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June 1, 2021  |  

Structural variant detection with low-coverage Pacbio sequencing

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.


June 1, 2021  |  

Detecting pathogenic structural variants with low-coverage PacBio sequencing.

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.


June 1, 2021  |  

Detecting pathogenic structural variants with long-read PacBio SMRT Sequencing

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.


June 1, 2021  |  

Joint calling and PacBio SMRT Sequencing for indel and structural variant detection in populations

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.


June 1, 2021  |  

FALCON-Phase integrates PacBio and HiC data for de novo assembly, scaffolding and phasing of a diploid Puerto Rican genome (HG00733)

Haplotype-resolved genomes are important for understanding how combinations of variants impact phenotypes. The study of disease, quantitative traits, forensics, and organ donor matching are aided by phased genomes. Phase is commonly resolved using familial data, population-based imputation, or by isolating and sequencing single haplotypes using fosmids, BACs, or haploid tissues. Because these methods can be prohibitively expensive, or samples may not be available, alternative approaches are required. de novo genome assembly with PacBio Single Molecule, Real-Time (SMRT) data produces highly contiguous, accurate assemblies. For non-inbred samples, including humans, the separate resolution of haplotypes results in higher base accuracy and more contiguous assembled sequences. Two primary methods exist for phased diploid genome assembly. The first, TrioCanu requires Illumina data from parents and PacBio data from the offspring. The long reads from the child are partitioned into maternal and paternal bins using parent-specific sequences; the separate PacBio read bins are then assembled, generating two fully phased genomes. An alternative approach (FALCON-Unzip) does not require parental information and separates PacBio reads, during genome assembly, using heterozygous SNPs. The length of haplotype phase blocks in FALCON-Unzip is limited by the magnitude and distribution of heterozygosity, the length of sequence reads, and read coverage. Because of this, FALCON-Unzip contigs typically contain haplotype-switch errors between phase blocks, resulting in primary contig of mixed parental origin. We developed FALCON-Phase, which integrates Hi-C data downstream of FALCON-Unzip to resolve phase switches along contigs. We applied the method to a human (Puerto Rican, HG00733) and non-human genome assemblies and evaluated accuracy using samples with trio data. In a cattle genome, we observe >96% accuracy in phasing when compared to TrioCanu assemblies as well as parental SNPs. For a high-quality PacBio assembly (>90-fold Sequel coverage) of a Puerto Rican individual we scaffolded the FALCON-Phase contigs, and re-phased the contigs creating a de novo scaffolded, phased diploid assembly with chromosome-scale contiguity.


June 1, 2021  |  

Improving the reference with a diversity panel of sequence-resolved structural variation

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.


June 1, 2021  |  

High-quality human genomes achieved through HiFi sequence data and FALCON-Unzip assembly

De novo assemblies of human genomes from accurate (85-90%), continuous long reads (CLR) now approach the human reference genome in contiguity, but the assembly base pair accuracy is typically below QV40 (99.99%), an order-of-magnitude lower than the standard for finished references. The base pair errors complicate downstream interpretation, particularly false positive indels that lead to false gene loss through frameshifts. PacBio HiFi sequence data, which are both long (>10 kb) and very accurate (>99.9%) at the individual sequence read level, enable a new paradigm in human genome assembly. Haploid human assemblies using HiFi data achieve similar contiguity to those using CLR data and are highly accurate at the base level1. Furthermore, HiFi assemblies resolve more high-identity sequences such as segmental duplications2. To enable HiFi assembly in diploid human samples, we have extended the FALCON-Unzip assembler to work directly with HiFi reads. Here we present phased human diploid genome assemblies from HiFi sequencing of HG002, HG005, and the Vertebrate Genome Project (VGP) mHomSap1 trio on the PacBio Sequel II System. The HiFi assemblies all exceed the VGP’s quality guidelines, approaching QV50 (99.999%) accuracy. For HG002, 60% of the genome was haplotype-resolved, with phase-block N50 of 143Kbp and phasing accuracy of 99.6%. The overall mean base accuracy of the assembly was QV49.7. In conclusion, HiFi data show great promise towards complete, contiguous, and accurate diploid human assemblies.


June 1, 2021  |  

Comprehensive structural and copy-number variant detection with long reads

To comprehensively detect large variants in human genomes, we have 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. 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 typical 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 and short reads. 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.


June 1, 2021  |  

Detection and phasing of small variants in Genome in a Bottle samples with highly accurate long 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.


June 1, 2021  |  

A workflow for the comprehensive detection and prioritization of variants in human genomes with PacBio HiFi 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.


June 1, 2021  |  

Comprehensive variant detection in a human genome with highly accurate long reads

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.


May 17, 2021  |  

Genomic Answers for Kids

Short-read genome-wide sequencing for molecular diagnosis has revolutionized pediatric rare disease care in the past decade. However, most families remain without specific knowledge of the cause of their child’s illness….


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