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PubMed2026

Integrating Optical Genome Mapping into the Genetic Diagnostic Algorithm: Clinical Utility in Unresolved Autosomal Recessive Disorders from a Large Cohort.

INTRODUCTION: The identification of precise genetic etiologies is indispensable for the clinical management of monogenic disorders. However, conventional diagnostic methods and exome sequencing (ES) frequently fail to identify complex structural variations (SVs), leaving the genetic basis unexplained in approximately 30-60% of suspected cases. Optical genome mapping (OGM) emerges as a high-resolution technology capable of detecting cryptic SVs inaccessible to standard methodologies. METHODS: In this study, we evaluated the clinical utility of integrating OGM into the diagnostic algorithm for unresolved monogenic diseases. Following negative or inconclusive results from standard ES pipelines, OGM was applied to a targeted subset of patients (n = 7) selected from a comprehensive clinical cohort of 1,257 individuals with suspected genetic disorders. RESULTS: The integration of OGM identified candidate SVs that may represent the second allelic alteration in two distinct cases; however, confirmation through parental segregation analysis remains pending. Specifically, OGM identified an intronic insertion in the TTLL5 gene and a deletion in a putative regulatory region approximately 400 kb upstream of the NMNAT1 gene, both of which were missed by prior diagnostic testing. CONCLUSION: Our findings suggest that OGM has potential value in investigating the missing heritability of autosomal recessive disorders. By detecting candidate SVs invisible to conventional methods, OGM may warrant consideration as a complementary diagnostic approach following inconclusive ES; however, larger cohorts and confirmatory functional studies are needed to establish its clinical utility.

Autosomal recessive disorders↗

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

Genome-wide variation analysis of two Salvia hispanica L. genotypes and implication for associations with metabolic and adaptive traits.

BACKGROUND: Advances in next-generation sequencing have accelerated genome-wide exploration of genetic diversity in underutilized oilseed crops. Salvia hispanica L. (chia), a high-nutrient pseudocereal rich in omega-3 fatty acids, is increasingly valued for its health benefits and commercial potential, yet it remains poorly characterized at the genomic level. Understanding the scale and nature of genomic variation is essential for improving complex traits such as oil yield, stress tolerance, and seed quality. METHODS: Two contrasting chia genotypes, Black-chia (CACH-B) and White- chia (CACH-W), were resequenced using the Bio-Resequencing Toolkit (BRT) pipeline. High-coverage sequencing, with a mapping rate exceeding 99% and an average depth of approximately 28×, facilitated the detection and annotation of single-nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy-number variations (CNVs), and structural variants (SVs). The functional classification of variant impacts enabled the identification of genes potentially linked to metabolic and adaptive traits. RESULTS: A total of 1.97 million SNPs, 401,493 InDels, 836 CNVs, and 15,288 SVs were identified across the chia genome. Notably, approximately 53% of exonic SNPs were non-synonymous (dN/dS ≈ 1.28), predominantly affecting lipid metabolism, transcriptional regulation, and stress response pathways, potentially altering key agronomic traits. In addition, CNV hotspots were concentrated in chromosomes 3 and 6, overlapping MYB, WRKY, and bZIP transcription factor loci, may potentially be involved in stress tolerance and yield. Furthermore, structural rearrangements, including inversions and duplications within the FAD2, FAD3, and CYP450 gene clusters, were potentially associated with seed pigmentation and omega-3 biosynthesis, pointing to their potential breeding relevance. Observed heterozygosity (Hₒ ≈ 0.71) and nucleotide diversity (π ≈ 7 × 10-3) indicated moderate to high allelic richness. In addition, the low FST value (0.038) indicates substantial genomic similarity between the two genotypes. CONCLUSION: This study presents the first comprehensive map integrating SNPs, CNVs, and SVs in S. hispanica L. The results reveal a structurally dynamic genome characterized by substantial sequence and structural variation, providing valuable insights into genomic diversity and potential adaptive mechanisms in chia. The coexistence of high SNP diversity and abundant structural variation underpins chia's nutritional specialization and environmental resilience. These results deliver a foundational genomic resource for marker-assisted breeding, genome-wide association studies, and the development of climate-resilient chia cultivars.

Copy-number variation, structural variation↗

PubMed2026

Analysis of 14q12 microdeletions reveals novel regulatory loci for the neurodevelopmental disorder-related gene FOXG1.

Up to 17% of neurodevelopmental disorders (NDDs) can be explained by pathogenic structural variants (SVs) that disrupt coding regions and elicit gene dosage defects. However, noncoding SVs which can perturb cis-regulatory elements (CREs) and downstream gene expression are understudied. In this study, we describe multiple 14q12 deletions downstream of NDD-related gene FOXG1 in individuals with overlapping phenotypes of FOXG1 haploinsufficiency. We show that deletion of a minimum region of overlap (MRO) reduced FOXG1 expression, disrupted CREs and altered FOXG1's native genomic interactions. Deleting the MRO did not fully eliminate FOXG1 expression, indicating that multiple CREs likely cooperate to regulate FOXG1 and would need to be deleted to completely prevent expression. The transcriptomic profiles of MRO loss overlap in part with FOXG1 loss, including direct FOXG1 targets, indicating converging molecular pathways. These findings expand the scope of FOXG1's complex regulatory region, and more broadly, of regulatory SVs in NDD susceptibility.

Forkhead Transcription Factors↗

PubMed2024

De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.

Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We developed a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implemented it in the SuPreMo-Akita software (Gjoni and Pollard 2024). With this tool, we ranked hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This revealed that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritized candidate variants that disrupt ASD CREints and validated our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study establishes disrupted genome folding as a potential genetic mechanism in ASD and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.

Journal Article↗

PubMed2025

The landscape of structural variation in pediatric cancer.

Structural variants (SVs) account for over 60% of the driver variants in pediatric cancer, and in many cases act as the cancer initiating event. To study SVs from a pan-cancer perspective, we analyzed 1,616 pediatric cancer genomes in 16 major cancer types of hematological malignancies (n = 908), brain tumors (n = 183), and solid tumors (n = 525) and compared their profiles to those of 2,203 adult cancers. The SV burden varied ~100-fold across pediatric cancer types and demonstrated an 8- to 16-fold reduction compared to adult brain and solid tumors but was comparable in pediatric versus adult hematological malignancies. Recurrent SV hotspots occurred uniquely in pediatric acute lymphoblastic leukemias (ALLs) in proximity to RAG-mediated recombination signal sequences (RSS) and disrupted multiple immune-related loci as well as 69 genes, which often involved cryptic RSS sites. By contrast, such hotspots affected only immune-related loci but not driver genes in adult lymphoid cancers. Eight SV signatures extracted from the cohort had varying distributions across cancer types, with clustered translocations reflecting templated insertions in osteosarcoma, and medium-sized deletions (10 kb to 1 Mb) enriched in cancers with RAG-mediated deletions. Intra-patient evolutionary analysis in 13 patients with multiple spatiotemporally distinct samples revealed that RAG-mediated recombination in leukemia and complex rearrangements in solid tumors occurred both early in disease initiation and continuously during later diversification, contributing to clonal heterogeneity. Finally, we found that both driver genes and fragile sites were the two genomic regions most frequently disrupted by SVs. The unique and diverse SV landscapes that emerged from this comprehensive analysis expand the scope of RSS-mediated mutagenesis in pediatric ALL and will be a valuable resource for guiding future functional studies and the design of clinical genomic testing in pediatric cancer.

Journal Article↗

PubMed2025

Comprehensive benchmarking of somatic structural variant detection at ultra-low allele fractions.

Postzygotic mosaicism gives rise to somatic structural variants (SVs) at ultra-low variant allele fractions (VAFs), which pose challenges for detection due to the high-coverage sequencing required and noise introduced by sequencing artifacts. Although somatic SV detection has been extensively studied in cancer, these studies are not directly applicable to the study of tissue mosaicism, as they rely on matched normals, target higher VAF ranges, and are enriched for different types of SVs. We present comprehensive benchmark data and best practices for non-cancer somatic SV detection. We created a synthetic mosaic sample by combining six HapMap individuals at varying proportions, generating allele fractions as low as 0.25%. This sample was sequenced to ~2,300x total coverage using Illumina, PacBio, and Nanopore technologies across multiple sequencing centers. A high-confidence benchmark SV set containing over 21,000 pseudo-somatic insertions and deletions ≥50bp was derived from haplotype-resolved assemblies. We evaluated 12 SV discovery pipelines and identified caller-specific strengths and sequencing platform-specific shortcomings. We find that short read-based approaches show reduced recall for insertions and repeat-associated SVs, whereas long-read sequencing achieves high accuracy throughout the genome, increasing linearly with coverage. The best algorithm's sensitivity exceeded 80% for VAFs ≥4% and 15% for VAFs of 0.5-1% with 60x coverage. The publicly available benchmarking data and comparative analysis of current methods provide a foundation for robust discovery of SV mosaicism in non-cancer tissues..

Journal Article↗

PubMed2026

De novo structural variants in autism spectrum disorder disrupt distal regulatory interactions of neuronal genes.

Three-dimensional genome organization plays a critical role in gene regulation, and disruptions can lead to developmental disorders by altering the contact between genes and their distal regulatory elements. Structural variants (SVs) can disturb local genome organization, such as the merging of topologically associating domains upon boundary deletion. Testing large numbers of SVs experimentally for their effects on chromatin structure and gene expression is time and cost prohibitive. To address this, we propose a computational approach to predict SV impacts on genome folding, which can help prioritize causal hypotheses for functional testing. We develop a weighted scoring method that measures chromatin contact changes specifically affecting regions of interest, such as regulatory elements or promoters, and implement it in the SuPreMo-Akita software. With this tool, we rank hundreds of de novo SVs (dnSVs) from autism spectrum disorder (ASD) individuals and their unaffected siblings based on predicted disruptions to nearby neuronal regulatory interactions. This reveals that putative cis-regulatory element interactions (CREints) are more disrupted by dnSVs from ASD probands versus unaffected siblings. We prioritize candidate variants that disrupt ASD CREints and validate our top-ranked locus using isogenic excitatory neurons with and without the dnSV, confirming accurate predictions of disrupted chromatin contacts. This study suggests that disrupted genome folding is a potential genetic mechanism in a subset of ASD cases and provides a general strategy for prioritizing variants predicted to disrupt regulatory interactions across tissues.

Humans↗

PubMed2026

A pangenome framework uncovers the role of deletions in repeated evolution of cave-derived traits.

Structural variants (SVs) are increasingly recognized as key contributors to adaptive evolution, yet they remain underexplored compared with single-nucleotide variation. To understand how large-scale genomic changes shape repeated evolution, we leveraged multiple levels of sequence data across the powerful evolutionary model system of the Mexican tetra fish (Astyanax mexicanus). We constructed one of the first pangenome graphs from a naturally evolving vertebrate, enabling comprehensive discovery of SVs among 120 fish from 11 populations. We discover substantial amounts of structural variation and explore the roles of genomic biases and selection in shaping the distribution of these variants. More than 2400 high-confidence cave-specific deletions are enriched in biological pathways involved in vision, metabolism, and behavior and cluster nonrandomly in quantitative trait loci linked to cavefish traits. Additionally, 67 genes harbor unique deletions between independent cavefish lineages. These reused genes show evidence of population-specific selection (99% contain selective sweeps compared with 8%-15% in genes lacking SVs), indicating that deletions likely rose in frequency through repeated positive selection rather than drift. Together, these results reveal that recurrent deletion events have repeatedly contributed to the evolution of cave-adapted phenotypes and highlight deletions as underexplored contributors of adaptive evolution in extreme environments.

Animals↗

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

Molecular residual disease assessment in colorectal and bladder cancer by somatic structural variant analysis of cell-free DNA whole-genome sequencing data.

BACKGROUND: Whole-genome sequencing (WGS)-based methods for circulating tumor DNA (ctDNA) detection typically rely on tumor-informed identification of somatic single nucleotide variants (SNVs). Somatic structural variants (SVs) are another type of cancer-specific genomic alteration, which owing to their larger genomic footprint and unique breakpoint junctions, are easier to distinguish from sequencing noise than SNVs. They are, however, rarely used for ctDNA detection because of (1) artifacts from WGS procedures that SV callers may falsely interpret as genuine SVs. This makes it difficult to establish high-confidence SV catalogos from short-read tumor WGS and can cause false-positive ctDNA detections. (2) Lack of robust strategies to quantify SV-supporting reads in plasma WGS. To address these barriers and enable integration of SV biomarkers into WGS-based ctDNA detection, we present a bioinformatic framework for algorithmic curation of somatic SV calls from fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tumors, coupled with a novel approach for sensitive, accurate mapping and quantification of SV breakpoint-supporting reads in plasma WGS. METHODS: Tumor, normal and plasma WGS data from 144 patients with stage III colorectal cancer was used to establish the bioinformatic framework. This included ~30x WGS data from 1564 serially collected plasma samples. The framework was validated using tumor/normal/plasma WGS data from 32 patients with muscle-invasive bladder cancer. SV-based ctDNA detection was benchmarked against previously published SNV-based ctDNA results for the same samples. RESULTS: After curation of SV calls and quantification in plasma WGS, our SV-based approach enabled robust ctDNA detection with overall specificity exceeding 99% in plasma samples. Furthermore, we observed strong concordance (Pearson’s r > 0.93, p < 2.2 × 10− 16) between ctDNA-positive samples identified by our SV-based method and previous SNV-based analyses, validating the reliability of our approach. Finally, we demonstrated application of the method in an independent bladder cancer cohort, highlighting its generalizability and potential clinical use. CONCLUSIONS: We provide a bioinformatic framework that establishes somatic SVs as ultra-specific biomarkers for WGS-based, tumor-informed ctDNA detection. The approach delivers specific detection even when the SV catalogos are established from FFPE samples. The SV framework can stand alone or enhance SNV-based analysis pipelines.

Humans↗

PubMed2025

The causal relationship between steroid hormones and risk of stroke: evidence from a two-sample Mendelian randomization study.

It is unclear how steroid hormones contribute to stroke, and conducting randomized controlled trials to obtain related evidence is challenging. Therefore, Mendelian randomization (MR) technique was employed in this study to examine this association. Through genome-wide association meta-analysis, the genetic variants of steroid hormones, including testosterone/17β-estradiol (T/E2) ratio, aldosterone, androstenedione, progesterone, and hydroxyprogesterone, were acquired as instrumental variables. Analysis was done on the impact of these steroid hormones on the risk of stroke subtypes. The T/E2 ratio was associated to an elevated risk of small vessel stroke (SVS) according to the inverse variance weighted approach which was the main MR analytic technique (OR, 1.23, 95% CI: 1.05-1.44, p = 0.009). These findings were solid since no heterogeneity nor horizontal pleiotropy were found. The causal association between T/E2 and SVS was also confirmed in the replication study (p = 0.009). Nevertheless, there was no proof that other steroid hormones increased the risk of stroke. According to this study, T/E2 ratio and SVS are causally related. However, strong evidence for the impact of other steroid hormones on stroke subtypes is still lacking. These findings may be beneficial for developing stroke prevention strategies from steroid hormones levels.

Mendelian Randomization Analysis↗

PubMed2026

Targeted long-read genomic and epigenomic profiling enhances timely comprehensive variant discovery in hypotonia and muscle weakness.

BACKGROUND: Identifying the genetic basis of hypotonia and muscle weakness is critical for patient management and family counseling. However, diagnosis is often hindered by diverse genomic alterations, including repeat expansions, structural variants (SVs), and methylation defects. Standard-of-care testing, largely based on short-read sequencing, is limited in its ability to detect this heterogeneous variation landscape, leaving many patients undiagnosed or requiring lengthy sequential testing. Long-read sequencing represents a promising solution. However, its application as a first-tier diagnostic assay for hypotonia remains unexplored. METHODS: We retrospectively analyzed 227 patients with hypotonia to assess diagnostic yield, time-to-diagnosis, and costs associated with standard-of-care testing. A long-read whole-genome sequencing (LR-WGS) workflow with targeted analysis of hypotonia-associated genes was developed to detect and prioritize pathogenic SNVs, SVs, and CNVs, repeat expansions, and methylation changes at key disease loci. The workflow was validated in a reference-positive cohort with known diagnoses (n = 15) and applied to an unsolved cohort (n = 14). Variant interpretation followed ACMG guidelines and was confirmed with orthogonal methods. RESULTS: Standard-of-care testing achieved a diagnostic yield of 42% with an average time-to-diagnosis of 68.7 days; however, 30% of diagnosed patients experienced significant delays (average 169 days) due to sequential testing. The LR-WGS based approach identified all known pathogenic variants in the positive cohort, including SMN1 deletions, methylation defects at 15q11.2/Prader-Willi locus, FMR1 repeat expansions, and sequence and copy-number variants in > 100 genes underlying myopathies and muscular dystrophies. The targeted long-read pipeline reduced prioritized variant calls by 97.9-99.9% and, in the unsolved cohort, yielded one definitive diagnosis (de novo COL6A3 deletion) and one possible diagnosis (aberrant methylation and copy number at POMK), for an additional 14% yield. Among patients diagnosed after sequential testing (n = 29), LR-WGS is expected to reduce time-to-diagnosis by ~ 85% and decrease cumulative diagnostic delays, with projected healthcare cost savings of $396,000-439,000. Across the entire 227 patient cohort, LR-WGS is anticipated to reduce testing costs by 6.5%, yielding an average savings of $105 per patient. CONCLUSIONS: LR-WGS enables comprehensive discovery of genomic and epigenomic variants in hypotonia and muscle weakness, improving diagnostic yield, shortening diagnostic timelines, and reducing costs compared with current standard-of-care testing.

Humans↗

PubMed2026

Optical genome mapping enhanced by refined variant interpretation in pediatric acute lymphoblastic leukemia.

Reliable detection of structural variants (SVs) and copy number variations (CNVs) is crucial in the contemporary diagnostics of pediatric B-cell acute lymphoblastic leukemia (B-ALL). However, limitations of commonly used conventional and molecular cytogenetic methods may hinder the accurate genetic characterization of patients. Optical genome mapping (OGM) offers a reliable alternative by enabling high-resolution, genome-wide detection of CNVs and SVs. Chromosomal aberrations were screened using OGM in 51 children with B-ALL. The results were compared with those of karyotyping, fluorescence in situ hybridization (FISH), digital multiplex ligation-dependent probe amplification (digitalMLPA), and targeted RNA sequencing (RNA-seq). OGM data showed high congruency with karyotyping and FISH findings, detecting clinically relevant variants beyond G-banding results and unraveling a complex KMT2A fusion undetected by FISH. Gene fusions involved in complex ETV6::RUNX1 translocations, but not detected by RNA-seq, were confirmed using FISH. Normalization of OGM copy number values with DNA-index-improved concordance with FISH-derived copy numbers in near-tri/tetraploid cases. In the peripheral regions of OGM variants (fringe-zones), a novel evaluation strategy called 'FriZone' was applied, which significantly improved the concordance between OGM and digitalMLPA. In addition, a co-segregation analysis revealed strong associations between ETV6::RUNX1 fusion and deletions of ETV6, RAG2, and NR3C2. OGM uncovered complex rearrangements undetected by widely used methods in 15% of cases, improving genetic classification and risk stratification in 10% of the patients. The FriZone analysis and normalization by DNA-index provide a refined, more accurate approach to OGM variant interpretation, facilitating the efficient application of OGM in clinical diagnostics. © 2026 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Humans↗

PubMed2026

Longitudinal ctDNA tracking in early and recurrent breast cancer using an ultrasensitive structural variant-based assay: an extended analysis from the TRACER study.

BACKGROUND: Detection of circulating tumor DNA (ctDNA) following curative-intent therapy is prognostic of disease recurrence in early-stage breast cancer (EBC). An ultrasensitive structural variant (SV)-based ctDNA assay was evaluated previously in a 100-patient EBC cohort treated with neoadjuvant therapy, demonstrating high sensitivity, specificity, and a long lead-time to relapse. The stability of primary tumor-specific SVs at and after metastatic recurrence and their utility for longer-term ctDNA monitoring had not been established. PATIENTS AND METHODS: An updated retrospective analysis of ctDNA dynamics was conducted in an expanded cohort of 121 patients with EBC treated with neoadjuvant therapy. Plasma samples were collected at key clinical timepoints and serially in several patients who experienced metastatic recurrence. Clinical variables were abstracted from medical records. Associations between ctDNA detection, dynamics, and clinical outcomes were evaluated in the early-stage and metastatic settings. RESULTS: Thirty of 121 patients experienced clinical recurrence (28 distant, 2 local) over a median follow-up of 4.2 years (range 0.5-8.8; 25 ctDNA evaluable with adjuvant timepoints). All patients with detectable ctDNA in the adjuvant setting developed metastatic recurrence (22/22). Median lead time from ctDNA detection to metastatic recurrence was 346 days (range 0-1937). Among recurrent cases, 79% of primary tumor-specific SVs (n = 17 patients, tumor fraction ≥0.1%) remained detectable in plasma [range 7% (1/14 SV)-100% (15/15); median: 92%]. ctDNA dynamics in the recurrent metastatic setting demonstrated a strong relationship with radiographic outcomes in evaluable patients (n = 9). CONCLUSION: This SV-based digital PCR assay provided ultrasensitive ctDNA detection in an expanded EBC cohort, maintaining 100% positive predictive value for metastatic recurrence. In patients with recurrence, ctDNA dynamics were concordant with radiographic outcomes. Prospective studies evaluating the clinical utility of longitudinal ctDNA monitoring are warranted.

MRD↗

PubMed2026

Optimizing GRIDSS for clinical use: A targeted NGS filtering strategy for germline structural variant detection.

Detecting intermediate-sized structural variants (SVs) remains challenging in diagnostics, as tools for single-nucleotide and copy-number variants, particularly read-depth-based methods, are often insufficient. GRIDSS addresses this gap by integrating paired-end mapping, split-read analysis, and assembly-based approaches. However, its use in targeted sequencing and diagnostic workflows remains complex. NGS panel data from 9726 patients with suspected hereditary cancer were analyzed using GRIDSS. A filtering strategy was developed to prioritize clinically relevant germline SVs. Multiple parameter settings were tested to optimize performance. The initial dataset of 1,307,592 variants was reduced to 89 candidates after applying the selected filtering strategy. Of these, 24 had been previously detected by routine callers and were not further analyzed. Among the remaining 65, 13 were considered likely true positives after visual inspection using IGV. Experimental validation was performed by Sanger/Nanopore long-read sequencing for these variants, all of which were confirmed. Eight were classified as (likely) pathogenic, including two frameshift duplications in MSH6, one splicing variant in BARD1, and five mobile element insertions in APC, BRCA2, and PALB2. Altogether, GRIDSS implementation increased diagnostic yield while maintaining feasibility for diagnostic workflows. Comprehensive workflow scheme for germline structural variant detection and results in our diagnostic setting.

Humans↗

PubMed2026

Genomic and genetic dissection underlying seedling drought resilience in oats.

Drought threatens global crop yields, and common oat, a vital nutritional source for food and feed, is particularly constrained in the semi‑arid regions where it is widely cultivated. Here, we report two high-quality genome assemblies for drought-resilient (Borris37) and drought-sensitive (XymC06) oat accessions with distinct seedling survival rates and genome sizes of 10.92 Gb and 10.96 Gb, and construct comprehensive landscapes of insertion‑deletions (InDels) and structural variants (SVs). Integrating population-level genomic, transcriptomic and phenotypic (seedling survival rate), we demonstrate that InDels and SVs underpin divergent drought resilience and identify 52 candidate genes associated with drought resistance whose expression is significantly modulated by these variants. Borris37 accumulates 36 favorable alleles of these genes. An InDel in the AsNF-YB3 promoter enhances binding to AsARF1, upregulating AsNF‑YB3 under drought, and overexpression of AsNF‑YB3 reduces ROS accumulation. Our findings provide resources and targets for drought‑resistance breeding in oat, thereby supporting global food security.

Drought Resistance↗

PubMed2025

OctopuSV and TentacleSV: a one-stop toolkit for multi-sample, cross-platform structural variant comparison and analysis.

MOTIVATION: Structural variants (SVs) influence gene regulation, disease progression, and diagnostics, yet integrating SV calls across platforms remains difficult due to inconsistent annotations, limited merging flexibility, and fragmented workflows. Ambiguous breakend (BND) annotations, which comprise many variant calls, are often discarded or misclassified, hindering variant characterization. Existing tools lack advanced merging operations essential for precise identification of disease-specific or somatic variants across samples or patient groups. Additionally, current SV analysis pipelines require extensive manual intervention and complex parameter tuning, compromising reproducibility and scalability. Addressing these gaps is crucial for improving the accuracy, interpretability, and clinical utility of SV analyses. RESULTS: We developed OctopuSV and TentacleSV to address these long-standing challenges in SV analysis. OctopuSV features a specialized BND correction module that converts ambiguous BND annotations into canonical SV types, recovering important variants that are often overlooked by existing tools. Additionally, it provides advanced set operations (difference, complement, custom-defined) that enable sophisticated variant filtering without programming expertise, critical for identifying tumor-specific SVs or variants unique to specific sample groups. TentacleSV completes our solution by automating the entire SV analysis process from raw sequencing data to high-confidence callsets, ensuring consistency and reproducibility across projects. Benchmarking across short-read and long-read platforms showed superior F1 score, complete SV type consistency compared to existing tools. Our framework enables experimental biologists and clinical researchers to perform sophisticated analyses ranging from cancer subtype-specific SV identification to multi-sample comparative studies without requiring specialized programming skills. AVAILABILITY AND IMPLEMENTATION: All codes are available at https://github.com/ylab-hi/OctopuSV; https://github.com/ylab-hi/TentacleSV.

Software↗