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June 1, 2021  |  

Phased full-length SMRT Sequencing of HLA DPB1

Aim: In contrast to exon-based HLA-typing approaches, whole gene genotyping crucially depends on full-length sequences submitted to the IMGT/HLA Database. Currently, full-length sequences are provided for only 7 out of 520 HLA-DPB1 alleles. Therefore, we developed a fully phased whole-gene sequencing approach for DPB1, to facilitate further exploration of the allelic structure at this locus. Methods: Primers were developed flanking the UTR-regions of DPB1 resulting in a 12 kb amplicon. Using a 4-primer approach, secondary primers containing barcodes were combined with the gene-specific primers to obtain barcoded full-gene amplicons in a single amplification step. Amplicons were pooled, purified, and ligated to SMRT bells (i.e. annealing points for sequencing primers) following standard protocols from Pacific Biosciences. Taking advantage of the SMRT chemistry, pools of 48 amplicons were sequenced full length in single runs on a Pacific Biosciences RSII instrument. Demultiplexing was performed using the SMRT portal. Sequence analysis was performed using the NGSengine software (GenDx). Results: We analyzed a set of 48 randomly picked samples. With 3 exceptions due to PCR failure, all genotype assignments conformed to standard genotyping results based on exons 2 and 3. Allelic proportions for heterozygous positions were evenly distributed (range 0.4 – 0.6) for all samples, suggesting unbiased amplifications. Despite the high per-read raw error rates typical for SMRT sequencing (~15%) the consensus sequence proved highly reliable. All consensus sequences for exons 2 and 3 were in full accordance with their MiSeq-derived sequences. We describe novel intronic sequence variation of the 7 so far genomically defined alleles, as well as 7 whole-length DPB1 alleles with hitherto unknown intronic regions. One of these alleles (HLA-DPB1*131:01) is classified as rare. Conclusion: Here we present a whole gene amplification and sequencing workflow for DPB1 alleles utilizing single molecule real-time (SMRT) sequencing from Pacific Biosciences. Validation of consensus sequences against known exonic sequences highlights the reliability of this technology. This workflow will facilitate amending the IMGT/HLA Database for DPB1.


June 1, 2021  |  

Access full spectrum of polymorphisms in HLA class I & II genes, without imputation for disease association and evolutionary research.

MHC class I and II genes are critically monitored by high-resolution sequencing for organ transplant decisions due to their role in GVHD. Their direct or linkage-based causal association, have increased their prominence as targets for drug sensitivity, autoimmune, cancer and infectious disease research. Monitoring HLA genes can however be tricky due to their highly polymorphic nature. Allele-level resolution is thus strongly preferred. However, most studies were historically focused on peptide binding domains of the HLA genes, due to technological challenges. As a result knowledge about the functional role of polymorphisms outside of exons 2 and 3 of HLA genes was rather limited. There are also relatively few full-length gene references currently available in the IMGT HLA database. This made it difficult to quickly adopt high-throughput reference-reliant methods for allele-level HLA sequencing. Increasing awareness regarding role of regulatory region polymorphisms of HLA genes in disease association1, nonetheless have brought about a revolution in full-length HLA gene sequencing. Researchers are now exploring ways to obtain complete information for HLA genes and integrate it with the current HLA database so it can be interpreted used by clinical researchers. We have explored advantages of SMRT Sequencing to obtain fully phased, allele-specific sequences of HLA class I and II genes for 96 samples using completely De novo consensus generation approach for imputation-free 4-field typing. With long read lengths (average >10 kb) and consensus accuracy exceeding 99.999% (Q50), a comprehensive snapshot of variants in exons, introns and UTRs could be obtained for spectrum of polymorphisms in phase across SNP-poor regions. Such information can provide invaluable insights in future causality association and population diversity research.


June 1, 2021  |  

Genome in a Bottle: You’ve sequenced. How well did you do?

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.


June 1, 2021  |  

A comprehensive lincRNA analysis: From conifers to trees

We have produced an updated annotation of the Norway spruce genome on the basis of an in siliconormalised set of RNA-Seq data obtained from 1,529 samples and comprising 15.5 billion paired-end Illumina HiSeq reads complemented by 18Mbp of PacBio cDNA data (3.2M sequences). In addition to augmenting and refining the previous protein coding gene annotation, here we focus on the addition of long intergenic non-coding RNA (lincRNA) and micro RNA (miRNA) genes. In addition to non-coding loci, our analyses also identified protein coding genes that had been missed by the initial genome annotation and enabled us to update the annotation of existing gene models. In particular, splice variant information, as supported by PacBio sequencing reads, has been added to the current annotation and previously fragmented gene models have been merged by scaffolding disjoint genomic scaffolds on the basis of transcript evidence. Using this refined annotation, a targeted analysis of the lincRNAs enabled their classification as i) deeply conserved, ii) conserved in seed plants iii) gymnosperm/conifer specific. Concurrently, complementary analyses were performed as part of the aspen genome project and the results of a comparative analysis of the lincRNAs conserved in both Norway spruce and Eurasian aspen enabled us to identify conserved and diverged expression profiles. At present, we are delving further into the expression results with the aim to functionally annotate the lincRNA genes, by developing a co-expression network analyses based GO annotation.


June 1, 2021  |  

How to Compare and Cluster Every Known Genome in about an Hour

Given a massive collection of sequences, it is infeasible to perform pairwise alignment for basic tasks like sequence clustering and search. To address this problem, we demonstrate that the MinHash technique, first applied to clustering web pages, can be applied to biological sequences with similar effect, and extend this idea to include biologically relevant distance and significance measures. Our new tool, Mash, uses MinHash locality-sensitive hashing to reduce large sequences to a representative sketch and rapidly estimate pairwise distances between genomes or metagenomes. Using Mash, we explored several use cases, including a 5,000-fold size reduction and clustering of all 55,000 NCBI RefSeq genomes in 46 CPU hours. The resulting 93 MB sketch database includes all RefSeq genomes, effectively delineates known species boundaries, reconstructs approximate phylogenies, and can be searched in seconds using assembled genomes or raw sequencing runs from Illumina, Pacific Biosciences, and Oxford Nanopore. For metagenomics, Mash scales to thousands of samples and can replicate Human Microbiome Project and Global Ocean Survey results in a fraction of the time. Other potential applications include any problem where an approximate, global sequence distance is acceptable, e.g. to triage and cluster sequence data, assign species labels to unknown genomes, quickly identify mis- tracked samples, and search massive genomic databases. In addition, the Mash distance metric is based on simple set intersections, which are compatible with homomorphic encryption schemes. To facilitate integration with other software, Mash is implemented as a lightweight C++ toolkit and freely released under a BSD license athttps://github.com/marbl/mash


June 1, 2021  |  

Diploid genome assembly and comprehensive haplotype sequence reconstruction

Outside of the simplest cases (haploid, bacteria, or inbreds), genomic information is not carried in a single reference per individual, but rather has higher ploidy (n=>2) for almost all organisms. The existence of two or more highly related sequences within an individual makes it extremely difficult to build high quality, highly contiguous genome assemblies from short DNA fragments. Based on the earlier work on a polyploidy aware assembler, FALCON ( https://github.com/PacificBiosciences/FALCON) , we developed new algorithms and software (“FALCON-unzip”) for de novo haplotype reconstructions from SMRT Sequencing data. We generate two datasets for developing the algorithms and the prototype software: (1) whole genome sequencing data from a highly repetitive diploid fungal (Clavicorona pyxidata) and (2) whole genome sequencing data from an F1 hybrid from two inbred Arabidopsis strains: Cvi-0 and Col-0. For the fungal genome, we achieved an N50 of 1.53 Mb (of the 1n assembly contigs) of the ~42 Mb 1n genome and an N50 of the haplotigs (haplotype specific contigs) of 872 kb from a 95X read length N50 ~16 kb dataset. We found that ~ 45% of the genome was highly heterozygous and ~55% of the genome was highly homozygous. We developed methods to assess the base-level accuracy and local haplotype phasing accuracy of the assembly with short-read data from the Illumina® platform. For the ArabidopsisF1 hybrid genome, we found that 80% of the genome could be separated into haplotigs. The long range accuracy of phasing haplotigs was evaluated by comparing them to the assemblies from the two inbred parental lines. We show that a more complete view of all haplotypes could provide useful biological insights through improved annotation, characterization of heterozygous variants of all sizes, and resolution of differential allele expression. The current Falcon-Unzip method will lead to understand how to solve more difficult polyploid genome assembly problems and improve the computational efficiency for large genome assemblies. Based on this work, we can develop a pipeline enabling routinely assemble diploid or polyploid genomes as haplotigs, representing a comprehensive view of the genomes that can be studied with the information at hand.


June 1, 2021  |  

Un-zipping diploid genomes – revealing all kinds of heterozygous variants from comprehensive hapltotig assemblies

Outside of the simplest cases (haploid, bacteria, or inbreds), genomic information is not carried in a single reference per individual, but rather has higher ploidy (n=>2) for almost all organisms. The existence of two or more highly related sequences within an individual makes it extremely difficult to build high quality, highly contiguous genome assemblies from short DNA fragments. Based on the earlier work on a polyploidy aware assembler, FALCON (https://github.com/PacificBiosciences/FALCON), we developed new algorithms and software (FALCON-unzip) for de novo haplotype reconstructions from SMRT Sequencing data. We apply the algorithms and the prototype software for (1) a highly repetitive diploid fungal genome (Clavicorona pyxidata) and (2) an F1 hybrid from two inbred Arabidopsis strains: CVI-0 and COL-0. For the fungal genome, we achieved an N50 of 1.53 Mb (of the 1n assembly contigs) of the ~42 Mb 1n genome and an N50 of the haplotigs of 872 kb from a 95X read length N50 ~16 kb dataset. We found that ~ 45% of the genome was highly heterozygous and ~55% of the genome was highly homozygous. We developed methods to assess the base-level accuracy and local haplotype phasing accuracy of the assembly with short-read data from the Illumina platform. For the Arabidopsis F1 hybrid genome, we found that 80% of the genome could be separated into haplotigs. The long range accuracy of phasing haplotigs was evaluated by comparing them to the assemblies from the two inbred parental lines. We show that a more complete view of all haplotypes could provide useful biological insights through improved annotation, characterization of heterozygous variants of all sizes, and resolution of differential allele expression. Finally, we applied this method to WGS human data sets to demonstrate the potential for resolving complicated, medically-relevant genomic regions.


June 1, 2021  |  

Minimization of chimera formation and substitution errors in full-length 16S PCR amplification

The constituents and intra-communal interactions of microbial populations have garnered increasing interest in areas such as water remediation, agriculture and human health. One popular, efficient method of profiling communities is to amplify and sequence the evolutionarily conserved 16S rRNA sequence. Currently, most targeted amplification focuses on short, hypervariable regions of the 16S sequence. Distinguishing information not spanned by the targeted region is lost and species-level classification is often not possible. SMRT Sequencing easily spans the entire 1.5 kb 16S gene, and in combination with highly-accurate single-molecule sequences, can improve the identification of individual species in a metapopulation. However, when amplifying a mixture of sequences with close similarities, the products may contain chimeras, or recombinant molecules, at rates as high as 20-30%. These PCR artifacts make it difficult to identify novel species, and reduce the amount of productive sequences. We investigated multiple factors that have been hypothesized to contribute to chimera formation, such as template damage, denaturing time before and during cycling, polymerase extension time, and reaction volume. Of the factors tested, we found two major related contributors to chimera formation: the amount of input template into the PCR reaction and the number of PCR cycles. Sequence errors generated during amplification and sequencing can also confound the analysis of complex populations. Circular Consensus Sequencing (CCS) can generate single-molecule reads with >99% accuracy, and the SMRT Analysis software provides filtering of these reads to >99.99% accuracies. Remaining substitution errors in these highly-filtered reads are likely dominated by mis-incorporations during amplification. Therefore, we compared the impact of several commercially-available high-fidelity PCR kits with full-length 16S amplification. We show results of our experiments and describe an optimized protocol for full-length 16S amplification for SMRT Sequencing. These optimizations have broader implications for other applications that use PCR amplification to phase variations across targeted regions and to generate highly accurate reference sequences.


June 1, 2021  |  

Immune regions are no longer incomprehensible with SMRT Sequencing

The complex immune regions of the genome, including MHC and KIR, contain large copy number variants (CNVs), a high density of genes, hyper-polymorphic gene alleles, and conserved extended haplotypes (CEH) with enormous linkage disequilibrium (LDs). This level of complexity and inherent biases of short-read sequencing make it challenging for extracting immune region haplotype information from reference-reliant, shotgun sequencing and GWAS methods. As NGS based genome and exome sequencing and SNP arrays have become a routine for population studies, numerous efforts are being made for developing software to extract and or impute the immune gene information from these datasets. Despite these efforts, the fine mapping of causal variants of immune genes for their well-documented association with cancer, drug-induced hypersensitivity and immune-related diseases, has been slower than expected. This has in many ways limited our understanding of the mechanisms leading to immune disease. In the present work, we demonstrate the advantages of long reads delivered by SMRT Sequencing for assembling complete haplotypes of MHC and KIR gene clusters, as well as calling correct genotypes of genes comprised within them. All the genotype information is detected at allele- level with full phasing information across SNP-poor regions. Genotypes were called correctly from targeted gene amplicons, haplotypes, as well as from a completely assembled 5 Mb contig of the MHC region from a de novo assembly of whole genome shotgun data. De novo analysis pipeline used in all these approaches allowed for reference-free analysis without imputation, a key for interrogation without prior knowledge about ethnic backgrounds. These methods are thus easily adoptable for previously uncharacterized human or non-human species.


June 1, 2021  |  

Reconstruction of the spinach coding genome using full-length transcriptome without a reference genome

For highly complex and large genomes, a well-annotated genome may be computationally challenging and costly, yet the study of alternative splicing events and gene annotations usually rely on the existence of a genome. Long-read sequencing technology provides new opportunities to sequence full-length cDNAs, avoiding computational challenges that short read transcript assembly brings. The use of single molecule, real-time sequencing from PacBio to sequence transcriptomes (the Iso-Seq method), which produces de novo, high-quality, full-length transcripts, has revealed an astonishing amount of alternative splicing in eukaryotic species. With the Iso-Seq method, it is now possible to reconstruct the transcribed regions of the genome using just the transcripts themselves. We present Cogent, a tool for finding gene families and reconstructing the coding genome in the absence of a high-quality reference genome. Cogent uses k-mer similarities to first partition the transcripts into different gene families. Then, for each gene family, the transcripts are used to build a splice graph. Cogent identifies bubbles resulting from sequencing errors, minor variants, and exon skipping events, and attempts to resolve each splice graph down to the minimal set of reconstructed contigs. We apply Cogent to the Iso-Seq data for spinach, Spinacia oleracea, for which there is also a PacBio-based draft genome to validate the reconstruction. The Iso-Seq dataset consists of 68,263 fulllength, Quiver-polished transcript sequences ranging from 528 bp to 6 kbp long (mean: 2.1 kbp). Using the genome mapping as ground truth, we found that 95% (8045/8446) of the Cogent gene families found corresponded to a single genomic loci. For families that contained multiple loci, they were often homologous genes that would be categorized as belonging to the same gene family. Coding genome reconstruction was then performed individually for each gene family. A total of 86% (7283/8446) of the gene families were resolved to a single contig by Cogent, and was validated to be also a single contig in the genome. In 59 cases, Cogent reconstructed a single contig, however the contig corresponded to 2 or more loci in the genome, suggesting possible scaffolding opportunities. In 24 cases, the transcripts had no hits to the genome, though Pfam and BLAST searches of the transcripts show that they were indeed coding, suggesting that the genome is missing certain coding portions. Given the high quality of the spinach genome, we were not surprised to find that Cogent only minorly improved the genome space. However the ability of Cogent to accurately identify gene families and reconstruct the coding genome in a de novo fashion shows that it will be extremely powerful when applied to datasets for which there is no or low-quality reference genome.


June 1, 2021  |  

Effect of coverage depth and haplotype phasing on structural variant detection with PacBio long reads

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.


June 1, 2021  |  

A high-quality genome assembly of SMRT Sequences reveals long-range haplotype structure in the diploid mosquito Aedes aegypti

Aedes aegypti is a tropical and subtropical mosquito vector for Zika, yellow fever, dengue fever, chikungunya, and other diseases. The outbreak of Zika in the Americas, which can cause microcephaly in the fetus of infected women, adds urgency to the need for a high-quality reference genome in order to better understand the organism’s biology and its role in transmitting human disease. We describe the first diploid assembly of an insect genome, using SMRT sequencing and the open-source assembler FALCON-Unzip. This assembly has high contiguity (contig N50 1.3 Mb), is more complete than previous assemblies (Length 1.45 Gb with 87% BUSCO genes complete), and is high quality (mean base >QV30). Long-range haplotype structure, in some cases encompassing more than 4 Mb of extremely divergent homologous sequence, is resolved using a combination of the FALCON-Unzip assembler, genome annotation, coverage depth, and pairwise nucleotide alignments.


June 1, 2021  |  

A high-quality genome assembly of SMRT sequences reveals long range haplotype structure in the diploid mosquito Aedes aegypti

Aedes aegypti is a tropical and subtropical mosquito vector for Zika, yellow fever, dengue fever, and chikungunya. We describe the first diploid assembly of an insect genome, using SMRT Sequencing and the open-source assembler FALCON-Unzip. This assembly has high contiguity (contig N50 1.3 Mb), is more complete than previous assemblies (Length 1.45 Gb with 87% BUSCO genes complete), and is high quality (mean base >QV30 after polishing). Long-range haplotype structure, in some cases encompassing more than 4 Mb of extremely divergent homologous sequence with dramatic differences in coding sequence content, is resolved using a combination of the FALCON-Unzip assembler, genome annotation, coverage depth, and pairwise nucleotide alignments.


June 1, 2021  |  

T-cell receptor profiling using PacBio sequencing of SMARTer libraries

T-cells play a central part in the immune response in humans and related species. T-cell receptors (TCRs), heterodimers located on the T-cell surface, specifically bind foreign antigens displayed on the MHC complex of antigen-presenting cells. The wide spectrum of potential antigens is addressed by the diversity of TCRs created by V(D)J recombination. Profiling this repertoire of TCRs could be useful from, but not limited to, diagnosis, monitoring response to treatments, and examining T-cell development and diversification.


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.


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