Biology subjects

Mishra, S.

Publications and source records attributed to Mishra, S..

At least 19 recordsLinked to original sources

bioRxiv2026

WarpDemuX-custom - Multiplexed sequence-specific direct RNA sequencing

Nanopore direct RNA sequencing has emerged as a powerful technology for studying RNA and modifications at single-molecule resolution. Although originally developed for polyadenylated RNAs, protocol adaptations have extended its application to non-polyadenylated RNA species, including tRNAs and rRNAs. However, the lack of open and flexible (de)multiplexing solutions remains a limitation for large-scale sequencing studies. Existing community-driven approaches enable multiplexing of polyadenylated RNAs and, more recently, tRNAs, but do not fully address the challenges of targeted sequence-specific Nanopore sequencing of non-polyadenylated RNAs. Here, we present an improved sequence-specific direct RNA sequencing protocol for ribosomal RNAs, achieving enhanced capture and longer read lengths as demonstrated for human 28S rRNA. We complement this protocol with an expanded WarpDemuX software toolbox for flexible sequence-specific (de)multiplexing. We validate the approach using human cell lines carrying knockouts of different C/D box snoRNAs involved in site-specific 2'-O-ribose methylation of 28S rRNA. Our results demonstrate efficient multiplexed detection of sequence-specific RNA molecules and associated modification changes. While established here using rRNA, we validate our approach on another panel of non-polyadenylated RNA species, providing an open and scalable framework for targeted direct RNA sequencing and RNA modification analysis

bioinformatics↗

bioRxiv2026

Identification of Novel Inhibitors of JEV RdRp as Potent Antiviral Drugs: Targeting NS5-NS3 Protein Interaction

Japanese Encephalitis Virus (JEV) belongs to the Flavivirus family, and the RNA dependent RNA polymerase (RdRp) domain located at the C terminus of non structural protein 5 (NS5) regulates de novo viral genome synthesis. The conserved priming loop inserted in the thumb domain of RDRP initiates de novo genome synthesis. Interestingly, the reported replication process initiates with an interaction between NS5 (methyltransferase/RDRP) and NS3 (protease/helicase), and inhibiting this interaction directly correlates with the inhibition of viral replication. The function of the priming loop in the context of the NS5 NS3 interaction is not yet known. In this study, we studied the priming loop function in the NS5 NS3 interaction and viral replication. Using a structure based drug design approach, we screened the Maybridge compound library against the RdRp priming loop and identified 15 candidate compounds based on binding energy. Among them, DSHS00151 showed significant dose dependent inhibition of the NS5 NS3 interaction with an IC50 of 3.5 micromolar in the mammalian two hybrid assay, inhibited viral infectivity with an IC50 of 2.54 micromolar, and reduced viral RNA load with an IC50 of 2.9 micromolar, compared to CD10712. Molecular Dynamics (MD) simulations revealed that DSHS00151 exhibits stronger and more stable binding with the priming loop residues (790 to 812) compared to CD10712. The molecular mechanism suggested by the docking of the NS5 and NS3 proteins showed that the priming loop tends to rotate toward the NS3 protein to stabilize the complex, and compound binding restricts this loop rotation, thus compromising the stability of the NS5 and NS3 complex and affecting viral replication. Overall, our study validated the function of the NS5 priming loop as an allosteric site, and compounds binding to this allosteric site belong to the Non Nucleoside Reverse Transcriptase Inhibitors (NNRTI) class of inhibitors, which disrupt the NS5 and NS3 interaction and could be developed as novel anti JEV therapeutics.

pathology↗

bioRxiv2026

Identification of novel HDAC11 inhibitors: In silico & in vitro studies

Histone deacetylases (HDACs) are pivotal epigenetic regulators that modulate diverse cellular pathways by removing acetyl groups from lysine residues on both histone and non-histone proteins. Histone deacetylase 11 (HDAC11), the sole member of class IV HDACs, exhibits both deacetylation and fatty acid deacylation activities. Accumulating evidence implicates HDAC11 as a key epigenetic regulator of fundamental cellular processes, including metabolism, immune responses, and tissue development. Dysregulation of HDAC11 activity has been associated with inflammatory diseases, metabolic disorders, neurodegenerative conditions, and cancer, highlighting its potential as a therapeutic target. Although several HDAC11-specific inhibitors have been identified, none have progressed to clinical development. In this study, we aimed to discover HDAC11-selective inhibitors by integrating in silico and in vitro validation approaches. Homology modelling of the HDAC11 structure was conducted, followed by model validation, structure-based virtual screening, molecular dynamics (MD) simulations, and binding free energy calculations. We identified and validated three lead compounds and their intermediates using biochemical and cell-based assays. Fluorescence-based and HPLC-based enzymatic assays demonstrated potent inhibition of both the deacetylase and deacylase activities of HDAC11, with Inhibitor 6 and Inhibitor 3 exhibiting the strongest effects among the six compounds tested. Further, a decrease in lipid accumulation, reduced stability of the HDAC11 substrate SHMT2, as determined by immunoblot analysis and decreased cell viability, as assessed by MTT assay, confirmed HDAC11 inhibition in cellular models. The study shows that new HDAC11 inhibitors significantly reduce the viability of breast cancer cells and induce apoptosis; inhibitor 6, in particular, showed high potency, similar to the reference compound SIS-17. Flow cytometry showed that treated MDA-MB-231 cells exhibited cell-cycle arrest and increased apoptosis, a finding further confirmed by Annexin V/PI staining. Molecular analysis showed that BAX increased while BCL2 decreased, indicating that apoptotic pathways were activated in novel compound-treated MDA-MB-231 cells. The results suggest that inhibiting HDAC11 is an effective way to induce cancer cell death and provide a basis for further assessment of these compounds as potential treatments for breast cancer. Collectively, this study identifies novel zinc-chelating HDAC11 inhibitors containing a nitro-sp2 group, providing promising candidates for further therapeutic development.

bioinformatics↗

bioRxiv2026

Longitudinal whole transcriptomic profiling of live cells through domain adaptation

Tracking transcriptomic profiles of cells over time in response to developmental cues and environmental stimuli can reveal critical insights into the fundamental mechanisms of development and disease. However, longitudinal molecular profiling at the global transcriptome level remains a major challenge, as RNA sequencing fundamentally alters or destroys cells. To overcome these limitations, we developed PENNE, a deep-learning framework that infers whole-transcriptomic profiles directly from live-cell images. Using gated attention mechanisms, PENNE trains on spatial transcriptomic datasets to align morphological features with gene expression. To enable inferences from images, our model performs domain adaptation to eliminate discrepancies between stained and unstained tissue images, effectively transferring molecular information from tissue sections to live-cell imaging. PENNE accurately identifies cell-type-specific and radiation-response markers via imputed expression. Furthermore, using only live-cell images stained with a G2/M cell cycle marker, our model captures temporal gene dynamics, evidenced by strong correlations between predicted expression and both ground-truth cellular confluency and cell-cycle progression. By bridging the gap between data-rich spatial transcriptomics and the practicality of live-cell imaging, PENNE provides a powerful new framework for monitoring molecular temporal dynamics directly through morphological information. This approach enables a paradigm-shifting workflow, fusing transcriptome-wide data with live-cell microscopy to fuel the discovery of novel gene programs via scalable, non-invasive, real-time interrogation of cellular states.

bioinformatics↗

bioRxiv2026

Germline BRCA1 Mutation Deregulates Irradiation-Induced Cell Cycle Checkpoints in Human Mammary Luminal Progenitors

Mammary ductal tree comprises two epithelial lineages, basal and luminal, which harbour stem and progenitor cell subsets essential to breast physiology and are cancer-initiating precursors. Dysregulated cellular stress response is an early event in tumorigenesis, yet lineage-rooted study of primary breast epithelium pertinent to familial mutation carriers is limited. Here, we establish a lineage-resolved monolayer culture system that enables propagation of primary human mammary epithelial populations while preserving lineage identity across passages. We identify intrinsically distinct cell cycle response of luminal progenitors and basal cells to irradiation stress where the former engages both G1/S and G2/M checkpoints to achieve cell cycle arrest and the latter relies on the G2/M checkpoint. These lineage distinctions are diminished in germline BRCA1 mutation carriers with an attenuated G1/S checkpoint in luminal progenitors. Paired transcriptomic-proteomic profiling of acute irradiation response uncovers BRCA1+/- luminal progenitor population with sustained AKT-mTOR signaling and compromised cell cycle arrest marking an early deviation in the stress response of these purported cells-of-origin of aggressive breast cancers known to arise in BRCA1 germline mutation carriers. Our study provides a functional framework for determining critical events in the expansion of genomically altered mammary epithelial cells in the high-risk breast to enable future preventive interventions.

cell biology↗

bioRxiv2026

How Bias Shapes the Leaderboard: Scoring Function Performance Under Scrutiny

Structure-based scoring functions leveraging machine learning have recently demonstrated superior performance over classical scoring functions, particularly on virtual screening benchmarks. However, due to the fundamental differences between their underlying model principles and architectures, it remains unclear to what extent performance stems from an understanding of molecular binding or from exploitation of systemic biases. Thus, disentangling the factors underlying benchmark performance is essential for determining whether a scoring function will generalize to novel chemical space and succeed in prospective drug discovery. To address this need, we present a case study investigating the nature and impact of systemic biases on benchmark comparisons between different scoring function paradigms. By systematically analyzing the evaluation workflows of prominent models, we reveal pocket bias, a form of spatial coordinate frame leakage arising from static binding pocket extraction, which artificially inflates benchmark performance. To progressively eliminate these sources of bias, we benchmarked two selected graph neural network scoring functions against two minmalist machine learning models and a classical scoring function under four increasingly stringent evaluation levels, successively removing pocket bias, reducing structural data leakage, and finally evaluating on out-of-distribution (OOD) protein targets. Upon removal of pocket bias and structural data leakage, the performance of all machine learning models dropped substantially. When evaluated on out-of-distribution protein families, the classical baseline AutoDock Vina outperformed the machine learning models in five of seven virtual screening tasks and dominated the docking power evaluation. Our findings indicate that benchmark performance can be heavily shaped by evaluation design and dataset artifacts, potentially overshadowing algorithmic improvements. While the tested machine learning models remain heavily dependent on encountering familiar data distributions to achieve competitive results, AutoDock Vina demonstrated superior generalization capacity on OOD targets. This work underscores the critical need for rigorous, artifact-free benchmarking protocols to guide the development of truly prospective machine learning models for virtual screening.

bioinformatics↗

bioRxiv2026

Multiscale active transport driven by gravitactic bioconvection promotes resilience in algal blooms

Algal blooms are frequently dominated by motile species1,2 whose vertical migration enhances resource acquisition and bloom development3,4. Yet bloom conditions present a paradox: high cell densities intensify nutrient depletion5 and self-shading6, making individual swimming increasingly costly under severe resource limitation. How motile blooms persist and remain resilient under such stress remains unresolved7, particularly as climate-driven warming strengthens stratification and resource scarcity8,9. Here we show that the red-tide-forming phytoplankton Heterosigma akashiwo overcomes bloom-induced constraints through bioconvection, a self-generated active flow that emerges above a critical cell density (>1.5x105 cells/ml). Using a custom ocean-on-chip platform that recapitulates bloom-relevant constraints, we identify an optimal synergy of cell concentration, swimming speed and gravitactic stability that promotes the formation of persistent bioconvective plumes. At constant cell density, plume onset is governed by two phenotypic traits-- vertical swimming velocity and reorientation time--demonstrating that collective transport is governed by the biophysical traits of single cells. We show that bioconvection drives ecologically relevant multiscale transport, enhancing exchange of molecules and micro-cargo across stratified interfaces, mimicking transport of nutrients, extracellular vesicles10 and co-existing species in a bloom environment11. By enabling cells to hitch a hike on self-generated flows when active propulsion becomes energetically prohibitive, bioconvection-mediated transport improves nutrient delivery, restores photosynthetic performance, reverses lipid accumulation associated with nutrient-stress, and facilitates recovery of cellular motility to ultimately mitigate resource limitations. Our findings identify bioconvection as a population-level adaptive mechanism that sustains algal blooms, and reveal a previously unrecognised role of collective microbial motion in bloom persistence under ecological stresses. One sentence summarySelf-organised bioconvection drives multiscale transport and resilience in algal blooms.

ecology↗

bioRxiv2026

New approaches to detecting and characterizing introgression in large species trees

Many current phylogeny-based methods to detect introgression use samples of species-quartets to detect asymmetries in gene tree frequencies. While this has proven to be an accurate and robust approach, applying it to larger species trees often means having to test dozens to hundreds of quartets across a tree. Furthermore, any single introgression event can have effects on multiple quartets--with no principled way to determine the number of unique events from a set of quartets--and the direction of introgression cannot always be determined from quartet comparisons alone. Here, we present a new approach to detecting introgression using the frequency with which more distantly related clades are attached to one another among a set of gene trees. Testing for introgression between pairs of branches is straightforward using these discordant attachment frequencies. We further show that the direction of introgression can be inferred between any pair of branches separated by at least two internal branches of the species tree, and that theoretical expectations of gene tree frequencies under introgression can be used to accurately determine the number of independent times genes have been exchanged. Application of these methods to data from cichlids and Drosophila demonstrate the power of the new approaches. The DAFT software package is available from: https://github.com/smishra677/DAFT/

evolutionary biology↗

bioRxiv2026

Dual lineages of Langerhans cells cooperate to restore the immune barrier after skin injury

Langerhans cells (LCs) are key immune sentinels of the epidermis. How this network reorganizes to safeguard epidermal immunity after injury has remained unclear. Here, we uncover a previously unrecognized two-lineage program of LC repopulation during wound repair. Classically, tissue-resident embryonically derived LCs (eLCs) migrate to lymph nodes in response to antigens. In contrast, we find that injury triggers nearby eLCs to migrate into wounds, providing immediate coverage. In parallel, circulating monocytes infiltrate the skin and differentiate into long-lived monocyte-derived LCs (mLCs) that integrate stably into the network. We identify the chemokine receptor CXCR2 as a novel regulator of eLC migration into wounds, distinct from the CXCR4/CCR7 pathways mediating LC egress to lymph nodes. Pharmacological inhibition of CXCR2 impairs directional eLC migration and is accompanied by increased mLC infiltration, preserving immune barrier density. These findings reveal a coordinated and flexible two-lineage repair program that ensures robust restoration of epidermal immunity.

cell biology↗

bioRxiv2026

Efficient and Robust Genomic DNA Isolation and Next-Generation Sequencing Library Preparation from Recalcitrant Wild Grape Species

This protocol details the extraction of high-molecular-weight genomic DNA from grapevine tissues (wild and cultivated Vitis spp., including pathogen-infected samples) and the subsequent preparation of Illumina(R) whole-genome sequencing libraries using bead-bound Tn5 transposase. It is designed to overcome challenges from polyphenolic compounds and secondary metabolites in wild plants, providing a cost-effective workflow for large-scale population genomics. It includes recipes for buffers, incubation times, critical notes, and troubleshooting tips to maximize yield and library quality. Although designed for the grapevine DNA, this protocol is potentially applicable to other similar wild plant species HighlightsO_LIOptimized CTAB-PTB DNA extraction protocol for field-collected wild plant tissues. C_LIO_LIEffective removal of polyphenols and secondary metabolites associated with DNA using PTB. C_LIO_LICost-effective Illumina DNA Prep library preparation using bead-bound Tn5 transposase (Tagmentation). C_LIO_LIScalable workflow suitable for large-scale population genomics in Vitis species. C_LIO_LIValidated method for high-molecular-weight DNA and high-quality sequencing data. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=195 SRC="FIGDIR/small/713680v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@b637d4org.highwire.dtl.DTLVardef@10b563aorg.highwire.dtl.DTLVardef@14a32caorg.highwire.dtl.DTLVardef@4c9577_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

Paired CRISPR screens identify mitochondrial metabolism and UBE2H as aneuploid-specific dependencies in human cancer cell lines

Aneuploidy is a hallmark of cancer and imposes widespread cellular stress, including proteotoxicity, transcriptional dysregulation, and increased metabolic demand. Although these stresses are predicted to create therapeutic vulnerabilities, the genetic dependencies of aneuploid cells remain incompletely characterized. Here, we performed paired CRISPR loss-of-function screens in isogenic aneuploid and near-euploid cancer cell line models to systematically identify aneuploidy-specific dependencies. Seven genome-wide paired screens identified ribosomes, rRNA processing, spliceosome-mediated RNA processing, proteasome subunits, and mitochondrial metabolism as top aneuploid-specific dependency gene groups. To identify therapeutically targetable aneuploid dependencies, we performed 18 additional paired CRISPR screens using a focused druggable genome library. This analysis identified the ubiquitin-conjugating enzyme UBE2H as a top aneuploid-selective dependency. Functional validation confirmed aneuploid cell dependency on UBE2H, and mechanistic analyses linked UBE2H to mitochondrial protein abundance, suggesting a role in maintaining mitochondrial proteostasis under aneuploid stress. Together, these findings define core cellular systems that support the viability of aneuploid cells and identify UBE2H as a potential therapeutic vulnerability connecting ubiquitin signaling to mitochondrial homeostasis.

cancer biology↗

bioRxiv2026

Multi-omic profiling of human antibody-secreting cells reveals diverse subsets sustain durable humoral immunity

Antibody-secreting cells (ASCs) provide humoral immunity that can mediate lifelong protection against pathogens. Current classifications cannot delineate the heterogenous functionalities, tissue residencies, and lifespans of human ASC subsets, impeding clinical translation. We applied multi-omic sequencing, spatial proteomics, and functional assays to discover and characterize human bone marrow (BM) ASC subsets. We identified two peripheral subsets (ASCp) also present in blood and three BM-resident subsets (ASCr), comprising a maturation continuum associated with increased mitochondrial networking, diminished antibody secretion, differential transcription factor motif accessibility, and preferential co-localization in homotypic niches. CD19+9+ASCr and CD19-ASCr exhibited poor recovery years after BM transplantation, indicating a strong dependence on supportive niches. Childhood vaccine antigens were recognized by long-lived ASCr subsets in adults and by immature HLA-DR+ASCp, implying ASCs can differentiate without recent antigen exposure. Our results provide new insights into ASC identity, maturation, and longevity and a generalizable framework for study and manipulation of human ASCs.

immunology↗

bioRxiv2026

Molecular basis of promiscuous chemokine-engagement by the Duffy antigen receptor

The Duffy blood group antigen, encoded by a seven transmembrane protein known as Duffy Antigen Receptor for Chemokines (DARC), or Atypical Chemokine Receptor 1 (ACKR1), serves as a key receptor for the malarial parasite, Plasmodium vivax, on erythrocytes. DARC exhibits remarkable functional divergence compared to prototypical chemokine receptors and other G protein-coupled receptors (GPCRs) as it does not engage canonical signal-transducers such as G-proteins, GPCR regulatory kinases (GRKs), and {beta}-arrestins. DARC is a highly promiscuous receptor interacting with several homeostatic and inflammatory C-C and C-X-C subtype chemokines, and similar to other chemokine receptors, these interactions are modulated by post-translational tyrosine sulfation in the N-terminus. A single nucleotide polymorphism in DARC leading to Gly42Asp substitution forms the basis for Fya vs. Fyb Duffy blood group antigen classification with differential impact on Plasmodium vivax infection and cancer progression. However, the molecular basis of promiscuous chemokine-binding by DARC and the modulation by receptor sulfation and Fya/Fyb allelic variation remains unclear. Here, we design a sortase-mediated chemical-ligation strategy to generate purified DARC with naturally-occurring tyrosine sulfation at the N-terminus, and determine high-resolution cryo-EM structures in complex with a C-C type chemokine, CCL7, and a C-X-C type chemokine, CXCL8. We observe that similar to CCL7, CXCL8 engages with DARC primarily through the N-terminus of the receptor, which is in stark contrast with the two-site binding mechanism displayed by other chemokine receptors. Interestingly, the E-L-R motif in CXCL8 engages a pseudo-R-D motif in DARC leading to superficial engagement unlike CXCR2, a prototypical chemokine receptor sharing the same agonist. Moreover, tyrosine sulfation and Fyb allelic variation leads to a repositioning of the receptor N-terminus on the core domain of CXCL8, resulting in distinct interaction network imparting greater binding affinity. Taken together, our study presents novel insights into promiscuous chemokine-binding to DARC, tyrosine sulfation-mediated fine-tuning of chemokine engagement, and a generalizable sortase-mediated chemical-ligation platform applicable to other chemokine receptors.

biochemistry↗

bioRxiv2026

Lessons from the equator: a window on the future of vibriosis in a warming Earth

Vibrios are important aquatic human pathogens, causing gastroenteritis, wound infections, and cholera. Vibriosis (non-cholera infection) has been increasing in temperate climates due to correlation between Vibrio abundance and water temperature. However, how warming oceans differentially influence various Vibrio species, and whether incidence is higher in tropical regions, remains understudied. We assembled the first comprehensive dataset of culture-confirmed vibriosis cases outside a temperate climate from equatorial Singapore. Comparison to cases from the detailed United States (US) CDC COVIS system revealed that vibriosis incidence is over two times higher in Singapore than the United States. Causative species also differ markedly, with Vibrio fluvialis and non-toxigenic Vibrio cholerae dominating in Singapore (>40%) but are much less prominent in the United States (<15%). Singapore cases have remained stable in the last decade, while US incidence is rising rapidly, especially for V. fluvialis and V. cholerae (13% and 17% per year). Differences in causative species in Singapore and the United States suggest ecological factors may shape infection dynamics, with some species benefitting more from warming oceans, raising their equatorial prominence. Incidence is stable in Singapore, likely due to slower warming of waters near the equator. In contrast, vibriosis in the United States will likely continue to increase steadily, with changing species composition, likely becoming tropicalized.

microbiology↗

bioRxiv2026

Testing for gene-environment (GxE) interaction using p-value aggregation identifies many GxE loci

Genome-wide gene-environment (GxE) interaction studies have seen limited success in detecting reliable GxE signals. A standard genome-wide GxE scan assumes a single genetic mode of inheritance, such as an additive model. It can lead to reduced statistical power when the true genetic model is non-additive, such as a recessive model. We propose a robust GxE testing approach that uses Cauchy p-value aggregation. It combines the p-values from GxE tests based on the additive, dominant, and recessive genetic models. Using extensive simulation studies, we demonstrate that the p-value combination strategy offers a robust and powerful approach to identifying GxE interactions regardless of the underlying genetic model. The method is substantially more powerful than the additive model when the true genetic model is recessive. It is also more powerful than the general two-degree-of-freedom genotypic test for GxE interaction. We apply our approach to analyze GxE interactions in the UK Biobank data across several combinations of phenotypes and environmental factors. For glycated hemoglobin (HbA1c) level, treating cumulative smoking exposure as the lifestyle factor, our approach identified 82 independent GxE loci while controlling FDR at 5%. The GxE test based on the additive genetic model detected 24 loci. For type 2 diabetes with sleep duration as a lifestyle factor, the proposed approach detected 563 independent GxE loci at 5% FDR, substantially exceeding the number of discoveries by the other approaches.

genomics↗

bioRxiv2026

Deciphering the Therapeutic Potential of Resveratrol Against Pancreatic Cancer Through Network Pharmacology

Resveratrol, a naturally occurring polyphenol, exhibits anticancer, anti-inflammatory, and antioxidant properties. However, its molecular mechanisms in pancreatic cancer remain incompletely understood, necessitating integrative approaches such as network pharmacology and molecular docking. Potential resveratrol targets were identified using Swiss Target Prediction, while pancreatic cancer-related genes were retrieved from GeneCards and NCBI Gene databases. Overlapping targets were obtained through Venn analysis, followed by protein- protein interaction network construction, hub gene selection, and enrichment analysis. Molecular docking validated compound-target interactions. A total of 100 predicted resveratrol targets and 1,447 pancreatic cancer- associated genes were screened, yielding 39 overlapping genes. Network analysis identified hub genes including EGFR, SRC, MTOR, PIK3CA, PIK3CB, BCL2, and PTGS2. Gene Ontology enrichment indicated roles in cell proliferation, apoptosis regulation, inflammatory response and metabolic regulation while KEGG pathway analysis highlighted the PI3K-Akt, ErbB, and EGFR inhibitor resistance signaling as being closely associated with pancreatic cancer pathway. Docking analysis revealed strong binding of resveratrol with KRAS (-8.2 kcal/mol), EGFR (-7.9 kcal/mol), and MTOR (-7.7 kcal/mol), stabilized by hydrogen bonding. The interaction with KRAS, although not among the predicted targets. Expression profiling validated upregulation of hub genes in tumor samples. Resveratrol exerts multi-targeted effects in pancreatic cancer by modulating oncogenic pathways, particularly KRAS and PI3K/Akt/mTOR signaling. Its favourable safety profile and robust hub gene interactions highlight its potential as a supplementary therapeutic drug, necessitating further preclinical and clinical confirmation.

bioinformatics↗

bioRxiv2026

La1: an evolutionarily conserved player in the Arabidopsis telomerase complex

Analysis of yeast and mammalian telomerase ribonucleoprotein (RNP) complexes reveals striking divergence in their biogenesis and protein complements. However, little is known about telomerase in plants. In addition to the catalytic subunit TERT and the templating RNA TR, we previously reported Arabidopsis thaliana contains two telomerase accessory factors, AtNAP57, a dyskerin homolog that in mammals is essential for telomerase activity, and the telomeric DNA binding protein AtPOT1a. Both proteins stimulate Arabidopsis telomerase repeat addition processivity. Here we employ quantitative mass spectrometry (MS) to further examine telomerase in Arabidopsis. Unexpectedly, dyskerin and AtPOT1a were not detected in our purified complexes, but AtLa1, an RNA-binding factor that recognizes the UUU-3'OH of RNA Pol III transcripts, was highly enriched. RNA-IP assays confirmed AtLa1 association with AtTR in vivo. RNAi-mediated knockdown of AtLa1 strongly diminished telomerase activity, indicating AtLa1 is required for its function in vivo. In vitro binding studies revealed that AtLa1 contacts AtTR via the UUU-3'OH and a plant-specific P1a-P1b-P4 three-way junction (TWJ). Since the TWJ is also required for AtNAP57 binding, the data suggesting that AtNAP57 and AtLa1 compete for AtTR binding or sequentially associate during RNP during biogenesis. In contrast to AtNAP57, AtLa1 did not stimulate telomerase activity when TERT and TR were assembled in vitro, consistent with function during a different step in telomerase assembly. We conclude Arabidopsis telomerase employs multiple accessory factors utilized by both mammalian and single-celled relatives. Further exploration of Arabidopsis telomerase may offer novel insight into telomerase evolution and mechanisms of biogenesis. Significance of ResearchQuantitative mass spectrometry of Arabidopsis telomerase uncovered AtLa1, a homolog of ciliate and yeast proteins that promotes telomerase maturation. AtLa1 is essential for telomerase function in vivo, and in vitro it engages the same region of AtTR bound by AtNAP57, homologous to a telomerase accessory from mammals.

plant biology↗

bioRxiv2026

Distribution of Gene Tree Topologies with Duplication, Loss, and Coalescence

MotivationMany methods can be used to infer the number and timing of gene duplication and loss events from gene trees. Most such reconciliation methods use a model of gene duplication that does not include the coalescent process, or that restricts it in important ways. As a result, changes to tree topologies due to coalescence will incur a cost of extra duplications and losses using these methods, events that did not actually occur. ResultsHere, we present results from the multispecies coalescent with duplication and loss (MSC-DL) model, which allows for the unrestricted interaction between duplication, loss, and coalescence. Theoretical results show that even histories with only a single duplication event can lead to many more trees than are normally considered: for a species tree with 2 tips, 9 trees are possible, while with 6 tips, more than 19 million trees are possible; adding even a single loss almost doubles the number of possible topologies. The probabilities of different topologies and their branch lengths under the MSC-DL for trees with two species are calculated exactly, and we provide an approach for calculating such probabilities on larger trees. These results have important implications for the accuracy of reconciliation methods, ortholog identification methods, and our understanding of evolutionary histories of duplication and loss. Supplementary InformationSupplementary materials are available at https://github.com/smishra677/Distribution-of-Gene-Tree-Topologies-with-Duplication-Loss-and-Coalescence.

evolutionary biology↗