Biology subjects

Gu, X.

Publications and source records attributed to Gu, X..

At least 19 recordsLinked to original sources

bioRxiv2026

Single-cell multiomic QTL mapping reveals state-dependent genetic regulation and associated gene during cellular senescence

How cellular senescence reshapes inherited regulatory effects across chromatin and transcription, and eventually contribute to non-coding risk loci of complex diseases, remains elusive. We generated single-cell multiome ATAC-RNA profiles from proliferating and replicatively senescent primary HUVECs derived from 100 genotyped donors. Alongside state-resolved eQTL and caQTL mapping, we implemented covariance-aware multivariate QTL mapping to identify chromatin accessibility-expression QTLs (caeQTLs), modeling accessibility and expression as a joint phenotype. Joint analysis recovered moderate, asymmetric and modality-distributed associations missed by single-modality scans, revealed senescence-associated regulatory programs, and prioritized candidate causal variants and effector genes at cardiovascular loci. Fine-mapping, chromatin-state annotation and heritability enrichment, together with independent SNP-to-gene algorithms, provided convergent orthogonal support. Mechanistic dissection revealed that rs2019090 modulates PDGFD expression and endothelial phenotypes through senescence-amplified, allele-specific, HMGA1-associated enhancer-promoter regulation. This study establishes senescence-resolved joint multiomic QTL mapping as a framework for narrowing the missing regulation gap in complex disease genetics.

genetics↗

bioRxiv2026

Single neurons in the human substantia nigra encode social learning signals

Humans are remarkable at adapting to changing norms, yet we know little about how the human brain encodes these social signals at the single neuron level. Here, we recorded the activity of single neurons in the substantia nigra and globus pallidus in neurosurgical participants as they played an iterative ultimatum game versus human and computer avatars. Using computational modeling of behavior, we found that putative dopaminergic units in the substantia nigra tracked the valence of norm prediction errors, with greater encoding during gameplay with human versus computer avatars. Analogous analyses in the globus pallidus, a nucleus adjacent to the substantia nigra, found no significant effect. Our results identify a novel role for the substantia nigra in encoding social learning signals.

neuroscience↗

bioRxiv2026

Hippocampal-cingulate dynamics in the human brain link reinforcement-learning and memory

Reinforcement learning (RL) models describe how reward computations shape our choices, but whether the same computations also shape memory in the human brain is unclear. To address this question, we combined multi-areal intracranial recordings with computational modeling of reward and memory in neurosurgical patients. Patients played a gambling task in which decisions yielded monetary rewards tied to trial-unique images, followed immediately by a recognition test for those images. Model-derived positive reward prediction errors (RPEs) predicted later memory for each image. During feedback, multivariate high-frequency activity revealed the spatiotemporal evolution of RPE representations across distributed prefrontal cortex. During subsequent recognition, however, only anterior cingulate cortex (ACC) transiently reinstated RPE representations, and successful recognition specifically associated with hippocampal reinstatement of these ACC representations. Hippocampal-cingulate theta synchrony scaled with RPE during recognition, alongside hippocampal theta decoding of upcoming memory choices. Thus, the RL computations that guide decision-making also shape memory through hippocampal-cingulate circuit dynamics in the human brain.

neuroscience↗

bioRxiv2026

MiRNA let-7a-5p Ameliorates Pulmonary Fibrosis by Suppressing TGFBR1-Mediated Endothelial-to-Mesenchymal Transition

Background Idiopathic Pulmonary Fibrosis (IPF) is a fatal chronic lung disease with limited therapeutic options. While alveolar epithelial injury and fibroblast activation are well-studied, endothelial-mesenchymal transition (EndoMT) is emerging as a critical pathogenic mechanism. The regulatory role of exosomal miRNAs in pulmonary fibrosis remains unclear. This study investigates serum exosomal miRNAs, particularly let-7a-5p, in modulating EndoMT during the onset of pulmonary fibrosis. Methods Clinical cohorts of IPF patients and healthy controls were enrolled. Serum exosomal miRNAs were profiled, followed by differential expression and functional enrichment analyses. In vitro experiments involved human pulmonary artery endothelial cells (HPAECs) transfected with let-7a-5p mimic or inhibitor. Dual-luciferase reporter assays confirmed the binding between let-7a-5p and TGFBR1. HPAECs were co-cultured with lung epithelial cells to examine paracrine signaling. In vivo studies used a bleomycin-induced mouse model with let-7a-5p agomir administration. Assessments included histopathological staining, hydroxyproline content, Western blot, qPCR, micro-CT, and pulmonary function tests. Results Let-7a-5p was significantly downregulated in serum exosomes from IPF patients, correlating with clinical indicators. Mechanistically, let-7a-5p directly bound the TGFBR1 3'UTR to inhibit its expression. Inhibition of let-7a-5p upregulated -SMA, FN1, smad2/3 phosphorylation, and collagen I, while downregulating CD31 and VE-cadherin. Therapeutically, let-7a-5p mimic reversed bleomycin-induced EndoMT and suppressed epithelial-mesenchymal transition (EMT) via paracrine signaling. Mice administered agomir showed reduced fibrosis, improved lung function, and suppressed TGF-{beta}/Smad signaling. Conclusion Serum exosomal let-7a-5p suppresses pulmonary fibrosis by targeting TGFBR1 to inhibit EndoMT. Its downregulation in IPF patients correlates with disease progression, highlighting its biomarker potential.

molecular biology↗

bioRxiv2026

Urothelial-lineage master transcription factor hub proteomics shows mechanisms impeding urothelial cancer cell differentiation

Urothelial cancer (UC) cells of the luminal subtype exhibit partial, incomplete differentiation towards umbrella cells that line bladder lumen, seen by morphology and gene expression. Differentiation is stalled even though the cells express master transcription factors (MTFs) that drive luminal urothelial differentiation, e.g., FOXA1 and CEBPB, at levels seen in normal differentiated urothelium. We therefore analyzed the FOXA1/CEBPB MTF hub by mass spectrometry. SWI/SNF coactivator complex (CoA) components, e.g., SMARCA4, ARID1A, that read the epigenetic activation mark histone 3 lysine 27 acetylation (H3K27ac) and use ATP-hydrolysis to open chromatin, were the most abundant proteins pulled-down with FOXA1/CEBPB. However, genes for these and other CoA, e.g., CREBBP, EP300 that write H3K27ac, were mutated/deleted in >95% of UCs in clinical series. Also contained in the hub were corepressors (CoR) that erase H3K27ac and close chromatin, e.g., HDAC1, CHD4 - genes for these CoR were recurrently gained in UCs. Chromatin analyses showed H3K27ac-centered remodeling was needed to activate umbrella but not constitutively accessible cell growth/division/housekeeping genes. Restoring ARID1A into ARID1A-mutated UC cells using lentiviral transduction, or inhibiting CoR with siRNA or small molecules, activated umbrella genes and terminated replications. In summary, UC-genesis selects for loss- and gain-of-function of CoA and CoR respectively in the urothelial-lineage MTF hub; small molecule CoR-inhibitors are candidate remedies to renew maturation towards terminal differentiated-fates. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/744501v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@bda7e5org.highwire.dtl.DTLVardef@159ea57org.highwire.dtl.DTLVardef@28132borg.highwire.dtl.DTLVardef@1028bee_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

INSM1 Regulates Neuroendocrine Plasticity and Tumor Progression in Prostate Cancer

AbstractNeuroendocrine prostate cancer (NEPC) is a highly aggressive and therapy-resistant subtype that arises from adenocarcinoma through lineage plasticity; however, the molecular mechanisms driving this transition remain incompletely defined. Insulinoma-associated protein 1 (INSM1), a zinc-finger transcription factor and established neuroendocrine lineage marker, has been implicated in a variety of neuroendocrine malignancies, yet its functional contribution to NEPC progression is not well understood. In this study, we demonstrate that INSM1 is consistently upregulated across NEPC patient tumors and experimental models, including both ASCL1 and NEUROD1 molecular subtypes, as revealed by integrated bulk and single-cell transcriptomic analyses. Functional studies revealed that INSM1 is sufficient to induce and necessary to maintain neuroendocrine lineage programs in prostate cancer, as overexpression promoted and depletion suppressed neuroendocrine-associated transcriptional networks. Mechanistically, pro-neural transcription factors, including ASCL1, NEUROD1, NEUROG3, and MYCN, directly or indirectly activate INSM1 expression, positioning it as a critical downstream effector of neuroendocrine lineage specification. Therapeutically, we identify homo-harringtonine (HHT), an FDA-approved protein synthesis inhibitor, as a potent suppressor of INSM1. HHT selectively reduces viability of INSM1-high NEPC cells at nanomolar concentrations, promotes ubiquitin-mediated degradation of INSM1, and significantly inhibits tumor growth in vivo. Notably, INSM1 depletion further enhances cellular sensitivity to HHT treatment. Collectively, our findings establish INSM1 as a key regulator of neuroendocrine plasticity and a promising therapeutic vulnerability in NEPC, providing a rationale for targeting INSM1 to suppress tumor progression.

cancer biology↗

bioRxiv2026

FLT3-ITD signals for CEBPA and p53 proteolysis by the ubiquitin-proteosome pathway

Internal-tandem-duplication of the receptor tyrosine kinase FLT3 (FLT3-ITD) generates ligand-independent signaling and is highly recurrent in acute myeloid leukemias (AMLs). One way signaling pathways can quickly influence cell fates is by phosphorylating key fate-determining proteins to trigger their proteolysis. We investigated the master transcription factor (MTF) driver of granulo-monocytic lineage-fates, CEBPA, for regulation by this mechanism because we found high CEBPA mRNA but little CEBPA protein in FLT3-ITD versus FLT3-wildtype AML cells, and inhibiting FLT3-ITD signaling with tyrosine kinase inhibitors (TKI) rapidly rescued CEBPA protein. Mass spectrometry analyses of CEBPA and its interactome demonstrated prominent interactions with major ubiquitin-proteosome pathway (UPP) components UHRF1 and USP7. TKI treatments decreased CEBPA and USP7 phosphorylations at serine 21 and serine 18 respectively alongside shifts in CEBPA interactions from degradative ubiquitin-ligase UHRF1 toward protective deubiquitinase USP7. The rescued CEBPA activated granulocytic-differentiation. Supporting that the serine-phosphorylations were phospho-degrons, UPP-inhibitors (bortezomib, MG132) increased phosphorylated and total CEBPA and USP7. The MTF regulator of apoptosis p53 is a known USP7 client, therefore, we also evaluated p53 status: TKIs and UPP-inhibitors stabilized USP7 and p53, triggering apoptosis in addition to granulocytic-differentiation specifically in FLT3-ITD but not FLT3-wildtype AML cells. UPP-inhibitors produced these consequences in TKI-resistant FLT3-ITD AML cells also. These data predicted genetic loss-of-function to CEBPA or TP53 is redundant in the FLT3-ITD context, borne out by mutual exclusivity of the mutations in clinical series. In summary, FLT3-ITD signals for CEBPA and p53 proteolysis to block lineage-maturation and apoptosis, positioning UPP-inhibitors as therapeutic candidates acting downstream of TKIs. KEY POINTSO_LIThe oncoprotein kinase FLT3-ITD signals for CEBPA and p53 proteolysis and hence suppresses lineage-differentiation and apoptosis C_LIO_LIProteosome-inhibitors are candidate remedies to restore CEBPA and p53, acting downstream of presently used FLT3-ITD kinase inhibitors C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=171 SRC="FIGDIR/small/738455v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@f3a2acorg.highwire.dtl.DTLVardef@13cd700org.highwire.dtl.DTLVardef@1475312org.highwire.dtl.DTLVardef@19efbd1_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

IL-21-producing peripheral helper T cells associate with autoimmune bile duct injury in biliary atresia

BackgroundBiliary atresia (BA) is a severe neonatal liver disease characterized by progressive fibrosis and bile duct obliteration. ObjectiveAlthough immune dysregulation is implicated in the pathogenesis of BA, the specific mechanisms driving bile duct injury remain incompletely understood. This study aimed to characterize tertiary lymphoid structures (TLSs) within extrahepatic biliary remnants (EBRs), identify their cellular mediators, and evaluate the therapeutic potential of targeting IL-21 receptor signaling. DesignWe performed integrated bulk RNA sequencing, single-cell RNA sequencing, spatial transcriptomics, multiplex immunohistochemistry, and flow cytometry on clinical samples from BA patients and non-BA cholestatic controls. TLS maturation was assessed by CD23 immunohistochemistry in EBRs from 148 BA patients and correlated with clinical parameters. Anti-IL-21R antibody treatment was evaluated in a rhesus rotavirus-induced BA mouse model, with treatment initiated on day 4 post-infection. ResultsTLSs were identified in BA EBRs with significantly higher prevalence than in matched liver tissues. Mature TLSs containing CD23 germinal centers were associated with elevated serum matrix metalloproteinase-7, more advanced hepatic fibrosis, and localized autoantibody deposition on injured bile ducts. Single-cell profiling revealed expanded CD4+ T peripheral helper (Tph) cells expressing IL-21 and CXCL13 within TLS-containing EBRs. Tph cells were enriched in peripheral blood of BA patients compared to non-BA cholestatic controls (P = 0.0025), and serum IL-21 was significantly elevated (P < 0.0001). Post-infection IL-21R blockade in the mouse model reduced jaundice incidence, improved weight gain, prevented extrahepatic biliary obstruction, and significantly improved long-term survival. ConclusionTLSs in BA extrahepatic biliary remnants harbor expanded Tph cells associated with IL-21-mediated B cell activation and bile duct injury. IL-21R blockade ameliorated disease in a murine BA model, identifying the IL-21/IL-21R axis as a potential therapeutic target warranting further investigation. Key MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSImmune dysregulation contributes to biliary atresia (BA), with documented lymphocyte infiltration and defective B cell tolerance. However, the cellular mechanisms linking local immune activation to bile duct injury are unclear, and the roles of organized lymphoid structures and specific CD4 T cell subsets in orchestrating local humoral responses have not been characterized. What this study addsThis study demonstrates that mature tertiary lymphoid structures in extrahepatic biliary remnants are associated with disease severity markers and localized bile duct injury in BA. We identify T peripheral helper cells as an expanded IL-21-producing CD4 T cell population within these structures, and show that post-infection IL-21 receptor blockade prevents biliary obstruction and improves survival in a murine BA model. How this study might affect research, practice or policyThese findings identify the IL-21/IL-21R signaling axis as a candidate therapeutic target in BA warranting further preclinical and translational investigation. TLS maturation status in biliary remnants and serum autoantibody levels may serve as potential biomarkers of disease severity, meriting prospective evaluation in clinical cohorts.

immunology↗

bioRxiv2026

Retrograde trafficking inhibitors allosterically trap Get3 to block tail-anchored protein biogenesis

Retro-1 and Retro-2 are structurally distinct small molecules that protect cells from diverse toxins and viruses by disrupting retrograde trafficking, yet their mechanism of action has remained elusive. We show that both compounds target Get3, the ATPase chaperone of the guided entry of tail-anchored proteins (GET) pathway, which mediates biogenesis of tail-anchored SNARE proteins required for retrograde transport to the ER membrane. Cryo-electron microscopy reveals that Retro compounds bind a cryptic pocket in Get3, allosterically stabilizing Get3 in a stalled complex with upstream pathway components. Our work uncovers the GET pathway as an unsuspected vulnerability in pathogen entry, provides clear routes toward compound optimization, and establishes stabilization of dynamic protein complexes as a therapeutic strategy.

biochemistry↗

bioRxiv2026

Computational reconstruction of hierarchical cis-regulatory networks reveals synergistic transcription control and disease-associated rewiring

Gene regulation emerges from coordinated interactions among dispersed cis-regulatory elements, yet how these elements integrate into functional regulatory networks and collectively regulate gene transcription remains poorly understood. Here, we present ORIGAMI, a multi-omics, gene-centric deep learning framework that reconstructs functional cis-regulatory networks constrained by transcriptional output. ORIGAMI formulates cis-regulatory modeling as a latent graph inference task, which integrates DNA sequence, epigenomic signals, and three-dimensional chromatin priors to infer denoised regulatory graphs that capture functional interactions rather than structural proximity alone. The inferred regulatory graphs exhibit distinct topological regimes, where hierarchical and modular organization encodes cell-state-specific functional demands and enables synergistic transcriptional control. Furthermore, we show that these regulatory architectures undergo measurable state-dependent rewiring across disease contexts. Finally, ORIGAMI accurately predicts the transcriptional consequences of both cis- and trans-regulatory perturbations and links the rearrangement of regulatory architecture to perturbation response. Together, ORIGAMI advances a network-based view of gene regulation and establishes a foundation for virtual cell modeling of regulatory dynamics.

bioinformatics↗

bioRxiv2026

CHORD: a framework for cross-species single-cell integration across gene, cell and cell-type levels

Quantifying cross-species relationships among cell types from single-cell transcriptomic data can reveal both conserved and divergent patterns of cell-type hierarchies. However, existing cross-species integration methods can be limited in modeling genes beyond orthologs by leveraging cell-type-resolved transcriptional context, or in learning explicit type-level representations. Here we present CHORD, a cross-species integration framework that jointly learns representations of genes, cells and cell types. We demonstrate that CHORD can integrate cross-species single-cell atlases and support cell-type annotation with unknown cell-type detection. In the frog-zebrafish embryogenesis and mammalian motor cortex atlases, CHORD infers cell-type trees that place conserved cell types from different species in relative proximity and summarize hierarchical relationships among cell types. CHORD also supports cross-species comparison of continuous phenotypic variation by placing embryonic cells along an aligned developmental timeline. CHORD further yields gene embeddings that capture orthologous and functional relationships, and gene importance scores linking genes to cell types.

bioinformatics↗

bioRxiv2026

TopicVI: A Knowledge-guided deep interpretable model for resolving context-specific gene programs

Mechanistic insights from single-cell and spatial transcriptomics largely rely on cell clustering, differential expression analysis, and interpretation through prior biological knowledge. However, this approach is often limited by the reliance on curated biological priors that fail to capture context-specific gene programs, particularly in complex disease states. To address this gap, we introduce TopicVI, a deep interpretable model that integrates established biological knowledge with data-driven refinement to discover context-dependent gene programs in single-cell and spatial transcriptomic data. TopicVI jointly infers cell clusters and gene topics using optimal transport to flexibly align prior gene programs with observed data while permitting context-specific refinements. Comprehensive benchmarking demonstrates that TopicVI outperforms existing methods in biological conservation, batch correction, topic coherence, and rare cell identification. TopicVI effectively disentangles multiple sources of biological variation, such as separating anatomy-specific expression patterns from disease-associated signatures in spatial transcriptomics. Applying TopicVI to glioblastoma datasets, we identify gene topics related to cell cycle regulation and EGFR signaling that reveal convergent tumor states across distinct drug perturbations. By integrating prior knowledge with data-driven discovery, TopicVI enables identification of interpretable gene programs that illuminate biological processes and therapeutic mechanisms in complex transcriptomics data.

bioinformatics↗

bioRxiv2026

Novel but stable endosymbionts have contrasting effects on aphid dispersal and plant feeding damage in the cereal pest Diuraphis noxia

Endosymbiotic bacteria can affect many ecological attributes of their insect hosts, including (in herbivorous insects) how insects interact with plants where they feed. This raises the issue of whether deliberate endosymbiont introductions could be used to decrease crop damage caused by insect pests. Here we investigate how transinfecting Rickettsiella viridis and Regiella insecticola endosymbionts into a novel pest aphid host, the Russian wheat aphid (Diuraphis noxia), influences population growth, alate production, dispersal ability and crop damage. Both the Rickettsiella (originating from pea aphids) and Regiella (from green peach aphids) were stably maintained in their new host where they had contrasting effects. Rickettsiella increased the severity of aphid damage on wheat and barley, resulting in greater leaf loss, chlorotic streaking, and higher aphid populations, whereas Regiella reduced aphid population growth and the severity of feeding damage by aphids. Their effects on dispersal morphology also differed: Regiella had no detectable impact on alate incidence, while Rickettsiella consistently suppressed wing formation in small cages, and in larger mesocosms with multiple wheat plants this endosymbiont suppressed dispersal. Endosymbiont-mediated changes in feeding damage did not involve the main plant immune response pathways: transinfected and wild type aphids induced similar levels of jasmonic acid, jasmonic acid-isoleucine, and salicylic acid in plant tissues, even though these plant defenses were strongly activated during aphid feeding. Novel endosymbionts can therefore modulate the severity of plant feeding damage by aphids as well as influencing aphid dispersal. Potential applications in controlling pest D. noxia populations are discussed. Significance statementEndosymbiotic bacteria that live within insect cells can have wide-ranging effects on the reproduction and fitness of their insect hosts in different environments. In herbivorous insects this includes effects on host plant use. Here we test if novel endosymbionts in a pest aphid, the Russian wheat aphid, might be used to decrease crop damage and dispersal. We show that the damage caused to wheat and barley plants from aphid feeding is modulated by novel but stably transmitted introduced endosymbionts. One endosymbiont (Rickettsiella) increased the severity of damage but decreased aphid dispersal, while another (Regiella) decreased damage severity without impacting dispersal. These contrasting effects may be associated with changes in aphid population growth and wing formation but were not linked to key plant immune response pathways. We discuss implications of these findings for using endosymbionts in agricultural pest management. Classification: Applied Biological Sciences, microbiology

microbiology↗

bioRxiv2026

Human claustrum neurons encode uncertainty and prediction errors during aversive learning

Flexible behavior depends on continuous updating of internal models, yet the neural circuits coordinating this process remain poorly understood [1]. The claustrum -- reciprocally connected to nearly the entire neocortex -- is uniquely positioned to influence cortical processing. Here we report single-neuron recordings from the human claustrum during aversive learning [2], with anterior cingulate cortex and amygdala recordings for comparison. Claustrum and anterior cingulate neurons displayed structured, task-related responses. Distinct subpopulations encoded stimulus onset and action-contingent outcomes, with outcome representations diverging between regions. Critically, both regions encoded model-derived latent variables -- uncertainty and prediction error -- but with different temporal profiles: only the anterior cingulate carried uncertainty signals during the intertrial period, while both regions encoded uncertainty and prediction error during the active-avoidance period. The amygdala, by contrast, showed minimal latent-variable modulation. These findings provide evidence that human claustrum neurons track higher-order cognitive variables not directly observable from sensory input, and reveal dissociable roles for the claustrum and anterior cingulate cortex in tracking latent task states.

neuroscience↗

bioRxiv2026

Predicting life-history traits in a stored bean petst beetle Callosobruchus chinensis (Coleoptera: Chrysomelidae: Bruchinae) using machine learning

Life-history traits play an important role in insect population dynamics and ecological processes. The azuki bean beetle Callosobruchus chinensis is a common pest of stored legumes and is also widely used as a model species in ecological and evolutionary research. In this study, we tested whether machine learning models could be used to estimate several traits of C. chinensis, including elytral length, development time and adult lifespan. Experimental data were obtained from laboratory populations. The dataset included biological and environmental variables such as strain, treatment condition, developmental day, sex, temperature, and CO2. Six different machine learning models were tested, including linear regression, random forest, support vector machine (SVM), neural network, gradient boosting and AdaBoost. Model performance was evaluated using cross-validation. The coefficient of determination (R2) and root mean square error (RMSE) were used to measure prediction accuracy. Prediction accuracy differed among traits. Elytral length showed relatively higher predictability than the other traits, while development time was difficult to estimate in most models. Lifespan was easier to predict than the other traits, and the neural network produced one of the highest prediction accuracies among the tested models. Feature importance analysis also showed that factors such as sex and treatment condition contributed to variation in several traits. Machine learning models therefore helped reveal relationships among biological variables and life-history traits in C. chinensis. Combining ecological experiments with machine learning analysis may help improve our understanding of insect traits and may support future studies in insect ecology and pest management.

ecology↗

bioRxiv2026

Large-scale Perturbation of Systems Biology-Derived Genes Reveals Modifiers of HD-associated Transcriptomic Networks and Pathology

In Huntingtons disease (HD), disease-driver genes are broadly expressed, but pathogenic players specific to vulnerable neurons remain poorly defined. Leveraging a previously defined mutant huntingtin (mHtt) CAG-length-associated gene network, we perturbed 115 module hub genes with heterozygous knockout (KO-het) to assess their striatal transcriptomic modifier effects in wildtype and Q140 HD mice. We generated 3,592 striatal RNA-seq datasets, mapped 6,517 perturbagen-responder gene pairs, and uncovered regulators of medium spiny neuron (MSN) identity gene expression and DNA- methylase/demethylase-sensitive genes. We developed a bioinformatic pipeline to rank the perturbations with significant impacts on striatal transcriptome and HD-associated gene networks in wildtype or Q140 mice. KO-het for FoxP1 and Scn4b (two MSN-selective genes) exacerbated, whereas Pdp1 KO-het ameliorated, Q140 striatal pathology. Importantly, knockdown of functionally opposing ion channels, SCN4B and KCNH4, dichotomously affected aggregation and neurodegeneration in reprogrammed HD patient MSNs. Together, our study rigorously evaluated systems biology-derived candidates to identify modifiers of HD-associated molecular networks and pathology, providing an in vivo perturbation- transcriptome resource and highlighting genes involved in MSN excitability, transcription, calcium signaling, and mitochondrial metabolism in HD pathogenesis.

genetics↗

bioRxiv2026

Macrophages regulate meiotic initiation and germ cell clearance in the developing ovary

Tissue-resident macrophages are increasingly recognized for their roles in promoting organogenesis, yet how macrophages are involved in fetal ovarian development remains unclear. In particular, little is known about ovarian macrophage ontogeny and how it relates to germ cell entry into meiosis and establishment of the oocyte reserve. Here we combine temporally-controlled lineage tracing of yolk-sac erythro-myeloid progenitors, fetal HSC-derived progenitors, and postnatal monocytes to map multi-wave seeding and remodeling of ovarian macrophages across fetal and early postnatal life. We identify three major resident subsets defined by MHCII and CSF1R that display distinct expansion kinetics and persistence, and we show that CCR2-dependent monocyte recruitment is required for efficient maturation of postnatal macrophage populations. Functionally, transient or sustained depletion of CSF1R fetal macrophages perturbs ovarian vascular growth and triggers precocious meiotic initiation without overt loss of germ cells, leading to persistent, premature meiotic progression. Extending macrophage depletion into late gestation disrupts perinatal physiological germ cell attrition despite rapid postnatal macrophage repopulation. Together, our findings establish ovarian macrophages as stage-specific regulators that couple immune ontogeny to ovarian morphogenesis and germ cell quality control during establishment of the oocyte reserve. One Sentence SummaryOvarian macrophages are required for the proper timing of germ cell meiotic entry and progression, vascular growth, and for the physiological clearance of germ cells during establishment of the oocyte reserve in perinatal stages.

developmental biology↗

bioRxiv2026

Summarizing RNA Structural Ensembles via Maximum Agreement Secondary Structures

Summarizing a collection P of related RNA secondary structures is a key challenge in applications like evolutionary analysis, alternative fold studies and mRNA vaccine design. This requires both clustering the input structures into similar groups and identifying the core structural motifs on which they agree or differ. Existing methods fail by focusing on only one of these goals: clustering methods do not output shared motifs, while consensus methods overlook the structural diversity present in the collection. Here, we introduce the MO_SCPLOWAXIMUMC_SCPLOW AO_SCPLOWGREEMENTC_SCPLOW SO_SCPLOWECONDARYC_SCPLOW SO_SCPLOWTRUCTURESC_SCPLOW (MASS) problem, which seeks the largest set F of structural features present in P that partition the input structures into a user-specified number{tau} of distinct clusters. We prove that MASS is NP-hard and also establish its equivalence to a constrained binary matrix projection problem. We present an exact integer linear program, an exact combinatorial algorithm, and a scalable beam-search heuristic. Using simulations we demonstrate the performance of these exact algorithms and heuristics relative to baseline methods that focus on either clustering or identifying a single consensus tree. On real data, we demonstrate that MASS identifies conserved scaffolds in conformational datasets, reveals conserved structural motifs in different species within RNA families, and recovers shared structural features among synonymous transcripts encoding the same protein. MASS provides a general and interpretable framework for summarizing RNA structural organization.

molecular biology↗