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Wheat is the second largest food crop with a very good breeding system and pedigree record in China. Investigating the genomic footprints of wheat cultivars will unveil potential avenues for future breeding efforts 1 , 2 . Here we report chromosome-level genome assemblies of 17 wheat cultivars that chronicle the breeding history of China. Comparative genomic analysis uncovered a wealth of structural rearrangements, identifying 249,976 structural variations with 49.03% (122,567) longer than 5 kb. Cultivars developed in 1980s displayed significant accumulations of structural variations, a pattern linked to the extensive incorporation of European and American varieties into breeding programmes of that era. We further proved that structural variations in the centromere-proximal regions are associated with a reduction of crossover events. We showed that common wheat evolved from spring to winter types via mutations and duplications of the VRN-A1 gene as an adaptation strategy to a changing environment. We confirmed shifts in wheat cultivars linked to dietary preferences, migration and cultural integration in Northwest China. We identified large presence or absence variations of pSc200 tandem repeats on the 1RS terminal, suggesting its own rapid evolution in the wheat genome. The high-quality genome assemblies of 17 representatives developed and their good complementarity to the 10+ pan-genomes offer a robust platform for future genomics-assisted breeding in wheat. The pan-genome of 17 wheat cultivars grown in China is explored, providing insights into the breeding history of wheat in East Asia.

Calling structural variations (SVs) is technically challenging, but using long reads remains the most accurate way to identify complex genomic alterations. Here we present Sniffles2, which improves over current methods by implementing a repeat aware clustering coupled with a fast consensus sequence and coverage-adaptive filtering. Sniffles2 is 11.8 times faster and 29% more accurate than state-of-the-art SV callers across different coverages (5–50×), sequencing technologies (ONT and HiFi) and SV types. Furthermore, Sniffles2 solves the problem of family-level to population-level SV calling to produce fully genotyped VCF files. Across 11 probands, we accurately identified causative SVs around MECP2 , including highly complex alleles with three overlapping SVs. Sniffles2 also enables the detection of mosaic SVs in bulk long-read data. As a result, we identified multiple mosaic SVs in brain tissue from a patient with multiple system atrophy. The identified SV showed a remarkable diversity within the cingulate cortex, impacting both genes involved in neuron function and repetitive elements. Sniffles2 detects mosaic structural variation from bulk long-read sequencing data.

Medulloblastoma, the most common malignant paediatric brain tumour, is currently treated with nonspecific cytotoxic therapies including surgery, whole-brain radiation, and aggressive chemotherapy. As medulloblastoma exhibits marked intertumoural heterogeneity, with at least four distinct molecular variants, previous attempts to identify targets for therapy have been underpowered because of small samples sizes. Here we report somatic copy number aberrations (SCNAs) in 1,087 unique medulloblastomas. SCNAs are common in medulloblastoma, and are predominantly subgroup-enriched. The most common region of focal copy number gain is a tandem duplication of SNCAIP , a gene associated with Parkinson’s disease, which is exquisitely restricted to Group 4α. Recurrent translocations of PVT1 , including PVT1-MYC and PVT1-NDRG1 , that arise through chromothripsis are restricted to Group 3. Numerous targetable SCNAs, including recurrent events targeting TGF-β signalling in Group 3, and NF-κB signalling in Group 4, suggest future avenues for rational, targeted therapy. Medulloblastoma is the most common malignant brain tumour in children; having assembled over 1,000 samples the authors report that somatic copy number aberrations are common in medulloblastoma, in particular a tandem duplication of SNCAIP , a gene associated with Parkinson’s disease, which is restricted to subgroup 4α, and translocations of PVT1 , which are restricted to Group 3. The medulloblastoma genome dissected Medulloblastoma is the most common malignant brain tumour in children. Four papers published in the 2 August 2012 issue of Nature use whole-genome and other sequencing techniques to produce a detailed picture of the genetics and genomics of this condition. Notable findings include the identification of recurrent mutations in genes not previously implicated in medulloblastoma, with significant genetic differences associated with the four biologically distinct subgroups and clinical outcomes in each. Potential avenues for therapy are suggested by the identification of targetable somatic copy-number alterations, including recurrent events targeting TGFβ signalling in Group 3, and NF-κB signalling in Group 4 medulloblastomas.

Structural variants (SVs) are large genomic alterations that can profoundly impact disease risk by disrupting gene function and regulation. Despite this, their role in Alzheimer's disease (AD) remains understudied due to challenges to accurate detection and prediction of potential impact. A recent Alzheimer's Disease Sequencing Project (ADSP) study addressed many of these challenges and identified >400k SVs (168,223 high quality) from the sequencing of ∼16k whole genomes. The study detected a burden of singletons and homozygous deletions in AD cases, as well as an association of protein-altering SVs with several known AD genes (H. Wang et al.; doi:10.1101/2023.09.13.23295505). This work highlights the essential role of SVs in AD genetics, emphasizing that further identification and analysis are needed. To support this, we have integrated these results into the NIA Genetics of Alzheimer's Disease Data Storage Site's (NIAGADS) Alzheimer's Genomics Database (GenomicsDB). Part of NIAGADS's Open Access Data Initiative, the GenomicsDB compiles unrestricted AD-relevant genetic data and annotations, making them more accessible to AD-researchers and facilitating data reuse. SVs detected in the ADSP study were harmonized with existing GenomicsDB data and each was assigned a unique identifier based on genomic location and variant type. The dataset was then augmented by detecting overlaps with SVs reported in key third-party databases (e.g., dbVar, gnomAD). Significant associations with known AD-genes detected in the analysis were flagged, and all variants were annotated using VEP and annotSV. Protein-altering variants were identified based on predicted consequences, and the relative functional impact of the SVs ranked. In its next release, the GenomicsDB will make public SV reports that compile both annotations and information on other genomic features and AD-genetic associations overlapping the variant span. An annotated SV genome browser track was also generated. Identification and analysis of SVs in AD is essential for gaining a more comprehensive understanding of the genetic underpinnings of this complex disease. By making these data accessible and placing them in the broader genomic context, inclusion of the ADSP Structural Variant study results in the GenomicsDB creates a unique and valuable resource for AD-researchers.

Indigenous Australians harbour rich and unique genomic diversity. However, Aboriginal and Torres Strait Islander ancestries are historically under-represented in genomics research and almost completely missing from reference datasets 1 – 3 . Addressing this representation gap is critical, both to advance our understanding of global human genomic diversity and as a prerequisite for ensuring equitable outcomes in genomic medicine. Here we apply population-scale whole-genome long-read sequencing 4 to profile genomic structural variation across four remote Indigenous communities. We uncover an abundance of large insertion–deletion variants (20–49 bp; n  = 136,797), structural variants (50  b–50 kb; n  = 159,912) and regions of variable copy number (>50 kb; n  = 156). The majority of variants are composed of tandem repeat or interspersed mobile element sequences (up to 90%) and have not been previously annotated (up to 62%). A large fraction of structural variants appear to be exclusive to Indigenous Australians (12% lower-bound estimate) and most of these are found in only a single community, underscoring the need for broad and deep sampling to achieve a comprehensive catalogue of genomic structural variation across the Australian continent. Finally, we explore short tandem repeats throughout the genome to characterize allelic diversity at 50 known disease loci 5 , uncover hundreds of novel repeat expansion sites within protein-coding genes, and identify unique patterns of diversity and constraint among short tandem repeat sequences. Our study sheds new light on the dimensions and dynamics of genomic structural variation within and beyond Australia. Population-scale whole-genome sequencing across four remote Indigenous Australian communities reveals a large fraction of structural variants that are unique to these populations, emphasizing the genetic distinctiveness of and diversity among Indigenous Australians.

In recent years, many software packages for identifying structural variants (SVs) using whole-genome sequencing data have been released. When published, a new method is commonly compared with those already available, but this tends to be selective and incomplete. The lack of comprehensive benchmarking of methods presents challenges for users in selecting methods and for developers in understanding algorithm behaviours and limitations. Here we report the comprehensive evaluation of 10 SV callers, selected following a rigorous process and spanning the breadth of detection approaches, using high-quality reference cell lines, as well as simulations. Due to the nature of available truth sets, our focus is on general-purpose rather than somatic callers. We characterise the impact on performance of event size and type, sequencing characteristics, and genomic context, and analyse the efficacy of ensemble calling and calibration of variant quality scores. Finally, we provide recommendations for both users and methods developers. A number of computational methods have been developed for calling structural variants (SVs) using short read sequencing data. Here, the authors perform a comprehensive benchmarking analysis comparing 10 general-purpose callers and provide recommendations for both users and methods developers.

Higher-order chromatin structure is important for the regulation of genes by distal regulatory sequences 1 , 2 . Structural variants (SVs) that alter three-dimensional (3D) genome organization can lead to enhancer–promoter rewiring and human disease, particularly in the context of cancer 3 . However, only a small minority of SVs are associated with altered gene expression 4 , 5 , and it remains unclear why certain SVs lead to changes in distal gene expression and others do not. To address these questions, we used a combination of genomic profiling and genome engineering to identify sites of recurrent changes in 3D genome structure in cancer and determine the effects of specific rearrangements on oncogene activation. By analysing Hi-C data from 92 cancer cell lines and patient samples, we identified loci affected by recurrent alterations to 3D genome structure, including oncogenes such as MYC , TERT and CCND1 . By using CRISPR–Cas9 genome engineering to generate de novo SVs, we show that oncogene activity can be predicted by using ‘activity-by-contact’ models that consider partner region chromatin contacts and enhancer activity. However, activity-by-contact models are only predictive of specific subsets of genes in the genome, suggesting that different classes of genes engage in distinct modes of regulation by distal regulatory elements. These results indicate that SVs that alter 3D genome organization are widespread in cancer genomes and begin to illustrate predictive rules for the consequences of SVs on oncogene activation. Results are presented that indicate that alterations to gene regulatory three-dimensional architecture are a critical mechanism that enables structural variant-based oncogene activation in cancer genomes and sheds light on the essential elements for such gene activation events.

Medulloblastoma is a highly malignant paediatric brain tumour currently treated with a combination of surgery, radiation and chemotherapy, posing a considerable burden of toxicity to the developing child. Genomics has illuminated the extensive intertumoral heterogeneity of medulloblastoma, identifying four distinct molecular subgroups. Group 3 and group 4 subgroup medulloblastomas account for most paediatric cases; yet, oncogenic drivers for these subtypes remain largely unidentified. Here we describe a series of prevalent, highly disparate genomic structural variants, restricted to groups 3 and 4, resulting in specific and mutually exclusive activation of the growth factor independent 1 family proto-oncogenes, GFI1 and GFI1B. Somatic structural variants juxtapose GFI1 or GFI1B coding sequences proximal to active enhancer elements, including super-enhancers, instigating oncogenic activity. Our results, supported by evidence from mouse models, identify GFI1 and GFI1B as prominent medulloblastoma oncogenes and implicate ‘enhancer hijacking’ as an efficient mechanism driving oncogene activation in a childhood cancer. Focusing on two ill-characterized subtypes of medulloblastoma (group 3 and group 4), this study identifies prevalent genomic structural variants that are restricted to these two subtypes and independently bring together coding regions of GFI1 family proto-oncogenes with active enhancer elements, leading to their mutually exclusive oncogenic activation. Oncogenesis through enhancer hijacking Medulloblastoma is a highly malignant paediatric brain tumour. Here the authors focus on two ill-characterized subtypes — group 3 and group 4 — which account for the majority of paediatric cases. They identify prevalent genomic structural variants, which are restricted to these two subtypes, and bring together coding regions of proto-oncogenes, GFI1 and GFI1B , and active enhancer elements leading to oncogene activation. This work identifies 'enhancer hijacking' as an efficient mechanism driving oncogene activation in a childhood cancer.

It has been hypothesized that individually-rare hidden structural variants (SVs) could account for a significant fraction of variation in complex traits. Here we identified more than 20,000 euchromatic SVs from 14 Drosophila melanogaster genome assemblies, of which ~40% are invisible to high specificity short-read genotyping approaches. SVs are common, with 31.5% of diploid individuals harboring a SV in genes larger than 5kb, and 24% harboring multiple SVs in genes larger than 10kb. SV minor allele frequencies are rarer than amino acid polymorphisms, suggesting that SVs are more deleterious. We show that a number of functionally important genes harbor previously hidden structural variants likely to affect complex phenotypes. Furthermore, SVs are overrepresented in candidate genes associated with quantitative trait loci mapped using the Drosophila Synthetic Population Resource. We conclude that SVs are ubiquitous, frequently constitute a heterogeneous allelic series, and can act as rare alleles of large effect. Rare structural variants may account for a significant fraction of variation in complex traits. Here the authors analyse 14 Drosophila melanogaster genomes and find that structural variants are common, found in functionally important genes, and associated with QTLs.

Structural variations (SVs) are a key type of cancer genomic alterations, contributing to oncogenesis and progression of many cancers, including colorectal cancer (CRC). However, SVs in CRC remain difficult to be reliably detected due to limited SV-detection capacity of the commonly used short-read sequencing. This study investigated the somatic SVs in 21 pairs of CRC samples by Nanopore whole-genome long-read sequencing. 5200 novel somatic SVs from 21 CRC patients (494 SVs / patient) were identified. A 4.9-Mbp long inversion that silences APC expression (confirmed by RNA-seq) and an 11.2-kbp inversion that structurally alters CFTR were identified. Two novel gene fusions that might functionally impact the oncogene RNF38 and the tumor-suppressor SMAD3 were detected. RNF38 fusion possesses metastasis-promoting ability confirmed by in vitro migration and invasion assay, and in vivo metastasis experiments. This work highlighted the various applications of long-read sequencing in cancer genome analysis, and shed new light on how somatic SVs structurally alter critical genes in CRC. The investigation on somatic SVs via nanopore sequencing revealed the potential of this genomic approach in facilitating precise diagnosis and personalized treatment of CRC.