Biology subjects

Krishnan, A.

Publications and source records attributed to Krishnan, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Bats decouple sonar gaze from steering to resolve sensory conflict

When sensory modalities yield conflicting information, animals must rapidly reassess stimuli to select their actions. We induced auditory-visual conflict in free-flying echolocating Egyptian fruit bats, by fitting animals with prisms that shifted the perceived visual location of a landing perch while echoes returned from its veridical location. Bats that course-corrected within a single goal-directed flight did so by decoupling sonar gaze from steering, to enable rapid reweighting of visual and auditory cues. We designed artificial agents that used Bayesian inference to construct estimates of goal locations in their environment. When competing estimates directed active-sensing behaviors distinctly from steering, agents course-corrected more rapidly. Consistent with this idea, when bats were fit with prisms and earplugs that attenuated auditory localization cues, they were unable to course-correct. Removing prisms produced no systematic after-effects. Our framework suggests that instead of correcting their behavior after failure, animals could efficiently employ active sensing to resolve sensory conflict before failure occurs. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=178 SRC="FIGDIR/small/743555v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@e9374aorg.highwire.dtl.DTLVardef@12d03bforg.highwire.dtl.DTLVardef@5109d2org.highwire.dtl.DTLVardef@5bbb2e_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOCover figure.C_FLOATNO Bat wearing helmet with clear-glasses and tracking markers. Photograph (C) 2026 Nikita M. Finger / Moss Laboratory. C_FIG

neuroscience↗

bioRxiv2026

Large-scale automated detection reveals pervasive sex imbalance in biomedical research

Sex is a critical biological variable that impacts disease risk, progression, and treatment response across virtually every organ system. However, decades of biomedical research have relied primarily on male study subjects, leaving large gaps in our understanding of female-specific disease biology. Quantifying the extent of this imbalance across thousands of disease areas and millions of publicly available biological samples has remained computationally intractable. Here, we present a multimodal computational framework that infers the biological sex of [~]230,000 publicly available human transcriptome samples and links inferred sex labels to disease terms extracted from [~]9,000 associated study records and [~]5,000 publication abstracts to quantify sex imbalance at scale. Applying this approach revealed that the majority of disease terms with the largest research-derived sex imbalance are skewed toward male representation, including areas with no known biological justification for that imbalance. After adjusting for global sex-specific disease prevalence to isolate biologically unjustified imbalance, up to 58% of all disease terms showed male-leaning association. Diseases including glioblastoma, cirrhosis, idiopathic pulmonary fibrosis, and schizophrenia emerged as critically understudied in females despite affecting both sexes comparably. These findings provide a principled, data-driven basis for prioritizing compensatory research efforts and offer a reusable framework for ongoing monitoring of sex representation in the biomedical literature. HighlightsO_LISkewed male and female study subject representation in biomedical research is the result of decades of studies conducted without adequate female representation. C_LIO_LIWe developed an automated, multimodal framework to estimate the sex imbalance across thousands of disease terms using metadata from [~]230,000 transcriptomics samples and their associated [~]9,000 studies and [~]5,000 publications. C_LIO_LIOur approach identifies non-sex-specific disease research areas that have been studied using an unbalanced sex demographic. These areas need compensatory and balanced studies to understand sex differences. C_LI

genomics↗

bioRxiv2026

Language Model Embedding Classifiers Enable Identification of Multiple Sclerosis-Associated BCRs and Repertoires

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease. It affects over 2 million people worldwide but has historically been challenging to diagnose, categorize, and treat. MS has an autoimmune component that involves the production of B-cell receptors (BCRs) and immunoglobulins (Igs) that are associated with disease pathophysiology. We reanalyzed all publicly available RNA sequencing data from MS patients and extracted over 11 million BCR immunoglobulin heavy chain (IGH) sequences obtained from a variety of tissue sources. We developed a new decoder-only BCR DNA embedding model that outperforms state-of-the-art BCR and general-purpose protein language models on sequence embedding tasks. We then trained a language model classifier capable of identifying BCR sequences associated with MS. Using low-dimensional representations of whole repertoire embeddings combined with sequence-disease predictions, we can distinguish MS patient repertoires from healthy, infectious disease, or other autoimmune disease repertoires. Our models also successfully rank known MS-associated myelin-binding IgG sequences relative to controls. These findings provide a methodological foundation for BCR-based MS detection and could facilitate identification and study of disease-associated antibodies from blood. SignificanceAutoimmune diseases are difficult to diagnose and treat. Circulating adaptive immune cells contain accessible information about a patients present and past immune experiences. To better use this information in the context of multiple sclerosis, we extracted a comprehensive dataset of B-cell receptor sequences from archival data, developed a new DNA foundation model to embed these sequences, and applied machine learning methods to classify sequence disease association and patient disease state. These findings will advance our ability to model and predict multiple sclerosis and other diseases.

bioinformatics↗

bioRxiv2026

Targeting CD73-A2aR-Mediated Adenosine Signaling at the Tumor-Immune Interface Overcomes Radioresistance

BackgroundRadiotherapy efficacy is constrained by an immunosuppressive tumor microenvironment (TME) enriched in extracellular adenosine and suppressive myeloid populations that attenuate cytotoxic T-cell responses. The CD73-adenosine-A2a/A2b receptor axis represents a key metabolic immune checkpoint; however, the relative contributions of tumor cell-intrinsic versus host-derived adenosine signaling to radiotherapy response remain incompletely defined. MethodsUsing orthotopic murine breast carcinoma models, we interrogated radiation-induced adenosine dynamics and downstream immune remodeling through quantitative adenosine measurements, bulk RNA sequencing, and multiparameter flow cytometry. Genetically engineered models were employed to dissect the roles of tumor-derived CD73 and host A2a/A2b receptors in regulating radiosensitivity. Therapeutic studies evaluated combinatorial targeting of CD73 and A2a/A2b receptors with radiotherapy and anti-PD-1, followed by comprehensive immune profiling in breast carcinomas. ResultsTumor cell-intrinsic CD73 and host A2A receptor signaling cooperatively drive radioresistance and tumor progression. Radiotherapy induces a rapid surge in intratumoral adenosine, triggering transcriptional and cellular programs consistent with myeloid-mediated immunosuppression and lymphocyte dysfunction. Although T-cell infiltration increases at later time point post-irradiation, effector function remains constrained. Pharmacologic inhibition of CD73 and A2a/A2b receptors partially restores T-cell functionality but is insufficient for durable tumor control as monotherapy. In contrast, concurrent blockade of adenosine signaling during radiotherapy, followed by adjuvant PD-1 inhibition, amplifies adaptive antitumor immunity and significantly enhances tumor control. ConclusionsThese findings define a mechanistic link between radiation-induced adenosine signaling and immune dysfunction in the TME. Targeting the CD73-A2a/A2b axis in combination with radiotherapy and checkpoint blockade represents a rational strategy to overcome radioresistance and improve antitumor immunity. STATEMENT OF SIGNIFICANCEThe tumor and immune cell contributions to adenosine signaling play a central role in shaping the therapeutic outcomes of tumor irradiation. Therapeutic targeting of the adenosine signaling axis improves radiosensitivity and efficacy of checkpoint blockade.

cancer biology↗

bioRxiv2026

Accurate ab initio gene prediction in eukaryotes with Tiberius in multiple clades

BackgroundEukaryotic genome annotation is currently bottlenecked by limitations in the generality, scalability or accuracy of computational methods and fewer than 20% of the genomes available at NCBI Datasets have associated gene annotations. Evidence-based pipelines such as BRAKER3 achieve high accuracy but require substantial extrinsic evidence and compute. Deep learning approaches have recently achieved large improvements in ab initio gene prediction accuracy. The end-to-end deep learning gene predictor Tiberius approaches the accuracy of evidence-based annotation on mammalian genomes without using any extrinsic evidence, but its published models were trained on mammals only, limiting its applicability across eukaryotes. ResultsWe extend Tiberius beyond mammals by training lineage-specific models for Mesan-giospermae, Fungi, Vertebrata, Insecta, Chlorophyta and Bacillariophyta, making the tool applicable to 92% of currently available eukaryotic assemblies. Across a benchmark of 33 species, Tiberius achieved higher exon-, transcript- and gene-level accuracy than the other evaluated ab initio methods, Helixer and ANNEVO, improving gene-level F1 score by 12-37 percentage points over Helixer and by 10-22 percentage points over ANNEVO, while also having the fastest runtimes overall. Compared with BRAKER3, which incorporates RNA-Seq and protein evidence, Tiberius approaches state-of-the-art accuracy in Mesangiospermae, Fungi, Bacillariophyta and Chlorophyta, while being on average 80 times faster when using a GPU. A reimplementation of the Tiberius backend reduced runtime by 31% compared to the previous implementation. Tiberius and its models are also available through a web server, which allows annotation of submitted assemblies without local resources. Furthermore, the Vertebrata model has been applied to annotate 2,948 vertebrate assemblies totalling nearly 6 trillion base pairs. ConclusionsTiberius is transferable well beyond Mammalia and reaches accuracy close to evidence-based annotation in several clades at a small fraction of the compute cost. This makes it a practical choice for highly accurate large-scale genome annotation, particularly when extrinsic evidence is unavailable or annotation throughput is limiting. Availability and implementationCode: https://github.com/Gaius-Augustus/Tiberius, web server: https://bioinf.uni-greifswald.de/tiberius.

bioinformatics↗

bioRxiv2026

Estimation of motion direction and speed using an organic-semiconductor retinal prosthetic in a blind retinae

For a vision system, estimating the speed and direction of movement at the retinal input stage is an essential function for survival in many organisms. Retinal ganglion cells specific to this movement function were identified using multi-electrode array recordings in neonatal chick retina. Motion-evoked "visual streaks" and direction selective responses were observed in chick ganglion cells upon sequential activation as a response to moving bar stimuli. These characteristics were preserved in the sub-retinal prosthetic consisting of a semiconductor polymer film coupled to the blind chick retina which generated spatiotemporal activity patterns resembling those in natural vision. The motion parameters of direction and speed inferred from these recordings demonstrate that polymer-based prostheses can evoke physiologically relevant activity patterns, suggesting their potential to restore motion perception in degenerative retinae.

neuroscience↗

bioRxiv2026

Linking Genetic Risk to Disease-Relevant Cellular States via Metacell-Informed Modeling with ICePop

Genome-wide association studies (GWAS) have implicated thousands of loci in complex diseases, but translating these population-level signals into specific cellular contexts remains a central challenge. Integrating GWAS with single-cell transcriptomics data has enabled systematic identification of disease-relevant cell types, yet existing methods face a fundamental tradeoff: approaches like seismic that optimized for statistical power operate at the annotated cell-type level and miss heterogeneous disease signals concentrated in specific cellular states, while single-cell-resolution approaches like scDRS that capture such heterogeneity often lack sufficient power to detect subtle associations. Here we present ICePop (Informative Cell Populations), a framework that resolves this tradeoff by performing disease-cell type association at metacell resolution, thus achieving statistical power comparable to cell-type-level methods while detecting heterogeneous disease signals within cell types. In simulations against seismic and scDRS, ICePop maintains appropriate false positive rates and demonstrates superior power when disease effects are concentrated in cellular subpopulations. Applied to Tabula Muris across 81 traits and 120 cell types, ICePop identifies 1,684 disease-cell type associations, including the preferential vulnerability of differentiated gut epithelial cells in ulcerative colitis and loss of cell identity in immune-stressed lung capillary endothelial cells underlying their association with lung function. Clustering diseases by metacell association profiles reveals groupings that diverge from genetic risk-based clustering, including separation of blood cell count traits from immune diseases despite shared genetic architecture, reflecting differences in cellular rather than genetic etiology. In autism spectrum disorder, ICePop identifies preferential enrichment of genetic risk in specific enteric neuron subtypes, implicating dysfunction of the enteric nervous system in gastrointestinal comorbidities. ICePops resolution of disease-relevant cell states within annotated cell types enables generation of testable, cell-state-specific hypotheses about disease mechanisms and therapeutic targets.

genomics↗

bioRxiv2026

Platelets Outperform Leukocytes in Transcriptomic Liquid Biopsy Profiling of Myeloproliferative Neoplasms

Myeloproliferative neoplasms (MPNs) are characterized by progressive myelofibrosis that drives morbidity and mortality. Liquid biopsy approaches to noninvasively monitor fibrotic progression remain limited. We performed comparative transcriptomic profiling of CD45-depleted platelet-enriched and CD45+ leukocyte-enriched fractions from matched peripheral blood samples of 76 individuals (27 primary myelofibrosis, 17 polycythemia vera, 14 essential thrombocythemia, 18 healthy controls). Platelet RNA sequencing was performed in 2018-2020 on Illumina HiSeq 4000, while WBC RNA sequencing was conducted in 2023 on Illumina NovaSeq 6000 from cryopreserved CD45+ enriched fractions of specimens obtained at the identical time and from the same blood sample as the platelet RNA. Despite comparable library preparation protocols and higher sequencing depth in WBC samples, platelet transcriptomes exhibited 5.1-fold more differential expression in myelofibrosis (3,453 versus 681 genes, adjusted p<0.05, |log2FC|>1). Platelet signatures were enriched for proteostasis pathways including endoplasmic reticulum stress and unfolded protein response, reflecting megakaryocyte dysfunction in the fibrotic bone marrow niche. WBC signatures predominantly featured immune activation and proliferative pathways, indicating systemic inflammatory responses. Multinomial LASSO classification demonstrated superior performance of platelet-based models for myelofibrosis diagnosis (AUROC 0.85) compared to WBC-based (AUROC 0.77) or clinical models (AUROC 0.59). Combined platelet+WBC models did not improve performance (AUROC 0.80), indicating complementary but non-additive information. These findings establish platelet transcriptomic profiling as a superior noninvasive biomarker platform for monitoring myelofibrosis in MPNs, capturing megakaryocyte-driven fibrogenesis with greater sensitivity than peripheral leukocyte-based approaches. HighlightsUsing matched WBC and platelet RNA-seq from MPN patients, we identify myelofibrosis-associated transcriptomic signatures specifically enriched in platelets. Multinomial LASSO modeling highlights platelet-derived gene expression as a dominant and predictive biomarker of myelofibrosis, outperforming clinical parameters and WBC signatures. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/714941v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@10a388borg.highwire.dtl.DTLVardef@66079org.highwire.dtl.DTLVardef@a7c29eorg.highwire.dtl.DTLVardef@1da1a96_HPS_FORMAT_FIGEXP M_FIG C_FIG

pathology↗

bioRxiv2026

Transcriptomics and mutational analysis to screen immunogenic neoantigen peptides and Patient stratification based on immune subtypes for TNBC

Triple-negative breast cancer (TNBC) is a highly aggressive and heterogeneous subtype with limited therapeutic options. In this study, we performed an integrative analysis of TNBC genomics data, including gene expression, somatic mutations, copy number alterations, survival outcomes, immune profiling, and clustering, to identify potential neoantigens, patient populations suitable for vaccination, and biomarkers for evaluating vaccine efficacy. This Integrated analysis identified POSTN and CAP1 as tumor-specific antigens. Incorporation of TNBC-specific mutations into the screened wild-type antigens led to the identification of three neoantigenic peptides with high potential for vaccine development. Immune subtyping stratified TNBC patients into four distinct subtypes, among which IS1 and IS3 were characterized by poor immune infiltration, lower mutation burden, and unfavorable prognosis, whereas IS2 and IS4 exhibited enhanced immune activity and better clinical outcomes. A vaccine incorporating the identified neoantigen peptides may potentially remodel the immune landscape of immune-cold subtypes (IS1 and IS3), converting them into immune-enriched phenotypes through vaccine-induced immune stimulation. Furthermore, weighted gene co-expression network analysis identified ten immune-related biomarkers from the blue and gray modules that were significantly associated with improved survival in IS2 and IS4. Functional enrichment and protein-protein interaction analyses revealed that hub genes primarily involved in immunoglobulin kappa chains and cytokine/TNF signaling pathways may serve as valuable immune biomarkers for prognostic assessment and monitoring vaccine efficacy.

cancer biology↗

bioRxiv2026

Modeling a Shared Reality of Tractography through Varied Structural Imaging

Though diffusion MRI (dMRI) is the gold standard for white matter tractography, fundamental questions remain about whether captured patterns reflect diffusion-specific phenomena or general structural properties accessible through alternative imaging approaches. This work investigates structural probabilities within the human brain as a complex manifold and examines structural-functional relationships of anatomical bundles to clarify what dMRI specifically captures in white matter architecture. We introduce a framework to extract white matter pathways from FLAIR images without additional subject-specific anatomical context. Using a teacher-student model, we capture systemic information from dMRI-based tractography to guide FLAIR-based tractogram creation. The teacher model trains on dMRI features to generate diffusion tractography, while the student utilizes frozen teacher layers to extract tractography features using only FLAIR input. In our pilot analysis of 14 randomly selected subjects from the Baltimore Longitudinal Study of Aging (BLSA), we performed additional inference on 9 withheld subjects to evaluate robustness. We assessed FLAIR-template generated streamlines using bundle adjacency and Dice coefficient at the voxel level across 39 white matter bundles compared to gold standard diffusion streamlines. Statistical evaluations compared our method against other non-diffusion tractography algorithms using T1-weighted and FLAIR images with subject-specific anatomical context. Results demonstrate our proposed method offers statistically similar performance to other non-diffusion methods when compared to diffusion streamlines These findings suggest that without diffusion data, our method captures unconditional subject-specific prior probabilities of tractography, indicating that tractography patterns may sample from a shared latent space of structural information not unique to any single imaging sequence.

bioengineering↗

bioRxiv2025

Organoid Pharmacotyping of Pancreatic Cancer Enables Functional Precision Oncology and Drug Repurposing

PurposePancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies, with limited benefit from current cytotoxic regimens and poor predictive value of genomics alone. Patient-derived organoids (PDOs) represent a promising platform for functional precision oncology, yet systematic pharmacotyping of genomically annotated PDAC PDOs remains sparse. Experimental DesignWe established a clinically annotated panel of ten treatment-naive PDAC PDOs spanning well-, moderately-, and poorly differentiated tumors. PDOs were evaluated for morphologic and genomic fidelity and screened against 1,813 clinically relevant small molecules in a high-throughput 384-well format. Drug sensitivities were quantified at the compound and drug-family levels and integrated with histologic grade, pathway-level mutational profiles, and available clinical treatment information. ResultsPDOs preserved hallmark tumor features, including glandular organization and subclonal mutational architecture. Pharmacotyping revealed both shared and subtype-specific vulnerabilities. Classical (well/moderately differentiated) PDOs showed enriched mutations in DNA repair, mitotic spindle, and chromatin-regulatory pathways and were preferentially sensitive to topoisomerase inhibitors, microtubule poisons, and HDAC inhibitors. In contrast, basal (poorly differentiated) PDOs displayed coordinated defects in mitochondrial function, vesicle trafficking, and ubiquitin-mediated proteostasis, at the pathway level, that conferred a previously unrecognized vulnerability to cardiac glycosides. Sensitivities to standard PDAC agents were heterogeneous across models, underscoring the limited predictive value of genotype alone and the need for functional drug testing. ConclusionsThis integrated genomic and pharmacologic analysis demonstrates that PDO pharmacotyping identifies biologically grounded, actionable vulnerabilities in PDAC, including novel therapeutic opportunities in basal, chemo-resistant tumors. These findings support PDO-guided functional profiling as a clinically relevant platform for refining drug selection and expanding treatment options for patients with PDAC. SignificancePDAC is dominated by chemoresistance and lacks reliable genomic predictors of therapy response. By integrating high-throughput drug screening with mutation-informed pathway analysis in patient-derived organoids, we identify differentiation-linked therapeutic liabilities, including a previously unrecognized vulnerability to cardiac glycosides in basal PDAC. These results highlight PDO pharmacotyping as a powerful functional complement to genomics for guiding treatment selection in pancreatic cancer.

cancer biology↗

bioRxiv2025

Amphibious Transitions Drive Lineage-Specific Diversification of Olfactory Receptors in Vertebrates

Olfactory receptors (ORs), which mediate chemical detection in vertebrates, constitute a highly dynamic and ecologically responsive gene family. While OR evolution has been well studied in fully terrestrial and aquatic lineages, its dynamics in amphibious vertebrates remain less explored. Species that occupy both aquatic and terrestrial habitats span a broad phylogenetic and ecological range--from amphibians to freshwater-dwelling mammals, semi-aquatic reptiles, and shoreline birds--and are subject to the functional demands of odour detection across two chemically disparate milieus. Here, we analysed OR gene repertoires across 230 vertebrate genomes, including 138 amphibious species. Our results show that OR repertoire expansion is not a uniform feature of terrestrial adaptation but is most pronounced in amphibious lineages, particularly those inhabiting freshwater systems, where chemically variable environments likely impose stronger selective pressures on olfaction. These expansions are primarily driven by lineage-specific expansions and correlate with ecologies that require sensing a wide range of chemical cues. While amphibious marine taxa possess larger OR repertoires than their fully marine relatives, they consistently exhibit fewer ORs than freshwater amphibious vertebrates. More broadly, species that rely on other sensory modalities--such as echolocation, electroreception, or vision--tend to exhibit reduced OR repertoires. Despite this diversity, several amphibious and terrestrial species within the same clade retain a small subset of shared OR genes, reflecting the retention of conserved OR orthologs--potentially those tuned to airborne odorants--across habitat transitions. However, overlap across clades is minimal, reflecting independent evolutionary responses to similar ecological pressures. Overall, our findings highlight amphibious lifestyles as key inflection points in vertebrate olfactory evolution--driving both OR repertoire expansion and divergence through the interplay of habitat complexity, sensory trade-offs, and lineage-specific constraints.

evolutionary biology↗

bioRxiv2025

Genome of the Predatory Volute Melo melo Provides Insights into Adaptive Gene Family Diversification in a Basal Neogastropod Lineage

Neogastropods represent one of the most diverse and ecologically specialized lineages of marine mollusks, yet many of their early-diverging families remain genomically underexplored. Here, we present the first high-contiguity genome of a volutid species, the tropical predatory snail Melo melo, assembled using PacBio HiFi long reads. The final assembly spans 2.29 Gb with high contiguity (N50: 18.6 Mb) and completeness (BUSCO: 92.4%). Phylogenomic analyses place M. melo as an early-branching neogastropod lineage, supporting the basal position of Volutidae within the order. Comparative genomic analyses reveal expansions of gene families associated with digestion and nutrient metabolism (e.g., metallopeptidases), neurotoxicity (conotoxin-like genes), neurotransmission (ion channels), detoxification (cytochrome P450s and ABC transporters), and innate immunity (C1q and LRR-containing proteins), among others. These expansions are consistent with M. melos predatory behavior and adaptation to sediment-rich benthic habitats. Notably, M. melo lacks nacre-related genes but retains several biomineralization-related gene families previously implicated in shell and pearl formation, offering a genomic basis for investigating its distinctive non-nacreous phenotype. Orthology and CAFE analyses further reveal both conserved and lineage-specific dynamics of gene families across the analyzed gastropods. This study fills a key phylogenetic gap in molluscan genomics and establishes Melo melo as a valuable model for understanding the genomic basis of ecological adaptation and trait evolution in basal neogastropods.

genomics↗

bioRxiv2025

Vocal sequences of diverse parrots suggest an important role for note repetition

Sequencing and syntax in complex animal vocal signals have been studied using several mathematical analyses. Commonly, sequences of vocalizations are assumed to follow a first-order Markov process, where each state depends on the state immediately before it. However, more recent computational analyses challenge this assumption, suggesting alternative processes may be important in vocal sequences. Open-ended vocal learners such as parrots possess complex, variable vocal sequences that may be dynamically modified throughout their lives and contain information about group membership and identity. Although this makes them important systems in which to identify general patterns within vocal sequences, parrot vocalizations remain generally understudied compared to passerine birds. Here, we examined vocal sequence structure in six species of parrots (Psittaculidae). We fit various metrics of sequence structure to those generated by multiple simulated processes, including Markov, random, hidden Markov and renewal processes. Two metrics exhibited the best fit to a renewal process (where a note repeats a certain number of times before transitioning to a new note), and two others to Markov processes. Importantly, all analyses were broadly concordant across species, and multiple metrics indicated an elevated probability of note repetition. Reconciling these results, we suggest a general vocal mechanism across the highly variable vocal sequences of parrots, where both note repetition and Markov processes are important. Note repetition patterns could help communicate individual or group identity, as well as social and behavioral context. Our study thus extends a simulation-based approach using diverse metrics to comparatively examine the complex, variable vocal sequences of these open-ended vocal learners.

animal behavior and cognition↗

bioRxiv2025

A sex hormone-BDNF-TrkB axis directs sympathetic innervation in the mouse mammary gland

Stromal-epithelial interactions underlie fundamental tissue morphogenesis in normal development, tissue regeneration and cancer. Peripheral nerves are increasingly implicated as important stromal drivers of normal and malignant epithelial tissue biology. In the mammary gland, epithelial cell fate is highly dependent on stromal cues during distinct stages of postnatal growth which are triggered by ovarian sex hormones estrogen and progesterone. However, the effects of sex hormones on peripheral nerves in the postnatal mammary gland is largely unknown. Here, we uncover extensive changes in peripheral sympathetic innervation in the mammary stromal microenvironment during puberty and pregnancy which are periods of active postnatal mammary epithelial growth. We find that sex hormones induce sympathetic axonal branching through an intricate hormone-epithelial-nerve cross-talk. Specifically, estrogen and progesterone stimulate the expression of brain-derived neurotrophic factor (BDNF) in mammary hormone receptor- expressing luminal epithelial cells which acts on Tropomyosin receptor kinase B (TrkB)- expressing sympathetic nerves to activate BDNF-TrkB signaling. Our findings illustrate a previously unrecognized capacity of hormone-sensing epithelial cells to modulate sympathetic innervation, providing a framework for understanding nerve dynamics during tissue regeneration and cancer.

molecular biology↗

bioRxiv2025

Expanding the Landscape of BREX Diversity: Uncovering Multi-Layered Functional Frameworks and Identification of Novel BREX-Related Defense Systems

Despite extensive scrutiny of BREX systems, several overarching questions persist regarding the functional modalities of individual components and the collective mechanistic framework underlying their defense responses. Using comparative genomics and sequence-structure analyses, we comprehensively map the phyletic distribution and domain-level functional annotations of BREX proteins across all subtypes. Our analysis uncovers numerous previously uncharacterized domains with key functional implications and demonstrates that BrxA- and BrxB-like homologs are universally present across all subtypes, thereby redefining the core machinery of BREX. Our survey strikingly expands the BREX landscape by characterizing three newly defined RM-like systems, which we term BREX-related (BR) systems, and establishes them as new subtypes that share multiple core components with BREX. Furthermore, we identified a novel composite anti-invader system that intriguingly integrates the BREX machinery with components derived from HerA/FtsK-based capture and Dpd defense systems, forming a unique multifaceted defense machinery. Notably, we identify an extensive repertoire of auxiliary effectors recruited alongside the primary effectors across all BREX and BR systems, functioning to reinforce initial restriction responses and counter phage anti-defense mechanisms. Based on these findings, we propose a unified model organized around a multi-modal "sensing-modifying-restricting" functional architecture, defining the fundamental basis of the multi-layered BREX defense systems.

genomics↗

bioRxiv2025

JAK2V617F Myeloproliferative Neoplasms Support Parallel Evolution of Independent Leukemic Clones

Myeloproliferative neoplasms (MPNs) are hematological diseases predominantly driven by the JAK2V617F mutation. Progression from chronic-phase MPN to secondary acute myeloid leukemia (sAML) is a severe complication that dramatically worsens disease prognosis. While progression to sAML is classically linked to MPN clones acquiring additional mutations, the absence of JAK2V617F in some cases of post-MPN sAML cases suggests alternative mechanisms of transformation. Utilizing patient samples and in vivo modeling, we establish that leukemic clones can emerge independently of JAK2-mutant cells and undergo positive selection in the pro-inflammatory MPN environment, leading to parallel disease evolution. Genetic and pharmacological inhibition of IL-12 and TNF mitigates this competitive advantage. Our data establish a new paradigm and show that disease progression in MPN can arise from parallel acute myeloid leukemia (pAML) clones.

cancer biology↗

bioRxiv2025

JARID2 Inhibition Reprograms Human Hematopoietic Progenitor Cells To Enhance Bone Marrow Transplantation

Hematopoietic stem cell transplantation is a common treatment for many blood disorders and can be a life-saving therapy for patients with leukemias, lymphomas and multiple myeloma. Umbilical cord blood (UCB) serves as a valuable source of hematopoietic stem and progenitor cells (HSPCs) for transplantation, particularly for patients lacking a matched donor. However, the limited number of repopulating cells in UCB units restricts its clinical utility. Our prior studies showed that genetic deletion of the polycomb repressive complex 2 (PRC2) co-factor Jarid2 in mouse multipotent progenitors (MPPs) conveyed ectopic self-renewal capacity. Here, we hypothesized that the function of human HSPCs could be enhanced through JARID2 inhibition. In this study, we demonstrate that both constitutive and transient knockdown of JARID2 increases the number and enhances the functionality of human HSPCs both in vitro and in vivo. This phenotype was distinct from inhibition of EZH2 in UCB cells, suggesting the mechanism was independent of PRC2 co-factor activity of JARID2. Mechanistically, JARID2 knockdown promotes a quiescent, long-term self-renewal gene expression program governed by upregulating STAT1 and characterized by an MHC class II immunophenotype. Analogous to mice, these mechanisms conferred HSC-like potential to human MPPs in vivo. Taken together, these findings highlight JARID2 inhibition as a novel and reversible approach to expand functional UCB-derived HSPCs ex vivo, potentially improving access to stem cell transplantation for a wider patient population. One Sentence SummaryGenetic inhibition of JARID2 enhances repopulating activity of human hematopoietic stem and progenitor cells in vivo via STAT1 upregulation.

developmental biology↗