Biology subjects

Li, N.

Publications and source records attributed to Li, N..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

STN1 upregulation promotes PARPi resistance in BRCA2-deficient cancer cells via replication fork protection and suppression of ssDNA gap formation

PARPi are effective therapy for BRCA1/2 mutant cancers, yet recurrent PARPi resistance frequently develops. The underlying mechanism of PARPi resistance remains largely unresolved. Here, we identify STN1, a component of the CTC1/STN1/TEN1 (CST) complex, as a modulator of PARPi resistance in BRCA2-deficient cells. RNA-seq analysis of PARPi-resistant cancer cells from BRCA2-mutated backgrounds shows largely distinct transcriptomic profiles with limited overlap, suggesting multiple routes to resistance. Notably, STN1 is consistently upregulated in resistant cells. We observe that overexpression of STN1 enhances Olaparib resistance in multiple BRCA2-deficient cell lines and alleviates DNA damage under replication stress. Mechanistically, we find that STN1 overexpression increases RAD51 loading to stalled replication forks while restricting MRE11 recruitment in BRCA2-deficient cells, thereby protecting stalled forks from nascent-strand degradation. Furthermore, STN1 overexpression rescues the accumulation of ssDNA gaps, a major determinant of PARPi sensitivity in BRCA2-deficient cells. Taken together, these findings suggest that elevated STN1 levels can partially compensate for BRCA2 loss by stabilizing stalled replication forks and limiting ssDNA gap accumulation. Our study uncovers a STN1-dependent pathway of replication stress tolerance that promotes PARPi resistance independently of homologous recombination restoration, highlighting STN1 as a potential biomarker and mechanistic contributor to therapeutic resistance in BRCA2-mutated cancers.

cancer biology↗

bioRxiv2026

Genetic canalization of nutrient resorption: evidence from a widespread grass under effective salt stress

Nutrient resorption is a key plant strategy for nutrient conservation, yet whether it responds plastically to non-nutrient stressors such as salinity remains unresolved. Using a common garden experiment with 110 genotypes of the cosmopolitan grass Phragmites australis, we first established that the imposed salinity treatment induced strong multi-level stress responses: above-ground biomass declined by >60%, sodium accumulated 3- to 5-fold across all leaf stages, and 484 metabolites showed significant differential accumulation, including canonical markers of osmotic and oxidative stress. Against this backdrop of confirmed stress, we found that nutrient resorption efficiency (NuRE) remained largely unaffected by salinity. Instead, NuRE was strongly correlated with phylogeographic lineage, ecotype, and latitude of origin, demonstrating evolutionary canalization rather than short-term acclimation. Element-specific regulatory patterns were also evident: while phosphorus resorption followed concentration-dependent control regardless of stress, nitrogen control was disrupted under salinity, and potassium resorption showed no such dependence. Our findings reveal that intraspecific variation in nutrient resorption is predominantly shaped by historical adaptation and geographic context, not by plasticity to salinity. This genetic canalization of a key functional trait implies that predictions of nutrient cycling under global change must account for the phylogeographic composition of plant populations.

ecology↗

bioRxiv2026

Self-Organized Neural Integrators in Noisy Spiking Networks

AO_SCPLOWBSTRACTC_SCPLOWNeural integrators convert brief inputs into persistent firing and underlie functions such as working memory, evidence accumulation, and gaze holding. Classical integrator models typically rely on finely tuned recurrent connectivity. Here we identify a biologically plausible route by which randomly connected noisy spiking networks can approximate integration over a finite region of parameter space. Mean-field theory (MFT) reveals surprisingly simple dynamics in such networks, governed by the mean recurrent weight and mean feedforward weight, and shows that linear integration critically depends on noise. We further show that this regime can be reached through a local, reward-modulated two-trace plasticity rule. Comparing the model with new experimental results from a delay-switching tactile decision-making task, we find that it reproduces key features of adaptive ramp-to-threshold cortical dynamics during timing-related learning. The same framework further connects to oculomotor persistence and evidence accumulation, providing a mechanistic realization of single-boundary drift-diffusion dynamics.

neuroscience↗

bioRxiv2026

Allogeneic CRISPR-Engineered CAR-T Cells Drive Potent Antitumor Activity in Solid Tumors

Chimeric antigen receptor (CAR) T-cell therapy has shown limited efficacy in solid tumors, in part due to variability in autologous T cells derived from heavily pretreated patients with advanced disease. To address these constraints, we developed an off-the-shelf allogeneic CAR-T platform using CRISPR-Cas9-mediated genome editing in T cells from healthy donors to enable targeted CAR insertion at the TRAC locus with concurrent disruption of B2M. Using adeno-associated virus (AAV) delivery, we designed CAR-T cells targeting glypican-2 (GPC2) and glypican-3 (GPC3), emerging antigens expressed in pediatric and adult solid tumors. Genome-edited allogeneic CAR-T cells exhibited potent, antigen-specific cytotoxicity across multiple tumor models. GPC2-directed allogeneic CAR-T cells demonstrated enhanced or comparable activity relative to conventional lentiviral CAR-T cells in neuroblastoma models and mediated tumor regression with prolonged survival in preclinical models. Notably, repeated dosing augmented antitumor efficacy without evidence of toxicity, supporting multi-dose regimens for solid tumors. Similarly, GPC3-targeted allogeneic CAR-T cells based on a single-domain antibody showed robust activity against hepatocellular carcinoma cells in vitro and in vivo. These findings establish a scalable, genome-engineered allogeneic CAR-T strategy with strong therapeutic potential and support the clinical development of off-the-shelf cell therapies for pediatric and adult solid tumors.

immunology↗

bioRxiv2026

DCN1 inhibitor induces fetal hemoglobin through self-limited regulation of CUL3 neddylation

Few genetic loci are as well-characterized as the globin gene locus, and the substitution of healthy {gamma}-globin (HbF) for missing or mutated {beta}-globin (HbB) is an established therapeutic strategy for {beta}-hemoglobinopathies including sickle cell disease (SCD) and {beta}-thalassemia. Although substantial progress has been made in understanding HbF derepression and globin switching, many current therapeutic strategies involving small molecules increase HbF through broad epigenetic perturbations or cytotoxic stress, raising concerns about dose-limiting cytopenias and off-target effects. By coupling single-cell transcriptomics, genetic perturbations, and functional genomics, we identified an unknown role of neddylation in the regulation of fetal hemoglobin (HbF). Partial impairment of neddylation of cullin ubiquitin ligase 3 (CUL3) through defective in cullin neddylation 1 (DCN1) inhibition leads to highly selective chromatin changes, histone demethylation, and globin locus binding of known activators of HbF transcription. Further, DCN1 inhibition drives globin switching and HbF increases in vitro and in vivo with minimal off-target transcriptional effects and no evidence of cytotoxicity or stress erythropoiesis. To therapeutically target this axis, we report the discovery and characterization of CLY-124, a first-in-class, covalent DCN1 inhibitor with favorable pharmacology properties. In a humanized mouse model, CLY-124 showed a dose-dependent increase in HbF as monotherapy and in synergy with hydroxyurea (HU), a current standard of care. Collectively, these findings highlight the power of single-cell transcriptomics to elucidate undiscovered biologic insights with therapeutic potential, and the promise of DCN-1 inhibitors like CLY-124 to address {beta}-hemoglobinopathies. With an appropriate nonclinical safety profile, a first-in human study of safety, pharmacokinetics and HbF assessments in healthy volunteers and participants with SCD is ongoing for CLY-124. One-sentence SummaryDCN1 is a promising target for {beta}-hemoglobinopathies

molecular biology↗

bioRxiv2026

Hypoglycemia Aggravated Cognitive Degeneration by activating Endothelial ZBP1-mediated PANoptosis in Type 2 Diabetes

Recurrent hypoglycemia increases cognitive impairment in diabetes mellitus patients. Following cerebral neuron injury, endothelial cells provide morphological, metabolic and immune support to damaged neurons. We investigated the inflammatory mechanism involved in hippocampal neuron degeneration. Behavioral experiments, including the open field test (OFT) and the Morris water maze test, were performed to measure cognitive changes. Using a vascular ring experiment, we evaluated vasodilation of the carotid artery. ZBP1 expression was knocked down after transfection with small interfering RNA in a brain endothelial cell line (bEnd3). In this study, PANoptosis, a recently defined form of programmed cell death (PCD), was found to be increased by hypoglycemia in the hippocampus of type 2 diabetic mice in vivo and by low glucose in bEnd3 cells in vitro. ZBP1 knockdown decreased PANoptosis induced by low-glucose stimulation in high-glucose-cultivated bEnd3 cells. RNA transcriptomics sequencing revealed that AGE-RAGE signaling significantly changed after ZBP1 was knocked down in bEnd3 cells. Corresponding biochemical data confirmed that ZBP1 knockdown regulated the advanced glycation end products (AGEs)-Receptor for Advanced Glycation End Products (RAGE) axis in bEnd3 cells. We present the first evidence that hypoglycemia impaired cognition in mice with type 2 diabetes by activating brain endothelial ZBP1-mediated PANoptosis via the AGE-RAGE axis. ARTICLE HIGHLIGHTSO_LIPANoptosis, a newly defined form of programmed cell death, is induced in the hippocampus after recurrent hypoglycemia in male db/db mice. C_LIO_LIZBP1, a sensor of the PANoptosome, was activated in low glucose cultured brain endothelial cells. C_LIO_LIHypoglycemia impairs vasodilation and cognitive function in type 2 diabetic mice. C_LIO_LIOur study indicates that inhibiting ZBP1-PANoptosis and the AGE-RAGE axis may be a potential approach to prevent hypoglycemia-induced cognitive degeneration in individuals with type 2 diabetes. C_LI

animal behavior and cognition↗

bioRxiv2026

Coordinated yet asymmetric striatal neuromodulatory dynamics encode associative learning

The striatum integrates dopamine and acetylcholine to support learning and behavioral flexibility, yet how these neuromodulators coordinate during associative learning remains unclear. Using longitudinal dual-color fiber photometry in mice, we simultaneously tracked both signals in the anterior dorsolateral striatum throughout Pavlovian conditioning. We find that learning recruits distinct forms of neuromodulatory plasticity: dopamine maintains rapid, contingency-dependent cue responses, whereas acetylcholine undergoes broader reorganization across training. Despite these differences, trial-by-trial covariance between the two signals converges onto a compact low-dimensional structure that reliably captures learned behavioral state and distinguishes associative learning from sensory exposure alone. Granger causality analyses further reveal a directional asymmetry, present in both paired and unpaired mice, whereby dopamine reliably predicts subsequent acetylcholine fluctuations, with only weak reciprocal prediction. Together, our results identify a low-dimensional organizational principle for dopamine-acetylcholine interactions, and suggest that dopamine acts as a leading temporal signal that shapes cholinergic dynamics during striatal learning.

neuroscience↗

bioRxiv2026

Comprehensive long-read transcriptome analysis uncovers alternative RNA processing feature and isoform diversity in ovarian cancer progression

Post-transcriptional processing has a crucial yet largely unresolved dynamic change and role during the malignant progression of ovarian cancer, especially due to the limited read length of short-read RNA sequencing being insufficient to capture transcript diversity. Here, we performed Iso and RNA sequencing on paired normal, primary tumor, and metastatic samples, generating a comprehensive isoform atlas of over 41,000 full-length transcripts including many unannotated isoforms. Integrative analyses revealed extensive isoform-level remodeling across disease states that often occurred without concordant alterations at the gene level, emphasizing the importance of qualitative transcript regulation. Notably, we identified isoform-level alterations with distinct biological and clinical relevance, including differential expression of the short KRAS isoform, a tumor-specific isoform switch of TMEM201, and an alternative first-exon event in FNDC3B associated with poor survival. Together, these findings provide a high-resolution map of the ovarian cancer transcriptome and illustrate how long-read sequencing exposes multiple layers of post-transcriptional and clinical insight that remain hidden in conventional expression profiling.

bioinformatics↗

bioRxiv2026

EnsAgent: a tool-ensemble multiple Agent system for robust annotation in spatial transcriptomics

MotivationAutomated domain annotation in spatially resolved transcriptomics (SRT) remains challenging since it depends on gene expression, morphology, and clinical conventions, which vary across cohorts and platforms. While Large Language Model (LLM)-driven agents show promise, current approaches typically condition semantic reasoning on static, single-method partitions. This reliance makes annotation pipelines fragile to upstream partition errors and prone to hallucinations when molecular evidence is ambiguous. A robust framework integrating ensemble intelligence with iterative, evidence-based reasoning is required to ensure reproducibility and accuracy. ResultsWe introduce EnsAgent, a tool-ensemble multi-agent system designed for robust SRT annotation. Uniquely, EnsAgent decouples structural partitioning from semantic labeling via a Consultation-Review workflow. A Tool-Runner Agent orchestrates a diverse portfolio of clustering algorithms via the Model Context Protocol (MCP), generating a consensus partition optimized by a multimodal Scoring Agent. Subsequently, a Proposer-Critic feedback loop coordinates four specialized experts (Marker, Pathway, Spatiality, and Visual) to formulate annotations with explicit evidence trails and uncertainty estimates. Benchmarking on three SRT datasets demonstrates that EnsAgent effectively neutralizes batch effects and resolves subtle tumor microenvironment niches missed by single-paradigm baselines, delivering state-of-the-art accuracy and interpretability. Availability and ImplementationEnsAgent is available at github.com/keviccz/ensAgent. Contactdongqishi@sztu.edu.cn, kexiao@sztu.edu.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2026

Red yeast rice-derived MKA ameliorates cardiac hypertrophy in hypertensive rats by inhibiting ERK1/2/c-Fos pathway

BackgroundCardiac hypertrophy is a key pathological process in hypertensive heart failure, yet current antihypertensive therapies do not directly target it. Red yeast rice (RYR), rich in monacolin K {beta}-hydroxy acid (MKA), is known for lipid-lowering effects, but its potential to ameliorate cardiac hypertrophy is unreported. PurposeTo investigate the effects of RYR-derived MKA on cardiac hypertrophy in spontaneously hypertensive rats (SHR) and elucidate its molecular mechanisms. MethodsSpontaneously hypertensive rats (SHR) were treated with 0.6% red yeast rice for 8 weeks to assess its effects on blood pressure, cardiac function (echocardiography), cardiac hypertrophy and fibrosis (histopathology), and multi-organ toxicity (histopathology). A multigenerational study was conducted to evaluate protective effects in offspring. Network pharmacology and transcriptomic analysis were integrated to predict molecular targets, which were subsequently validated by molecular docking and experiments. ResultsEight-week RYR treatment significantly reduced blood pressure, inhibited cardiac hypertrophy and fibrosis, and improved cardiac function without gender differences. No pulmonary, hepatic, or renal toxicity was observed. Offspring from treated parents exhibited further reduced hypertrophy upon continued treatment. Mechanistically, MKA bound ERK1/2 with high affinity, inhibiting its phosphorylation and downstream c-Fos expression, thereby downregulating hypertrophy markers. ConclusionRed yeast rice improves hypertensive cardiac hypertrophy via MKA-mediated inhibition of the ERK1/2/c-Fos pathway. Its multi-organ safety and transgenerational effects offer a novel dual-therapy strategy for hypertension and cardiac hypertrophy. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=139 HEIGHT=200 SRC="FIGDIR/small/710945v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@8225acorg.highwire.dtl.DTLVardef@775f43org.highwire.dtl.DTLVardef@10f5201org.highwire.dtl.DTLVardef@d0cd88_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2026

Intracellular Delivery of Peptides and Proteins with an Engineered Membrane Translocation Domain

Antibodies and other protein therapeutics have revolutionized medicine, but their application is largely limited to extracellular targets. The lack of efficient intracellular delivery methods remains a major bottleneck. Here, we engineered a family of small ([~]90 amino acids), metabolically stable membrane translocation domains (MTDs) by modifying the loop sequences of a human fibronectin type III (FN3) domain. The most potent variant, MTD4, is highly cell-permeable and can be recombinantly fused to the N- or C-terminus of any peptide or protein, serving as a versatile "plug-and-play" vehicle. We demonstrate that MTD4 fusions efficiently deliver a wide variety of functional peptides and proteins into the cytosol and nucleus of eukaryotic cells, both in vitro and in vivo. Following systemic administration, MTD4 fusion proteins exhibit broad biodistribution and homogenous tissue penetration in mice. Importantly, MTD4 is effective at low nanomolar (nM) concentrations, making it a promising platform for addressing a vast range of intracellular and previously "undruggable" targets.

bioengineering↗

bioRxiv2026

A precise atlas of the human subcortex

Clinical interventions and neuroimaging in the subcortex require anatomical definitions that exceed the resolution and anatomical detail of currently available deformable brain atlases. Here, we introduce a high-resolution human brain atlas comprising 95 manually segmented grey and white matter structures as well as 82 white matter tracts compiled from a multitude of resources including ex-vivo MRI, histology, fibre dissections, and neuroanatomy textbooks. The atlas is defined at an isotropic resolution of 100 m and can be precisely deformed to individual subject brain anatomy. By providing precise definitions of both grey and white matter structures within and around the basal ganglia, thalamus, subthalamus, midbrain and cerebellum, the atlas provides a foundational resource for stereotactic surgery and subcortical brain imaging research, as well as for development of next-generation neuromodulation strategies.

neuroscience↗

bioRxiv2026

PhyloSOLID: Robust phylogeny reconstruction from single-cell data despite inherent error and sparsity

While lineage tracing based on somatic mutations in single-cell sequencing data offers a powerful approach to reconstructing cellular histories in vivo, its reliability is fundamentally limited by pervasive technical artifacts--specifically, high error rates and data sparsity. These issues introduce false phylogenetic signals that corrupt tree topology and lead to spurious evolutionary conclusions. To overcome these limitations, we present PhyloSOLID, a phylogenetic algorithm designed to be inherently robust to these data imperfections. PhyloSOLID employs a progressive scaffolding strategy that begins with graph-based construction of a low-resolution, high-confidence backbone tree from reliable and uniformly covered mutations. This scaffold is then refined through the iterative integration of remaining data, guided by a Bayesian statistical model that penalizes phylogenetic inconsistencies to effectively separate the true evolutionary signal from technical artifacts. Benchmarking on both simulated datasets and multiple ground-truth datasets demonstrates that PhyloSOLID achieves superior lineage reconstruction accuracy over existing methods, for both single-cell RNA-seq and DNA-seq data. Additionally, a user-friendly web interface enables customized quality assessment, artifact removal, and interpretation of lineage structures. PhyloSOLID provides a powerful solution for decoding cellular evolution in developmental and disease contexts.

bioinformatics↗

bioRxiv2026

Prophylactic Lipoxin A4 Attenuates Clostridioides difficile Infection by Augmenting Epithelial Barrier and Resolving Inflammation

Clostridioides difficile infection (CDI) is a leading healthcare-associated diarrhea with high recurrence rates, partially due to antibiotic-induced dysbiosis and dysregulated host inflammation. Specialized pro-resolving mediators (SPMs), such as Lipoxin A4 (LXA4), offer promise in controlling excessive inflammation and promoting tissue repair, yet their role in CDI remains unexplored. Here, we developed a compact, gas-tight gut-on-a-chip (GOC) system that reconciles the anaerobic requirements of C. difficile with the oxic needs of human intestinal epithelium, enabling physiologically relevant co-culture within a standard incubator. A CDI in vitro model was established based on this GOC system. Using the model, we demonstrated that prophylactic administration of LXA4 significantly preserved epithelial barrier integrity, attenuated pro-inflammatory cytokine secretion (IL-8 and IFN-{gamma}), and reduced bacterial colonization. Transcriptomic analysis revealed that LXA4 pretreatment upregulated genes involved in cell junction organization while downregulated immune activation pathways. These protective effects were validated in a murine CDI model, where LXA4 pretreatment reduced weight loss, pathological damage, and fecal bacterial burden. Furthermore, prophylactic administration of LXA4 synergized with vancomycin treatment further enhanced antibiotic efficacy while allowing a 50% dose reduction without compromising therapeutic outcomes. Our study establishes a robust approach for CDI research and highlights the prophylactic and adjuvant potential of inflammation-resolving strategies, offering a novel approach to mitigate CDI incidence and improve treatment outcomes.

bioengineering↗

bioRxiv2026

Scalable probe-based single-cell transcriptional profiling for virtual cell perturbation mapping and synthetic biology phenotyping

Large-scale single-cell transcriptional phenotyping of genetic perturbations (perturb-seq) links genes to phenotypes and should enable virtual cell predictive modeling and cellular engineering. However, current perturb-seq single-cell methods are costly, information sparse and require barcodes for many applications. We developed ProPer-seq, a perturb-seq method that uses multiplexed custom DNA probe panels to measure and phenotype synthetic biology perturbations at single-cell resolution without barcodes, including multidomain proteins and sgRNAs. ProPer-seq faithfully reproduces gold-standard perturb-seq phenotypes while achieving 4-fold cost reduction and 50% increased gene detection per cell. As a scalable fixed-cell profiling method, ProPer-seq enables atlas-scale profiling for virtual-cell initiatives and demonstrates data quality suitable for training and validating predictive models. Lastly, ProPer-seqs targeted detection of modular transgenes enables library-on-library perturbation profiling of combinatorial synthetic protein design spaces. We applied this to 3,550 sgRNA x dCas9 effector combinations as well as 260 CAR x ORF combinations dynamically profiled in primary T cells, revealing principles of transcriptional control and cell state modulation by multidomain synthetic transgenes.

synthetic biology↗

bioRxiv2026

Predicting driver distraction using a single channel ear EEG

Cognitive distraction poses a major risk to driving safety, yet remains difficult to detect in real time because it often lacks overt behavioral markers. Neurophysiological measures such as electroencephalography (EEG) provide objective indices of cognitive load, but conventional EEG systems are impractical for real-world deployment due to their intrusiveness and computational demands. The present study examined whether cognitive distraction during naturalistic driving can be decoded using a single-channel, non-invasive in-ear EEG, and how its temporal dynamics compare with those obtained from full-cap scalp EEG and behavioral measures. Twenty-seven participants performed a dual-task paradigm in a highly immersive driving simulator, combining continuous vehicle control with low- and high-load arithmetic tasks presented on an in-vehicle display. Single-channel in-ear EEG, 24-channel scalp EEG, eye movements, and head rotation were recorded concurrently. Time-resolved multivariate pattern analysis was applied to decode working-memory load with millisecond precision across modalities. Cognitive distraction was reliably decoded from in-ear EEG, with detection latency and temporal generalization profiles closely matching those of full-cap scalp EEG. Although peak decoding performance was higher for scalp EEG, the timing and temporal stability of distraction-related neural signatures were largely overlapping between the two neural modalities. Eye velocity provided the earliest and most sensitive behavioral marker of distraction, while head rotation contributed complementary but weaker information. Scalp EEG topographies indicated that neural signals underlying decoding were closely linked to oculomotor and visuomotor processes engaged during task performance. These findings demonstrate that single-channel in-ear EEG provides a temporally precise and low-burden neural marker of cognitive distraction during driving. By prioritizing early detection and minimal hardware over maximal classification accuracy, the results identify a practical operating point for wearable EEG-based driver monitoring systems and support the feasibility of fast, off-the-shelf decoding approaches for real-world applications.

neuroscience↗

bioRxiv2025

Sampling Function-Related Metastable States of Proteins With DASH

Rational discovery of function-specific protein modulators as well as activity-enhanced engineering proteins underscore the need to identify function-related metastable states (FMSs) of proteins. However, current experimental and computational methods struggle to generate these states directly from their native state (NS), likely because the NS [->] FMS transition is non-spontaneous. To address this challenge, we introduce Deep learning guided Adaptive sampling with seed Selection and Hopping (DASH), integrating both deep learning and physical functions to guide molecular dynamics (MD) simulation towards FMS. DASH successfully sampled NS [->] FMS transitions in 18 cases across two tasks: protein activation and cryptic allosteric site opening. DASH combined with secondary-structure collective variables is further able to sample folding of disordered regions. Compared to existing methods, DASH demonstrates superior performance while requiring comparable simulation time. Crucially, we applied DASH to sample new conformations of proteins, by which revealing new folding states, previously unknown allosteric sites, and potential activators. These predictions have been further verified in wet-lab experiments and crystal structures determinations. Collectively, our framework provides a robust strategy for function-specific pharmacy research and could accelerate future drug discovery efforts.

bioinformatics↗

bioRxiv2025

Benchmarking of duplex sequencing approaches to reveal somatic mutation landscapes

Detecting somatic mutations in normal tissues is challenging due to sequencing errors and the low allele fractions of post-zygotic variants. Duplex sequencing greatly reduces errors and can detect mutations at any allele fraction, but systematic, cross-platform comparisons are lacking. We present a comprehensive benchmarking of six duplex sequencing technologies used by the SMaHT Network: CODEC, CompDuplex-seq, HiDEF-seq, NanoSeq, ppmSeq, and VISTA-seq. We evaluated their performance using cord blood DNA, a tumor-normal cell line mixture, and homogenates from six human tissues. Each method shows distinct profiles in genomic footprint, sensitivity, and cost. Despite differences in library construction and sequencing platforms, estimates of mutation rates and mutational signatures are highly concordant. Integration with ultra-deep whole-genome sequencing shows that duplex approaches sensitively capture mutations and signatures beyond embryonic or clonally expanded variants. These results provide a foundation for selecting duplex methods and interpreting their data, enabling scalable single-molecule analyses of somatic mutation landscapes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=101 SRC="FIGDIR/small/692823v1_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@123b221org.highwire.dtl.DTLVardef@83ba0aorg.highwire.dtl.DTLVardef@2b0ab0org.highwire.dtl.DTLVardef@1cae35e_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗