Structural variation accounts for much of the variation among human genomes. Structural variants of all types are known to cause Mendelian disease and contribute to complex disease. Learn how long-read sequencing is enabling detection of the full spectrum of structural variants to advance the study of human disease, evolution and genetic diversity.
The Sequel System, powered by Single Molecule, Real Time (SMRT) Technology, delivers long reads, high consensus accuracy, uniform coverage and epigenetic characterization.
The Sequel II System, powered by Single Molecule, Real Time (SMRT) Technology, delivers highly accurate long reads for a comprehensive view of genomes, transcriptomes and epigenomes.
Interested to learn about pangenomes? Explore this guide to learn how they provide a more complete picture of the core genes of a given species and how that can provide better biological understanding.
As the foundation for scientific discoveries in genetic diversity, sequencing data must be accurate and complete. With highly accurate long-read sequencing, or HiFi sequencing, there is no longer a compromise between read length and accuracy. HiFi sequencing enables some of the highest quality de novo genome assemblies available today as well as comprehensive variant detection in human samples. PacBio HiFi libraries constructed using our standard library workflows require at least 3 µg of DNA input per 1 Gb of genome length, or ~10 µg for a human sample. For some samples it is not possible to extract this amount of DNA for sequencing. For samples where between 300 ng and 3 ug of DNA is available, the Low DNA Input Workflow enables users to generate high-quality genome assemblies of small-bodied organisms. For samples where even less DNA is available (as low as 5 ng), the amplification-based Ultra-Low DNA Input Workflow is available.
The study of genomics has revolutionized our understanding of science, but the field of transcriptomics grew with the need to explore the functional impacts of genetic variation. While different tissues in an organism may share the same genomic DNA, they can differ greatly in what regions are transcribed into RNA and in their patterns of RNA processing. By reviewing the history of transcriptomics, we can see the advantages of RNA sequencing using a full-length transcript approach become clearer.
At DuPont Pioneer, DNA sequencing is paramount for R&D to reveal the genetic basis for traits of interest in commercial crops such as maize, soybean, sorghum, sunflower, alfalfa, canola, wheat, rice, and others. They cannot afford to wait the years it has historically taken for high-quality reference genomes to be produced. Nor can they rely on a single reference to represent the genetic diversity in its germplasm.
To bring personalized medicine to all patients, cancer researchers need more reliable and comprehensive views of somatic variants of all sizes that drive cancer biology.
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.
With PacBio single-cell RNA sequencing using the Iso-Seq method, you can now distinguish between alternative transcript isoforms at the single-cell level. The highly accurate long reads (HiFi reads) can span the entire 5′ to 3′ end of a transcript, allowing a high-resolution view of isoform diversity and revealing cell-to-cell heterogeneity without the need for assembly.
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.
In this study we demonstrate the utility of Single-Molecule Real Time SMRT sequencing to detect variants and to recapitulate whole mitochondrial genomes in an association study of Metabolic syndrome using samples from a well-studied cohort from Micronesia. The Micronesian island of Kosrae is a rare genetic isolate that offers significant advantages for genetic studies of human disease. Kosrae suffers from one of the highest rates of MetS (41%), obesity (52%), and diabetes (17%) globally and has a homogeneous environment making this an excellent population in which to study these significant health problems. We are conducting family-based association analyses aimed at identifying specific mitochondrial variants that contribute to obesity and other co-morbid conditions. We sequenced whole mitochondrial genomes from 10 Kosraen individuals who represent greater than 25 % of the mitochondrial genetic diversity for the entire Kosraen population. Using Pacific Biosciences C2 chemistry, SMRTbell libraries were constructed from pooled, full-length, unsheared 5 kb PCR amplicons, tiling the entire 16.6 kb mtDNA genome. Average read lengths for each sample were between 2500-3000 bp, with 5% of reads between 6,000-8,000 bases, depending on movie lengths. The data generated in this study serve as proof of principle that SMRT Sequencing data can be utilized for identification of high-quality variants and complete mitochondrial genome sequences. These data will be leveraged to identify causative variants for Metabolic syndrome and associated disorders.
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.
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.
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