In 2012, NIST convened the Genome in a Bottle Consortium to develop the metrology infrastructure needed to enable confidence in human whole genome variant calls.
AGBT 2015 Workshop Presentation Slides: Dick McCombie from Cold Spring Harbor Laboratory (CSHL) described the use of SMRT Sequencing to analyze a breast cancer cell line with complex genomic events. Still ongoing, the project has already uncovered structural variants missed by other sequencers.
The long reads, random error, and unbiased sampling of SMRT Sequencing enables high quality, de novo assembly of the human genome. PacBio long reads are capable of resolving genomic variations at all size scales, including SNPs, insertions, deletions, inversions, translocations, and repeat expansions, all of which are important in understanding the genetic basis for human disease and difficult to access via other technologies. In demonstration of this, we report a new high-quality, diploid aware de novo assembly of Craig Venter’s well-studied genome.
2015 SMRT Informatics Developers Conference Presentation Slides: Shinichi Morishita of the University of Tokyo presented on how his team has been using SMRT Sequencing to better understand methylomes, metagenomes and structural variation of various eukaryotic genomes.
The Genome in a Bottle Consortium is developing the reference materials, reference methods , and reference data n
Purpose: Clinical laboratories, research laboratories and technology developers all need DNA samples with reliably known genotypes in order to help validate and improve their methods. The Genome in a Bottle Consortium (genomeinabottle.org) has been developing Reference Materials with high-accuracy whole genome sequences to support these efforts.Methodology: Our pilot reference material is based on Coriell sample NA12878 and was released in May 2015 as NIST RM 8398 (tinyurl.com/giabpilot). To minimize bias and improve accuracy, 11 whole-genome and 3 exome data sets produced using 5 different technologies were integrated using a systematic arbitration method [1]. The Genome in a Bottle Analysis Group is adapting these methods and developing new methods to characterize 2 families, one Asian and one Ashkenazi Jewish from the Personal Genome Project, which are consented for public release of sequencing and phenotype data. We have generated a larger and even more diverse data set on these samples, including high-depth Illumina paired-end and mate-pair, Complete Genomics, and Ion Torrent short-read data, as well as Moleculo, 10X, Oxford Nanopore, PacBio, and BioNano Genomics long-read data. We are analyzing these data to provide an accurate assessment of not just small variants but also large structural variants (SVs) in both “easy” regions of the genome and in some “hard” repetitive regions. We have also made all of the input data sources publicly available for download, analysis, and publication.Results: Our arbitration method produced a reference data set of 2,787,291 single nucleotide variants (SNVs), 365,135 indels, 2744 SVs, and 2.2 billion homozygous reference calls for our pilot genome. We found that our call set is highly sensitive and specific in comparison to independent reference data sets. We have also generated preliminary assemblies and structural variant calls for the next 2 trios from long read data and are currently integrating and validating these.Discussion: We combined the strengths of each of our input datasets to develop a comprehensive and accurate benchmark call set. In the short time it has been available, over 20 published or submitted papers have used our data. Many challenges exist in comparing to our benchmark calls, and thus we have worked with the Global Alliance for Genomics and Health to develop standardized methods, performance metrics, and software to assist in its use.[1] Zook et al, Nat Biotech. 2014.
Structural Variants (SVs), which include deletions, insertions, duplications, inversions and chromosomal rearrangements, have been shown to effect organism phenotypes, including changing gene expression, increasing disease risk, and playing an important role in cancer development. Still it remains challenging to detect all types of SVs from high throughput sequencing data and it is even harder to detect more complex SVs such as a duplication nested within an inversion. To overcome these challenges we developed algorithms for SV analysis using longer third generation sequencing reads. The increased read lengths allow us to span more complex SVs and accurately assess SVs in repetitive regions, two of the major limitations when using short Illumina data. Our enhanced open-source analysis method Sniffles accurately detects structural variants based on split read mapping and assessment of the alignments. Sniffles uses a self-balancing interval tree in combination with a plane sweep algorithm to manage and assess the identified SVs. Central to its high accuracy is its advanced scoring model that can distinguish erroneous alignments from true breakpoints flanking SVs. In experiments with simulated and real genomes (e.g human breast cancer), we find that Sniffles outperforms all other SV analysis approaches in both the sensitivity of finding events as well as the specificity of those events. Sniffles is available at: https://github.com/fritzsedlazeck/Sniffles
With the increasing availability of whole-genome sequencing, haplotype reconstruction of individual genomes, or haplotype assembly, remains unsolved. Like the de novo genome assembly problem, haplotype assembly is greatly simplified by having more long-range information. The Targeted Locus Amplification (TLA) technology from Cergentis has the unique capability of targeting a specific region of the genome using a single primer pair and yielding ~2 kb DNA circles that are comprised of ~500 bp fragments. Fragments from the same circle come from the same haplotype and follow an exponential decay in distance from the target region, with a span that reaches the multi-megabase range. Here, we apply TLA to the BRCA1 gene on NA12878 and then sequence the resulting 2 kb circles on a PacBio RS II. The multiple fragments per circle were iteratively mapped to hg19 and then haplotype assembled using HAPCUT. We show that the 80 kb length of BRCA1 is represented by a single haplotype block, which was validated against GIAB data. We then explored chromosomal-scale haplotype assembly by combining these data with whole genome shotgun PacBio long reads, and demonstrate haplotype blocks approaching the length of chromosome 17 on which BRCA1 lies. Finally, by performing TLA without the amplification step and size selecting for reads >5 kb to maximize the number of fragments per read, we target whole genome haplotype assembly across all chromosomes.
The long reads, random error, and unbiased sampling of SMRT Sequencing enables high quality, de novo assembly of the human genome. PacBio long reads are capable of resolving genomic variations at all size scales, including SNPs, insertions, deletions, inversions, translocations, and repeat expansions, all of which are both important in understanding the genetic basis for human disease, and difficult to access via other technologies. In demonstration of this, we report a new high-quality, diploid-aware de novo assembly of Craig Venter’s well-studied genome.
Sequence-based estimation of genetic diversity of Plasmodium falciparum, the most lethal malarial parasite, has proved challenging due to a lack of a complete genomic assembly. The skewed AT-richness (~80.6% (A+T)) of its genome and the lack of technology to assemble highly polymorphic sub-telomeric regions that contain clonally variant, multigene virulence families (i.e. var and rifin) have confounded attempts using short-read NGS technologies. Using single molecule, real-time (SMRT) sequencing, we successfully compiled all 14 nuclear chromosomes of the P. falciparum genome from telomere-to-telomere in single contigs. Specifically, amplification-free sequencing generated reads of average length 12 kb, with =50% of the reads between 15.5 and 50 kb in length. A hierarchical genome assembly process (HGAP), was used to assemble the P. falciparum genome de novo. This assembly accurately resolved centromeres (~90-99% (A+T)) and sub-telomeric regions, and identified large insertions and duplications in the genome that added extra genes to the var and rifin virulence families, along with smaller structural variants such as homopolymer tract expansions. These regions can be used as markers for genetic diversity during comparative genome analyses. Moreover, identifying the polymorphic and repetitive sub-telomeric sequences of parasite populations from endemic areas might inform the link between structural variation and phenotypes such as virulence, drug resistance and disease transmission.
Alzheimer’s disease (AD) is a devastating neurodegenerative disease that is genetically complex. Although great progress has been made in identifying fully penetrant mutations in genes such as APP, PSEN1 and PSEN2 that cause early-onset AD, these still represent a very small percentage of AD cases. Large-scale, genome-wide association studies (GWAS) have identified at least 20 additional genetic risk loci for the more common form of late-onset AD. However, the identified SNPs are typically not the actual risk variants, but are in linkage disequilibrium with the presumed causative variant (Van Cauwenberghe C, et al., The genetic landscape of Alzheimer disease: clinical implications and perspectives. Genet Med 2015;18:421-430). Long-read sequencing together with hybrid-capture targeting technologies provides a powerful combination to target candidate genes/transcripts of interest. Shearing the genomic DNA to ~5 kb fragments and then capturing with probes that span the whole gene(s) of interest can provide uniform coverage across the entire region, identifying variants and allowing for phasing into two haplotypes. Furthermore, capturing full-length cDNA from the same sample using the same capture probes can also provide an understanding of isoforms that are generated and allow them to be assigned to their corresponding haplotype. Here we present a method for capturing genomic DNA and cDNA from an AD sample using a panel of probes targeting approximately 20 late-onset AD candidate genes which includes CLU, ABCA7, CD33, TREM2, TOMM40, PSEN2, APH1 and BIN1. By combining xGen® Lockdown® probes with SMRT Sequencing, we provide completely sequenced candidate genes as well as their corresponding transcripts. In addition, we are also able to evaluate structural variants that due to their size, repetitive nature, or low sequence complexity have been un-sequenceable using short-read technologies.
Genes associated with several neurological disorders have been shown to be highly polymorphic. Targeted sequencing of these genes using NGS technologies is a powerful way to increase the cost-effectiveness of variant discovery and detection. However, for a comprehensive view of these target genes, it is necessary to have complete and uniform coverage across regions of interest. Unfortunately, short-read sequencing technologies are not ideal for these types of studies as they are prone to mis-mapping and often fail to span repetitive regions. Targeted sequencing with PacBio long reads provides the unique advantage of single-molecule observations of complex genomic regions. PacBio long reads not only provide continuous sequence data though polymorphic or repetitive regions, but also have no GC bias. Here we describe the characterization of the poly-T locus in TOMM40, a gene known to be associated with progression to Alzheimer’s, using PacBio long reads. Probes were designed to capture a 20 kb region comprising the TOMM40 and ApoE genes. Target regions were captured in multiple cell lines and sequencing libraries made using standard sample preparation methods. We will present our results on the poly-T structural variants that we observed in TOMM40 in these cell lines. We will also present our results on probe design optimization and barcoding strategies for a cost-effective solution.
The human immunoglobulin heavy chain locus (IGH) remains among the most understudied regions of the human genome. Recent efforts have shown that haplotype diversity within IGH is elevated and exhibits population specific patterns; for example, our re-sequencing of the locus from only a single chromosome uncovered >100 Kb of novel sequence, including descriptions of six novel alleles, and four previously unmapped genes. Historically, this complex locus architecture has hindered the characterization of IGH germline single nucleotide, copy number, and structural variants (SNVs; CNVs; SVs), and as a result, there remains little known about the role of IGH polymorphisms in inter-individual antibody repertoire variability and disease. To remedy this, we are taking a multi-faceted approach to improving existing genomic resources in the human IGH region. First, from whole-genome and fosmid-based datasets, we are building the largest and most ethnically diverse set of IGH reference assemblies to date, by employing PacBio long-read sequencing combined with novel algorithms for phased haplotype assembly. In total, our effort will result in the characterization of >15 phased haplotypes from individuals of Asian, African, and European descent, to be used as a representative reference set by the genomics and immunogenetics community. Second, we are utilizing this more comprehensive sequence catalogue to inform the design and analysis of novel targeted IGH genotyping assays. Standard targeted DNA enrichment methods (e.g., exome capture) are currently optimized for the capture of only very short (100’s of bp) DNA segments. Our platform uses a modified bench protocol to pair existing capture-array technologies with the enrichment of longer fragments of DNA, enabling the use of PacBio sequencing of DNA segments up to 7 Kb. This substantial increase in contiguity disambiguates many of the complex repeated structures inherent to the locus, while yielding the base pair fidelity required to call SNVs. Together these resources will establish a stronger framework for further characterizing IGH genetic diversity and facilitate IGH genomic profiling in the clinical and research settings, which will be key to fully understanding the role of IGH germline variation in antibody repertoire development and disease.
Structural variant calling combining Illumina and low-coverage Pacbio Detection of large genomic variation (structural variants) has proven challenging using short-read methods. Long-read approaches which can span these large events have promise to dramatically expand the ability to accurately call structural variants. Although sequencing with Pacific Biosciences (Pacbio) long-read technology has become increasingly high throughput, generating high coverage with the technology can still be limiting and investigators often would like to know what pacbio coverages are adequate to call structural variants. Here, we present a method to identify a substantially higher fraction of structural variants in the human genome using low-coverage pacbio data by multiple strategies for ensembling data types and algorithms. Algorithmically, we combine three structural variant callers: PBHoney by Adam English, Sniffles by Fritz Sedlazeck, and Parliament by Adam English (which we have modified to improve for speed). Parliament itself uses a combination of Pacbio and Illumina data with a number of short-read callers (Breakdancer, Pindel, Crest, CNVnator, Delly, and Lumpy). We show that the outputs of these three programs are largely complementary to each other, with each able to uniquely access different sets of structural variants at different coverages. Combining them together can more than double the recall of true structural variants from a truth set relative to sequencing with Illumina alone, with substantial improvements even at low pacbio coverages (3x – 7x). This allows us to present for the first time cost-benefit tradeoffs to investigators about how much pacbio sequencing will yield what improvements in SV-calling. This work also builds upon the foundational work of Genome in a Bottle led by Justin Zook in establishing a truth set for structural variants in the Ashkenazim-Jewish trio data recently released. This work demonstrates the power of this benchmark set – one of the first of its kind for structural variation data – to help understand and refine the accuracies of calling structural variants with a number of approaches.
Each human genome has thousands of structural variants compared to the reference assembly, up to 85% of which are difficult or impossible to detect with Illumina short reads and are only visible with long, multi-kilobase reads. The PacBio RS II and Sequel single molecule, real-time (SMRT) sequencing platforms have made it practical to generate long reads at high throughput. These platforms enable the discovery of structural variants just as short-read platforms did for single nucleotide variants. Numerous software algorithms call structural variants effectively from PacBio long reads, but algorithm sensitivity is lower for insertion variants and all heterozygous variants. Furthermore, the impact of coverage depth and read lengths on sensitivity is not fully characterized. To quantify how zygosity, coverage depth, and read lengths impact the sensitivity of structural variant detection, we obtained high coverage PacBio sequences for three human samples: haploid CHM1, diploid NA12878, and diploid SK-BR-3. For each dataset, reads were randomly subsampled to titrate coverage from 0.5- to 50-fold. The structural variants detected at each coverage were compared to the set at “full” 50-fold coverage. For the diploid samples, additional titrations were performed with reads first partitioned by phase using single nucleotide variants for essentially haploid structural variant discovery. Even at low coverages (1- to 5-fold), PacBio long reads reveal hundreds of structural variants that are not seen in deep 50-fold Illumina whole genome sequences. At moderate 10-fold PacBio coverage, a majority of structural variants are detected. Sensitivity begins to level off at around 40-fold coverage, though it does not fully saturate before 50-fold. Phasing improves sensitivity for all variant types, especially at moderate 10- to 20-fold coverage. Long reads are an effective tool to identify and phase structural variants in the human genome. The majority of variants are detected at moderate 10-fold coverage, and even extremely low long-read coverage (1- to 5-fold) reveals variants that are invisible to short-read sequencing. Performance will continue to improve with better software and longer reads, which will empower studies to connect structural variants to healthy and disease traits in the human population.
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