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PubMed2025

Epstein-Barr Virus-Associated Gastric Cancer: A Histopathologic Study With Comprehensive Molecular Profiling.

A subset of gastric cancers (GCs) is linked to Epstein-Barr virus (EBV) infection. This study aims to characterize the histopathological and molecular features of EBV-associated GCs (EBVaGCs), focusing on predictive biomarkers and genomic and transcriptomic analysis. A total of 35 primary EBVaGCs were considered. The presence of EBV was confirmed with in situ hybridization. Immunohistochemical analyses for HER2, PD-L1, claudin 18.2, and mismatch repair proteins were performed. Genomic and transcriptomic profiles were assessed using AmoyDx Master Panel, which can identify single-nucleotide variants, InDels, and copy number variations on 571 hot genes, as well as microsatellite status, tumor molecular burden, and homologous recombination deficiency at the DNA level; however, at the RNA level, it identifies rearrangements/fusions in 45 genes and also quantifies the expression of 2396 cancer-related transcripts. The following histotypes were identified: carcinoma with lymphoid stroma (CLS; 69%), tubular (20%), and mixed (11%). Most cases were associated with atrophic gastritis (71%), and only 11% with dysplasia. The vast majority (94%) of EBVaGCs expressed EBV-encoded RNA in all tumor cells. Mismatch repair deficiency and HER2 overexpression were each observed in 6% of cases, whereas all tumors had a PD-L1-combined positive score ≥10. Sixty-six percent of cases showed moderate/strong claudin 18.2 expression in ≥75% of cancer cells. The most frequently altered genes were PIK3CA (41%) and ARID1A (17%). Transcriptomic analysis revealed substantial differential gene expression between EBVaGCs and EBV-negative controls, with upregulation of genes involved in antigen presentation, natural killer cell-mediated cytotoxicity, and cytokine-cytokine receptor interaction in EBVaGCs. Within EBVaGC, CLS showed higher expression of immune-related transcripts and higher PD-L1 expression than other histotypes. This study establishes EBVaGC as a distinct molecular class, with a distinctive profile of genomic alterations and expression of predictive biomarkers, and also with a unique immune microenvironment with enhanced cytotoxic activity. The findings highlight EBV's role in early tumor development and EBVaG-CLS as a distinct subgroup within EBVaGC, characterized by unique morphologic features and a pronounced immune activation profile.

Humans↗

PubMed2026

Likelihood-based optimization enables accurate copy number estimation for paralogous genes using exome data.

MOTIVATION: Exome sequencing is widely used for genetic studies; however, accurate detection of copy number variants (CNV) in paralogous genes is challenging due to short-read mapping ambiguity and extensive copy-number variation. The human genome contains several hundred paralogous genes, many of which are known to harbor disease-associated CNVs. Existing exome CNV callers are primarily designed for rare CNV detection in uniquely mappable regions and are not well-suited for paralogous genes. METHODS: We describe a computational method (EdgeCopy) for copy number profiling of paralogous genes using whole-exome sequence data. EdgeCopy aggregates reads mapped to all copies of paralogous genes and relates observed read depth to copy number for multiple exome samples using an approximate composite likelihood function. The likelihood function is optimized using numerical optimization to obtain gene-level fractional copy number estimates that are discretized and refined using a Hidden Markov Model to obtain exon-level copy number estimates. RESULTS: Benchmarking of Edgecopy using experimental copy number data showed high concordance (mean = 0.973) for six disease-associated paralogous genes. We evaluated performance using whole-exome data from approximately 2400 samples across five continental populations from the 1000 Genomes Project. EdgeCopy shows robust concordance with whole-genome sequencing based estimates (0.974-0.982) across populations and 130 paralogous genes spanning a wide range of copy-number variation. In comparison, copy number analysis using a state-of-the-art exome CNV caller failed to estimate copy number for paralogous genes with very high mapping ambiguity and showed much lower concordance (0.565) for CNV events compared to EdgeCopy (0.908). AVAILABILITY: EdgeCopy is freely available at https://github.com/vibansal-lab/edgecopy.

Humans↗

PubMed2025

Anticancer drug response prediction integrating multi-omics pathway-based difference features and multiple deep learning techniques.

Individualized prediction of cancer drug sensitivity is of vital importance in precision medicine. While numerous predictive methodologies for cancer drug response have been proposed, the precise prediction of an individual patient's response to drug and a thorough understanding of differences in drug responses among individuals continue to pose significant challenges. This study introduced a deep learning model PASO, which integrated transformer encoder, multi-scale convolutional networks and attention mechanisms to predict the sensitivity of cell lines to anticancer drugs, based on the omics data of cell lines and the SMILES representations of drug molecules. First, we use statistical methods to compute the differences in gene expression, gene mutation, and gene copy number variations between within and outside biological pathways, and utilized these pathway difference values as cell line features, combined with the drugs' SMILES chemical structure information as inputs to the model. Then the model integrates various deep learning technologies multi-scale convolutional networks and transformer encoder to extract the properties of drug molecules from different perspectives, while an attention network is devoted to learning complex interactions between the omics features of cell lines and the aforementioned properties of drug molecules. Finally, a multilayer perceptron (MLP) outputs the final predictions of drug response. Our model exhibits higher accuracy in predicting the sensitivity to anticancer drugs comparing with other methods proposed recently. It is found that PARP inhibitors, and Topoisomerase I inhibitors were particularly sensitive to SCLC when analyzing the drug response predictions for lung cancer cell lines. Additionally, the model is capable of highlighting biological pathways related to cancer and accurately capturing critical parts of the drug's chemical structure. We also validated the model's clinical utility using clinical data from The Cancer Genome Atlas. In summary, the PASO model suggests potential as a robust support in individualized cancer treatment. Our methods are implemented in Python and are freely available from GitHub (https://github.com/queryang/PASO).

Deep Learning↗

PubMed2025

Structural variation detection and association analysis of whole-genome-sequence data from 16,543 Alzheimer's disease sequencing project subjects.

INTRODUCTION: The role of structural variations (SVs) in Alzheimer's disease (AD) remains understudied. METHODS: We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N = 16,543) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). RESULTS: We found a burden of singletons (odds ratio [OR] = 1.07, p = 0.0017) and homozygous deletions (OR = 1.14, p < 0.0001) in cases. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in LD (R2 = 0.99) with rs143080277 in NCK2. We identified a rare deletion near RNA5SP293 associated with AD (OR = 1.99, p = 1.3 × 10-5), which was replicated using an independent dataset. DISCUSSION: This study highlights the pivotal role of SVs in AD genetics. HIGHLIGHTS: Observed a significant burden of singletons and homozygous deletions in Alzheimer's disease (AD) patients. Identified rare protein-altering structural variations (SVs) in ABCA7, APP, PLCG2, and SORL1. Established linkages between SVs and AD risk-associated single nucleotide variants (SNVs). Discovered a novel deletion near RNA5SP293 linked to AD, replicated independently. Uncovered over-representation of SVs in neuronal function pathways.

Humans↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

Development and evaluation of a one-pot RPA-Cas12a assay based on a primer-driven reverse screening strategy for preliminary screening of megalocytivirus-related viruses.

A primer-driven reverse-screening strategy was used to identify an RPA-Cas12a target suitable for the rapid preliminary screening of megalocytivirus-related viruses. The ISKNV reference genome NC_003494.1 was used as the initial template, and candidate amplification units were designed according to RPA primer-design requirements, primer physicochemical properties, and the availability of Cas12a protospacer-adjacent motif (PAM) sites and crRNA target sequences. Following preliminary amplification assessment, the retained candidate primers were aligned individually against 75 complete genome sequences of megalocytivirus-related viruses. Of these, 67 sequences met the predefined criteria for target-region integrity, primer-binding-site compatibility, and Cas12a recognition. Retrospective mapping to the reference genome located the candidate amplification region within ORF057L. Based on the resulting candidate detection unit, a one-pot RPA-Cas12a assay incorporating a commercially available lyophilized RPA amplification module was developed. Optimization showed that 400 nM reporter and 80 nM crRNA-1 provided relatively stable fluorescence output. A cut-off value of 1281.6 relative fluorescence units (RFU) was established as the mean plus three standard deviations of the endpoint fluorescence values obtained from 20 qPCR-negative samples. In analytical sensitivity testing, the assay generated fluorescence signals above the negative control at low plasmid copy numbers. However, because only a limited number of replicates were tested at these low template concentrations, these findings were not used to define a formal limit of detection. ISKNV, RSIV, and TRBIV samples tested positive, whereas the MRV sample produced an endpoint fluorescence value below the cut-off. Repeatability analysis of the same sample in six independent reactions yielded a coefficient of variation of 8.03%. Among the 39 samples examined, no discordant qualitative results were observed between the RPA-Cas12a assay and qPCR. These findings support the use of the ORF057L-targeted one-pot RPA-Cas12a assay as a rapid preliminary screening tool for megalocytivirus-related viruses. Nevertheless, its formal limit of detection, inter-batch stability, cross-reactivity with additional non-target pathogens, and clinical diagnostic performance require further evaluation.

Lyophilized RPA↗

PubMed2024

Comparative analysis of chloroplast genomes in ten holly (Ilex) species: insights into phylogenetics and genome evolution.

In order to clarify the chloroplast genomes and structural features of ten Ilex species and provide insights into the phylogeny and genome evolution of the genus Ilex, we conducted a comparative analysis of chloroplast genomes using bioinformatics methods. The chloroplast genomes of ten Ilex species were obtained, and their structural features and variations were compared. The results indicated that all chloroplast genomes in the genus Ilex exhibit a double-stranded circular structure, with sizes ranging from 157,356 to 158,018 bp, showing minimal differences in size. The chloroplast genomes of the ten Ilex species have a relatively conservative gene count, with a total of 134 to 135 genes, including 88 or 89 protein-coding genes, and a conserved number of 8 rRNA genes. Each chloroplast genome contains 3 to 123 SSR (Simple Sequence Repeat) sites, predominantly composed of mononucleotide and trinucleotide repeats, with no detection of pentanucleotide or hexanucleotide repeats. The variation in dispersed repeat sequences among Ilex species is minimal, with a total repeat sequence number ranging from 1 to 14, concentrated in the length range of 30 to 42 base pairs. The expansion and contraction of chloroplast genome boundaries among Ilex species are relatively stable, with only minor variations observed in individual species. Variations in non-coding regions are more pronounced than those in coding regions, with the variability in the Large Single Copy region (LSC) being the highest, while the variability in the Inverted Repeat region A (IRa) is the lowest. The divergence time among Ilex species was estimated using the MCMC-tree module, revealing the evolutionary relationships among these species, their common ancestors, and their differentiation throughout the evolutionary process. The research findings provide a valuable reference for the systematic study and molecular marker development of Ilex plants.

Genome, Chloroplast↗

PubMed2025

Unequally Abundant Chromosomes and Unusual Collections of Transferred Sequences Characterize Mitochondrial Genomes of Gastrodia (Orchidaceae), One of the Largest Mycoheterotrophic Plant Genera.

The mystery of genomic alternations in heterotrophic plants is among the most intriguing in evolutionary biology. Compared to plastid genomes (plastomes) with parallel size reduction and gene loss, mitochondrial genome (mitogenome) variation in heterotrophic plants remains underexplored in many aspects. To further unravel the evolutionary outcomes of heterotrophy, we present a comparative mitogenomic study with 13 de novo assemblies of Gastrodia (Orchidaceae), one of the largest fully mycoheterotrophic plant genera, and its relatives. Analyzed Gastrodia mitogenomes range from 0.56 to 2.1 Mb, each consisting of numerous, unequally abundant chromosomes or contigs. Size variation might have evolved through chromosome rearrangements followed by stochastic loss of "dispensable" chromosomes, with deletion-biased mutations. The discovery of a hyper-abundant (∼15 times intragenomic average) chromosome in two assemblies represents the hitherto most extreme copy number variation in any mitogenomes, with similar architectures discovered in two metazoan lineages. Transferred sequence contents highlight asymmetric evolutionary consequences of heterotrophy: despite drastically reduced intracellular plastome transfers convergent across heterotrophic plants, their rarity of horizontally acquired sequences sharply contrasts parasitic plants, where massive transfers from their hosts prevail. Rates of sequence evolution are markedly elevated but not explained by copy number variation, extending prior findings of accelerated molecular evolution from parasitic to heterotrophic plants. Putative evolutionary scenarios for these mitogenomic convergence and divergence fit well with the common (e.g. plastome contraction) and specific (e.g. host identity) aspects of the two heterotrophic types. These idiosyncratic mycoheterotrophs expand known architectural variability of plant mitogenomes and provide mechanistic insights into their content and size variation.

Genome, Mitochondrial↗

PubMed2026

Complete telomere-to-telomere genome assembly of Guazuma ulmifolia uncovers evolutionary mechanisms, drought adaptation, and flavonoid biosynthesis.

The first T2T reference genome of Guazuma ulmifolia is reported, which serves as a core genomic resource for stress adaptation research and stress-tolerant breeding in cacao wild relatives. Climate change, particularly increased incidence of drought, poses a major threat to food security. Understanding the genomic basis of environmental adaptation in crop wild relatives can provide valuable resources for improving stress resilience. Guazuma ulmifolia, a wild relative of Theobroma cacao with important ecological and medicinal value, lacks high-quality reference genomic resources. Here, we report the first telomere-to-telomere (T2T) chromosome-level genome assembly of G. ulmifolia, with a genome size of 311.31 Mb, contig N50 of 35.19 Mb, and 98.70% BUSCO completeness. Repetitive sequences constitute 27.43% of the G. ulmifolia genome, with LTR retrotransposons as the predominant class. Comparative genomic analyses revealed that genome-size variation among Malvaceae species is associated with differences in polyploidization history and TE dynamics. Ancestral karyotype reconstruction identified five lineage-specific chromosome fusion events distinguishing G. ulmifolia from T. cacao. Comparative analyses further identified tandem duplication-associated expansion of stress-related LEA and GST gene families, suggesting potential genomic features associated with stress responses. Flavonoid biosynthesis genes were largely conserved in copy number but showed tissue-specific expression patterns, providing candidate genes for investigating secondary metabolism. Together, this study establishes a high-quality T2T genome resource for exploring genome evolution, chromosome organization, and stress-related genomic features in Malvaceae.

Genome, Plant↗

PubMed2026

Graph-KIR: graph-based KIR copy number estimation and allele calling using short-read sequencing data.

MOTIVATION: The Killer-cell Immunoglobulin-like Receptor (KIR) is a highly polymorphic region in the human genome, associated with autoimmune diseases and organ transplantation. The sequences of KIR genes are highly similar among star alleles as well as in between individual genes, with the copy number of each KIR gene typically ranging from 0 to 4. In this study, we introduce Graph-KIR, a tool designed to estimate gene copy numbers and predict full-resolution (7-digit, encompassing both coding and non-coding sequence variations) from a whole genome sequencing (WGS) sample. RESULTS: Graph-KIR is capable of independently typing KIR alleles per sample with no reliance on the distribution of any framework gene in a cohort. In a set of 100 simulated samples, Graph-KIR demonstrated 99.2% accuracy in copy number estimation and high F1-score of allele typing: 91.79% at 7-digit resolution, 97.37% at 5-digit resolution, and 97.11% at 3-digit resolution. Graph-KIR outperforms existing tools such as Geny (96.39% F1-score), PING's WGS version (92.77% F1-score), and T1K (90.44% F1-score) at 5-digit resolution. By analyzing the results on 44 HPRC samples, Graph-KIR achieves better F1-score than Geny and PING at 7-digit resolution. The release of Graph-KIR adds another valuable tool to assist users in accurately estimating copy numbers and calling alleles of KIR genes from WGS samples. AVAILABILITY AND IMPLEMENTATION: The Graph-KIR and paper-related pipeline codes are available at https://github.com/linnil1/KIR_graph.

Receptors, KIR↗

PubMed2026

Association of FOXC1 Duplications With Juvenile Open-Angle Glaucoma.

IMPORTANCE: While FOXC1 single-nucleotide variants and deletions are well-established causes of Axenfeld-Rieger syndrome, few FOXC1 duplications have been reported. This study investigated families with duplications encompassing the FOXC1 gene to refine the associated phenotypic spectrum and contribution to glaucoma. OBJECTIVE: To investigate the prevalence and phenotype of FOXC1 duplications in 2 large glaucoma registries. DESIGN, SETTING, AND PARTICIPANTS: This retrospective observational genetic cohort study included participants recruited from the Australian & New Zealand Registry of Advanced Glaucoma (ANZRAG) and the Massachusetts Eye and Ear (MEE) cohort from 2008 through 2025. Participants with glaucoma, and available relatives, underwent genomic testing to identify duplications encompassing FOXC1 using exome sequencing and genotyping arrays (ANZRAG) or whole-genome sequencing (MEE). Data analyses were conducted from 2022 through 2025. MAIN OUTCOMES AND MEASURES: Prevalence of FOXC1 duplications, age at glaucoma onset, and phenotype, including ocular and systemic features. RESULTS: Twenty individuals from 10 families (50% female and 50% male; 70% self-described as broadly European [Australian/British, British, English/German, English/Polish, European, or Scottish], 25% as Asian [Chinese or Filipino], and 5% as Latin American [Salvadoran]) were identified with FOXC1 duplications. All genetically tested individuals were diagnosed with glaucoma, demonstrating high penetrance. Seventeen individuals were referred with juvenile open-angle glaucoma (JOAG), 1 with primary open-angle glaucoma, 1 with primary congenital glaucoma, and 1 with anterior segment dysgenesis. The diagnosis of 4 individuals from 1 family with ectropion uveae was revised to anterior segment dysgenesis. Systemic features were reported for 2 participants (10.5%), including subtle dental findings and mild facial dysmorphism. Duplications encompassing FOXC1 were among the most common monogenic contributors to JOAG. In the ANZRAG group, they accounted for 13.5% (95% CI, 6.7%-25.3%) of JOAG probands with a genetic diagnosis, second to MYOC (53.8%; 95% CI, 40.5%-66.7%). In the MEE group, FOXC1 duplications accounted for 9.5% (95% CI, 2.7%-28.9%) of JOAG probands with a genetic diagnosis. CONCLUSIONS AND RELEVANCE: These findings suggest FOXC1 duplications are an underrecognized, highly penetrant, but variably expressive, genetic variation associated with JOAG. Findings for the relatively modest number of individuals in the retrospective study were associated with wide confidence intervals. This limitation is often inherent to studies of JOAG, a rare condition for which individual genetic variants account for only a subset of cases. Despite this, the findings highlight the genetic heterogeneity of JOAG and support the potential importance of considering routine genetic copy-number variant analysis for individuals with JOAG.

Humans↗

PubMed2026

Integrated single-cell and spatial transcriptomic analyses reveal malignant epithelial glycolytic heterogeneity and spatial niche remodeling during colorectal cancer progression.

Colorectal cancer (CRC) progression is shaped by metabolic reprogramming and complex interactions within the tumor microenvironment. However, the cellular heterogeneity, spatial organization, and clinical relevance of glycolytic activity in CRC remain incompletely understood. In this study, we integrated single-cell RNA sequencing, bulk transcriptomics, and spatial transcriptomics data to systematically characterize glycolytic heterogeneity in CRC. Glycolytic activity was quantified using five independent scoring methods, consistently showing that epithelial cells exhibited the highest glycolytic activity across the two single-cell cohorts. Stratification of CopyKAT-verified aneuploid malignant epithelial cells into high-glycolysis (HG) and low-glycolysis (LG) subgroups by glycolysis scores revealed that HG cells exhibited higher stemness scores and chromosomal copy number variations. Cell-cell communication analysis revealed that, compared with LG cells, HG cells exhibited increased interaction frequency and strength with immune and stromal populations, indicating enhanced malignant epithelial-microenvironment crosstalk. Spatial transcriptomics analyses further revealed that glycolytic activity varied across normal colorectal tissue, primary CRC, and colorectal liver metastases, accompanied by progressive remodeling of epithelial-associated spatial niches and MIF-mediated intercellular communication. Bulk transcriptomic analysis identified a glycolysis-related prognostic signature with robust predictive performance, which served as an independent prognostic factor for overall survival in CRC cohorts. Collectively, these findings indicate that glycolytic heterogeneity is a key feature of CRC malignant epithelial cells and is closely associated with tumor progression, microenvironmental remodeling, and clinical outcomes.

Humans↗

PubMed2026

Histopathologic, Genomic, and Clinical Characteristics of Primary Cutaneous Melanocytic Tumors With Concomitant NRAS Q61 and IDH1 R132C Mutations.

Cutaneous melanocytic tumors with concomitant NRAS Q61 and IDH1 R132C mutations have been described as intermediate-grade melanocytomas with characteristic biphasic morphology, but the malignant end of this genotype-defined spectrum remains poorly characterized. We assessed histopathologic, immunohistochemical, molecular, and clinical features of 16 primary cutaneous melanocytic tumors harboring both mutations. Following integrated review, 7 tumors were classified as melanocytoma and 9 as melanoma. Melanocytomas showed reproducible biphasic architecture with congenital nevus-like features, a biphasic HMB-45 pattern, low Ki-67, PRAME negativity, retained p16, and minimal copy number variations (CNVs). Melanomas retained partial morphologic overlap in a subset but were distinguished by higher-grade cytology, immunohistochemical features supportive of malignancy, and progression-associated genomic alterations, including TERT promoter mutation (9/9), 9p21/CDKN2A loss (4/7), and higher CNV burden. NRAS and IDH1 variant allele frequencies were strongly concordant (r = 0.83, P < 0.001), supporting their presence in the same dominant clone. Clinically, two patients presented with stage IIIB disease, but no distant metastasis or melanoma-related death occurred during a median melanoma follow-up of 3.9 years (IQR, 2.5-5.1). In exploratory analyses, moderate-to-severe atypia (RR, 6.2; 95% CI, 1.0-38.8; P = .009), Ki-67 ≥10% (RR, 4.4; 95% CI, 1.1-18.4; P = .003), lymphocytic infiltrate (RR, 2.4; 95% CI, 1.1-5.3; P = .03), absence of the typical biphasic pattern (RR, 2.4; 95% CI, 1.1-5.3; P = .03), and complete p16 loss (RR, 2.4; 95% CI, 1.1-5.3; P = .03) were associated with molecular or clinical progression to melanoma, defined as the presence of at least one of the following: TERT promoter mutation, pathogenic CDKN2A mutation, 9p21/CDKN2A loss, ≥3 genome-wide segmental CNVs, or any metastasis. These findings support the existence of NRAS/IDH1 co-mutated melanoma as the malignant counterpart of NRAS/IDH1-mutated melanocytoma within a single genotype-defined spectrum.

IDH1 mutations↗

PubMed2026

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10 kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

DNA Copy Number Variations↗

PubMed2025

ELViS: an R package for estimating copy number levels of viral genomic segments at base-resolution.

MOTIVATION: Tumor viruses account for ∼10% of cancer diagnoses. Virally induced tumorigenesis is understood as direct signaling through oncogenes such as E6 and E7 genes in the case of human papillomavirus. Furthermore, pathogen characteristics such as viral oncogene dose may impact the disease course. To our knowledge, no tool has been proposed to assess the intra-viral copy number alterations that define the gene dose of viral oncogenes and associated suppressive pathways native to the pathogen's normal life cycle. RESULTS: We propose an R package, "ELViS," that analyzes viral copy number changes from DNA sequencing of whole viral genomes. The method adjusts for viral load with 2D transformation and segmentation to offer the relative viral gene doses. AVAILABILITY AND IMPLEMENTATION: The ELViS R package is available from https://bioconductor.org/packages/ELViS. This article used controlled access data from dbGaP (phs001713.v1.p1).

Software↗

PubMed2025

Absolute Quantification of Cellular and Cell-Free Mitochondrial DNA Copy Number from Human Blood and Urinary Samples Using Real Time Quantitative PCR.

Mitochondrial DNA copy number (mtDNA-CN) in human body fluids is widely used as a biomarker of mitochondrial dysfunction in common metabolic diseases. Here we describe protocols to measure cellular and/or cell free (cf)-mtDNA-CN in human peripheral blood and urine. Cellular mtDNA is located inside the mitochondria where it encodes key subunits of the respiratory complexes in mitochondria and is usually normalized with reference to the nuclear genome as the mitochondrial genome to nuclear genome ratio (Mt/N) in either whole blood, peripheral blood mononuclear cells (PBMCs), or whole urine. Cf -mtDNA is usually found outside of the mitochondria, often released following mitochondrial damage, can trigger inflammatory pathways, and is usually measured as mtDNA-CN per volume of the starting material. Here we describe how to (1) separate whole blood into PBMCs, plasma, and serum fractions and whole urine into urinary supernatant and pellet, (2) prepare DNA from each of these fractions, (3) prepare reference standards for absolute quantification, (4) carry out qPCR for either relative or absolute quantification from test samples, (5) analyze qPCR data, and (6) calculate the sample size to adequately power studies. The protocol presented here is suitable for high throughput use and can be modified to quantify mtDNA from other body fluids, human cells, and tissues.

Humans↗

PubMed2026

Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.

BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.

Humans↗

PubMed2025

MPAC: a computational framework for inferring pathway activities from multi-omic data.

MOTIVATION: Fully capturing cellular state requires examining genomic, epigenomic, transcriptomic, proteomic, and other assays for a biological sample and comprehensive computational modeling to reason with the complex and sometimes conflicting measurements. Modeling these so-called multi-omic data is especially beneficial in disease analysis, where observations across omic data types may reveal unexpected patient groupings and inform clinical outcomes and treatments. RESULTS: We present Multi-omic Pathway Analysis of Cells (MPAC), a computational framework that interprets multi-omic data through prior knowledge from biological pathways. MPAC leverages network relationships encoded in pathways through a factor graph to infer consensus activity levels for proteins and associated pathway entities from multi-omic data, runs permutation testing to eliminate spurious activity predictions, and groups biological samples by pathway activities to allow identifying and prioritizing proteins with potential clinical relevance, e.g. associated with patient prognosis. Using DNA copy number alteration and RNA-seq data from head and neck squamous cell carcinoma patients from The Cancer Genome Atlas as an example, we demonstrate that MPAC predicts a patient subgroup related to immune responses not identified by analysis with either input omic data type alone. Key proteins identified via this subgroup have pathway activities related to clinical outcome as well as immune cell composition. Our MPAC R package enables similar multi-omic analyses on new datasets. AVAILABILITY AND IMPLEMENTATION: The MPAC package is available at Bioconductor https://bioconductor.org/packages/MPAC.

Humans↗