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Results for “molecular biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2019

A literature mining method to judge whether there are uncertaintiesin empirical-dependent antineoplastic drug distribution in specificclinical scenarios.

Cancer clinical practice guidelines recommend different treatment options for different cancer types and are mainly developed by clinicians. In theory, those recommendation schemes that are supported by scientific research should provide better efficacy for patients. However, in actual clinical practice: "Is the choice of a specific antineoplastic drug for a specific cancer supported by the results of molecular biology mechanisms or based on the subjective experience of the clinician?" Answering this question is of significant importance for guiding clinical practice, but there is currently no operational method to provide objective judgment in specific cases. This paper describes a literature mining method that collates information from specific antineoplastic drug-related literature to establish an antineoplastic drug-gene association matrix for global or specific cancer scenarios, and further establishes a standard model and scenario models. Based on the parameters of these models, we constructed a linear regression analysis method to evaluate whether the models in different scenarios deviated from a random distribution. Finally, we determined the possible efficacy of an antineoplastic drug in different cancer types, which was validated by the Genomics of Drug Sensitivity in Cancer (GDSC) database. Using our mining method, we tested 18 antineoplastic drugs in 16 cancer types. We found that cisplatin used in ovarian cancer was more efficacious and may benefit patients more than when used in breast cancer, which provides a new paradigm for rational knowledge-driven drug distribution patterns in clinical practice.

bioinformatics↗

bioRxiv2019

CiteFuse enables multi-modal analysis of CITE-seq data

Multi-modal profiling of single cells represents one of the latest technological advancements in molecular biology. Among various single-cell multi-modal strategies, cellular indexing of transcriptomes and epitopes by sequencing (CITE-seq) allows simultaneous quantification of two distinct species: RNA and surface marker proteins (ADT). Here, we introduce CiteFuse, a streamlined package consisting of a suite of tools for pre-processing, modality integration, clustering, differential RNA and ADT expression analysis, ADT evaluation, ligand-receptor interaction analysis, and interactive web-based visualization of CITE-seq data. We show the capacity of CiteFuse to integrate the two data modalities and its relative advantage against data generated from single modality profiling. Furthermore, we illustrate the pre-processing steps in CiteFuse and in particular a novel doublet detection method based on a combined index of cell hashing and transcriptome data. Collectively, we demonstrate the utility and effectiveness of CiteFuse for the integrative analysis of transcriptome and epitope profiles from CITE-seq data.

bioinformatics↗

bioRxiv2019

Mycolactone-independent pathogenicity of Mycobacterium ulcerans: an experimental study in plants.

Mycobacterium ulcerans, the etiologic agent of Buruli ulcer in humans and animals, secretes macrolide exotoxins mycolactones which damage tissues after a cascade of cellular effects. M. ulcerans, an environmental organism with still elusive reservoirs and sources has been detected in soil and water in endemic areas where it could be in contact with plants. Symptom observations, microscopy and molecular biology were used to investigate M. ulcerans contact with plants in an experimental model mimicking the known pathology of Buruli ulcer in humans. Solanum lycopereum (tomato) plants with scarified or intact roots were transplanted into pots containing contaminated soil with M. ulcerans or a mixture of mycolactones A/B and C in the presence of negative control groups. Whereas plants with intact roots remained asymptomatic, M. ulcerans-infected plants with scarified roots had significantly more diseased leaves than controls (p = 0.004). Optic microscopy examination showed significantly more mycobacteria in the secondary and main roots than in controls (p=0.0008). Real-time PCRs detected M. ulcerans DNA in 7/12 (58%) of infected root samples versus none in the control plants (p = 0.04). Further study of plants with mycolactones A/B and C yielded no significant difference with negative controls. These results suggest that in this model, M. ulcerans exhibits a mycolactone-independent pathogenicity whose mechanism remains to be elucidated.

microbiology↗

bioRxiv2025

Improved long transcript representation in Oxford Nanopore direct RNA sequencing with UltraMarathonRT

While most RNA-seq methods sequence amplified cDNA molecules, the advent of direct RNA sequencing (DRS) empowered the scientific community to read native RNA. This technology unlocked characterization of natural RNA modifications and long RNA isoforms without the inherent biases of PCR amplification. In the library preparation prior to Oxford Nanopore (ONT) sequencing, polyadenylated RNAs are copied by a reverse transcriptase (RT) to generate an RNA-cDNA hybrid. The step aims to eliminate the secondary and tertiary structure inherent to most RNA sequences prior to presentation of the RNA strand to the pore for sequencing. The current recommended protocol for DRS utilizes Induro(R) RT and requires reverse transcription at 60{degrees}C. We demonstrate that these RT conditions promote hydrolysis of the RNA strand. We further show that UltraMarathonRT(R) (uMRT), an ultraprocessive reverse transcriptase with intrinsic helicase activity that works optimally at 30{degrees}C, can be incorporated into a new uMRT-based DRS method that results in longer RNA reads in ONT DRS and longer final isoform predictions. We optimize this reaction along with other molecular biology steps and demonstrate the performance improvements of this new workflow on the benchmark sample, Universal Human Reference RNA, along with human brain RNA. This improved DRS protocol should empower new discoveries by the scientific community.

genomics↗

bioRxiv2025

Critical role of Cas9 aggregation on in vitro DNA cleavage

The CRISPR/Cas9 system is a powerful genome-editing tool widely used in molecular biology and gene therapy, whose efficiency strongly depends on the physicochemical properties of the Cas9 ribonucleoprotein complex. Optimizing Cas9 activity remains essential for reliable genome- editing applications, yet the factors limiting its in vitro cleavage efficiency are not fully understood. Among these, protein aggregation has been suggested to critically impair Cas9 functionality, although its role has not been systematically analysed. Here, we investigate Cas9 aggregation under different environmental conditions and evaluate its impact on in vitro DNA cleavage efficiency. Using fluorescently labelled Cas9 and single-molecule fluorescence techniques, we quantify aggregation as a function of buffer composition, ionic strength, salt concentration and sgRNA presence, and relate these properties to cleavage activity. Our results show that Cas9 aggregation significantly reduces DNA cleavage efficiency, with higher aggregation levels consistently correlating with lower activity. In contrast, buffers with higher ionic strength or stabilizing components reduce aggregation and enhance Cas9 performance. Overall, this study demonstrates that Cas9 aggregation plays a critical role in determining in vitro cleavage efficiency and highlights the importance of controlling protein aggregation to optimize CRISPR/Cas9-based genome-editing applications and delivery strategies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC="FIGDIR/small/696176v1_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@14dbd87org.highwire.dtl.DTLVardef@d5f812org.highwire.dtl.DTLVardef@1916c53org.highwire.dtl.DTLVardef@5ed798_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

ColabPCR: A validated Google Colaboratory Notebook for Reproducible and Precise Primer Design.

The Polymerase Chain Reaction (PCR) method often has a lower success rate when amplifying specific genomic regions in eukaryotic genomes. This is frequently due to the non-specific annealing of primers at various genomic locations. To address this issue, we created ColabPCR, a program specifically designed to optimize the selection and evaluation of primers for a defined genomic region. ColabPCR refines primer length and melting temperature parameters through the utilization of Primer3 software, and it quantifies the number of potential off-target binding regions within the target genome via BLASTn analysis. Furthermore, the program facilitates the integration of restriction enzyme recognition sites at the 5 termini of primers and provides a mechanism to confirm the absence of such sites within the intended amplification region. ColabPCR centralizes all these functionalities within a single interface, utilizing Google Colabs computational resources to ensure high performance and accessibility without requiring local software installation. We rigorously validated ColabPCR by designing primers for promoter and terminator regions within the Daucus carota (DCARv2, DH1v3) reference genome. Our findings unequivocally demonstrate significantly enhanced success rates, particularly when primers exhibiting off-target binding are excluded from the primer design process. In summary, ColabPCR offers a user-friendly and powerful solution that simplifies and enhances the primer design and evaluation workflow, leading to increased accuracy and success in molecular biology experiments.

bioinformatics↗

bioRxiv2025

Evidence for an ancient master sex determination gene in Hymenoptera

The vast majority of Hymenopterans determine sex by haplodiploidy, in which males and females develop from haploid unfertilized and diploid fertilized eggs, respectively. At the molecular level, the majority of Hymenoptera are thought to determine sex by so-called Complementary Sex Determination (CSD). Under CSD, sex is determined by the feminizing effects of one or more allele-rich loci, in which the feminizing function is imparted by the interactions of functionally distinct alleles. Because of high allelic diversity, most diploids are heterozygous and develop as females, whereas haploid individuals develop as males, as do rare homozygous diploids. Despite diverse empirical results suggesting that CSD is widespread in Hymenopterans, and substantial theoretical and empirical study of the consequences of CSD, the molecular biology of CSD has received little attention outside of the honeybee, Apis mellifera. Available evidence provides support for divergent perspectives ranging from a single (nearly) universally-conserved CSD locus or a pattern dominated by evolutionary turnover with different genes serving as the CSD gene(s) in different lineages. Recently, a novel non-coding RNA gene named ANTSR was shown to serve as a CSD gene in different ant lineages, and the authors suggested that ANTSR might serve as a more broadly-conserved CSD gene. To assess the role of ANTSR role in CSD across diverse Hymenoptera, we studied syntenic conservation and polymorphism patterns in the broad ANTSR locus, genome-wide sequence from available male and female diploid Formica ants, and data from a sibling cross for Bombus terrestris. We find evidence that ANTSR is a conserved CSD gene across diverse Aculeata, the largest group of Hymenoptera, and provide preliminary evidence that Formica may have multiple CSD loci including ANTSR.

genetics↗

bioRxiv2025

Spontaneous cancer regression as inversion of spontaneous cancer progression: Malignant melanoma remission as a case-study towards clinical applicability

The spontaneous cancer regression process (SCR) a rather rare paradoxical natural phenomenon, shows that malignant tumors can episodically undergo complete permanent elimination without treatment, and thus may be used for gaining clues to incisive therapeutic innovations. SCR of malignant breast tumors occurs subclinically across human populations ([~]22% rate), according to Scandinavian and Wisconsin Screening Registries (monitoring 0.33million and 2.95million population respectively). SCR occurs in discoid melanomas ([~]12% rate). SCR process has high novelty with no toxicity nor recurrence, and duplicating SCR process is indeed clinically desirable. We aim to probe SCR using melanoma as illustrative pilot-study, and identify candidate leads that may mimic SCR on the tumor. We investigated molecular biological of melanoma, finding two reciprocal phases: spontaneous-progression and spontaneous-regression, and showed driver genes for melanoma SCR. Then, we pursued network pharmaco-informatics analysis. We found that spontaneous melanoma eradication shows an unexpected finding, in distinct contrast to the prevalent view that immunological processes and immunotherapy are critical for melanoma regression, than targeting DNA. We found that in contradistinction, it is DNA interference process that is primary route for melanoma regression, while anti-tumor immune activation is only secondarily needed. We observed that targeting two pathways (kinase-system, inositide-system) by inhibiting two genes, arrested melanoma-progression phase, and activated the reverse phase, melanoma-regression. We investigated the interactions of possible candidate leads, indicating significant therapeutic potency. Our findings underscore the high impact possibility for leveraging the anomalous phenomenon of spontaneous cancer regression as a general oncological principle for probing targeted therapeutic interventions, with substantial clinical potentials.

cancer biology↗

bioRxiv2026

A moments-based approach for inferring mechanisms of transcriptional regulation using nascent RNA data

AbstractUnraveling the kinetics of transcriptional regulation is a central challenge in molecular biology. Traditional inference methods based on cell-to-cell mRNA variability are limited because mRNA levels reflect not only transcriptional activity but also post-transcriptional processes. Recent advances in quantifying nascent RNAs across isogenic cells provide a more direct readout of transcriptional dynamics. Here, we present a moments-based theoretical framework that leverages nascent RNA data to infer transcriptional kinetics. We derive closed-form expressions for the first two time-dependent moments of nascent RNA across three canonical transcription models and demonstrate that nascent RNA exhibits distinct transient overshoots and higher Fano factors compared to mature mRNA. Through analysis of synthetic datasets, we show that these features enable more accurate estimation of transcriptional kinetics and allow reliable model selection, distinguishing single from multi-pathway promoter activation with over 75% accuracy even from small sample sizes. We further validated our model selection method using real experimental transcription datasets in yeast and E. coli cells, with nascent RNA demonstrating superior performance in identifying cross-talk pathway regulation. Our framework thus offers a computationally efficient and mechanistically informative approach for decoding transcriptional dynamics, emphasizing the advantages of time-dependent nascent RNA measurements over mature mRNA in capturing the true kinetics of transcriptional regulation.

biophysics↗

bioRxiv2026

Preparation and application of YFV-17D-derived Anterograde Trans-neuronal Viral Vectors for Neuroscience Research

Trans-neuronal viruses that spread between synaptically connected neurons have become invaluable tools in neuroscience, enabling circuit mapping and targeted delivery of genetic material to cells within defined pathways. Although most available trans-neuronal viral tracers propagate retrogradely, an anterograde trans-neuronal virus that spread from presynaptic to postsynaptic neurons would substantially expand experimental capabilities. We previously demonstrated that YFV-17D--a live attenuated yellow fever vaccine used clinically for decades--spreads anterogradely along neuronal circuits. We further developed a suite of recombinant YFV-17D-based vectors for diverse applications, including tracing monosynaptic projectome of defined neuronal cell types, multiplex mapping of parallel pathways, and trans-neuronal genetic manipulation with minimal neurotoxicity. We have now tested and optimized procedures for vector production and application. Based on these optimizations, here, we present a two-part guide for preparing and deploying this viral vector system to map brain connectivity. The first part describes the molecular biology and cell culture workflows required to generate high-quality viral vectors, yielding titers of [~]1 x 10^10 to 5 x 10^11 genomic copies per milliliter within approximately two weeks. The second part outlines optimized animal procedures, including intracranial injections, perioperative care, and experimental considerations tailored to specific aims and vector variants. Depending on the application, efficient trans-neuronal tracing can be achieved within 1-4 weeks following delivery.

neuroscience↗

bioRxiv2026

Isolation and Characterisation of Hair Follicle-Derived Melanocytes

Melanocytes are unique population of cells which produce melanin pigment. However, the property of melanocytes from hair follicle and epidermis, particularly, their molecular signatures remained largely unknown. In this study, we investigated the properties of epidermis and hair follicle melanocytes by biochemical and molecular biological assays. We found that epidermal melanocytes are differentiated and mature form of hair follicle melanocytes, and they are potentially related. Irradiation with NB-UVB did not induce cell death of hair follicle melanocytes as observed in epidermal melanocytes, but activate hair follicle melanocytes, promote proliferation and migration. In situ study suggested that after UVB irradiation, root sheath of hair follicles, particularly proximity of interfollicular epidermis and hair bulb become darker, suggesting migration and maturation of hair follicle melanocytes after UVB irradiation, rather than cell death. This observation provides hints and evidence to the relationship between hair follicle and epidermal melanocytes, helps to explain the contradiction of melanocytes cell death after UVB irradiation and the use of UVB in treatment of vitiligo lesion, as well as the perifollicular repigmentation phenomenon observed in vitiligo lesion after NB-UVB phototherapy.

cell biology↗

bioRxiv2026

Transmembrane PhoxID: Photo-proximity labelling across the plasma membrane

Transmembrane proteins perform essential roles in cellular transport, signalling, and communication. The function and dynamics of these proteins are precisely regulated by interactions on both sides of the plasma membrane; thus, mapping the composition of these interactomes is a fundamental challenge in molecular biology. Proximity labelling methods are powerful tools for this purpose; however, existing approaches that rely on membrane-impermeable reactive species are limited by the ability to detect only one side, either the extracellular or the intracellular region, of transmembrane proteins. Here, we capitalized on the cell permeability of singlet oxygen to carry out proximity labelling of the cytoplasmic side of transmembrane proteins using an extracellularly anchored photosensitizer. We applied this method, termed transmembrane PhoxID (tmPhoxID), to several receptors (GRID2, GABAAR, and GRM1) in the living mouse brain and successfully determined their specific intracellular interactomes. Notably, network analysis of the identified proteins revealed that this method can characterize the native components of transsynaptic nanocolumns formed at parallel fibre-Purkinje cell synapses. Furthermore, our study revealed a previously uncharacterized GABAAR-CAMKV interaction in mice and human brains. Our results provide a proof of concept for transmembrane and transcellular proximity labelling, providing a powerful platform for analysing the interactome of transmembrane proteins.

neuroscience↗

bioRxiv2026

Atomistic simulation study reveals transduction of mechanical work generated by ATP hydrolysis onto myosin II functional loops

Myosin II is a paradigm of biological molecular energy transducers that convert the chemical energy of ATP, via hydrolysis, into mechanical work with high efficiency in living cells. The physicochemical mechanisms underlying energy conversion by myosin II have been extensively investigated. However, a remaining challenge concerns the initial stage of the ATP hydrolysis cycle, specifically the conversion of ATP-to-ADP:Pi, because of technical difficulties in directly and seamlessly observing atomic trajectories during this early step and the subsequent processes. Here, we simulate the consequences of the chemical reaction by switching force field parameters between reactant and product systems within classical molecular dynamics simulations. We consider two possible ATP hydrolysis mechanisms in which either singly protonated (Pi{superscript 2}-) or doubly protonated (Pi-) inorganic phosphate is produced. Our results indicate that, in both Pi-generating processes, the kinetic energy supplied by conversion of ATP-to-ADP:Pi increases only transiently, whereas myosin functional loops store several kcal/mol of potential energy. Meanwhile, the amount of potential energy stored in the Pi{superscript 2}--producing reaction is approximately five-fold larger than that in the Pi--producing reaction. Our analysis indicates that this difference emerges when ATP-derived mechanical work is transmitted into the functional loops via rearrangement of intermolecular hydrogen bonds with the hydrolysis products. Notably, these steric interactions remain stably established even when the kinetic energy input associated with ATP-to-ADP:Pi conversion is actively quenched. We therefore propose that transient storage of ATP-derived mechanical work as atomic-scale conformational strain within myosin molecules constitutes a critical step for efficient conversion of ATP chemical energy into mechanical work under conditions of intracellular thermal noise. SignificanceMyosin II converts chemical energy released by ATP hydrolysis into mechanical work with exceptionally high efficiency, even in the presence of substantial thermal fluctuations in living systems. It has long been proposed that release of inorganic phosphate (Pi) from myosin II is a critical step for efficient energy transfer. However, this prevailing view has been challenged by recent state-of-the-art experimental observations, necessitating a reexamination of the chemical steps responsible for ATP-derived energy storage. Here, we employ atomistic molecular dynamics simulations specifically designed to capture key aspects of ATP hydrolysis. We demonstrate that ATP hydrolysis increases the potential energy of myosin II functional loops while Pi remains bound, and that this increase occurs independently of heat release associated with the reaction. Together, these findings identify an alternative mechanism for energy retention and emphasize the intrinsic robustness of myosin II as a highly efficient molecular motor.

biophysics↗

bioRxiv2026

Can Antisense lncRNA bind to the product of its sense pair?

Long non-coding RNAs (lncRNAs) account for a major proportion of the transcriptional output in complex organismal genomes. Their emergence as auxiliary regulators of gene expression as well as their roles in metastasis and cancer progression has put them in the limelight. LncRNAs perform multitudes of functions and often moonlight as regulators, scaffolds and guides. Most lncRNAs are cell and tissue specific and can act as markers for diseases as well as targets for therapeutic interventions. LncRNAs are also known to make use of higher order structures such as G-quadruplexes (G4) to facilitate complex functions and interactions. THAP9-antisense1 (AS1) is a lncRNA coding gene (recently annotated by Ensembl) that codes for 12 lncRNA transcripts and has been implicated in many disease pathologies like gastric cancer, spontaneous neutrophil apoptosis, hepatocellular carcinoma, and the progression of oesophageal cancer. It is the antisense gene pair of the THAP9 gene ( a transposase derived gene) with which it shares a promoter. THAP9-AS1 has been reported to be dysregulated during stress and several cancers. However, the exact role of the lncRNA is not well understood. Bioinformatics driven strategies are used to identify putative quadruplex forming sequences (PQSs) within the lncRNA THAP9-AS1. The identified PQSs are further validated using biophysical, spectroscopic and molecular biology driven techniques. The importance of each G-tract in the formation of a particular RNA G-quadruplex (rG4) is studied via the investigation of several deletion mutants. The findings demonstrate the rG4 forming potential of the identified PQSs within THAP9-AS1.

biochemistry↗

bioRxiv2026

Adaptive and Spandrel-like Constraints at Functional Sites in Protein Folds

How new molecular functions emerge during protein evolution remains a fundamental question in molecular biology. The energy landscape theory states that proteins are minimally frustrated, i.e. they have minimized their internal conflicts, to allow robust folding. Yet, not all energetic conflicts are eliminated, with functional regions such as catalytic residues and ligand-binding sites being often enriched in frustrated interactions, trading localized stability for biological activity. However, it is still uncertain whether this functional frustration is an evolutionary adaptation, positively selected despite its energetic cost or an inevitable physical byproduct of the fold architecture. Here, we combine reverse folding, structure prediction, and sequence analysis with local frustration profiling to address this long-standing question. Unexpectedly, we found that reverse folding algorithms are unable to energetically minimize evolutionary conserved frustration at specific residues, even when detrimental to overall structural stability. We propose that these frustration hotspots act as architectural spandrels, inherent physical constraints of the fold that evolution subsequently co-opts for function. Our findings connect biophysical constraints and evolutionary selection, providing a new framework to understand how functional specificity emerges in protein landscapes.

bioinformatics↗

bioRxiv2026

Unifying Non-Equilibrium Information Thermodynamics and Genome Engine Dynamics: Maxwell's Demon Control of Cancer Cell Fates

Molecular biology has revealed immense spatiotemporal complexity in cancer regulatory networks. A fundamental physical question remains: Does a physical principle exist that governs how this complexity self-organizes into genome-wide fate commitment and determines whether and when that commitment becomes irreversible? We address this question through an integrative biophysical analysis of time-series transcriptomes from two cancer systems under four conditions: MCF-7 human breast cancer cells stimulated with heregulin (HRG) or epidermal growth factor (EGF), and HL-60 human leukemia cells stimulated with all-trans retinoic acid (atRA) or dimethyl sulfoxide (DMSO). Our analysis establishes self-organized criticality (SOC) control as a biophysical principle that unifies information thermodynamics with genome-engine dynamics in a single open, non-equilibrium physical system. This principle elucidates how information processing is converted into mechanical work during cancer-fate commitment. Under SOC control, the genome operates as an open, non-equilibrium engine that maintains a critical dynamic balance between homeostatic stability and fate-guiding critical transitions. The critical point (CP) gene ensemble drives this genome-wide control. Within the environment-coupled whole expression system, the CP performs two coupled roles converging in a Maxwells demon (MD) actuation cycle. This cycle is implemented through rewritable chromatin memory exhibiting bistable switching. Thermodynamically, the CP acts as an MD operator regulating entropy and information-work conversion through phase synchronization. Dynamically, it acts as an SOC controller synchronizing with the genome attractor, driving genome-wide reorganization, and generating the dominant mechanical work. This unified mechanism distinguishes the rapid HRG, delayed DMSO, and two-step atRA commitments from the non-committing EGF response. It satisfies three open-system thermodynamic criteria for an irreversible arrow of time and defines time-gated rules with predictive intervention windows for dynamic cancer-fate control.

genomics↗

bioRxiv2026

TOXsiRNA: A web server to predict the toxicity of chemically modified siRNAs

Small interfering RNAs (siRNAs) are largely modified with chemical molecules to enhance their properties for use in molecular biology research and therapeutic applications. Toxicity effects may arise due to these chemical moieties as well as sequence based off-targets at cellular level. Enormous resources are required to experimentally design and test the toxicity of these chemical modifications and their combinations on siRNAs. To address this problem, we developed TOXsiRNA web server to computationally predict the toxicity of chemically modified siRNAs and their off-targets. We selected 2749 siRNAs with different permutations and combinations of 21 different chemical modifications engineered on them. Next, we used Support Vector Machine (SVM), Linear Regression (LR), K-Nearest Neighbor (KNN) and Artificial Neural Network (ANN) machine learning applications to develop models. Best performance was displayed by mononucleotide composition-based model developed with SVM, offering Pearson Correlation Coefficient (PCC) of 0.91 and 0.92 on training testing and independent validations respectively. Other sequence features like dinucleotide composition binary pattern and their combinations were also tested. Finally, three models of chemically modified siRNAs were implemented on the web server. Other algorithms that include predicting normal as well as chemically modified siRNA knockdown efficacy, off target etc. are also integrated. The resource is hosted online for scientific use freely at url: http://bioinfo.imtech.res.in/manojk/toxsirna.

bioinformatics↗

bioRxiv2026

A Cophylogenetic Approach for Virus-Host Interaction Prediction

Advances in metagenomics have rapidly expanded viral discovery, revealing vast diversity across Earths virosphere. Yet most virus-host interactions--i.e., which viruses infect which hosts--remain unrecorded. Identifying these interactions is essential for anticipating zoonotic spillover events and advancing biomedical applications such as bacteriophage therapy. However, the sheer diversity of viruses and hosts makes comprehensive experimental mapping infeasible, motivating the need for computational approaches. Most existing prediction methods rely on supervised learning strategies that use sequence-derived features, such as codon usage bias or k-mer frequencies, and do not model the coevolutionary processes that shape virus-host interactions. This limits their ability to generalize and the evolutionary interpretability of their predictions. We introduce CoEvoLink, a framework for predicting virus-host interactions that integrates sequence-based evidence with phylogenetic signal by explicitly modeling the coevolutionary histories of viruses and hosts. CoEvoLink infers likely but unobserved interactions by minimizing the number of evolutionary events required to explain them, yielding the most parsimonious interaction under a coevolutionary model. This formulation generalizes classical maximum parsimony, typically defined on a single phylogeny, by jointly optimizing parsimony across both virus and host phylogenies. Sequence-based information is incorporated by assigning a cost to each potential interaction that reflects its likelihood based on genomic features. By drawing a connection between computing parsimony on interaction matrices and maximum parsimony on phylogenetic networks, we derive a polynomial-time algorithm that balances parsimony with sequence-derived prediction cost. We demonstrate the effectiveness of CoEvoLink on simulated data under diverse coevolutionary models. Applying CoEvoLink, we identified putative bat hosts of betacoronaviruses that have not yet been cataloged in the VIRION database. On a benchmark derived from metagenomic sequencing data, we demonstrate that CoEvoLink improves the performance of existing phage-host prediction tools using cophylogenetic information. Code availabilityhttps://github.com/sashittal-group/CoEvoLink Note: This paper is accepted at RECOMB 2026 (30th Annual International Conference on Research in Computational Molecular Biology).

evolutionary biology↗