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.
Fast and effective variant calling algorithms have been crucial to the successful application of DNA sequencing in human genetics. In particular, joint calling – in which reads from multiple individuals are pooled to increase power for shared variants – is an important tool for population surveys of variation. Joint calling was applied by the 1000 Genomes Project to identify variants across many individuals each sequenced to low coverage (about 5-fold). This approach successfully found common small variants, but broadly missed structural variants and large indels for which short-read sequencing has limited sensitivity. To support use of large variants in rare disease and common trait association studies, it is necessary to perform population-scale surveys with a technology effective at detecting indels and structural variants, such as PacBio SMRT Sequencing. For these studies, it is important to have a joint calling workflow that works with PacBio reads. We have developed pbsv, an indel and structural variant caller for PacBio reads, that provides a two-step joint calling workflow similar to that used to build the ExAC database. The first stage, discovery, is performed separately for each sample and consolidates whole genome alignments into a sparse representation of potentially variant loci. The second stage, calling, is performed on all samples together and considers only the signatures identified in the discovery stage. We applied the pbsv joint calling workflow to PacBio reads from twenty human genomes, with coverage ranging from 5-fold to 80-fold per sample for a total of 460-fold. The analysis required only 102 CPU hours, and identified over 800,000 indels and structural variants, including hundreds of inversions and translocations, many times more than discovered with short-read sequencing. The workflow is scalable to thousands of samples. The ongoing application of this workflow to thousands of samples will provide insight into the evolution and functional importance of large variants in human evolution and disease.
High-throughput NGS methods are increasingly utilized in the clinical genomics market. However, short-read sequencing data continues to remain challenged by mapping inaccuracies in low complexity regions or regions of high homology and may not provide adequate coverage within GC-rich regions of the genome. Thus, the use of Sanger sequencing remains popular in many clinical sequencing labs as the gold standard approach for orthogonal validation of variants and to interrogate missed regions poorly covered by second-generation sequencing. The use of Sanger sequencing can be less than ideal, as it can be costly for high volume assays and projects. Additionally, Sanger sequencing generates read lengths shorter than the region of interest, which limits its ability to accurately phase allelic variants. High-throughput SMRT Sequencing overcomes the challenges of both the first- and second-generation sequencing methods. PacBio’s long read capability allows sequencing of full-length amplicons
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.
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.
Introduction: Long-read sequencing has been applied successfully to assemble genomes and detect structural variants. However, due to high raw-read error rates (10-15%), it has remained difficult to call small variants from long reads. Recent improvements in library preparation and sequencing chemistry have increased length, accuracy, and throughput of PacBio circular consensus sequencing (CCS) reads, resulting in 10-20kb reads with average read quality above 99%. Materials and Methods: We sequenced a 12kb library from human reference sample HG002 to 18-fold coverage on the PacBio Sequel II System with three SMRT Cells 8M. The CCS algorithm was used to generate highly-accurate (average 99.8%) 11.4kb reads, which were mapped to the hg19 reference with pbmm2. We detected small variants using Google DeepVariant with a model trained for CCS and phased the variants using WhatsHap. Structural variants were detected with pbsv. Variant calls were evaluated against Genome in a Bottle (GIAB) benchmarks. Results: With these reads, DeepVariant achieves SNP and Indel F1 scores of 99.82% and 96.70% against the GIAB truth set, and pbsv achieves 95.94% recall on structural variants longer than 50bp. Using WhatsHap, small variants were phased into haplotype blocks with 105kb N50. The improved mappability of long reads allows us to align to and detect variants in medically relevant genes such as CYP2D6 and PMS2 that have proven “difficult-to-map” with short reads. Conclusions: These highly-accurate long reads combine the mappability and ability to detect structural variants of long reads with the accuracy and ability to detect small variants of short reads.
Introduction: Long-read PacBio SMRT Sequencing has been applied successfully to assemble genomes and detect structural variants. However, due to high raw read error rates of 10-15%, it has remained difficult to call small variants from long reads. Recent improvements in library preparation, sequencing chemistry, and instrument yield have increased length, accuracy, and throughput of PacBio Circular Consensus (CCS) reads, resulting in 10-20 kb “HiFi” reads with mean read quality above 99%. Materials and Methods: We sequenced 11 kb size-selected libraries from the Genome in a Bottle (GIAB) human reference samples HG001, HG002, and HG005 to approximately 30-fold coverage on the Sequel II System with six SMRT Cells 8M each. The CCS algorithm was used to generate highly accurate (average 99.8%) reads of mean length 10-11 kb, which were then mapped to the hs37d5 reference with pbmm2. We detected small variants using Google DeepVariant and compared these variant calls to GIAB benchmarks. Small variants were then phased with WhatsHap. Results: With these long, highly accurate CCS reads, DeepVariant achieves high SNP and Indel accuracy against the GIAB benchmark truth set for all three reference samples. Using WhatsHap, small variants were phased into haplotype blocks with N50 from 82 to 146 kb. The improved mappability of long reads allows detection of variants in many medically relevant genes such as CYP2D6and PMS2that have proven ‘difficult-to-map’ with short reads. We show that small variant precision and recall remain high down to 15-fold coverage. Conclusions: These highly accurate long reads combine the mappability of noisy long reads with the accuracy and small variant detection utility of short reads, which will allow the detection and phasing of variants in regions that have proven recalcitrant to short read sequencing and variant detection.
Long-read sequencing of diverse humans has revealed more than 20,000 insertion, deletion, and inversion structural variants spanning more than 12 Mb in a healthy human genome. Most of these variants are too large to detect with short reads and too small for array comparative genome hybridization (aCGH). While the standard approaches to calling structural variants with long reads thrive in the 50 bp to 10 kb size range, they tend to miss exactly the large (>50 kb) copy-number variants that are called more readily with aCGH. Standard algorithms rely on reference-based mapping of reads that fully span a variant or on de novo assembly; and copy-number variants are often too large to be spanned by a single read and frequently involve segmentally duplicated sequence that is not yet included in most de novo assemblies. To comprehensively detect large variants in human genomes, we extended pbsv – a structural variant caller for long reads – to call copy-number variants (CNVs) from read-clipping and read-depth signatures. In human germline benchmark samples, we detect more than 300 CNVs spanning around 10 Mb, and we call hundreds of additional events in re-arranged cancer samples. Together with insertion, deletion, inversion, duplication, and translocation calling from spanning reads, this allows pbsv to comprehensively detect large variants from a single data type.
Introduction: Long-read sequencing has been applied successfully to assemble genomes and detect structural variants. However, due to high raw-read error rates (10-15%), it has remained difficult to call small variants from long reads. Recent improvements in library preparation and sequencing chemistry have increased length, accuracy, and throughput of PacBio circular consensus sequencing (CCS) reads, resulting in 15-20kb reads with average read quality above 99%. Materials and Methods: We sequenced a library from human reference sample HG002 to 18-fold coverage on the PacBio Sequel II with two SMRT Cells 8M. The CCS algorithm was used to generate highly accurate (average 99.9%) 12.9kb reads, which were mapped to the hg19 reference with pbmm2. We detected small variants using Google DeepVariant with a model trained for CCS and phased the variants using WhatsHap. Structural variants were detected with pbsv. Variant calls were evaluated against Genome in a Bottle (GIAB) benchmarks. Results: With these reads, DeepVariant achieves SNP and Indel F1 scores of 99.70% and 96.59% against the GIAB truth set, and pbsv achieves 97.72% recall on structural variants longer than 50bp. Using WhatsHap, small variants were phased into haplotype blocks with 145kb N50. The improved mappability of long reads allows us to align to and detect variants in medically relevant genes such as CYP2D6 and PMS2 that have proven “difficult-to-map” with short reads. Conclusions: These highly accurate long reads combine the mappability and ability to detect structural variants of long reads with the accuracy and ability to detect small variants of short reads.
PacBio HiFi reads (minimum 99% accuracy, 15-25 kb read length) have emerged as a powerful data type for comprehensive variant detection in human genomes. The HiFi read length extends confident mapping and variant calling to repetitive regions of the genome that are not accessible with short reads. Read length also improves detection of structural variants (SVs), with recall exceeding that of short reads by over 30%. High read quality allows for accurate single nucleotide variant and small indel detection, with precision and recall matching that of short reads. While many tools have been developed to take advantage of these qualities of HiFi reads, there is no end-to-end workflow for the filtering and prioritization of variants uniquely detected with long reads for rare and undiagnosed disease research. We have developed a flexible, modular workflow and web portal for variant analysis from HiFi reads and applied it to a set of rare disease cases unsolved by short-read whole genome sequencing. We expect that broad application of long-read variant detection workflows will solve many more rare disease cases. We have made these tools available at https://github.com/williamrowell/pbRUGD-workflow, and we hope they serve a starting point for developing a robust analysis framework for long read variant detection for rare diseases.
Introduction: Long-read sequencing has revealed more than 20,000 structural variants spanning over 12 Mb in a healthy human genome. Short-read sequencing fails to detect most structural variants but has remained the more effective approach for small variants, due to 10-15% error rates in long reads, and copy-number variants (CNVs), due to lack of effective long-read variant callers. The development of PacBio highly accurate long reads (HiFi reads) with read lengths of 10-25 kb and quality >99% presents the opportunity to capture all classes of variation with one approach.Methods: We sequence the Genome in a Bottle benchmark sample HG002 and an individual with a presumed Mendelian disease with HiFi reads. We call SNVs and indels with DeepVariant and extend the structural variant caller pbsv to call CNVs using read depth and clipping signatures. Results: For 18-fold coverage with 13 kb HiFi reads, variant calling in HG002 achieves an F1 score of 99.7% for SNVs, 96.6% for indels, and 96.4% for structural variants. Additionally, we detect more than 300 CNVs spanning around 10 Mb. For the Mendelian disease case, HiFi reads reveal thousands of variants that were overlooked by short-read sequencing, including a candidate causative structural variant. Conclusions: These results illustrate the ability of HiFi reads to comprehensively detect variants, including those associated with human disease.
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