Profiling metagenomic communities using circular consensus and Single Molecule, Real-Time Sequencing.
There are many sequencing-based approaches to understanding complex metagenomic communities spanning targeted amplification to whole-sample shotgun sequencing. While targeted approaches provide valuable data at low sequencing depth, they are limited by primer design and PCR amplification. Whole-sample shotgun experiments generally use short-read, second-generation sequencing, which results in data processing difficulties. For example, reads less than 1 kb in length will likely not cover a complete gene or region of interest, and will require assembly. This not only introduces the possibility of incorrectly combining sequence from different community members, it requires a high depth of coverage. As such, rare community members may not be represented in the resulting assembly. Circular-consensus, single molecule, real-time (SMRT) Sequencing reads in the 1-2 kb range, with >99% accuracy can be efficiently generated for low amounts of input DNA. 10 ng of input DNA sequenced in 4 SMRT Cells would generate >100,000 such reads. While throughput is low compared to second-generation sequencing, the reads are a true random sampling of the underlying community, since SMRT Sequencing has been shown to have no sequence-context bias. Long read lengths mean that that it would be reasonable to expect a high number of the reads to include gene fragments useful for analysis.