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PubMed2026

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans↗
PubMed2026

Shared genetic architecture and cellular convergence between female reproductive disorders and pulmonary function: a genome-wide cross-trait analysis.

Female reproductive disorders (FRDs), including polycystic ovary syndrome, endometriosis, uterine leiomyomata, and infertility, have been epidemiologically associated with impaired pulmonary function. However, it remains unclear whether this cross-organ link reflects shared genetic etiology and, if so, which cellular mechanisms mediate it. We performed a systematic genome-wide cross-trait analysis of three FRDs and lung function traits (FEV₁, FVC, FEV₁/FVC) using GWAS summary statistics from individuals of European ancestry, integrating genetic correlation, bidirectional causal inference, pleiotropy mapping, and single-cell enrichment analyses. We identified significant negative genetic correlations between FRDs and lung volume traits, most prominently for FVC (rg range: - 0.077 to - 0.178). Bidirectional causal analyses indicated that FRDs have a detrimental effect on lung volume, with higher FRD genetic liability associated with reduced lung volume. Cross-trait meta-analysis identified 17 pleiotropic variants across 11 loci, with the 19q13.2 (LTBP4) and 12q13.13 (HOXC6/HOXC9) loci showing strong evidence of shared causal variants. Critically, single-cell analyses revealed that shared genetic risk converged on mesenchymal lineages across organs, specifically alveolar adventitial fibroblasts in the lung and stromal/smooth muscle cells in the endometrium. Transcriptome-wide analyses further nominated the estrogen-responsive gene RERG as a convergent gene linking these conditions with lung function. Our study revealed a shared genetic architecture between female reproductive disorders and lung function traits, providing a basis for further mechanistic investigations and potential clinical evaluation. Furthermore, our findings suggest that shared fibroproliferative and hormone-responsive pathways may offer insights into the biological mechanisms underlying these conditions.

Female↗
PubMed2026

Mapping the immune-genetic architecture of Epstein-Barr virus-related phenotypes and multiple sclerosis through a single-cell genetic framework for target prioritization and pharmacologic hypothesis generation.

BACKGROUND: Multiple sclerosis (MS) is a severe neuroinflammatory disease causing substantial long-term disability. Strong epidemiologic evidence links Epstein-Barr virus (EBV) exposure with MS risk, but genetic evidence for immune target prioritization in EBV-related phenotypes remains limited. METHODS: We integrated single-cell cis-eQTL data from 14 immune cell types with GWASs of an EBV-related clinical phenotype and MS using a single-cell Mendelian randomization framework with colocalization analyses. Candidate eGenes were evaluated in independent cohorts. For multi-SNP instruments, we performed heterogeneity, pleiotropy, MR-Egger, weighted median, mode-based, and MR-PRESSO sensitivity analyses. We also conducted phenome-wide association analyses and queried DrugBank to annotate candidate compounds targeting prioritized genes. RESULTS: We prioritized 43 immune-cell-specific candidate eGenes with convergent genetic support, including 6 for the EBV-related phenotype and 37 for MS. SERPINB1 in NK cells was associated with increased risk of the EBV-related phenotype, whereas HLA-G was associated with decreased risk. For MS, APOM and MSH5 showed protective associations, while AHI1 showed cell-type-dependent, bidirectional associations across immune lineages. Colocalization and independent cohort evaluation supported these findings. Among FDR-significant multi-SNP associations, MR-Egger intercept tests did not indicate directional pleiotropy, although a small subset showed heterogeneity or MR-PRESSO signals. Phenome-wide analyses identified no significant adverse phenotypic associations among evaluable genes at the prespecified threshold. DrugBank annotation nominated sodium nitroprusside, fasudil, artenimol, and choline as hypothesis-generating compounds for experimental follow-up. CONCLUSIONS: This study provides a single-cell genetic framework for prioritizing immune-cell-specific candidate targets for EBV-related phenotypes and MS, and nominates genetically supported targets and pharmacologic hypotheses for experimental investigation.

Humans↗
PubMed2026

Context matters: coordinated transcriptional regulation and root plasticity under multinutrient conditions.

Plants often encounter simultaneous imbalances in multiple nutrients, but the regulatory logic coordinating their responses remains poorly understood. We aimed to uncover shared transcriptional programs and regulatory nodes underpinning multinutrient adaptation in Arabidopsis thaliana roots. We analyzed publicly available RNA-seq datasets spanning 15 nutrient and beneficial element conditions using differential expression, co-expression network (WGCNA), and gene regulatory network analysis. Selected transcription factors (TFs) were validated via root phenotyping, suberin staining, and ionomic profiling under two-nutrient stress conditions. We identified a core set of 2050 genes responsive to multiple nutrient treatments, enriched for suberin biosynthesis, and structured into modular co-expression clusters. Eight prioritized candidate TFs (ARR10, GBF3, HHO5, NAC32, NF-YA3, NF-YB2, SARD1, and WRKY33) were shown to modulate root system architecture under specific nutrient combinations. WRKY33 and NF-YB2, in particular, regulated nutrient-responsive suberin deposition and ionomic plasticity. These findings reveal suberin remodeling as a shared downstream process in multinutrient responses and suggest that plasticity is not a fixed trait but a modular, polygenic, and context-dependent outcome. Repurposed TFs with pleiotropic functions coordinate structural and physiological traits, providing regulatory entry points for improving nutrient resilience.

Plant Roots↗
PubMed2026

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans↗
PubMed2026

Divergent trajectories of genome architecture and chromosome evolution in ferns and angiosperms.

Ferns and angiosperms represent the two largest vascular plant lineages but exhibit striking genomic and ecological contrasts. We investigated whether differences in genome size, chromosome architecture, GC content, and stomatal traits reveal divergent evolutionary trajectories between these lineages. We assembled the most comprehensive dataset to date, integrating genome size, chromosome number and size, GC content, and stomatal traits for over 1100 fern species and compared it with an extensive angiosperm dataset. Ferns exhibited markedly lower variability and c. 16-fold slower rates of chromosome size evolution than angiosperms. A persistent positive relationship between genome size and chromosome number in ferns suggests limited cytological post-polyploid diploidization. While ferns generally possess larger stomata, this difference disappears after accounting for genome size, indicating that nucleotypic constraints, rather than lineage-specific physiology, dictate stomatal dimensions. Both groups share a unimodal GC-genome size relationship peaking at c. 14 Gbp. Larger fern chromosomes imply lower genome-wide recombination rates, potentially limiting genetic reshuffling and adaptive potential. Our results highlight fundamentally divergent evolutionary trajectories, likely shaped by meiotic symmetry in ferns and meiotic asymmetry, possibly centromere drive, and post-polyploid diploidization in angiosperms, defining the functional and genomic landscapes of these lineages across deep evolutionary timescales.

Genome, Plant↗
PubMed2026

Epigenetic Gene Networks Governing Immune State Transitions Across the Lifespan.

Immune function across development, tissue repair, aging, and disease depends not only on signaling pathways but also on epigenetic architectures that determine whether coordinated transcriptional programs can be accessed and resolved. Increasing evidence indicates that epigenetic gene networks regulate the accessibility and reversibility of semi-stable immune states, shaping plastic, homeostatic, reparative, and degenerative configurations. We propose the concept of epigenetic transition windows, defined as temporally and contextually restricted intervals during which epigenetic constraints are relaxed, permitting coordinated and reversible transitions between immune states. During development, these windows are broad and support immune tolerance and adaptive plasticity. In adulthood they become spatially and temporally restricted, preserving stability while enabling conditional adaptation. With aging, they progressively narrow, contributing to chronic inflammation, impaired repair, and increased vulnerability to neurodegeneration. Conversely, pathological persistence of regulatory permissiveness may underlie immune evasion and sustained plasticity in cancer. We outline operational genomic readouts for quantifying transition windows, including chromatin accessibility variance, enhancer switching dynamics, reversibility metrics, and cross-cell coordination indices, and derive experimentally testable predictions that distinguish this model from pathway-centric or damage-centric explanations. By reframing immune dysfunction as a failure of regulated state transition rather than excessive signaling alone, this framework integrates inflammaging, trained immunity, immune resolution failure, and tumor immune escape within a unified regulatory architecture and provides a systems-level perspective on immune adaptability across the lifespan.

Epigenesis, Genetic↗
PubMed2026

Ultrastructural Insights Into the Reproductive Anatomy and Eggs of Cotton Pink Bollworm, Pectinophora gossypiella Saunders (Lepidoptera: Gelechiidae).

The pink bollworm, Pectinophora gossypiella Saunders is a major pest of cotton, notorious for its high reproductive potential and rapid evolution of resistance to Bacillus thuringiensis (Bt) toxins. Despite its economic significance, detailed knowledge of its reproductive anatomy and egg ultrastructure has remained limited, constraining the development of advanced molecular control strategies such as CRISPR/Cas9-based genome editing. The present study provides the first comprehensive characterization of the reproductive system and egg surface morphology of P. gossypiella using stereomicroscopy and scanning electron microscopy (SEM) techniques. The male reproductive system consists of fused, bean-shaped testes, seminal vesicles, duplex and simplex ejaculatory ducts, and paired accessory glands. The female reproductive system comprises paired ovaries with four polytrophic ovarioles per ovary, lateral and common oviducts, accessory glands, corpus bursae, and spermathecal glands. Eggs are oval, dorsoventrally flattened, exhibit a reticulated chorion with distinct micropylar and aeropylar regions. SEM images revealed 6-9 rosette cells encircling a circular micropylar plate, 14-19 first order and 17-23 s order ribs, and 250-291 polygonal surface cells. The structural features of P. gossypiella eggs reveal key sites for sperm entry, aeropylar respiration, and candidate zones for microinjection in gene editing applications. These findings establish a morphological baseline critical for optimizing embryo manipulation and ribonucleoprotein (RNP) delivery in lepidopteran genome editing. This study represents a pioneering effort to integrate classical egg morphology with molecular entomology, thereby advancing precision genetic interventions aimed at resistance management and population suppression in P. gossypiella.

Animals↗
PubMed2026

Insights into the regulation of the HOTAIR proximal promoter.

HOTAIR (HOX transcript antisense RNA) is a HOXC-cluster long intervening non-coding RNA (lincRNA) whose cancer relevance is tightly coupled to how its transcription is wired into hormone, hypoxia, inflammatory, and developmental signaling. HOTAIR is known to associate with cancer cell proliferation, motility, tumor invasion, and metastasis. The present mini-review focuses on the regulatory architecture and mechanistic complexity of HOTAIR transcriptional regulation, with emphasis on three organizing principles. First, we consider the impact of promoter choice between a canonical proximal promoter (P1), which supports the 2.2-2.4 kb transcript, and an alternative upstream promoter/TSS (P2), which contributes to context-dependent transcription initiation. Second, we examine the long-distance enhancer-promoter communication between HOTAIR distal enhancer and P1/P2. Third, we summarize the recent epigenetic and epi-transcriptomic mechanisms involved in HOTAIR transcript initiation and elongation. A combination of these events determines isoform-specific transcription to govern cell-type-, context-, and cancer specific modulation of HOTAIR expression that promotes tumor formation and cancer progression. Finally, the review proposes how large-scale RNA datasets, long-read sequencing, and isoform-specific studies can refine our understanding of this versatile lincRNA's regulation.

Humans↗
PubMed2026

Emerging Principles in Spatial Functional Genomics.

Spatial transcriptomic and proteomic atlases have enabled mapping of gene programs within intact tissues, but these measurements remain largely descriptive and do not define the mechanisms controlling tissue biology. Pooled CRISPR screening provides scalable causal interrogation of gene function but remains largely confined to dissociated systems that lack spatial context. In vivo spatial functional genomics (SFG) bridges these approaches by integrating genetic perturbations with in situ transcriptomic and proteomic readouts to measure gene function within intact tissue ecosystems. By preserving spatial organization, SFG enables interpretation of perturbations through effects on cell-cell interactions, diffusible signals, multicellular niches, and tissue architecture. Here, we outline key design axes of SFG: perturbation strategy, barcoding strategy, and phenotypic readout. We discuss computational challenges, including spatial autocorrelation, neighborhood dependence, and context-aware null modeling, and highlight how SFG reveals non-cell-autonomous, architecture-dependent mechanisms of gene function, advancing toward predictive models of tissue organization and gene function.

Genomics↗
PubMed2026

Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

Consanguinity↗
PubMed2026

A multi-model genome-wide association study identifies genetic variants underlying resistance to Largemouth Bass Ranavirus (LMBV) in Micropterus salmoides.

Largemouth bass (Micropterus salmoides) is an economically important freshwater aquaculture species, yet recurrent outbreaks of Largemouth Bass Ranavirus (LMBV) continue to impair production and cause substantial losses. The genetic basis of host variation in LMBV resistance remains insufficiently characterized. Here, we applied a multi-model genome-wide association study (GWAS) to identify loci associated with resistance following a controlled challenge with the LMBV-23PY strain. Whole-genome resequencing was performed for 146 phenotyped fish, including 72 susceptible and 74 resistant individuals. After stringent quality control, 877,262 high-quality variants were retained and tested using six GWAS models. Across binary survival status and survival time phenotypes, 32 shared suggestive variants were consistently detected across models, representing suggestive loci for LMBV-23PY resistance. Genes within ±50 kb of these loci were annotated, and functional enrichment highlighted immune- and redox-related biological processes. Three prioritized candidates-GSTT3L (glutathione S-transferase theta-3-like), CGRP2 (calcitonin gene-related peptide 2), and NPPC (natriuretic peptide C)-were associated with pathways involved in oxidative stress responses and immune regulation. Collectively, these results provide insight into the genetic architecture of LMBV-23PY resistance in largemouth bass and identify suggestive variants and associated candidate genes for downstream validation, functional interrogation, and the development of marker-assisted and genome-enabled breeding strategies.

Animals↗
PubMed2026

Biallelic Variants in ATP1A4 Are Associated with Oligoasthenoteratozoospermia and Male Infertility.

Male infertility, often caused by structural and functional sperm defects, remains genetically unexplained in a substantial proportion of cases. ATP1A4 encodes a testis-specific isoform of the Na+, K+-ATPase, a membrane enzyme crucial for maintaining cellular ionic homeostasis. Previous studies on Atp1a4 knockout mice have demonstrated severe defects in sperm motility and flagellar architecture; however, the contribution of ATP1A4 variants to human male reproduction remains to be elucidated. In this study, we identified compound biallelic variants in ATP1A4, a missense variant (c.2578 T>A, p.Tyr860Asn) and a frameshift variant (c.2582del, p.Gly861Aspfs*5), in a patient presenting with severe oligoasthenoteratozoospermia. Both variants markedly affected ATP1A4 protein expression. Morphological analyses revealed coiled and folded flagella, disrupted mitochondrial sheaths, and irregular head morphology in the patient's spermatozoa. Expression profiling revealed that ATP1A4 was highly enriched in post-meiotic spermatids and localized along the entire flagellum of mature sperm in both humans and mice, indicating a critical role in flagellar assembly and structural integrity. Notably, intracytoplasmic sperm injection (ICSI) in this patient resulted in low fertilization efficiency and failed implantation, suggesting a potential adverse impact of ATP1A4 deficiency on sperm functional competence beyond motility. These findings broaden the genetic spectrum of oligoasthenoteratozoospermia and highlight ATP1A4 as a potential gene associated with human male infertility.

Male↗
PubMed2026

Whole-Genome Deep Learning Predicts Chemotherapy Response in Colorectal Cancer.

Chemotherapy response in colorectal cancer (CRC) exhibits significant heterogeneity, with current clinical predictors failing to capture complex genomic determinants of resistance. We developed a hybrid deep learning framework integrating convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks to analyze whole-genome somatic mutations, evolutionary conservation, chromatin accessibility, and 3D genome architecture in 2,546 TCGA patients. An attention mechanism identified predictive genomic regions. The model achieved an AUC of 0.92 (95% CI: 0.89-0.94) in cross-validation and 0.88 (95% CI: 0.85-0.91) in independent validation, outperforming clinical models (&#x394;AUC = +0.18, p < 0.001). Key predictors included non-coding variants in TP53, KRAS, and PIK3CA regulatory regions. Triple-positive patients (mutations in all 3 regions) had significantly worse progression-free survival (HR = 4.7, p < 0.001). Our framework enables accurate chemotherapy response prediction and reveals novel non-coding resistance mechanisms, advancing precision oncology in CRC.

Humans↗
PubMed2026

Strategies for mosaic variant calling in brain disorders.

The human brain is a genomic mosaic, where postzygotic mutations arising from embryogenesis to senescence drive diverse neurodevelopmental and neurodegenerative diseases. Because of numerous sequencing artifacts at ultralow variant allele frequencies (VAFs), detecting these variants remains a significant analytical challenge. This review focuses on single-nucleotide variants and small indels, summarizing current strategies for aligning sampling methods, including bulk, laser capture microdissection, and single-cell genomics, with the expected clonal architecture of the brain. It emphasizes that mosaic detection sensitivity is fundamentally constrained by sequencing depth, since even the most advanced algorithms cannot identify variants not physically represented in the sequencing library. The review further recommends the selection of variant calling algorithms based on validated VAF detection performance, matching tools like MuTect2 and MosaicForecast to their optimal performance ranges. Furthermore, we discuss how multitissue sampling, as emphasized by the SMaHT project, addresses the matched-control dilemma and supports accurate variant classification via cross-tissue VAF gradients. Integrating these established pipelines with multiomics modalities, including transcriptomic and epigenetic data, could advance the field toward a functional understanding of how the somatic genome impacts human brain health and disease.

Humans↗
PubMed2026

The present and future of nonviral delivery-based genome editing for hereditary hearing loss.

PURPOSE OF REVIEW: This review summarizes nonviral genome-editing delivery platforms for hereditary hearing loss, focusing on lipid nanoparticles (LNPs) and engineered virus-like particles (eVLPs), and discusses their advantages over adeno-associated virus-based delivery, as well as the barriers to clinical translation. RECENT FINDINGS: Recent advances have established LNPs as a clinically advanced nonviral platform, although challenges related to inner ear biodistribution, cell type specificity, endosomal escape, and immunogenicity remain to be addressed. In parallel, eVLPs have undergone substantial technical evolution, progressing from early low efficiency systems to advanced base editor- and prime editor-eVLP architectures that enhance cargo loading and editing efficiency. Extracellular vesicle-based genome editing has also emerged as an additional platform, although issues related to reproducibility, loading efficiency, and scalability remain major hurdles. SUMMARY: Nonviral genome editing platforms expand the therapeutic toolkit for hereditary hearing loss by enabling transient delivery of genome editors with potential safety advantages. Future efforts should focus on characterizing biodistribution and immunogenicity, refining cell type-specific tropism, and establishing scalable manufacturing processes to enable successful clinical translation.

Humans↗
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↗