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.
Explore the types of human genomic variation and the diseases known to be caused by structural variants.
Explore how long-read sequencing enables solving of rare and mendelian diseases.
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.
PacBio highly accurate long reads – HiFi reads – offer a single-platform solution for rare and inherited disease research, elucidating suspected genetic causes of disease in up to ~50% of cases that have not previously been explained using short-read exome or whole genome sequencing. PacBio offers an efficient workflow, developed in collaboration with Children’s Mercy Kansas City, which provides a scalable solution for sequencing 100s to 1000s of whole human genomes per year on the Sequel II and Sequel IIe Systems.
With highly accurate long reads (HiFi reads) from the Sequel II or IIe Systems you can comprehensively detect variants in 100s to 1000s of genomes in a year. HiFi reads provide high precision and recall for single nucleotide variants (SNVs), indels, structural variants (SVs), and copy number variants (CNVs), including in difficult-to-map repetitive regions.
Learn how PacBio highly accurate long reads enable an improved approach to whole genome sequencing to understand the genetic origins of rare diseases.
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.
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.
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.
Although the accuracy of the human reference genome is critical for basic and clinical research, structural variants (SVs) have been difficult to assess because data capable of resolving them have been limited. To address potential bias, we sequenced a diversity panel of nine human genomes to high depth using long-read, single-molecule, real-time sequencing data. Systematically identifying and merging SVs =50 bp in length for these nine and one public genome yielded 83,909 sequence-resolved insertions, deletions, and inversions. Among these, 2,839 (2.0 Mbp) are shared among all discovery genomes with an additional 13,349 (6.9 Mbp) present in the majority of humans, indicating minor alleles or errors in the reference, which is partially explained by an enrichment for GC-content and repetitive DNA. Genotyping 83% of these in 290 additional genomes confirms that at least one allele of the most common SVs in unique euchromatin are now sequence-resolved. We observe a 9-fold increase within 5 Mbp of chromosome telomeric ends and correlation with de novo single-nucleotide variant mutations showing that such variation is nonrandomly distributed defining potential hotspots of mutation. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. To illustrate the utility of sequence-resolved SVs in resequencing experiments, we mapped 30 diverse high-coverage Illumina-sequenced samples to GRCh38 with and without contigs containing SV insertions as alternate sequences, and we found these additional sequences recover 6.4% of unmapped reads. For reads mapped within the SV insertion, 25.7% have a better mapping quality, and 18.7% improved by 1,000-fold or more. We reveal 72,964 occurrences of 15,814 unique variants that were not discoverable with the reference sequence alone, and we note that 7% of the insertions contain an SV in at least one sample indicating that there are additional alleles in the population that remain to be discovered. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity. We present a summary of our findings and discuss ideas for revealing variation that was once difficult to ascertain.
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