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PubMed2026

Clinical Variant Interpretation with the Integrative Genomics Viewer (IGV) for Molecular Pathologists.

The integrative genomics viewer (IGV) is a pivotal tool in clinical genomics, enabling the visualization and interpretation of complex sequencing data. Bringing clinical knowledge to bear with visual evaluation of sequencing results is the primary means by which molecular pathologists and other professionals assess and finalize cases. A variety of software tools can assist, but their relationship to the underlying data must be understood and applied systematically. This study includes essential background on next-generation sequencing (NGS) data file types (e.g., FASTQ, BAM, VCF) with a discussion of their format and purpose. We then describe features of IGV that derive nuances from these files. We utilize a series of curated practical cases based on clinical vignettes through which the reader will interact with clinical NGS sequencing data using the IGV software to review various types of clinically relevant variants relative to the human reference genome. These clinical vignettes have been curated to describe examples of some of the complexities of interpretation of genomic data, and how utilizing IGV as part of a routine workflow can provide additional interpretive information for variants beyond routine bioinformatic software algorithm variant calls. The visual inspection of genomic variants utilizing the tools within IGV can unmask subtle contextual cues (i.e., variant allele frequency, strand bias, tissue-specific context) that can influence the interpretation of genomic variants. Although this study focuses on using IGV for the detection and interpretation of somatic variants, the provided applications can be extrapolated for use in the germline setting, including analysis of complex variants and detection of mosaicism.

Humans↗

PubMed2026

MACS3: A Peak-calling Platform for Bulk and Single-cell Regulatory Genomics.

Since the original publication of Model-based Analysis for ChIP-Seq (MACS), the software has been widely used to identify enriched genomic regions in ChIP-seq, ATAC-seq, CUT&RUN, DNase-seq, and related regulatory genomics assays. Over the years, MACS has evolved substantially, with MACS version 3 (MACS3) now serving as the actively maintained implementation. MACS3 preserves the core MACS framework for fragment pileup, dynamic local background noise, statistical enrichment testing, and peak refinement, while adding functionality needed for contemporary bulk and single-cell workflows. It supports conventional bulk peak calling, paired-end and fragment-based file formats, modular signal processing, direct analysis of single-cell ATAC-seq fragment files, barcode-restricted pseudobulk and cluster-level peak calling, specialized ATAC-seq and variant-calling modules, as well as command-line and programmatic interfaces. MACS3 is distributed through standard software channels and supported by continuous testing across operating systems, Python versions, and CPU architectures. Here we describe the architecture, current capabilities, and recommended use of MACS3, providing an updated reference for applying the MACS framework in contemporary bulk and single-cell regulatory genomics workflows. MACS3 is open-source software available at https://github.com/macs3-project/MACS.

Bioinformatics software↗

PubMed2026

Comprehensive evaluation of new sequencer T20 and well-established T7 with 507 human samples.

The DNBSEQ-T20×2 (T20) sequencer, developed by MGI Tech, enables cost-effective human whole-genome sequencing (WGS) at 30× coverage for less than $100 per genome. Here, we evaluate the sequencing performance and data quality of the T20 platform by benchmarking it against the established DNBSEQ-T7 (T7) sequencer using 507 samples derived from blood (N = 75), stool (N = 242), and saliva (N = 190). The T20 exhibited lower sequencing quality metrics compared with the T7, with Q20 scores of 95.76%-95.83% and Q30 scores of 87.25%-87.40%, compared with 97.81%-97.93% and 93.26%-93.60%, respectively, for T7 data. Quality differences were more evident toward the end of reads, and PCR-free libraries sequenced on the T20 showed similar reductions in quality scores. The median empirical base error rate estimated from 102 ZymoBIOMICS samples was 0.33%. The T20 demonstrated comparable coverage uniformity to the T7 and showed high concordance in microbiome composition analysis, with a median Bray-Curtis dissimilarity of 0.02. Variant calling performance was highly consistent between the two platforms. Among variants with non-missing genotype calls on both platforms, 94.92% of SNPs and 87.20% of InDels showed concordant genotypes between T20 and T7. Overall, the T20 delivers reliable sequencing accuracy and reproducibility for large-scale genomic and microbiome studies, providing a cost-effective alternative for high-throughput sequencing applications.

Metagenomics↗

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↗

PubMed2025

MRDagent: iterative and adaptive parameter optimization for stable ctDNA-based MRD detection in heterogeneous samples.

MOTIVATION: Minimal residual disease (MRD) as critical biomarker for cancer prognosis and management plays a crucial role in improving patient outcomes. However, detecting MRD via next-generation sequencing-based circulating tumor DNA variant calling remains unstable due to the extremely low variant allele frequency and significant inter- and intra-sample heterogeneity. Although parameter optimization can theoretically enhance the detection performance of variants, achieving stable MRD detection remains challenging due to three key factors: (i) the necessity for individualized parameter tuning across numerous heterogeneous genomic intervals within each sample, (ii) the tightly interdependent parameter requirements across different stages of variant detection workflows, and (iii) the limitations of current automated parameter optimization methods. RESULTS: In this study, we propose MRDagent, a novel variant detection tool designed specifically for MRD detection. MRDagent incorporates an iterative and self-adaptive optimization framework capable of handling unknown objectives, varying constraints, and highly coupled parameters across stages. A key innovation of MRDagent is the integration of a convolutional neural network-based meta-model, trained on historical data to enable rapid parameter prediction. This significantly enhances computational efficiency and generalization performance. Extensive evaluations on simulated and real-world datasets demonstrate MRDagent's superior and stable performance, providing an efficient, reliable solution for MRD detection in clinical and high-throughput research applications. AVAILABILITY AND IMPLEMENTATION: MRDagent is freely available at https://github.com/aAT0047/MRDagent.git. The corresponding dataset and software archive are available at Zenodo: https://doi.org/10.5281/zenodo.15458496.

Circulating Tumor DNA↗

PubMed2026

Genetic diversity of Plasmodium falciparum helical interspersed subtelomeric (phistb) gene in Tanzania and neighboring countries.

BACKGROUND: Lysine-rich membrane associated Plasmodium helical interspersed subtelomeric gene (phistb) is a member of the phist family of genes which encodes exported proteins essential for the parasite's survival within infected red blood cells. Recent studies suggest the phistb gene as a promising malaria vaccine candidate, however, its genetic diversity remains understudied. This study assessed the genetic diversity of the phistb gene in regions of varying malaria transmission aiming to generate data and improve our understanding of this promising malaria vaccine candidate gene. METHODS: Genomic data from 1472 Plasmodium falciparum samples from Tanzania, Kenya, Uganda, and Ethiopia were retrieved in variant Calling file format (VCF) format from the MalariaGEN Pf7 database. Variants were filtered to include only biallelic Single Nucleotide Polymorphism (SNPs) with Variant Quality Score Log- Odds (VQSLOD) > 1 and "PASS" status. Genetic diversity, differentiation, and selection signatures were analyzed using population genetics metrics. RESULTS: After filtering, 1312 samples were retained. Wright's inbreeding coefficient (Fws) showed that 875 (66.7%) samples had monoclonal infections, with the highest proportion of monoclonal infections in Ethiopia (95.3%), followed by Tanzania (67.2%), Kenya (65.7%), and Uganda (50%). Among the 875 monoclonal samples, 88 haplotypes were identified, with Hap_1 (renamed PF3D7) and Hap_13 comprising 37.9 and 21.5 of the samples, respectively. Nucleotide and haplotype diversity were relatively higher in Kenya with 0.097, and 0.88 respectively, compared to the other study populations. The overall fixation index (Fst) was < 0.05, and Principal Component Analysis revealed no clear population sub-structure among countries. Negative Tajima's D values in Tanzania, Kenya, and Ethiopia indicated an excess of low-frequency alleles. CONCLUSION: This study reports low genetic diversity of the phistb gene in the four countries despite varying malaria transmission intensities among them, thus making it a suitable candidate gene for malaria vaccine. Further studies should be conducted to assess individual antibodies recognition of the phistb variants and the ability to elicit cross reactivity to further support its potential as a vaccine candidate.

Plasmodium falciparum↗

PubMed2026

Identification of candidate variants in plasma associated with early versus late disease progression under anti-PD-1 therapy in metastatic NSCLC.

BACKGROUND: Immune checkpoint inhibitors (ICIs), including anti-programmed cell death protein 1 (anti-PD-1) antibodies, have significantly improved outcomes in patients with metastatic non-small cell lung cancer (mNSCLC). However, substantial heterogeneity exists in clinical benefit, with some patients exhibiting early progression (EP) and others late progression (LP). To date, no biomarkers of EP versus LP disease have been implemented in clinical practice. Circulating tumor DNA (ctDNA) analysis represents a minimally invasive strategy for identifying such biomarkers. In this proof-of-concept study, we evaluated the performance of the TruSight Oncology 500 ctDNA (TSO500 ctDNA) panel and explored its feasibility to identify candidate variants associated with early and late disease progression under anti-PD-1 therapy. METHODS: Baseline ctDNA from eight mNSCLC patients treated with pembrolizumab was extracted and sequenced using the TSO500 ctDNA assay, a 523-gene targeted next-generation sequencing panel. Patients were classified according to their response as LP or EP. Variant calling was performed using the DRAGEN Bio-IT platform, and variants were annotated and clinically interpreted using the Clinical Genomics Workspace (CGW; PierianDx) according to Association for Molecular Pathology (AMP)/American Society of Clinical Oncology (ASCO)/College of American Pathologists (CAP) guidelines. Survival outcomes were assessed using Kaplan-Meier and log-rank tests. Performance of ctDNA variants was evaluated using receiver operating characteristic (ROC) curve analysis, and multi-gene models were assessed using leave-one-out cross-validation with penalized logistic regression. RESULTS: All patients harbored detectable variants, including SNVs (100%), MNVs (87.5%), deletions (75%), and insertions (62.5%). Tier I variants were identified in 37.5% of patients, while all cases showed tier II and multiple tier III alterations. TP53 variants were associated with poorer outcomes under anti-PD-1 therapy. Individual gene alterations in TP53, ERBB3, SMC1A or LATS1 showed moderate discriminatory performance between LP and EP patients; however, combination of mutated genes improved apparent discrimination. Notably, specific two-gene combinations (SMC1A + LATS1 or ERBB3 + LATS1) showed the highest discriminatory performance between LP and EP patients in this exploratory cohort. CONCLUSIONS: This study demonstrates the feasibility and analytical performance of the TSO500 ctDNA panel and provides hypothesis-generating evidence that plasma gene variants may be useful to evaluate early versus late disease progression in patients with mNSCLC receiving immunotherapy.

TruSight Oncology 500↗

PubMed2025

NAVIP: Unraveling the influence of neighboring small sequence variants on functional impact prediction.

Once a suitable reference sequence has been generated, intra-species variation is often assessed by re-sequencing. Variant calling processes can reveal all differences between strains, accessions, genotypes, or individuals. These variants can be enriched with predictions about their functional implications based on available structural annotations, i.e., gene models. Although these functional impact predictions on a per-variant basis are often accurate, some challenging cases require the simultaneous incorporation of multiple adjacent variants into this prediction process. Examples include neighboring variants which modify each other's functional impact. The Neighborhood-Aware Variant Impact Predictor (NAVIP) considers all variants within a given protein coding sequence when predicting the effect. As a proof of concept, variants between the Arabidopsis thaliana accessions Columbia-0 and Niederzenz-1 were annotated. NAVIP is freely available on GitHub (https://github.com/bpucker/NAVIP) and accessible through a web server (https://pbb-tools.de).

Arabidopsis↗

PubMed1979

[Pathobiochemistry of alcoholism].

Liver alcohol dehydrogenase (ADH) represents the main enzyme of normal alcohol metabolism. Total activity of this enzyme varies largely due to the occurrence of isoenzymes and of genetic polymorphisms. One genetic variant, called "atypical", is characterized by a higher specific activity. In carriers of this variant enzyme an initially faster rate of ethanol metabolism leads to higher blood acetaldehyde levels. Acetaldehyde, as a toxic intermediary metabolite, causes tachycardia, nausea and flushing of the face. A high frequency for "atypical" ADH is observed in mongolid races and consequently a hypersensitivity to alcohol is often observed in Orientals. Hence, certain genetically determined enzyme patterns may represent an aversive factor with regard to alcohol consumption. In Caucasians the phenotypes with "atypical" ADH are less frequent. However, in individuals with the "atypical" variant regular intake of alcohol may lead to an increased organotoxicity due to acetaldehyde.

Acetaldehyde↗

PubMed1978

G6PD Vientiane: a new glucose-6-phosphate dehydrogenase variant with increased stability.

A new G6PD variant, called G6PD Vientiane, has been discovered in a patient from Laos. The characteristics of this variant are: mild enzyme deficiency (about 50% of the normal activity) in the granulocytes and the red cells, with normal G6PD-related antigen concentration; increased stability; normal Km glucose 6-phosphate and NADP+; increased inhibition constant by NADPH; decreased inhibition by ATP; slightly increased utilization of the substrate analogue; abnormal pH curve, with maximum activity at pH 9.5; slightly reduced starch gel electrophoretic migration. The implications of the molecular stability of a deficient mutant variant are discussed.

Adult↗

PubMed2026

First nationwide full-genome characterisation of human-derived Andes virus in Chile: a retrospective genomic epidemiology study.

BACKGROUND: Andes virus (ANDV) is the only hantavirus known to transmit between humans and causes hantavirus cardiopulmonary syndrome in Chile and Argentina. In Chile, ANDV genomic diversity remains incompletely characterised. This study aimed to characterise the genetic diversity, geographical structure, and molecular signatures of ANDV using human clinical samples collected over a 13-year period (2011-24). METHODS: We conducted a retrospective genomic epidemiology study of ANDV infections in Chile. Clinical samples from patients with confirmed ANDV, collected between March 9, 2011, and June 27, 2024, were analysed and sequenced. Clinical and epidemiological data were obtained from diagnostic laboratories and surveillance programmes. Consensus sequences for the S, M, and L segments were generated, and genetic clustering and divergence were assessed using phylogenetic inference and variant calling. FINDINGS: We analysed clinical samples from 58 infected individuals and identified two major genomic variants of ANDV with distinct geographical distributions, defined by regionally structured patterns of nucleotide and amino acid substitutions across the S, M, and L segments: ANDV Chi-North (central Chile) and ANDV-South (southern Chile). No consistent clustering by clinical severity was observed, and no recurrent non-synonymous substitutions were uniquely associated with severe disease. Substitutions previously associated with person-to-person transmission in outbreaks in Argentina were not consistently observed in Chilean sequences, including in four person-to-person transmission cases. Although some substitutions described in ANDV-like viruses were present in the Chi-North lineage, this lineage remained phylogenetically distinct and geographically restricted to central Chile. INTERPRETATION: To our knowledge, this study provides the first nationwide genomic characterisation of human-derived ANDV in Chile. The identification of geographically structured variants indicates that ANDV diversity in Chile is driven by regional diversification rather than clinical outcome. The absence of consistent amino acid signatures associated with disease severity or person-to-person transmission suggests that these phenotypes are unlikely to be explained by viral genetic variation alone. These findings refine current understanding of ANDV evolution and highlight the need for continued integrated genomic surveillance in endemic regions. FUNDING: Agencia Nacional de Investigación y Desarrollo de Chile and National Institutes of Health.

Humans↗

PubMed2024

Diversity of ribosomes at the level of rRNA variation associated with human health and disease.

With hundreds of copies of rDNA, it is unknown whether they possess sequence variations that form different types of ribosomes. Here, we developed an algorithm for long-read variant calling, termed RGA, which revealed that variations in human rDNA loci are predominantly insertion-deletion (indel) variants. We developed full-length rRNA sequencing (RIBO-RT) and in situ sequencing (SWITCH-seq), which showed that translating ribosomes possess variation in rRNA. Over 1,000 variants are lowly expressed. However, tens of variants are abundant and form distinct rRNA subtypes with different structures near indels as revealed by long-read rRNA structure probing coupled to dimethyl sulfate sequencing. rRNA subtypes show differential expression in endoderm/ectoderm-derived tissues, and in cancer, low-abundance rRNA variants can become highly expressed. Together, this study identifies the diversity of ribosomes at the level of rRNA variants, their chromosomal location, and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Humans↗

PubMed2026

An alignment-free strategy for circulating tumor DNA detection and tumor fraction estimation from whole-genome sequencing data.

Circulating tumor DNA (ctDNA) is emerging as a promising biomarker for postoperative monitoring of cancer patients. Precise estimation of circulating tumor fraction is crucial for evaluating treatment effects and timely detection of disease recurrence. All current ctDNA detection methods that utilize whole-genome sequencing (WGS) data rely on the reference genome alignment of sequencing reads and often apply separate tools for detecting different variant types. However, various bioinformatic analysis confounders and the application of external variant calling tools could be avoided by analyzing k-mers from unaligned sequencing reads. While k-mer-based methods have successfully been applied for somatic variant validation and detection, the potential of k-mer-based ctDNA detection is unexplored. We have developed a tumor-informed alignment-free ctDNA detection tool called ctDNAmer that detects tumor-specific somatic variation directly from unaligned sequencing data by identifying k-mers unique to the tumor DNA. ctDNAmer detects variant information across the genome by comparing the primary tumor and germline WGS data and accounts for sample-specific germline variability and technical noise in the same framework. We tested the utility of ctDNAmer for tumor fraction estimation on postoperative plasma cfDNA WGS data (mean sequencing depth ~ 28x) from 90 stage III colorectal cancer patients with three years of follow-up. The tumor fraction (TF) estimates agreed with the available clinical information and ctDNA was detected in 77% (17/22) of recurring patients with a median lead time of 8 months compared to radiological imaging. We further validated ctDNAmer's tumor fraction estimates based on a comparison with the mean cfDNA allele frequencies of somatic clonal SNVs identified from aligned primary tumor sequencing data. The TF estimates showed a strong Pearson correlation of 0.897 with the mean allele frequencies and improved ctDNA detection results across samples with an AUC of 0.79 compared to 0.75 if the mean allele frequency of clonal mutations is used.

Circulating Tumor DNA↗

PubMed2026

'PePApipe': A complete bioinformatics analysis pipeline for African Swine Fever Virus genome.

African Swine Fever Virus (ASFV) is of high concern in porcine livestock across the world due to both the high mortality rates and the trade restrictions imposed on affected regions. The viral genome is large and complex, and genomic analysis is essential for tracing its origin and evolution. Although several bioinformatics tools exist for genome assembly and analysis, no single platform integrates all necessary steps in an accessible and systematic way. In this study the authors developed 'PePApipe', a custom-built, user-friendly pipeline that enables rapid, complete, and efficient ASFV genome analysis. It is specifically designed for laboratory professionals with limited bioinformatics experience, requiring only basic command-line knowledge. Starting from raw sequencing data, PePApipe integrates thirteen software tools into one automated workflow, covering quality control and pre-processing of raw reads, de novo genome assembly and variant calling. Programmed in Python, it can be executed locally through bash scripts, or using a Slurm protocol for batch processing of multiple samples. The main outputs are the ASFV consensus genome sequence and a file listing its putative variants compared to the selected reference genome. PePApipe classifies generated files into structured folders and produces intermediate files that can be used as inputs for further or parallel analyses; users can also enable or disable specific steps in each particular case. This pipeline is adaptable and complementary to downstream steps such as viral genome annotation or genome visualization. By consolidating all stages of viral genome analysis into a single automated workflow, PePApipe reduces the likelihood of user error, and enhances reproducibility and efficiency. This user-friendly pipeline facilitates the transition from sequencing to assembly and downstream analysis of viral genomes, ensuring a fast and reliable response to molecular analysis demands. Finally, the pipeline can be easily adapted to the study of other viral species, expanding its application in infectious diseases surveillance.

African Swine Fever Virus↗

PubMed2026

A de novo algorithm for allele reconstruction from Oxford nanopore amplicon reads, with application to CYP2D6.

MOTIVATION: The Oxford Nanopore Technologies' sequencing platform offers a path towards bedside genomics, producing long reads that can completely cover a gene of interest, and detect any known or novel variant the gene contains. However, the analysis of these long reads to identify actionable genotypes remains challenging and typically requires customization depending on the target gene. RESULTS: Here, we describe a generic algorithm to accurately reconstruct allele sequences derived from long-reads of amplicon-based data. Rather than calling variants directly from these long-reads, our method takes a "sequence-first" approach, performing an unbiased reconstruction of the underlying amplicon sequences to generate high-confidence reconstructed allele sequences. This is done without user input of the target gene, allowing for any source amplicon to be reconstructed. These high-confidence reconstructed allele sequences are then compared to the genomic reference sequence of the gene to infer the specific diplotype present in the sample. This approach is agnostic towards the number of genes and alleles present and readily detects novel variants. We demonstrate our approach using three independent data sets for CYP2D6, a diverse and complex gene with over 175 known alleles of clinical significance. We show how our approach can accurately recover validated CYP2D6 diplotypes from 20 Coriell samples covering 14 distinct alleles, using different amplicons, flow cell versions, and depths. This includes inferring occurrences of allele duplication events from relative abundances of each allele, a critical factor for ascribing functional effects to a diplotype. Further, we demonstrate our approach's utility for other genomic regions, including HLA. AVAILABILITY: Custom code is available at the following GitHub repository, along with instructions for use and test data: https://github.com/scottdbrown/allele-reconstruction-long-read-amplicon-data. A snapshot of the code at the time of publication is available on Zenodo.org; doi 10.5281/zenodo.19716004. Raw .fastq sequence data for our three sequencing runs is available at the SRA under Bioproject PRJNA1357883 (https://www.ncbi.nlm.nih.gov/bioproject/1357883).

Alleles↗

PubMed2024

Diversity of ribosomes at the level of rRNA variation associated with human health and disease.

Ribosomal DNA and RNA (rDNA and rRNA) sequences are usually discarded from sequencing analyses. But with hundreds of copies of rDNA genes it is unknown whether they possess sequence variations that form different types of ribosomes that affect human physiology and disease. Here, we developed an algorithm for variant-calling between paralog genes (termed RGA) and compared rDNA variations found in short- and long-read sequencing data from the 1,000 Genomes Project (1KGP) and Genome In A Bottle (GIAB). We additionally developed a novel protocol for long-read sequencing full-length rRNA (RIBO-RT) from actively translating ribosomes. Our analyses identified hundreds of rDNA variants, most of which, surprisingly, are short insertion-deletions (indels) and dozens of highly abundant rRNA variants that are incorporated into translationally active ribosomes. To visualize variant ribosomes at the single cell level, we developed an in-situ rRNA sequencing method (SWITCH-seq) which revealed that variants are co-expressed within individual cells. Strikingly, by analyzing rDNA, we found that variants assemble into distinct ribosome subtypes. We discovered that these subtypes acquire different rRNA structures by successfully employing dimethyl sulfate (DMS) probing of full length rRNA. With this atlas we investigated rRNA variation changes across human tissues and cancer types. This revealed tissue-specific rRNA subtype expression in endoderm/ectoderm-derived tissues. In cancer, low abundant rRNA variants can become highly expressed, which suggests the presence of cancer-specific ribosomes. Together, this study identifies and comprehensively characterizes the diversity of ribosomes at the level of rRNA variants which is dominated by indel variants, their chromosomal location and unique structure as well as the association of ribosome variation with tissue-specific biology and cancer.

Journal Article↗

PubMed2025

Vcfexpress: flexible, rapid user-expressions to filter and format VCFs.

MOTIVATION: Variant call format (VCF) files are the standard output format for various software tools that identify genetic variation from DNA sequencing experiments. Downstream analyses require the ability to query, filter, and modify them simply and efficiently. Several tools are available to perform these operations from the command line, including BCFTools, vembrane, slivar, and others. RESULTS: Here, we introduce vcfexpress, a new, high-performance toolset for the analysis of VCF files, written in the Rust programming language. It is nearly as fast as BCFTools, but adds functionality to execute user expressions in the lua programming language for precise filtering and reporting of variants from a VCF or BCF file. We demonstrate performance and flexibility by comparing vcfexpress to other tools using the vembrane benchmark. AVAILABILITY AND IMPLEMENTATION: vcfexpress is available under the MIT license at https://github.com/brentp/vcfexpress with code used for the manuscript deposited in https://doi.org/10.5281/zenodo.14756838.

Software↗

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↗