Biology subjects

Luo, Y.

Publications and source records attributed to Luo, Y..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Mineralized Tissue-Targeting Expression System for Local Control of Gene Expression

Targeted control of gene expression in mineralized tissue would enable the use of nucleic acids to modulate the local microenvironment at diseased sites, ultimately promoting bone regeneration. Piperazine-linked bisphosphonate ionizable lipids provide a facile approach to targeting the transfection of mineralized tissue with lipid nanoparticles (LNPs). Here, we develop a Mineralized Tissue-Targeting Expression System (MiTEX) using bisphosphonate LNPs to locally target mineralized tissues by adsorption to mineral surfaces and bone graft materials. MiTEX demonstrated a significant increase in the adsorption of RNA onto hydroxyapatite substrates, which retained the ability to transfect bone mesenchymal cells via the adsorbed layer of mRNA LNPs. Bone graft scaffolds functionalized by adsorbed Cre mRNA-LNP were implanted to genetically label newly formed bone tissues in vivo. The surface affinity and adsorption of bisphosphonate lipids provided a local reservoir in mineralized tissues, sustaining the in vivo delivery of MiTEX. Furthermore, the targeted delivery of RNA therapeutics was demonstrated using STAT3 siRNA to modulate gene expression and proinflammatory cytokine release in ex vivo periodontal tissues. The design of this new RNA-functionalized delivery platform will promote the development of precision nucleic acid therapeutics for local anti-inflammatory treatments and bone regeneration at mineralized tissue interfaces.

bioengineering↗

bioRxiv2025

Gut metabolite IPA alleviates white matter injury post-ICH by enhancing myelin debris phagocytosis via Stap1 inhibition

BackgroundIntracerebral hemorrhage (ICH) causes neurological dysfunction and white matter injury (WMI) characterized by myelin loss, axonal injury and myelin debris accumulation. Microglia-mediated debris clearance is critical for WMI repair. The microbiota-gut-brain axis plays an essential role in the central nervous system diseases, one of the ways in which gut microbiota affects brain is via producing metabolites. Indole-3-proprionic acid (IPA), a tryptophan-derived metabolite that mainly produced by Clostridium sporogenes, exhibits anti-inflammatory and neuroprotective properties. However, its effect on ICH remains unclear. This study aims to investigate the IPA level after ICH and the therapeutic effects of IPA on neurological deficits and WMI, as well as the potential mechanisms underlying IPA-mediated neuroprotection. MethodsAn ICH model was established using C57BL/6 mice, which then received intragastric IPA (20 mg/kg/day). Fecal abundance of IPA-related genes and IPA levels in feces and plasma were measured by qPCR and UPLC-MS/MS. Behavioral tests, qPCR, and immunofluorescence staining were used to assess neurological function, myelin integrity, and axonal injury. In vitro, BV2 microglia, with or without Stap1 knockdown, were co-cultured with myelin debris to assess IPAs effects on phagocytosis. Additionally, targeted plasma IPA profiling was performed in 30 ICH patients and 30 matched healthy controls. ResultsThe relative abundance of IPA production-related genes and IPA levels in feces and plasma were significantly decreased after ICH and remained low into the chronical phase. After IPA administration, the neurological deficits, myelin loss and axonal injury of mice with ICH were significantly improved. In vitro, IPA increased BV2 microglia myelin debris phagocytosis by inhibiting Stap1 expression. IPA levels were significantly reduced in ICH patients, consistent with ICH mouse model. ConclusionsOur findings demonstrated that the gut microbiota-derived metabolite IPA could facilitate neurological deficits recovery and alleviate WMI, which could be a promising therapeutic strategy to improve ICH prognosis.

neuroscience↗

bioRxiv2025

The emerging contaminant Cl-PFESA/F-53B is toxic to meiotic cell division and reproduction in Arabidopsis thaliana

The emerging contaminant Cl-PFESA/F-53B damages vegetative development in plants and has been evidenced to be toxic to both mitotic and meiotic cells in animals. We have recently reported that F-53B induces nuclei unviability in meristematic cells leading to disrupted root development in Arabidopsis (Arabidopsis thaliana). However, the toxicity of F-53B to reproductive system in plants remains unelucidated. In this study, by using cytogenetic and microscopic approaches, we analyzed embryo and anther development and multiple meiosis processes in Arabidopsis exposed to 50 or 100 M F-53B. We showed that F-53B disrupts embryo development which results in reduced seed setting in Arabidopsis. Histochemical staining of anthers and a live-imaging assay using a reporter line that expresses GFP-tagged Aborted Microspores (AMS), a key regulator of the tapetum, demonstrated that F-53B impairs anther development. Moreover, we showed that F-53B interferes with chromosome segregation and/or distribution and alters microtubule organization during male meiosis. Quantification of the chiasmata and immunolocalization of the Human Enhancer of Invasion 10 (HEI10) protein on diakinesis chromosomes suggested that F-53B reduces crossover rate. Furthermore, F-53B reduced the number of DNA Meiotic Recombinase 1 (DMC1) protein foci on zygotene chromosomes in Arabidopsis wild-type Columbia-0 (Col-0), and it partially promoted meiotic chromosome integrity in Arabidopsis depleted with Ataxia Telangiectasia Mutated (ATM), a central regulator of DNA double-strand break (DSB) repair, which suggested that F-53B reduces meiotic DSB formation. Taken together, our study reveals the toxicity of F-53B to meiotic cells and reproduction in Arabidopsis, which highlights its potential threats to agricultural safety and ecological diversity. HighlightO_LIF-53B impairs embryo and anther development in Arabidopsis. C_LIO_LIF-53B interferes with chromosome segregation and distribution during male meiosis. C_LIO_LIF-53B interferes with meiotic microtubule organization. C_LIO_LIF-53B reduces meiotic crossover formation. C_LIO_LIF-53B reduces DNA double-strand breaks in meiocytes. C_LI

plant biology↗

bioRxiv2025

Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction

Drug-target interaction prediction is an important task in computational drug discovery. To address the limitations of existing graph neural network approaches in propagation depth and robustness, we propose PDDMA-DTI (Physics-Diffusion-Driven Multiscale Aggregation for Drug-Target Interaction Prediction), a physics-inspired, multiscale adaptive aggregation framework. PDDMA-DTI injects a physics-motivated diffusion operator into a heterogeneous drug-target network: global diffusion models cross-modal information propagation via the graph Laplacian, while local diffusion performs neighborhood smoothing in the low-dimensional embedding space. Both processes are solved with the implicit Euler scheme to ensure numerical stability. For each node, we introduce an adaptive stopping rule based on steady-state convergence and a weighted fusion strategy. This strategy leverages hop counts and node degrees to aggregate multi-step diffusion snapshots into a final representation that preserves original features while capturing multi-scale context. To emphasize strong interaction pathways, we further propose a Physical Interaction Summation Enhancement module that augments pairwise interaction features with a linear plus quadratic energy term, thereby amplifying highly correlated drug-target pairs. Extensive experiments on multiple benchmark datasets show that PDDMA-DTI consistently outperforms representative baselines in accuracy and robustness.

bioinformatics↗

bioRxiv2025

An unusual ring pattern in the Rosβ lanthipeptide of the two-component lantibiotic roseocin

Two-component lantibiotics comprise two post-translationally modified peptides that synergistically exert antimicrobial activity. Most known two-component lantibiotics are made up of a structurally conserved -lanthipeptide that binds to the peptidoglycan precursor lipid II and a {beta}-lanthipeptide that is believed to interact with the -peptide-lipid II complex to form pores in the membranes of susceptible bacteria. A few two-component lantibiotics including roseocin do not follow this general scheme and act by different, currently unresolved mechanisms. An important first step in studying this group of lanthipeptides is determination of their chemical structure. Roseocins {beta}-peptide (Ros{beta}) is formed by the RosM lanthipeptide synthetase from the RosA1 precursor peptide. RosM carries out nine dehydrations of Ser and Thr residues to the corresponding dehydroamino acids followed by six Michael-type additions of the thiols of Cys residues to a subset of the dehydroamino acids forming six thioether crosslinks. Sequence alignment with structurally characterized lanthipeptides does not allow prediction of its ring pattern. In this study, Ros{beta} was produced in Escherichia coli and its ring pattern was established by multi-dimensional NMR spectroscopy. The stereochemistry of the lanthionine and methyllanthionine residues was determined by Marfeys analysis with authentic standards. Ros{beta} is shown to have a unique ring pattern amongst previously characterized lanthipeptides. TOC graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/684949v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@125226borg.highwire.dtl.DTLVardef@f6a170org.highwire.dtl.DTLVardef@1e0e57corg.highwire.dtl.DTLVardef@1fa4c8d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Intraspecific sequence variation and complete genomes refine the identification of rapidly evolved regions in humans

Summary Humans exhibit significant phenotypic differences from other great apes, yet pinpointing the underlying genetic changes has been limited by incomplete reference genomes and a reliance on single assemblies to represent a species. We aligned 20 telomere-to-telomere (T2T) assemblies spanning great ape divergence and variation to define 1,596 Consensus HAQERs (consensus human ancestor quickly evolved regions), regions that diverged rapidly between the human-chimpanzee ancestor and an ancestral node of modern humans. Unlike prior HAQER sets, Consensus HAQERs incorporate population variation, reducing the likelihood of intraspecies variation appearing as interspecies divergence. Consensus HAQERs exhibit signatures of elevated mutation rates, ancient positive selection, bivalent regulatory function, are enriched in disease-linked loci, and often emerged in previously inaccessible repetitive DNA. Through multiplex, single-cell enhancer assays, we identify HAQERs as active enhancers in the developing brain and cardiomyocytes, highlighting their potential contributions to human-specific gene regulation across multiple tissues. Highlights[bullet] Telomere-to-telomere alignments of diverse human and great ape genomes identify 1,596 Consensus HAQERs, regions of rapid sequence divergence separating human ancestors from other great apes. [bullet]Consensus HAQERs exhibit signatures of both elevated mutation rates and ancient positive selection. [bullet]HAQERs are enriched in bivalent regulatory elements and disease-linked loci. [bullet]Multiplex, single-cell gene regulatory assays identify HAQERs as enhancers in the developing heart and brain.

genomics↗

bioRxiv2025

Deterministic co-encapsulation of microparticles in droplets via synchronized merging for single-cell genomics

Droplet encapsulation of microparticles such as hydrogel beads and cells is fundamental to high-throughput bioanalytical assays, including single-cell genomics. However, co-encapsulation of multiple particles at defined ratios remains a technical challenge. Here, we present a simple and robust strategy for deterministic co-encapsulation, combining particle-triggered droplet generation with synchronized droplet merging. Close-packed hydrogel particles initiate droplet formation, and the resulting droplets are synchronized and merged within a microfluidic channel, enabling efficient encapsulation of microparticles at user-defined ratios. We systematically characterized the process and demonstrated reliable co-loading of 55 {micro}m and 80 {micro}m hydrogel particles at 1:1 and 2:1 ratios. Using this platform, we developed a single-cell 16S rRNA gene sequencing workflow by co-encapsulating hydrogel capsules containing amplified microbial genomes with barcode beads. Applied to a 1:1 mixture of Escherichia coli and Bacillus subtilis, the method enabled accurate, high-throughput single-cell taxonomic profiling. This co-encapsulation approach offers broad applicability for single-cell genomics, digital assays, and interaction-based studies requiring precise particle pairing.

microbiology↗

bioRxiv2025

SpatialESD: spatial ensemble domain detection in spatial transcriptomics

Spatial transcriptomics (ST) measures gene expression while preserving spatial context within tissues. One of the key tasks in ST analysis is spatial domain detection, which remains challenging due to the complex structure of ST data and the varying performance of individual clustering methods. To address this, we propose SpatialESD, a Spatial EnSemble Domain detection method that integrates results from different spatial domain detection methods to improve spatial domain detection. SpatialESD captures both direct co-occurrence patterns and multiscale indirect relationships between clusters, improving the robustness and accuracy of spatial domain detection. We evaluated SpatialESD on simulated datasets and multiple 10x Visium spatial transcriptomics datasets, including human brain, breast cancer, and ovarian cancer samples. The results show that SpatialESD consistently outperforms individual methods and the existing EnSDD ensemble method in terms of clustering accuracy and stability. Based on the identified domains, we further detected region-specific differentially expressed genes and performed trajectory and cell-cell interaction analyses. These results reveal spatial patterns of gene expression and cellular communication, offering insights into tissue organization and disease mechanisms. Overall, SpatialESD provides a reliable and effective solution for spatial domain detection in ST data and facilitates downstream biological discovery. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=131 SRC="FIGDIR/small/675735v1_ufig1.gif" ALT="Figure 1"> View larger version (39K): org.highwire.dtl.DTLVardef@1344724org.highwire.dtl.DTLVardef@12ab936org.highwire.dtl.DTLVardef@1e59d57org.highwire.dtl.DTLVardef@1bcd55f_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Unfolding Suppression: statistical learning drives suppression through dynamic attentional states modulated by threat

How does statistical learning drive distractor suppression? A central debate in current research concerns whether the underlying mechanism operates proactively or reactively. Here, we propose a Temporal Dynamics of Attentional Suppression (TDAS) hypothesis, successfully reconciling these seemingly contradictory views. Across four visual search experiments, participants faced a probabilistic electric shock when a neutral distractor (Experiments 1a, 1b) or a threat-associated distractor (Experiments 2a, 2b) appeared at a threat-related high-probability location. Trial-averaged results showed faster responses and reduced fixations on distractors, but slower responses and fewer fixations on targets at these locations, consistent with learned distractor suppression. SMART analyses for eye-tracking data further revealed that learned suppression emerged from temporal state transitions: from distractor dominance via attentional limbo states to proactive suppression. Critically, spatial probability gates suppression pathways. At low-probability locations, suppression transitions to limbo states, while at high-probability locations, suppression either unfolds through the full three-state sequence or shifts directly from attentional limbo states to proactive suppression. Furthermore, threat signals accelerated these transitions compared to neutral contexts. Overall, these findings contribute to resolving the ongoing debate about the mechanisms of learned distractor suppression. They also offer a new theoretical perspective by establishing spatiotemporally distributed suppression as a core principle of attentional selection, thereby providing a unifying framework for understanding the dynamic nature of attentional control.

neuroscience↗

bioRxiv2025

DNA-Directed Assembly of Multivalent Lipid Nanoparticles for Targeted T Cell Gene Delivery

Lipid nanoparticles (LNPs) are a powerful emerging tool for in vivo T cell engineering with applications ranging from B cell lymphomas to other cancers and autoimmune diseases. Key challenges in designing these therapeutics include achieving both precise cell targeting and efficient mRNA translation. While single-targeted LNPs have been extensively studied, bispecific LNPs have only been briefly explored. Engagement of multiple T cell receptors offers the opportunity for enhanced mRNA delivery, expression, and T cell targeting. Here, a DNA-tethering method enables rapid modification of lipid nanoparticles with commercial antibodies. Using this strategy, we evaluated a variety of bispecific LNPs for targeted mRNA delivery to T cells both in vitro and in vivo. We identify bispecific formulations that improve targeting and subsequent transfection of T cells in vitro and in vivo relative to monotargeted LNPs. Additionally, we find that targeting molecules can alter LNP biodistribution to the spleen and liver. This fast and efficient approach to assembling antibody-targeted LNPs should enable high-throughput screening of diverse antibody combinations for improved specificity and efficiency of in vivo gene delivery. Significance StatementA major challenge in in vivo gene delivery is achieving both precise targeting and efficient mRNA translation. Multitargeted LNPs offer a potential solution to this challenge; however, their rapid assembly remains difficult, necessitating the development of new methods to construct and evaluate targeted LNPs. Here, we use a DNA-tethering method to enable rapid antibody modification of LNPs and evaluate bispecific formulations for targeted T cell mRNA delivery in vitro and in vivo. We find bispecific LNPs improve T cell targeting and expression compared to single-targeted particles. To the best of our knowledge, this study represents the first systematic screening and comparison of bispecific LNPs. Our method provides a modular approach for identifying effective antibody combinations to enhance in vivo gene delivery that can be customized for different undruggable diseases.

immunology↗

bioRxiv2025

Cross-species optimization of nuclei isolation in plants

Single-cell technologies are transforming plant biology, yet broadly transferable nuclei isolation remains a key bottleneck for snRNA-seq. We developed a reproducible, Percoll-based workflow that is applicable to multiple maize tissues and eight additional plant species. In maize, nuclei from root, stem, leaf, and embryo consistently concentrated at the 80% Percoll interface and exhibited high integrity, with typical recoveries > 50,000 nuclei per sample. For other species, gradient compositions were tuned according to genome size to achieve efficient enrichment and clean suspensions, and yields ranged from 20,000 to 50,000 nuclei per sample. Downstream validation showed that nuclei from special interest maize and Tripsacum generated high-quality 10x Genomics snRNA-seq libraries, as supported by cDNA quality profiles. These results demonstrate the versatility and robustness of the method across species and tissues.

plant biology↗

bioRxiv2025

Developmental expression of risk genes implicates the age of onset for neuropsychiatric disorders

The functional effects of genetic variants associated with complex diseases exhibit pronounced spatiotemporal specificity. Although spatially resolved studies have advanced, their temporal dynamics remain poorly characterized. Here, we present an analytical framework integrating developmental gene expression with genome-wide association studies to decipher age-specific windows during which genetic variants exert their effects and to elucidate underlying mechanisms. Applying this framework to five major neuropsychiatric disorders, we uncover a fundamental principle: the peak incidence of a disease precisely coincides with the developmental window of peak expression of its associated risk genes in the prefrontal cortex. These risk windows are characterized by distinct biological processes; for instance, childhood risk for attention-deficit/hyperactivity disorder aligns with a peak in presynaptic machinery gene expression, whereas late-life risk for Alzheimers disease corresponds to heightened immune-related gene activity. Leveraging this principle of temporal convergence significantly improves the prioritization of disease genes. Our work establishes the developmental basis for the age of onset of complex diseases, providing a temporal roadmap for understanding disease mechanisms and developing age-appropriate therapeutic strategies.

genetics↗

bioRxiv2025

STARNet enables spatially resolved inference of gene regulatory networks from spatial multi-omics data

Biological tissues are composed of distinct microenvironments that spatially orchestrate gene expression and cell identity. However, the regulatory principles governing domain-specific cellular functions remain poorly understood due to the lack of effective methods for mapping gene regulatory networks (GRNs) in situ. To address this gap, we introduce STARNet, a representation learning approach that leverages heterogeneous hypergraph modeling of spatial transcriptomic and epigenomic data to resolve tissue-domain-specific regulatory interactions. By integrating graph neural networks with contrastive learning in a self-supervised framework, STARNet learns unified embeddings that preserve both multi-modal molecular features and anatomical spatial context, enabling accurate and domain-resolved GRN reconstruction within complex tissues. Benchmarking on both simulated and real datasets demonstrates that STARNet achieves state-of-the-art performance. We further demonstrate its broad applicability across diverse biological contexts, including neural development, genetic disease risk, and drug-induced developmental toxicity. In the mouse brain, it delineates region-specific regulatory networks and reconstructs spatiotemporal programs underlying neural stem cell differentiation. In human genetics, it provides a mechanistic link between genotypes and phenotypes by showing how genome-wide association study (GWAS) variants for complex diseases perturb hippocampus-specific GRNs. In developmental toxicology, STARNet reveals that drug-induced disruptions of GRNs in defined embryonic regions underlie tissue-specific vulnerability. Collectively, STARNet offers a powerful and versatile framework for resolving the spatial regulatory logic of complex tissues, providing multi-angle insights into tissue patterning, development, and disease mechanisms.

bioinformatics↗

bioRxiv2025

BACH2 dosage establishes the hierarchy of stemness and finetunes antitumor immunity in CAR T cells

Self-renewing stem-like T cells promote the efficacy of cancer immunotherapy and are a heterogeneous population with sub-lineages demonstrating different degrees of stemness. At the apex of this hierarchy is long-term (LT) stem-like T cells with the highest capacity of persistence, repopulation and response to immune checkpoint inhibitors (ICI). However, the pathway that establishes the hierarchy of stemness in chimeric antigen receptor (CAR) T cells and its role in antitumor efficacy of CAR T cells are unclear. Here, we demonstrate that LT stem-like differentiation and antitumor immunity of CAR T cells are dose-dependently regulated by BACH2. Pre-infusion LT stem-like CAR T cells showed epigenetic activation of BACH2 and superior antitumor response in mice and humans. After clearing tumor in vivo, LT stem-like T cells emerged as a CAR subset that transcriptionally and epigenetically upregulated BACH2 and downregulated TOX. Loss-of-function experiments revealed an essential role of BACH2 in the antitumor response of CAR T cells and the transcriptional program of LT stem-like CAR T cells. In exhaustion-prone GD2 CAR T cells with high tonic signaling, we showed that quantitative control of BACH2 protein level by a small molecule drug finetuned the degree of stemness and exhaustion in CAR T cells. Chemically inducing temporal BACH2 activation during manufacture of GD2 CAR T cells imprinted greater antitumor immunity against solid tumor after infusion. Together, we show that BACH2 dosage establishes the hierarchy of stem-like CAR T cells and can be temporally and tunably controlled in CAR T cells to optimize differentiation and antitumor immunity.

cancer biology↗

bioRxiv2025

Expanding tunable selection in yeast using auxotrophic markers URA3 and TRP1

Auxotrophic markers are fundamental tools in yeast genetics, but their use is traditionally binary (growth or no growth), which limits quantitative analysis. Here we repurpose the classic auxotrophic markers URA3 and TRP1 as tunable selection tools that quantitatively link gene-expression levels to growth outcomes. In uracil-deficient medium (SC-Ura), URA3 yields a positive, semi-quantitative growth response proportional to its expression level. Conversely, under selection with 5-fluoroanthranilic acid (5-FAA), TRP1 shows an inverse relationship between expression and survival: higher TRP1 expression triggers greater 5-FAA toxicity and reduced growth. Using integrative plasmids to vary gene copy number, we tuned expression levels and found that even [~]2-4-fold differences produce distinct growth phenotypes. We also obtained dose-response results correlating marker expression with growth rates. Finally, applying this system to a synthetic mitochondrial mRNA localization scheme, we detected the resulting increase in protein expression via the growth-based readout. By converting traditional binary markers into tunable, quantitative selectors, this platform expands the yeast toolkit for evaluating gene expression differences and synthetic circuit function with simple growth assays.

microbiology↗

bioRxiv2025

Single-cell clonal lineage tracing identifies the transcriptional program controlling the cell fate decisions by neoantigen-specific CD8+ T cells

Neoantigen-specific T cells specifically recognize tumor cells and are critical for cancer immunotherapies. However, the transcriptional program controlling the cell fate decisions by neoantigen-specific T cells is incompletely understood. Here, using joint single-cell transcriptome and TCR profiling, we mapped the clonal expansion and differentiation of neoantigen-specific CD8+ T cells in the tumor and draining lymph node in mouse prostate cancer. Compared to other antitumor CD8+ T cells and bystanders, neoantigen-specific CD8+ tumor-infiltrating lymphocytes (TILs) upregulated gene signatures of T cell activation and exhaustion. In the tumor draining lymph node, we identified TCF1+TOX- TSCM, TCF1+TOX+ TPEX, and TCF1-TOX+ effector-like TEX subsets among neoantigen-specific CD8+ T cells. Clonal tracing analysis of neoantigen-specific CD8+ T cells revealed greater clonal expansion in divergent clones and less expansion in clones biased towards TEX, TPEX, or TSCM. The TPEX subset had greater clonal diversity and likely represented the root of neoantigen-specific CD8+ T cell differentiation, whereas highly clonally expanded effector-like TEX cells were positioned at the branch point where neoantigen-specific clones exited the lymph node and differentiated into TEX TILs. Notably, TSCM differentiation of neoantigen-specific CD8+ clones in the lymph node negatively correlated with exhaustion and clonal expansion of the same clones in the tumor. In addition, the gene signature of neoantigen-specific clones biased toward tumor infiltration relative to lymph node residence predicted a poorer response to immune checkpoint inhibitor. Together, we identified the transcriptional program that controls the cell fate choices by neoantigen-specific CD8+ T cells and correlates with clinical outcomes in cancer patients.

cancer biology↗

bioRxiv2025

Benchmarking RNA velocity methods across 17 independent studies

RNA velocity techniques offer great potential for unveiling trajectories of cell state transitions in different biological contexts. While diverse computational methods have been developed, there is no evidence-based guidelines for best-practice in RNA velocity inference. Here we conducted a benchmark study for 14 existing RNA velocity methods in 17 independent datasets. Many validations were done for the first time. We evaluated the performances of each method by measuring accuracy, stability, and usability. Our data showed no single method exhibited superior performance in all the assessments, and unexpected underperformance was observed in certain cases. Especially, the lack of uniformity in the inference results highlights the necessity to compare and control of multiple methods in a single analysis. Our study revealed current limitations and challenges in the RNA velocity methods and informed the best-practice for future studies.

bioinformatics↗

bioRxiv2025

Distributed control circuits across a brain-and-cord connectome

Just as genomes revolutionized molecular genetics, connectomes (maps of neurons and synapses) are transforming neuroscience. To date, the only species with complete connectomes are worms1-3 and sea squirts4 (103-104 synapses). By contrast, the fruit fly is more complex (108 synaptic connections), with a brain that supports learning and spatial memory5,6 and an intricate ventral nerve cord analogous to the vertebrate spinal cord7-11. Here we report the first densely reconstructed adult fly connectome that unites the brain and ventral nerve cord, and we leverage this resource to investigate principles of neural control. We show that effector neurons (motor neurons, endocrine cells and efferent neurons targeting the viscera) are primarily influenced by sensory neurons in the same body part, forming local feedback loops. These local loops are linked by long-range circuits involving ascending and descending neurons organized into behavior-centric modules. Single ascending and descending neurons are often positioned to influence the voluntary movements of multiple body parts, together with the endocrine cells or visceral organs that support those movements. Brain regions involved in learning and navigation supervise these circuits. These results reveal an architecture that is distributed, parallelized and embodied, reminiscent of distributed control architectures in engineered systems12,13.

neuroscience↗