16S amplicon sequencing has proven to be an important tool for identifying and quantifying microbes present in metagenomic samples. We have several researchers here at IGS who have used this to analyze organismal and environmental communities for several years.
Together with these researchers, the GRC has been working over the past year to transition high-throughput sequencing of 16S rRNA regions amplified from metagenomic samples from the 454 platform to the Illumina platform. With the increased read length (2x250bp) on the MiSeq, it is now well suited to generate 16S data for a fraction of the cost of generating data on the 454 FLX.
A typical 16S amplicon run on the 454 produces ~1M reads with an average read length of ~500 bp, which enables deep profiling of 100-200 samples. A paired-end MiSeq run generates 500 bp of sequence per amplicon and produces an average of 12M read pairs per run. We are now routinely profiling a minimum of 400 samples per run with even greater depth than possible on 454 for less than half the per-sample cost.
Please contact us for more information about our 16S profiling service using the Illumina MiSeq.
We’ve spent some time recently testing a new way to assemble PacBio data called HGAP, which stands for “hierarchical genome assembly process”. Unlike previous assemblers of PacBio data that have relied on the use of either Illumina and/or PacBio CCS reads for error correction of PacBio long reads, HGAP uses multiple alignments of all reads to perform the corrections, potentially eliminating the need for other libraries and data types. The corrected reads are assembled with an overlap-layout consensus assembler (in this case Celera Assembler) to form contigs. More details about HGAP can be read found here: https://github.com/PacificBiosciences/DevNet/wiki/Hierarchical-Genome-Assembly-Process-%28HGAP%29
We have evaluated HGAP on several of our projects and compared it to our assembly of illumina-corrected Pacbio reads assembled with Celera Assembler. So far, the results have been very encouraging and we have seen significant improvement in many cases. The chart below shows several examples:
So the assemblies are more contiguous, but are the corrections good enough to generate accurate consensus sequence? In an attempt to verify the consensus accuracy of these HGAP assemblies for several Bordetella genomes, we aligned >240x coverage of 250bp Illumina MiSeq data to the HGAP-generated contigs and looked for discrepancies and SNPs using GATK. We found no cases of high-quality, passed-filter variants, which supports a highly accurate consensus sequence generated by the HGAP assembly. We continue to test and compare HGAP with other PacBio assembly methods but are encouraged by initial results.
Ken Dewar, McGill University, highlights how PacBio Circular Consensus Sequencing could be used to sequence ‘Rhino’viruses: