Biology subjects

Zhao, L.

Publications and source records attributed to Zhao, L..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Quantitative metagenomics reveals fine-scale population dynamics across bacteria, archaea, and microbial eukaryotes in an estuarine-coastal continuum

Microbial communities are foundational to marine ecosystem function, yet their diversity is often obscured by broad taxonomic groupings and relative-abundance surveys that mask the dynamics of individual populations. This limitation is especially important across estuarine-coastal gradients, where microbial standing stocks, environmental conditions, and community composition vary sharply over space and time. Here, we used quantitative, genome-resolved metagenomics to examine microbial population dynamics across a one-year estuary-to-ocean transect spanning the Neuse River Estuary, Pamlico Sound, and adjacent North Atlantic shelf waters. Internal standard normalization enabled absolute abundance estimates for single-copy genes and metagenome-assembled genomes (MAGs), allowing individual populations to be tracked as genome equivalents per liter. Bacterial standing stocks were higher in estuarine waters, and communities varied primarily with salinity and season. We recovered 415 MAGs, including 386 bacterial genomes that represented, on average, 52% of bacterial genome equivalents, along with archaeal and eukaryotic representatives. Many abundant MAGs lacked close reference genomes, demonstrating that numerically important coastal populations remain poorly characterized. Genome-resolved abundances revealed pronounced niche partitioning among closely related taxa, including seasonal and spatial turnover of Synechococcus, Cyanobium, and Vulcanococcus populations associated with distinct pigment-defined cytometric groups. Rhodobacteraceae MAGs also showed population-specific correlations with picoeukaryotic MAGs, including a winter offshore Planktomarina population that reached 18% of total bacterial genome equivalents during a Micromonas-associated bloom. By providing absolute population abundances, this study transformed coastal microbiome surveys into numerical frameworks for resolving microbial population structure, ecological interactions, and biogeochemical relevance across dynamic environmental gradients. IMPORTANCEEstuarine and coastal waters contain diverse microbial communities that help regulate food webs and the cycling of carbon and nutrients, but many of the individual microbial populations responsible for these processes remain poorly understood. In this study, we examined bacteria, archaea, and small algae across the Neuse River Estuary, Pamlico Sound, and nearby coastal ocean waters over one year. By measuring the absolute abundance of individual microbial genomes, rather than only their relative proportions, we showed that closely related populations can have very different seasonal and spatial patterns. This was especially clear for cyanobacteria related to Synechococcus and heterotrophic bacteria in the family Rhodobacteraceae, which showed distinct population dynamics and associations with small algae. These results demonstrate how quantitative genome-resolved measurements can reveal hidden microbial population structure and improve our understanding of how microorganisms shape coastal ecosystem function.

genomics↗

bioRxiv2026

Identification of drug candidates for rescue of SOX17 gene targets in pulmonary arterial hypertension

BackgroundBoth rare and common variants in the SRY-Box Transcription Factor 17 (SOX17) locus are associated with pulmonary arterial hypertension (PAH). SOX17 dysregulation leads to pulmonary artery endothelial cell (PAEC) dysfunction and the obstructive remodelling that characterises PAH. HypothesisImpaired SOX17 expression contributes to the pathogenesis of PAH. Restoring the function of SOX17 or its downstream targets using compounds that mimic its transcriptomic signature will rescue PAEC dysfunction and prevent PAH development. Methods and ResultsWe defined thousands of genes with direct SOX17 genomic binding sites and identified important potential binding partners, including ETS-transcription factors such as ERG by ChIP-seq in PAECs. Through the integration of three PAEC RNA-seq datasets involving overexpression and silencing of SOX17, we defined a robust SOX17 transcriptomic signature. In PAH patients, circulating plasma protein levels of 10 SOX17 signature genes were associated with the SOX17 common risk variants. This included EFNB2 and UNC5B; knockdown of these genes altered the viability and apoptosis of PAECs in response to TNF treatment. The drug-transcriptome database Connectivity Map (CMap) was used to predict novel potential therapeutic compounds to correct the SOX17 transcriptomic signature. Five compounds were selected for in vitro testing and were able to partially reinstate SOX17 target gene expression in PAECs. One compound, BX-912, was selected for in vivo testing as it corrected the levels of multiple target genes, including suppressing Runt-related transcription factor-1 (RUNX1). BX-912 blocked the development of pulmonary hypertension in mice lacking the SOX17 enhancer associated with human disease. ConclusionWe have demonstrated the therapeutic potential of targeting SOX17 in PAH through correction of its gene targets, identifying BX-912 as a lead compound with in vivo efficacy.

pharmacology and toxicology↗

bioRxiv2026

Impaired SOX17 Expression Causes Endothelial Dysfunction and Pulmonary Arterial Hypertension by Insufficient Suppression of RUNX1

Genome-wide association studies have identified rare and common mutations associated with increased risk of pulmonary arterial hypertension (PAH), but the mechanism by which impaired SOX17 expression increases PAH risk is not known. Notably, SOX17 plays a critical role in endothelial identity during development by suppressing RUNX1 through binding to its promoter and directing stem and progenitor cells toward an endothelial rather than a hematopoietic cell fate. RUNX1 functions as a key regulator of myeloid differentiation, aberrant angiogenesis and adverse cardiac remodeling. Previously, we found that RUNX1 inhibition reverses pulmonary hypertension (PH) in multiple animal models. Here, we hypothesize that impaired expression of SOX17 in PAH leads to endothelial cell (EC) dysfunction by failing to suppress RUNX1. METHODSHuman pulmonary artery endothelial cells (HPAECs) with stable SOX17 CRISPR/Cas9 knockout or RUNX1 overexpression were generated and examined for endothelial and hematopoietic gene expression, proliferation, migration, apoptosis, and angiogenesis. Immortalized lymphoblastoid cell lines (LCLs) from PAH patients with SOX17 mutations and healthy controls were reprogrammed into induced pluripotent stem cells (iPSCs) and differentiated into ECs. The effect of RUNX1 inhibition on Sugen/hypoxia-PH was examined in rats, SOX17 enhancer knockout (SOX17enhKO) mice, and Cdh5-CreERT2;Runx1(flox/flox);SOX17enhKO triple transgenic mice. SOX17 and RUNX1 expression were analyzed in peripheral blood samples from PAH patients (n=359). RESULTSHPAECs with SOX17 deletion or RUNX1 overexpression exhibited decreased expression of EC markers, enhanced proliferation and migration, defective angiogenesis, and decreased apoptosis. RUNX1 siRNA knockdown or RUNX1 inhibition by Ro5-3335 partially restored the endothelial properties in SOX17 KO HPAECs. ECs differentiated from SOX17 mutant PAH patient iPSCs exhibited upregulated RUNX1 expression and loss of endothelial identity, which was also partially restored by RUNX1 siRNA or Ro5-3335. In addition, SOX17enhKO mice had increased RUNX1 expression and susceptibility to Sugen/hypoxia-induced PH (SuHx-PH). Treatment with RUNX1 inhibitors or inducible endothelial-specific deletion of RUNX1 rescued SuHx-PH susceptibility in SOX17enhKO mice. RUNX1 inhibitors Ro5-3335 and Ro24-7429 also reversed SuHx-PH in wild-type rats. In addition, plasma RUNX1 expression was higher in PAH patients lacking detectable SOX17 expression than in patients with detectable SOX17 expression. CONCLUSIONSImpaired SOX17 expression increases the risk of PAH through insufficient suppression of RUNX1, leading to pulmonary endothelial dysfunction. RUNX1 inhibition mitigates PH associated with SOX17 deficiency and may represent a novel therapeutic strategy for PAH, especially those with rare or common SOX17 mutations.

cell biology↗

bioRxiv2026

Humanization of N-glycan-dependent protein quality control system in Kluyveromyces marxianus promotes glycoprotein secretion

Human N-glycoproteins constitute a market worth hundreds of billions of dollars. However, their production in yeast is often limited by misfolding and subsequent degradation, largely due to differences in N-glycan-dependent protein quality control (QC) systems between humans and yeast. Notably, yeast lacks the UGGT-mediated reglucosylation-refolding cycle that rescues misfolded glycoproteins, and its degradation pathway involves fewer rate-limiting steps. To address this, we engineer the glycoprotein QC system in Kluyveromyces marxianus, a promising host for protein production, by introducing key human components and modifying native pathways. Expression of human UGGT1 or UGGT2 enhances the soluble and secretory production of glycoproteins in an activity-dependent manner. This effect is further improved by co-expression of the UGGT cochaperone SEP15 and by reducing native glucosidase II trimming activity. In addition, introduction of human EDEM2, a rate-limiting enzyme in glycoprotein degradation, delays ER-associated degradation and increases secretion. Integration of these engineering strategies substantially enhances the production of several high-value human-derived glycoprotein therapeutics, including etanercept, dulaglutide, and abatacept, with up to a [~]12-fold increase. These findings demonstrate that engineering a human-like glycoprotein QC network in yeast is an effective strategy to improve glycoprotein folding and secretion.

bioengineering↗

bioRxiv2026

Targeting cancer-associated cell surface RNAs with oligonucleotide-drug conjugates enables broad antitumor activity

Recent studies have revealed the presence of RNAs on mammalian cell surfaces, yet the linkage of cell surface RNAs (csRNAs) to cellular states and their potential as extracellular accessible drug targets remains unexplored. Here we develop Cell-surface and Intracellular RNAs Co-mapping (CIRCmap), a highly multiplexed in situ profiling approach that simultaneously detects thousands of cell-surface and intracellular RNAs at single-cell resolution. Using CIRCmap, we uncover that csRNA distributions are correlated with cellular states and identified cancer-associated csRNAs. Integrative analysis of cell-surface and intracellular RNAs within the same cells implies that the csRNAs undergo endocytosis and endolysosomal trafficking, which is further supported by perturbation experiments and co-localization visualization. We design oligonucleotide-drug conjugates (ODCs) that target cancer-associated csRNAs for endocytic delivery of cytotoxic payloads selectively to cancer cells. ODCs exhibit broad antitumor activity in cell lines and an in vivo mouse tumor model, opening a promising new avenue for targeted cancer therapy.

cell biology↗

bioRxiv2026

Organoid modeling of tumor-associated macrophages reveals phagocytosis checkpoint blockade-induced conversion to an immunosuppressive SPP1+ phenotype

Tumor-associated macrophages (TAM) exert essential functions during the immune response to cancer. However, investigations of TAM within a native human tumor microenvironment (TME) have been impeded by a lack of appropriate model systems. Here, patient-derived organoids (PDO) from air-liquid interface (ALI)-grown tumor fragments, containing a human TME that encompassed stroma and immune subsets, robustly preserved TAM that were maintained by endogenous CSF-1 and appropriately responded to polarization signals. Antibody blockade of the CD47 regulatory checkpoint in organoids stimulated phagocytosis and remodeled TAM cytokine secretion profiles that were confirmed in anti-CD47 phase I trial patients. Amongst PDO histologies screened, anti-CD47 tumor killing was notable in clear cell renal cell carcinoma (ccRCC) which was associated with increased TAM infiltration. PDO contained diverse previously described TAM subsets; however, anti-CD47 reprogrammed organoid TAM toward an immunosuppressive SPP1+ phenotype, highlighting a negative feedback mechanism. Our findings uncover a resistance circuit engaged by macrophage checkpoint blockade and position ALI PDO as a robust translational platform for dissecting human macrophage biology and informing precision immunotherapy.

cancer biology↗

bioRxiv2026

Correlation, Regression, and Growth Curve Analyses of Body Weight and Body Measurements in Female Jiangyue Donkeys

ObjectiveThis study aimed to systematically analyze the correlation between body weight and body measurement traits and the growth pattern of female Jiangyue donkeys. MethodsA total of 484 female Jiangyue donkeys were selected to determine their body weight (Y) and 11 body measurement traits, including withers height (X1), body length (X2), chest circumference (X3), cannon circumference (X4), head length (X5), neck length (X6), chest width (X7), chest depth (X8), rump height (X9), rump length (X10) and rump width (X11). SPSS 27.0 statistical software was used to conduct descriptive statistics, correlation and regression analysis on body weight and body measurement traits, and the optimal regression equation between them was established by the stepwise method and validated. Furthermore, four growth curve models (Logistic, Gompertz, Brody and Von Bertalanffy) were used to fit the body weight of 241 female Jiangyue donkeys at different months of age. ResultsThe body weight of female Jiangyue donkeys was significantly positively correlated with all body measurement traits (p<0.01), with the highest correlation coefficient observed for chest circumference. The optimal regression equations for body weight established by stepwise regression yielded R{superscript 2} values of 0.918 and 0.844 for growing and adult donkeys, respectively (p<0.01). Among the four growth curve models, the Von Bertalanffy model exhibited the best fitting effect (R{superscript 2}=0.99992), with an estimated asymptotic body weight of 184.41 kg, which was close to the measured values of growing female donkeys. ConclusionThe regression models for body weight estimation and the Von Bertalanffy growth curve model for growth pattern evaluation established in this study can serve as effective tools and production management of female Jiangyue donkeys.

genetics↗

bioRxiv2026

CMS: Achieving Uniform and High-Quality Sequencing across Challenging Non-canonical Genomic Regions

High-throughput sequencing is essential in modern biological research, yet low-complexity sequences remain challenging as they form structurally complex, non-canonical (non-B) DNA conformations that impede sequencing enzyme read-through. This leads to a long-standing trade-off: maximizing coverage introduces false positives (FP), while stringent filtering causes coverage loss and false negatives (FN). To address this, we developed CMS (Cross Mountains and Seas) on GeneMind sequencing platforms by optimizing its chemistry and enzymatic systems to traverse these secondary structures with high fidelity. Benchmarking across whole-genome (WGS) and whole-exome (WES) sequencing demonstrates that CMS addresses the trade-off by simultaneously enhancing both coverage uniformity and accuracy, notably achieving an approximately 100-fold reduction in low-coverage bins for WGS and a 70% reduction in FN insertions/deletions (INDELs) within complex non-B regions. Specifically, a synthetic G-quadruplex (G4) motif sequencing experiment demonstrates that CMS maintains a 1:1 strand ratio, effectively handling G4-induced biases where benchmarked platforms exhibit extensive depletion. These findings establish CMS as a reliable technology for the precise characterization of structural-challenging but functional-essential genome regions.

genomics↗

bioRxiv2026

A Context-Aware Target Engagement and Pharmacodynamic Biomarker Resource to Accelerate Drug Discovery and Development

Confirming target engagement in tumor experimental models remains a major challenge in oncology drug development. Pharmacodynamic biomarkers can help address this, but few systematic resources link drug targets to candidate biomarkers. We developed TargetTrace, a comprehensive resource to identify and prioritize pharmacodynamic biomarkers across nine key target classes, including transcription factors/cofactors, kinases, phosphatases, ubiquitin ligases, deubiquitinases, acetyltransferases, deacetylases, methyltransferases, and demethylases. Biomarker candidates were gathered from curated molecular interaction resources and refined using external annotations to improve accuracy. For enzyme targets with measurable substrate changes, we applied a two-agent large language model workflow, followed by manual review, to harmonize antibody information from the antibody resources and ensure that the selected biomarkers are measurable with existing laboratory tests. From more than 92,000 input interactions and over 2,300 targets, we compiled 71,323 target-biomarker relationships involving 2,270 potential drug targets, encompassing both transcription factor/cofactor-target gene and enzyme-substrate interactions. Commercial antibodies were available for over 1,400 biomarkers, supporting laboratory validation. This resource provides a structured and reusable resource for systematic identification and prioritization of pharmacodynamic biomarkers in oncology.

bioinformatics↗

bioRxiv2026

Vascularized Human Cardiac Organoids Reveal Endothelial-Cardiomyocyte Crosstalk and Mechanisms of Carfilzomib-Induced Cardiotoxicity

Human cardiac organoids (hCOs) provide a powerful platform for modeling heart development and disease, yet their lack of vasculature limits physiological relevance. Here, we generate vascularized human cardiac organoids (vhCOs) by assembling hCOs with blood vessel organoids, enabling the self-organized formation of unified tissues with extensive vascular networks and substantially enhanced cardiomyocyte (CM) maturation. Single-nucleus multiomic profiling reveals CM state resembling the 17-week human fetal heart, while endothelial cells (ECs) acquire cardiac-specific and arterial-like identities. Integrative cell-cell communication analyses and experimental validation identify CM-derived Laminin-2 as a driver of arterial EC specification, while reciprocal EFNB2 signaling from arterial ECs promotes CM maturation, uncovering bidirectional cardiac-vascular crosstalk. Modeling carfilzomib-induced cardiotoxicity in vhCOs reveals ATF4-dependent endoplasmic reticulum (ER) stress and IL8-mediated inflammatory responses that are blunted in non-vascularized hCOs. Pharmacological attenuation of ER stress alleviates carfilzomib-induced cardiotoxicity. Altogether, vhCOs provide a developmentally advanced and physiologically faithful human cardiac model.

cell biology↗

bioRxiv2026

In Situ Landscape of Focal Adhesions and Cytoskeletal Integration Revealed by Cryo-Electron Tomography

Focal adhesions (FAs) are dynamic hubs for mechanotransduction, linking the extracellular matrix to actin fibers, intermediate filaments, and microtubules. Using cryo-electron tomography combined with 3-dimensional segmentation and subtomogram averaging, we visualize in situ the structural architecture of the FA environment at the leading edge of human fibroblasts. Our analysis reveals a rich architectural diversity within the FA landscape, where the spatial organisation and interplay of FA protein clusters, actin, vimentin, and microtubules change from the actin bundle core to its tip and across adjacent regions. Notably, we reveal diverse arrangements and connections of vimentin filaments, supporting their multifaceted role in the control and mechanics of adhesions. Together, these findings establish a structural framework for FA maturation and cytoskeletal integration, extending classical lamellipodial adhesion models and providing mechanistic insight into how FAs coordinate force transmission during cell migration.

cell biology↗

bioRxiv2026

Box H/ACA snoRNP regulates lipid storage through insulin signaling pathway in Drosophila melanogaster

Text abstractsLipid homeostasis is essential for organismal physiology, and its disruption contributes to metabolic disorders. Using an unbiased genetic modifier screen in Drosophila, we identified GAR1, a core component of the box H/ACA small nucleolar ribonucleoprotein complex, as a pivotal regulator of systemic lipid storage. We show that the H/ACA snoRNP complex is essential for maintaining lipid droplet morphology in adipose tissue and preventing ectopic fat accumulation. Moreover, null mutants of Gar1 or Dkc1 exhibit severe developmental defects, including reduced body size and larval lethality. RNA-seq analysis revealed that Gar1 dysfunction triggered widespread alternative splicing defects, specifically targeting key transcripts within the insulin signaling cascade, including chico, Pi3K92E, sgg, and Lip4. Furthermore, knockdown of Gar1 impaired insulin signaling, as evidenced by the reduced membrane localization of the tGPH fluorescence. Genetic epistasis further positions GAR1 upstream of the lin-28/foxo axis, as knocking down lin-28 or foxo fully rescues the lipometabolic defects in GAR1-deficient animals. These findings reveal a previously unrecognized link between the snoRNP machinery and metabolic process, establishing the box H/ACA complex as an important coordinator that integrates RNA processing with insulin-mediated nutrient sensing to ensure developmental and lipid homeostasis. Article summaryLipid metabolism is tightly controlled by multiple factors. To find new regulators, the authors performed a genetic screen and identified a small nucleolar protein GAR1 participate in fat storage and larval development. They demonstrated a critical role of box H/ACA snoRNP complex in modulating alternative splicing and balancing insulin cascade. Blocking two insulin-related genes reversed the lipid defects caused by Gar1 loss. These findings revealed the box H/ACA complex integrates RNA processing with insulin-mediated nutrient sensing to ensure developmental and lipid homeostasis, offering a perspective for understanding the metabolic regulation network.

genetics↗

bioRxiv2026

PITPβ Drives JAK2 V617F-Mediated Myeloproliferative Neoplasms by Promoting PtdIns(3,4)P2-Dependent AKT Hyperactivation

JAK2 is a key regulator of cytokine-mediated proliferative signaling in hematopoietic stem and progenitor cells. Activating mutations, most commonly JAK2 V617F, trigger aberrant cytokine signaling driving the pathogenesis of myeloproliferative neoplasms (MPNs). Phosphatidylinositol transfer proteins (PITPs) facilitate phosphoinositide synthesis by delivering phosphatidylinositol to lipid kinases, though their roles in oncogenic signaling have remained poorly defined. Here we show that PITP{beta} is critical for the development of JAK2V617F-driven MPN in mice. Deleting Pitp{beta} across the hematopoietic system, but not Pitp, prolonged 25-week survival of Jak2V617F mice from 10% to 85%. Loss of Pitp{beta} attenuated disease-associated splenomegaly and curtailed erythroid progenitors expansion both in vivo and in vitro. Mechanistically, PITP{beta} is necessary for AKT hyperactivation in hematopoietic progenitors, while STAT5 and ERK signaling remain unaffected. In alignment with this role, PITP{beta} promotes the production of PtdIns(3,4)P2, a phosphoinositide that sustains aberrant AKT signaling in Jak2V617F progenitors. Pharmacologic inhibition of AKT with the FDA-approved inhibitor capivasertib in Jak2V617F-transplanted mice similarly reduced splenomegaly and erythroid proliferation, mimicking the effects of Pitp{beta} loss. Collectively, these results identify a novel PITP{beta}-PtdIns(3,4)P2 signaling axis that selectively maintains pathological AKT activation in JAK2V617F-driven MPN, revealing a promising therapeutic vulnerability.

cancer biology↗

bioRxiv2026

Chromatin landscape and epigenetic heterogeneity of acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive hematologic cancer characterized by proliferation of immature myeloblasts. It shows profound molecular heterogeneity, which has been primarily studied through genetic abnormalities, providing the basis for disease classification, prognostication, and therapeutic choice. However, genetic factors alone may not fully explain AML pathogenesis and diversity, while leaving the role of abnormal epigenome, particularly chromatin state, largely unexplored in a large cohort of patients. Here we show that AML is classified into 16 subgroups with distinct chromatin accessibility profiles based on ATAC-seq in 1,563 AML cases, including novel AML subgroups not previously recognized in conventional genomic classifications. By integrating multi-omics analyses of genome, transcriptome, and major histone marks, we show that these epigenetic subgroups exhibit unique features in clinical presentation, gene mutations, differentiation states, gene expression, and super-enhancer profiles, which are validated across independent cohorts. Single-cell sequencing demonstrates the presence of subgroup-specific ATAC signatures that are shared by all leukemic cells, confirming the definitive role of the epigenome in the ATAC-based classification. Mechanistically, each subgroup is associated with a distinct gene regulatory network centered on key transcription factors, where subgroup-specific super-enhancers play a pivotal role. These ATAC subgroups also have prognostic significance independent of genomic classification, and help reveal unexpected drug sensitivities. In summary, ATAC-based chromatin profiling in this large sample set, combined with multi-omics data, provides new insights into AML pathogenesis beyond genomic profiling and also serves as an invaluable resource for AML research.

cancer biology↗

bioRxiv2026

Rastair: an integrated variant and methylation caller

Cytosine methylation is a crucial epigenetic mark that impact tissue-specific chromatin conformation and gene expression. For many years, bisulfite sequencing (BS-seq), which converts all non-methylated cytosine (C) to thymine (T), remained the only approach to measure cytosine methylation at base resolution. Recently, however, several new methods that convert only methylated cytosines to thymine (mC[->]T) have become widely available. Here we present rastair, an integrated software toolkit for simultaneous SNP detection and methylation calling from mC[->]T sequencing data such as those created with Watchmakers TAPS+ and Illuminas 5-Base chemistries. Rastair combines machine-learning-based variant detection with genotype-aware methylation estimation. Using NA12878 benchmark datasets, we show that rastair outperforms existing methylation-aware SNP callers and achieves F1 scores exceeding 0.99 for datasets above 30x depth, matching the accuracy of state-of-the-art tools run on whole-genome sequencing data. At the same time, rastair is significantly faster than other genetic variant callers, processing a 30x depth file takes less than 30 minutes given 32 CPU cores on an Intel Xeon, and half as long when a GPU is available. By integrating genotyping with methylation calling, rastair reports an additional 500,000 positions in NA12878 where a SNP turns a non-CpG reference position into a "de-novo" CpG. Vice-versa, rastair also identifies positions where a variant disrupts a CpG and corrects their reported methylation levels. Rastair produces standard-compliant outputs in vcf, bam and bed formats, facilitating integration into downstream analyses pipelines. Rastair is open-source and available via conda, Dockerhub, and as pre-compiled binaries from https://www.rastair.com.

bioinformatics↗

bioRxiv2026

A Long-Context Generative Foundation Model Deciphers RNA Design Principles

Programmable design of RNA sequences with defined functions remains a central challenge in biology. Despite recent advances, existing RNA generative models lack robust controllable design capabilities and are constrained by short context windows, limiting their capacity to model the complex evolutionary manifold of full-length transcripts. Here, we introduce EVA (Evolutionary Versatile Architect), a long-context generative RNA foundation model trained on over 114 million full-length RNA sequences spanning the full breadth of evolutionary diversity. By integrating a Mixture-of-Experts architecture with an 8,192-token context window, EVA learns a unified, evolution-consistent representation of RNA sequence space that captures both global transcript structure and fine-grained functional elements. EVA establishes a unified framework for a broad spectrum of RNA design tasks within a single architecture, ranging from mutational fitness prediction to context-aware sequence engineering. We demonstrate EVAs versatility through the de novo design and targeted optimization of diverse RNA classes, including tRNAs, aptamers, and CRISPR guide RNAs, as well as mRNA and circular RNA therapeutics. In systematic evaluations, EVA achieves state-of-the-art performance across seven of nine established benchmarks, improving structural modeling accuracy by up to an order of magnitude compared to existing approaches. EVA is fully open-source at the following repository: https://github.com/GENTEL-lab/EVA.

molecular biology↗

bioRxiv2026

Identification and Masking of Artefactual and Misleading Within-Host Variants in Deep-Sequencing SARS-CoV-2 Data

Deep sequencing data are increasingly used to study within-host viral diversity and to inform evolutionary inference. For SARS-CoV-2, analyses based on intra-host single-nucleotide variants (iSNVs) have been widely applied to quantify within-host diversity and infer transmission dynamics. However, these applications critically depend on the reliable identification of low-frequency variants, which remain vulnerable to systematic and technical artefacts. In this study, we show that recurrent artefactual iSNVs are common in large-scale SARS-CoV-2 sequencing data and can persist even under conservative minor allele frequency (MAF) thresholds. Using data from the UKs Office for National Statistics COVID-19 Infection Survey, we demonstrate that such artefacts are predominantly sequencing centre-rather than protocol-specific. Each centre exhibits a modest, distinct set of recurrent artefactual variants showing little overlap with sites routinely masked at the consensus level. To address this, we developed a systematic, dataset-aware framework that uses recurrence within sequencing datasets to identify small, noise-adapted sets of artefactual iSNVs to mask. Applying this framework reduces spurious sharing of low-frequency variants between samples and qualitatively alters downstream inferences, including estimates of within-host diversity and transmission bottleneck sizes. Together, these findings highlight the importance of explicit, dataset-aware artefact control for robust inference from within-host variation, particularly as genomic studies increasingly seek to exploit sub-consensus diversity in rapidly evolving pathogens such as SARS-CoV-2.

genomics↗

bioRxiv2026

Therapeutic targeting inflammation linking periodontitis and atherosclerotic comorbidities using cell-free DNA-capturing nanomaterials

Periodontitis-associated systemic inflammation makes it a great challenge to explore therapeutic options applicable to periodontitis and atherosclerotic comorbidities. Here, we identify the crucial role of cell-free DNA (cfDNA) that underlies these comorbidities. Hypothesizing cfDNA as a therapeutic target, we engineer polyamidoamine dendrimer-functionalized nanomaterials to modulate such local-systemic inflammatory crosstalk. Periodontium-originated DNA can be systemically captured by cationic nanomaterials, and capturing cfDNA, whether locally or systemically, alleviates both periodontitis and atherosclerosis prior to severe atherosclerotic development in vivo. The transcriptomic and single-cell RNA sequencing analyses together reveal that cfDNA-capturing nanomaterials regulate inflammatory foam cell transformation in macrophages by modulating the expression of lipid-related foamy markers Spp1 and Fabp4. This study provides a proof of concept for cfDNA-driven periodontitis-atherosclerosis crosstalk, and offers a cfDNA-capturing nanoplatform for therapeutic intervention targeting periodontitis and atherosclerotic comorbidities in a holistic fashion.

immunology↗