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Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers

Author(s)
Guo, Mira T; Briggs, Adrian W; A Weitz, David; Pitkänen, Leena K; Vigneault, Francois; Virta, Marko PJuhani; Spencer, Sarah J.; Tamminen, Manu V.; Preheim, Sarah P.; Brito, Ilana Lauren; ... Show more Show less
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Abstract
Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here, we describe epicPCR (Emulsion, Paired Isolation and Concatenation PCR), a new technique that links functional genes and phylogenetic markers in uncultured single cells, providing a throughput of hundreds of thousands of cells with costs comparable to one genomic library preparation. We demonstrate the utility of our technique in a natural environment by profiling a sulfate-reducing community in a freshwater lake, revealing both known sulfate reducers and discovering new putative sulfate reducers. Our method is adaptable to any conserved genetic trait and translates genetic associations from diverse microbial samples into a sequencing library that answers targeted ecological questions. Potential applications include identifying functional community members, tracing horizontal gene transfer netw
Date issued
2015-09
URI
http://hdl.handle.net/1721.1/108419
Department
Massachusetts Institute of Technology. Computational and Systems Biology Program; Massachusetts Institute of Technology. Department of Biological Engineering; Massachusetts Institute of Technology. Department of Civil and Environmental Engineering
Journal
The ISME Journal
Publisher
Nature Publishing Group
Citation
Spencer, Sarah J et al. “Massively Parallel Sequencing of Single Cells by epicPCR Links Functional Genes with Phylogenetic Markers.” The ISME Journal 10.2 (2016): 427–436. © 2016 International Society for Microbial Ecology
Version: Final published version
ISSN
1751-7362
1751-7370

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