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Detailed summary of HPV16 genome somatic single nucleotide variations identified by targeted capture sequencing analysis of FFPE tumor specimens

Detailed summary of HPV16 genome somatic INDELs identified by targeted capture sequencing analysis of FFPE tumor specimens

Purpose:In locally advanced p16+ oropharyngeal squamous cell carcinoma (OPSCC), (i) to investigate kinetics of human papillomavirus (HPV) circulating tumor DNA (ctDNA) and association with tumor progression after chemoradiation, and (ii) to compare the predictive value of ctDNA to imaging biomarkers of MRI and FDG-PET.Experimental Design:Serial blood samples were collected from patients with AJCC8 stage III OPSCC (n = 34) enrolled on a randomized trial: pretreatment; during chemoradiation at weeks 2, 4, and 7; and posttreatment. All patients also had dynamic-contrast-enhanced and diffusion-weighted MRI, as well as FDG-PET scans pre-chemoradiation and week 2 during chemoradiation. ctDNA values were analyzed for prediction of freedom from progression (FFP), and correlations with aggressive tumor subvolumes with low blood volume (TVLBV) and low apparent diffusion coefficient (TVLADC), and metabolic tumor volume (MTV) using Cox proportional hazards model and Spearman rank correlation.Results:Low pretreatment ctDNA and an early increase in ctDNA at week 2 compared with baseline were significantly associated with superior FFP (P < 0.02 and P < 0.05, respectively). At week 4 or 7, neither ctDNA counts nor clearance were significantly predictive of progression (P = 0.8). Pretreatment ctDNA values were significantly correlated with nodal TVLBV, TVLADC, and MTV pre-chemoradiation (P < 0.03), while the ctDNA values at week 2 were correlated with these imaging metrics in primary tumor. Multivariate analysis showed that ctDNA and the imaging metrics performed comparably to predict FFP.Conclusions:Early ctDNA kinetics during definitive chemoradiation may predict therapy response in stage III OPSCC.

Tumor somatic alterations defined by targeted capture sequencing. (A)Using this capture probe panel, we obtained an average of 8,121,723 sequencing reads per tumor (range: 3,068,132 - 13,084,648), which corresponded to a minimum coverage of >1000x per base targeted in all samples as detailed in Supplemental Table 1. Somatic alteration analysis identified an average of 4.1 mutations and INDELs per tumor (range 0 - 28, of 226 genes tested)). As shown in the oncoplot, while several commonly altered HNSCC genes were identified, we also observed several interesting mutations in DNA damage repair proteins, including three mutations in ATM (R2419G, G1023E and a splice region alteration), ATRX (L532F), BRCA1 (stopgain) and BRCA2 (frameshift alteration). Four of 5 patients harboring these mutations experienced tumor progression. (B) The level of microhomology (in bp) at the breakpoint is numerically depicted. Number of overlapping nucleotides between HPV and host (indicating microhomology) are indicated as positive numbers, 0 indicates a clean break between HPV and host with no overlapping or inserted sequence, and negative numbers indicate the number of inserted base pairs between the HPV and host genome.

DNA extraction from plasma, Droplet Digital PCR for HPV ctDNA Analysis, Host genome mutation and INDEL Analysis,DNA isolation from Tumor Tissue. tumor NGS

Next generation sequencing quality control data, HPViewer read counts and somatic alteration burden

Detailed summary of host genome somatic single nucleotide variations identified by targeted capture sequencing analysis of FFPE tumor specimens

Detailed summary of host genome somatic INDELs identified by targeted capture sequencing analysis of FFPE tumor specimens

Number of plasma samples analyzed at each time point

Legends for supplementary figure and tables

Detailed summary of HPV to host genome integration sites identified by targeted capture sequencing analysis of FFPE tumor specimens

The transfer of mitochondrial DNA into the nuclear genomes of eukaryotes (Numts) has been linked to lifespan in non-human species1–3and recently demonstrated to occur in rare instances from one human generation to the next4. Here we investigated numtogenesis dynamics in humans in two ways. First, we quantified Numts in 1,187 post-mortem brain and blood samples from different individuals. Compared to circulating immune cells (n=389), post-mitotic brain tissue (n=798) contained more Numts, consistent with their potential somatic accumulation. Within brain samples we observed a 5.5-fold enrichment of somatic Numt insertions in the dorsolateral prefrontal cortex compared to cerebellum samples, suggesting that brain Numts arose spontaneously during development or across the lifespan. Moreover, more brain Numts was linked to earlier mortality. The brains of individuals with no cognitive impairment who died at younger ages carried approximately 2 more Numts per decade of life lost than those who lived longer. Second, we tested the dynamic transfer of Numts using a repeated-measures WGS design in a human fibroblast model that recapitulates several molecular hallmarks of aging5. These longitudinal experiments revealed a gradual accumulation of one Numt every ∼13 days. Numtogenesis was independent of large-scale genomic instability and unlikely driven cell clonality. Targeted pharmacological perturbations including chronic glucocorticoid signaling or impairing mitochondrial oxidative phosphorylation (OxPhos) only modestly increased the rate of numtogenesis, whereas patient-derivedSURF1-mutant cells exhibiting mtDNA instability accumulated Numts 4.7- fold faster than healthy donors. Combined, our data document spontaneous numtogenesis in human cells and demonstrate an association between brain cortical somatic Numts and human lifespan. These findings open the possibility that mito-nuclear horizontal gene transfer among human post-mitotic tissues produce functionally-relevant human Numts over timescales shorter than previously assumed.

Candida albicansis a frequent colonizer of human mucosal surfaces as well as an opportunistic pathogen.C. albicansis remarkably versatile in its ability to colonize diverse host sites with differences in oxygen and nutrient availability, pH, immune responses, and resident microbes, among other cues. It is unclear how the genetic background of a commensal colonizing population can influence the shift to pathogenicity. Therefore, we undertook an examination of commensal isolates from healthy donors with a goal of identifying site-specific phenotypic adaptation and genetic variation associated with these phenotypes. We demonstrate that healthy people are reservoirs for genotypically and phenotypically diverseC. albicansstrains, and that this genetic diversity includes both SNVs and structural rearrangements. Using limited diversity exploitation, we identified a single nucleotide change in the uncharacterizedZMS1transcription factor that was sufficient to drive hyper invasion into agar. However, our commensal strains retained the capacity to cause disease in systemic models of infection, including outcompeting the SC5314 reference strain during systemic competition assays. This study provides a global view of commensal strain variation and within-host strain diversity ofC. albicansand suggests that selection for commensalism in humans does not result in a fitness cost for invasive disease.

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and medical genetic initiatives are reliant upon short-read whole-genome sequencing (srWGS), which presents challenges for the detection of structural variants (SVs) relative to emerging long-read WGS (lrWGS) technologies. Given this ubiquity of srWGS in large-scale genomics initiatives, we sought to establish expectations for routine SV detection from this data type by comparison with lrWGS assembly, as well as to quantify the genomic properties and added value of SVs uniquely accessible to each technology. Analyses from the Human Genome Structural Variation Consortium (HGSVC) of three families captured ~11,000 SVs per genome from srWGS and ~25,000 SVs per genome from lrWGS assembly. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplication (SD) and simple repeat (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of reference sequence, we observed extremely high (93.8%) concordance between technologies for deletions in these datasets. In contrast, lrWGS was superior for detection of insertions across all genomic contexts. Given that non-SD/SR sequences encompass 95.9% of currently annotated disease-associated exons, improved sensitivity from lrWGS to discover novel pathogenic deletions in these currently interpretable genomic regions is likely to be incremental. However, these analyses highlight the considerable added value of assembly-based lrWGS to create new catalogs of insertions and transposable elements, as well as disease-associated repeat expansions in genomic sequences that were previously recalcitrant to routine assessment.

Candida albicans is a frequent colonizer of human mucosal surfaces as well as an opportunistic pathogen. C. albicans is remarkably versatile in its ability to colonize diverse host sites with differences in oxygen and nutrient availability, pH, immune responses, and resident microbes, among other cues. It is unclear how the genetic background of a commensal colonizing population can influence the shift to pathogenicity. Therefore, we examined 910 commensal isolates from 35 healthy donors to identify host niche-specific adaptations. We demonstrate that healthy people are reservoirs for genotypically and phenotypically diverse C. albicans strains. Using limited diversity exploitation, we identified a single nucleotide change in the uncharacterized ZMS1 transcription factor that was sufficient to drive hyper invasion into agar. We found that SC5314 was significantly different from the majority of both commensal and bloodstream isolates in its ability to induce host cell death. However, our commensal strains retained the capacity to cause disease in the Galleria model of systemic infection, including outcompeting the SC5314 reference strain during systemic competition assays. This study provides a global view of commensal strain variation and within-host strain diversity of C. albicans and suggests that selection for commensalism in humans does not result in a fitness cost for invasive disease.

Germline copy number variants (CNVs) and single-nucleotide polymorphisms (SNPs) form the basis of inter-individual genetic variation. Although the phenotypic effects of SNPs have been extensively investigated, the effects of CNVs is relatively less understood. To better characterize mechanisms by which CNVs affect cellular phenotype, we tested their association with variable CpG methylation in a genome-wide manner. Using paired CNV and methylation data from the 1000 genomes and HapMap projects, we identified genome-wide associations by methylation quantitative trait locus (mQTL) analysis. We found individual CNVs being associated with methylation of multiple CpGs and vice versa. CNV-associated methylation changes were correlated with gene expression. CNV-mQTLs were enriched for regulatory regions, transcription factor-binding sites (TFBSs), and were involved in long-range physical interactions with associated CpGs. Some CNV-mQTLs were associated with methylation of imprinted genes. Several CNV-mQTLs and/or associated genes were among those previously reported by genome-wide association studies (GWASs). We demonstrate that germline CNVs in the genome are associated with CpG methylation. Our findings suggest that structural variation together with methylation may affect cellular phenotype.

HPV positive Oropharyngeal Squamous Cell Carcinoma (HPV positive OPSCC) is rising in incidence and, for patients that recur, survival is extremely poor. Recent technological advances have led to a better understanding of patterns of HPV integration in primary tumors but have not yet tested the evolution of these events in deadly forms of the disease. Therefore, we performed multi-region sequencing analysis on a cohort of 34 recurrent and metastatic patients with HPV positive OPSCC (29% survival rate) plus one recurrent HPV positive model pair, UPCI-90 and UPCI-152. We then used our recently developed capture-based sequencing HPV integration caller and assembler pipeline, SearcHPV, to identify patterns of viral integration into the host genome and Oxford Nanopore long-read whole genome sequencing to validate the integration events in selected cases. In total, 1591 HPV integrations were called and assembled. Unexpectedly, our analysis revealed that HPV integration events are heterogenous as multiple independent integration events were observed in different spatial regions of the same tumor. Further, when comparing independent and anatomically distinct regions of recurrence from the same patient, independent integration events were also observed. Heterogeneity of integration structures was found to include variation of local HPV copy number, distribution of the specific HPV integration sites within the structures as well as distinct characteristics of rearrangement breakpoints (human-HPV, HPV-HPV, human-human). Given this observation, we then evaluated the hypothesis that HPV integration events could be clonally selected by comparing the integration profiles from a cohort of matched primary and recurrent tumors. In this cohort, 64 integration events (11 exact same; 53 clustered in the same genes) were maintained throughout tumor progression to recurrence, while other integration events were lost, supporting a model of clonal evolution with driver and passenger integrations. We then explored this further using one recurrent HPV positive model pair, UPCI-90 and UPCI-152, using long-read whole genome sequencing which validated the heterogeneity and clonal selection of HPV integration events. Finally, to test if differences in HPV integration content in spatially distinct regions could drive spatially distinct phenotypic differences, we performed multi-region RNA-seq analysis on 8 HPV16 positive OPSCCs, which demonstrated spatial differences in HPV16 E7 expression, that were validated with RNAscope assays, as well as statistically significant spatial enrichment of independent oncogenic gene sets. Collectively, we report evidence showing that HPV integration events are heterogenous, clonally selected during progression and associated with distinct transcriptomic profiles. Based on this data, we now propose a new working model of disease pathogenesis in which heterogeneity and clonal evolution of HPV integration events serve as a critical driver of the disease process. Citation Format: Wenjin Gu, Apurva Bhangale, Collin V. Brummel, Elizabeth Gensterblum-Miller, Matthew E. Spector, Ryan E. Mills, Chad Brenner. HPV integration events are heterogenous, clonally selected and associated with spatially distinct transcriptomic profiles in aggressive HPV positive oropharyngeal squamous cell carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr LB252.

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

Purpose: In locally advanced p16+ oropharyngeal squamous cell carcinoma (OPSCC), (i) to investigate kinetics of human papillomavirus (HPV) circulating tumor DNA (ctDNA) and association with tumor progression after chemoradiation, and (ii) to compare the predictive value of ctDNA to imaging biomarkers of MRI and FDG-PET. Experimental Design: Serial blood samples were collected from patients with AJCC8 stage III OPSCC (n = 34) enrolled on a randomized trial: pretreatment; during chemoradiation at weeks 2, 4, and 7; and posttreatment. All patients also had dynamic-contrast-enhanced and diffusion-weighted MRI, as well as FDG-PET scans pre-chemoradiation and week 2 during chemoradiation. ctDNA values were analyzed for prediction of freedom from progression (FFP), and correlations with aggressive tumor subvolumes with low blood volume (TVLBV) and low apparent diffusion coefficient (TVLADC), and metabolic tumor volume (MTV) using Cox proportional hazards model and Spearman rank correlation. Results: Low pretreatment ctDNA and an early increase in ctDNA at week 2 compared with baseline were significantly associated with superior FFP (P < 0.02 and P < 0.05, respectively). At week 4 or 7, neither ctDNA counts nor clearance were significantly predictive of progression (P = 0.8). Pretreatment ctDNA values were significantly correlated with nodal TVLBV, TVLADC, and MTV pre-chemoradiation (P < 0.03), while the ctDNA values at week 2 were correlated with these imaging metrics in primary tumor. Multivariate analysis showed that ctDNA and the imaging metrics performed comparably to predict FFP. Conclusions: Early ctDNA kinetics during definitive chemoradiation may predict therapy response in stage III OPSCC.

Identifying structural variation (SV) is essential for genome interpretation but has been historically difficult due to limitations inherent to available genome technologies. Detection methods that use ensemble algorithms and emerging sequencing technologies have enabled the discovery of thousands of SVs, uncovering information about their ubiquity, relationship to disease and possible effects on biological mechanisms. Given the variability in SV type and size, along with unique detection biases of emerging genomic platforms, multiplatform discovery is necessary to resolve the full spectrum of variation. Here, we review modern approaches for investigating SVs and proffer that, moving forwards, studies integrating biological information with detection will be necessary to comprehensively understand the impact of SV in the human genome. To map the full extent of structural variation in the human genome, detection methods are needed that improve on short-read approaches. This Review discusses how ensemble algorithms and emerging sequencing technologies are helping to resolve the full spectrum of structural variations.

Significance Long interspersed element-1s (L1s) encode 2 proteins (ORF1p and ORF2p) that preferentially mobilize (i.e., retrotranspose) their encoding messenger RNA (mRNA) transcript. ORF1p and/or ORF2p can also mobilize other cellular RNAs, including short interspersed elements (SINEs), U6 small nuclear RNA (snRNA), and mRNAs. Here, we demonstrate the RNA ligase RtcB can join U6 snRNA to L1 or other cellular RNAs to create chimeric RNAs; retrotransposition of the resultant chimeric RNAs leads to chimeric pseudogene formation; and chimeric U6/L1 RNAs are part of the transcriptome in multiple human cells. These data suggest RNA ligation contributes to the plasticity of the transcriptome and that the retrotransposition of chimeric RNAs can generate genetic variation in the human genome., Long interspersed element-1 (LINE-1 or L1) amplifies via retrotransposition. Active L1s encode 2 proteins (ORF1p and ORF2p) that bind their encoding transcript to promote retrotransposition in cis. The L1-encoded proteins also promote the retrotransposition of small-interspersed element RNAs, noncoding RNAs, and messenger RNAs in trans. Some L1-mediated retrotransposition events consist of a copy of U6 RNA conjoined to a variably 5′-truncated L1, but how U6/L1 chimeras are formed requires elucidation. Here, we report the following: The RNA ligase RtcB can join U6 RNAs ending in a 2′,3′-cyclic phosphate to L1 RNAs containing a 5′-OH in vitro; depletion of endogenous RtcB in HeLa cell extracts reduces U6/L1 RNA ligation efficiency; retrotransposition of U6/L1 RNAs leads to U6/L1 pseudogene formation; and a unique cohort of U6/L1 chimeric RNAs are present in multiple human cell lines. Thus, these data suggest that U6 small nuclear RNA (snRNA) and RtcB participate in the formation of chimeric RNAs and that retrotransposition of chimeric RNA contributes to interindividual genetic variation.

Background & Aims African American and European American individuals have a similar prevalence of gastroesophageal reflux disease (GERD), yet esophageal adenocarcinoma (EAC) disproportionately affects European American individuals. We investigated whether the esophageal squamous mucosa of African American individuals has features that protect against GERD-induced damage, compared with European American individuals. Methods We performed transcriptional profile analysis of esophageal squamous mucosa tissues from 20 African American and 20 European American individuals (24 with no disease and 16 with Barrett's esophagus and/or EAC). We confirmed our findings in a cohort of 56 patients and analyzed DNA samples from patients to identify associated variants. Observations were validated using matched genomic sequence and expression data from lymphoblasts from the 1000 Genomes Project. A panel of esophageal samples from African American and European American subjects was used to confirm allele-related differences in protein levels. The esophageal squamous-derived cell line Het-1A and a rat esophagogastroduodenal anastomosis model for reflux-generated esophageal damage were used to investigate the effects of the DNA-damaging agent cumene-hydroperoxide (cum-OOH) and a chemopreventive cranberry proanthocyanidin (C-PAC) extract, respectively, on levels of protein and messenger RNA (mRNA). Results We found significantly higher levels of glutathione S-transferase theta 2 (GSTT2) mRNA in squamous mucosa from African American compared with European American individuals and associated these with variants within the GSTT2 locus in African American individuals. We confirmed that 2 previously identified genomic variants at the GSTT2 locus, a 37-kb deletion and a 17-bp promoter duplication, reduce expression of GSTT2 in tissues from European American individuals. The nonduplicated 17-bp promoter was more common in tissue samples from populations of African descendant. GSTT2 protected Het-1A esophageal squamous cells from cum-OOH–induced DNA damage. Addition of C-PAC increased GSTT2 expression in Het-1A cells incubated with cum-OOH and in rats with reflux-induced esophageal damage. C-PAC also reduced levels of DNA damage in reflux-exposed rat esophagi, as observed by reduced levels of phospho-H2A histone family member X. Conclusions We found GSTT2 to protect esophageal squamous cells against DNA damage from genotoxic stress and that GSTT2 expression can be induced by C-PAC. Increased levels of GSTT2 in esophageal tissues of African American individuals might protect them from GERD-induced damage and contribute to the low incidence of EAC in this population.

BackgroundHuman papillomavirus (HPV) is a well-established driver of malignant transformation in a number of sites including head and neck, cervical, vulvar, anorectal and penile squamous cell carcinomas; however, the impact of HPV integration into the host human genome on this process remains largely unresolved. This is due to the technical challenge of identifying HPV integration sites, which includes limitations of existing informatics approaches to discover viral-host breakpoints from low read coverage sequencing data.MethodsTo overcome this limitation, we developed a new HPV detection pipeline called SearcHPV based on targeted capture technology and applied the algorithm to targeted capture data. We performed an integrated analysis of SearcHPV-defined breakpoints with genome-wide linked read sequencing to identify potential HPV-related structural variations.ResultsThrough analysis of HPV+ models, we show that SearcHPV detects HPV-host integration sites with a higher sensitivity and specificity than two other commonly used HPV detection callers. SearcHPV uncovered HPV integration sites adjacent to known cancer-related genes including TP63 and MYC, as well as near regions of large structural variation. We further validated the junction contig assembly feature of SearcHPV, which helped to accurately identify viral-host junction breakpoint sequences. We found that viral integration occurred through a variety of DNA repair mechanisms including non-homologous end joining, alternative end joining and microhomology mediated repair.ConclusionsIn summary, we show that SearcHPV is a new optimized tool for the accurate detection of HPV-human integration sites from targeted capture DNA sequencing data.

Oxford Nanopore sequencers provide results in real time as DNA passes through a nanopore and can eject a molecule after it has been partly sequenced. However, the computational challenge of deciding whether to keep or reject a molecule in real time has limited the application of this capability. We present SquiggleNet, the first deep learning model that can classify nanopore reads directly from their electrical signals. SquiggleNet operates faster than the DNA passes through the pore, allowing real-time classification and read ejection. When given the amount of sequencing data generated in one second, the classifier achieves significantly higher accuracy than base calling followed by sequence alignment. Our approach is also faster and requires an order of magnitude less memory than approaches based on alignment. SquiggleNet distinguished human from bacterial DNA with over 90% accuracy, generalized to unseen species, identified bacterial species in a human respiratory meta genome sample, and accurately classified sequences containing human long interspersed repeat elements.

Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent–child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average contig N50: 26 Mbp) integrate all forms of genetic variation across even complex loci such as the major histocompatibility complex. We focus on 107,590 structural variants (SVs), of which 68% are inaccessible by short-read sequencing. We identify new SV hotspots (spanning megabases of gene-rich sequence), characterize 130 of the most active mobile element source elements, and find that 63% of all SVs arise by homology-mediated mechanisms—a twofold increase from previous studies. Our resource now enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1,525 expression quantitative trait loci (SV-eQTLs) as well as SV candidates for adaptive selection within the human population.

Resolving genomic structural variationMany human genomes have been reported using short-read technology, but it is difficult to resolve structural variants (SVs) using these data. These genomes thus lack comprehensive comparisons among individuals and populations. Ebertet al.used long-read structural variation calling across 64 human genomes representing diverse populations and developed new methods for variant discovery. This approach allowed the authors to increase the number of confirmed SVs and to describe the patterns of variation across populations. From this dataset, they identified quantitative trait loci affected by these SVs and determined how they may affect gene expression and potentially explain genome-wide association study hits. This information provides insights into patterns of normal human genetic variation and generates reference genomes that better represent the diversity of our species.Science, this issue p.eabf7117

Post-zygotic mutations incurred during DNA replication, DNA repair, and other cellular processes lead to somatic mosaicism. Somatic mosaicism is an established cause of various diseases, including cancers. However, detecting mosaic variants in DNA from non-cancerous somatic tissues poses significant challenges, particularly if the variants only are present in a small fraction of cells. Here, the Brain Somatic Mosaicism Network conducted a coordinated, multi-institutional study to: (i) examine the ability of existing methods to detect simulated somatic single nucleotide variants (SNVs) in DNA mixing experiments; (ii) generate multiple replicates of whole genome sequencing data from the dorsolateral prefrontal cortex, other brain regions, dura mater, and dural fibroblasts of a single neurotypical individual; (iii) devise strategies to discover somatic SNVs; and (iv) apply various approaches to validate somatic SNVs. These efforts led to the identification of 43 bona fide somatic SNVs that ranged in variant allele fractions from ~0.005 to ~0.28. Guided by these results, we devised best practices for calling mosaic SNVs from 250X whole genome sequencing data in the accessible portion of the human genome that achieve 90% specificity and sensitivity. Finally, we demonstrated that analysis of multiple bulk DNA samples from a single individual allows the reconstruction of early developmental cell lineage trees. Thus, this study provides a unified set of best practices to detect somatic SNVs in non-cancerous tissues. The data and methods are freely available to the scientific community and should serve as a guide to assess the contributions of somatic SNVs to neuropsychiatric diseases.

The main goal of this collaborative effort is to provide genome wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for the public data release. DNBSEQ-G50 sequences, and genotypes by an Illumina GWAS chip were cross-validated on multiple samples, and additionally referenced to one sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage. The genome data has been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, CNVs, SNPs and microsatellites. This study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for historic and medical research in a large understudied population. While most of the common variation is shared with other European populations, this survey of population variation contributes a number of novel SNPs and structural variants that have not been reported in the gnomAD/1KG databases representing global distribution of genomic variation. These endemic variants will become a valuable resource for designing future population and clinical studies, help address questions about ancestry and admixture, and will fill a missing place in the puzzle characterizing human population diversity in Eastern Europe. Our results indicate that genetic diversity of the Ukrainian population is uniquely shaped by the evolutionary and demographic forces, and cannot be ignored in the future genetic and biomedical studies. This data will contribute a wealth of new information bringing forth different risk and/or protective alleles. The newly discovered low frequency and local variants can be added to the current genotyping arrays for genome wide association studies, clinical trials, and in genome assessment of proliferating cancer cells.

BackgroundThe main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage.ResultsThe genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population.ConclusionsOur results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.

Virtually all genome sequencing efforts in national biobanks, complex and Mendelian disease programs, and emerging clinical diagnostic approaches utilize short-reads (srWGS), which present constraints for genome-wide discovery of structural variants (SVs). Alternative long-read single molecule technologies (lrWGS) offer significant advantages for genome assembly and SV detection, while these technologies are currently cost prohibitive for large-scale disease studies and clinical diagnostics (∼5-12X higher cost than comparable coverage srWGS). Moreover, only dozens of such genomes are currently publicly accessible by comparison to millions of srWGS genomes that have been commissioned for international initiatives. Given this ubiquitous reliance on srWGS in human genetics and genomics, we sought to characterize and quantify the properties of SVs accessible to both srWGS and lrWGS to establish benchmarks and expectations in ongoing medical and population genetic studies, and to project the added value of SVs uniquely accessible to each technology. In analyses of three trios with matched srWGS and lrWGS from the Human Genome Structural Variation Consortium (HGSVC), srWGS captured ∼11,000 SVs per genome using reference-based algorithms, while haplotype-resolved assembly from lrWGS identified ∼25,000 SVs per genome. Detection power and precision for SV discovery varied dramatically by genomic context and variant class: 9.7% of the current GRCh38 reference is defined by segmental duplications (SD) and simple repeats (SR), yet 91.4% of deletions that were specifically discovered by lrWGS localized to these regions. Across the remaining 90.3% of the human reference, we observed extremely high concordance (93.8%) for deletions discovered by srWGS and lrWGS after error correction using the raw lrWGS reads. Conversely, lrWGS was superior for detection of insertions across all genomic contexts. Given that the non-SD/SR sequences span 90.3% of the GRCh38 reference, and encompass 95.9% of coding exons in currently annotated disease associated genes, improved sensitivity from lrWGS to discover novel and interpretable pathogenic deletions not already accessible to srWGS is likely to be incremental. However, these analyses highlight the added value of assembly-based lrWGS to create new catalogues of functional insertions and transposable elements, as well as disease associated repeat expansions in genomic regions previously recalcitrant to routine assessment.

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed a sequence-resolved benchmark set for identification of both false-negative and false-positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12,745 isolated, sequence-resolved insertion (7,281) and deletion (5,464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5,262 insertions and 4,095 deletions supported by ≥1 diploid assembly. We demonstrate that the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked- and long-read sequencing and optical mapping.

The transfer and integration of whole and partial mitochondrial genomes into the nuclear genomes of eukaryotes is an ongoing process that has facilitated the transfer of genes and contributed to the evolution of various cellular pathways. Many previous studies have explored the impact of these insertions, referred to as NumtS, but have focused primarily on older events that have become fixed and are therefore present in all individual genomes for a given species. We previously developed an approach to identify novel Numt polymorphisms from next-generation sequence data and applied it to thousands of human genomes. Here, we extend this analysis to 79 individuals of other great ape species including chimpanzee, bonobo, gorilla, orang-utan and also an old world monkey, macaque. We show that recent Numt insertions are prevalent in each species though at different apparent rates, with chimpanzees exhibiting a significant increase in both polymorphic and fixed Numt sequences as compared to other great apes. We further assessed positional effects in each species in terms of evolutionary time and rate of insertion and identified putative hotspots on chromosome 5 for Numt integration, providing insight into both recent polymorphic and older fixed reference NumtS in great apes in comparison to human events. Funding: National Institutes of Health (1R01HG007068-01A1 to R.E.M). T.M.B is supported by funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 864203), BFU2017-86471-P (MINECO/FEDER, UE), “Unidad de Excelencia María de Maeztu”, funded by the AEI (CEX2018-000792-M), Howard Hughes International Early Career, Obra Social "La Caixa" and Secretaria d’Universitats i Recerca and CERCA Programme del Departament d’Economia i Coneixement de la Generalitat de Catalunya (GRC 2017 SGR 880)

Long Interspersed Element-1 (LINE-1) retrotransposition contributes to inter- and intra-individual genetic variation and occasionally can lead to human genetic disorders. Various strategies have been developed to identify human-specific LINE-1 (L1Hs) insertions from short-read whole genome sequencing (WGS) data; however, they have limitations in detecting insertions in complex repetitive genomic regions. Here, we developed a computational tool (PALMER) and used it to identify 203 non-reference L1Hs insertions in the NA12878 benchmark genome. Using PacBio long-read sequencing data, we identified L1Hs insertions that were absent in previous short-read studies (90/203). Approximately 81% (73/90) of the L1Hs insertions reside within endogenous LINE-1 sequences in the reference assembly and the analysis of unique breakpoint junction sequences revealed 63% (57/90) of these L1Hs insertions could be genotyped in 1000 Genomes Project sequences. Moreover, we observed that amplification biases encountered in single-cell WGS experiments led to a wide variation in L1Hs insertion detection rates between four individual NA12878 cells; under-amplification limited detection to 32% (65/203) of insertions, whereas over-amplification increased false positive calls. In sum, these data indicate that L1Hs insertions are often missed using standard short-read sequencing approaches and long-read sequencing approaches can significantly improve the detection of L1Hs insertions present in individual genomes.

BackgroundMultiple myeloma (MM) is a hematological cancer caused by abnormal accumulation of monoclonal plasma cells in bone marrow. With the increase in treatment options, risk-adapted therapy is becoming more and more important. Survival analysis is commonly applied to study progression or other events of interest and stratify the risk of patients.ResultsIn this study, we present the current state-of-the-art model for MM prognosis and the molecular biomarker set for stratification: the winning algorithm in the 2017 Multiple Myeloma DREAM Challenge, Sub-Challenge 3. Specifically, we built a non-parametric complete hazard ranking model to map the right-censored data into a linear space, where commonplace machine learning techniques, such as Gaussian process regression and random forests, can play their roles. Our model integrated both the gene expression profile and clinical features to predict the progression of MM. Compared with conventional models, such as Cox model and random survival forests, our model achieved higher accuracy in 3 within-cohort predictions. In addition, it showed robust predictive power in cross-cohort validations. Key molecular signatures related to MM progression were identified from our model, which may function as the core determinants of MM progression and provide important guidance for future research and clinical practice. Functional enrichment analysis and mammalian gene-gene interaction network revealed crucial biological processes and pathways involved in MM progression. The model is dockerized and publicly available at https://www.synapse.org/#!Synapse:syn11459638. Both data and reproducible code are included in the docker.ConclusionsWe present the current state-of-the-art prognostic model for MM integrating gene expression and clinical features validated in an independent test set.

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. To help translate these methods to routine research and clinical practice, we developed the first sequence-resolved benchmark set for identification of both false negative and false positive germline large insertions and deletions. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods from diverse technologies. The final benchmark set contains 12745 isolated, sequence-resolved insertion (7281) and deletion (5464) calls ≥50 base pairs (bp). The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.51 Gbp and 5262 insertions and 4095 deletions supported by ≥1 diploid assembly. We demonstrate the benchmark set reliably identifies false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping.

New technologies and analysis methods are enabling genomic structural variants (SVs) to be detected with ever-increasing accuracy, resolution, and comprehensiveness. Translating these methods to routine research and clinical practice requires robust benchmark sets. We developed the first benchmark set for identification of both false negative and false positive germline SVs, which complements recent efforts emphasizing increasingly comprehensive characterization of SVs. To create this benchmark for a broadly consented son in a Personal Genome Project trio with broadly available cells and DNA, the Genome in a Bottle (GIAB) Consortium integrated 19 sequence-resolved variant calling methods, both alignment- and de novo assembly-based, from short-, linked-, and long-read sequencing, as well as optical and electronic mapping. The final benchmark set contains 12745 isolated, sequence-resolved insertion and deletion calls ≥50 base pairs (bp) discovered by at least 2 technologies or 5 callsets, genotyped as heterozygous or homozygous variants by long reads. The Tier 1 benchmark regions, for which any extra calls are putative false positives, cover 2.66 Gbp and 9641 SVs supported by at least one diploid assembly. Support for SVs was assessed using svviz with short-, linked-, and long-read sequence data. In general, there was strong support from multiple technologies for the benchmark SVs, with 90% of the Tier 1 SVs having support in reads from more than one technology. The Mendelian genotype error rate was 0.3%, and genotype concordance with manual curation was >98.7%. We demonstrate the utility of the benchmark set by showing it reliably identifies both false negatives and false positives in high-quality SV callsets from short-, linked-, and long-read sequencing and optical mapping. GIAB is working towards a new version of the benchmark set that will use new technologies and methods such as PacBio Circular Consensus Sequencing and ultralong Oxford Nanopore sequencing to expand to more challenging genome regions and include more challenging SVs such as inversions. We are also developing a robust integration process to make calls on GRCh37 and GRCh38 for all seven GIAB samples.

Background Upstream open reading frames (uORFs) initiate translation within mRNA 5′ leaders, and have the potential to alter main coding sequence (CDS) translation on transcripts in which they reside. Ribosome profiling (RP) studies suggest that translating ribosomes are pervasive within 5′ leaders across model systems. However, the significance of this observation remains unclear. To explore a role for uORF usage in a model of neuronal differentiation, we performed RP on undifferentiated and differentiated human neuroblastoma cells. Results Using a spectral coherence algorithm (SPECtre), we identify 4954 consistently translated uORFs across 31% of all neuroblastoma transcripts. These uORFs predominantly utilize non-AUG initiation codons and exhibit translational efficiencies (TE) comparable to annotated coding regions. On a population basis, the global impact of both AUG and non-AUG initiated uORFs on basal CDS translation were small, even when analysis is limited to conserved and consistently translated uORFs. However, uORFs did alter the translation of a subset of genes, including the Diamond-Blackfan Anemia associated ribosomal gene RPS24. With retinoic acid induced differentiation, we observed an overall positive correlation in translational shifts between uORF/CDS pairs. However, CDSs downstream of uORFs show smaller shifts in TE with differentiation relative to CDSs without a predicted uORF, suggesting that uORF translation buffers cell state dependent fluctuations in CDS translation. Conclusion This work provides insights into the dynamic relationships and potential regulatory functions of uORF/CDS pairs in a model of neuronal differentiation. Electronic supplementary material The online version of this article (10.1186/s12864-019-5775-1) contains supplementary material, which is available to authorized users.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (, Structural variants (SVs) in human genomes contribute diversity and diseases. Here, the authors use a multi-platform strategy to generate haplotype-resolved SVs for three human parent–child trios.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, and strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three human parent–child trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (