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Here the Human Pangenome Reference Consortium presents a first draft of the human pangenome reference. The pangenome contains 47 phased, diploid assemblies from a cohort of genetically diverse individuals1. These assemblies cover more than 99% of the expected sequence in each genome and are more than 99% accurate at the structural and base pair levels. Based on alignments of the assemblies, we generate a draft pangenome that captures known variants and haplotypes and reveals new alleles at structurally complex loci. We also add 119 million base pairs of euchromatic polymorphic sequences and 1,115 gene duplications relative to the existing reference GRCh38. Roughly 90 million of the additional base pairs are derived from structural variation. Using our draft pangenome to analyse short-read data reduced small variant discovery errors by 34% and increased the number of structural variants detected per haplotype by 104% compared with GRCh38-based workflows, which enabled the typing of the vast majority of structural variant alleles per sample.

Whole-genome sequencing (WGS) can identify variants that cause genetic disease, but the time required for sequencing and analysis has been a barrier to its use in acutely ill patients. In the present study, we develop an approach for ultra-rapid nanopore WGS that combines an optimized sample preparation protocol, distributing sequencing over 48 flow cells, near real-time base calling and alignment, accelerated variant calling and fast variant filtration for efficient manual review. Application to two example clinical cases identified a candidate variant in

Circular consensus sequencing with Pacific Biosciences (PacBio) technology generates long (10-25 kilobases), accurate 'HiFi' reads by combining serial observations of a DNA molecule into a consensus sequence. The standard approach to consensus generation, pbccs, uses a hidden Markov model. We introduce DeepConsensus, which uses an alignment-based loss to train a gap-aware transformer-encoder for sequence correction. Compared to pbccs, DeepConsensus reduces read errors by 42%. This increases the yield of PacBio HiFi reads at Q20 by 9%, at Q30 by 27% and at Q40 by 90%. With two SMRT Cells of HG003, reads from DeepConsensus improve hifiasm assembly contiguity ( NG50 4.9 megabases (Mb) to 17.2 Mb), increase gene completeness (94% to 97%), reduce the false gene duplication rate (1.1% to 0.5%), improve assembly base accuracy (Q43 to Q45) and reduce variant-calling errors by 24%. DeepConsensus models could be trained to the general problem of analyzing the alignment of other types of sequences, such as unique molecular identifiers or genome assemblies.

The precisionFDA Truth Challenge V2 aimed to assess the state of the art of variant calling in challenging genomic regions. Starting with FASTQs, 20 challenge participants applied their variant-calling pipelines and submitted 64 variant call sets for one or more sequencing technologies (Illumina, PacBio HiFi, and Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with updated Genome in a Bottle benchmark sets and genome stratifications. Challenge submissions included numerous innovative methods, with graph-based and machine learning methods scoring best for short-read and long-read datasets, respectively. With machine learning approaches, combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.

Disclaimer This article was written prior to the COVID-19 pandemic, and it is in no way meant to replace or supersede the advice of expert epidemiologists. We are grateful to those in the scientifi...

Every human inherits one copy of the genome from their mother and another from their father. Parental inheritance helps us understand the transmission of traits and genetic diseases, which often involve de novo variants and rare recessive alleles. Here we present DeepTrio, which learns to analyze child-mother-father trios from the joint sequence information, without explicit encoding of inheritance priors. DeepTrio learns how to weigh sequencing error, mapping error, and de novo rates and genome context directly from the sequence data. DeepTrio has higher accuracy on both Illumina and PacBio HiFi data when compared to DeepVariant. Improvements are especially pronounced at lower coverages (with 20x DeepTrio roughly equivalent to 30x DeepVariant). As DeepTrio learns directly from data, we also demonstrate extensions to exome calling solely by changing the training data. DeepTrio includes pre-trained models for Illumina WGS, Illumina exome, and PacBio HiFi.

Long-read sequencing has the potential to transform variant detection by reaching currently difficult-to-map regions and routinely linking together adjacent variations to enable read-based phasing. Third-generation nanopore sequence data have demonstrated a long read length, but current interpretation methods for their novel pore-based signal have unique error profiles, making accurate analysis challenging. Here, we introduce a haplotype-aware variant calling pipeline, PEPPER-Margin-DeepVariant, that produces state-of-the-art variant calling results with nanopore data. We show that our nanopore-based method outperforms the short-read-based single-nucleotide-variant identification method at the whole-genome scale and produces high-quality single-nucleotide variants in segmental duplications and low-mappability regions where short-read-based genotyping fails. We show that our pipeline can provide highly contiguous phase blocks across the genome with nanopore reads, contiguously spanning between 85% and 92% of annotated genes across six samples. We also extend PEPPER-Margin-DeepVariant to PacBio HiFi data, providing an efficient solution with superior performance over the current WhatsHap-DeepVariant standard. Finally, we demonstrate de novo assembly polishing methods that use nanopore and PacBio HiFi reads to produce diploid assemblies with high accuracy (Q35+ nanopore-polished and Q40+ PacBio HiFi-polished). The PEPPER-Margin-DeepVariant pipeline achieves highly accurate variant calling using nanopore and other long-read sequencing data.

SummaryThe precisionFDA Truth Challenge V2 aimed to assess the state-of-the-art of variant calling in difficult-to-map regions and the Major Histocompatibility Complex (MHC). Starting with FASTQ files, 20 challenge participants applied their variant calling pipelines and submitted 64 variant callsets for one or more sequencing technologies (~35X Illumina, ~35X PacBio HiFi, and ~50X Oxford Nanopore Technologies). Submissions were evaluated following best practices for benchmarking small variants with the new GIAB benchmark sets and genome stratifications. Challenge submissions included a number of innovative methods for all three technologies, with graph-based and machine-learning methods scoring best for short-read and long-read datasets, respectively. New methods out-performed the 2016 Truth Challenge winners, and new machine-learning approaches combining multiple sequencing technologies performed particularly well. Recent developments in sequencing and variant calling have enabled benchmarking variants in challenging genomic regions, paving the way for the identification of previously unknown clinically relevant variants.

Summary Ribbon is an alignment visualization tool that shows how alignments are positioned within both the reference and read contexts, giving an intuitive view that enables a better understanding of structural variants and the read evidence supporting them. Ribbon was born out of a need to curate complex structural variant calls and determine whether each was well supported by long-read evidence, and it uses the same intuitive visualization method to shed light on contig alignments from genome-to-genome comparisons. Availability and implementation Ribbon is freely available online at http://genomeribbon.com/ and is open-source at https://github.com/marianattestad/ribbon. Supplementary information Supplementary data are available at Bioinformatics online.

Structural variations (SVs) are the largest source of genetic variation, but remain poorly understood because of limited genomics technology. Single molecule long read sequencing from Pacific Biosciences and Oxford Nanopore has the potential to dramatically advance the field, although their high error rates challenge existing methods. Addressing this need, we introduce open-source methods for long read alignment (NGMLR, https://github.com/philres/ngmlr) and SV identification (Sniffles, https://github.com/fritzsedlazeck/Sniffles) that enable unprecedented SV sensitivity and precision, including within repeat-rich regions and of complex nested events that can have significant impact on human disorders. Examining several datasets, including healthy and cancerous human genomes, we discover thousands of novel variants using long reads and categorize systematic errors in short-read approaches. NGMLR and Sniffles are further able to automatically filter false events and operate on low amounts of coverage to address the cost factor that has hindered the application of long reads in clinical and research settings.

While genome assembly projects have been successful in a number of haploid or inbred species, one of the current main challenges is assembling non-inbred or rearranged heterozygous genomes. To address this critical need, we introduce the open-source FALCON and FALCON-Unzip algorithms (https://github.com/PacificBiosciences/FALCON/) to assemble Single Molecule Real-Time (SMRT®) Sequencing data into highly accurate, contiguous, and correctly phased diploid genomes. We demonstrate the quality of this approach by assembling new reference sequences for three heterozygous samples, including an F1 hybrid of the model species Arabidopsis thaliana, the widely cultivated V. vinifera cv. Cabernet Sauvignon, and the coral fungus Clavicorona pyxidata that have challenged short-read assembly approaches. The FALCON-based assemblies were substantially more contiguous and complete than alternate short or long-read approaches. The phased diploid assembly enabled the study of haplotype structures and heterozygosities between the homologous chromosomes, including identifying widespread heterozygous structural variations within the coding sequences.

The SK-BR-3 cell line is one of the most important models for HER2+ breast cancers, which affect one in five breast cancer patients. SK-BR-3 is known to be highly rearranged, although much of the variation is in complex and repetitive regions that may be underreported. Addressing this, we sequenced SK-BR-3 using long-read single molecule sequencing from Pacific Biosciences and develop one of the most detailed maps of structural variations (SVs) in a cancer genome available, with nearly 20,000 variants present, most of which were missed by short-read sequencing. Surrounding the important ERBB2 oncogene (also known as HER2), we discover a complex sequence of nested duplications and translocations, suggesting a punctuated progression. Full-length transcriptome sequencing further revealed several novel gene fusions within the nested genomic variants. Combining long-read genome and transcriptome sequencing enables an in-depth analysis of how SVs disrupt the genome and sheds new light on the complex mechanisms involved in cancer genome evolution.

SummaryGenomeScope is an open-source web tool to rapidly estimate the overall characteristics of a genome, including genome size, heterozygosity rate, and repeat content from unprocessed short reads. These features are essential for studying genome evolution, and help to choose parameters for downstream analysis. We demonstrate its accuracy on 324 simulated and 16 real datasets with a wide range in genome sizes, heterozygosity levels, and error rates.Availability and Implementationhttp://genomescope.org,https://github.com/schatzlab/genomescope.gitContactmschatz@jhu.edu.Supplementary informationSupplementary data are available atBioinformaticsonline.

Genomic rearrangements and associated copy number changes are important drivers in cancer as they can alter the expression of oncogenes and tumor suppressors, create gene fusions, and misregulate gene expression. Here we present SplitThreader (http://splitthreader.com), an open-source interactive web application for analysis and visualization of genomic rearrangements and copy number variation in cancer genomes. SplitThreader constructs a sequence graph of genomic rearrangements in the sample and uses a priority queue breadth-first search algorithm on the graph to search for novel interactions. This is applied to detect gene fusions and other novel sequences, as well as to evaluate distances in the rearranged genome between any genomic regions of interest, especially the repositioning of regulatory elements and their target genes. SplitThreader also analyzes each variant to categorize it by its relation to other variants and by its copy number concordance. This identifies balanced translocations, identifies simple and complex variants, and suggests likely false positives when copy number is not concordant across a candidate breakpoint. It also provides explanations when multiple variants affect the copy number state and obscure the contribution of a single variant, such as a deletion within a region that is overall amplified. Together, these categories triage the variants into groups and provide a starting point for further systematic analysis and manual curation. To demonstrate its utility, we apply SplitThreader to three cancer cell lines, MCF-7 and A549 with Illumina paired-end sequencing, and SK-BR-3, with long-read PacBio sequencing. Using SplitThreader, we examine the genomic rearrangements responsible for previously observed gene fusions in SK-BR-3 and MCF-7, and discover many of the fusions involved a complex series of multiple genomic rearrangements. We also find notable differences in the types of variants between the three cell lines, in particular a much higher proportion of reciprocal variants in SK-BR-3 and a distinct clustering of interchromosomal variants in SK-BR-3 and MCF-7 that is absent in A549.

The methylotrophic yeast, Pichia pastoris, has been genetically engineered to produce many heterologous proteins for industrial and research purposes. In order to secrete proteins for easier purification from the extracellular medium, the coding sequence of recombinant proteins are initially fused to the Saccharomyces cerevisiae α-mating factor secretion signal leader. Extensive site-directed mutagenesis of the prepro region of the α-mating factor secretion signal sequence was performed in order to determine the effects of various deletions and substitutions on expression. Though some mutations clearly dampened protein expression, deletion of amino acids 57-70, corresponding to the predicted 3rd alpha helix of α-mating factor secretion signal, increased secretion of reporter proteins horseradish peroxidase and lipase at least 50% in small-scale cultures. These findings raise the possibility that the secretory efficiency of the leader can be further enhanced in the future.

Third-generation long-range DNA sequencing and mapping technologies are creating a renaissance in high-quality genome sequencing. Unlike second-generation sequencing, which produces short reads a few hundred base-pairs long, third-generation single-molecule technologies generate over 10,000 bp reads or map over 100,000 bp molecules. We analyze how increased read lengths can be used to address longstanding problems in de novo genome assembly, structural variation analysis and haplotype phasing.

Summary: Assemblytics is a web app for detecting and analyzing structural variants from a de novo genome assembly aligned to a reference genome. It incorporates a unique anchor filtering approach to increase robustness to repetitive elements, and identifies six classes of variants based on their distinct alignment signatures. Assemblytics can be applied both to comparing aberrant genomes, such as human cancers, to a reference, or to identify differences between related species. Multiple interactive visualizations enable in-depth explorations of the genomic distributions of variants. Availability and Implementation: http://qb.cshl.edu/assemblytics, https://github.com/marianattestad/assemblytics Contact: mnattest@cshl.edu

Pichia pastoris is a methylotrophic yeast that has been genetically engineered to express over one thousand heterologous proteins valued for industrial, pharmaceutical and basic research purposes. In most cases, the 5′ untranslated region (UTR) of the alcohol oxidase 1 (AOX1) gene is fused to the coding sequence of the recombinant gene for protein expression in this yeast. Because the effect of the AOX1 5′UTR on protein expression is not known, site-directed mutagenesis was performed in order to decrease or increase the length of this region. Both of these types of changes were shown to affect translational efficiency, not transcript stability. While increasing the length of the 5′UTR clearly decreased expression of a β-galactosidase reporter in a proportional manner, a deletion analysis demonstrated that the AOX1 5′UTR contains a complex mixture of both positive and negative cis-acting elements, suggesting that the construction of a synthetic 5′UTR optimized for a higher level of expression may be challenging.

Genomic instability is one of the hallmarks of cancer, leading to widespread copy number variations, chromosomal fusions, and other structural variations in many cancers. 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, along with numerous other amplifications and deletions. 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 characterized the amplifications of the HER2 region, discovering a complex series of nested duplications and translocations between chr17 and chr8, two of the most frequent translocation partners in primary breast cancers. 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. Citation Format: Maria Nattestad, Karen Ng, Sara Goodwin, Timour Baslan, Fritz Sedlazeck, James Gurtowski, Elizabeth Hutton, Yogi Sundaravadanam, Tyler Garvin, Marley Alford, Elizabeth Tseng, Philipp Rescheneder, Jason Chin, Timothy Beck, Melissa Kramer, John McPherson, James Hicks, Michael C. Schatz, William R. McCombie. Comprehensive genome and transcriptome structural analysis of a breast cancer cell line using single molecule sequencing. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 850.

The application of next-generation sequencing to estimate genetic diversity of Plasmodium falciparum, the most lethal malaria parasite, has proved challenging due to the skewed AT-richness [∼80.6% (A + T)] of its genome and the lack of technology to assemble highly polymorphic subtelomeric regions that contain clonally variant, multigene virulence families (Ex: var and rifin). To address this, we performed amplification-free, single molecule, real-time sequencing of P. falciparum genomic DNA and generated reads of average length 12 kb, with 50% of the reads between 15.5 and 50 kb in length. Next, using the Hierarchical Genome Assembly Process, we assembled the P. falciparum genome de novo and successfully compiled all 14 nuclear chromosomes telomere-to-telomere. We also accurately resolved centromeres [∼90–99% (A + T)] and subtelomeric regions and identified large insertions and duplications that add extra var and rifin genes to the genome, along with smaller structural variants such as homopolymer tract expansions. Overall, we show that amplification-free, long-read sequencing combined with de novo assembly overcomes major challenges inherent to studying the P. falciparum genome. Indeed, this technology may not only identify the polymorphic and repetitive subtelomeric sequences of parasite populations from endemic areas but may also evaluate structural variation linked to virulence, drug resistance and disease transmission.