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.
2015 SMRT Informatics Developers Conference Presentation Slides: Adam English, from the Human Genome Sequencing Center at Baylor College of Medicine presents on the structural variation tools being developed at Baylor.
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.
We have developed several candidate gene screening applications for both Neuromuscular and Neurological disorders. The power behind these applications comes from the use of long-read sequencing. It allows us to access previously unresolvable and even unsequencable genomic regions. SMRT Sequencing offers uniform coverage, a lack of sequence context bias, and very high accuracy. In addition, it is also possible to directly detect epigenetic signatures and characterize full-length gene transcripts through assembly-free isoform sequencing. In addition to calling the bases, SMRT Sequencing uses the kinetic information from each nucleotide to distinguish between modified and native bases.
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.
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.
Bipolar disorder (BD) is a phenotypically and genetically complex and debilitating neurological disorder that affects 1% of the worldwide population. There is compelling evidence from family, twin and adoption studies supporting the involvement of a genetic predisposition in BD with estimated heritability up to ~ 80%. The risk in first-degree relatives is ten times higher than in the general population. Linkage and association studies have implicated multiple putative chromosomal loci for BP susceptibility, however no disease genes have been identified to date.
Despite amazing progress over the past quarter century in the technology to detect genetic variants, intermediate-sized structural variants (50 bp to 50 kb) have remained difficult to identify. Such variants are too small to detect with array comparative genomic hybridization, but too large to reliably discover with short-read DNA sequencing. Recent de novo assemblies of human genomes have demonstrated the power of PacBio Single Molecule, Real-Time (SMRT) Sequencing to fill this technology gap and sensitively identify structural variants in the human genome. While de novo assembly is the ideal method to identify variants in a genome, it requires high depth of coverage. A structural variant discovery approach that utilizes lower coverage would facilitate evaluation of large patient and population cohorts. Here we introduce such an approach and apply it to 10-fold coverage of several human genomes generated on the PacBio Sequel System. To identify structural variants in low-fold coverage whole genome sequencing data, we apply a reference-based, re-sequencing workflow. First, reads are mapped to the human reference genome with a local aligner. The local alignments often end at structural variant loci. To connect co-linear local alignments across structural variants, we apply a novel algorithm that merges alignments into “chains” and refines the alignment edges. Then, the chained alignments are scanned for windows with an excess of insertions or deletions to identify candidate structural variant loci. Finally, the read support at each putative variant locus is evaluated to produce a variant call. Single nucleotide information is incorporated to phase and evaluate the zygosity of each structural variant. In 10-fold coverage human genome sequence, we identify the vast majority of the structural variants found by de novo assembly, thus demonstrating the power of low-fold coverage SMRT Sequencing to affordably and effectively detect structural variants.
Though a role for structural variants in human disease has long been recognized, it has remained difficult to identify intermediate-sized variants (50 bp to 5 kb), which are too small to detect with array comparative genomic hybridization, but too large to reliably discover with short-read DNA sequencing. Recent studies have demonstrated that PacBio Single Molecule, Real-Time (SMRT) sequencing fills this technology gap. SMRT sequencing detects tens of thousands of structural variants in the human genome, approximately five times the sensitivity of short-read DNA sequencing.
Structural variants (genomic differences =50 base pairs) contribute to the evolution of organisms traits and human disease. Most structural variants (SVs) are too small to detect with array comparative genomic hybridization but too large to reliably discover with short-read DNA sequencing. Recent studies in human genomes show that PacBio SMRT Sequencing sensitively detects structural variants.
Most of the base pairs that differ between two human genomes are in intermediate-sized structural variants (50 bp to 5 kb), which are too small to detect with array comparative genomic hybridization or optical mapping but too large to reliably discover with short-read DNA sequencing. Long-read sequencing with PacBio Single Molecule, Real-Time (SMRT) Sequencing platforms fills this technology gap. PacBio SMRT Sequencing detects tens of thousands of structural variants in a human genome with approximately five times the sensitivity of short-read DNA sequencing. Effective application of PacBio SMRT Sequencing to detect structural variants requires quality bioinformatics tools that account for the characteristics of PacBio reads. To provide such a solution, we developed pbsv, a structural variant caller for PacBio reads that works as a chain of simple stages: 1) map reads to the reference genome, 2) identify reads with signatures of structural variation, 3) cluster nearby reads with similar signatures, 4) summarize each cluster into a consensus variant, and 5) filter for variants with sufficient read support. To evaluate the baseline performance of pbsv, we generated high coverage of a diploid human genome on the PacBio Sequel System, established a target set of structural variants, and then titrated to lower coverage levels. The false discovery rate for pbsv is low at all coverage levels. Sensitivity is high even at modest coverage: above 85% at 10-fold coverage and above 95% at 20-fold coverage. To assess the potential for PacBio SMRT Sequencing to identify pathogenic variants, we evaluated an individual with clinical symptoms suggestive of Carney complex for whom short-read whole genome sequencing was uninformative. The individual was sequenced to 9-fold coverage on the PacBio Sequel System, and structural variants were called with pbsv. Filtering for rare, genic structural variants left six candidates, including a heterozygous 2,184 bp deletion that removes the first coding exon of PRKAR1A. Null mutations in PRKAR1Acause autosomal dominant Carney complex, type 1. The variant was determined to be de novo, and it was classified as likely pathogenic based on ACMG standards and guidelines for variant interpretation. These case studies demonstrate the ability of pbsv to detect structural variants in low-coverage PacBio SMRT Sequencing and suggest the importance of considering structural variants in any study of human genetic variation.
Structural variants (genomic differences =50 base pairs) contribute to the evolution of traits and disease. Most structural variants (SVs) are too small to detect with array comparative genomic hybridization and too large to reliably discover with short-read DNA sequencing.
Maize is an amazingly diverse crop. A study in 20051 demonstrated that half of the genome sequence and one-third of the gene content between two inbred lines of maize were not shared. This diversity, which is more than two orders of magnitude larger than the diversity found between humans and chimpanzees, highlights the inability of a single reference genome to represent the full pan-genome of maize and all its variants. Here we present and review several efforts to characterize the complete diversity within maize using the highly accurate long reads of PacBio Single Molecule, Real-Time (SMRT) Sequencing. These methods provide a framework for a pan-genomic approach that can be applied to studies of a wide variety of important crop species.
Structural variants (SVs) – genomic differences =50 base pairs – are few by count compared to single nucleotide variants (SNVs) and indels but include most of the base pairs that differ between two humans.
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