SMRT Sequencing is a DNA sequencing technology characterized by long read lengths and high consensus accuracy, regardless of the sequence complexity or GC content of the DNA sample. These characteristics…
This webinar, presented by Nisha Pillai, provides an overview of amplicon sequencing to target specific regions of a genome using PacBio Single Molecule, Real-Time (SMRT) Sequencing. This session provides an…
In this presentation, Shawn Levy from the HudsonAlpha Institute for Biotechnology and HudsonAlpha Discovery offers a look at his team’s early access experience with the Sequel II System. Recent work…
In this PacBio User Group Meeting presentation, Eugenio Daviso from Covaris talks about the use of adaptive focused acoustics for gentle cell lysis and extraction of high molecular weight DNA.
In this PacBio User Group Meeting lightning talk, Masako Nakanishi presents a study of how the gut microbiome alters an organism’s susceptibility to colonic ulceration; next, she plans to examine…
New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls =50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90 % of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3 %, and genotype concordance with manual curation was >98.7 %. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.
Over the past decade, RNA sequencing (RNA-seq) has become an indispensable tool for transcriptome-wide analysis of differential gene expression and differential splicing of mRNAs. However, as next-generation sequencing technologies have developed, so too has RNA-seq. Now, RNA-seq methods are available for studying many different aspects of RNA biology, including single-cell gene expression, translation (the translatome) and RNA structure (the structurome). Exciting new applications are being explored, such as spatial transcriptomics (spatialomics). Together with new long-read and direct RNA-seq technologies and better computational tools for data analysis, innovations in RNA-seq are contributing to a fuller understanding of RNA biology, from questions such as when and where transcription occurs to the folding and intermolecular interactions that govern RNA function.
Cell-free DNA (cfDNA) fragments in maternal plasma contain DNA damage and may negatively impact the sensitivity of noninvasive prenatal testing (NIPT). However, some of these DNA damages are potentially reparable. We aimed to recover these damaged cfDNA molecules using PreCR DNA repair mix.cfDNA was extracted from 20 maternal plasma samples and was repaired and sequenced by the Illumina platform. Size profiles and fetal DNA fraction changes of repaired samples were characterized. Targeted sequencing of chromosome Y sequences was used to enrich fetal cfDNA molecules following repair. Single-molecule real-time (SMRT) sequencing platform was employed to characterize long (>250 bp) cfDNA molecules. NIPT of five trisomy 21 samples was performed.Size profiles of repaired libraries were altered, with significantly increased long (>250 bp) cfDNA molecules. Single nucleotide polymorphism (SNP)-based analyses showed that both fetal- and maternal-derived cfDNA molecules were enriched by the repair. Fetal DNA fractions in maternal plasma showed a small but consistent (4.8%) increase, which were contributed by a higher increment of long fetal cfDNA molecules. z-score values were improved in NIPT of all trisomy 21 samples.Plasma DNA repair recovers and enriches long cfDNA molecules of both fetal and maternal origins in maternal plasma. © 2018 John Wiley & Sons, Ltd.
Comparative genomics can unravel the genetic basis of species differences; however, successful reports on quantitative traits are still scarce. Here we present genome assemblies of 31 so-far unassembled Brassicaceae plant species and combine them with 16 previously published assemblies to establish the Brassicaceae Diversity Panel. Using a new interspecies association strategy for quantitative traits, we found a so-far unknown association between the unexpectedly high variation in CG to TG substitution rates in genes and the absence of CHROMOMETHYLASE3 (CMT3) orthologues. Low substitution rates were associated with the loss of CMT3, while species with conserved CMT3 orthologues showed high substitution rates. Species without CMT3 also lacked gene-body methylation (gbM), suggesting an evolutionary trade-off between the unknown function of gbM and low substitution rates in Brassicaceae, possibly due to low mutability of non-methylated cytosines.
Activating mutations in PIK3CA are frequent in human breast cancer, and phosphoinositide 3-kinase alpha (PI3Ka) inhibitors have been approved for therapy. To characterize determinants of sensitivity to these agents, we analyzed PIK3CA-mutant cancer genomes and observed the presence of multiple PIK3CA mutations in 12 to 15% of breast cancers and other tumor types, most of which (95%) are double mutations. Double PIK3CA mutations are in cis on the same allele and result in increased PI3K activity, enhanced downstream signaling, increased cell proliferation, and tumor growth. The biochemical mechanisms of dual mutations include increased disruption of p110a binding to the inhibitory subunit p85a, which relieves its catalytic inhibition, and increased p110a membrane lipid binding. Double PIK3CA mutations predict increased sensitivity to PI3Ka inhibitors compared with single-hotspot mutations.Copyright © 2019 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Next generation DNA sequencing is used to determine the HLA-A, -B, -C, -DRB1, -DRB3/4/5, and -DQB1 assignments of 1009 unrelated volunteers for the unrelated donor registry in The Netherlands. The analysis characterizes all HLA exons and introns for class I alleles; at least exons 2 to 3 for HLA-DRB1; and exons 2 to 6 for HLA-DQB1. Of the distinct alleles present, there are 229 class I and 71 class II; 36 of these alleles are novel. The majority (approximately 98%) of the cumulative allele frequency at each locus is contributed by alleles that appear three or more times. Alleles encoding protein variation outside of the antigen recognition domains are 0.6% of the class I assignments and 5.3% of the class II assignments. © 2019 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Comprehensive molecular characterization of myriad somatic alterations and aberrant gene expressions at personal level is key to precision cancer therapy, yet limited by current short-read sequencing technology, individualized catalog of complete genomic and transcriptomic features is thus far elusive. Here, we integrated second- and third-generation sequencing platforms to generate a multidimensional dataset on a patient affected by metastatic epithelial ovarian cancer. Whole-genome and hybrid transcriptome dissection captured global genetic and transcriptional variants at previously unparalleled resolution. Particularly, single-molecule mRNA sequencing identified a vast array of unannotated transcripts, novel long noncoding RNAs and gene chimeras, permitting accurate determination of transcription start, splice, polyadenylation and fusion sites. Phylogenetic and enrichment inference of isoform-level measurements implicated early functional divergence and cytosolic proteostatic stress in shaping ovarian tumorigenesis. A complementary imaging-based high-throughput drug screen was performed and subsequently validated, which consistently pinpointed proteasome inhibitors as an effective therapeutic regime by inducing protein aggregates in ovarian cancer cells. Therefore, our study suggests that clinical application of the emerging long-read full-length analysis for improving molecular diagnostics is feasible and informative. An in-depth understanding of the tumor transcriptome complexity allowed by leveraging the hybrid sequencing approach lays the basis to reveal novel and valid therapeutic vulnerabilities in advanced ovarian malignancies.
IGH@ proto-oncogene translocation is a common oncogenic event in lymphoid lineage cancers such as B-ALL, lymphoma and multiple myeloma. Here, to investigate the interplay between IGH@ proto-oncogene translocation and IGH allelic exclusion, we perform long-read whole-genome and transcriptome sequencing along with epigenetic and 3D genome profiling of Nalm6, an IGH-DUX4 positive B-ALL cell line. We detect significant allelic imbalance on the wild-type over the IGH-DUX4 haplotype in expression and epigenetic data, showing IGH-DUX4 translocation occurs on the silenced IGH allele. In vitro, this reduces the oncogenic stress of DUX4 high-level expression. Moreover, patient samples of IGH-DUX4 B-ALL have similar expression profile and IGH breakpoints as Nalm6, suggesting a common mechanism to allow optimal dosage of non-toxic DUX4 expression.
Recombinant adeno-associated virus (rAAV)-based gene therapy has entered a phase of clinical translation and commercialization. Despite this progress, vector integrity following production is often overlooked. Compromised vectors may negatively impact therapeutic efficacy and safety. Using single molecule, real-time (SMRT) sequencing, we can comprehensively profile packaged genomes as a single intact molecule and directly assess vector integrity without extensive preparation. We have exploited this methodology to profile all heterogeneic populations of self-complementary AAV genomes via bioinformatics pipelines and have coined this approach AAV-genome population sequencing (AAV-GPseq). The approach can reveal the relative distribution of truncated genomes versus full-length genomes in vector preparations. Preparations that seemingly show high genome homogeneity by gel electrophoresis are revealed to consist of less than 50% full-length species. With AAV-GPseq, we can also detect many reverse-packaged genomes that encompass sequences originating from plasmid backbone, as well as sequences from packaging and helper plasmids. Finally, we detect host-cell genomic sequences that are chimeric with inverted terminal repeat (ITR)-containing vector sequences. We show that vector populations can contain between 1.3% and 2.3% of this type of undesirable genome. These discoveries redefine quality control standards for viral vector preparations and highlight the degree of foreign products in rAAV-based therapeutic vectors.
Studies indicate that more than 90% of human genes are alternatively spliced, suggesting the complexity of the transcriptome assembly and analysis. The splicing process is often disrupted, resulting in both functional and non-functional end-products (Sveen et al. 2016) in many cancers. Harnessing the immune system to fight against malignant cancers carrying aberrantly mutated or spliced products is becoming a promising approach to cancer therapy. Advances in immune checkpoint blockade have elicited adaptive immune responses with promising clinical responses to treatments against human malignancies (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Emerging data suggest that recognition of patient-specific mutation-associated cancer antigens (i.e. from alternative splicing isoforms) may allow scientists to dissect the immune response in the activity of clinical immunotherapies (Schumacher and Schreiber 2015). The advent of high-throughput sequencing technology has provided a comprehensive view of both splicing aberrations and somatic mutations across a range of human malignancies, allowing for a deeper understanding of the interplay of various disease mechanisms. Meanwhile, studies show that the number of transcript isoforms reported to date may be limited by the short-read sequencing due to the inherit limitation of transcriptome reconstruction algorithms, whereas long-read sequencing is able to significantly improve the detection of alternative splicing variants since there is no need to assemble full-length transcripts from short reads. The analysis of these high-throughput long-read sequencing data may permit a systematic view of tumor specific peptide epitopes (also known as neoantigens) that could serve as targets for immunotherapy (Tumor Neoantigens in Personalized Cancer Immunotherapy 2017). Currently, there is no software pipeline available that can efficiently produce mutation-associated cancer antigens from raw high-throughput sequencing data on patient tumor DNA (The Problem with Neoantigen Prediction 2017). In addressing this issue, we introduce a R package that allows the discoveries of peptide epitope candidates, which are the tumor-specific peptide fragments containing potential functional neoantigens. These peptide epitopes consist of structure variants including insertion, deletions, alternative sequences, and peptides from nonsynonymous mutations. Analysis of these precursor candidates with widely used tools such as netMHC allows for the accurate in-silico prediction of neoantigens. The pipeline named neoantigeR is currently hosted in https://github.com/ICBI/neoantigeR.
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