Learn how Single Molecule, Real-Time (SMRT) Sequencing and the Sequel IIe System and will accelerate your research by delivering highly accurate long reads to provide the most comprehensive view of genomes, transcriptomes and epigenomes.
In this SMRT Science Journal Club talk, John Lovell from HudsonAlpha Institute for Biotechnology discusses his work constructing and analyzing de novo pecan genome assemblies and annotations to help accelerate…
Generation of Lineage-Resolved Complete Metagenome-Assembled Genomes in Complex Microbial Communities
In this SMRT Science Journal Club talk, Mikhail Kolmogorov from the University of California Santa Cruz discusses his computational approach to the generation of lineage-resolved complete MAGs by precision phasing.
With SMRT Link you can unlock the power of PacBio Single Molecule, Real-Time (SMRT) Sequencing using our portfolio of software tools designed to set up and monitor sequencing runs, review performance metrics, analyze, visualize, and annotate your sequencing data.
At Cold Spring Harbor Laboratory, scientists used SMRT Sequencing to decode one of the most challenging cancer genomes ever encountered. Along the way, they built a portfolio of open-access analysis tools that will help researchers everywhere make structural variation discoveries with long-read sequencing data.
Complete HIV-1 genomes from single molecules: Diversity estimates in two linked transmission pairs using clustering and mutual information.
We sequenced complete HIV-1 genomes from single molecules using Single Molecule, Real- Time (SMRT) Sequencing and derive de novo full-length genome sequences. SMRT sequencing yields long-read sequencing results from individual DNA molecules with a rapid time-to-result. These attributes make it a useful tool for continuous monitoring of viral populations. The single-molecule nature of the sequencing method allows us to estimate variant subspecies and relative abundances by counting methods. We detail mathematical techniques used in viral variant subspecies identification including clustering distance metrics and mutual information. Sequencing was performed in order to better understand the relationships between the specific sequences of transmitted viruses in linked transmission pairs. Samples representing HIV transmission pairs were selected from the Zambia Emory HIV Research Project (Lusaka, Zambia) and sequenced. We examine Single Genome Amplification (SGA) prepped samples and samples containing complex mixtures of genomes. Whole genome consensus estimates for each of the samples were made. Genome reads were clustered using a simple distance metric on aligned reads. Appropriate thresholds were chosen to yield distinct clusters of HIV genomes within samples. Mutual information between columns in the genome alignments was used to measure dependence. In silico mixtures of reads from the SGA samples were made to simulate samples containing exactly controlled complex mixtures of genomes and our clustering methods were applied to these complex mixtures. SMRT Sequencing data contained multiple full-length (greater than 9 kb) continuous reads for each sample. Simple whole genome consensus estimates easily identified transmission pairs. The clustering of the genome reads showed diversity differences between the samples, allowing us to characterize the diversity of the individual quasi-species comprising the patient viral populations across the full genome. Mutual information identified possible dependencies of different positions across the full HIV-1 genome. The SGA consensus genomes agreed with prior Sanger sequencing. Our clustering methods correctly segregated reads to their correct originating genome for the synthetic SGA mixtures. The results open up the potential for reference-agnostic and cost effective full genome sequencing of HIV-1.
Advances in sequence consensus and clustering algorithms for effective de novo assembly and haplotyping applications.
One of the major applications of DNA sequencing technology is to bring together information that is distant in sequence space so that understanding genome structure and function becomes easier on a large scale. The Single Molecule Real Time (SMRT) Sequencing platform provides direct sequencing data that can span several thousand bases to tens of thousands of bases in a high-throughput fashion. In contrast to solving genomic puzzles by patching together smaller piece of information, long sequence reads can decrease potential computation complexity by reducing combinatorial factors significantly. We demonstrate algorithmic approaches to construct accurate consensus when the differences between reads are dominated by insertions and deletions. High-performance implementations of such algorithms allow more efficient de novo assembly with a pre-assembly step that generates highly accurate, consensus-based reads which can be used as input for existing genome assemblers. In contrast to recent hybrid assembly approach, only a single ~10 kb or longer SMRTbell library is necessary for the hierarchical genome assembly process (HGAP). Meanwhile, with a sensitive read-clustering algorithm with the consensus algorithms, one is able to discern haplotypes that differ by less than 1% different from each other over a large region. One of the related applications is to generate accurate haplotype sequences for HLA loci. Long sequence reads that can cover the whole 3 kb to 4 kb diploid genomic regions will simplify the haplotyping process. These algorithms can also be applied to resolve individual populations within mixed pools of DNA molecules that are similar to each, e.g., by sequencing viral quasi-species samples.
A comparison of 454 GS FLX Ti and PacBio RS in the context of characterizing HIV-1 intra-host diversity.
PacBio 2013 User Group Meeting Presentation Slides: Lance Hepler from UC San Diego’s Center for AIDS Research used the PacBio RS to study intra-host diversity in HIV-1. He compared PacBio’s performance to that of 454® sequencer, the platform he and his team previously used. Hepler noted that in general, there was strong agreement between the platforms; where results differed, he said that PacBio data had significantly better reproducibility and accuracy. “PacBio does not suffer from local coverage loss post-processing, whereas 454 has homopolymer problems,” he noted. Hepler said they are moving away from using 454 in favor of the PacBio system.