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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  |  

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  |  

Building a platinum human genome assembly from single haplotype human genomes generated from long molecule sequencing

The human reference sequence has provided a foundation for studies of genome structure, human variation, evolutionary biology, and disease. At the time the reference was originally completed there were some loci recalcitrant to closure; however, the degree to which structural variation and diversity affected our ability to produce a representative genome sequence at these loci was still unknown. Many of these regions in the genome are associated with large, repetitive sequences and exhibit complex allelic diversity such producing a single, haploid representation is not possible. To overcome this challenge, we have sequenced DNA from two hydatidiform moles (CHM1 and CHM13), which are essentially haploid. CHM13 was sequenced with the latest PacBio technology (P6-C5) to 52X genome coverage and assembled using Daligner and Falcon v0.2 (GCA_000983455.1, CHM13_1.1). Compared to the first mole (CHM1) PacBio assembly (GCA_001007805.1, 54X) contig N50 of 4.5Mb, the contig N50 of CHM13_1.1 is almost 13Mb, and there is a 13-fold reduction in the number of contigs. This demonstrates the improved contiguity of sequence generated with the new chemistry. We annotated 50,188 RefSeq transcripts of which only 0.63% were split transcripts, and the repetitive and segmental duplication content was within the expected range. These data all indicate an extremely high quality assembly. Additionally, we sequenced CHM13 DNA using Illumina SBS technology to 60X coverage, aligned these reads to the GRCh37, GRCh38, and CHM13_1.1 assemblies and performed variant calling using the SpeedSeq pipeline. The number of single nucleotide variants (SNV) and indels was comparable between GRCh37 and GRCh38. Regions that showed increased SNV density in GRCh38 compared to GRCh37 could be attributed to the addition of centromeric alpha satellite sequence to the reference assembly. Alternatively, regions of decreased SNV density in GRCh38 were concentrated in regions that were improved from BAC based sequencing of CHM1 such as 1p12 and 1q21 containing the SRGAP2 gene family. The alignment of PacBio reads to GRCh37 and GRCh38 assemblies allowed us to resolve complex loci such as the MHC region where the best alignment was to the DBB (A2-B57-DR7) haplotype. Finally, we will discuss how combining the two high quality mole assemblies can be used for benchmarking and novel bioinformatics tool development.


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  |  

Comprehensive genome and transcriptome structural analysis of a breast cancer cell line using PacBio long read sequencing

Genomic instability is one of the hallmarks of cancer, leading to widespread copy number variations, chromosomal fusions, and other structural variations. The breast cancer cell line SK-BR-3 is an important model for HER2+ breast cancers, which are among the most aggressive forms of the disease and affect one in five cases. Through short read sequencing, copy number arrays, and other technologies, the genome of SK-BR-3 is known to be highly rearranged with many copy number variations, including an approximately twenty-fold amplification of the HER2 oncogene. However, these technologies cannot precisely characterize the nature and context of the identified genomic events and other important mutations may be missed altogether because of repeats, multi-mapping reads, and the failure to reliably anchor alignments to both sides of a variation. To address these challenges, we have sequenced SK-BR-3 using PacBio long read technology. Using the new P6-C4 chemistry, we generated more than 70X coverage of the genome with average read lengths of 9-13kb (max: 71kb). Using Lumpy for split-read alignment analysis, as well as our novel assembly-based algorithms for finding complex variants, we have developed a detailed map of structural variations in this cell line. Taking advantage of the newly identified breakpoints and combining these with copy number assignments, we have developed an algorithm to reconstruct the mutational history of this cancer genome. From this we have discovered a complex series of nested duplications and translocations between chr17 and chr8, two of the most frequent translocation partners in primary breast cancers, resulting in amplification of HER2. We have also carried out full-length transcriptome sequencing using PacBio’s Iso-Seq technology, which has revealed a number of previously unrecognized gene fusions and isoforms. Combining long-read genome and transcriptome sequencing technologies enables an in-depth analysis of how changes in the genome affect the transcriptome, including how gene fusions are created across multiple chromosomes. This analysis has established the most complete cancer reference genome available to date, and is already opening the door to applying long-read sequencing to patient samples with complex genome structures.


June 1, 2021  |  

The resurgence of reference quality genome

Several new 3rd generation long-range DNA sequencing and mapping technologies have recently become available that are starting to create a resurgence in genome sequence quality. Unlike their 2nd generation, shortread counterparts that can resolve a few hundred or a few thousand basepairs, the new technologies can routinely sequence 10,000 bp reads or map across 100,000 bp molecules. The substantially greater lengths are being used to enhance a number of important problems in genomics and medicine, including de novo genome assembly, structural variation detection, and haplotype phasing. Here we discuss the capabilities of the latest technologies, and show how they will improve the “3Cs of Genome Assembly”: the contiguity, completeness, and correctness. We derive this analysis from (1) a metaanalysis of the currently available 3rd generation genome assemblies, (2) a retrospective analysis of the evolution of the reference human genome, and (3) extensive simulations with dozens of species across the tree of life. We also propose a model using support vector regression (SVR) that predicts genome assembly performance using four features: read lengths(L) and coverage values(C) that can be used for evaluating potential technologies along with genome size(G) and repeats(R) that present species specific characteristics. The proposed model significantly improves genome assembly performance prediction by adopting data-driven approach and addressing limitations of the previous hypothesis-driven methodology. Overall, we anticipate these technologies unlock the genomic “dark matter”, and provide many new insights into evolution, agriculture, and human diseases.


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  |  

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  |  

Highly contiguous de novo human genome assembly and long-range haplotype phasing using SMRT Sequencing

The long reads, random error, and unbiased sampling of SMRT Sequencing enables high quality, de novo assembly of the human genome. PacBio long reads are capable of resolving genomic variations at all size scales, including SNPs, insertions, deletions, inversions, translocations, and repeat expansions, all of which are both important in understanding the genetic basis for human disease, and difficult to access via other technologies. In demonstration of this, we report a new high-quality, diploid-aware de novo assembly of Craig Venter’s well-studied 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.


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