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We performed a phase 1 clinical trial to evaluate outcomes in patients receiving donor-derived CD19-specific chimeric antigen receptor (CAR) T cells for B-cell malignancy that relapsed or persisted after matched related allogeneic hemopoietic stem cell transplant. To overcome the cost and transgene-capacity limitations of traditional viral vectors, CAR T cells were produced using the piggyBac transposon system of genetic modification. Following CAR T-cell infusion, 1 patient developed a gradually enlarging retroperitoneal tumor due to a CAR-expressing CD4+ T-cell lymphoma. Screening of other patients led to the detection, in an asymptomatic patient, of a second CAR T-cell tumor in thoracic para-aortic lymph nodes. Analysis of the first lymphoma showed a high transgene copy number, but no insertion into typical oncogenes. There were also structural changes such as altered genomic copy number and point mutations unrelated to the insertion sites. Transcriptome analysis showed transgene promoter–driven upregulation of transcription of surrounding regions despite insulator sequences surrounding the transgene. However, marked global changes in transcription predominantly correlated with gene copy number rather than insertion sites. In both patients, the CAR T-cell–derived lymphoma progressed and 1 patient died. We describe the first 2 cases of malignant lymphoma derived from CAR gene–modified T cells. Although CAR T cells have an enviable record of safety to date, our results emphasize the need for caution and regular follow-up of CAR T recipients, especially when novel methods of gene transfer are used to create genetically modified immune therapies. This trial was registered at www.anzctr.org.au as ACTRN12617001579381.

Long-read sequencing technologies have now reached a level of accuracy and yield that allows their application to variant detection at a scale of tens to thousands of samples. Concomitant with the development of new computational tools, the first population-scale studies involving long-read sequencing have emerged over the past 2 years and, given the continuous advancement of the field, many more are likely to follow. In this Review, we survey recent developments in population-scale long-read sequencing, highlight potential challenges of a scaled-up approach and provide guidance regarding experimental design. We provide an overview of current long-read sequencing platforms, variant calling methodologies and approaches for de novo assemblies and reference-based mapping approaches. Furthermore, we summarize strategies for variant validation, genotyping and predicting functional impact and emphasize challenges remaining in achieving long-read sequencing at a population scale., Long-read sequencing at the population scale presents specific challenges but is becoming increasingly accessible. In this Review, Sedlazeck and colleagues discuss the major platforms and analytical tools, considerations in project design and challenges in scaling long-read sequencing to populations.

Probing epigenetic features on DNA has tremendous potential to advance our understanding of the phased epigenome. In this study, we use nanopore sequencing to evaluate CpG methylation and chromatin accessibility simultaneously on long strands of DNA by applying GpC methyltransferase to exogenously label open chromatin. We performed nanopore sequencing of Nucleosome Occupancy and Methylome (nanoNOMe) on four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231). The single-molecule resolution allows footprinting of protein and nucleosome binding and determining the combinatorial promoter epigenetic signature on individual molecules. Long-read sequencing makes it possible to robustly assign reads to haplotypes, allowing us to generate the first fully phased human epigenome, consisting of chromosome-level allele-specific profiles of CpG methylation and chromatin accessibility. We further apply this to a breast cancer model to evaluate differential methylation and accessibility between cancerous and non-cancerous cells.

Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of the disease and its progression. We performed whole-genome sequencing of the SKBR3 breast cancer cell line and patient-derived tumor and normal organoids from two breast cancer patients using Illumina/10x Genomics, Pacific Biosciences (PacBio), and Oxford Nanopore Technologies (ONT) sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings show that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long reads even at relatively low coverage (25×–30×). Furthermore, we integrated SV and CNV data into a unifying karyotype-graph structure to present a more accurate representation of the mutated cancer genomes. We find hundreds of variants within known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.

De novo assembly of a human genome using nanopore long-read sequences has been reported but it used more than 150,000 CPU hours and weeks of wall-clock time. To enable rapid human genome assembly we present Shasta, a de novo long read assembler, and polishing algorithms named MarginPolish and HELEN. Using a single PromethION nanopore sequencer and our toolkit, we assembled eleven highly contiguous human genomes de novo in nine days. We achieved ~63x coverage, 42 Kb read N50, and 6.5x coverage in 100 Kb+ reads using three flow cells per sample. Shasta produced a complete haploid human genome assembly in under six hours on a single commercial compute node. MarginPolish and HELEN polished haploid assemblies to more than 99.9% identity (QV30) with nanopore reads alone. Addition of proximity ligation (Hi-C) sequencing enabled near chromosome-level scaffolds for all eleven genomes. We compare our assembly performance to existing methods for diploid, haploid, and trio-binned human samples and report superior accuracy and speed., Editors summary High contiguity human genomes can be assembled de novo in 6 hours using nanopore long-read sequences and the Shasta toolkit.

Despite recent improvements in sequencing methods, there remains a need for assays that provide high sequencing depth and comprehensive variant detection. Current methods1-4 are limited by the loss of native modifications, short read length, high input requirements, low yield, or long protocols. Here, we describe nanopore Cas9-targeted sequencing (nCATS), an enrichment strategy that uses targeted cleavage of chromosomal DNA with Cas9 to ligate adaptors for nanopore sequencing. We show that nCATS can simultaneously assess haplotype-resolved single-nucleotide variants (SNVs), structural variations (SVs) and CpG methylation. We apply nCATS to four cell lines, a cell-line-derived xenograft, and normal and paired tumor/normal primary human breast tissue. Median sequencing coverage was 675X using a minION flow cell and 34X using the smaller flongle flow cell. nCATS requires only ~3μg of genomic DNA and can target a large number of loci in a single reaction. The method will facilitate the use of long-read sequencing in research and in the clinic., Editorial summary Point mutations, structural variants and DNA methylation at target loci are assessed by nanopore sequencing.

Background The Syrian hamster (Mesocricetus auratus) has been suggested as a useful mammalian model for a variety of diseases and infections, including infection with respiratory viruses such as SARS-CoV-2. The MesAur1.0 genome assembly was generated in 2013 using whole-genome shotgun sequencing with short-read sequence data. Current more advanced sequencing technologies and assembly methods now permit the generation of near-complete genome assemblies with higher quality and greater continuity. Findings Here, we report an improved assembly of the M. auratus genome (BCM_Maur_2.0) using Oxford Nanopore Technologies long-read sequencing to produce a chromosome-scale assembly. The total length of the new assembly is 2.46 Gb, similar to the 2.50-Gb length of a previous assembly of this genome, MesAur1.0. BCM_Maur_2.0 exhibits significantly improved continuity, with a scaffold N50 that is 6.7 times greater than MesAur1.0. Furthermore, 21,616 protein-coding genes and 10,459 noncoding genes are annotated in BCM_Maur_2.0 compared to 20,495 protein-coding genes and 4,168 noncoding genes in MesAur1.0. This new assembly also improves the unresolved regions as measured by nucleotide ambiguities, where ∼17.11% of bases in MesAur1.0 were unresolved compared to BCM_Maur_2.0, in which the number of unresolved bases is reduced to 3.00%. Conclusions Access to a more complete reference genome with improved accuracy and continuity will facilitate more detailed, comprehensive, and meaningful research results for a wide variety of future studies using Syrian hamsters as models.

GBA variants cause the autosomal recessive Gaucher disease, and carriers are at increased risk of Parkinson’s disease (PD) and Lewy body dementia (LBD). The presence of a highly homologous nearby pseudogene (GBAP1) predisposes to a range of structural variants arising from either gene conversion or reciprocal recombination, the latter resulting in copy number gains or losses, complicating genetic testing and analysis. To date, short-read sequencing has not been able to fully resolve these or other variants in the key homology region, and targeted long-read sequencing has not previously resolved reciprocal recombinants. We present and validate two independent methods to resolve recombinant alleles and other variants in GBA: Gauchian, a novel bioinformatics tool for short-read, whole-genome sequencing data analysis, and Oxford Nanopore long-read sequencing after enrichment with appropriate PCR. The methods were concordant for 42 samples including 30 with a range of recombinants and GBAP1-related mutations, and Gauchian outperforms the GATK Best Practices pipeline. Applying Gauchian to Illumina sequencing of over 10,000 individuals from publicly available cohorts shows that copy number variants (CNVs) spanning GBAP1 are relatively common in Africans. CNV frequencies in PD and LBD are similar to controls, but gains may coexist with other mutations in patients, and a modifying effect cannot be excluded. Gauchian detects a higher frequency of GBA variants in LBD than PD, especially severe ones. These findings highlight the importance of accurate GBA mutation detection in these patients, which is possible by either Gauchian analysis of short-read whole genome sequencing, or targeted long-read sequencing.

Background Cryptosporidium parvum is an apicomplexan parasite commonly found across many host species with a global infection prevalence in human populations of 7.6%. Understanding its diversity and genomic makeup can help in fighting established infections and prohibiting further transmission. The basis of every genomic study is a high-quality reference genome that has continuity and completeness, thus enabling comprehensive comparative studies. Findings Here, we provide a highly accurate and complete reference genome of Cryptosporidium parvum. The assembly is based on Oxford Nanopore reads and was improved using Illumina reads for error correction. We also outline how to evaluate and choose from different assembly methods based on 2 main approaches that can be applied to other Cryptosporidium species. The assembly encompasses 8 chromosomes and includes 13 telomeres that were resolved. Overall, the assembly shows a high completion rate with 98.4% single-copy BUSCO genes. Conclusions This high-quality reference genome of a zoonotic IIaA17G2R1 C. parvum subtype isolate provides the basis for subsequent comparative genomic studies across the Cryptosporidium clade. This will enable improved understanding of diversity, functional, and association studies.

Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost. Tracking low frequency intra-host variants provides important insights with respect to elucidating within-host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable computational solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluate Variabel on both synthetic data (SARS-CoV-2) and patient derived datasets (Ebola virus, norovirus, SARS-CoV-2); our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel.

Long-read sequencing has been shown to have advantages in structural variation (SV) detection and methylation calling. Many studies focus either on SV, methylation, or phasing of SNV; however, only the combination of variants provides a comprehensive insight into the sample and thus enables novel findings in biology or medicine. PRINCESS is a structured workflow that takes raw sequence reads and generates a fully phased SNV, SV, and methylation call set within a few hours. PRINCESS achieves high accuracy and long phasing even on low coverage datasets and can resolve repetitive, complex medical relevant genes that often escape detection. PRINCESS is publicly available at https://github.com/MeHelmy/princess under the MIT license.

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 Mbp of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome to clinical and functional study. Here we demonstrate how the new reference universally improves read mapping and variant calling for 3,202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of novel variants per sample—a new frontier for evolutionary and biomedical discovery. Simultaneously, the new reference eliminates tens of thousands of spurious variants per sample, including up to 12-fold reduction of false positives in 269 medically relevant genes. The vast improvement in variant discovery coupled with population and functional genomic resources position T2T-CHM13 to replace GRCh38 as the prevailing reference for human genetics.One Sentence SummaryThe T2T-CHM13 reference genome universally improves the analysis of human genetic variation.

The high variability characteristic of short tandem repeat (STR) markers is harnessed for human identification in forensic genetic analyses. Despite the power and reliability of current typing techniques, sequence-level information both within and around STRs are masked in the length-based profiles generated. Forensic STR typing using next generation sequencing (NGS) has therefore gained attention as an alternative to traditional capillary electrophoresis (CE) approaches. In this proof-of-principle study, we evaluate the forensic applicability of the newest and smallest NGS platform available – the Oxford Nanopore Technologies (ONT) MinION device. Although nanopore sequencing on the handheld MinION offers numerous advantages, including on-site sample processing, the relatively high error rate and lack of forensic-specific analysis software has prevented accurate profiling across STR panels in previous studies. Here we present STRspy, a streamlined method capable of producing length- and sequence-based STR allele designations from noisy, long-read data. To demonstrate the capabilities of STRspy, seven reference samples (female: n = 2; male: n = 5) were amplified at 15 and 30 PCR cycles using the Promega PowerSeq 46GY System and sequenced on the ONT MinION device in triplicate. Basecalled reads were processed with STRspy using a custom database containing alleles reported in the STRSeq BioProject NIST 1036 dataset. Resultant STR allele designations and flanking region single nucleotide polymorphism (SNP) calls were compared to the manufacturer-validated genotypes for each sample. STRspy generated robust and reliable genotypes across all autosomal STR loci amplified with 30 PCR cycles, achieving 100% concordance based on both length and sequence. Furthermore, we were able to identify flanking region SNPs with >90% accuracy. These results demonstrate that nanopore sequencing platforms are capable of revealing additional variation in and around STR loci depending on read coverage. As the first long-read platform-specific method to successfully profile the entire panel of autosomal STRs amplified by a commercially available multiplex, STRspy significantly increases the feasibility of nanopore sequencing in forensic applications.

The high variability characteristic of short tandem repeat (STR) markers is harnessed for human identification in forensic genetic analyses. Despite the power and reliability of current typing techniques, sequence-level information both within and around STRs are masked in the length-based profiles generated. Forensic STR typing using next generation sequencing (NGS) has therefore gained attention as an alternative to traditional capillary electrophoresis (CE) approaches. In this proof-of-principle study, we evaluate the forensic applicability of the newest and smallest NGS platform available – the Oxford Nanopore Technologies (ONT) MinION device. Although nanopore sequencing on the handheld MinION offers numerous advantages, including low startup cost and on-site sample processing, the relatively high error rate and lack of forensic-specific analysis software has prevented accurate profiling across STR panels in previous studies. Here we present STRspy, a streamlined method capable of producing length- and sequence-based STR allele designations from noisy, error-prone third generation sequencing reads. To assess the capabilities of STRspy, seven reference samples (female: n = 2; male: n = 5) were amplified at 15 and 30 PCR cycles using the Promega PowerSeq 46GY System and sequenced on the ONT MinION device in triplicate. Basecalled reads were then processed with STRspy using a custom database containing alleles reported in the STRSeq BioProject NIST 1036 dataset. Resultant STR allele designations and flanking region single nucleotide polymorphism (SNP) calls were compared to the manufacturer-validated genotypes for each sample. STRspy generated robust and reliable genotypes across all autosomal STR loci amplified with 30 PCR cycles, achieving 100% concordance based on both length and sequence. Furthermore, we were able to identify flanking region SNPs in the 15-cycle dataset with > 90% accuracy. These results demonstrate that when analyzed with STRspy ONT reads can reveal additional variation in and around STR loci depending on read coverage. As the first and only third generation sequencing platform-specific method to successfully profile the entire panel of autosomal STRs amplified by a commercially available multiplex, STRspy significantly increases the feasibility of nanopore sequencing in forensic applications.

The repetitive nature and complexity of multiple medically important genes make them intractable to accurate analysis, despite the maturity of short-read sequencing, resulting in a gap in clinical applications of genome sequencing. The Genome in a Bottle Consortium has provided benchmark variant sets, but these excluded some medically relevant genes due to their repetitiveness or polymorphic complexity. In this study, we characterize 273 of these 395 challenging autosomal genes that have multiple implications for medical sequencing. This extended, curated benchmark reports over 17,000 SNVs, 3,600 INDELs, and 200 SVs each for GRCh37 and GRCh38 across HG002. We show that false duplications in either GRCh37 or GRCh38 result in reference-specific, missed variants for short- and long-read technologies in medically important genes including CBS, CRYAA, and KCNE1. Our proposed solution improves variant recall in these genes from 8% to 100%. This benchmark will significantly improve the comprehensive characterization of these medically relevant genes and guide new method development.

Recent research into structural variants (SVs) has established their importance to medicine and molecular biology, elucidating their role in various diseases, regulation of gene expression, ethnic diversity, and large-scale chromosome evolution—giving rise to the differences within populations and among species. Nevertheless, characterizing SVs and determining the optimal approach for a given experimental design remains a computational and scientific challenge. Multiple approaches have emerged to target various SV classes, zygosities, and size ranges. Here, we review these approaches with respect to their ability to infer SVs across the full spectrum of large, complex variations and present computational methods for each approach.

Purpose:To provide a validated method to confidently identify exon-containing copy number variants (CNVs), with a low false discovery rate (FDR), in targeted sequencing data from a clinical laboratory with particular focus on single-exon CNVs.Methods:DNA sequence coverage data are normalized within each sample and subsequently exonic CNVs are identified in a batch of samples (midpool), when the target log2 ratio of the sample to the batch median exceeds defined thresholds. The quality of exonic CNV calls is assessed by C-scores (Z-like scores) using thresholds derived from gold standard samples and simulation studies. We integrate an ExonQC threshold to lower FDR and compare performance with alternate software (VisCap).Results:Thirteen CNVs were used as a truth set to validate Atlas-CNV and compared with VisCap. We demonstrated FDR reduction in validation, simulation and 10,926 eMERGESeq samples without sensitivity loss. Sixty-four multi-exon and 29 single-exon CNVs with high C-scores were assessed by MLPA.Conclusions:Atlas-CNV is validated as a method to identify exonic CNVs in targeted sequencing data generated in the clinical laboratory. The ExonQC and C-score assignment can reduce FDR (identification of targets with high variance) and improve calling accuracy of single-exon CNVs respectively. We proposed guidelines and criteria to identify high confidence single-exon CNVs.

Hybridization can induce transposons to jump into new genomic positions, which may result in their accumulation across the genome. Alternatively, transposon copy numbers may increase through non-allelic (ectopic) homologous recombination in highly repetitive regions of the genome. The relative contribution of transposition bursts versus recombination-based mechanisms to evolutionary processes remains unclear because studies on transposon dynamics in natural systems are rare. We assessed the genome-wide distribution of transposon insertions in a young hybrid lineage ("invasive Cottus", n=11) and its parental species Cottus rhenanus (n=17) and Cottus perifretum (n=9) using a reference genome assembled from long single molecule PacBio reads. An inventory of transposable elements was reconstructed from the same data and annotated. Transposon copy numbers in the hybrid lineage increased in 120 (15.9%) out of 757 transposons studied here. The copy number increased on average by 69% (range: 10 - 197%). Given the age of the hybrid lineage, this suggests that they have proliferated within a few hundred generations since admixture began. However, frequency spectra of transposon insertions revealed no increase of novel and rare insertions across assembled parts of the genome. This implies that transposons were added to repetitive regions of the genome that remain difficult to assemble. Future studies will need to evaluate whether recombination-based mechanisms rather than genome-wide transposition may explain the majority of the recent transposon proliferation in the hybrid lineage. Irrespectively of the underlying mechanism, the observed over-abundance in repetitive parts of the genome suggests that gene-rich regions are unlikely to be directly affected. This article is protected by copyright. All rights reserved.

In 2001, Celera Genomics and the International Human Genome Sequencing Consortium published their initial drafts of the human genome, which revolutionized the field of genomics. While these drafts and the updates that followed effectively covered the euchromatic fraction of the genome, the heterochromatin and many other complex regions were left unfinished or erroneous. Addressing this remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium has finished the first truly complete 3.055 billion base pair (bp) sequence of a human genome, representing the largest improvement to the human reference genome since its initial release. The new T2T-CHM13 reference includes gapless assemblies for all 22 autosomes plus Chromosome X, corrects numerous errors, and introduces nearly 200 million bp of novel sequence containing 2,226 paralogous gene copies, 115 of which are predicted to be protein coding. The newly completed regions include all centromeric satellite arrays and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies for the first time.

Haplotype-resolved or phased genome assembly provides a complete picture of genomes and their complex genetic variations. However, current algorithms for phased assembly either do not generate chromosome-scale phasing or require pedigree information, which limits their application. We present a method named diploid assembly (DipAsm) that uses long, accurate reads and long-range conformation data for single individuals to generate a chromosome-scale phased assembly within 1 day. Applied to four public human genomes, PGP1, HG002, NA12878 and HG00733, DipAsm produced haplotype-resolved assemblies with minimum contig length needed to cover 50% of the known genome (NG50) up to 25 Mb and phased ~99.5% of heterozygous sites at 98–99% accuracy, outperforming other approaches in terms of both contiguity and phasing completeness. We demonstrate the importance of chromosome-scale phased assemblies for the discovery of structural variants (SVs), including thousands of new transposon insertions, and of highly polymorphic and medically important regions such as the human leukocyte antigen (HLA) and killer cell immunoglobulin-like receptor (KIR) regions. DipAsm will facilitate high-quality precision medicine and studies of individual haplotype variation and population diversity., Assembly of phased human genomes is achieved by combining long reads and long-range conformational data.

Structural variants (SVs) are associated with cancer progression and Mendelian disorders, but challenges with estimating SV frequency remain a barrier to somatic and de novo classification. In particular, variability in filtering and variant calling heuristics limit our ability to use SV catalogs from large cohorts. We present a method to index and search the raw alignments from thousands of samples that overcomes these limitations and supports robust SV analysis.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for ∼25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Recent population studies are ever growing in size of samples to investigate the diversity of a given population or species. These studies reveal ever new polymorphism that lead to important insights into the mechanisms of evolution, but are also important for the interpretation of these variations. Nevertheless, while the full catalog of variations across entire species remains unknown, we can predict which regions harbor additional variations that remain hidden and investigate their properties, thereby enhancing the analysis for potentially missed variants.To achieve this we implemented SVhound (https://github.com/lfpaulin/SVhound), which based on a population level SVs dataset can predict regions that harbor novel SV alleles. We tested SVhound using subsets of the 1000 genomes project data and showed that its correlation (average correlation of 2,800 tests r=0.7136) is high to the full data set. Next, we utilized SVhound to investigate potentially missed or understudied regions across 1KGP and CCDG that included multiple genes. Lastly we show the applicability for SVhound also on a small and novel SV call set for rhesus macaque (Macaca mulatta) and discuss the impact and choice of parameters for SVhound. Overall SVhound is a unique method to identify potential regions that harbor hidden diversity in model and non model organisms and can also be potentially used to ensure high quality of SV call sets.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin–angiotensin–aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies.

The COVID-19 pandemic has sparked an urgent need to uncover the underlying biology of this devastating disease. Though RNA viruses mutate more rapidly than DNA viruses, there are a relatively small number of single nucleotide polymorphisms (SNPs) that differentiate the main SARS-CoV-2 lineages that have spread throughout the world. In this study, we investigated 129 RNA-seq data sets and 6928 consensus genomes to contrast the intra-host and inter-host diversity of SARS-CoV-2. Our analyses yielded three major observations. First, the mutational profile of SARS-CoV-2 highlights intra-host single nucleotide variant (iSNV) and SNP similarity, albeit with differences in C > U changes. Second, iSNV and SNP patterns in SARS-CoV-2 are more similar to MERS-CoV than SARS-CoV-1. Third, a significant fraction of insertions and deletions contribute to the genetic diversity of SARS-CoV-2. Altogether, our findings provide insight into SARS-CoV-2 genomic diversity, inform the design of detection tests, and highlight the potential of iSNVs for tracking the transmission of SARS-CoV-2. National Institutes of Health | Ref. R01HD091731 National Institute of Allergy and Infectious Diseases | Ref. U19AI144297-01 National Aeronautics and Space Administration | Ref. NNX16AO69A European Research Council | Ref. ERC-617457-PHYLOCANCER Xunta de Galicia | Ref. CT850A-2 Ministerio de España de Economía y Competitividad | Ref. PID2019-106247GB-I00

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity and provided evidence of expression of ORF10. Heterogeneous allelic frequencies along the 20kb ORF1ab gene suggested the presence of a defective interfering viral RNA species subpopulation in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

Somatic mosaicism, manifesting as single nucleotide variants (SNVs), mobile element insertions, and structural changes in the DNA, is a common phenomenon in human brain cells, with potential functional consequences. Using a clonal approach, we previously detected 200–400 mosaic SNVs per cell in three human fetal brains (15–21 wk postconception). However, structural variation in the human fetal brain has not yet been investigated. Here, we discover and validate four mosaic structural variants (SVs) in the same brains and resolve their precise breakpoints. The SVs were of kilobase scale and complex, consisting of deletion(s) and rearranged genomic fragments, which sometimes originated from different chromosomes. Sequences at the breakpoints of these rearrangements had microhomologies, suggesting their origin from replication errors. One SV was found in two clones, and we timed its origin to ∼14 wk postconception. No large scale mosaic copy number variants (CNVs) were detectable in normal fetal human brains, suggesting that previously reported megabase-scale CNVs in neurons arise at later stages of development. By reanalysis of public single nuclei data from adult brain neurons, we detected an extrachromosomal circular DNA event. Our study reveals the existence of mosaic SVs in the developing human brain, likely arising from cell proliferation during mid-neurogenesis. Although relatively rare compared to SNVs and present in ∼10% of neurons, SVs in developing human brain affect a comparable number of bases in the genome (∼6200 vs. ∼4000 bp), implying that they may have similar functional consequences.

An increasingly important scenario in population genetics is when a large cohort has been genotyped using a low-resolution approach (e.g., microarrays, exome capture, short-read WGS), from which a few individuals are resequenced using a more comprehensive approach, especially long-read sequencing. The subset of individuals selected should ensure that the captured genetic diversity is fully representative and includes variants across all subpopulations. For example, human variation has historically focused on individuals with European ancestry, but this represents a small fraction of the overall diversity. Addressing this, SVCollector identifies the optimal subset of individuals for resequencing by analyzing population-level VCF files from low-resolution genotyping studies. It then computes a ranked list of samples that maximizes the total number of variants present within a subset of a given size. To solve this optimization problem, SVCollector implements a fast, greedy heuristic and an exact algorithm using integer linear programming. We apply SVCollector on simulated data, 2504 human genomes from the 1000 Genomes Project, and 3024 genomes from the 3000 Rice Genomes Project and show the rankings it computes are more representative than alternative naive strategies. When selecting an optimal subset of 100 samples in these cohorts, SVCollector identifies individuals from every subpopulation, whereas naive methods yield an unbalanced selection. Finally, we show the number of variants present in cohorts selected using this approach follows a power-law distribution that is naturally related to the population genetic concept of the allele frequency spectrum, allowing us to estimate the diversity present with increasing numbers of samples.

Structural variation (SV) constitutes an important type of genetic mutations providing the raw material for evolution. Here, we uncover the genome-wide spectrum of intra- and interspecific SV segregating in natural populations of seven songbird species in the genus Corvus. Combining short-read (N = 127) and long-read re-sequencing (N = 31), as well as optical mapping (N = 16), we apply both assembly- and read mapping approaches to detect SV and characterize a total of 220,452 insertions, deletions and inversions. We exploit sampling across wide phylogenetic timescales to validate SV genotypes and assess the contribution of SV to evolutionary processes in an avian model of incipient speciation. We reveal an evolutionary young (~530,000 years) cis-acting 2.25-kb LTR retrotransposon insertion reducing expression of the NDP gene with consequences for premating isolation. Our results attest to the wealth and evolutionary significance of SV segregating in natural populations and highlight the need for reliable SV genotyping., Structural genomic variation can fuel evolution. Here, authors present genome data from seven Corvus species and unearth structural variants that vary between incipient crow species in Europe, with implications for premating isolation involving plumage patterning.

Structural variants (SVs) underlie important crop improvement and domestication traits. However, resolving the extent, diversity, and quantitative impact of SVs has been challenging. We used long-read nanopore sequencing to capture 238,490 SVs in 100 diverse tomato lines. This panSV genome, along with 14 new reference assemblies, revealed large-scale intermixing of diverse genotypes, as well as thousands of SVs intersecting genes and cis-regulatory regions. Hundreds of SV-gene pairs exhibit subtle and significant expression changes, which could broadly influence quantitative trait variation. By combining quantitative genetics with genome editing, we show how multiple SVs that changed gene dosage and expression levels modified fruit flavor, size, and production. In the last example, higher order epistasis among four SVs affecting three related transcription factors allowed introduction of an important harvesting trait in modern tomato. Our findings highlight the underexplored role of SVs in genotype-to-phenotype relationships and their widespread importance and utility in crop improvement.

In less than nine months, the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) killed over a million people, including >25,000 in New York City (NYC) alone. The COVID-19 pandemic caused by SARS-CoV-2 highlights clinical needs to detect infection, track strain evolution, and identify biomarkers of disease course. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs and a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, viral, and microbial profiling. We applied these methods to clinical specimens gathered from 669 patients in New York City during the first two months of the outbreak, yielding a broad molecular portrait of the emerging COVID-19 disease. We find significant enrichment of a NYC-distinctive clade of the virus (20C), as well as host responses in interferon, ACE, hematological, and olfaction pathways. In addition, we use 50,821 patient records to find that renin–angiotensin–aldosterone system inhibitors have a protective effect for severe COVID-19 outcomes, unlike similar drugs. Finally, spatial transcriptomic data from COVID-19 patient autopsy tissues reveal distinct ACE2 expression loci, with macrophage and neutrophil infiltration in the lungs. These findings can inform public health and may help develop and drive SARS-CoV-2 diagnostic, prevention, and treatment strategies., Here, using clinical samples and autopsy tissues, the authors combine fast-colorimetric test (LAMP) for SARS-CoV-2 infection and large-scale shotgun metatranscriptomics for host, viral, and microbial profiling and provide a map of the viral genetic features of the New York City outbreak and associate specific host responses and gene expression perturbations with SARS-CoV-2 infection.

Most human genomes are characterized by aligning individual reads to the reference genome, but accurate long reads and linked reads now enable us to construct accurate, phased de novo assemblies. We focus on a medically important, highly variable, 5 million base-pair (bp) region where diploid assembly is particularly useful - the Major Histocompatibility Complex (MHC). Here, we develop a human genome benchmark derived from a diploid assembly for the openly-consented Genome in a Bottle sample HG002. We assemble a single contig for each haplotype, align them to the reference, call phased small and structural variants, and define a small variant benchmark for the MHC, covering 94% of the MHC and 22368 variants smaller than 50 bp, 49% more variants than a mapping-based benchmark. This benchmark reliably identifies errors in mapping-based callsets, and enables performance assessment in regions with much denser, complex variation than regions covered by previous benchmarks., Accurate, phased assemblies are a key tool in understanding the human genome, particularly in highly polymorphic regions like the medically important MHC. Here the authors provide an assembly-based benchmark for this difficult-to-characterize region.

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.

Genome copy number is an important source of genetic variation in health and disease. In cancer, Copy Number Alterations (CNAs) can be inferred from short-read sequencing data, enabling genomics-based precision oncology. Emerging Nanopore sequencing technologies offer the potential for broader clinical utility, for example in smaller hospitals, due to lower instrument cost, higher portability, and ease of use. Nonetheless, Nanopore sequencing devices are limited in the number of retrievable sequencing reads/molecules compared to short-read sequencing platforms, limiting CNA inference accuracy. To address this limitation, we targeted the sequencing of short-length DNA molecules loaded at optimized concentration in an effort to increase sequence read/molecule yield from a single nanopore run. We show that short-molecule nanopore sequencing reproducibly returns high read counts and allows high quality CNA inference. We demonstrate the clinical relevance of this approach by accurately inferring CNAs in acute myeloid leukemia samples. The data shows that, compared to traditional approaches such as chromosome analysis/cytogenetics, short molecule nanopore sequencing returns more sensitive, accurate copy number information in a cost effective and expeditious manner, including for multiplex samples. Our results provide a framework for short-molecule nanopore sequencing with applications in research and medicine, which includes but is not limited to, CNAs.

Improved identification of structural variants (SVs) in cancer can lead to more targeted and effective treatment options as well as advance our basic understanding of disease progression. We performed whole genome sequencing of the SKBR3 breast cancer cell-line and patient-derived tumor and normal organoids from two breast cancer patients using 10X/Illumina, PacBio, and Oxford Nanopore sequencing. We then inferred SVs and large-scale allele-specific copy number variants (CNVs) using an ensemble of methods. Our findings demonstrate that long-read sequencing allows for substantially more accurate and sensitive SV detection, with between 90% and 95% of variants supported by each long-read technology also supported by the other. We also report high accuracy for long-reads even at relatively low coverage (25x-30x). Furthermore, we inferred karyotypes from these data using our enhanced RCK algorithm to present a more accurate representation of the mutated cancer genomes, and find hundreds of variants affecting known cancer-related genes detectable only through long-read sequencing. These findings highlight the need for long-read sequencing of cancer genomes for the precise analysis of their genetic instability.

Structural variation (SV) accounts for a substantial part of genetic mutations segregating across eukaryotic genomes with important medical and evolutionary implications. Here, we characterized SV across evolutionary time scales in the songbird genus Corvus using de novo assembly and read mapping approaches. Combining information from short-read (N = 127) and long-read re-sequencing data (N = 31) as well as from optical maps (N = 16) revealed a total of 201,738 insertions, deletions and inversions. Population genetic analysis of SV in the Eurasian crow speciation model revealed an evolutionary young (~530,000 years) cis-acting 2.25-kb retrotransposon insertion reducing expression of the NDP gene with consequences for premating isolation. Our results attest to the wealth of SV segregating in natural populations and demonstrate its evolutionary significance.

The advent of inexpensive, clinical exome sequencing (ES) has led to the accumulation of genetic data from thousands of samples from individuals affected with a wide range of diseases, but for whom the underlying genetic and molecular etiology of their clinical phenotype remains unknown. In many cases, detailed phenotypes are unavailable or poorly recorded and there is little family history to guide study. To accelerate discovery, we integrated ES data from 18,696 individuals referred for suspected Mendelian disease, together with relatives, in an Apache Hadoop data lake (Hadoop Architecture Lake of Exomes [HARLEE]) and implemented a genocentric analysis that rapidly identified 154 genes harboring variants suspected to cause Mendelian disorders. The approach did not rely on case-specific phenotypic classifications but was driven by optimization of gene- and variant-level filter parameters utilizing historical Mendelian disease-gene association discovery data. Variants in 19 of the 154 candidate genes were subsequently reported as causative of a Mendelian trait and additional data support the association of all other candidate genes with disease endpoints.

We present RaGOO, a reference-guided contig ordering and orienting tool that leverages the speed and sensitivity of Minimap2 to accurately achieve chromosome-scale assemblies in minutes. After the pseudomolecules are constructed, RaGOO identifies structural variants, including those spanning sequencing gaps. We show that RaGOO accurately orders and orients 3 de novo tomato genome assemblies, including the widely used M82 reference cultivar. We then demonstrate the scalability and utility of RaGOO with a pan-genome analysis of 103 Arabidopsis thaliana accessions by examining the structural variants detected in the newly assembled pseudomolecules. RaGOO is available open source at https://github.com/malonge/RaGOO.

Accurate detection and genotyping of structural variations (SVs) from short-read data is a long-standing area of development in genomics research and clinical sequencing pipelines. We introduce Paragraph, a fast and accurate genotyper that models SVs using sequence graphs and SV annotations produced by a range of methods and technologies. We demonstrate the accuracy of Paragraph on whole genome sequence data from a control sample with both short and long read sequencing data available, and then apply it at scale to a cohort of 100 samples of diverse ancestry sequenced with short-reads. Comparative analyses indicate that Paragraph has better accuracy than other existing genotypers. The Paragraph software is open-source and available at https://github.com/Illumina/paragraph

International audience; Genome editing technologies are being widely adopted in plant breeding1. However, a looming challenge of engineering desirable genetic variation in diverse genotypes is poor predictability of phenotypic outcomes due to unforeseen interactions with pre-existing cryptic mutations2-4. In tomato, breeding with a classical MADS-box gene mutation that improves harvesting by eliminating fruit stem abscission frequently results in excessive inflorescence branching, flowering and reduced fertility due to interaction with a cryptic variant that causes partial mis-splicing in a homologous gene5-8. Here, we show that a recently evolved tandem duplication carrying the second-site variant achieves a threshold of functional transcripts to suppress branching, enabling breeders to neutralize negative epistasis on yield. By dissecting the dosage mechanisms by which this structural variant restored normal flowering and fertility, we devised strategies that use CRISPR-Cas9 genome editing to predictably improve harvesting. Our findings highlight the under-appreciated impact of epistasis in targeted trait breeding and underscore the need for a deeper characterization of cryptic variation to enable the full potential of genome editing in agriculture.

Mutation and recombination are key evolutionary processes governing phenotypic variation and reproductive isolation. We here demonstrate that biodiversity within all globally known strains of Schizosaccharomyces pombe arose through admixture between two divergent ancestral lineages. Initial hybridization was inferred to have occurred ∼20–60 sexual outcrossing generations ago consistent with recent, human-induced migration at the onset of intensified transcontinental trade. Species-wide heritable phenotypic variation was explained near-exclusively by strain-specific arrangements of alternating ancestry components with evidence for transgressive segregation. Reproductive compatibility between strains was likewise predicted by the degree of shared ancestry. To assess the genetic determinants of ancestry block distribution across the genome, we characterized the type, frequency, and position of structural genomic variation using nanopore and single-molecule real-time sequencing. Despite being associated with double-strand break initiation points, over 800 segregating structural variants exerted overall little influence on the introgression landscape or on reproductive compatibility between strains. In contrast, we found strong ancestry disequilibrium consistent with negative epistatic selection shaping genomic ancestry combinations during the course of hybridization. This study provides a detailed, experimentally tractable example that genomes of natural populations are mosaics reflecting different evolutionary histories. Exploiting genome-wide heterogeneity in the history of ancestral recombination and lineage-specific mutations sheds new light on the population history of S. pombe and highlights the importance of hybridization as a creative force in generating biodiversity.

Understanding how the genome and the epigenome work together to control gene transcription has applications in our understanding of diseases such as human cancer. In this study, we combine the ability of NOMe-seq to simultaneously evaluate CpG methylation and chromatin accessibility, with long-read nanopore sequencing technology, a method we call nanoNOMe. We generated >60Gb whole-genome nanopore sequencing data for each of four human cell lines (GM12878, MCF-10A, MCF-7, MDA-MB-231) including repetitive regions inaccessible by short read sequencing. Using the long reads, we find that we can observe phased methylation and chromatin accessibility, large scale pattern changes, and genetic changes such as structural variations from a single assay.

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.

Several new genomics technologies have become available that offer long-read sequencing or long-range mapping with higher throughput and higher resolution analysis than ever before. These long-range technologies are rapidly advancing the field with improved reference genomes, more comprehensive variant identification and more complete views of transcriptomes and epigenomes. However, they also require new bioinformatics approaches to take full advantage of their unique characteristics while overcoming their complex errors and modalities. Here, we discuss several of the most important applications of the new technologies, focusing on both the currently available bioinformatics tools and opportunities for future research.

PurposeMutations inGBAcause Gaucher disease when biallelic, and are strong risk factors for Parkinson’s disease when heterozygous.GBAanalysis is complicated by the nearby pseudogene. We aimed to design and validate a method for sequencingGBAon the Oxford Nanopore MinION.MethodsWe sequenced an 8.9 kb amplicon from DNA samples of 17 individuals, including patients with Parkinson’s and Gaucher disease, on older and current (R9.4) flow cells. These included samples with known mutations, assessed in a blinded fashion on the R9.4 data. We used NanoOK for quality metrics, two different aligners (Graphmap and NGMLR), Nanopolish and Sniffles to call variants, and Whatshap for phasing.ResultsWe detected all known mutations, including the common p.N409S (N370S) and p.L483P (L444P), and three rarer ones, at the correct zygosity, as well as intronic SNPs. In a sample with the complex RecNciI allele, we detected an additional coding mutation, and a 55-base pair deletion. We confirmed compound heterozygosity where relevant. False positives were easily identified.ConclusionThe Oxford Nanopore MinION can detect missense mutations and an exonic deletion in this difficult gene, with the added advantage of phasing and intronic analysis. It can be used as an efficient diagnostic tool.

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.

MotivationLinked reads are a form of DNA sequencing commercialized by 10X Genomics that uses highly multiplexed barcoding within microdroplets to tag short reads to progenitor molecules. The linked reads, spanning tens to hundreds of kilobases, offer an alternative to long-read sequencing for de novo assembly, haplotype phasing and other applications. However, there is no available simulator, making it difficult to measure their capability or develop new informatics tools.ResultsOur analysis of 13 real linked read datasets revealed their characteristics of barcodes, molecules and partitions. Based on this, we introduce LRSim that simulates linked reads by emulating the library preparation and sequencing process with fine control of 1) the number of simulated variants; 2) the linked-read characteristics; and 3) the Illumina reads profile. We conclude from the phasing and genome assembly of multiple datasets, recommendations on coverage, fragment length, and partitioning when sequencing human and non-human genome.AvailabilityLRSIM is under MIT license and is freely available at https://github.com/aquaskyline/LRSIMContactrluo5@jhu.edu