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June 1, 2021  |  

Making the most of long reads: towards efficient assemblers for reference quality, de novo reconstructions

2015 SMRT Informatics Developers Conference Presentation Slides: Gene Myers, Ph.D., Founding Director, Systems Biology Center, Max Planck Institute delivered the keynote presentation. He talked about building efficient assemblers, the importance of random error distribution in sequencing data, and resolving tricky repeats with very long reads. He also encouraged developers to release assembly modules openly, and noted that data should be straightforward to parse since sharing data interfaces is easier than sharing software interfaces.


June 1, 2021  |  

Transcriptome analysis using Hybrid-Seq

2015 SMRT Informatics Developers Conference Presentation Slides: Kin Fau Au of the University of Iowa presented on a suite of transcriptome analysis tools for junction detection, error correction, isoform detection and prediction, and gene fusion.


June 1, 2021  |  

Introduction to SMRT informatics developers conference

2015 SMRT Informatics Developers Conference Presentation Slides: Kevin Corcoran of PacBio provided a brief review of community involvement in the development of analysis tools and showed a preview of upcoming sample preparation, chemistry and informatics improvements.


June 1, 2021  |  

Highly accurate read mapping of third generation sequencing reads for improved structural variation analysis

Characterizing genomic structural variations (SV) is vital for understanding how genomes evolve. Furthermore, SVs are known for playing a role in a wide range of diseases including cancer, autism, and schizophrenia. Nevertheless, due to their complexity they remain harder to detect and less understood than single nucleotide variations. Recently, third-generation sequencing has proven to be an invaluable tool for detecting SVs. The markedly higher read length not only allows single reads to span a SV, it also enables reliable mapping to repetitive regions of the genome. These regions often contain SVs and are inaccessible to short-read mapping. However, current sequencing technologies like PacBio show a raw read error rate of 10% or more consisting mostly of insertions and deletions. Especially in repetitive regions the high error rate causes current mapping methods to fail finding exact borders for SVs, to split up large deletions and insertions into several small ones, or in some cases, like inversions, to fail reporting them at all. Furthermore, for complex SVs it is not possible to find one end-to-end alignment for a given read. The decision of when to split a read into two or more separate alignments without knowledge of the underlying SV poses an even bigger challenge to current read mappers. Here we present NextGenMap-LR for long single molecule PacBio reads which addresses these issues. NextGenMap-LR uses a fast k-mer search to quickly find anchor regions between parts of a read and the reference and evaluates them using a vectorized implementation of the Smith-Waterman (SW) algorithm. The resulting high-quality anchors are then used to determine whether a read spans an SV and has to be split or can be aligned contiguously. Finally, NextGenMap-LR uses a banded SW algorithm to compute the final alignment(s). In this last step, to account for both the sequencing error and real genomic variations, we employ a non-affine gap model that penalizes gap extensions for longer gaps less than for shorter ones. Based on simulated as well as verified human breast cancer SV data we show how our approach significantly improves mapping of long reads around SVs. The non-affine gap model is especially effective at more precisely identifying the position of the breakpoint, and the enhanced scoring scheme enables subsequent variation callers to identify SVs that would have been missed otherwise.


June 1, 2021  |  

Detection of structural variants using third generation sequencing

Structural Variants (SVs), which include deletions, insertions, duplications, inversions and chromosomal rearrangements, have been shown to effect organism phenotypes, including changing gene expression, increasing disease risk, and playing an important role in cancer development. Still it remains challenging to detect all types of SVs from high throughput sequencing data and it is even harder to detect more complex SVs such as a duplication nested within an inversion. To overcome these challenges we developed algorithms for SV analysis using longer third generation sequencing reads. The increased read lengths allow us to span more complex SVs and accurately assess SVs in repetitive regions, two of the major limitations when using short Illumina data. Our enhanced open-source analysis method Sniffles accurately detects structural variants based on split read mapping and assessment of the alignments. Sniffles uses a self-balancing interval tree in combination with a plane sweep algorithm to manage and assess the identified SVs. Central to its high accuracy is its advanced scoring model that can distinguish erroneous alignments from true breakpoints flanking SVs. In experiments with simulated and real genomes (e.g human breast cancer), we find that Sniffles outperforms all other SV analysis approaches in both the sensitivity of finding events as well as the specificity of those events. Sniffles is available at: https://github.com/fritzsedlazeck/Sniffles


June 1, 2021  |  

Cogent: Reconstructing the coding genome from full-length transcriptome sequences

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 Pacific Biosciences to sequence transcriptomes (the Iso-SeqTM 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 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 a Cuttlefish Iso-Seq dataset, for which there is a highly fragmented, Illumina-based draft genome assembly and little annotation. We show that Cogent successfully discovers gene families and can reconstruct the coding region of gene loci. The reconstructed contigs can then be used to visualize alternative splicing events, identify minor variants, and even be used to improve genome assemblies.


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  |  

An improved circular consensus algorithm with an application to detection of HIV-1 Drug-Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger Sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach arbitrarily high quality across longer insert lengths at a lower cost and higher throughput than Sanger Sequencing. We apply this new algorithm, dubbed CCS2, to the characterization of the HIV-1 K103N drug-resistance associated mutation, which is both important clinically, and represents a challenge due to regional sequence context. A mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1,300 bp were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to arbitrarily high accuracy. This result, previously demonstrated for multi-molecule consensus sequences with the Quiver algorithm, is made possible by incorporating per-Zero Mode Waveguide (ZMW) characteristics, thus accounting for the intrinsic changes in the sequencing process that are unique to each ZMW. With CCS2, we are able to achieve a per-read empirical quality of QV30 with 19X coverage. This yields ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40. Additionally, we demonstrate a 0% miscall rate in both unmixed samples, and estimate a 48:52% frequency for the K103N mutation in the mixed sample, consistent with data produced by orthogonal platforms.


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  |  

Phased human genome assemblies with Single Molecule, Real-Time Sequencing

In recent years, human genomic research has focused on comparing short-read data sets to a single human reference genome. However, it is becoming increasingly clear that significant structural variations present in individual human genomes are missed or ignored by this approach. Additionally, remapping short-read data limits the phasing of variation among individual chromosomes. This reduces the newly sequenced genome to a table of single nucleotide polymorphisms (SNPs) with little to no information as to the co-linearity (phasing) of these variants, resulting in a “mosaic” reference representing neither of the parental chromosomes. The variation between the homologous chromosomes is lost in this representation, including allelic variations, structural variations, or even genes present in only one chromosome, leading to lost information regarding allelic-specific gene expression and function. To address these limitations, we have made significant progress integrating haplotype information directly into genome assembly process with long reads. The FALCON-Unzip algorithm leverages a string graph assembly approach to facilitate identification and separation of heterozygosity during the assembly process to produce a highly contiguous assembly with phased haplotypes representing the genome in its diploid state. The outputs of the assembler are pairs of sequences (haplotigs) containing the allelic differences, including SNPs and structural variations, present in the two sets of chromosomes. The development and testing of our de-novo diploid assembler was facilitated and carefully validated using inbred reference model organisms and F1 progeny, which allowed us to ascertain the accuracy and concordance of haplotigs relative to the two inbred parental assemblies. Examination of the results confirmed that our haplotype-resolved assemblies are “Gold Level” reference genomes having a quality similar to that of Sanger-sequencing, BAC-based assembly approaches. We further sequenced and assembled two well-characterized human samples into their respective phased diploid genomes with gap-free contig N50 sizes greater than 23 Mb and haplotig N50 sizes greater than 380 kb. Results of these assemblies and a comparison between the haplotype sets are presented.


June 1, 2021  |  

Structural variant combining Illumina and low-coverage PacBio

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.


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.


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