Biology subjects

Wang, S.

Publications and source records attributed to Wang, S..

At least 109 records · Page 6Linked to original sources

bioRxiv2026

Hidden genetic diversity in 320 nearly-complete East Asian genome assemblies

East Asian populations, representing over 20% of the global population, remain critically underrepresented in human genomic studies, limiting our understanding of population-stratified genetic variation and its implications for health and disease. Here we present the first phase of the Asian Pan-Genome project (APG), comprising 320 nearly complete, fully phased haploid genome assemblies from 160 East Asian individuals. These assemblies achieve unprecedented quality, with an average contig N50 of 144.3 megabase pairs and an average quality value of 64.5. Leveraging these superior assemblies, we reveal previously uncharacterized diversity in human repeatome, including population-stratified patterns in centromere satellites and rDNA arrays. Compared to existing global human genome assemblies, the newly generated genomes supplement 152 million base pairs of novel sequences, 355 gene gains, 18,300 structural variation loci and 26 large euchromatic inversions missing from current human pangenomes. We perform population stratification analyses of structural variations, and further resolve the structural haplotypes of complex genomic regions such as Major Histocompatibility Complex and Survival Motor Neuron loci across global pangenomes, exemplifying tandem-duplicate and inversion-rich complex locus architectures in the human genome, respectively. This resource provides a critical foundation for human genetic studies, especially for East Asian populations, promoting more accurate variant discovery, reducing bias, and ultimately advancing the equity and efficacy of genomic medicine.

genomics↗

bioRxiv2026

Patterns and correlates of invasive alien plant richness in China's abandoned croplands

Cropland abandonment is a widespread socio-ecological transition that can generate heterogeneous ecological outcomes, including opportunities for vegetation recovery as well as the accumulation of invasive alien plants (IAPs). Understanding broad-scale correlates of IAP richness in abandoned croplands is challenging because published studies differ in sampling design, spatial extent, and reporting detail. To provide an exploratory national-scale synthesis, we compiled literature-derived occurrence records of 57 IAP species reported from abandoned croplands across China and examined study-level recorded richness using generalized linear mixed models (GLMMs) with province as a random effect. Fourteen socio-economic and environmental predictors were screened for multicollinearity and standardized, and the number of Higher Education Institutions (HEIs) was included as a proxy for potential sampling-effort variation. Asteraceae accounted for 43.9% of recorded species, and more than 70% of taxa were classified as high-risk invaders (Levels 1-2). Recorded richness exhibited a pronounced southeast-northwest gradient, with higher values in economically developed coastal provinces. In the exploratory GLMM, regional GDP (IRR = 1.67, p < 0.05) and mean annual temperature (IRR = 1.49, p < 0.05) were positively associated with recorded richness, whereas other environmental, accessibility, soil, and sampling-effort variables showed no detectable associations. Model diagnostics indicated no evidence of overdispersion, zero inflation, or residual spatial autocorrelation. Given the heterogeneous nature of literature-derived data and the small number of study units, these results should be interpreted as broad-scale correlational patterns rather than causal drivers. The findings highlight regional socio-economic context and climatic conditions as key correlates of recorded IAP richness in abandoned croplands and provide an initial baseline for understanding invasion patterns in post-agricultural landscapes undergoing rapid land-use transitions..

ecology↗

bioRxiv2026

A germline shortcut in protein language model retrieval of adaptive immune receptors

Protein language models (PLMs) are increasingly used to represent adaptive immune receptors; however, their advantages over classical alignment-based methods remain unclear. We benchmarked the ESM2 family, ESM-C, antibody-, and TCR-specific PLMs against sequence-alignment methods across four B-cell and T-cell receptor databases using CDR3, clonotype, paratope, and full variable domain representations. At the CDR3 level, alignments consistently out-performed all PLMs, except SCEPTR, a contrastively pre-trained TCR model that additionally encodes the germline V gene. BLOSUM62 and Levenshtein distance metrics exceeded all ESM2 variants by 7-12 percentage points in top-1 retrieval accuracy, and domain-specific PLMs did not close this gap. At the full variable domain level, the alignments and PLMs converged. Alignment performance peaked at the paratope level, whereas PLMs benefited primarily from the addition of conserved framework information in the full-length sequences. The one exception was heavily-mutated HIV-1 antibodies, where PLMs outperformed alignments. These results, together with germline reversion analyses, indicate that full-length PLM performance takes advantage of a germline shortcut rather than improved extraction of antigen-specific information from CDRs. We further showed that conventional random train-test splits inflate retrieval accuracy by 15-28 percentage points owing to clonal leakage. Together, these findings define the strengths and limitations of frozen zero-shot PLM embeddings for immune receptor retrieval and establish clone-aware benchmarking as a practical standard of comparison. Key PointsO_LIClassical sequence alignment consistently outperformed frozen protein language models (PLMs) for CDR3 immune-receptor retrieval across the four datasets. C_LIO_LIProtein language models reached parity only in the full variable domain by exploiting the conserved germline-derived sequence, thus revealing a germline shortcut. C_LIO_LIFrozen PLMs exceeded alignment only for highly mutated HIV-1 antibodies. C_LIO_LIOne PLM matching alignment at CDR3, SCEPTR, encoded germline V gene information. C_LIO_LIRandom train-test splitting inflated accuracy by 15-28 percentage points; clone-aware splitting should be the standard. C_LI Bibliographical NoteDaron M. Standley is Professor of Genome Informatics at the Research Institute for Microbial Diseases, Osaka University. His research developed computational methods for immune repertoire analysis and antibody discovery.

bioinformatics↗

bioRxiv2026

A multimodal interrogation of Broca's area in the pediatric and adult human brain

Language is a defining trait of our species, and disruptions in language acquisition can have profound consequences to the individuals affected. Uncovering the neurodevelopmental basis of this complex trait requires detailed molecular and cellular insights into the neocortical areas that support linguistic abilities. Here we performed joint gene expression and chromatin accessibility profiling at single-nucleus resolution (10x Genomics Single cell Multiome) and spatial transcriptomic profiling (Xenium high-plex in situ spatial transcriptomics) of Brocas area alongside adjacent motor cortical areas. We profiled individuals from different ancestries (European and African) and developmental stages (infancy, childhood, adolescence, and adulthood). We provide a high-resolution dissection of the cellular and molecular architecture of Brocas and motor cortical areas across early life stages and anchor the trajectories to the cellular states found in the adult human brain. We identify distinct area- and stage-specific cellular signatures, including a prominent role of glia populations and interneuron subtypes contributing to cytoarchitectonic specializations. Using longitudinal single cell spatial transcriptomic profiling, we orthogonally validate our consensus cell taxonomy and spatially resolve layer enrichment of neuronal and astrocyte subtypes that distinguish Brocas area and motor cortex. We also uncover cell type-specific molecular signatures that distinguish cell developmental trajectories in these cortical areas, including an early molecular code established by differential expression of cadherin genes that might contribute to area-specific intercellular communication. We also identify cell type-specific vulnerabilities to language- related neurodevelopmental and neuropsychiatric disorders, with selective susceptibility of particular somatostatin-positive interneuron subtypes to ASD/ADHD. Finally, evolutionary analysis of differentially accessible regions between Brocas area and motor cortex suggests that genetic mutations that might have contributed to the emergence of linguistic abilities accumulated over the course of million years following the divergence of human and chimpanzee lineages. Together, our study provides a comprehensive molecular, cellular and spatial definition of Brocas area and motor cortex, laying the groundwork for investigations into unique aspects of human cognition and related neurodevelopmental and neuropsychiatric disorders.

neuroscience↗

bioRxiv2026

Astrocyte-driven small vessel disease is an early, amyloid-independent feature of PSEN1 E280A familial Alzheimer's disease

Cerebral Small vessel disease (cSVD) is a prevalent feature of Alzheimers disease (AD) pathology. Whether this pathology is a late consequence of amyloid and tau accumulation or an early, direct effect of PSEN1 dysfunction has remained unresolved. We found that it is more severe in familial AD (FAD) caused by E280A mutation in presenilin 1 (PSEN1). These cases present with a distinctive proteomic signature, associated with pathological features, more dysregulated in the occipital cortex (OC) compared to the frontal cortex (FC), and characterized by multiple dysregulated proteins involved in extracellular matrix (ECM) and RNA-associated processes. This proteomic fingerprint was associated with abnormal collagen build up, ECM disorganization, and signatures of aberrant angiogenesis. Six months old transgenic knock-in mice homozygous for Psen1 E280A mutation (PSEN1Ki) also showed a similar phenotype with microvascular tortuosity and proteomic changes. Critically, these mice develop neither A{beta} plaques nor tau tangles, indicating that the shared microvascular and RNA-associated changes are direct consequences of PSEN1 dysfunction rather than downstream effects of amyloid pathology. Remarkably, dysregulated RNA-associated protein networks overlapped between FAD and PSEN1Ki mice. Cerebral microvessels microstructure in PSEN1Ki mice at two months and six months showed abnormal astrocytic end-feet with lamellar deposits implicating blood-brain barrier damage. Finally, single nuclei transcriptomic analysis of AD patients and controls showed similar abnormal astrocytes in both sporadic and familial variants, but FAD astrocytes expressed dysregulated genes identified in the proteomic analyses, such as GLUL, APOE, and CLU. Our findings suggest that cSVD is an early pathological event in PSEN1 FAD and that is driven by abnormal RNA-associated processes and astrocytic dysfunction.

neuroscience↗

bioRxiv2026

Do lovebirds ever forget? Long-term memory retention and adaptive forgetting in rosy-faced lovebirds

Long-term memory has been extensively documented in many animals across a range of ecological contexts. Far less is understood, however, about how long memories persist after active modification or how conflicting memories are adaptively regulated to enable flexible behaviour. Parrots are widely recognized for their high intelligence and cognitive capability, yet the study of memory has focused on only a handful of large parrot species. Here, using a binary choice symbolic system, we conducted three experiments on 28 rosy-faced lovebirds (Agapornis roseicollis) to investigate (1) memory retention of initial associative learning at intervals of two weeks, half a year, and one year; (2) reversal learning, where the rewarded and unrewarded symbols were swapped; and (3) memory retention, following reversal learning at two-week and half-year intervals. We revealed that (a) initial associative learning memory was strikingly persistent, remaining detectable after nearly 600 days; (b) reversal learning performance was comparable to that of large parrot species; and (c) while the post-reversal forgetting curve mirrored the pattern of initial learning, it exhibited a shorter retention duration and a lower retention plateau. These findings suggest that forgetting may serve as an adaptive mechanism that regulates the retrievability of conflicting information, rather than a simple erasure of memory traces. When the environment changes, the retrievability of previously functional but now maladaptive memories is suppressed, but their long-term storage is preserved for potential future use under analogous circumstances. Such dynamic regulations prevent the repetitive overwriting of information in a fluctuating environment, thereby fostering greater behavioural flexibility across dynamic scenarios.

animal behavior and cognition↗

bioRxiv2026

Rational and computation-assisted engineering of a compact and efficient StaCas9 genome editor

Type II-A CRISPR-Cas9 nucleases are widely used for genome editing, yet their functional diversity and therapeutic potential remain incompletely explored. In this study, we systematically analyzed natural variation in PAM recognition among SaCas9 orthologs and identified StaCas9 as a compact and efficient nuclease recognizing an NNG PAM. Structural and sequence analyses revealed that S983 within the PAM-interacting domain contributes to the PAM preference of StaCas9. StaCas9 enabled efficient genome editing across multiple endogenous loci in human cells and achieved high-efficiency disruption of the therapeutically relevant PCSK9 gene, supporting its potential for gene therapy. Furthermore, guided by structural insights, we significantly enhanced the editing activity of StaCas9. Together, these results expand our understanding of PAM recognition in type II-A Cas9 nucleases and establish StaCas9 as a high-performance genome-editing tool for therapeutic applications.

genomics↗

bioRxiv2026

A structured-illumination miniscope for optically sectioned imaging and real-time neural decoding

Single-photon miniscopes enable large-scale calcium imaging in freely behaving animals but are limited by out-of-focus background fluorescence that degrades image contrast and single-cell signal fidelity. Multiphoton approaches address this limitation but remain costly and complex. Here we introduce a lightweight (<3 g), low-cost structured illumination miniscope that achieves optical sectioning in freely behaving mice. Using HiLo imaging implemented with a simple Ronchi grating and time-multiplexed excitation, the system strongly suppresses background fluorescence while preserving the speed, field of view, and accessibility of widefield miniscopes, and supports optical-sectioned multi-plane imaging to increase neuronal yield. Using hippocampal recordings, we show enhanced region-of-interest (ROI)-based signal quality and spatial information readout, allowing simple ROI-averaged signals to approach the performance of offline algorithm-extracted signals. We further demonstrate a proof-of-principle closed-loop brain-machine interface enabled by rapid online signal extraction and real-time neural decoding. Together, these results establish structured illumination as a practical and accessible strategy for achieving high-contrast calcium imaging with miniaturized microscopes.

neuroscience↗

bioRxiv2026

scWeave: A deep learning model that bidirectionally translates between gene expression and chromatin structure at single cell resolution

Chromatin structure and gene expression are intimately linked, yet characterizing how the two covary has proven challenging, primarily because the two modalities are rarely measured in the same cells. Recently, single-cell co-assay protocols have enabled simultaneous profiling of both modalities within the same cells, but these experiments remain costly and technically challenging. To better characterize the relationship between 3D chromatin architecture and gene expression and to enable cross-modality inference from single-modality measurements, we developed a model called scWeave that bidirectionally translates between gene expression (scRNA-seq) and 3D chromatin architecture (scHi-C) at single-cell resolution. The scWeave model employs dual autoencoders to extract separate cell-level latent representations and learns to translate between these representations using dedicated translation modules. We evaluate scWeave on six publicly available co-assay datasets spanning mouse embryonic development, mouse cortex, mouse olfactory epithelium, and human bone marrow. On held-out mouse cells, scWeave outperforms a nearest-neighbor baseline and existing methods adapted to single-cell resolution, achieving a 57% improvement in median Spearman correlation when predicting gene expression from chromatin structure and an 18.8% improvement in median HiCRep similarity in the reverse direction relative to the next-best baseline. We further show that scWeave learns cross-modally aligned latent representations at single-cell resolution, enabling cells profiled in one modality to be matched to their counterparts in the other. Finally, scWeave generalizes to entirely held-out developmental timepoints in mouse olfactory epithelium and performs well on held-out human bone marrow cells despite limited human training data. By predicting the unmeasured chromatin architecture or transcriptional state from a single measured modality, scWeave offers a route to extend the benefits of costly co-assays to the many cell types, developmental stages, and species that are currently profiled with only one modality.

genomics↗

bioRxiv2026

IL-27 Signaling Protects Against Influenza-Associated Pulmonary Aspergillosis Through Inhibition of Type 2 Immunity and Enhanced Antifungal Immunity

Influenza-associated pulmonary aspergillosis (IAPA) is a severe complication of influenza infection associated with substantial mortality. Influenza disrupts pulmonary host defenses and alters innate immune responses, predisposing patients to invasive fungal infection. Interleukin-27 (IL-27) is an immunoregulatory cytokine with context-dependent antiviral and antifungal effects; however, its role during IAPA remains undefined. A mouse model of IAPA was established by infecting wild-type and IL-27 receptor -deficient (Il27ra-/-) mice with influenza A, followed by Aspergillus fumigatus challenge. IL-27 and IL-27R expression were increased during IAPA. Single-cell RNA sequencing identified monocytes as the primary source of IL-27 and T cells as major IL-27r-expressing cells. Il27ra-/- mice exhibited significantly increased pulmonary fungal and influenza viral burden, enhanced type 2 immune responses characterized by elevated IL-4, IL-5, IL-9, IL-13, eosinophils, Th2 cells, pathogenic Th2 cells, and ILC2s. Despite increased eosinophil abundance, eosinophil-mediated conidial killing was impaired in Il27ra-/- mice. IL-27R deficiency also reduced macrophage abundance and impaired macrophage conidial uptake. Conversely, timed administration of rIL-27 enhanced fungal clearance, improved survival, and increased macrophage conidial uptake and augmented eosinophil killing capacity during IAPA. IL-27 signaling is a protective immunoregulatory cytokine during IAPA that limits pathological type 2 inflammation and enhances antifungal effector function of both eosinophils and macrophages. These findings identify IL-27 as a potential therapeutic in IAPA.

immunology↗

bioRxiv2026

Broad remodeling of the pulmonary immune landscape occurs during IAPA with specific functional deficits of neutrophil subsets

BackgroundInfluenza-associated pulmonary aspergillosis (IAPA) is a severe complication of influenza infection associated with prolonged intensive care unit stay and increased mortality. Although impaired antifungal immunity has been implicated in IAPA pathogenesis, the cell type-specific immune mechanisms driving susceptibility remain incompletely understood. We aimed to characterize the pulmonary immune landscape during IAPA using single-cell transcriptomics and functional neutrophil assays. MethodsMale C57BL/6 mice were assigned to naive control, influenza A/PR/8/34 (H1N1) infection, A. fumigatus (ATCC 42202) infection, or IAPA groups. Lung CD45+ immune cells underwent single-cell RNA sequencing with downstream clustering and CellChat ligand-receptor interaction analysis. Differential gene expression analyses were performed across myeloid, lymphoid, and neutrophil populations. Functional neutrophil responses were evaluated using flow cytometry, myeloperoxidase activity assays, and FLARE (fluorescent Aspergillus reporter) conidia to assess fungal conidia uptake and killing. Cross-species validation was performed using gene set enrichment analysis compared with published human IAPA transcriptomic datasets. ResultsIAPA broadly remodeled the pulmonary immune landscape across myeloid, lymphoid, and neutrophil compartments. Myeloid cells showed coordinated suppression of fungal pattern recognition receptors, lysosomal biogenesis programs, and inflammatory signaling. Lymphoid populations exhibited transcriptional signatures of T cell exhaustion and Th17 suppression. Within the neutrophil compartment, we identified two transcriptionally and functionally distinct populations, conventional and inflammatory neutrophils, with divergent antifungal effector capacities. Inflammatory neutrophils showed selective killing defects, while both subsets exhibited impaired phagocytic uptake during IAPA. Murine transcriptomic findings demonstrated strong concordance with immune dysfunction signatures identified in human IAPA. ConclusionIAPA susceptibility arises from coordinated transcriptional dysfunction spanning innate and adaptive immune compartments. Distinct neutrophil subset dysfunction, impaired fungal recognition pathways, and T-cell exhaustion signatures collectively contribute to defective fungal clearance, providing mechanistic insight into IAPA susceptibility and potential therapeutic targets.

immunology↗

bioRxiv2026

A multi-agent workflow converts CAR-T patient evidence into experimentally testable hypotheses

Clinical studies of chimeric antigen receptor (CAR)-T therapy generate diverse molecular and clinical evidence that remains fragmented across publications, public repositories and patient-derived datasets, limiting systematic therapeutic discovery. Here we present BioPathfinder, an evidence-guided multi-agent workflow for closed-loop biomedical discovery. BioPathfinder constructs a provenance-aware knowledge resource linking publications with patient single-cell RNA sequencing (scRNA-seq) datasets and clinical metadata, and uses role-specialized large language model agents to generate, review and prioritize diverse, falsifiable and dataset-aware mechanistic hypotheses for computational and experimental validation. Applied to a curated corpus of CAR-T-treated patient studies and matched scRNA-seq datasets, BioPathfinder identified candidate mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. The workflow prioritized the hypothesis that genes associated with an NK-like transition programme could be targeted to reduce CAR-T exhaustion and improve persistence. Analysis of patient scRNA-seq datasets showed enrichment of this programme in exhausted post-infusion CAR-T cells. Virtual perturbation prioritized transition-associated receptor genes, including KLRC1, KLRD1 and KLRG1, and expert review selected KLRC1, encoding NKG2A, for experimental validation. In vitro and in vivo chronic-stimulation models showed that NKG2A marked activated, exhaustion-associated CD8 CAR-T cells, whereas NKG2A blockade enhanced antitumour activity and persistence-associated functional readouts in vivo. BioPathfinder establishes a generalizable framework that transforms fragmented clinical single-cell evidence into experimentally validated therapeutic hypotheses, providing a scalable strategy for AI-guided biomedical discovery. HIGHLIGHTSO_LIBioPathfinder integrates fragmented CAR-T clinical studies, patient scRNA-seq datasets and metadata into a provenance-aware evidence resource for AI-guided hypothesis discovery. C_LIO_LIA multi-agent workflow generates, critiques and prioritizes diverse, falsifiable, dataset-aware mechanisms underlying CAR-T persistence, dysfunction and therapeutic resistance. C_LIO_LIBioPathfinder prioritizes KLRC1/NKG2A as a therapeutic target, and experimental validation demonstrates that NKG2A blockade enhances CAR-T persistence and antitumour function. C_LI

bioengineering↗

bioRxiv2026

LARP4 is a B cell-specific metabolic checkpoint for plasma cell differentiation and a therapeutic target in systemic lupus erythematosus

RNA-binding protein LARP4 plays an important role in T cell activation and differentiation, but its role in B cell biology and the pathogenesis of systemic lupus erythematosus (SLE) remains unclear. This study found that LARP4 was specifically highly expressed in B cells of SLE patients and was positively correlated with disease activity. By constructing T cell-specific and B cell-specific conditional knockout mice, we found that deletion of LARP4 in B cells, but not in T cells, significantly alleviated pristane-induced and Bm12-induced lupus nephritis. Further analysis showed that LARP4 deletion selectively inhibited B cell differentiation into plasma cells, but did not affect germinal center B cell formation. Integrated transcriptomic and metabolomics analyses revealed that this effect is due to reduced phosphatidic acid synthesis and decreased mTORC1 activity caused by mitochondrial oxidative phosphorylation dysfunction. Furthermore, we used LIPEP, a LARP4 inhibitory peptide that effectively mimicked the therapeutic effects of LARP4 gene knockout in the MRL/lpr spontaneous lupus model and outperformed cyclophosphamide in reducing glomerular immune complex deposition and improving extrarenal dermatitis. These results indicates that LARP4 is a key metabolic checkpoint regulating B cell differentiation into Plasma cells and suggest that it may be a potential therapeutic target for SLE.

immunology↗

bioRxiv2026

Temporal Variation in Mosquito Vector Population Dynamics in Urban Areas

Locally acquired arboviral infections are an increasing public health concern in the United States. Aedes aegypti and Culex quinquefasciatus, vectors of dengue virus and West Nile virus, respectively, are established in regions where local transmission has been reported. Seasonal variation in mosquito abundance affects vector density, human-vector contact, and arbovirus transmission risk. The aim of this study is to investigate seasonal variations in Ae. aegypti and Cx. quinquefasciatus population dynamics in Miami-Dade County, Florida; Maricopa County, Arizona; and Clark County, Nevada. Monthly relative abundance, average mosquitoes collected per trap-night, normalized abundance ratios, and seasonal-trend decomposition were used to evaluate species- and location-specific seasonal patterns. Mosquito population dynamics differed by species and location. In Miami-Dade County, the two species showed seasonal turnover, with Cx. quinquefasciatus peaking during winter and spring and Ae. aegypti peaking during summer. In Maricopa and Clark counties, both species peaked primarily between August and September. Species dominance also differed by site, with Ae. aegypti more abundant than Cx. quinquefasciatus in Maricopa County and Cx. quinquefasciatus more abundant than Ae. aegypti in Clark and Miami-Dade counties. Seasonal decomposition showed that Ae. aegypti peaked earlier in Miami-Dade County than in Maricopa and Clark counties, whereas Cx. quinquefasciatus showed a spring peak in Miami-Dade County and bimodal seasonal patterns in Maricopa and Clark counties. These results suggest that mosquito population dynamics are species- and location-specific and support the use of local surveillance data to guide the timing of mosquito control and arbovirus preparedness.

ecology↗

bioRxiv2026

Lineage recording reveals hijacked hepatic progenitor states as a common origin of HCC and ICC

HighlightsCERAMIC enables continuous and high-capacity lineage tracing of liver tumor initiation Fatty liver-associated hepatocytes acquire regenerative and premalignant cell states before malignant transformation Lineage reconstruction identifies Hep_Bi-zonal cells as the cellular origin of liver tumor initiation Transcriptional and regulatory programs distinguish tumor-fated hepatocytes from failed-to-transform lineages Peroxisomal metabolism is required for progenitor-state formation and liver tumor initiation Spatial remodeling identifies a macrophage niche associated with tumor-fated hepatocytes Dual ontogenies and functional specialization of lipid-associated macrophages shape the tumor-fated hepatocyte niche Fatty liver disease predisposes to primary liver cancer, yet the lineage routes and niche mechanisms that select rare tumor-fated hepatocytes remain unclear. Here we developed CERAMIC, a high-capacity CRISPR-Cas9 lineage recorder that co-recovers editing scars and transcriptomes from single cells, and applied it to an AKT/NRAS-driven model of MASLD-associated liver tumor initiation. Longitudinal lineage, single-cell and spatial analyses revealed a hierarchical trajectory in which bipotential bi-zonal hepatocytes (Hep_Bi-zonal), rather than pericentral-like hepatocytes (Hep_CVlike), generated regenerative and neoplastic hepatocyte progenitor states that progressed toward both hepatocellular carcinoma and intrahepatic cholangiocarcinoma lineages. Tumor-fated cells preferentially expanded along a remodeled midlobular-periportal axis and depended on ACOX1-mediated peroxisomal beta-oxidation to withstand lipotoxic and oxidative stress. Spatial and lineage analyses further identified a sequential lipid-associated macrophage niche, in which monocyte-derived LAMs engaged tumor-fated hepatocytes through an LGALS9-P4HB axis, and P4HB inhibition suppressed tumor expansion. These findings define liver tumor initiation as a lineage-restricted process licensed by peroxisomal metabolic adaptation and macrophage-derived niche signals.

cancer biology↗

bioRxiv2026

MKMC enables reference-free transcriptomic analysis using k-mer representations

Traditional RNA-seq analysis depends heavily on genome alignment and gene annotation, limiting its utility in non-model organisms and introducing biases that can obscure regulatory complexity. We present MKMC (Multi-sample Kmer Counter), a scalable, reference-free toolkit for RNA-seq analysis that leverages k-mer-based statistics to detect biological variation without requiring alignment. MKMC integrates fast k-mer counting, abundance matrix generation, normalization, dimensionality reduction, and differential analysis into a unified workflow. Across diverse datasets, MKMC recapitulates key biological signals--including sex differences in killifish liver--and matches alignment-based pipelines in differential expression analysis and transcriptomic age prediction. Notably, MKMC detects isoform-specific events missed by traditional methods, one of which we validated using in situ hybridization. These results reveal previously hidden isoform-level regulatory events that contribute to sex-and age-associated transcriptional programs. MKMC offers a robust, extensible alternative to alignment-based approaches, enabling transcriptomic discovery across both model and non-model systems. While we focus here on RNA-seq as a primary application, MKMC is broadly applicable to any k-mer-based analysis of next-generation sequencing data.

bioinformatics↗

bioRxiv2026

MYC2 mediated regulation of xylan substitution patterns

O-Acetylation is the most abundant xylan decoration in eudicot plants and plays a critical role in determining xylan conformation and its interactions with cellulose and lignin, thereby contributing to secondary cell wall (SCW) integrity. In Arabidopsis, loss of the xylan O-acetyltransferase TBL29/ESK1 causes collapsed xylem and growth defects that can be suppressed by mutations in strigolactone (SL) biosynthesis genes such as MAX3. However, the molecular basis of this suppression remains unknown. Hypoacetylated xylan in tbl29 has a higher frequency of methyl glucuronic acid (MeGlcA) substituents, while the ratio of GlcA/MeGlcA is recovered in tbl29 max3. Furthermore, gene expression analyses reveal that the three xylan glucuronoxylan methyltransferases (GXM1/2/3) involved in xylan MeGlcA modification are upregulated in tbl29 SCWs but downregulated in tbl29 max3. Genetic analysis shows that the transcription factor MYC2 is required for max3-mediated suppression: the loss of MYC2 in tbl29 max3 prevents growth recovery and reverts GXM genes expression and xylan MeGlcA substitution levels. We propose a model where SL deficiency enhances MYC2 transcription, which in turn represses GXMs, thereby fine-tuning xylan methylation and re-establishing the MeGlcA/GlcA substitution balance under conditions of reduced O-acetylation. Our findings identify a MYC2-dependent regulatory module linking SL signalling to xylan methylation and reveal a genetically encoded compensatory mechanism that mitigates the consequences of defective xylan O-acetylation. More broadly, this work demonstrates that plants can preserve SCW function through adaptive remodelling of polysaccharide substitution patterns, highlighting an unexpected plasticity in SCW biosynthesis. Significance StatementSecondary cell wall integrity depends on the coordinated modification of xylan. We show that defects caused by reduced xylan O-acetylation can be alleviated through a strigolactone- and MYC2-dependent pathway that alters xylan methylglucuronidation. Rather than restoring the original wall composition, this mechanism appears to compensate for the loss of O-acetyl groups by remodelling polysaccharide substitution patterns to maintain cell wall function, revealing a new layer of plasticity in secondary wall biosynthesis.

developmental biology↗

bioRxiv2026

Targeting folate-dependent purine synthesis sensitizes melanoma cells to immune attack through suppressing glycolysis

Cytotoxic T lymphocytes (CTLs) play a central role in antitumor immunity; however, metabolic reprogramming within the tumor microenvironment often compromises their effector function, making metabolic targeting crucial for the improvement of T cell function. Folate-dependent purine synthesis, a core pathway sustaining the nucleotide pool, is highly activated in tumors, yet its role in regulating tumor immune sensitivity remains unclear. Here, by establishing a co-culture system of melanoma cells and human T Cell Receptor (TCR)-engineered T cells, we systematically evaluated the effects of folate-dependent purine synthesis inhibitors on tumor cell response to CD8+ T cell cytotoxicity. We found that inhibition of key enzymes such as methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) and glycinamide ribonucleotide transformylase (GART) markedly enhanced tumor cell sensitivity to T cell killing, an effect also observed with exogenous nucleoside supplementation. Mechanistically, inhibition of folate-dependent purine synthesis suppresses glycolysis by downregulating critical glycolytic enzymes, thereby reducing lactate production. Reduction in lactate further weakens lactylation and stability of the immune checkpoint protein PD-L1. In parallel, impaired purine synthesis disrupts uridine metabolism, blocks ribose salvage, and distally influences glycolysis. Collectively, our study identified the folate-dependent purine synthesis - glycolysis axis as key regulator of tumor immune response and highlights metabolic targeting as a promising strategy to improve cancer immunotherapy.

cancer biology↗