additional soils suggested persistent low-abundance distributions of these novel 16S rRNA genes. The results demonstrate this sequence analysis and retrieval pipeline as applicable for exploring phylogenetic novelty and recovering taxa that may represent significant steps in bacterial evolution.


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