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The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines identified a previously undescribed form of structural variation, “heterocateny,” characterized by diverse, interrelated, and repetitive patterns of concatemerized virus and host DNA segments within a cancer. Unique breakpoints shared across structural variants facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that virus and virus–host concatemers are unstable and, upon insertion into and excision from chromosomes, facilitate capture, amplification, and recombination of host DNA and chromosomal rearrangements. Evidence of heterocateny was detected in extrachromosomal and intrachromosomal DNA. These findings indicate that heterocateny is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intratumoral heterogeneity and clonal evolution. Significance: Long-read sequencing of HPV-positive cancers revealed “heterocateny,” a previously unreported form of genomic structural variation characterized by heterogeneous, interrelated, and repetitive genomic rearrangements within a tumor. Heterocateny is driven by unstable concatemerized HPV genomes, which facilitate capture, rearrangement, and amplification of host DNA, and promotes intratumoral heterogeneity and clonal evolution. See related commentary by McBride and White, p. 814. This article is highlighted in the In This Issue feature, p. 799

The human papillomavirus (HPV) genome is integrated into host DNA in most HPV-positive cancers, but the consequences for chromosomal integrity are unknown. Continuous long-read sequencing of oropharyngeal cancers and cancer cell lines identified a previously undescribed form of structural variation, “heterocateny,” characterized by diverse, interrelated, and repetitive patterns of concatemerized virus and host DNA segments within a cancer. Unique breakpoints shared across structural variants facilitated stepwise reconstruction of their evolution from a common molecular ancestor. This analysis revealed that virus and virus–host concatemers are unstable and, upon insertion into and excision from chromosomes, facilitate capture, amplification, and recombination of host DNA and chromosomal rearrangements. Evidence of heterocateny was detected in extrachromosomal and intrachromosomal DNA. These findings indicate that heterocateny is driven by the dynamic, aberrant replication and recombination of an oncogenic DNA virus, thereby extending known consequences of HPV integration to include promotion of intratumoral heterogeneity and clonal evolution.Significance:Long-read sequencing of HPV-positive cancers revealed “heterocateny,” a previously unreported form of genomic structural variation characterized by heterogeneous, interrelated, and repetitive genomic rearrangements within a tumor. Heterocateny is driven by unstable concatemerized HPV genomes, which facilitate capture, rearrangement, and amplification of host DNA, and promotes intratumoral heterogeneity and clonal evolution.See related commentary by McBride and White, p. 814.This article is highlighted in the In This Issue feature, p. 799

The assignment of variants across haplotypes, phasing, is crucial for predicting the consequences, interaction, and inheritance of mutations and is a key step in improving our understanding of phenotype and disease. However, phasing is limited by read length and stretches of homozygosity along the genome. To overcome this limitation, we designed MethPhaser, the first method that utilizes methylation signals from Oxford Nanopore Technologies to extend SNV-based phasing. Across control samples, we extend the phase length N50 by almost 3-fold while minimally increasing the phasing error by ∼0.02%. Nevertheless, methylation signals have limitations, such as random signals on sex chromosomes or tissue purity. To assess the latter, we also applied MethPhaser on blood samples from 4 patients, still showing improvements over SNV-only phasing. MethPhaser further improves phasing acrossHLAand multiple other medically relevant genes, improving our understanding of how mutations interact across multiple phenotypes. MethPhaser is available athttps://github.com/treangenlab/methphaser.

Tandem repeat (TR) variation is associated with gene expression changes and over 50 rare monogenic diseases. Recent advances in sequencing have enabled accurate, long reads that can characterize the full-length sequence and methylation profile of TRs. However, despite these advances in sequencing technology, computational methods to fully profile tandem repeats across the genome do not exist. To address this gap, we introduce tools for tandem repeat genotyping (TRGT), visualization and an accompanying TR database. TRGT accurately resolves the length and sequence composition of TR regions in the human genome. Assessing 937,122 TRs, TRGT showed a Mendelian concordance of 99.56%, allowing a single repeat unit difference. In six samples with known repeat expansions, TRGT detected all repeat expansions while also identifying methylation signals, mosaicism, and providing finer resolution of repeat length. Additionally, we release a database with allele sequences and methylation levels for 937,122 TRs across 100 genomes.

Figure S1.1. Circos plots of human genomes. Figure S1.2. Circos plots of HPV genomes. Figure S1.3. PacBio HiFi read length distributions. Figure S1.4. Oxford Nanopore (ONT) read length distributions. Figure S2.1. Detection of circularized mitochondrial DNA by LR-seq reads. Figure S2.2. Detection of HPV concatemers by LR-seq reads. Figure S2.3. ONT reads show structural rearrangements in HPV concatemers. Figure S3.1. Absence of sequence variants at breakpoints. Figure S3.2. AmpliconArchitect predicts inaccurate HPV ecDNA structures. Figure S4.1. Evolution of structural variants at Chr. 22 of Tumor 2. Figure S4.2. Evidence of heterocateny in Tumor 5 and Tumor 3. Figure S5.1. HPV integration into icDNA in GUMC-395, HeLa, and HTEC. Figure S5.2. HPV integrants at Chr. 17 and Chr. X of VU147. Figure S5.3. Metaphase FISH identifies HPV-containing ecDNAs in cell lines. Figure S5.4. Circle-seq analysis of HeLa, GUMC-395, VU147, and HTEC cells. Figure S6. Transcription levels of HPV genes. Table S1.1. Depths of autosomal and mitochondrial genome sequencing coverage from WGS and LR-seq. Table S1.2. Depths of autosomal and HPV genome sequencing coverage from WGS and LR-seq. Table S2.1. Breakpoints and normal segment junctions in Tumor 4. Table S2.2. Definition of genomic segments flanking HPV integrants in Tumor 4. Table S3.1. Breakpoints and normal segment junctions in Tumor 2. Table S3.2. Definition of genomic segments flanking HPV integrants in Tumor 2. Table S3.3. Breakpoints and normal segment junctions in Tumor 5. Table S3.4. Definition of genomic segments flanking HPV integrants in Tumor 5. Table S3.5. Breakpoints and normal segment junctions in Tumor 3. Table S3.6. Definition of genomic segments flanking HPV integrants in Tumor 3. Table S4.1. Breakpoints and normal segment junctions in GUMC-395 cells. Table S4.2. Definition of genomic segments flanking HPV integrants in GUMC-395 cells. Table S5.1. Breakpoints and normal segment junctions in HeLa cells. Table S5.2. Definition of genomic segments flanking HPV integrants in HeLa cells. Table S5.3. Breakpoints and normal segment junctions in VU147 cells. Table S5.4. Definition of genomic segments flanking HPV integrants in VU147 cells. Table S5.5. Breakpoints and normal segment junctions in HTEC cells. Table S5.6. Definition of genomic segments flanking HPV integrants in HTEC cells.

Structural variants are associated with cancers and developmental disorders, but challenges with estimating population frequency remain a barrier to prioritizing mutations over inherited variants. In particular, variability in variant calling heuristics and filtering limits the use of current structural variant catalogs. We present STIX, a method that, instead of relying on variant calls, indexes and searches the raw alignments from thousands of samples to enable more comprehensive allele frequency estimation.

Since its initial release in 2000, the human reference genome has covered only the euchromatic fraction of the genome, leaving important heterochromatic regions unfinished. Addressing the remaining 8% of the genome, the Telomere-to-Telomere (T2T) Consortium presents a complete 3.055 billion–base pair sequence of a human genome, T2T-CHM13, that includes gapless assemblies for all chromosomes except Y, corrects errors in the prior references, and introduces nearly 200 million base pairs of sequence containing 1956 gene predictions, 99 of which are predicted to be protein coding. The completed regions include all centromeric satellite arrays, recent segmental duplications, and the short arms of all five acrocentric chromosomes, unlocking these complex regions of the genome to variational and functional studies.

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

The current version of the human reference genome, GRCh38, contains a number of errors including 1.2 Mbp of falsely duplicated and 8.04 Mbp of collapsed regions. These errors impact the variant calling of 33 protein-coding genes, including 12 with medical relevance. Here, we present FixItFelix, an efficient remapping approach, together with a modified version of the GRCh38 reference genome that improves the subsequent analysis across these genes within minutes for an existing alignment file while maintaining the same coordinates. We showcase these improvements over multi-ethnic control samples, demonstrating improvements for population variant calling as well as eQTL studies.

The structure of the genome, specifically repetitive and duplicated regions, leads to difficulty in accurately characterizing variation across a variety of sequencing technologies and variant detection methods. The Genome in a Bottle consortium generates variant benchmarks for DNA Reference Materials from seven human cell lines to reliably identify errors in comparison variant sets, as well as stratification files for error analysis in specific genomic regions. Current genome stratifications include discrete bins of homopolymer size, tandem repeat size, mappability, and segmental duplications focusing on regions subject to bias in sequencing technologies and/or variant calling methods. To move to a data-driven approach for genome stratification development and interrogation of variant calling errors, we developed a stratification model - StratoMod. StratoMod is built with an interpretable machine learning classifier, Explainable Boosting Machines (EBMs), to predict variant calling errors from features derived from genomic and sequencing data. EBMs quantify univariate effects and pairwise interactions, which facilitates understanding how each feature contributes to a prediction. Here, we describe the design, training, testing, and application of StratoMod, including demonstrating its ability to identify characteristics of sequencing reads and repetitive genome regions that are likely to generate variant calling errors. Specifically, StratoMod identified distinct associations with errors for A/T vs. G/C homopolymer lengths, and quantified sources of error for a new sequencing technology. We also demonstrated that the model could predict clinically-relevant variants that may be missed by certain methods, using DeepVariant calls from Illumina as an example. For this example, we produced a resource of difficult-to-map genes with challenging variants and large challenging INDELs. Using this model with GIAB benchmarks facilitates a deeper quantitative understanding of sources of variant calling errors from a wide variety of methods.

Background Recent population studies are ever growing in number of samples to investigate the diversity of a population or species. These studies reveal 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 not yet detected variations and investigate their properties, thereby enhancing the analysis for potentially missed variants. Results To achieve this we developed SVhound (https://github.com/lfpaulin/SVhound), which based on a population level SVs dataset can predict regions that harbor unseen SV alleles. We tested SVhound using subsets of the 1000 genomes project data and showed that its correlation (average correlation of 2800 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. Lastly we also apply SVhound on a small and novel SV call set for rhesus macaque (Macaca mulatta) and discuss the impact and choice of parameters for SVhound. Conclusions 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.

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 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Current methods for inference of phylogenetic trees require running complex pipelines at substantial computational and labor costs, with additional constraints in sequencing coverage, assembly and annotation quality, especially for large datasets. To overcome these challenges, we present Read2Tree, which directly processes raw sequencing reads into groups of corresponding genes and bypasses traditional steps in phylogeny inference, such as genome assembly, annotation and all-versus-all sequence comparisons, while retaining accuracy. In a benchmark encompassing a broad variety of datasets, Read2Tree is 10-100 times faster than assembly-based approaches and in most cases more accurate-the exception being when sequencing coverage is high and reference species very distant. Here, to illustrate the broad applicability of the tool, we reconstruct a yeast tree of life of 435 species spanning 590 million years of evolution. We also apply Read2Tree to >10,000 Coronaviridae samples, accurately classifying highly diverse animal samples and near-identical severe acute respiratory syndrome coronavirus 2 sequences on a single tree. The speed, accuracy and versatility of Read2Tree enable comparative genomics at scale., Nature Biotechnology, ISSN:1546-1696, ISSN:1087-0156

Background The growing volume and heterogeneity of next-generation sequencing (NGS) data complicate the further optimization of identifying DNA variation, especially considering that curated high-confidence variant call sets frequently used to validate these methods are generally developed from the analysis of comparatively small and homogeneous sample sets. Findings We have developed xAtlas, a single-sample variant caller for single-nucleotide variants (SNVs) and small insertions and deletions (indels) in NGS data. xAtlas features rapid runtimes, support for CRAM and gVCF file formats, and retraining capabilities. xAtlas reports SNVs with 99.11% recall and 98.43% precision across a reference HG002 sample at 60× whole-genome coverage in less than 2 CPU hours. Applying xAtlas to 3,202 samples at 30× whole-genome coverage from the 1000 Genomes Project achieves an average runtime of 1.7 hours per sample and a clear separation of the individual populations in principal component analysis across called SNVs. Conclusions xAtlas is a fast, lightweight, and accurate SNV and small indel calling method. Source code for xAtlas is available under a BSD 3-clause license at https://github.com/jfarek/xatlas.

The human Y chromosome has been notoriously difficult to sequence and assemble because of its complex repeat structure including long palindromes, tandem repeats, and segmental duplications. As a result, more than half of the Y chromosome is missing from the GRCh38 reference sequence and it remains the last human chromosome to be finished. Here, the Telomere-to-Telomere (T2T) consortium presents the complete 62,460,029 base pair sequence of a human Y chromosome from the HG002 genome (T2T-Y) that corrects multiple errors in GRCh38-Y and adds over 30 million base pairs of sequence to the reference, revealing the complete ampliconic structures ofTSPY, DAZ, andRBMY; 42 additional protein-coding genes, mostly from theTSPYgene family; and an alternating pattern of human satellite 1 and 3 blocks in the heterochromatic Yq12 region. We have combined T2T-Y with a prior assembly of the CHM13 genome and mapped available population variation, clinical variants, and functional genomics data to produce a complete and comprehensive reference sequence for all 24 human chromosomes.

Genome in a Bottle benchmarks are widely used to help validate clinical sequencing pipelines and develop variant calling and sequencing methods. Here we use accurate linked and long reads to expand benchmarks in 7 samples to include difficult-to-map regions and segmental duplications that are challenging for short reads. These benchmarks add more than 300,000 SNVs and 50,000 insertions or deletions (indels) and include 16% more exonic variants, many in challenging, clinically relevant genes not covered previously, such as

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.

In a cross between two homozygous Brassica napus plants of synthetic and natural origin, we demonstrate that novel structural genome variants from the synthetic parent cause immediate genome diversification among F1 offspring. Long read sequencing in twelve F1 sister plants revealed five large-scale structural rearrangements where both parents carried different homozygous alleles but the heterozygous F1 genomes were not identical heterozygotes as expected. Such spontaneous rearrangements were part of homoeologous exchanges or segmental deletions and were identified in different, individual F1 plants. The variants caused deletions, gene copy-number variations, diverging methylation patterns and other structural changes in large numbers of genes and may have been causal for unexpected phenotypic variation between individual F1 sister plants, for example strong divergence of plant height and leaf area. This example supports the hypothesis that spontaneous de novo structural rearrangements after de novo polyploidization can rapidly overcome intense allopolyploidization bottlenecks to re-expand crops genetic diversity for ecogeographical expansion and human selection. The findings imply that natural genome restructuring in allopolyploid plants from interspecific hybridization, a common approach in plant breeding, can have a considerably more drastic impact on genetic diversity in agricultural ecosystems than extremely precise, biotechnological genome modifications.

Protein phosphatase 1 regulatory subunit 35 (PPP1R35) encodes a centrosomal protein required for recruiting microtubule-binding elongation machinery. Several proteins in this centriole biogenesis pathway correspond to established primary microcephaly (MCPH) genes, and multiple model organism studies hypothesize PPP1R35 as a candidate MCPH gene. Here, using exome sequencing (ES) and family-based rare variant analyses, we report a homozygous, frameshifting indel deleting the canonical stop codon in the last exon of PPP1R35 [Chr7: c.753_*3delGGAAGCGTAGACCinsCG (p.Trp251Cysfs*22)]; the variant allele maps in a 3.7 Mb block of absence of heterozygosity (AOH) in a proband with severe MCPH (-4.3 SD at birth, -6.1 SD by 42 months), pachygyria, and global developmental delay from a consanguineous Turkish kindred. Droplet digital PCR (ddPCR) confirmed mutant mRNA expression in fibroblasts. In silico prediction of the translation of mutant PPP1R35 is expected to be elongated by 18 amino acids before encountering a downstream stop codon. This complex indel allele is absent in public databases (ClinVar, gnomAD, ARIC, 1000 genomes) and our in-house database of 14,000+ exomes including 1800+ Turkish exomes supporting predicted pathogenicity. Comprehensive literature searches for PPP1R35 variants yielded two probands affected with severe microcephaly (-15 SD and -12 SD) with the same homozygous indel from a single, consanguineous, Iranian family from a cohort of 404 predominantly Iranian families. The lack of heterozygous cases in two large cohorts representative of the genetic background of these two families decreased our suspicion of a founder allele and supports the contention of a recurrent mutation. We propose two potential secondary structure mutagenesis models for the origin of this variant allele mediated by hairpin formation between complementary GC rich segments flanking the stop codon via secondary structure mutagenesis.

BackgroundThe multiplede novocopy number variant (MdnCNV) phenotype is described by having four or more constitutionalde novoCNVs (dnCNVs) arising independently throughout the human genome within one generation. It is a rare peri-zygotic mutational event, previously reported to be seen once in every 12,000 individuals referred for genome-wide chromosomal microarray analysis due to congenital abnormalities. These rare families provide a unique opportunity to understand the genetic factors of peri-zygotic genome instability and the impact ofdnCNV on human diseases.MethodsChromosomal microarray analysis (CMA), array-based comparative genomic hybridization, short- and long-read genome sequencing (GS) were performed on the newly identified MdnCNV family to identifyde novomutations includingdnCNVs,de novosingle-nucleotide variants (dnSNVs), and indels. Short-read GS was performed on four previously published MdnCNV families fordnSNV analysis. Trio-based rare variant analysis was performed on the newly identified individual and four previously published MdnCNV families to identify potential genetic etiologies contributing to the peri-zygotic genomic instability. Lin semantic similarity scores informed quantitative human phenotype ontology analysis on three MdnCNV families to identify gene(s) driving or contributing to the clinical phenotype.ResultsIn the newly identified MdnCNV case, we revealed eightde novotandem duplications, each ~ 1 Mb, with microhomology at 6/8 breakpoint junctions. Enrichment ofde novosingle-nucleotide variants (SNV; 6/79) andde novoindels (1/12) was found within 4 Mb of thednCNV genomic regions. An elevated post-zygotic SNV mutation rate was observed in MdnCNV families. Maternal rare variant analyses identified three genes in distinct families that may contribute to the MdnCNV phenomenon. Phenotype analysis suggests that gene(s) withindnCNV regions contribute to the observed proband phenotype in 3/3 cases. CNVs in two cases, a contiguous gene duplication encompassingPMP22andRAI1and another duplication affectingNSD1andSMARCC2, contribute to the clinically observed phenotypic manifestations.ConclusionsCharacteristic features ofdnCNVs reported here are consistent with a microhomology-mediated break-induced replication (MMBIR)-driven mechanism during the peri-zygotic period. Maternal genetic variants in DNA repair genes potentially contribute to peri-zygotic genomic instability. Variable phenotypic features were observed across a cohort of three MdnCNV probands, and computational quantitative phenotyping revealed that two out of three had evidence for the contribution of more than one genetic locus to the proband’s phenotype supporting the hypothesis ofde novomultilocus pathogenic variation (MPV) in those families.

Xia-Gibbs syndrome is a rare mendelian disorder characterized by Development Delay (DD), intellectual disability (ID), and hypotonia. Individuals with XGS typically harbor de novo protein-truncating mutations in the AT-Hook DNA binding motif containing 1 (AHDC1) gene, although some missense mutations can also cause XGS. Large de novo heterozygous deletions that encompass the AHDC1 gene have also been ascribed as diagnostic for the disorder, without substantial evidence to support their pathogenicity. We analyzed 19 individuals with large contiguous deletions involving AHDC1, along with other genes. One individual bore the smallest known contiguous AHDC1 deletion (∼350 Kb), encompassing eight other genes within chr1p36.11 (Feline Gardner-Rasheed, IFI6, FAM76A, STX12, PPP1R8, THEMIS2, RPA2, SMPDL3B) and terminating within the first intron of AHDC1. The breakpoint junctions and phase of the deletion were identified using both short and long read sequencing (Oxford Nanopore). Quantification of RNA expression patterns in whole blood revealed that AHDC1 exhibited a mono-allelic expression pattern with no deficiency in overall AHDC1 expression levels, in contrast to the other deleted genes, which exhibited a 50% reduction in mRNA expression. These results suggest that AHDC1 expression in this individual is compensated by a novel regulatory mechanism and advances understanding of mutational and regulatory mechanisms in neurodevelopmental disorders.

The advancements in sequencing technologies and assembly methods enable the regular production of high-quality genome assemblies characterizing complex regions. However, challenges remain in efficiently interpreting variations at various scales, from smaller tandem repeats to megabase re-arrangements, across many human genomes. We present a pangenome research toolkit enabling analyses of complex pangenome variations at multiple scales. A graph decomposition method is developed for interpreting such variations. Surveying a set of 395 challenging and medically important genes in pangenome provides quantitative insights into repetitiveness and diversity that could impact the accuracy of variant calls. We apply the graph decomposition methods to the Y-chromosome gene, DAZ1/DAZ2/DAZ3/DAZ4, of which structural variants have been linked to male infertility, and X-chromosome genes OPN1LW and OPN1MW linked to eye disorders, highlighting the power of PGR-TK and pangenomics to resolve complex variation in regions of the genome that were previously too complex to analyze across many haplotypes.