Generating de novo reference genome assemblies for non-model organisms is a laborious task that often requires a large amount of data from several sequencing platforms and cytogenetic surveys. By using PacBio sequence data and new library creation techniques, we present a de novo, high quality reference assembly for the goat (Capra hircus) that demonstrates a primarily sequencing-based approach to efficiently create new reference assemblies for Eukaryotic species. This goat reference genome was created using 38 million PacBio P5-C3 reads generated from a San Clemente goat using the Celera Assembler PBcR pipeline with PacBio read self-correction. In order to generate the assembly, corrected and filtered reads were pre-assembled into a consensus model using PBDAGCON, and subsequently assembled using the Celera Assembly version 8.2. We generated 5,902 contigs using this method with a contig N50 size of 2.56 megabases. In order to generate chromosome-sized scaffolds, we used the LACHESIS scaffolding method to identify cis-chromosome Hi-C interactions in order to link contigs together. We then compared our new assembly to the existing goat reference assembly to identify large-scale discrepancies. In our comparison, we identified 247 disagreements between the two assemblies consisting of 123 inversions and 124 chromosome-contig relocations. The high quality of this data illustrates how this methodology can be used to efficiently generate new reference genome assemblies without the use of expensive fluorescent cytometry or large quantities of data from multiple sequencing platforms.
The goat (Capra hircus) remains an important livestock species due to the species’ ability to forage and provide milk, meat and wool in arid environments. The current goat reference assembly and annotation borrows heavily from other loosely related livestock species, such as cattle, and may not reflect the unique structural and functional characteristics of the species. We present preliminary data from a new de novo reference assembly for goat that primarily utilizes 38 million PacBio P5-C3 reads generated from an inbred San Clemente goat. This assembly consists of only 5,902 contigs with a contig N50 size of 2.56 megabases which were grouped into scaffolds using cis-chromosome associations generated by the analysis of Hi-C sequence reads. To provide accurate functional genetic annotation, we utilized existing RNA-seq data and generated new data consisting of over 784 million reads from a combination of 27 different developmental timepoints/tissues. This dataset provides a tangible improvement over existing goat genomics resources by correcting over 247 misassemblies in the current goat reference genome and by annotating predicted gene models with actual expressed transcript data. Our goal is to provide a high quality resource to researchers to enable future genomic selection and functional prediction within the field of goat genomics.
2015 SMRT Informatics Developers Conference Presentation Slides: Adam English, from the Human Genome Sequencing Center at Baylor College of Medicine presents on the structural variation tools being developed at Baylor.
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
Reference quality de novo genome assemblies were once solely the domain of large, well-funded genome projects. While next-generation short read technology removed some of the cost barriers, accurate chromosome-scale assembly remains a real challenge. Here we present efforts to de novo assemble the goat (Capra hircus) genome. Through the combination of single-molecule technologies from Pacific Biosciences (sequencing) and BioNano Genomics (optical mapping) coupled with high-throughput chromosome conformation capture sequencing (Hi-C), an inbred San Clemente goat genome has been sequenced and assembled to a high degree of completeness at a relatively modest cost. Starting with 38 million PacBio reads, we integrated the MinHash Alignment Process (MHAP) with the Celera Assembler (CA) to produce an assembly composed of 3110 contigs with a contig N50 size of 4.7 Mb. This assembly was scaffolded with BioNano genome maps derived from a single IrysChip into 333 scaffolds with an N50 of 23.1 Mb including the complete scaffolding of chromosome 20. Finally, cis-chromosome associations were determined by Hi-C, yielding complete reconstruction of all autosomes into single scaffolds with a final N50 of 91.7 Mb. We hope to demonstrate that our methods are not only cost effective, but improve our ability to annotate challenging genomic regions such as highly repetitive immune gene clusters.
Characterizing haplotype diversity at the immunoglobulin heavy chain locus across human populations using novel long-read sequencing and assembly approaches
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.
A method for the identification of variants in Alzheimer’s disease candidate genes and transcripts using hybridization capture combined with long-read sequencing
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 causal 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).
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.
Over the past decades neurological disorders have been extensively studied producing a large number of candidate genomic regions and candidate genes. The SNPs identified in these studies rarely represent the true disease-related functional variants. However, more recently a shift in focus from SNPs to larger structural variants has yielded breakthroughs in our understanding of neurological disorders.Here we have developed candidate gene screening methods that combine enrichment of long DNA fragments with long-read sequencing that is optimized for structural variation discovery. We have also developed a novel, amplification-free enrichment technique using the CRISPR/Cas9 system to target genomic regions.We sequenced gDNA and full-length cDNA extracted from the temporal lobe for two Alzheimer’s patients for 35 GWAS candidate genes. The multi-kilobase long reads allowed for phasing across the genes and detection of a broad range of genomic variants including SNPs to multi-kilobase insertions, deletions and inversions. In the full-length cDNA data we detected differential allelic isoform complexity, novel exons as well as transcript isoforms. By combining the gDNA data with full-length isoform characterization allows to build a more comprehensive view of the underlying biological disease mechanisms in Alzheimer’s disease. Using the novel PCR-free CRISPR-Cas9 enrichment method we screened several genes including the hexanucleotide repeat expansion C9ORF72 that is associated with 40% of familiar ALS cases. This method excludes any PCR bias or errors from an otherwise hard to amplify region as well as preserves the basemodication in a single molecule fashion which allows you to capture mosaicism present in the sample.
Though a role for structural variants in human disease has long been recognized, it has remained difficult to identify intermediate-sized variants (50 bp to 5 kb), which are too small to detect with array comparative genomic hybridization, but too large to reliably discover with short-read DNA sequencing. Recent studies have demonstrated that PacBio Single Molecule, Real-Time (SMRT) sequencing fills this technology gap. SMRT sequencing detects tens of thousands of structural variants in the human genome, approximately five times the sensitivity of short-read DNA sequencing.
Structural variants (genomic differences =50 base pairs) contribute to the evolution of organisms traits and human disease. Most structural variants (SVs) are too small to detect with array comparative genomic hybridization but too large to reliably discover with short-read DNA sequencing. Recent studies in human genomes show that PacBio SMRT Sequencing sensitively detects structural variants.
Most of the base pairs that differ between two human genomes are in intermediate-sized structural variants (50 bp to 5 kb), which are too small to detect with array comparative genomic hybridization or optical mapping but too large to reliably discover with short-read DNA sequencing. Long-read sequencing with PacBio Single Molecule, Real-Time (SMRT) Sequencing platforms fills this technology gap. PacBio SMRT Sequencing detects tens of thousands of structural variants in a human genome with approximately five times the sensitivity of short-read DNA sequencing. Effective application of PacBio SMRT Sequencing to detect structural variants requires quality bioinformatics tools that account for the characteristics of PacBio reads. To provide such a solution, we developed pbsv, a structural variant caller for PacBio reads that works as a chain of simple stages: 1) map reads to the reference genome, 2) identify reads with signatures of structural variation, 3) cluster nearby reads with similar signatures, 4) summarize each cluster into a consensus variant, and 5) filter for variants with sufficient read support. To evaluate the baseline performance of pbsv, we generated high coverage of a diploid human genome on the PacBio Sequel System, established a target set of structural variants, and then titrated to lower coverage levels. The false discovery rate for pbsv is low at all coverage levels. Sensitivity is high even at modest coverage: above 85% at 10-fold coverage and above 95% at 20-fold coverage. To assess the potential for PacBio SMRT Sequencing to identify pathogenic variants, we evaluated an individual with clinical symptoms suggestive of Carney complex for whom short-read whole genome sequencing was uninformative. The individual was sequenced to 9-fold coverage on the PacBio Sequel System, and structural variants were called with pbsv. Filtering for rare, genic structural variants left six candidates, including a heterozygous 2,184 bp deletion that removes the first coding exon of PRKAR1A. Null mutations in PRKAR1Acause autosomal dominant Carney complex, type 1. The variant was determined to be de novo, and it was classified as likely pathogenic based on ACMG standards and guidelines for variant interpretation. These case studies demonstrate the ability of pbsv to detect structural variants in low-coverage PacBio SMRT Sequencing and suggest the importance of considering structural variants in any study of human genetic variation.
Structural variants (genomic differences =50 base pairs) contribute to the evolution of traits and disease. Most structural variants (SVs) are too small to detect with array comparative genomic hybridization and too large to reliably discover with short-read DNA sequencing.
Microbes play an important role in nearly every part of our world, as they affect human health, our environment, agriculture, and aid in waste management. Complete closed genome sequences, which have become the gold standard with PacBio long-read sequencing, can be key to understanding microbial functional characteristics. However, input requirements, consumables costs, and the labor required to prepare and sequence a microbial genome have in the past put PacBio sequencing out of reach for some larger projects. We have developed a multiplexed library prep approach that is simple, fast, and cost-effective, and can produce 4 to 16 closed bacterial genomes from one Sequel SMRT Cell. Additionally, we are introducing a streamlined analysis pipeline for processing multiplexed genome sequence data through de novo HGAP assembly, making the entire process easy for lab personnel to perform. Here we present the entire workflow from shearing through assembly, with times for each step. We show HGAP assembly results with single or very few contigs from bacteria from different size genomes, sequenced without or with size selection. These data illustrate the benefits and potential of the PacBio multiplexed library prep and the Sequel System for sequencing large numbers of microbial genomes.
Structural variants (SVs) – genomic differences =50 base pairs – are few by count compared to single nucleotide variants (SNVs) and indels but include most of the base pairs that differ between two humans.