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Learn why it is critically important to understand accuracy in DNA sequencing to distinguish important biological information from sequencing errors.
Our understanding of microbiology has evolved enormously over the last 150 years. Few institutions have witnessed our collective progress more closely than the National Collection of Type Cultures (NCTC). In fact, the collection itself is a record of the many milestones microbiologists have crossed, building on the discoveries of those who came before. To date, 60% of NCTC’s historic collection now has a closed, finished reference genome, thanks to PacBio Single Molecule, Real- Time (SMRT) Sequencing. We are excited to be their partner in crossing this latest milestone on their quest to improve human and animal health by understanding the microscopic world.
The bacteria living on and within us can impact health, disease, and even our behavior, but there is still much to learn about the breadth of their effects. The torrent of new discoveries unleashed by high-throughput sequencing has captured the imagination of scientists and the public alike. Scientists at Second Genome are hoping to apply these insights to improve human health, leveraging their bioinformatics expertise to mine bacterial communities for potential therapeutics. Recently they teamed up with scientists at PacBio to explore how long-read sequencing might supplement their short-read-based pipeline for gene discovery, using an environmental sample as a test case. They were especially interested in identifying unique, complete, and error-free gene clusters in metagenomic assemblies.
The UK’s National Collection of Type Cultures (NCTC) is a unique collection of more than 5,000 expertly preserved and authenticated bacterial cultures, many of historical significance. Founded in 1920, NCTC is the longest established collection of its type anywhere in the world, with a history of its own that has reflected — and contributed to — the evolution of microbiology for more than 100 years.
Many scientists are using PacBio Single Molecule, Real-Time (SMRT) Sequencing to explore the genomes and transcriptomes of a wide variety of marine species and ecosystems. These studies are already adding to our understanding of how marine species adapt and evolve, contributing to conservation efforts, and informing how we can optimize food production through efficient aquaculture.
Discover the benefits of HiFi reads and learn how highly accurate long-read sequencing provides a single technology solution across a range of applications.
Highly accurate long reads – HiFi reads – with single-molecule resolution make Single Molecule, Real-Time (SMRT) Sequencing ideal for full-length 16S rRNA sequencing, shotgun metagenomic profiling, and metagenome assembly.
Shiga toxin-producing Escherichia coli (STEC) is an emerging pathogen. Recently there has been a global in the number of outbreaks caused by non-O157 STECs, typically involving six serogroups O26, O45, 0103, 0111, and 0145. STEC O145:H28 has been associated with severe human disease including hemolytic-uremic syndrome (HUS), and is demonstrated by the 2007 Belgian ice-cream-associated outbreak and 2010 US lettuce-associated outbreak, with over 10% of patients developing HUS in each. The goal of this work was to do comparative genomics of strains, clinical and environmental, to investigate genome diversity and virulence evolution of this important foodborne pathogen.
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.
Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single-nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non- pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA Sequencing with short reads (SMRT CCS (circular consensus) or second-generation reads), wherein the short reads are used to error-correct the long reads which are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which SMRT sequencing reads from a single long insert library are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run, and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) for numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT Sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. With relatively short sequencing run times and automated analysis pipelines, it is possible to go from an unknown DNA sample to its complete de novo genome and epigenome in about a day.
Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non-pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA sequencing with short, high-accuracy reads (SMRT (circular consensus sequencing) CCS or second-generation reads) to generate long, highly accurate reads that are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which long SMRT sequencing reads (average readlengths >5,000 bases) are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) to numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. The process has been automated and requires less than 1 day from an unknown DNA sample to its complete de novo genome and epigenome.
Background: To better understand the relationships among HIV-1 viruses in linked transmission pairs, we sequenced several samples representing HIV transmission pairs from the Zambia Emory HIV Research Project (Lusaka, Zambia) using Single Molecule, Real-Time (SMRT) Sequencing. Methods: Single molecules were sequenced as full-length (9.6 kb) amplicons directly from PCR products without shearing. This resulted in multiple, fully-phased, complete HIV-1 genomes for each patient. We examined Single Genome Amplification (SGA) prepped samples, as well as samples containing complex mixtures of genomes. We detail mathematical techniques used in viral variant subspecies identification, including clustering distance metrics and mutual information, which were used to derive multiple de novo full-length genome sequences for each patient. Whole genome consensus estimates for each sample were made. Genome reads were clustered using a simple distance metric on aligned reads. Appropriate thresholds were chosen to yield distinct clusters of HIV-1 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. Results: SMRT Sequencing data contained multiple full-length (>9 kb) continuous reads for each sample. Simple whole-genome consensus estimates easily identified transmission pairs. Clustering of genome reads showed diversity differences between samples, allowing characterization of the quasi-species diversity 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. Conclusions: 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. The results open up the potential for reference-agnostic and cost effective full genome sequencing of HIV-1.
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.
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