Auto Tag: Single molecules

June 1, 2021  |  

Single Molecule Real Time (SMRT) sequencing sensitively detects polyclonal and compound BCR-ABL in patients who relapse on kinase inhibitor therapy.

Secondary kinase domain (KD) mutations are the most well-recognized mechanism of resistance to tyrosine kinase inhibitors (TKIs) in chronic myeloid leukemia (CML) and other cancers. In some cases, multiple drug resistant KD mutations can coexist in an individual patient (“polyclonality”). Alternatively, more than one mutation can occur in tandem on a single allele (“compound mutations”) following response and relapse to sequentially administered TKI therapy. Distinguishing between these two scenarios can inform the clinical choice of subsequent TKI treatment. There is currently no clinically adaptable methodology that offers the ability to distinguish polyclonal from compound mutations. Due to the size of the BCR-ABL KD where TKI-resistant mutations are detected, next-generation platforms are unable to generate reads of sufficient length to determine if two mutations separated by 500 nucleotides reside on the same allele. Pacific Biosciences RS Single Molecule Real-Time (SMRT) circular consensus sequencing technology is a novel third generation deep sequencing technology capable of rapidly and reliably achieving average read lengths of ~1000 bp and frequently beyond 3000 bp, allowing sequencing of the entire ABL KD on single strand of DNA. We sought to address the ability of SMRT sequencing technology to distinguish polyclonal from compound mutations using clinical samples obtained from patients who have relapsed on BCR-ABL TKI treatment.

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June 1, 2021  |  

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.

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June 1, 2021  |  

Rapid sequencing of HIV-1 genomes as single molecules from simple and complex samples.

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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June 1, 2021  |  

High-throughput analysis of full-length proviral HIV-1 genomes from PBMCs.

Background: HIV-1 proviruses in peripheral blood mononuclear cells (PBMCs) are felt to be an important reservoir of HIV-1 infection. Given that this pool represents an archival library, it can be used to study virus evolution and CD4+ T cell survival. Accurate study of this pool is burdened by difficulties encountered in sequencing a full-length proviral genome, typically accomplished by assembling overlapping pieces and imputing the full genome. Methodology: Cryopreserved PBMCs collected from a total of 8 HIV+ patients from 1997-2001 were used for genomic DNA extraction. Patients had been receiving cART for 2-8 years at the time samples were obtained. 7 patients had pVL >50 copies/mL (mean: 312,282, range: 18,372-683,400) and 1 had pVL <50. Genomic DNA was subjected to limiting dilution prior to amplification of near-full-length genomes by a newly developed nested PCR. The predicted size of the PCR product was 9.0 kb, spanning from the 5’ LTR through the 3’ LTR. Single molecules were sequenced as near-full-length amplicons directly from PCR products without shearing using commercially available P4-C2 reagents and standard protocols on a PacBio RS II instrument. Quality of the genomes was validated by clonal positive controls and synthetic mixtures. Results: Near-full-length provirus genome sequences were successfully obtained from all 8 patients as continuous long reads from single molecules. PacBio sequencing required approximately 10% of the PCR product needed for Sanger sequencing and generated 325 MB per 3-hour run including 1,800 full-length intact genome reads on average. One patient’s sample was not at a limiting dilution and analysis revealed multiple subspecies. For 8 near-fulllength provirus genomes derived from the other 7 patients, large internal deletions were noted in 2 proviruses; APOBEC-mediated hypermutations were seen in 2 proviruses; and 4 proviruses appeared to be intact genomes. All of the defective proviruses showed a complete absence of resistance mutations in either RT or protease, even after 2-8 years of cART. On the contrary, all of the intact proviruses contained evidence of ART-resistance associated mutations suggesting that they represented relatively recent variants. Conclusions: Combining a novel protocol for full-length limiting dilution amplification of proviruses with PacBio SMRT sequencing allowed for the generation of near-full-length genomes with good quality and an ability to detect minor variants at the 1-10% level. Preliminary data analyses suggest that defective proviruses may represent archival variants that persist long-term in host cells, while intact proviruses within the PBMC pool showing evidence of active virus replication may represent more recent variants.

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June 1, 2021  |  

Genomic DNA sequences of HLA class I alleles generated using multiplexed barcodes and SMRT DNA Sequencing technology.

Allelic-level resolution HLA typing is known to improve survival prognoses post Unrelated Donor (UD) Haematopoietic Stem Cell Transplantation (HSCT). Currently, many commonly used HLA typing methodologies are limited either due to the fact that ambiguity cannot be resolved or that they are not amenable to high-throughput laboratories. Pacific Biosciences’ Single Molecule Real-Time (SMRT) DNA sequencing technology enables sequencing of single molecules in isolation and has read-length capabilities to enable whole gene sequencing for HLA. DNA barcode technology labels samples with unique identifiers that can be traced throughout the sequencing process. The use of DNA barcodes means that multiple samples can be sequenced in a single experiment but data can still be attributed to the correct sample. Here we describe the results of experiments that use DNA barcodes to facilitate sequencing of multiple samples for full-length HLA class I genes (known as multiplexing).

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June 1, 2021  |  

Sequencing complex mixtures of HIV-1 genomes with single-base resolution.

A large number of distinct HIV-1 genomes can be present in a single clinical sample from a patient chronically infected with HIV-1. We examined samples containing complex mixtures of near-full-length HIV-1 genomes. Single molecules were sequenced as near-full-length (9.6 kb) amplicons directly from PCR products without shearing. Mathematical analysis techniques deconvolved the complex mixture of reads into estimates of distinct near-full-length viral genomes with their relative abundances. We correctly estimated the originating genomes to single-base resolution along with their relative abundances for mixtures where the truth was known exactly by independent sequencing methods. Correct estimates were made even when genomes diverged by a single base. Minor abundances of 5% were reliably detected. SMRT Sequencing data contained near-full-length continuous reads for each sample including some runs with greater than 10,000 near-full-length-genome reads in a three-hour collection time. SMRT Sequencing yields long- read sequencing results from individual DNA molecules with a rapid time-to-result. The single-molecule, full-length nature of the sequencing method allows us to estimate variant subspecies and relative abundances even from samples containing complex mixtures of genomes that differ by single bases. These results open the possibility of cost-effective full-genome sequencing of HIV-1 in mixed populations for applications such as incorporated-HIV-1 screening. In screening, genomes can differ by one to many thousands of bases and the ability to measure them can help scientifically inform treatment strategies.

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June 1, 2021  |  

Full-length isoform sequencing of the human MCF-7 cell line using PacBio long reads.

While advances in RNA sequencing methods have accelerated our understanding of the human transcriptome, isoform discovery remains a challenge because short read lengths require complicated assembly algorithms to infer the contiguity of full-length transcripts. With PacBio’s long reads, one can now sequence full-length transcript isoforms up to 10 kb. The PacBio Iso- Seq protocol produces reads that originate from independent observations of single molecules, meaning no assembly is needed. Here, we sequenced the transcriptome of the human MCF-7 breast cancer cell line using the Clontech SMARTer® cDNA preparation kit and the PacBio RS II. Using PacBio Iso-Seq bioinformatics software, we obtained 55,770 unique, full-length, high-quality transcript sequences that were subsequently mapped back to the human genome with = 99% accuracy. In addition, we identified both known and novel fusion transcripts. To assess our results, we compared the predicted ORFs from the PacBio data against a published mass spectrometry dataset from the same cell line. 84% of the proteins identified with the Uniprot protein database were recovered by the PacBio predictions. Notably, 251 peptides solely matched to the PacBio generated ORFs and were entirely novel, including abundant cases of single amino acid polymorphisms, cassette exon splicing and potential alternative protein coding frames.

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June 1, 2021  |  

SMRT Sequencing for the detection of low-frequency somatic variants

The sensitivity, speed, and reduced cost associated with Next-Generation Sequencing (NGS) technologies have made them indispensable for the molecular profiling of cancer samples. For effective use, it is critical that the NGS methods used are not only robust but can also accurately detect low frequency somatic mutations. Single Molecule, Real-Time (SMRT) Sequencing offers several advantages, including the ability to sequence single molecules with very high accuracy (>QV40) using the circular consensus sequencing (CCS) approach. The availability of genetically defined, human genomic reference standards provides an industry standard for the development and quality control of molecular assays. Here we characterize SMRT Sequencing for the detection of low-frequency somatic variants using the Quantitative Multiplex DNA Reference Standard from Horizon Diagnostics, combined with amplification of the variants using the Multiplicom Tumor Hotspot MASTR Plus assay. The Horizon Diagnostics reference sample contains precise allelic frequencies from 1% to 24.5% for major oncology targets verified using digital PCR. It recapitulates the complexity of tumor composition and serves as a well-characterized control. The control sample was amplified using the Multiplicom Tumor Hotspot Master Plus assay that targets 252 amplicons (121-254 bp) from 26 relevant cancer genes, which includes all 11 variants in the control sample. The amplicons were sequenced and analyzed using SMRT Sequencing to identify the variants and determine the observed frequency. The random error profile and high accuracy CCS reads make it possible to accurately detect low frequency somatic variants.

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June 1, 2021  |  

An improved circular consensus algorithm with an application to detection of HIV-1 Drug-Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger Sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach arbitrarily high quality across longer insert lengths at a lower cost and higher throughput than Sanger Sequencing. We apply this new algorithm, dubbed CCS2, to the characterization of the HIV-1 K103N drug-resistance associated mutation, which is both important clinically, and represents a challenge due to regional sequence context. A mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1,300 bp were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to arbitrarily high accuracy. This result, previously demonstrated for multi-molecule consensus sequences with the Quiver algorithm, is made possible by incorporating per-Zero Mode Waveguide (ZMW) characteristics, thus accounting for the intrinsic changes in the sequencing process that are unique to each ZMW. With CCS2, we are able to achieve a per-read empirical quality of QV30 with 19X coverage. This yields ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40. Additionally, we demonstrate a 0% miscall rate in both unmixed samples, and estimate a 48:52% frequency for the K103N mutation in the mixed sample, consistent with data produced by orthogonal platforms.

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June 1, 2021  |  

Highly sensitive and cost-effective detection of somatic cancer variants using single-molecule, real-time sequencing

Next-Generation Sequencing (NGS) technologies allow for molecular profiling of cancer samples with high sensitivity and speed at reduced cost. For efficient profiling of cancer samples, it is important that the NGS methods used are not only robust, but capable of accurately detecting low-frequency somatic mutations. Single Molecule, Real-Time (SMRT) Sequencing offers several advantages, including the ability to sequence single molecules with very high accuracy (>QV40) using the circular consensus sequencing (CCS) approach. The availability of genetically defined, human genomic reference standards provides an industry standard for the development and quality control of molecular assays for studying cancer variants. Here we characterize SMRT Sequencing for the detection of low-frequency somatic variants using the Quantitative Multiplex DNA Reference Standards from Horizon Discovery, combined with amplification of the variants using the Multiplicom Tumor Hotspot MASTR Plus assay. First, we sequenced a reference standard containing precise allelic frequencies from 1% to 24.5% for major oncology targets verified using digital PCR. This reference material recapitulates the complexity of tumor composition and serves as a well-characterized control. The control sample was amplified using the Multiplicom Tumor Hotspot MASTR Plus assay that targets 252 amplicons (121-254 bp) from 26 relevant cancer genes, which includes all 11 variants in the control sample. Next, we sequenced control samples prepared by SeraCare Life Sciences, which contained a defined mutation at allelic frequencies from 10% down to 0.1%. The wild type and mutant amplicons were serially diluted, sequenced and analyzed using SMRT Sequencing to identify the variants and determine the observed frequency. The random error profile and high-accuracy CCS reads make it possible to accurately detect low-frequency somatic variants.

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June 1, 2021  |  

An improved circular consensus algorithm with an application to detect HIV-1 Drug Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach high quality across longer insert lengths at a lower cost and higher throughput than Sanger sequencing. We applied CCS2 to the characterization of the HIV-1 K103N drug-resistance associated mutation in both clonal and patient samples. This particular DRAM has previously proved to be clinically relevant, but challenging to characterize due to regional sequence context. First, a mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1.3 kb were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Additionally, the proviral reservoir of a subject with known dates of virologic failure of an Efavirenz-based regimen and with documented emergence of drug resistant (K103N) viremia was sequenced at several time points as a proof-of-concept study to determine the kinetics of retention and decay of K103N.Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to high accuracy. With CCS2, we are able to achieve a per-read empirical quality of QV30 (99.9% accuracy) at 19X coverage. A total of ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40 (99.99%) were obtained for each sample. We demonstrate a 0% miscall rate in both unmixed control samples, and estimate a 48:52 frequency for the K103N mutation in the mixed (50:50) plasmid sample, consistent with data produced by orthogonal platforms. Additionally, the K103N escape variant was only detected in proviral samples from time points subsequent (19%) to the emergence of drug resistant viremia. This tool might be used to monitor the HIV reservoir for stable evolutionary changes throughout infection.

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June 1, 2021  |  

Comprehensive variant detection in a human genome with PacBio high-fidelity reads

Human genomic variations range in size from single nucleotide substitutions to large chromosomal rearrangements. Sequencing technologies tend to be optimized for detecting particular variant types and sizes. Short reads excel at detecting SNVs and small indels, while long or linked reads are typically used to detect larger structural variants or phase distant loci. Long reads are more easily mapped to repetitive regions, but tend to have lower per-base accuracy, making it difficult to call short variants. The PacBio Sequel System produces two main data types: long continuous reads (up to 100 kbp), generated by single passes over a long template, and Circular Consensus Sequence (CCS) reads, generated by calculating the consensus of many sequencing passes over a single shorter template (500 bp to 20 kbp). The long-range information in continuous reads is useful for genome assembly and structural variant detection. The higher base accuracy of CCS effectively detects and phases short variants in single molecules. Recent improvements in library preparation protocols and sequencing chemistry have increased the length, accuracy, and throughput of CCS reads. For the human sample HG002, we collected 28-fold coverage 15 kbp high-fidelity CCS reads with an average read quality above Q20 (99% accuracy). The length and accuracy of these reads allow us to detect SNVs, indels, and structural variants not only in the Genome in a Bottle (GIAB) high confidence regions, but also in segmental duplications, HLA loci, and clinically relevant “difficult-to-map” genes. As with continuous long reads, we call structural variants at 90.0% recall compared to the GIAB structural variant benchmark “truth” set, with the added advantages of base pair resolution for variant calls and improved recall at compound heterozygous loci. With minimap2 alignments, GATK4 HaplotypeCaller variant calls, and simple variant filtration, we have achieved a SNP F-Score of 99.51% and an INDEL F-Score of 80.10% against the GIAB short variant benchmark “truth” set, in addition to calling variants outside of the high confidence region established by GIAB using previous technologies. With the long-range information available in 15 kbp reads, we applied the read-backed phasing tool WhatsHap to generate phase blocks with a mean length of 65 kbp across the entire genome. Using an alignment-based approach, we typed all major MHC class I and class II genes to at least 3-field precision. This new data type has the potential to expand the GIAB high confidence regions and “truth” benchmark sets to many previously difficult-to-map genes and allow a single sequencing protocol to address both short variants and large structural variants.

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June 1, 2021  |  

The value of long read amplicon sequencing for clinical applications

NGS is commonly used for amplicon sequencing in clinical applications to study genetic disorders and detect disease-causing mutations. This approach can be plagued by limited ability to phase sequence variants and makes interpretation of sequence data difficult when pseudogenes are present. Long-read highly accurate amplicon sequencing can provide very accurate, efficient, high throughput (through multiplexing) sequences from single molecules, with read lengths largely limited by PCR. Data is easy to interpret; phased variants and breakpoints are present within high fidelity individual reads. Here we show SMRT Sequencing of the PMS2 and OPN1 (MW and LW) genes using the Sequel System. Homologous regions make NGS and MLPA results very difficult to interpret.

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