2015 SMRT Informatics Developers Conference Presentation Slides: Ali Bashir of Mount Sinai School of Medicine discussed methods for characterizing structural variation in human genomes across a variety of coverage levels.
The Genome in a Bottle Consortium is developing the reference materials, reference methods , and reference data n
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.
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.
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
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.
Full-length gene capture solutions offer opportunities to screen and characterize structural variations and genetic diversity to understand key traits in plants and animals. Through a combined Roche NimbleGen probe capture and SMRT Sequencing strategy, we demonstrate the capability to resolve complex gene structures often observed in plant defense and developmental genes spanning multiple kilobases. The custom panel includes members of the WRKY plant-defense-signaling family, members of the NB-LRR disease-resistance family, and developmental genes important for flowering. The presence of repetitive structures and low-complexity regions makes short-read sequencing of these genes difficult, yet this approach allows researchers to obtain complete sequences for unambiguous resolution of gene models. This strategy has been applied to genomic DNA samples from soybean coupled with barcoding for multiplexing.
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.
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.
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.
With the increasing availability of whole-genome sequencing, haplotype reconstruction of individual genomes, or haplotype assembly, remains unsolved. Like the de novo genome assembly problem, haplotype assembly is greatly simplified by having more long-range information. The Targeted Locus Amplification (TLA) technology from Cergentis has the unique capability of targeting a specific region of the genome using a single primer pair and yielding ~2 kb DNA circles that are comprised of ~500 bp fragments. Fragments from the same circle come from the same haplotype and follow an exponential decay in distance from the target region, with a span that reaches the multi-megabase range. Here, we apply TLA to the BRCA1 gene on NA12878 and then sequence the resulting 2 kb circles on a PacBio RS II. The multiple fragments per circle were iteratively mapped to hg19 and then haplotype assembled using HAPCUT. We show that the 80 kb length of BRCA1 is represented by a single haplotype block, which was validated against GIAB data. We then explored chromosomal-scale haplotype assembly by combining these data with whole genome shotgun PacBio long reads, and demonstrate haplotype blocks approaching the length of chromosome 17 on which BRCA1 lies. Finally, by performing TLA without the amplification step and size selecting for reads >5 kb to maximize the number of fragments per read, we target whole genome haplotype assembly across all chromosomes.
Alzheimer’s disease (AD) is a devastating neurodegenerative disease that is genetically complex. Although great progress has been made in identifying fully penetrant mutations in genes such as APP, PSEN1 and PSEN2 that cause early-onset AD, these still represent a very small percentage of AD cases. Large-scale, genome-wide association studies (GWAS) have identified at least 20 additional genetic risk loci for the more common form of late-onset AD. However, the identified SNPs are typically not the actual risk variants, but are in linkage disequilibrium with the presumed causative variant (Van Cauwenberghe C, et al., The genetic landscape of Alzheimer disease: clinical implications and perspectives. Genet Med 2015;18:421-430). Long-read sequencing together with hybrid-capture targeting technologies provides a powerful combination to target candidate genes/transcripts of interest. Shearing the genomic DNA to ~5 kb fragments and then capturing with probes that span the whole gene(s) of interest can provide uniform coverage across the entire region, identifying variants and allowing for phasing into two haplotypes. Furthermore, capturing full-length cDNA from the same sample using the same capture probes can also provide an understanding of isoforms that are generated and allow them to be assigned to their corresponding haplotype. Here we present a method for capturing genomic DNA and cDNA from an AD sample using a panel of probes targeting approximately 20 late-onset AD candidate genes which includes CLU, ABCA7, CD33, TREM2, TOMM40, PSEN2, APH1 and BIN1. By combining xGen® Lockdown® probes with SMRT Sequencing, we provide completely sequenced candidate genes as well as their corresponding transcripts. In addition, we are also able to evaluate structural variants that due to their size, repetitive nature, or low sequence complexity have been un-sequenceable using short-read technologies.
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.
The human immunoglobulin heavy chain locus (IGH) remains among the most understudied regions of the human genome. Recent efforts have shown that haplotype diversity within IGH is elevated and exhibits population specific patterns; for example, our re-sequencing of the locus from only a single chromosome uncovered >100 Kb of novel sequence, including descriptions of six novel alleles, and four previously unmapped genes. Historically, this complex locus architecture has hindered the characterization of IGH germline single nucleotide, copy number, and structural variants (SNVs; CNVs; SVs), and as a result, there remains little known about the role of IGH polymorphisms in inter-individual antibody repertoire variability and disease. To remedy this, we are taking a multi-faceted approach to improving existing genomic resources in the human IGH region. First, from whole-genome and fosmid-based datasets, we are building the largest and most ethnically diverse set of IGH reference assemblies to date, by employing PacBio long-read sequencing combined with novel algorithms for phased haplotype assembly. In total, our effort will result in the characterization of >15 phased haplotypes from individuals of Asian, African, and European descent, to be used as a representative reference set by the genomics and immunogenetics community. Second, we are utilizing this more comprehensive sequence catalogue to inform the design and analysis of novel targeted IGH genotyping assays. Standard targeted DNA enrichment methods (e.g., exome capture) are currently optimized for the capture of only very short (100’s of bp) DNA segments. Our platform uses a modified bench protocol to pair existing capture-array technologies with the enrichment of longer fragments of DNA, enabling the use of PacBio sequencing of DNA segments up to 7 Kb. This substantial increase in contiguity disambiguates many of the complex repeated structures inherent to the locus, while yielding the base pair fidelity required to call SNVs. Together these resources will establish a stronger framework for further characterizing IGH genetic diversity and facilitate IGH genomic profiling in the clinical and research settings, which will be key to fully understanding the role of IGH germline variation in antibody repertoire development and disease.
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