Journal of Bioinformatics and Systems Biology

Purpose: Autosomal Dominant Polycystic Kidney Disease is the most common monogenic kidney disease and largely due to variants in PKD1. We aimed to assess pathogenicity evidence for PKD1 missense variants in disease databases and evaluate in silico pathogenicity prediction tool performance. Methods: PKD1 missense variants reported as pathogenic, likely pathogenic or likely benign were extracted from ClinVar and PKDB. Variants were re-classified using ACMG/AMP criteria to identify "truth sets" of pathogenic and benign variants. In silico scores were obtained from five tools (SIFT, PolyPhen-2, CADD, REVEL, AlphaMissense) and evaluated using established thresholds. A Receiver Operating Characteristic curve analysis was performed using the PKD1 variant truth sets. Results: 346/389 (89%) reported disease-causing missense variants in PKD1 were downgraded to Variants of Unknown Significance (VUS) using current classification criteria. Based on current thresholds, REVEL achieved the highest sensitivity of 62%, with specificity of 79%. AlphaMissense was the only tool not to misclassify any truth set variants, but many of the variant scores were between the pathogenic and benign thresholds. Conclusion: A large majority of PKD1 missense variants are classified as VUS with current pathogenicity criteria. Commonly used in silico tools, applied with established genome-wide thresholds, do not reliably distinguish pathogenic and benign missense variants in PKD1.

With the rapid development of modern biotechnology, DNA vectors have become fundamental tools for inserting, transferring, and expressing specific gene sequences in various fields such as gene cloning, gene expression, gene editing, and gene therapy. However, when dealing with complex structured DNA sequences, traditional vector construction methods face challenges with low connection efficiency. This study proposes a new method for constructing recombinant vectors by employing a strategy of high-temperature treatment followed immediately by placement on ice, effectively reducing the complexity of DNA structures and enhancing the efficiency of PCR product-vector connection, thereby improving the construction efficiency of recombinant vectors. This paper describes the technical details of the method, experimental validation, and applications in gene cloning, gene recombination editing, and the preparation of gene therapy drugs, providing a new efficient tool for molecular biology experiments.

In many bioinformatic data analysis projects, it is convenient to visualize plots and results through an interactive web app or dashboard. These interactive reports can then be shared with customers, collaborators, or the general public. Publishing and sharing these apps is not straightforward, becoming especially cumbersome when the number of projects and customers start growing. Docker containers offer a convenient way to package, distribute, and run interactive web apps, and their use is already widespread in the bioinformatics community. We developed Kiosc to simplify the orchestration of containerized web apps, organize them into projects, and regulate access control. We implemented it as a web server based on the Django framework, with a user- and admin-friendly interface as well as a REST API for programmatic tasks. Users can select Docker containers packaging apps like Plotly Dash, Shiny, or Quarto, and configure them to display the results of their analysis. Kiosc runs the containers with the appropriate network configuration and acts as a proxy to the web services running inside the containers. We have been maintaining a Kiosc instance for more than 5 years, serving 321 containers in 150 projects across multiple institutions. In this article, we introduce the main functionality in Kiosc and describe four use-cases that show how Kiosc can prove helpful to the broader bioinformatics community, such as configuring and running web apps for the interactive visualization of workflow results, and publishing companion apps for scientific articles. Kiosc is a self-hosted platform for publishing web apps, which doesn't require significant expertise in either Docker or network administration to be deployed. It provides a similar service to Kubernetes, but with a convenient web interface and much lower administration overhead.

Purpose: To identify transcript-level variants in crystallin genes in paediatric patients with unilateral cataracts. Methods: Anterior capsulorhexis (n=12) from patients underwent surgical management of congenital unilateral cataracts was collected. Total RNA was isolated from lens epithelial cells, and complementary DNA (cDNA) was synthesized. Full-length RNA transcripts of 10 lens-specific crystallin genes were PCR-amplified and analysed via Sanger sequencing. Identified transcript variants were further validated using genomic DNA (gDNA) through Sanger sequencing. In addition, the full-length (~7,535 bp) CRYBA1 genomic region was sequenced using Oxford Nanopore Technology. Results: Aberrant low molecular weight (LMW) amplicons (~370 bp) of the CRYBA1 transcript were identified in three patients presented with unilateral cataract. Of 3 patients, 2 had persistent fetal vasculature (PFV) and 1 had pre-existing posterior capsular defect (PPCD). Sanger sequencing revealed a precise loss of exons 2 to 4 in the CRYBA1 RNA transcript. No coding, splice-site, or large deletion variants were detected in the genomic DNA of the patients or their parents. In silico analysis predicted two possible truncated proteins arising from these alternatively spliced transcripts: one comprising the first 11 amino acids of the N-terminal region with a loss of all Greek key motifs, and another comprising 90 amino acids encoded by exons 5 and 6, initiated from an alternative start codon in exon 5, and loss of Greek key motifs 1 & 2. Conclusion: The precise skipping of exons 2 to 4, consistent with canonical splicing signals (5-prime-GU...AG-3-prime), in the absence of genomic alterations, suggests the presence of alternatively spliced (AS) CRYBA1 transcripts in human lenses. This is the first report documenting AS-CRYBA1 transcripts in association with childhood cataracts with PFV and PPCD.

The rapid growth of biotechnology manufacturing for synthetic DNA and proteins has raised concerns that adversaries could exploit commercial synthesis pipelines to create biological weapons. Without effective safeguards, an attacker could seek regulated genetic sequences from synthesis providers; while synthetic DNA is not itself a pathogen or toxin, access to such sequences can lower barriers to downstream misuse, motivating robust order-time screening. To mitigate this risk, Biosecurity Screening Software (BSS) systems have been developed to flag potentially malicious synthesis orders. Here, we propose one of the first deterministic benchmarks for evaluating the robustness of Biosecurity Screening Software. Our framework enables systematic testing of BSS behaviors and potential on specific nucleic-acid sequences and on targeted regions of malicious genomes. Our framework allows for insights into what is being flagged as malicious in BSSs, leading to potential discussions if specific BSS is fit for a specific manufacturing pipeline. We additionally introduce a dataset of manipulated genomes derived from the HHS and USDA Select Agents and Toxins List. When evaluated on this dataset, SeqScreen flags 42% of the sequences as malicious, while Commec flags 10.2%. Across a range of manipulation strategies, we find that simple manipulations, such as padding sequences by adding a repeated nucleotides at 1.5 times the original length, perform nearly as well as more targeted methods, such as embedding malicious sequences within benign genomic context. Padding-based methods trail embedding-based methods by only 0.75 percentage points in average detection rate. Consistent with prior reports from BSS developers and studies, we observe a sharp drop in detection rate when input sequence length falls below a critical threshold, typically between 50 and 100 base pairs (bp). Under our threat model, this implies that an adversary can bypass most existing safeguards by splitting a target genome into fragments shorter than 50 bp. Fragment-level analysis further reveals that some toxin regions evade detection entirely by SeqScreen, while other malicious genomes remain detectable even when fragmented into 30-50 base-pair segments. We open-source this benchmark to support reproducible evaluation of BSS robustness and to inform the development of next-generation biosecurity screening tools (https://github.com/HenryCWong/DNAS-Bench). For ethical concerns we only open-source the framework while the data is available upon request.

Scientific computing has become a central component of modern scientific discovery. Yet many computational tools are developed by small, specialized teams under incentives that encourage the release of rapidly prototyped tooling without commensurate attention to engineering concerns, including performance and maintainability. These gaps are particularly visible in the life sciences, where the advent of high-throughput sequencing and molecular profiling has made the production and processing of datasets routine at scales that strain reliability and cost. Recently, LLM-based agents have become increasingly capable, with publicly available systems possessing both significant domain knowledge in many scientific fields and the ability to autonomously operate over complex and specialized codebases in pursuit of well-defined goals. Together, these developments create a practical opportunity for scientific computing. Many of the persistent weaknesses of the scientific computing ecosystem stem from technical debt and a shortage of sustained engineering labor and expertise. Here, we examine coding agents as a potential way to address these weaknesses: we present an exploratory field report of eight early case studies in the application of LLM agents to scientific computing across a range of project scopes, from lightweight maintenance tasks to full performance-oriented rewrites of scientific libraries, with a focus on the life sciences. Each of these case studies is accompanied by reflections from the individual or group responsible for the work, including lessons from the process. Overall, we find that the use of coding agents in scientific computing holds great promise for accelerating scientific research and increasing the reliability of critical systems, but that outstanding concerns remain, including responsibility and ownership for such projects, and we suggest collaboration and stewardship with existing maintainers when feasible.

The Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) and associated nuclease gene (Cas), originating from the bacteria acquired immune system, have revolutionized gene editing technology. In this regard, type II (Cas9) been extensively studied and widely applied CRISPR system so far. The mechanism for precise manipulation of genomic sequences is guided by small RNA called CRISPR RNA (crRNA). In this study we devised and optimized CRISPR-Cas9 screening system based on Cas9 gene detection, targeting a conserved part of recognition domain (REC) consisting of arginine rich bridge helix (BH). We used hemi-nested PCR approach for screening sensitivity and reproducibility. The recombinant E. coli DH5 alpha containing the pRGEB32 vector (DH5 alpha/pRGEB32) with the Cas9 gene was used for system optimization. Subsequently, the screening system was applied and validated on different environmental bacterial strains including Alcaligenes faecalis and Pseudomonas stutzeri, isolated from sewerage samples. The optimized hemi-nested PCR resulted in amplification of targeted region in environmental bacterial strains and results were reproduced successfully. Furthermore, nucleotides and amino acid sequence, motif and domain analysis of PCR products, confirmed the targeted Cas9 REC-BH domain. Presently, no rapid and cost effective CRISPR-Cas screening system is available except expensive whole genome sequencing approach. Our investigation aimed to device rapid and cost effective screening system for identification of new variants of Cas9 proteins in environmental bacterial species. In this context, the developed Cas9 gene-based CRISPR-Cas screening system (C9CSS) may be a potential rapid screening tool to identify new Cas9 orthologs in different bacterial genomes with improved functions.

We now exist in the era of massive datasets from genomics, large language models, and all the known knowledge of humanity right at our fingertips. Much of this data is becoming more accessible; however, processing such data remains an ongoing issue across systems including high performance computing (HPC) infrastructures. Massively parallel computing (MPP) has solved this using a divide and conquer approach by splitting workloads across independent nodes (i.e., central processing units (CPU) allowing for higher scaling of data). The main engine for this in python is Ray; however, it has many issues including a large code space, security issues, debugging opacity, and memory management issues. Here, we present HydraMPP, a lightweight, ease of use and utilization, with high auditability, and with SLURM ergonomics.

We developed BWR-finder (Burrows-Wheeler transform-based Repeat finder), a new software tool for database-free detection of interspersed repeats in large genomes of tens of gigabases. BWR-finder employs a BWT-based seed-and-extend repeat detection algorithm and parallelized extension computation, improving both runtime and memory usage. In benchmarks using the rice and human genomes, BWR-finder reduced runtime compared with RepeatModeler2, HiTE, and REPrise, and reduced memory usage compared with HiTE and REPrise, while maintaining high nucleotide-level repeat detection sensitivity. BWR-finder also enabled whole-genome repeat detection in genomes larger than 10 Gb and identified candidate repeat regions and repeat consensus sequences in the 20.3-Gb Pleurodeles waltl genome that were not associated with existing repeat annotations or libraries.

The rapid expansion of high-quality, nearly complete eukaryotic genomes demands computational accelerations of existing bioinformatic infrastructure. TIR-Learner has been widely used for the de novo identification of Terminal Inverted Repeat (TIR) transposons, but suffers from slow runtime and a large memory footprint. Here we present TIR-Learner v4, a complete rewrite of TIR-Learner v3 and key supporting programs, which accelerates runtimes by two orders of magnitude and caps at a low RAM footprint irrespective of genome size. We demonstrate the scalability of TIR-Learner v4 by annotating TIRs in all 579 VGP Phase I genomes in around 4 hours.

Derived Cleaved Amplified Polymorphic Sequences (dCAPS) assays have been widely performed historically to detect known base substitutions in many model organisms--notably Caenorhabditis elegans, Arabidopsis thaliana, Saccharomyces cerevisiae, and Schizosaccharomyces pombe-- where chemical mutagens that induce point mutations are frequently used. With the rise of whole-genome sequencing and genome editing technologies, dCAPS is increasingly applied to detect diverse nucleotide changes in additional organisms, including Drosophila, zebrafish, mammals, and agricultural crops (e.g., Oryza sativa and Hordeum vulgare). However, a key limitation of dCAPS is that genomic target sites amenable to primer designs that both preserve PCR amplification and create recognition sites for inexpensive, high-performance restriction enzymes are scarce. Here we report One-step dual-primer dCAPS (OddCAPS), a modification that uses three primers in one reaction to overcome this constraint. Two of these primers, an intermediate primer and a dCAPS primer, sequentially introduce 1-2 base substitutions each into the amplicon, enabling up to four engineered base changes near the nucleotide of interest. By using the intermediate primer at 1/10-1/100 the concentration of the other primers, the desired product is generated directly in a single-tube, one-step PCR. Increasing the number of engineered substitutions improves the chance of using a researchers preferred restriction enzyme. In principle, having eight common restriction enzymes (BamHI, EcoRI, NheI, SalI, BglII, ClaI, HindIII, and MluI) suffices to detect any single-nucleotide variant in any biological or synthetic DNA sequence with this approach.

Archaea are promising chassis organisms in biotechnology, and the accurate annotation of their chromosomal replication origins (oriCs) is the key to unlocking their full potential. However, the existing Ori-Finder 2 web server suffers from low accuracy, slow speed, and limited scalability. In this study, we present Ori-Finder-Arch, an updated web server for high-performance oriC prediction in archaea. This pipeline integrates HMMER-based replication initiation protein (RIP) annotation, refined consensus motif recognition, and GC profile-based DNA unwinding element (DUE) detection. On a benchmark set of experimentally validated oriCs, Ori-Finder-Arch achieved a recall of 95.6% and a precision of 86.0%, substantially outperforming Ori-Finder 2 (62.2% and 63.6%, respectively), while running 4.75 times faster and supporting diverse assembly levels. When applied to the available archaeal assemblies, it successfully annotated 17,472 oriCs. Meanwhile, the web server provides interactive visualizations at different levels. In conclusion, Ori-Finder-Arch offers an efficient, accurate, and user-friendly platform for advanced studies of archaeal DNA replication initiation and synthetic biology applications, and is freely available at https://tubic.org/Ori-Finder-Arch/ and https://tubic.tju.edu.cn/Ori-Finder-Arch/.

Nephrons are the functional units of the kidney; within each nephron, the glomerulus is the initial site of selective filtration that allows removal of waste products while preserving proteins in the bloodstream. Each glomerulus consists of a network of capillaries surrounded by specialized epithelial cells, podocytes, which mediate selective filtration. Abnormalities in glomerular structure impair renal function, resulting in proteinuria and kidney disease. Although several microscopy-based approaches exist to characterize glomerular architecture and structural abnormalities, quantitative analysis is often limited by labor-intensive image segmentation. In this study we present a semi-automated approach for segmentation and analysis of glomerular architecture from three-dimensional confocal microscopy data. Using mTmG transgenic mice that express membrane-associated EGFP in podocytes and membrane-associated tdTomato across all other cell types, we reconstruct podocyte processes and glomerular capillaries from volumetric renal images. This semi-automated approach reduces manual segmentation effort and supports more efficient, standardized analysis of glomerular architecture in three-dimensional confocal microscopy datasets.

Activated leukocyte cell adhesion molecule A (Alcama) plays a role in axonal guidance, cell differentiation, and retinal lamination in a developing retina and was identified as a marker for activated Muller glial cells in adult zebrafish. However, its spatiotemporal localization and its involvement in retina regeneration remains unclear. Here we induced focal photoreceptor damage in zebrafish using laser photocoagulation and examined the expression and localization of Alcama at different time points post lesion. Immunohistochemistry in wild type fish and Tg(kdrl-EGFP) fish showed Alcama localized to the blood retina barrier with increased expression in Muller glial end feet and radial processes in a regenerating retina. To confirm its role in retina regeneration, alcama expression was transiently knocked down using morpholinos in adult fish. Scanning laser ophthalmoscopy, Zpr1 immunostaining and EdU staining showed delayed retina regeneration in alcama knockdown fish, indicating a possible role for Alcama in zebrafish retina regeneration.

Containerization enables portable, reproducible, and scalable scientific computing. However, container development, documentation, and deployment practices can vary widely, even within a single domain. Understanding patterns of how containers are implemented in real-world settings can inform community guidelines, quality scoring rubrics, and systems to automate software review. Focusing on bioinformatics as an exemplar domain, we surveyed published software tools to find applied containerization examples. After identifying >250 tools to review, we annotated metadata regarding version control, asset provenance, and general container image health and tested the ability to build and pull the container images in a purpose-built evaluation platform (https://github.com/vpnagraj/socr8s). The majority of images tested did not build successfully in our environment. Of the tool characteristics we tracked, the strongest predictor of build success was version control activity. Tools with commits in the preceding two years were roughly twice as likely to build. Deeper assessment of failures identified a variety of issues, including missing assets and broken dependency chains. While many tools had published images accessible in open registries, 24% could neither be built nor pulled. Images tended to be large, with median size of 1.57GB for those that were able to be built. Where image specification files were available, we found that more advanced container orchestration and build techniques were uncommon. Our results highlight areas of improvement in how containerized tools are built and maintained in bioinformatics and scientific computing software in general.

Structural variants (SVs) are a diverse group of genetic variants defined by a minimum size of 50 base pairs. SVs account for the majority of all variant bases in a persons genome and are commonly implicated in inherited disease and cancer. However, SV analysis is complex due to their wide variation in type and size, degree of polymorphism, involvement of repetitive sequences, and the myriad ways they may elicit a functional impact, as well as technical factors like imprecise breakpoint detection, and alternative representations of the same event. Despite recent advances in the detection and characterisation of SVs, it remains difficult to assess them beyond basic annotations and comparisons. Here we introduce SVlog, a transparent and extensible meta-programming framework for SV analysis. With the logic programming language Souffle as its engine, SVlog provides a declarative ontology describing relationships among SVs, genes and other genomic elements. Genome annotations and SV datasets - both user-provided and public reference data - are converted into relational facts, to which SVlog applies logical rules that define predicates. Predicates are specific, transparent and deterministic, yet fully flexible and composable, enabling detailed evaluation of SVs without relying on stochastic "black box" approaches. To showcase SVlog, we have developed a ready-made predicate library for SV annotation, comparison and prioritisation in the context of rare inherited disease. Despite its compact codebase, SVlog evaluates more than 50 input predicates to generate over 70 informative output predicates. It synthesises evidence from population and clinical genomic databases, and applies a tiered filtering strategy to identify candidate pathogenic SVs in patients with inherited disease. By focusing on explainability and modularity, SVlog offers a fast, reliable library for SV analysis and is a powerful deterministic alternative to traditional bioinformatics pipelines for clinical variant curation.

Introduction: C3 glomerulopathy (C3G) is driven by fluid-phase alternative complement pathway dysregulation, with emerging evidence linking glomerular neutrophil infiltration to disease severity. Neutrophil extracellular traps (NETs) are implicated in other forms of glomerulonephritis. However, their participation in the pathogenesis of C3G remains undefined. Methods: Kidney biopsies from 33 patients with C3G (15 with dense deposit disease [DDD] and 18 with C3 glomerulonephritis [C3GN]) were compared with 15 anti-neutrophil cytoplasmic antibody associated vasculitis (AAV) biopsies as a neutrophil-rich disease control in this retrospective cross-sectional study. Glomerular neutrophils and NETs were identified using immunofluorescence, staining for myeloperoxidase, citrullinated histone H3, peptidyl arginine deiminase-4, and DNA. Supervised machine learning was used to quantify glomerular NET formation, and the data were correlated with kidney function at time of biopsy using linear regression. Results: Intraglomerular NETs were abundant and detected in the majority of glomeruli in C3G biopsies. Compared with AAV, C3G showed a significantly higher fraction of neutrophils forming NETs, despite similar neutrophil counts per glomerulus. NET abundance was similar in DDD and C3GN. In exploratory analyses, a greater proportion of glomeruli containing NETs was associated with lower kidney function (estimated glomerular filtration rate) at biopsy, and this association remained significant after adjustment for age, C3G subtype, and interstitial fibrosis. Conclusions: These observations demonstrate that intraglomerular NETs are a common and prominent observation in C3G and are associated with reduced kidney function at biopsy. These findings raise the possibility that NET deposition in glomeruli is a previously unrecognized driver of glomerular injury in C3G.

Gene model for the ortholog of Insulin-like peptide 3 (Ilp3) in the D. pseudoobscura Apr. 2013 (BCM-HGSC Dpse_3.0/DpseGB3) Genome Assembly (GenBank Accession: GCA_000001765.2) of Drosophila pseudoobscura. This ortholog was characterized as part of a developing dataset to study the evolution of the Insulin/insulin-like growth factor signaling pathway (IIS) across the genus Drosophila using the Genomics Education Partnership gene annotation protocol for Course-based Undergraduate Research Experiences.

Extraocular motoneurons are the final neuronal relay implicated in gaze motor control and are known to be subdivided in functional subgroups, differently implicated in ocular motion dynamics. However, the maturation of these functional populations of extraocular motoneurons, in relation with the development of gaze-stabilizing reflexes remains largely unexplored. In amphibian tadpoles, the angular vestibulo-ocular reflex (VOR) appears later than other visuo-vestibular ocular reflexes and matures until the metamorphosis climax. Two types of Abducens motoneurons have been described to participate to the angular VOR in larval frog: spontaneous motor units, exhibiting a robust resting activity and silent motor units recruited only during head motion. The aim of this study was to investigate the maturation of these two types of Abducens motor units in relation with the development of the angular VOR by evaluating their discharge dynamic in response to head rotation in semi-intact preparations of larval Xenopus laevis. During larval life, the discharge modulation during sinusoidal head rotations increases significantly for silent units only, demonstrating a better sensitivity of this Abducens motoneuron sub-population to horizontal semicircular canal activation. In addition, this functional maturation was accompanied by an increase of the myelination in the lateral rectus motor nerve, promoting a faster conductivity in late larval stages than in early one. These findings showed that the development of the angular VOR is supported by a selective maturation of extraocular motoneurons subpopulations, specifically implicated in the improvement of the ocular kinematic during the reflex.

Click-qPCR is a browser-based application for relative qPCR analysis that requires a tidy-format CSV file containing four columns: sample, group, gene, and Cq. Preparing this input from qPCR instrument output typically requires manual reformatting and calculation of mean Cq values for technical replicates. To simplify this process, we developed Click-Prep (https://kubo-azu.shinyapps.io/Click-Prep/), an interactive web-based application designed specifically to create Click-qPCR input files. Click-Prep imports CSV, TXT, TSV, and XLS/XLSX files and supports skipping of instrument-generated metadata rows, interactive column mapping, and manual assignment of experimental groups. Users can review technical-replicate measurements, exclude selected rows according to predefined quality-control criteria, and calculate mean Cq values for each sample-group-target combination. Missing or nonnumeric Cq values are flagged for review and must be resolved before the mean is calculated. Click-Prep can also combine compatible formatted CSV files, such as datasets obtained from separate qPCR plates. The resulting dataset is exported as a standardized CSV file containing the four fields required by Click-qPCR. By integrating these operations into a guided browser-based workflow, Click-Prep enables users to prepare Click-qPCR input files rapidly and consistently without programming.