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PubMed2026

Rare variant analysis of whole genome sequenced juvenile idiopathic arthritis multiplex pedigrees identifies rare variants in NOD2 and ACVR1.

Juvenile idiopathic arthritis is a complex rheumatic disease that is influenced by environmental and genetic factors. Linkage and genome-wide association studies have identified genes that contribute to the risk of developing juvenile idiopathic arthritis but are limited in their ability to identify disease-risk variants of large effect. Penetrant, heritable risk variants can be detected in high-risk families, but such cases are uncommon due to the low prevalence of juvenile idiopathic arthritis. This study utilizes whole-genome sequencing of 23 multiplex families, the largest such cohort to date, to discover variants and genes relevant to JIA pathogenesis. Pathogenic variants in NOD2 associated with Blau syndrome, an ultra-rare Mendelian inflammatory disorder, are the most recurrent variants in the cohort, consistent with previous reports that milder presentations of Blau syndrome are oftentimes misdiagnosed as juvenile idiopathic arthritis. For the first time, however, rare variants in ACVR1 and SMAD6, integral components of the Bone Morphogenic Protein pathway, are found to be associated with juvenile idiopathic arthritis. Identified ACVR1 variants map to critical protein domains. AlphaFold modeling predicts that the ACVR1 interaction with its inhibitor OGT is disrupted by these variants, indicating that the patient-mutated protein has a gain-of-function phenotype. Drosophila melanogaster expressing either a wild-type or patient-mutated version of ACVR1 exhibit embryonic lethality, with the mutant exhibiting 1.4-fold greater lethality than wild-type. The combination of family-based cohorts for gene discovery, AI-based computational tools, and animal model studies for tests of variant function underscores shared disease pathogenesis between JIA and monogenic disorders of immunity and connective tissue.

Arthritis, Juvenile↗

PubMed2026

Targeted variant analysis of feline mediastinal lymphoma using MassARRAY and clinical associations.

Lymphoma is the most commonly diagnosed cancer in cats. This study used the Agena MassARRAY to genotype 40 variants across 17 genes in feline mediastinal lymphoma. These variants have previously been identified in tumors, including T- and B-cell lymphomas, acute and chronic lymphocytic leukemias, and mast cell tumors, in humans, dogs, and cats, using various methods. They were selected based on high prevalence reported in prior oncology studies, potential relevance to targeted therapy, and suitability for multiplex PCR amplification. Pleural fluid samples were collected from 76 cats with mediastinal lymphoma, including 69 domestic shorthairs, two Persians, two Siamese, two Wichienmaat, and one Scottish Fold. The most prevalent variants were found in the BCL2, KIT, STAT3, and ZEB1 genes. Specifically, BCL2 c.83275986G > A and c.83275992G > T were present in 71.1% and 57.9%, respectively. In cats with variant-positive in KIT c.163965724C > CT significantly reduced (11 days) compared to wild-type cats (94 days) (p < 0.001). In cats with variant-positive in STAT3 c.42942437C > CA, resulted in shorter median survival compared to wild-type cats (18 days vs. 77 days, p = 0.006). The findings suggest that the variant panel could be useful for the genomic landscape of feline mediastinal lymphoma and warrant further validation.

Animals↗

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↗

PubMed1978

Rheumatoid arthritis and its variants: analysis of scintiphotographic, radiographic, and clinical examinations.

99mTc pyrophosphate radionuclide scans of the axial and appendicular skeletons in 23 patients with rheumatoid arthritis and 15 patients with systemic arthritic conditions were compared to clinical and radiographic examinations. The nuclear scan was the most sensitive indicator of active disease and correlated extremely well with the other methods. A pattern of abnormal radionuclide activity in rheumatoid arthritis consisting of a symmetric peripheral joint process can be distinguished from that of the rheumatoid variants which tend to have more central skeletal involvement and asymmetric peripheral articular involvement. The nuclear scan is less specific than the radiograph in its ability to distinguish among the clinical entities. However, documentation of scintigraphic activity often antedated radiographic or clinical abnormalities.

Adult↗

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↗

PubMed2026

Application of qualifying variants for genomic analysis.

MOTIVATION: Qualifying variants (QVs) are genomic alterations selected by defined criteria within analysis pipelines. Although crucial for both research and clinical diagnostics, QVs are often seen as simple filters rather than dynamic elements that influence the entire workflow. In practice these rules are embedded within pipelines, which hinders transparency, audit, and reuse across tools. A unified, portable specification for QV criteria is needed. RESULTS: Our aim is to embed the concept of a "QV" into the genomic analysis vernacular, moving beyond its treatment as a single filtering step. By decoupling QV criteria from pipeline variables and code, the framework enables clearer discussion, application, and reuse. It provides a flexible reference model for integrating QVs into analysis pipelines, improving reproducibility, interpretability, and interdisciplinary communication. Validation across diverse applications confirmed that QV based workflows match conventional methods while offering greater clarity and scalability. AVAILABILITY AND IMPLEMENTATION: The source code and data are accessible at the Zenodo repository https://doi.org/10.5281/zenodo.17414191. Manuscript files are available at https://github.com/DylanLawless/qvApp2025lawless. The QV framework is available under the MIT licence, and the dataset will be maintained for at least two years following publication.

Genomics↗

PubMed2026

Unraveling the genomic blueprint of the Indian black soldier fly: From genome assembly to evolutionary insights.

The black soldier fly (BSF) (Hermetia illucens) has been renowned for its sustainable bioconversion capabilities, resulting in smart protein production with wide applications in animal feed, bioenergy, and biofertilizer. However, the genetic mechanisms underlying efficient bioconversion and productivity remain poorly understood. To advance strain-specific applications and strengthen genetic resource availability, we present the whole genome sequencing (WGS) data for an Indian isolate of black soldier fly. The assembled genome was 1.46 Gb with a scaffold N50 of 172.7 Mb, and a GC content of 42.6%. Furthermore, 64.17% of genomic sequences were masked as repeated, and 14,317 protein-coding sequences were identified. Variant analysis against the reference genome identified 34.44 million variants (∼33.25 million SNPs and ∼ 1.18 million INDELs), with the majority (99.3%) classified as MODIFIER, 0.54% as LOW impact, 0.14% as MODERATE, and only 0.003% as HIGH impact. Comparative genomic analysis with other related species revealed expansions of gene families in BSF associated with Immune effector (Antimicrobial peptides (AMPs), Lysozymes, and Peptidoglycan Recognition Protein (PGRP) and Detoxification (cytochrome P450 enzymes). Notably, AMPs in the Indian isolate showed enhanced copy number variation in defensin (27) and PGRP (40) compared to reference BSF, suggesting potential regional adaptations to pathogen exposure. Collectively, this genomic data provides an improved resource for evolutionary studies, functional genomics, and targeted genetic improvement of BSF for sustainable bioconversion applications.

Comparative genomics↗

PubMed2026

Genomic and computational analysis of variants in telomere regulatory genes in subjects with bone marrow failure.

Telomere Biology Disorders (TBDs) are a genetically heterogeneous and often under-recognized cause of Bone Marrow Failure Syndromes (BMFS), driven by defective telomere maintenance and progressive telomere attrition. We performed an integrated genomic, telomeric and computational analysis in 118 subjects presenting clinical features of BMFS to delineate the contribution of Telomere Regulatory Genes (TRGs) variants to disease pathogenesis. Whole exome sequencing (WES) identified pathogenic (18.18%), likely pathogenic (27.27%) and rare variants of uncertain significance (54.54%) in 27 subjects (22.9%) across five TRGs: RTEL1, TERT, TINF2, NOP10, and WRAP53. Telomere Length (TL) assessment revealed significant telomere shortening in TRG variant-positive subjects compared with age-matched controls, with the most profound attrition observed in individuals harboring de novo TINF2 gene variants. RTEL1 emerged as the most frequently affected gene, with recurrent clustering of variants within its C-terminal regulatory region. A familial NOP10 variant, Asp12His, segregated with cutaneous pigmentation and hematological abnormalities consistent with the established role of NOP10 in dyskeratosis congenita, further broadening the known mutational spectrum of the gene. Structure-guided in-silico analyses predicted that both novel and recurrent variants disrupt protein stability, telomerase assembly or trafficking and shelterin complex integrity. Reduced TERT expression and a significant inverse correlation between telomere length and clinical severity further underscored the functional impact of TRG defects. Collectively, this study provides the first comprehensive characterization of TRG variants in the Indian BMFS cohort and highlights the utility of integrating genomic sequencing, telomere length measurement and computational modeling to improve diagnostic precision, variant interpretation and clinical stratification in TBDs.

Journal Article↗

PubMed2025

De novo rare EMX2 variants lead to idiopathic hypogonadotropic hypogonadism.

PURPOSE: The genetic etiology of infertility remains unknown. To identify genes for human infertility, we applied a de novo variant analysis in 142 parent-proband trios with idiopathic hypogonadotropic hypogonadism (IHH), an infertility disorder caused by gonadotropin-releasing hormone (GnRH) deficiency. METHODS: Rare de novo copy-number and single-nucleotide variants (CNVs and SNVs) were called from exome sequencing data of the IHH trios. An association study of common EMX2 variants and disease outcomes was performed in the Massachusetts General Brigham Biobank (N = 65,253). GnRH neuronal development and migration was studied in organotypic explants with knocked down of Emx2 and in a mouse model lacking Emx2. RESULTS: We identified that the gene EMX2 harbored both rare de novo CNVs and SNVs. Rare de novo EMX2 variants led to IHH, developmental delay, and hearing loss. Common EMX2 variants were linked to infertility, Parkinson disease, and hearing loss. Knockdown of Emx2 in nasal explants resulted in attenuated GnRH cell migration and GnRH cells were confined to nasal regions of Emx2 knockout (KO) mice, consistent with IHH pathogenesis. CONCLUSION: By utilizing a de novo variant analysis and cellular assays, EMX2 was uncovered as a gene for human infertility.

Humans↗

PubMed2025

A Comprehensive Bioinformatics Approach to Analysis of Variants: Variant Calling, Annotation, and Prioritization.

Next-Generation Sequencing (NGS), also known as high-throughput sequencing technologies, has enabled rapid and efficient sequencing of large amounts of DNA and RNA. These technologies have revolutionized the field of genomics, transcriptomics, and proteomics and have been widely used in cancer research, leading to advances in clinical diagnosis and treatment. Improvements in the NGS technologies enabled millions of fragments to be sequenced simultaneously in a time- and cost-effective manner and resulted in large amount of genomic data which require efficient analysis methods. Analysis of the genomic data requires both efficient computer resources and bioinformatics approaches. This chapter details a comprehensive computational approach and analysis steps for genomic data analysis.

Computational Biology↗

PubMed2025

Analysis of Variants' Dynamic Using the CLIMB Database in COVID-19 Patients Admitted to Hospitals of Barts Health NHS Trust.

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant global health challenges. This study analyzes the dynamics of SARS-CoV-2 variants among patients admitted to Barts Health National Health Service (NHS) Trust hospitals using data from the CLIMB-COVID decentralized digital infrastructure allowing precise identification of SARS-CoV-2 variants. A total of 423 patients admitted between October 2020 and March 2021 were included in the study and divided into two groups: the alpha lineage group, which comprised the B.1.1.7 variant, and the other lineages group, which included all other variants. Whole-genome sequencing of SARS-CoV-2 genomes was conducted using the COVID-CLIMB pipelines. Clinical outcomes, such as mortality rates and deterioration within 28 days, were analyzed. To ensure robust findings, analyzes were adjusted for confounding factors, including age and comorbidities. Our findings revealed a significant increase in mortality with age for the alpha lineage and other lineages. The study underscores the importance of age adjustment in clinical studies to accurately assess the impact of different variants. Consistent genomic sequencing and data completeness are crucial for obtaining reliable results and guiding public health responses. These insights are vital for improving patient outcomes and providing a truthful picture of the pandemic, informing both current and future healthcare strategies.

Humans↗

PubMed2026

The Biobank Rare Variant consortium powers the discovery of rare genetic associations through global collaboration.

Rare coding variants can have large effects on disease risk and provide direct routes from human genetics to disease mechanisms and therapeutic targets, but their discovery is constrained by sample size, particularly for low-prevalence diseases. Here we establish the Biobank Rare Variant Analysis (BRaVa) consortium, a global rare variant association resource that integrates sequencing and linked health-record data from ten biobanks and cohorts comprising over 1.2 million individuals across diverse ancestries. We performed gene-based meta-analyses of rare coding variation across 33 clinical endpoints and 11 quantitative traits. Aggregating evidence across biobanks and ancestries identified 514 gene-trait associations, including 31 not previously reported in prior studies or curated association resources following systematic literature review. Notably, 36.1% of gene-level associations were undetectable in any individual biobank, and 91 emerged only through cross-ancestry meta-analysis, demonstrating that federated integration enables discovery beyond the reach of single cohorts. Similar gains were observed at the variant level, where 25.0% of phenotype-locus associations were detectable only through meta-analysis. Effect size estimates were correlated across ancestries with concordant directions of effect, supporting the generalizability of rare variant associations. The identified signals implicate pathways involved in transcriptional and epigenetic regulation, metabolism, vascular and epithelial biology, and immune function, highlighting rare coding variation as an engine for biological discovery across medical record phenotypes. For example, damaging variation in ANKRD12 implicates inflammatory transcriptional dysregulation in asthma and chronic obstructive pulmonary disease, and ultra-rare predicted loss-of-function variants in NAA15 link protein acetylation processes to type 2 diabetes risk. BRaVa establishes a scalable framework and freely available community resource for rare variant meta-analysis across global biobanks. Public release of gene- and variant-level association summary statistics provides a reference map of rare coding variant associations to support disease gene discovery, biological interpretation, and therapeutic target prioritization as sequencing-linked health-record resources continue to expand.

Journal Article↗

PubMed1979

Amino acid substitution: its use in detection and analysis of genetic variants.

Techniques of chemical analysis, amino acid sequencing and autoradiography are being used to study the frequency of incorporation of normally noncoded amino acids into hemoglobins and seminal fluid proteins. We are studying, by the sequencing of radiolabeled proteins followed by the recovery of [3H]isoleucine phenylthiohydantoin by high-performance liquid chromatography, the frequency at which normally noncoded isoleucine is incorporated into hemoglobin because of base-substitution mutations versus translational errors. Irradiation increases the isoleucine content of human hemoglobin and the frequency of substitution of isoleucine for specific amino acids in rabbit hemoglobin. Studies to date indicate that these techniques have been developed sufficiently for initial analysis of the potential of drugs and environmental pollutants to induce base-substitution mutations in mammalian somatic cells.

Amino Acid Sequence↗

PubMed2025

Rare variants in MIR184 are a novel genetic cause of Fuchs endothelial corneal dystrophy.

PURPOSE: To identify novel genetic causes of Fuchs endothelial corneal dystrophy (FECD) within a genetically unsolved patient cohort lacking repeat expansions in the TCF4 gene (Exp-). METHODS: A rare variant analysis framework (CoCoRV) was applied to exome data, in combination with in silico modeling, luciferase reporter, and RNA-seq analysis to characterize transcriptome-wide consequences of identified variants. RESULTS: A gene burden analysis identified MIR184, a microRNA encoding gene, to be enriched for rare pathogenic variants within the studied Exp- FECD cohort. In total, 2 noncoding rare variants were identified in 4 unrelated FECD probands: NR_029705.1:n.58G>A and n.73G>T. Both variants altered highly conserved mature sequence residues, were predicted to induce hairpin structural changes, and were experimentally determined to disrupt microRNA-mRNA interactions. RNA-seq of transfected human corneal endothelial cells revealed that the mutants elicited distinct transcriptomic profiles. Enriched KEGG pathways included PI3K-Akt signaling, focal adhesion, and immune response, revealing shared pathogenic mechanisms between MIR184-associated FECD and the more common TCF4 repeat expansion-mediated form of disease. CONCLUSION: MIR184 variants are a novel rare genetic cause of FECD, and common pathways of transcriptomic dysregulation are shared across genetically distinct subtypes of the disease. These pathways may serve as future gene agnostic targets for therapeutic interventions.

Humans↗

PubMed2026

No receptor-binding domain adaptation detected in within-host H5N1 surveillance of 4,559 US dairy outbreak sequences.

BACKGROUND: The 2024-2026 US H5N1 clade 2.3.4.4b dairy cattle outbreak has been characterised primarily through consensus-level phylogenetics. Whether mammalian-adaptation variants are emerging at sub-consensus frequencies within infected hosts, particularly at the haemagglutinin receptor-binding domain (RBD), remains unknown because no systematic within-host variant analysis of the public sequencing corpus has been performed. METHODS: We conducted a pre-registered, corpus-wide intrahost single-nucleotide variant (iSNV) analysis of all publicly available H5N1 cattle, feline-spillover, and retail-milk sequences on the NCBI Sequence Read Archive (4559 samples across 7 BioProjects). A dual-caller concordance pipeline (iVar + LoFreq) with empirically determined allele frequency (AF) threshold (3%, set via four-criterion validation including synthetic spike-in controls) was applied to an 11-site Tier 1 mammalian-adaptation panel spanning the polymerase complex, haemagglutinin RBD, and accessory proteins. Within-host nucleotide diversity was compared across host categories. RESULTS: The HA RBD sites Q226L and G228S (H3 numbering) showed zero detections across >4300 adequately sequenced samples at all AF thresholds tested (1-5%), despite the pipeline detecting other non-synonymous variants at these exact codon positions (upper 95% CI for prevalence: 0.08%). Seven of eleven adaptation sites carried statistically significant iSNV signals after Bonferroni correction (corrected α = 0.00417), though all at low prevalence (≤2.95%). Genotype stratification showed that most polymerase-site detections reflected genotype structure rather than within-host emergence: the apparent PB2 631 L→M "reversion" was largely the ancestral avian state of the D1.1 genotype (20 of 23 detections), which never acquired the 631L mammalian adaptation, with only two genuine sub-consensus events in the B3.13 background, while consensus-level PB2 701N was a fixed feature of the D1.1 genotype (10 of 14 detections) rather than independent sub-consensus emergence. Cattle exhibited significantly higher within-host nucleotide diversity than feline-spillover samples (π = 1.59 × 10-4 vs 6.11 × 10-5; Kruskal-Wallis p = 6.6 × 10-15), a finding that persisted after depth-matching (p = 4.6 × 10-5); this may reflect prolonged mammary-gland infection, though sampling differences and host biology cannot be excluded. CONCLUSIONS: We did not detect HA receptor-switching adaptation (the acquisition of human-type α2,6 receptor binding via Q226L/G228S) at any tested allele frequency in the US dairy H5N1 outbreak. Sub-consensus mammalian-adaptation signals exist at polymerase-complex sites but at low prevalence, are genotype-structured rather than independently recurrent, and require functional characterisation before informing risk assessment.

Dairy cattle↗

PubMed2026

Whole exome sequencing of paediatric patients with Cogan's syndrome to identify monogenic mimics.

OBJECTIVES: Cogan's syndrome (CS) is a rare variable vessel vasculitis, describing sensorineural hearing loss (SNHL), inflammatory ocular disease and vestibular dysfunction. We hypothesized that within paediatric-onset (p)CS, a proportion would have monogenic disease, either autoinflammatory and/or associated with SNHL. METHODS: Whole exome sequencing (WES) was performed and analysed using an in-house pipeline incorporating virtual gene panels for inflammation and SNHL; copy number variant analysis (ExomeDepth); and phenotype-driven variant prioritization (Exomiser). Genetic variants were interpreted by a multi-disciplinary team according to American College of Medical Genetics and Genomics guidelines. RESULTS: Ten patients with a clinical diagnosis of pCS were enrolled. Three/10 (30%) had a monogenic contribution to the phenotype based on Class 4/5 variants: de novo NLRP3 p.T915R (n = 1) associated with Cryopyrin-associated periodic syndrome; MYO7A p.K542Qfs*5 (n = 1) causing SNHL; and HBB homozygous p.E7V causing sickle cell disease (associated with hearing loss and uveitis). A further two cases had possible monogenic contribution with the following rare variants of uncertain significance (class 3): ADGRV1 compound heterozygous variants (n = 1) associated with Usher syndrome; and a novel ALPK1 p.H735P (n = 1), associated with Retinal dystrophy Optic nerve oedema Splenomegaly Anhidrosis Headache (ROSAH) syndrome. CONCLUSIONS: In children presenting with features suggesting CS, genetic screening should be considered before conferring this rare diagnostic label since at least 30% had an alternative monogenic contribution to the phenotype rather than true pCS, with implications for treatment and prognosis. We thus advocate for genetic testing using next-generation sequencing for patients presenting with pCS.

Humans↗

PubMed2026

T-rex: standardized analysis of germline variants in whole-exome sequencing trios.

Whole-exome sequencing (WES) enables the identification of rare germline variants contributing to pediatric diseases. Trio-based sequencing, comparing affected children with their parents, is particularly effective for rare disease genetics. However, WES data analysis requires bioinformatics expertise, varies across institutions, and is often incompatible with clinical workflows. We developed T-Rex (Trio Rare variant analysis of EXomes), a cross-platform desktop application that enables the standardized and local analysis of WES germline Trio data without the need for programming knowledge. T-Rex integrates state-of-the-art tools for alignment, dual-variant calling (GATK HaplotypeCaller + VarScan2), annotation (SNPEff/SNPSift), rare-variant filtering based on population frequencies (gnomAD), and family-based statistical testing, including the Transmission Disequilibrium Test with multiple-testing correction. Benchmarking of the dual-caller strategy on the Genome in a Bottle Ashkenazim Trio demonstrates high precision (99.2%) while maintaining robust sensitivity (91.1%). User testing (n = 13) confirmed quick learning across clinicians and researchers. Application to a cohort of n = 121 pediatric cancer Trio datasets, filtering for rare protein-coding variants (MAF ≤ 0.1% in gnomAD v4.1), validated all assessable previously reported pathogenic variants. Overall, T-Rex enables clinicians to robustly analyze WES Trio data in compliance with data protection regulations without requiring additional software licenses. As one of the first platforms for comprehensive WES Trio analysis that requires no programming expertise while providing reproducible, end-to-end workflows for clinical genomics, T-Rex facilitates collaborative research between clinics and reduces reliance on external providers.

Humans↗

PubMed2024

Refining the genetic diagnostic puzzle: A case report on a Chinese ARPKD patient with a reciprocal balanced translocation and c.2507 T > C (p.V836A) in PKHD1.

INTRODUCTION: Autosomal recessive polycystic kidney disease (ARPKD) ranks among the most severe chronic kidney diseases (CKD). Its primary cause is variants in the Polycystic Kidney and Hepatic Disease 1 gene (PKHD1). The clinical spectrum of ARPKD varies widely, ranging from mild late-onset symptoms to severe perinatal mortality. However, achieving an early genetic diagnosis in ARPKD patients before clinical symptoms appear proves challenging. CASE PRESENTATION: This case is a 4-year-old boy who experienced a convulsion characterized by a generalized tonic attack lasting approximately 3-5 minutes and later sought treatment to our hospital. However, routine abdominal ultrasound examination accidentally detected that he had diffuse liver lesions, splenomegaly, and bilateral renal enlargement with renal pelvis dilation. Given the uncertainty regarding the underlying cause of the patient's structural abnormalities and convulsions, karyotyping, whole exome sequencing (WES), structural variant analysis (SV analysis) of whole genome sequencing (WGS) were recommended. The result of SV analysis revealed that he has an RBT impacting PKHD1 and the precise location of breakpoints was confirmed through Long-Range Polymerase Chain Reaction (LR-PCR). However, WES did not screen out pathogenic variants initially, the WES data was reviewed subsequently based on SV analysis results. CONCLUSION: We identified an infrequent variant combination, c.2507T>C (p.V836A) in PKHD1 and an RBT with broken PKHD1, which extends the genetic spectrum of ARPKD, and provide a basis for further genetic counselling to the family.

Humans↗