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PubMed2025

CCRR: a user-friendly platform for analyzing complex chromosomal rearrangements in tumors.

SUMMARY: Complex chromosomal rearrangements in tumors involve intricate genomic alterations that significantly affect gene function and contribute to cancer development. Identifying these events is crucial for cancer research but is often challenging due to the complexity and limitations of existing tools. We developed the Complex Chromosomal Rearrangements Resolver (CCRR), a comprehensive, reproducible, and user-friendly platform for analyzing complex rearrangements in tumors. CCRR integrates multiple SV and CNV detection tools within a Docker container environment, simplifying installation and configuration. It can be easily deployed, automating the execution and merging of results, providing high-confidence consensus SV and CNV calls, allowing researchers to efficiently analyze complex chromosomal rearrangements in tumors without extensive bioinformatics expertise. CCRR also includes a web server for one-click analysis and customized visualization. AVAILABILITY AND IMPLEMENTATION: The CCRR platform is freely available at https://www.ccrr.life. Source code and executables can be accessed at https://github.com/laslk/CCRR. An archived version is available at Zenodo: https://doi.org/10.5281/zenodo.15386513.

Software↗

PubMed2025

Pan-Genome Analysis Reveals Local Adaptation to Climate Driven by Introgression in Oak Species.

The genetic base of local adaptation has been extensively studied in natural populations. However, a comprehensive genome-wide perspective on the contribution of structural variants (SVs) and adaptive introgression to local adaptation remains limited. In this study, we performed de novo assembly and annotation of 22 representative accessions of Quercus variabilis, identifying a total of 543,372 SVs. These SVs play crucial roles in shaping genomic structure and influencing gene expression. By analyzing range-wide genomic data, we identified both SNPs and SVs associated with local adaptation in Q. variabilis and Quercus acutissima. Notably, SV-outliers exhibit selection signals that did not overlap with SNP-outliers, indicating that SNP-based analyses may not detect the same candidate genes associated with SV-outliers. Remarkably, 29%-37% of candidate SNPs were located in a 250 kb region on chromosome 9, referred to as Chr9-ERF. This region contains 8 duplicated ethylene-responsive factor (ERF) genes, which may have contributed to local adaptation of Q. variabilis and Q. acutissima. We also found that a considerable number of candidate SNPs were shared between Q. variabilis and Q. acutissima in the Chr9-ERF region, suggesting a pattern of repeated selection. We further demonstrated that advantageous variants in this region were introgressed from western populations of Q. acutissima into Q. variabilis, providing compelling evidence that introgression facilitates local adaptation. This study offers a valuable genomic resource for future studies on oak species and highlights the importance of pan-genome analysis in understating mechanism driving adaptation and evolution.

Quercus↗

PubMed2026

Comprehensive transcriptomics and proteomics analysis of neointima formation in human saphenous vein: implications for bypass graft disease.

Human saphenous veins (SVs) are widely used as grafts in coronary artery bypass (CABG) surgery but often fail due to neointima formation. Little is known, however, regarding the cellular, transcriptomic, and proteomic dynamics of neointima formation in human veins. Here, we performed transcriptomics and proteomics analysis in an ex vivo tissue culture model of neointima formation in human SVs procured for CABG surgery. Histological examination demonstrated significant elastin degradation and neointima formation (indicated by increased neointima area and neointima-to-media ratio) in SVs subjected to tissue culture. Analysis of data from 72 patients suggests that the progression of SV remodeling and neointima formation differs according to sex and body mass index, which is negatively associated with neointima formation in males only. RNA sequencing demonstrated upregulation of proinflammatory and proliferation-related genes during neointima formation and identified novel processes, including increased cellular stress and DNA damage responses, reflecting tissue trauma associated with vein harvesting. Proteomic analysis identified upregulated extracellular matrix-related and coagulation/thrombosis proteins and downregulated metabolic proteins. Spatial transcriptomics, used to infer regionally enriched gene expression, suggested dynamic alterations in fibroblast and vascular smooth muscle cell (VSMC) states during neointima formation. Specifically, we identified the emergence of HES1+ and matrix metalloproteinase 2- and 14-positive (MMP2+/MMP14+) expression in VSMCs and fibroblasts, respectively, during neointima formation. Furthermore, our data suggest that MIR647, identified through screening, maintains VSMC contractile gene expression. Our findings suggest dynamic transcriptomic and proteomic changes during neointima formation in human veins and provide useful mechanistic information for the pathogenesis of SV graft disease.NEW & NOTEWORTHY Using multiomics and spatial transcriptomics, we uncover dynamic molecular and cellular changes driving neointima proliferation in human saphenous veins, the most common conduit for bypass surgery. Our study highlights sex- and body mass index-associated differences, novel fibroblast and smooth muscle cell states, and a role for microRNA-647 in preserving vascular contractile phenotype. These findings provide new insight into the mechanisms of vein graft failure and may guide future strategies to improve coronary bypass outcomes.

Humans↗

PubMed2026

Dual-dimensional profiling of host genomic variations and HPV integration in PD-L1-stratified cervical cancer via Oxford Nanopore Technology.

BACKGROUND: The integration of human papillomavirus (HPV) DNA into the host genome is a key step in the development of HPV-associated cervical cancer (CC). However, the genomic characteristics of host genomic variations and HPV integration within the context of programmed death-ligand 1 (PD-L1) expression stratification have not been systematically investigated. METHODS: Whole-genome sequencing was performed using Oxford Nanopore Technology (ONT) on six samples (three from the high PD-L1 expression group and three from the low PD-L1 expression group). The characteristics of host genomic variations under different PD-L1 expression stratifications were explored, including structural variations (SV), copy number variations (CNV), single nucleotide polymorphisms (SNP), and insertion-deletions (Indel). Subsequently, the distribution features of HPV integration sites were analyzed, different integration types were identified, and pathway analysis was conducted. RESULTS: Whole-genome SV analysis revealed that the total number of SVs and the composition of mutation types were similar between the high and low PD-L1 expression groups, with insertions (INS) and deletions (DEL) predominating in both. These variations were primarily enriched in intergenic regions and introns. In the low PD-L1 expression group, integration events were observed at multiple chromosomal loci, with the most frequent integration occurring in the KLF5 gene region on chromosome 13. No frequently integrated loci were identified in the high PD-L1 expression group. Additionally, four distinct HPV integration breakpoint patterns were preliminarily identified and analyzed. CONCLUSION: PD-L1 expression stratification did not significantly alter the overall genomic instability of the host. However, differences were observed in the distribution patterns of HPV integration sites. These findings provide new insights into the genomic heterogeneity of CC under different PD-L1 expression backgrounds and may lay the groundwork for future research exploring stratified immunotherapy based on HPV integration features.

Humans↗

PubMed2025

Structural variants linked to Alzheimer's disease and other common age-related clinical and neuropathologic traits.

BACKGROUND: Alzheimer's disease (AD) is a complex neurodegenerative disorder with substantial genetic influence. While genome-wide association studies (GWAS) have identified numerous risk loci for late-onset AD (LOAD), the functional mechanisms underlying most of these associations remain unresolved. Large genomic rearrangements, known as structural variants (SVs), represent a promising avenue for elucidating such mechanisms within some of these loci. METHODS: By leveraging data from two ongoing cohort studies of aging and dementia, the Religious Orders Study and Rush Memory and Aging Project (ROS/MAP), we performed genome-wide association analysis testing 20,205 common SVs from 1088 participants with whole genome sequencing (WGS) data. A range of Alzheimer's disease and other common age-related clinical and neuropathologic traits were examined. RESULTS: First, we mapped SVs across 81 AD risk loci and discovered 22 SVs in linkage disequilibrium (LD) with GWAS lead variants and directly associated with the phenotypes tested. The strongest association was a deletion of an Alu element in the 3'UTR of the TMEM106B gene, in high LD with the respective AD GWAS locus and associated with multiple AD and AD-related disorders (ADRD) phenotypes, including tangles density, TDP-43, and cognitive resilience. The deletion of this element was also linked to lower TMEM106B protein abundance. We also found a 22-kb deletion associated with depression in ROS/MAP and bearing similar association patterns as GWAS SNPs at the IQCK locus. In addition, we leveraged our catalog of SV-GWAS to replicate and characterize independent findings in SV-based GWAS for AD and five other neurodegenerative diseases. Among these findings, we highlight the replication of genome-wide significant SVs for progressive supranuclear palsy (PSP), including markers for the 17q21.31 MAPT locus inversion and a 1483-bp deletion at the CYP2A13 locus, along with other suggestive associations, such as a 994-bp duplication in the LMNTD1 locus, suggestively linked to AD and a 3958-bp deletion at the DOCK5 locus linked to Lewy body disease (LBD) (P = 3.36 × 10-4). CONCLUSIONS: While still limited in sample size, this study highlights the utility of including analysis of SVs for elucidating mechanisms underlying GWAS loci and provides a valuable resource for the characterization of the effects of SVs in neurodegenerative disease pathogenesis.

Humans↗

PubMed2026

Cross-kingdom genomic variation in chicken gut microbiomes: insights from China's diverse local breeds.

BACKGROUND: The gut microbiome possesses substantial genetic diversity that supports microbial adaptation, but the genomic variation patterns across its prokaryotic and viral populations remain incompletely characterized. RESULTS: Through integrated metagenomic and metatranscriptomic analysis of ten indigenous chicken breeds from China, we recovered 1527 representative prokaryotic MAGs, 37,555 representative DNA viral contigs, and 1867 representative RNA viral contigs (primarily comprising Bacillota/Bacteroidota, Uroviricota, and Lenarviricota/Pisuviricota, respectively). By integrating complementary short-read and long-read metagenomics with metatranscriptomics, we identified structural variants (SVs) and single-nucleotide variants (SNVs) in these cross-kingdom genomes. Positive SV-SNV density correlations occurred consistently across all microbial groups, indicating coordinated mutational processes. DNA viruses exhibited the highest variant prevalence (86.9% SNVs, 47.7% SVs), with temperate phages accumulating significantly more variants than virulent phages. Functionally, prokaryotic variants accumulated in carbohydrate metabolism and amino acid metabolism, while viral variants demonstrated broad metabolic hijacking. Horizontal gene transfer (HGT) was characterized by a strong virus-associated signature (69.40% of 536 events) and marked by an asymmetric pattern, with phage-to-bacteria (P-to-B) flow alone constituting 37.50% of all events. Random forest analysis revealed a strong bidirectional predictive relationship between SV and SNV densities across prokaryotic, DNA viral, and RNA viral populations, suggesting coupled genomic instability. Niche breadth emerged as a major driver of SNVs across kingdoms and was positively correlated with variant density. In prokaryotes, HGT events significantly shaped variant patterns. For viruses, genomic GC content was an important factor and consistently showed a negative correlation with SNV density in both DNA and RNA viruses. CONCLUSIONS: These findings demonstrate that coordinated mutational processes and kingdom-specific intrinsic factors drive genomic variation, with viruses serving as key genetic exchange vectors in chicken gut ecosystems. Video Abstract.

Animals↗

PubMed2026

RAG-mediated structural variation and its impact on relapse risk in acute lymphoblastic leukemia.

Relapse during treatment of B-cell acute lymphoblastic leukemia (B-ALL) is a harbinger of poor outcomes. Identifying biomarkers for subsequent relapse risk which are detectable at B-ALL diagnosis remains a priority. Off-target recombination-activating gene (RAG)-mediated structural variants (SVs) generate genomic instability that drives leukemogenesis and may underlie treatment resistance. Leveraging sequencing data in 1,496 pediatric B-ALL patients enriched for relapse status (relapse n=532; non-relapse n=964), we characterized RAG-mediated SVs across B-ALL molecular subtypes and examined their association with patient characteristics and their impact on clinical outcomes. Off-target RAG-mediated SVs were overall frequent, particularly in ETV6::RUNX1, ETV6::RUNX1-like, and Ph-like B-ALL subtypes, while increasing age-at-diagnosis was positively associated with burden of off-target RAG-mediated SVs (P<.001). Off-target RAG-mediated SVs with a recombination signal sequence (RSS) at one breakpoint, a hallmark of off-target RAG activity, were significantly more frequent at diagnosis in patients who subsequently relapsed (P=.001). This association remained significant in multivariable regression analysis (per SV odds ratio [OR]:1.08, 95%CI:1.04-1.12), in minimal residual disease (MRD)-negative patients (OR:1.09, 95%CI:1.04-1.14) and across subtypes. Excluding deletions, MRD-negative ETV6::RUNX1 patients with ≥3 off-target RAG-mediated SVs had a >3-fold risk of relapse (hazard ratio:3.47, 95% CI:1.86-6.49). RAG-mediated SVs were also associated with relapse risk in T-cell ALL patients. Off-target RAG-mediated SV burden at diagnosis is a risk factor of relapse in pediatric ALL across molecular subtypes and independent of MRD status.

Journal Article↗

PubMed2026

Structural variant discovery and diagnostic impact in rare diseases from short-read and long-read sequencing.

Rare diseases collectively affect 1 in 10 individuals, yet current genetic testing fails to identify a causal variant for most cases. At present, cytogenetic methods and/or sequencing approaches such as exome (ES) or short-read genome sequencing (srGS) represent the state-of-the-art for comprehensive clinical discovery of sequence and structural variants (SVs), including copy number variants, balanced SVs, complex SVs, and tandem repeats (TRs). Recently, long-read genome sequencing (lrGS), coupled with multiomics data, has presented great promise to resolve variation in genomic regions recalcitrant to characterization by srGS such as highly repetitive simple repeat sequences and segmental duplications. However, there are few guidelines to enable clinical interpretation of genetic variation in these highly repetitive genomic regions, and the enthusiasm of the field in adopting lrGS has made it difficult to assess the true added diagnostic yield of this technology due to widely variable and inconsistently applied analytic pipelines and variable degrees of pre-screening by ES or srGS. Here, we investigated the contribution of SVs to rare diseases using srGS as a front-line strategy when paired with highly sensitive SV discovery and evaluate the added diagnostic yield of incorporating lrGS for a subset of cases. Our srGS analysis encompassed 1,462 families (3,450 individuals) recruited through the Broad Institute Center for Mendelian Genetics and the Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) programs. Diagnostic SVs were identified in 5.4% of cases (79/1,462), of which 80% were uniquely detectable by srGS compared to standard cytogenetic techniques. For 96 families (including 10 families with a heterozygous variant observed in a known recessive gene of clinical relevance), we performed lrGS with methylation profiling, as well as long-read transcriptomic analyses in a subset of 20 trios. Analyses with lrGS yielded over 25,000 SVs per genome, 63% of which were not captured by srGS, along with an additional ~200 rare SNV/indels per genome not previously captured and 12 differentially methylated regions per genome. Among these, we identified only one diagnostic variant not interpreted by srGS, an apparently mosaic de novo SNV in CASK that was absent in the srGS callset due to allelic imbalance. No new diagnoses were supported by long-read transcriptomics or episignatures. In this well characterized rare disease cohort, the added diagnostic yield was thus 1.04% (1/96 families). Following a systematic literature review of prior lrGS studies, we find that most reported diagnoses were detectable by srGS and that our added diagnostic yield is consistent with those prior studies. These studies emphasize the significant impact of comprehensive SV discovery in rare disease cases and further demonstrate the power for increased discovery of novel genomic variation and episignatures from lrGS. Nonetheless, they also serve to temper expectations of dramatic diagnostic advances in rare disease patients until there is more extensive annotation of the functional and clinical impact of all coding and noncoding variation uniquely accessible to lrGS with extensive reference databases spanning highly repetitive genomic sequencing that could be enabled by this transformative technology.

Journal Article↗

PubMed2026

Chromosome-scale genome remodeling in tumor evolution: Copy number alterations and structural variants as two sides of the same coin.

Chromosome-scale genomic rearrangements are a dominant force in tumor evolution. Copy-number alterations (CNAs) and structural variants (SVs) constitute two complementary axes of this process. Although detection technologies now deliver near-comprehensive catalogs, technical resolution has outpaced conceptual integration. In this review, we frame CNAs and SVs as inextricable facets of chromosomal aberrations. They reshape cancer genomes through altered gene dosage and three-dimensional regulatory rewiring. CNAs quantify the gene-dosage imbalance, yet arise through mechanistically distinct routes. Segmental CNAs typically require chromosomal breakage, and therefore often coincide with SV junctions. By contrast, whole-chromosome aneuploidy and whole-genome doubling (WGD) primarily reflect mitotic or cytokinetic failure and can occur without local breakpoints, while nevertheless reshaping the karyotypic landscape and seeding subsequent structural complexity. SVs, in turn, range from unbalanced events that alter copy number to ostensibly balanced exchanges that predominantly rewire regulatory architecture. Despite their diverse and sometimes catastrophic architectures, SVs are ultimately rooted in double-strand break formation and error-prone resolution. By integrating CNAs and SVs within a unified mechanistic and functional framework, we aim to convert catalogs into concepts and distill the organizing principles that govern tumor genome evolution.

Humans↗

PubMed2026

The value of structural variants to conservation genomics in the pangenome era.

Structural variants (SVs) comprise an axis of genetic diversity with strong consequences for phenotype and fitness, making them a potentially important target for conservation genomics. Here, we review how and why SVs can play a role in conservation genomics; the different types of SVs and how they can affect phenotype; and how pangenomes and long-read sequencing are illuminating their evolution in populations, including small populations and those of conservation concern. SVs comprise multinucleotide mutations including insertions, deletions, transpositions, inversions, and other multinucleotide mutations, often overlapping genes and other functional genome regions. As a result, SVs often play important roles in phenotypic evolution and local adaptation and can contribute substantially to genetic load in inbred populations. However, our understanding of the factors influencing SV diversity in populations is still in its infancy and is complicated by the vast range of sizes, effects, and mechanisms of formation of these mutations. We argue that SVs are an important axis of genetic diversity which should be characterized alongside more traditional metrics of genetic diversity in conservation contexts. There are a number of analytical challenges to detecting and studying SVs, but analyses aimed at understanding the role of SVs in inbreeding load and population health are rapidly becoming realizable goals, accelerated by new technologies and analytical approaches. New tools, including population-scale long-read sequencing and pangenome approaches, are beginning to make SVs accessible in ways which can be readily applied in conservation settings.

Genomic Structural Variation↗

PubMed2026

The Rise of Plant Pan-Genomes: From Genome Variation to Predictive Breeding.

Plant pan-genomics is entering a new phase beyond genome variation discovery, requiring a shift from cataloguing genomic diversity toward understanding how variation generates biological function and breeding value. Here, we propose that the future of plant pan-genomics will be shaped by three conceptual transitions. First, structural variation (SV), presence-absence variation (PAV), and haplotype diversity should be interpreted not merely as genomic differences, but as regulatory components that influence gene networks, chromatin organization, and complex traits. Second, the expansion from species-level pan-genomes to genus-level super pan-genomes provides an evolutionary framework for uncovering adaptive genetic modules preserved in wild relatives and overlooked during domestication. Third, integrating pan-genomes with pan-omics, three-dimensional genome analyses, and artificial intelligence will enable the transformation of genomic variation into predictive models for crop improvement. We further propose that the ultimate value of pan-genomes lies not in generating increasingly complete genome collections, but in establishing a mechanistic bridge between genome diversity, biological function, and breeding decisions. This transition will move crop improvement from empirical selection toward rational genome design, where evolutionary diversity can be systematically interpreted, predicted, and engineered.

Journal Article↗

PubMed2026

Dissecting genetic architecture and improving machine learning‑based genomic prediction of flowering time in Osmanthus fragrans by integrating structural variants.

Sweet osmanthus (Osmanthus fragrans), a traditional ornamental plant in China, exhibits substantial variation in autumn flowering time, which significantly affects landscape application and cultivation efficiency. Here, we performed a genome-wide association study on 127 resequenced accessions classified into early, intermediate, and late flowering types, using a set of 2,325,410 single-nucleotide polymorphisms (SNPs) and 246,824 structural variants (SVs). By integrating SNP/insertion and deletion (Indel) and SV data with weighted gene co-expression network analysis, machine learning, and genomic prediction, we dissected the genetic architecture of flowering time. We identified 24 associated SNP/Indels and six SVs, mapping to 30 candidate genes, including known flowering regulators FLK, LOS1, Y14, MIF2, and GID1B. These genes showed tissue-specific expression, with some responding to low temperature. The two hub genes, GUX1 and LYG027904, were located within modules of the co-expression network associated with low-temperature treatment. Haplotype analysis revealed a specific three-SNP haplotype associated with late flowering and linked to LOS1, and epistatic interactions among combined genotypes contributed to phenotypic variation. Notably, integrating SVs with SNP/Indels improved genomic prediction accuracy; the gradient boosting decision tree model outperformed other machine learning algorithms, achieving a mean accuracy of 0.859 and an AUC > 0.8 (where AUC is area under receiver operating characteristic curve) for all flowering types. These findings provide insights into the genetic mechanisms underlying flowering time variation in O. fragrans, offer candidate genes and haplotypes for molecular breeding, and highlight the value of integrating SVs with machine learning for genomic prediction in woody ornamentals.

Machine Learning↗

PubMed2026

Pan-genome characterization of the maize 4CL gene family and its dynamic responses to abiotic stress.

1.Pan-genome analysis across 26 maize inbred lines identified 13 Zm4CL genes (nine core and four near-core) classified into three evolutionary clades.2.Structural variations (SVs) are significantly associated with the expression and altered conserved protein domains of key Zm4CL genes.3.Zm4CL genes exhibit distinct tissue-specific expression patterns and dynamic enzymatic and transcriptional responses to stresses, particularly cold and drought.4-Coumarate:CoA ligase (4CL) is a key enzyme in the phenylpropanoid pathway and plays important roles in plant growth, development, and responses to environmental stresses. However, a comprehensive pan-genome analysis of the 4CL gene family in maize is still lacking. In this study, 13 Zm4CL genes were identified from a maize pan-genome comprising 26 diverse inbred lines, including nine core genes and four near-core genes. Phylogenetic analysis classified these genes into three evolutionary clades, while Ka/Ks analysis indicated that most members have been maintained under purifying selection, although several genes exhibited greater evolutionary divergence and relatively relaxed evolutionary constraints. Structural variation (SV) analysis revealed significant associations between SVs and the expression of Zm4CL2 and Zm4CL3, while sequence comparisons suggested that SVs were also associated with alterations in conserved protein domains in some genotypes. Transcriptome analyses revealed distinct tissue-specific expression patterns and diverse transcriptional responses to abiotic and biotic stresses. Enzyme activity assays showed that cold stress significantly increased 4CL activity at 12 h, whereas heat, salt, and alkali stresses caused an initial decrease followed by recovery, while drought had no significant effect. Time-course RT-qPCR further validated dynamic expression changes of representative Zm4CL genes under cold and drought stresses. Overall, this study provides a comprehensive pan-genome framework for understanding the evolutionary conservation, regulatory diversification, and stress-responsive characteristics of the maize Zm4CL gene family, providing valuable resources for future functional studies and the genetic improvement of stress tolerance in maize.

Zea mays↗

PubMed2026

Robot-assisted versus manual percutaneous vascular interventions across vascular territories: a systematic review and meta-analysis.

Robot-assisted percutaneous vascular intervention (R-PVI) has expanded beyond coronary procedures, but previous reviews were largely coronary-focused and observational. Recent randomized controlled trials (RCTs) warrant broader reassessment of R-PVI versus manual percutaneous vascular intervention (M-PVI) across vascular territories. PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials were searched from database inception to January 31, 2026, following PRISMA guidelines. RCTs and observational studies including ≥10 adult patients in total were eligible. Comparative studies informed primary analyses, while single-arm studies provided supportive evidence. Primary outcomes were clinical success rate and major adverse cardiovascular/cerebrovascular events (MACE) rate. Secondary outcomes included mortality rate, technical success rate, procedural time metrics, contrast volume, and radiation exposure. Random-effects models were used. Forty studies were included: 3 RCTs, 10 comparative observational studies, and 27 single-arm observational studies, comprising 3,870 patients undergoing R-PVI and 1,142 undergoing M-PVI. Comparative analyses showed similar clinical success rates (RR 1.00, P = 0.46), MACE rates (RR 0.72, P = 0.43), and mortality. Single-arm pooled estimates for clinical and technical success were 98.76% and 96.09%, respectively. R-PVI prolonged total procedure time overall (MD 15.92 min, P = 0.01), with consistent increases in the neurovascular, RCT, and non-RCT subgroups. Fluoroscopy time was also longer (MD 1.91 min, P = 0.04), mainly in the RCT subgroup (MD 2.83 min, P = 0.001). In contrast, intravascular intervention time was unchanged overall and in RCTs, but was prolonged in non-RCTs (MD 8.72 min, P = 0.006). Operator radiation exposure was markedly reduced (MD -33.97 μSv, P < 0.001), whereas patient radiation exposure and contrast volume were similar. R-PVI appears feasible and safe across selected vascular procedures. Its clearest benefit is reduced operator radiation exposure, whereas lower whole-procedure efficiency remains its main limitation.

Humans↗

PubMed2026

Evaluating the pathogenic significance of unique chromosomal variants in craniosynostosis using patient-derived induced pluripotent stem cells and mouse modelling.

PURPOSE: Unravelling causal links between unique structural/copy-number variants (SV/CNV) and associated phenotypes is essential for correct genetic counselling. We investigated two families in which patients with craniosynostosis had SV/CNV potentially dysregulating a fibroblast growth factor (FGF)-encoding gene; a 730 kb dup(4)(q21.21) including FGF5; and a complex 568 kb interspersed 13q12.11 duplication, located 841 kb from FGF9. METHODS: We combined bioinformatic predictions of altered topologically-associating domain (TAD) structure, with experimental analysis (RNA- and ATAC- [assay for transposase-accessible chromatin] sequencing) of patient induced pluripotent stem cell lines (iPSCs) differentiated to neural crest (NCC) and osteoprogenitor (OPC) identities. For the dup(4)(q21.21) we generated a mouse bearing an equivalent rearrangement using CRISPR-Cas9 targeting. RESULTS: TAD analysis suggested potential dysregulation of the FGF5/FGF9 gene by bringing it into a novel genomic milieu. The RNA- and ATAC-seq assays demonstrated FGF5/FGF9 upregulation (2.7-18x) and local opening of chromatin, in 3/4 cell lines. For the dup(4)(q21.21), a causal role was supported by the mouse model, whereas interpretation of the 13q12.11 SV is confounded by a co-existing FOXP2 pathogenic variant. CONCLUSION: Patient iPSC-differentiated NCC and OPC lines, combined with TAD-based modelling to generate testable functional hypotheses, provide valuable functional evidence when evaluating causation of unique SV/CNV in craniosynostosis.

copy-number variant↗

PubMed2026

Long-read Sequences Mapped to a Complete Reference Genome Uncover Uncaptured Structural Variants across the Beta-globin Cluster in Africans with Sickle Cell Disease.

African genomes are marked by extensive complexity in the number and distribution of variants, yet remain under-represented in genetic databases and the human reference genome. This gap in representation limits the broad application of genomic medicine. Sickle cell disease (SCD) - one of the most common monogenic diseases - has its highest prevalence in Africa, and variation in disease severity has consistently been linked to the beta-globin locus, including levels of fetal hemoglobin (HbF). Modulation of HbF is central to current SCD gene therapies; however, the inherent complexity and variation at the locus in African genomes presents a challenge to translating these advances to Africa. Here, we align long-read single molecule sequences (LRS) targeted to the beta-globin region to the hg38 and T2T-CHM13v2 genome references in 40 individuals with SCD, predominantly recruited from three African countries. We demonstrate that the expanded T2T-CHM13v2 reference sequence at this locus reduces Structural Variant (SV) calls by 70% and uncovers uncaptured single nucleotide variants (SNVs). Across the cluster we report 343 SVs and 196 SNVs that have not been previously reported, including in LRS data from the All of Us project. By including African populations from ethnolinguistic groups that have not been previously surveyed we improve variant resolution and bolster evidence for observed variation. Finally, we identify a common ∼4kb insertion locus overlapping the HBB promoter among individuals with high HbF. These results demonstrate the utility of combining a comprehensive reference genome with LRS in African populations to uncover genomic variation at disease-associated loci.

SNV↗

PubMed2025

Complex de novo structural variants are an underestimated cause of rare disorders.

Complex de novo structural variants (dnSVs) are crucial genetic factors in rare disorders, yet their prevalence and characteristics in rare disorders remain poorly understood. Here, we conduct a comprehensive analysis of whole-genome sequencing data of 12,568 families, including 13,698 offspring with rare diseases, obtained as part of the UK 100,000 Genomes Project. We identify 1,870 dnSVs, constituting the largest dnSV dataset reported to date. Complex dnSVs (n = 158; 8.4%) emerge as the third most common type of SV, following simple deletions and duplications. We classify 65% of these complex dnSVs into 11 subtypes. Among probands with dnSVs (n = 1,696), 9% exhibit exon-disrupting pathogenic dnSVs associated with the probands' phenotype. Notably, 12% of exon-disrupting pathogenic dnSVs and 22% of de novo deletions or duplications previously identified by array-based or whole-exome sequencing methods are found to be complex dnSVs. We also find distinct genomic properties of de novo deletions depending on the parent of origin. This study highlights the importance of complex dnSVs in the cause of rare disorders and demonstrates the necessity of specific genomic analysis to avoid overlooking these variants.

Humans↗

PubMed2026

Analysis of deep-resequencing data of 984 soybean accessions reveals structural variations underlying agronomic traits.

Genomic structural variants (SVs) are major sources of genetic variation and have profound impacts on phenotypic traits. However, their functional effects remain largely unexplored in soybean. Here, we resequence 940 soybean accessions. Together with 44 publicly available datasets, we identify 602,281 SVs. Using a graph-based genome, we detect an additional 58,760 presence/absence variations (PAVs) that broadly affect gene expression. Population genomic analyses reveal that SVs serve as a core driving force for soybean domestication and improvement. Integrating SVs with QTLs for oil and protein content, and performing GWAS on 27 traits, we identify key functional SVs. These include transposable element insertions altering seed coat color, multiple insertions within a cytochrome P450 gene modifying flower and hypocotyl color, and a GmMATE1 deletion enhancing seed size. Together, our study establishes a comprehensive SV map of soybean, offering a valuable resource for dissecting the genetic basis of complex traits to accelerate molecular breeding.

Glycine max↗