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 . 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. Zook et al, Nat Biotech. 2014.
AGBT Virtual Poster: Generation of local reference genomes using PacBio and BioNano data, and analysis of the “dark matter” of structural variants in 1000 Swedish genomes
In this AGBT 2017 poster, Ulf Gyllensten from Uppsala University presents two local reference genomes generated with PacBio and Bionano Genomics data. These assemblies include structural variation and repetitive regions…
Structural variants (SVs, differences >50 base pairs) account for most of the base pairs that differ between two human genomes, and are known to cause over 1,000 genetic disorders including…
In this ASHG 2020 PacBio Workshop Jonas Korlach, CSO, shares how the new PacBio Sequel IIe System makes highly accurate long-read sequencing easy and affordable so?all scientists can gain comprehensive…
The landscape of SNCA transcripts across synucleinopathies: New insights from long reads sequencing analysis
Dysregulation of alpha-synuclein expression has been implicated in the pathogenesis of synucleinopathies, in particular Parkinsontextquoterights Disease (PD) and Dementia with Lewy bodies (DLB). Previous studies have shown that the alternatively spliced isoforms of the SNCA gene are differentially expressed in different parts of the brain for PD and DLB patients. Similarly, SNCA isoforms with skipped exons can have a functional impact on the protein domains. The large intronic region of the SNCA gene was also shown to harbor structural variants that affect transcriptional levels. Here we apply the first study of using long read sequencing with targeted capture of both the gDNA and cDNA of the SNCA gene in brain tissues of PD, DLB, and control samples using the PacBio Sequel system. The targeted full-length cDNA (Iso-Seq) data confirmed complex usage of known alternative start sites and variable 3textquoteright UTR lengths, as well as novel 5textquoteright starts and 3textquoteright ends not previously described. The targeted gDNA data allowed phasing of up to 81% of the ~114kb SNCA region, with the longest phased block excedding 54 kb. We demonstrate that long gDNA and cDNA reads have the potential to reveal long-range information not previously accessible using traditional sequencing methods. This approach has a potential impact in studying disease risk genes such as SNCA, providing new insights into the genetic etiologies, including perturbations to the landscape the gene transcripts, of human complex diseases such as synucleinopathies.
Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.
Evolution and global transmission of a multidrug-resistant, community-associated MRSA lineage from the Indian subcontinent
The evolution and global transmission of antimicrobial resistance has been well documented in Gram-negative bacteria and healthcare-associated epidemic pathogens, often emerging from regions with heavy antimicrobial use. However, the degree to which similar processes occur with Gram-positive bacteria in the community setting is less well understood. Here, we trace the recent origins and global spread of a multidrug resistant, community-associated Staphylococcus aureus lineage from the Indian subcontinent, the Bengal Bay clone (ST772). We generated whole genome sequence data of 340 isolates from 14 countries, including the first isolates from Bangladesh and India, to reconstruct the evolutionary history and genomic epidemiology of the lineage. Our data shows that the clone emerged on the Indian subcontinent in the early 1970s and disseminated rapidly in the 1990s. Short-term outbreaks in community and healthcare settings occurred following intercontinental transmission, typically associated with travel and family contacts on the subcontinent, but ongoing endemic transmission was uncommon. Acquisition of a multidrug resistance integrated plasmid was instrumental in the divergence of a single dominant and globally disseminated clade in the early 1990s. Phenotypic data on biofilm, growth and toxicity point to antimicrobial resistance as the driving force in the evolution of ST772. The Bengal Bay clone therefore combines the multidrug resistance of traditional healthcare-associated clones with the epidemiological transmission of community-associated MRSA. Our study demonstrates the importance of whole genome sequencing for tracking the evolution of emerging and resistant pathogens. It provides a critical framework for ongoing surveillance of the clone on the Indian subcontinent and elsewhere.Importance The Bengal Bay clone (ST772) is a community-acquired and multidrug-resistant Staphylococcus aureus lineage first isolated from Bangladesh and India in 2004. In this study, we show that the Bengal Bay clone emerged from a virulent progenitor circulating on the Indian subcontinent. Its subsequent global transmission was associated with travel or family contact in the region. ST772 progressively acquired specific resistance elements at limited cost to its fitness and continues to be exported globally resulting in small-scale community and healthcare outbreaks. The Bengal Bay clone therefore combines the virulence potential and epidemiology of community-associated clones with the multidrug-resistance of healthcare-associated S. aureus lineages. This study demonstrates the importance of whole genome sequencing for the surveillance of highly antibiotic resistant pathogens, which may emerge in the community setting of regions with poor antibiotic stewardship and rapidly spread into hospitals and communities across the world.
The discovery of mutations associated with human genetic dis- ease is an exercise in comparative genomics (see Glossary). Although there are many different strategies and approaches, the central premise is that affected persons harbor a significant excess of pathogenic DNA variants as com- pared with a group of unaffected persons (controls) that is either clinically defined1 or established by surveying large swaths of the general population.2 The more exclu- sive the variant is to the disease, the greater its penetrance, the larger its effect size, and the more relevant it becomes to both disease diagnosis and future therapeutic investigation. The most popular approach used by researchers in human genetics is the case–control design, but there are others that can be used to track variants and disease in a family context or that consider the probability of different classes of mutations based on evolutionary patterns of divergence or de novo mutational change.3,4 Although the approaches may be straightforward, the discovery of patho- genic variation and its mechanism of action often is less trivial, and decades of research can be required in order to identify the variants underlying both mendelian and complex genetic traits.
Benchmark small variant calls are required for developing, optimizing and assessing the performance of sequencing and bioinformatics methods. Here, as part of the Genome in a Bottle (GIAB) Consortium, we apply a reproducible, cloud-based pipeline to integrate multiple short- and linked-read sequencing datasets and provide benchmark calls for human genomes. We generate benchmark calls for one previously analyzed GIAB sample, as well as six genomes from the Personal Genome Project. These new genomes have broad, open consent, making this a ‘first of its kind’ resource that is available to the community for multiple downstream applications. We produce 17% more benchmark single nucleotide variations, 176% more indels and 12% larger benchmark regions than previously published GIAB benchmarks. We demonstrate that this benchmark reliably identifies errors in existing callsets and highlight challenges in interpreting performance metrics when using benchmarks that are not perfect or comprehensive. Finally, we identify strengths and weaknesses of callsets by stratifying performance according to variant type and genome context.
The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.0 million insertions and deletions (indels). The pipeline processes one whole-genome sequencing sample in 6.5?h using a system with 36?CPU cores. We show that using a graph genome reference improves read mapping sensitivity and produces a 0.5% increase in variant calling recall, with unaffected specificity. Structural variations incorporated into a graph genome can be genotyped accurately under a unified framework. Finally, we show that iterative augmentation of graph genomes yields incremental gains in variant calling accuracy. Our implementation is an important advance toward fulfilling the promise of graph genomes to radically enhance the scalability and accuracy of genomic analyses.
Reference genome sequences of two cultivated allotetraploid cottons, Gossypium hirsutum and Gossypium barbadense.
Allotetraploid cotton species (Gossypium hirsutum and Gossypium barbadense) have long been cultivated worldwide for natural renewable textile fibers. The draft genome sequences of both species are available but they are highly fragmented and incomplete1-4. Here we report reference-grade genome assemblies and annotations for G. hirsutum accession Texas Marker-1 (TM-1) and G. barbadense accession 3-79 by integrating single-molecule real-time sequencing, BioNano optical mapping and high-throughput chromosome conformation capture techniques. Compared with previous assembled draft genomes1,3, these genome sequences show considerable improvements in contiguity and completeness for regions with high content of repeats such as centromeres. Comparative genomics analyses identify extensive structural variations that probably occurred after polyploidization, highlighted by large paracentric/pericentric inversions in 14 chromosomes. We constructed an introgression line population to introduce favorable chromosome segments from G. barbadense to G. hirsutum, allowing us to identify 13 quantitative trait loci associated with superior fiber quality. These resources will accelerate evolutionary and functional genomic studies in cotton and inform future breeding programs for fiber improvement.
Current genotyping approaches for single-nucleotide variations rely on short, accurate reads from second-generation sequencing devices. Presently, third-generation sequencing platforms are rapidly becoming more widespread, yet approaches for leveraging their long but error-prone reads for genotyping are lacking. Here, we introduce a novel statistical framework for the joint inference of haplotypes and genotypes from noisy long reads, which we term diplotyping. Our technique takes full advantage of linkage information provided by long reads. We validate hundreds of thousands of candidate variants that have not yet been included in the high-confidence reference set of the Genome-in-a-Bottle effort.