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PubMed2026

Development of a cell-based nanoluciferase reporter system for high-throughput screening of HBV cccDNA inhibitors.

Hepatitis B virus (HBV) persistence is sustained by the viral covalently closed circular DNA (cccDNA) minichromosome, which remains a major barrier to curative antiviral therapies. The lack of reliable quantitative cccDNA detection methods and surrogate markers has hindered efforts to target cccDNA in antiviral high-throughput screening (HTS). Here, we established a novel inducible cccDNA-dependent nanoluciferase (NLuc) reporter cell line, designated HepBLE12, by inserting an in-frame 11-amino acid split-NLuc HiBiT tag into the precore (pC) coding region of an HBV transgene. The resulting 1.3-kDa HiBiT tag on pC serves as the detection module of the split NLuc system, generating quantitative luminescence upon high-affinity complementation with the cognate 18-kDa LgBiT subunit in cell lysates. Notably, the HiBiT assay enables direct detection of intracellular HiBiT-pC protein rather than secreted HBeAg, providing a reporter signal more closely linked to cccDNA activity. HepBLE12 cells exhibited inducible and robust viral DNA replication, and the cccDNA-dependent HiBiT signal was validated under diverse experimental conditions that modulate cccDNA formation or transcription. We further miniaturized the assay to a 384-well format and optimized key parameters following standard HTS assay development practices. The assay was successfully automated and demonstrated excellent performance in a multi-day variability study and a pilot screen, with signal-to-background (S/B) ≈ 9, coefficient of variance (CV) < 10%, and average Z-factor value of 0.74, exceeding canonical HTS quality benchmarks. Together, the HepBLE12 cell-based HTS platform provides a robust and practical tool for identifying inhibitors targeting HBV cccDNA.

Hepatitis B virus↗

PubMed2026

High-throughput glycan array screening reveals rhamnogalacturonan-I as a ligand for Arabidopsis leucine-rich repeat receptor kinases involved in plant immunity.

The plant cell wall not only serves as a physical barrier against pathogens but, when damaged, also functions as a source of cell wall-derived molecules that play crucial roles in plant immunity as damage-associated molecular patterns. While oligogalacturonides from homogalacturonan are well-studied damage-associated molecular patterns, the immune-signaling potential of other cell wall components remains largely unexplored. Conventional genetic and biochemical approaches aimed at identifying ligand-receptor pairs in plant immunity have been limited by the vast diversity of potential ligand molecules and functional redundancy of putative receptors. In this study, we developed a high-throughput screening pipeline that simultaneously examines multiple interactions between plant cell wall-derived glycans and >350 extracellular domains of receptor kinases and receptor-like proteins in Arabidopsis, resulting in the screening of >40 000 interactions. We discovered a group of leucine-rich repeat receptor kinases named ARMs (AWARENESS of RG-I MAINTENANCES) that interact with rhamnogalacturonan-I (RG-I), a major component of pectin. RG-I treatment induced pattern-triggered immunity responses with distinct kinetics compared to oligogalacturonide responses. We identified RG-I oligosaccharide structures required for interaction with ARM receptors and immune activation and found that ARM receptors function redundantly in plant immunity. Collectively, our work provides a powerful platform for discovering glycan-receptor pairs in plants, facilitating a more comprehensive understanding of cell wall surveillance mechanisms in plant immunity.

Arabidopsis↗

PubMed2026

Integrating ex vivo platforms with AI to guide glioblastoma treatment.

PURPOSE: Ex vivo platforms can rapidly and cost-effectively screen patient-derived tumor cells or tissue. Artificial intelligence (AI) algorithms can search and identify patterns in large datasets and provide predictions. This review focuses on integrating microphysiological platforms with AI to inform physician and patient decision-making. METHODS AND RESULTS: Combining efficacy, safety, and pharmacology results from drug screens with the output of extensive AI searches can yield insights to guide physician and patient decision-making and potentially improve a patient's prognosis. We detail ex vivo platforms at different stages of development that represent the diversity of approaches: a microphysiological system and a high-throughput screen that assesses drug cytotoxicity in both bulk and drug-tolerant tumor cells. We review AI approaches that can enhance the utility of microphysiological platforms. CONCLUSION: Integrating emerging microphysiological platforms with AI is expected to significantly impact physician and patient choice of treatment.

Humans↗

PubMed2026

Decoding sequence recognition code of nucleic acid-binding proteins of human-infecting DNA viruses.

Human-infecting DNA viruses remain major health threats, yet the DNA-recognition mechanisms of their nucleic acid-binding proteins (NBPs) are poorly understood. Here, we systematically profiled 103 viral NBPs from human-infecting DNA viruses, with three NBPs from non-human-infecting DNA viruses as controls, using high-throughput screening. This analysis identified diverse DNA-binding motifs and specificity modules, including convergent recognition of a conserved CCACC motif across phylogenetically distant viruses. Notably, viral NBP binding-site distributions varied with genome size, and several NBPs from small-genome viruses showed enrichment on mitochondrial DNA. Functional assays further supported their mitochondrial association and effects on mitochondrial membrane potential. By integrating an ivTRT-based ssDNA-SELEX workflow, we further found that ssDNA viral NBPs recognize dimer-like and inverted-repeat sequences with potential to form stem-loop structures. Collectively, this study constructs a comprehensive viral NBP DNA-recognition atlas, offering a fundamental resource for elucidating viral genome recognition mechanisms, virus-mitochondria interactions, and developing future antiviral strategies.

Letter↗

PubMed2026

A streamlined protocol for small-scale protoplast generation and CRISPR/Cpf1-mediated genome editing in Fusarium oxysporum.

Fusarium oxysporum is a significant threat to agriculture and One Health, requiring advanced molecular tools for functional genomic analyses and biological control agent development. Existing gene-editing methods are hampered by costly protoplast preparation protocols and by CRISPR-Cas9 limitations, such as restricted protospacer adjacent motif (PAM) sequences and complex guide RNA requirements. We engineered an efficient CRISPR/Cpf1 system that overcomes these issues through three main innovations: small-scale protoplast generation using filter column-based methods that greatly reduce enzyme consumption while simplifying workflows, a CRISPR/Cpf1 system with shorter guide RNA design and staggered DNA cleavage to promote homologous recombination, and minimal homology arm strategies that significantly decrease cloning complexity. Extensive validation confirms successful gene targeting with molecular verification and functional analysis via standardized pathogenicity assays. This integrated platform offers affordable, accessible tools for systematic F. oxysporum research, enhancing fundamental understanding of plant-pathogen interactions and supporting high-throughput screening vital for agricultural biotechnology and biological agent development.

CRISPR/Cpf1↗

PubMed2026

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-β (Aβ) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article↗

PubMed2026

Generation of spCAS9 expressing human mesenchymal stem cell line to study gene function during osteoblast differentiation.

Human bone marrow-derived stromal cells (hMSCs) are a great resource for studying how genes influence cell fate and differentiation into various cell types like osteoblasts, adipocytes, and chondrocytes, among other cell types. However, genetic manipulation of primary hMSCs has been challenging due to their short lifespan and cellular senescence after limited passaging. Their low and unstable transfection efficiency also complicates gene delivery or inactivation, hindering long-term functional studies. The limited lifespan has been effectively solved by immortalizing hMSCs with telomerase reverse transcriptase (hMSCs-TERT). The use of these cells is ideal for functional studies of osteoblast and adipocyte differentiation through genetic manipulation, providing a stable and reliable model. Here, we have engineered a stable CAS9 expressing hMSC-TERT cell line (hMSC-TERTCAS9) via lentiviral transduction. The constitutive expression of spCas9 enables efficient and reproducible gene editing. We demonstrate the potential of these hMSC-TERTCAS9 cells for generating gene disruptions using plasmid delivery of guide RNAs as a fast and efficient strategy for targeted genome editing. The edited cells can be sorted and expanded as single cells to obtain homogenous clonal cell lines with mono- as well as bi-allelic gene deletions, a crucial step for producing reliable experimental results. We further validate this cell line as a powerful tool for studying gene function during hMSC proliferation and differentiation, providing 3 distinct examples of its utility. Through the generation of indels, single-cell sorting, and clonal selection, we have efficiently inactivated the vitamin D receptor and created both larger (256 nucleotides) gene disruptions in Forkhead box protein O1 and precise removals of a small genomic sequence (73 nucleotides) coding for microRNA MIR675. This novel hMSC-TERTCAS9 cell line represents a significant advancement, offering a stable, efficient, and versatile platform for advanced genetic studies, high-throughput screening, and the creation of reliable cellular disease models.

CRISPR-Cas9↗

PubMed2026

Pediatric sarcomas: challenges and opportunities.

Pediatric sarcomas are a heterogeneous group of rare mesodermal malignancies. These cancers, which affect children from infancy through adolescence and young adulthood, are in general challenging to treat with currently available therapies. Biologically, many are characterized by quiet genomes, fusion oncoproteins, immune "cold" microenvironments, and vast epigenetic deregulation that contributes to diverse and complex mechanistic drivers. Multifaceted advancements in research strategies, including high-throughput screening, new model systems, surfaceome profiling, and study of oncogenic fusion condensates have led to new opportunities for understanding the biology of pediatric sarcomas. To continue to make progress for these difficult to treat cancers, it will be critical to continue to improve access to bioinformatic data, approach patient care using innovative clinical trial frameworks, and foster interdisciplinary partnerships among medicinal chemists, scientists, clinicians, advocates, and industry partners.

Humans↗

PubMed2026

Molecular biology and integrated strategies for activating cryptic biosynthetic gene clusters toward next-generation antibiotic discovery.

Antimicrobial resistance (AMR) has been identified as one of the 21st century's severest global public health crises. AMR led to an estimated 4.95 million deaths in 2019 and will claim 10 million lives a year by 2050 in the absence of targeted interventions. During the same period, the number of novel antibiotics discovered has decreased drastically as many researchers are rediscovering known antibiotics, non-model microorganisms are poorly understood or difficult to culture and antibiotic research and development investment has declined drastically. However, high-throughput whole genome sequencing and the subsequent application of bioinformatics in bacterial and fungal genomes have shown that a numerous of cryptic or silent biosynthetic gene clusters (BGCs) remain latent at ambient laboratory conditions since their genes are transcriptionally inactive. Cryptic BGCs represent a vast source of unique secondary metabolites, many of which may yield novel antibacterial, antifungal, anti-cancer and other potentially valuable natural products. This review discusses the biological relevance of cryptic BGCs, the major limiting factors that restricts their activation and novel strategies that have been employed to activate them and exploit their potential to produce novel natural products. The review focuses on biological approaches including CRISPR-Cas mediation for the activation of cryptic BGCs, promoter engineering, pathway refactoring, and heterologous expression; biochemical strategies such as Osman, OsMAC, Precursor Feeding, Chemical Elicitation, Epigenetic Regulation and Co-cultivation and technology-based strategies such as Genome mining, Microfluidic Cultivation systems, High-Throughput Screening, Metabolomics, Molecular Networking and Artificial Intelligence and Machine Learning based prediction of BGCs and their metabolites. The use of multi-omics technologies combined with synthetic biology to achieve better discovery, characterization and large-scale production of novel natural products is also discussed herein. Finally, we will talk about the ecological significance and evolutionary advantage of cryptic BGCs' role in interactions between microorganisms, such as competition, communication, symbiosis and environmental adaptability, so as to provide a useful background for accelerating next-generation antibiotics.

CRISPR-Cas activation↗

PubMed2026

Identification and characterization of ectopic chromosomal amplifications in acute myeloid leukemia cell limes using high-throughput chromosome conformation capture screening.

Despite advanced molecular diagnostics, improving outcomes for refractory acute myeloid leukemia (AML) remains challenging. Although many cancer-related genes are identified, their molecular mechanisms are not fully elucidated. Amplification is a mechanism of cancer-associated gene activation, and ectopic gene amplification may have particularly high pathological significance. However, research on ectopically amplified cancer-associated genes in leukemia remains limited. Here, we evaluated the usefulness of high-throughput chromosomal conformation capture (Hi-C) as a screening method for ectopic gene amplification and assessed whether ectopic amplification of cancer-associated genes may represent a general phenomenon in AML. We screened the U-937 and NB-4 cell lines using in situ Hi-C. Regions appearing as "high-intensity bands" in Hi-C contact maps were identified and validated using fluorescence in situ hybridization (FISH). Additionally, copy number variation analysis was performed using whole-genome sequencing (WGS) to extract cancer-associated genes with ectopic amplification. In the U-937, three genomic regions showing "high-intensity bands" were identified and confirmed as ectopic amplifications-including PDCD1LG2 (PD-L2), CD274 (PD-L1), and JAK2; that is, four copies were detected by WGS, and amplification signals were observed by FISH. In the NB-4, four such regions were detected, including MYC and KRAS, with expression level of 498 transcripts per million (TPM) and 34 TPM, respectively. Copy number variation analysis further identified multiple cancer-associated genes with ectopic amplification. Overall, these findings demonstrate the presence of ectopic amplification of cancer-associated genes in AML cell lines and support the usefulness of Hi-C as a screening method for detecting such genomic alterations.

Acute myeloid leukemia↗

PubMed2026

From complexity to clarity: Building dashboards for hit selection in high throughput screens.

High throughput screening produces large, complex datasets that are difficult to interrogate without programming expertise, making hit selection time-consuming and inflexible. While instrument software and commercial tools offer partial solutions, they often lack adaptability or require costly infrastructure. Interactive dashboards provide an effective alternative by enabling dynamic filtering and integrated visualization within a single interface. Here, we present simple R Markdown-based templates for creating customizable, modular dashboards for screen data analysis. Built using the flexdashboard and crosstalk R packages, and HTML widgets, these lightweight, easy-to-build HTML dashboards require no complex installation process or installation of licensed software. They support linked visualizations, threshold-based filtering (e.g., Z-score, p-value, fold change), and interactive data exploration and are shared as a standalone HTML file. This framework enables rapid, flexible hit selection across diverse high throughput screening applications and is designed for users with basic R experience.

High-Throughput Screening Assays↗

PubMed2026

Innovations in microbial physical mutagenesis for food fermentation: An overview from traditional to emerging technologies.

Microbial strains serve as an important factor affecting fermentation efficiency and product quality. To obtain superior strains, mutation breeding is a classic strategy. Compared to chemical mutagenesis, physical mutagenesis directly induces genomic changes, providing notable advantages such as the elimination of chemical residues and environmental sustainability, hence rendering it a favored method for enhancing food-grade microorganisms. Conventional physical mutagenesis mostly depends on UV, rays, high pressure, or space radiation. As physical technologies advance, emerging methods such as ion implantation, plasma, microwave, ultrasound, and pulsed light are widely utilized for genetic modification. Mutagenesis technologies are progressively transitioning from single-effect to multi-effect synergy. Recent evaluations indicate that emerging technologies can enhance microbial mutation efficiency at the application level relative to established technologies. Nonetheless, the systematic clarification and comparative analysis at the mechanistic level remain inadequate, hindering intuitive comprehension of the qualities and distinctions across techniques. Furthermore, physical mutagenesis encounters several significant obstacles, such as cellular damage, limited rates of advantageous mutations, and laborious screening processes. This review carefully elucidates the mechanisms and properties of physical mutagenesis technology and delineates the distinctions among approaches through comparative analysis. Simultaneously, solutions for optimizing mutagenesis are presented to tackle the principal challenges mentioned above. This review aims to offer a theoretical foundation and practical guidance for the enhanced application of physical mutagenesis technologies in microbial breeding.

Mutagenesis↗

PubMed2026

Engineering bubble structures as Cas12a activators for highly sensitive monitoring of WRN helicase function.

The Werner syndrome helicase (WRN) is a critical synthetic lethal target in microsatellite instability cancers, essential for resolving complex genomic structures like replication bubbles and R-loops. However, strategies to simultaneously discriminate WRN activity on DNA versus DNA-RNA substrates in living cells are lacking. Here, we developed a structure-specific CRISPR/Cas12a biosensing strategy to visualize WRN functional activity by engineering bubble-structure probes. These probes were rationally designed to structurally mimic DNA replication bubbles and R-loop associated DNA-RNA hybrids. Upon specific unwinding by WRN, the probes release a sequestered activator strand that triggers Cas12a trans-cleavage, effectively converting the unwinding event into an amplified fluorescent signal. This assay achieves low picomolar sensitivity (LODs: 5.6-6.0 pM) and exceptional selectivity against homologous RecQ helicases. Uniquely, this strategy enables the parallel quantification of WRN activity on both substrate types, providing insights into distinct WRN-mediated pathways for resolving genomic stress. We further demonstrated the strategy's utility by visualizing endogenous WRN dynamics in living cells and profiling the efficacy of small-molecule inhibitors. This work offers a powerful molecular toolkit for dissecting WRN biology and facilitating high-throughput drug screening in targeted cancer therapy.

Werner Syndrome Helicase↗

PubMed2026

DURABLE: A Workflow for Determining Corrosion-Driving and Protective Microbial Mechanisms.

Microbiologically influenced corrosion (MIC) threatens global infrastructure, causing billions of dollars in annual losses. Its persistence stems from unresolved mechanisms─particularly the metabolites produced by microorganisms that drive or inhibit corrosion─and the microbial community structures. Progress has been hindered by the absence of systematic workflows to rapidly and accurately identify MIC-relevant microorganisms and their functions. Here, we present DURABLE (Detection of Unique Corrosion Resistant or Accelerating Biologics in a Laboratory Environment), a pipeline that couples high-throughput microbial screening with genomic and metabolic workflows. We applied the DURABLE workflow to six diesel tank samples and revealed fuel-dependent microbial community structures, which showed greater diversity and evenness in bacterial communities than their fungal counterparts. The workflow used carbon steel beads to rapidly screen over 80 bacterial isolates for corrosive activity, reducing assay time to approximately 2 days compared with the conventional 30-day metal coupon test. More than 40 isolates were identified as corrosive. Further testing using mass spectrometry analysis revealed corrosion-associated metabolites, which were further validated using electrochemical assays. Thus, DURABLE achieved a ∼15-fold increase in screening speed and provided a scalable and mechanistic framework for dissecting MIC dynamics. We expect this advance will enable the development of precision mitigation strategies in hydrocarbon fuel infrastructure.

Bacteria↗

PubMed2026

High-throughput recovery of integron cassettes for gene discovery screens.

Integrons capture functional genes in mobile genetic elements called integron cassettes, which represent an untapped source of genes of biotechnological interest. Here we present two tools, cassette gatherer and cassette hunter, that enable high-throughput establishment of gene libraries either from genetically tractable strains or directly from DNA. We re-engineered a class 1 integron into counterselection markers on a plasmid or on the chromosome of a naturally competent Vibrio cholerae, which enabled capture of single cassettes in a sequence- and function-independent manner. When applied to Vibrio strains and genomic libraries, our tools recovered hundreds of single cassettes per assay with more than 99% specificity. We further subjected the library of cassettes generated by the hunter and gatherer tools to screens against phages ICP2 and T4, and identified nine phage-defence systems, including five previously undescribed. These tools enable rapid and large-scale recovery of integron cassettes that could be leveraged for functional gene discovery.

Journal Article↗

PubMed2026

Genome-scale overexpression screening identifies product tolerance and efflux transport as key determinants of high-level L-tryptophan production in Escherichia coli.

L-tryptophan is a high-value aromatic amino acid widely used in the food, feed, and pharmaceutical industries. However, large-scale microbial production is constrained by insufficient precursor supply and limited strain tolerance to high product concentrations. In this study, modular metabolic engineering was first employed to enhance the availability of key precursors, including shikimate, serine, and glutamine, yielding strain TRPJ-13 with a 34.6% increase in L-tryptophan titer. To enhance strain tolerance, an indigo-based high-throughput reporter system was constructed and coupled with genome-scale overexpression library screening, leading to the identification of soxS as a tolerance-conferring target. Mechanistic analysis demonstrated that soxS upregulated lpxC to enhance lipopolysaccharide biosynthesis, thereby reinforcing membrane integrity and improving L-tryptophan tolerance. Combinatorial engineering of soxS and lpxC generated strain TRPJ-23, which increased L-tryptophan tolerance by 74.8% and L-tryptophan titer by 10.3%. Furthermore, YicL was identified as a novel transmembrane protein involved in L-tryptophan transport that effectively promoted L-tryptophan efflux, further increasing the titer by 9.0%. After fermentation optimization, strain TRPJ-28 produced 74.3 g/L L-tryptophan in a 5-L bioreactor, with a yield of 0.26 g/g and a productivity of 1.24 g/L/h. In a 1000-L pilot-scale bioreactor, TRPJ-28 reached a titer, yield, and productivity of 70.4 g/L, 0.25 g/g, and 1.17 g/L/h, respectively. This study provides new engineering insights for developing industrially promising L-tryptophan-producing strains.

Genome-scale overexpression screening↗

PubMed2026

Development of a PCR-based technique for genotyping UGT1A1 gene and distribution of rs3064744 alleles in the Russian population.

BACKGROUND: Accurate determination of tandem thymine-adenine (TA) repeat numbers in the UGT1A1 promoter region (rs3064744) is essential for diagnosing Gilbert's syndrome and personalizing therapy with toxic agents like irinotecan and atazanavir. However, traditional polymerase chain reaction (PCR) assays face severe limitations due to the AT-rich sequence and overlapping melting temperatures (Tm) of the highly homologous 7TA and 8TA alleles. In this context, melting curve analysis (MCA) employing fluorophore-quencher systems has emerged as a promising alternative. The purpose of this study was to develop a novel genotyping approach combining optimized aPCR-MCA analysis with an automated classifier to overcome the limitations posed by the differentiation of highly homologous alleles and to demonstrate its practical application, providing the distribution of rs3064744 genotypes across four regional cohorts of the Russian population. METHODS: A specialized Dual Head 1D-convolutional neural network (1D-CNN) ensemble with Test-Time Augmentation (TTA) was developed. The model was trained and internally validated on 1,620 engineered plasmid samples, and independently evaluated on an external clinical test set of 440 unique patient genomic DNA specimens. Real-time PCR was performed on CFX96 and DTprime platforms. Additionally, population-wide screening was conducted on 997 archival clinical samples from Moscow, Sakha (Yakutia), Dagestan, and Rostov regions. RESULTS: While 5TA and 6TA alleles were easily separated, absolute Tm distributions of 7TA and 8TA alleles overlapped significantly, and non-uniform Tm shifts of 0.8 °C-1.4 °C occurred across platforms. Conventional absolute Tm thresholding was therefore inadequate. By assessing relative morphological curve divergence against co-amplified 7TA/7TA and 7TA/8TA reference anchors, the 1D-CNN ensemble neutralized instrument noise. It achieved 100% accuracy on internal validation and 100% concordance (440/440) with clinical reference pyrosequencing. Population screening revealed that Dagestan, Yakutia, and Rostov cohorts closely align with the European population. Rare 5TA and 8TA alleles were detected at low frequencies in Yakutia and Moscow. CONCLUSION: Combining LNA-modified aPCR-MCA with a comparative 1D-CNN model successfully circumvents thermodynamic limitations and eliminates human operator bias. This integrated system offers an accessible, high-throughput, and clinically valid solution for routine UGT1A1 pharmacogenetic testing.

1D-CNN↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗