Biology subjects

Chen, S.

Publications and source records attributed to Chen, S..

At least 127 records · Page 7Linked to original sources

bioRxiv2026

Ecological Role of the Heterotrophic Protist Aurantiochytrium (Labyrinthulomycetes) as a Key Consumer of Viral-Induced Dissolved Organic Matter Following the Lysis of the Red Tide-forming Microalga Heterosigma akashiwo

Marine algal blooms play a vital role in oceanic carbon cycling, yet the ecological consequences of algal organic matter released following their collapse via viral infection are poorly understood. Recent studies have shown that viral infection dramatically alters the hosts intracellular metabolite composition, and the subsequent viral lysate selectively promotes the growth of specific prokaryotic populations. This study aimed to elucidate the effect of organic matter derived from healthy and virus-infected cells of the bloom-forming alga Heterosigma akashiwo on the growth of heterotrophic eukaryotes, specifically Labyrinthulomycetes. These marine protists are primarily saprotrophic or predatory and contribute to dissolved organic matter (DOM) decomposition and nutrient cycling. Our field monitoring in Osaka Bay over 12 months revealed that while the overall Labyrinthulomycetes community showed no clear seasonality, specific populations of the protists co-occurred with Heterosigma akashiwo. To mechanistically investigate the potential trophic linkage suggested by these field observations, a co-culture system comprising H. akashiwo, its specific virus (HaV53), and Aurantiochytrium sp. NBRC102614, used here as a model Labyrinthulomycete, was established. In the co-culture experiments, viral lysis of H. akashiwo led to a significant increase in the cell density of Aurantiochytrium sp., demonstrating that Aurantiochytrium can thrive on substrates derived from the virus-infected alga, such as viral-induced dissolved organic matter (vDOM). These findings highlight that heterotrophic Labyrinthulomycetes are one of key consumers of virus-modified organic matter, playing a pivotal role in carbon cycling following the collapse of harmful algal blooms and influencing carbon transfer in coastal microbial food webs. IMPORTANCEMarine ecosystems are tightly regulated by the interplay between microalgae, viruses, and heterotrophic eukaryotes, yet their roles within this network have long been underestimated. Accordingly, this study aimed to provide an overview of the dynamics of environmental microalgae and heterotrophic eukaryotes, namely Heterosigma species and Labyrinthulomycetes, and to elucidate the impact of virus-infected Heterosigma akashiwo on the growth and proliferation of Aurantiochytrium species within heterotrophic Labyrinthulomycetes. This study revealed the dynamics of several Labyrinthulomycetes species associated with Heterosigma populations in coastal marine environments and demonstrated that Aurantiochytrium species have the capacity to redistribute carbon, such as by utilizing vDOM released during the termination of Heterosigma blooms via viral infection, thereby repositioning Aurantiochytrium from a passive component of Heterosigma viral infection toward an active ecological agent that facilitates energy transfer and contributes to the maintenance of microalgal community dynamics. Overall, this work provides new insights into the fate of virus-infected Heterosigma in coastal marine systems mediated by heterotrophic Labyrinthulomycetes, particularly Aurantiochytrium species, thereby filling an important knowledge gap in microbial ecology.

microbiology↗

bioRxiv2026

Design of Fluorescent Membrane Scaffold Proteins for Nanodiscs

Nanodiscs are nanoscale lipid bilayer membrane mimetics surrounded by two membrane scaffold proteins (MSP). They are widely used as soluble cassettes for membrane proteins and lipids in diverse applications in structural, functional, and biophysical studies. The original MSP was derived directly from human apolipoprotein A-1, and novel constructs have been adapted from this original design, including fluorescent nanodiscs of varying designs. However, chemical derivatization with fluorophores can be expensive, and prior designs of split fluorescent proteins fused to MSP were limited in the color pallet available. Here, we developed MSPs with a wide range of different fluorescent C-terminal protein tags, including a versatile HaloTag fusion. These fluorescent MSP were purified following typical MSP purification procedures with similar yield. Then, we demonstrate that fluorescent MSPs form nanodiscs with similar structure and stoichiometry to conventional MSP nanodiscs. They are also suitable for assembly of nanodiscs with embedded integral membrane protein. Finally, we apply these constructs to monitor peripheral membrane protein binding to lipids via fluorescence resonance energy transfer. These fluorescent MSP constructs enable a range of different applications and provide a versatile template for future design of nanodiscs with unique functions. For Table of Contents Only O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=109 SRC="FIGDIR/small/716332v3_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@1bf2d2borg.highwire.dtl.DTLVardef@2ea07eorg.highwire.dtl.DTLVardef@12aeccforg.highwire.dtl.DTLVardef@121430d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

eSIG-Net: Accurate prediction of single-mutation induced perturbations on protein interactions using a language model

Most proteins exert their functions in complex with other interactors. Single mutations can exhibit a profound impact on perturbing protein interactions, leading to human disease. However, predicting the effect of single mutations on protein interactions remains a major computational challenge. Deep learning, particularly protein language models or transformers, has become an effective tool in bioinformatics for protein structure prediction. However, the functional divergence of mutations makes it difficult to predict their interaction perturbation profiles. To address this fundamental challenge, we present eSIG-Net (edgetic mutation Sequence-based Interaction Grammar Network), a novel sequence-based "Interaction Language Model" for predicting protein interaction alterations caused by single mutations. eSIG-Net combines various protein sequence embeddings, introduces a mutation-encoding module with syntax and evolutionary insights, and employs contrastive learning to evaluate mutation-induced interaction changes. eSIG-Net significantly outperforms current state-of-the-art sequence-based and structure-based prediction methods at predicting mutational impact on protein interactions. We highlight examples where eSIG-Net nominates causal variants with high confidence and elucidates their functional role under relevant biological contexts. Together, eSIG-Net is a first-in-kind "interaction language model" that can accurately predict interaction-specific rewiring by single mutations with only sequence information, and exhibits generalizability across biological contexts.

bioinformatics↗

bioRxiv2026

A Non-Canonical Role of SMAD4 in Regulating 3D Genome Architecture to Inhibit Lung Squamous Cell Carcinoma Development

Lung squamous cell carcinoma (LUSC) lacks clearly defined key drivers and effective targeted therapies, reflecting an incomplete understanding of its molecular pathogenesis. Here, we identify SMAD4 as a critical regulator of three-dimensional (3D) genome organization in LUSC and uncover a mechanistic link between tumor suppressor loss and oncogenic transcriptional activation. By integrating clinical datasets, genetically engineered mouse models, human and murine LUSC cell lines, and multi-omics analyses, we demonstrate that SMAD4 deficiency promotes LUSC progression by unleashing EP300-mediated enhancer-promoter looping at the SOX2 locus. Mechanistically, SMAD4 does not directly bind SOX2 regulatory elements but instead constrains chromatin looping by sequestering EP300 away from loop anchor regions. Loss of SMAD4 leads to enhanced H3K27ac deposition, aberrant SOX2 activation, and increased LUSC tumor cell proliferation. Together, these findings reveal a non-canonical role for a transcription factor (e.g., SMAD4) in regulating dysregulated 3D genome architecture to inhibit tumor development.

cancer biology↗

bioRxiv2026

Polyclonal-Monoclonal Transition in Lung Squamous Cell Carcinoma Evolution

The evolutionary trajectory of lung squamous cell carcinoma (LUSC) remains poorly defined, hindering the development of effective therapies. By integrating genomic and transcriptomic sequencing from human LUSC specimens, we delineated a polyclonal-to-monoclonal evolutionary trajectory during LUSC progression. This evolutionary pattern was corroborated by single-cell RNA sequencing, which revealed consistent tumor cell heterogeneity. Specifically, the SBS5 mutational signature was enriched and correlated with poor prognosis independent of tumor stage. By further utilizing the spontaneous LUSC mouse model to identify key genomic and genetic events in LUSC progression, we observed that the JNK pathway was inhibited and that cytoskeleton-related pathways were dysregulated during LUSC development, and identified the mutations in the JNK pathway (e.g., DACT1) and cytoskeletal regulators (e.g., KIF26A). Collectively, these findings established a polyclonal-monoclonal evolution paradigm for LUSC, potentially regulated by JNK pathways, which could benefit LUSC precision therapeutics.

genomics↗

bioRxiv2026

EthoClaw: An Integrated AI Workflow Platform for Automated Analysis in Neuroethology

Computational methods have advanced the analysis of animal behavior, yet significant challenges remain in data standardization, analytical reproducibility, and workflow integration. Existing computational solutions often demand extensive programming proficiency or compel users to navigate a highly fragmented ecosystem of disconnected tools for tracking, statistical analysis, and visualization. Here, we present EthoClaw, an open-source, artificial intelligence-driven workflow platform built upon the OpenClaw agentic framework, functioning as a locally deployable AI assistant for behavioral research. EthoClaw provides an integrated computational infrastructure that seamlessly bridges the gap between raw behavioral video acquisitions and publishable scientific results. In this study, we demonstrate the platforms capacity to natively ingest video data via a dual-mode tracking architecture: utilizing ultra-fast image processing for rapid object detection, and leveraging the SuperAnimal methods for precise, markerless postural tracking. To ensure maximal interoperability, EthoClaw automatically converts various tracking data formats into DeepLabCut-compatible formats, enabling high-throughput phenotyping by generating publication-quality visualizations alongside rigorous multidimensional statistical profiling. Furthermore, the platform incorporates a large language model (LLM)-driven reporting module that dynamically synthesizes analytical documents, ensuring methodological transparency. Through an open field test, we validate the practical usability of EthoClaw while accelerating computational throughput by localizing heavy video processing to circumvent cloud bandwidth bottlenecks. Operating via an omnichannel natural language interface that integrates seamlessly with ubiquitous instant messaging software, EthoClaw democratizes advanced computational behavioral analysis, offering a holistic, highly efficient ecosystem that enforces experimental reproducibility and open science principles.

animal behavior and cognition↗

bioRxiv2026

Pluripotency Factors Modulate Interferon Signaling in Embryonic Stem Cells

Despite lacking a robust interferon response, pluripotent stem cells remain highly resistant to viral infection, in part through the constitutive expression of immune genes traditionally classified as interferon-stimulated genes. While interferon signaling has been shown to be incompatible with the maintenance of pluripotency, the molecular mechanisms underlying this relationship remain poorly understood. Here, we investigate the transcriptional response of human embryonic stem cells (hESCs) to infection with a potent activator of the interferon response, an influenza A virus mutant lacking the viral NS1 protein. Single-cell RNA sequencing revealed that while most hESCs remain unresponsive to infection, a distinct subpopulation expresses type I and III interferons. Notably, only interferon-expressing cells mounted a robust antiviral response, characterized by strong induction of interferon-stimulated genes. In contrast to the bulk hESC population, interferon responding cells exhibited reduced expression of core pluripotency factors as well as negative regulators of interferon signaling, such as SOCS1 and SPRY4. Depletion of SOCS1 enabled hESCs to respond robustly to interferon stimulation, showing that this negative regulator is a key suppressor of interferon signaling in pluripotent stem cells. We further show that SOCS1 and additional negative regulators of IFN signaling are intrinsically expressed in hESCs and are transcriptionally controlled by pluripotency factors, such as NANOG, SOX2 and OCT4. Together, our findings support a model in which pluripotency factors regulate intrinsic immune gene expression, including negative regulators of interferon signaling, thereby suppressing canonical interferon signaling to preserve pluripotency while maintaining antiviral resistance. IMPORTANCEBy combining single-cell transcriptomics with functional studies, we demonstrate that the pluripotency transcriptional program active in pluripotent stem cells coordinately regulates pluripotency factors, antiviral genes, and negative regulators of interferon signaling. This integrated control enables pluripotent stem cells to achieve effective protection against viral infection while preserving their differentiation potential, providing new insights into how innate immunity is selectively constrained in pluripotent stem cells. These findings have important implications for stem cell-based therapies, where transient modulation of antiviral responses without disrupting pluripotency could improve therapeutic efficacy. More broadly, this work advances our understanding of interferon regulation that could inform the development of antiviral strategies that enhance protective immune responses while limiting harmful or unwanted inflammatory signaling.

immunology↗

bioRxiv2026

Aberrant retinal structure and vasculature in mouse models of dominant retinopathies caused by CRX homeodomain mutations

CRX is a transcription factor essential for photoreceptor differentiation and functional development. Two missense mutations in CRX homeodomain, CRXE80A and CRXK88N, are linked to early-onset dominant retinopathies. Molecular studies have revealed distinct profiles of perturbed gene expression in differentiating photoreceptors of knock-in mouse models, resulting from altered DNA binding activities of mutant CRX proteins. This study characterizes concurrent retinal and vascular alterations in knock-in mouse models. Fated cones are present in heterozygous and homozygous CrxE80A and CrxK88N mutants at birth, but subsequent cone differentiation is rapidly compromised. Expression of rod marker rhodopsin (RHO) is absent in CrxK88N/Nretinae but present in other mutants through adulthood. Notably, as compared to wildtype controls, RHO expression is prematurely activated in neonatal CrxE80A mutants. Among tested mutants, only CrxE80A/+retinae elaborate rod outer segments but still lose visual function by young adulthood. The presence of irregular retinal rosettes is a striking pathological phenotype in all mutants. Retinal rosettes displace the localization of inner neurons without affecting their cell numbers during retinal development. Retinal vessels develop close contact with rosette structures. In summary, disrupted photoreceptor differentiation leads to the loss of visual function and formation of retinal rosettes. The presence of retinal rosettes secondarily impairs the localization of inner neurons and vasculature. A deeper understanding of these cellular underpinnings will inform pathogenesis of CRX homeodomain mutations.

neuroscience↗

bioRxiv2026

Hyperactive STAT1 Promotes T Follicular Helper Type 1 Cell Differentiation to Trigger Autoimmunity

ABSTRACTSHeterozygous gain-of-function (GOF) mutations in signal transducer and activator of transcription 1 (STAT1) cause an inborn error of immunity characterized by immune dysregulation, recurrent infections and various autoimmune manifestations. However, the precise pathogenic mechanism by which STAT1 GOF contributes to autoimmunity remains elusive. In our cohort, STAT1-GOF patients exhibit biased circulating follicular helper T (cTfh) populations with CXCR3+ Tfh1-like features. Using a Stat1 GOF mouse model that spontaneously developed autoimmunity, we found that overactivated STAT1 promotes Tfh differentiation and disrupted T cell-dependent humoral responses with skewed immunoglobulin class switching towards IgG2. Furthermore, STAT1 GOF directly targets to Tfh and Th1 cell signature genes and thereby drives the development of Tfh1 cells with excessive IFN-{gamma} production, which implicated in autoantibody production and the development of autoimmunity. Notably, IFN-{gamma} neutralization significantly alleviated autoimmune cellular responses and autoantibody levels in mutant mice, highlighting IFN-{gamma} blockade as a promising targeted therapy for the STAT1-GOF patients with autoimmunity. Our findings suggest that proper regulation of STAT1 activity within a reasonable magnitude is crucial for ensuring optimal host-protective humoral immunity. One-sentence summaryOveractivated STAT1 promotes Tfh1 differentiation to drive autoimmunity.

immunology↗

bioRxiv2026

SCALE: Scalable Conditional Atlas-Level Endpoint transport for virtual cell perturbation prediction

Virtual cell models aim to enable in silico experimentation by predicting how cells respond to genetic, chemical, or cytokine perturbations from single-cell measurements. In practice, however, large-scale perturbation prediction remains constrained by three coupled bottlenecks: inefficient training and inference pipelines, unstable modeling in high-dimensional sparse expression space, and evaluation protocols that overemphasize reconstruction-like accuracy while underestimating biological fidelity. In this work we present a specialized large-scale foundation model SCALE for virtual cell perturbation prediction that addresses the above limitations jointly. First, we build a BioNeMo-based training and inference framework that substantially improves data throughput, distributed scalability, and deployment efficiency, yielding 12.51* speedup on pretrain and 1.29* on inference over the prior SOTA pipeline under matched system settings. Second, we formulate perturbation prediction as conditional transport and implement it with a set-aware flow architecture that couples LLaMA-based cellular encoding with endpoint-oriented supervision. This design yields more stable training and stronger recovery of perturbation effects. Third, we evaluate the model on Tahoe-100M using a rigorous cell-level protocol centered on biologically meaningful metrics rather than reconstruction alone. On this benchmark, our model improves PDCorr by 12.02% and DE Overlap by 10.66% over STATE. Together, these results suggest that advancing virtual cells requires not only better generative objectives, but also the co-design of scalable infrastructure, stable transport modeling, and biologically faithful evaluation.

cell biology↗

bioRxiv2026

The enhanced multi-tissue atlas of regulatory effects in cattle

Cattle are integral to global food security, yet the molecular architecture of their complex traits remains poorly understood. Here, we present the Cattle Genotype-Tissue Expression (CattleGTEx) Phase 1 resource (https://cattlegtex.farmgtex.org/), a substantial expansion of the pilot study. By leveraging 12,422 RNA-seq profiles across 43 tissues and 82 breeds, we characterized 433,972 primary and 161,428 non-primary regulatory effects spanning seven molecular phenotypes. This high-resolution atlas resolves 75% of GWAS signals for 44 complex traits, significantly addressing the "missing regulation" in livestock. We propose a genetic regulatory model demonstrating how variants across multiple biological layers interact with specific biological contexts to shape phenotypic variation. Furthermore, CattleGTEx elucidates mechanisms underlying adaptive evolution between Bos taurus and Bos indicus, as well as artificial selection in dairy and beef breeds. Finally, by mapping evolutionary constraints on these regulatory effects, we demonstrate the translational value of this resource for prioritizing causal variants in human complex diseases. Together, Phase 1 of CattleGTEx provides a transformative framework for functional genomics, precision breeding, and comparative genetics.

genetics↗

bioRxiv2026

Automated Cyclic Super-Resolution Microscopy for Nanoscale Protein Mapping

Nanoscale mapping of multiple molecular targets is essential for decoding cellular architecture, but current approaches are limited by low throughput, intensive manual intervention, and signal variability across imaging cycles. Here, we introduce CycSTORM, an integrated super-resolution imaging platform for automated cyclic (d)STORM that enables multiplexed nanoscale protein mapping in single cells. To overcome the instability inherent in multi-day imaging, CycSTORM combines automated fluidic exchange, active 3D drift correction, and an oxygen-excluded imaging environment to stabilize fluorophore blinking and enables sub-5 nm registration across day-long experiments. Furthermore, CycSTORM incorporates a rapid chemical inactivation step using meta-chloroperoxybenzoic acid (mCPBA), eliminating >99.9% residual fluorescence within 10 minutes and minimizing inter-cycle crosstalk while preserving sample integrity. By standardizing labeling to Alexa Fluor 647, a fluorophore with stable and well-characterized blinking behavior, CycSTORM minimizes fluorophore-dependent variation and provides a robust platform for consistent localization precision across cycles, enabling reliable mapping of protein organization in single cells. Using CycSTORM, we simultaneously map multiple protein targets within the same cells with nanometer precision. Together, these advances transform cyclic super-resolution imaging into a scalable approach for quantitative nanoscale mapping of molecular organization in single cells.

cell biology↗

bioRxiv2026

PRMT5 is Frequently Upregulated and a Potential Therapeutic Target in MTAP-deficient Malignant Peripheral Nerve Sheath Tumors

Malignant peripheral nerve sheath tumors (MPNSTs) are highly aggressive sarcomas with poor prognosis and a strong tendency for metastasis and relapse. Surgical removal remains the mainstay of treatment but is frequently ineffective or impractical. Currently, no effective targeted therapy exists for this type of malignancy. PRMT5 has recently emerged as a promising therapeutic target in various human cancers with MTAP loss, which results in cancer cell dependency on PRMT5 activity. The frequent loss of MTAP in MPNSTs suggests that PRMT5 inhibition is a promising therapeutic option and enables the stratification of cancer patients with few treatment options. We first examined human nerve sheath tumor samples and found that increased PRMT5 expression and activity correlated with MTAP loss in 86.8% (33/38) of MPNSTs and in atypical neurofibromatous neoplasm with uncertain biologic potential (ANNUBP) (5/5). When PRMT5 activity was inhibited genetically and chemically, the cell growth of MTAP-deficient MPNST cell lines was suppressed, but not that of MTAP-proficient MPNST cell lines. Moreover, in the PRMT5-inhibited MTAP-deficient MPNST cell lines, spontaneous DNA damage accumulation was observed following G2/M cell cycle arrest. The DNA replication stress marker RPA32 decreased, and CHK1 was activated early after PRMT5 knockdown, likely contributing to the accumulation of DNA damage. In addition, we combined PRMT5 inhibition with the DNA-damaging agents doxorubicin and gemcitabine, resulting in synergistic effects and increased cancer cell death in MTAP-deficient MPNST cell lines. Together, these findings identify PRMT5 as a compelling therapeutic target in MTAP-deficient MPNSTs. This PRMT5 inhibition strategy has strong translational potential for MPNSTs. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=181 SRC="FIGDIR/small/710638v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@15abc35org.highwire.dtl.DTLVardef@1fa4ebborg.highwire.dtl.DTLVardef@470c51org.highwire.dtl.DTLVardef@79cc3f_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

A recipient-based anti-conjugation factor triggers an abortive mechanism by targeting the Type IV secretion system

Many bacterial defense (immune) systems prevent the entry of foreign DNA by directly recognizing and targeting nucleic acids, effectively blocking all mechanisms of horizontal gene transfer1. However, systems defending specifically against conjugation, a major route for gene dissemination, have heretofore not been reported. We have discovered a novel defense factor, which we name AbjA (Abortive conjugation protein A), that specifically limits successful plasmid conjugation into a recipient bacterium. AbjA interacts directly with and targets the ATPase component TrbE of the Type IV secretion system (T4SS)2,3 to induce cell death; this contrasts with most other defense systems that act at the nucleic acid level. AbjA therefore represents the first member of a new class of bacterial defense factors that trigger what we term abortive conjugation. Previously, recipient bacteria were viewed largely as defenseless against the mechanism of conjugation4-6; our discovery and characterization of AbjA demonstrates that recipient bacteria can block conjugation to limit the transfer (and thus spread) of plasmids. Discovery of this class of defense systems thus has implications for bacterial defense, plasmid evolution, and possible strategic alternatives to rationally target plasmid spread, particularly with respect to virulence and antibiotic resistance.

microbiology↗

bioRxiv2026

Lysosomal Expansion Compartments Mediate Zinc and Copper Homeostasis in Caenorhabditis elegans

Zinc is an essential transition metal that participates in many biological processes. In C. elegans, excess zinc is stored in lysosomes in intestinal cells; this process involves increasing the expression of the zinc transporter CDF-2 and remodeling of lysosomes characterized by an increase in the volume of the expansion compartment. To determine if this is a more general property, we investigated other metals. Here we report that lysosomes are remodeled in response to excess copper, manganese, and cadmium, with each metal causing an increase in the volume of the expansion compartment. Mutants with a reduced number of lysosomes were hypersensitive to growth retardation caused by excess copper and manganese, suggesting metal toxicity is prevented by metal sequestration in lysosomes. Using a novel method to analyze isolated lysosomes by X-ray Fluorescence Microscopy we demonstrated that zinc, copper and manganese are detectable in the lumen of lysosomes. To further analyze copper, we examined localization of CUA-1.1, a copper transporter that moves copper into the lumen of lysosomes. Like the zinc transporter CDF-2, CUA-1.1 localizes to both the acidified and expansion compartments in excess copper. These results indicate that the same intestinal lysosomes store zinc, copper and manganese. Lysosome remodeling characterized by an increase in volume of the expansion compartment is not specific to zinc but is a more general phenomenon during metal storage in lysosomes.

molecular biology↗

bioRxiv2026

selscape: A Snakemake Workflow for Investigating Genomic Landscapes of Natural Selection

Analyzing natural selection is a central task in evolutionary genomics, yet applying multiple tools across populations in a reproducible and scalable manner is often complicated by heterogeneous input formats, parameter settings, and tool dependencies. Here, we present selscape, a Snakemake workflow that automates end-to-end genome-wide selection analysis--from input preparation and statistic calculation to functional annotation, downstream visualization, and summary reporting. We demonstrate selscape on high-coverage genomes from the 1000 Genomes Project, illustrating how the workflow enables efficient, large-scale analyses and streamlined comparisons across populations. By unifying diverse tools with Snakemake, selscape lowers the barrier to robust genome-wide analyses and provides a flexible framework for future extensions and integration with complementary population genetic analyses.

bioinformatics↗

bioRxiv2026

Nitro Reduction-Based RNA Control and Ultrafast Release

RNA protection and controlled release are critical for both fundamental research and therapeutic applications, yet the development of simple, efficient, and reversible post-synthetic RNA modification strategies remains a significant challenge. Here, we introduce a straight forward approach based on ribose 2'-hydroxyl acylation with a nitro-functionalized carbamate, which acts as a redox-responsive center. This modification selectively inhibits native RNA function while remaining inert to endogenous biogenic reductants and common reducing agents used in biological assays. Upon treatment with low millimolar concentrations of the THDB- BIPY reducing pair, RNA function is rapidly restored on a minute timescale. This methodology is broadly applicable across diverse RNA classes and functional contexts, including synthetic RNA oligomers, fluorogenic RNA aptamers, single-guide RNAs in CRISPR-Cas9 gene-editing systems, and mRNAs in living cells for translation control and RNAi-mediated gene silencing. These results demonstrate the general utility of this approach as a chemically controllable functional switch, providing a versatile toolkit for temporal regulation of RNA activity in both research and biotechnological applications.

biochemistry↗

bioRxiv2026

CsFDL1-CsFTL3 complex represses CsFTL3 via negative feedback to fine-tune flowering in Chrysanthemum seticuspe

In many flowering plants, the transition from vegetative growth to reproductive development is regulated by seasonal changes in photoperiod. Under inductive photoperiods, leaves produce the florigen FT (FLOWERING LOCUS T), which is transported to the shoot apex to promote flowering. The photoperiod is known to have a major effect on the flowering of chrysanthemum. In the perennial short-day (SD) plant Chrysanthemum seticuspe, the expression of CsFTL3 (FT-like gene) does not increase immediately after shifting from long-day (LD) to SD conditions but gradually accumulates under continuous SD conditions, peaking during inflorescence development. However, the underlying mechanism remains elusive. We show that CsFDL1 (an ortholog of FD) and CsFTL3 exhibit a significant inverse expression pattern in leaves during the initial stage of short-day inductions. Furthermore, the expression of CsFTL3 is upregulated in the leaves of CsFDL1-knockdown transgenic lines. CsFDL1 is expressed in leaves and forms a complex with CsFTL3 to recognize several TCGA- and ACGT-containing motifs in the CsFTL3 promoter. The CsFTL3-CsFDL1 complex downregulates CsFTL3 expression, thereby preventing its excessive induction by SD signals and inhibiting precocious floral transition. This study reveals that CsFDL1 acts as a key early repressor in the photoperiodic flowering pathway of chrysanthemum leaf, mediating negative feedback regulation by forming a complex with CsFTL3 to achieve precise temporal control of short-day-dependent flowering responses.

plant biology↗