Biology subjects

Morgan, M.

Publications and source records attributed to Morgan, M..

At least 19 recordsLinked to original sources

bioRxiv2026

N6-methyladenosine regulates Influenza A virus mRNA stability yet is rarely found on genomic RNA

Previous studies have found widespread N6-methyladenosine (m6A methylation) on all forms of Influenza A virus (IAV) RNA, with m6A found critical for viral replication, pathogenicity as well as viral RNA packaging. Here we applied the latest quantitative technologies to revisit the methylation landscape on the anti-sense genomic RNA of IAV. Unexpectedly, upon Ultra-Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS) analysis of IAV virion -extracted genomic RNA, we detected very little m6A regardless of production from human cells or chicken eggs. Concordantly, Nanopore direct RNA sequencing also detected an overall low occurrence and stoichiometry (generally <5%) of m6A across all viral genomic RNA segments, compared with abundant m6A sites on viral mRNAs at ~20-30% m6A. Cross validation with glyoxal- and nitrite-mediated deamination of unmethylated adenosines (GLORI) confirmed multiple m6A sites on viral mRNA yet very few m6A on the genomic RNA. This paucity of m6A on genomic RNA makes it unlikely that m6A contributes to viral RNA packaging. Knockdown or pharmacological inhibition of the m6A methyltransferase METTL3 as well as the reader protein YTHDF2 both reduced viral mRNA levels and infectious viral particle production, with YTHDF2 promoting viral mRNA stability. Thus, the presence of m6A on IAV transcripts is indeed proviral, yet it is the mRNAs instead of genomic RNAs that are methylated at functionally relevant levels. Lastly, we provide proof of concept that a METTL3 small molecule inhibitor can be antiviral, and propose that m6A-targeted antivirals would mainly impact the intracellular gene expression phase of IAV replication.

microbiology↗

bioRxiv2026

cellNexus: Quality control, annotation, aggregation and analytical layers for the Human Cell Atlas data

Large-scale single-cell atlases such as the Human Cell Atlas have transformed our understanding of human biology. Yet, the lack of a robust framework that standardises quality control, expands cellular annotation, and adds normalisation and analytical layers, limits multi-study analyses and the usefulness of this resource. Here we present cellNexus, a comprehensive resource that enhances the Human Cell Atlas collection into analysis-ready data by linking quality control layers, metadata enrichment, expression normalisation, analysis and data aggregation. These enhancements enable robust large-scale statistical modelling across studies, exemplified here by a multi-tissue map of immune cell communication during ageing. All harmonised layers are accessible via a public web interface and with R and Python APIs. By providing continuous integration with CELLxGENE releases, cellNexus transforms large cell atlas corpora into an accessible, reproducible, interoperable foundation for large-scale biological discovery and the next generation of single-cell foundation models.

bioinformatics↗

bioRxiv2026

Evaluation of an Oxford Nanopore sequencing workflow for mycobacteria from primary MGIT culture

Illumina sequencing of primary MGIT cultures is an established workflow in several reference mycobacteriology laboratories. Oxford Nanopore Technologies (ONT) provides real-time genetic sequencing yielding long reads which help resolve repetitive genomes and is being explored for in-house implementation within diagnostic laboratories. However, low DNA yields from primary MGIT cultures frequently limit the application of ONT workflows, due to high minimum DNA input requirements for library preparation. We validated a modified ONT workflow combining rapid, semi-automated DNA extraction from MGIT cultures with Rapid PCR-Barcoding for whole-genome amplification, and compared its performance with Illumina sequencing for species identification and Mycobacterium tuberculosis complex (MTBC) single-nucleotide polymorphism (SNP) detection. A platform-agnostic analysis pipeline enabled consistent human read removal, taxonomic assignment, and MTBC genomic characterisation. ONT sequencing data was subsampled at 1, 6, and 72 hours to determine the earliest time point for reliable species identification. The concordance between sequencing platforms on species classification was 98.3% (95.8-99.5%) with all differences arising from potential mixed infections. SNP agreement was high, with a mean of 0.3 and a median of 0 SNP differences between sequencing platforms after masking. These findings demonstrate the feasibility of PCR-amplified ONT sequencing as a reliable alternative for routine genomic characterisation of MGIT cultures. IMPORTANCERapid identification of mycobacterial infections is essential for timely patient care and infection control. Many clinical laboratories currently rely on outsourcing sequencing to external reference centres, which adds time and delays the return of clinically actionable results. These services commonly use Illumina sequencing, which, while highly accurate, involves complex workflows and longer turnaround times. Newer technologies offer the potential to generate results in real time, but their use has been limited by the low amount of DNA available from routine culture samples. In this study, we developed an improved workflow that increases the amount of usable DNA and enables reliable, rapid sequencing directly from these samples. This approach allows multiple samples to be processed together and reduces the time needed to obtain results. Importantly, it could enable clinical laboratories to perform sequencing in-house, reducing reliance on external services and improving turnaround times.

molecular biology↗

bioRxiv2025

Harvesting more reads from single-cell combinatorial barcoding data with scarecrow

SummaryCombinatorial barcoding technologies for single-cell nucleotide sequencing, such as split-pool ligation protocols, involve sequential rounds of cell barcoding to uniquely tag individual cells. The rapid adoption of combinatorial barcoding in recent years is due in part to its scalability across cells and samples. However, small shifts in barcode positions within sequencing reads caused by technical artifacts, e.g. during barcode incorporation or synthesis, can impact the accurate assignment of reads to cell barcodes. Existing processing tools typically assume barcodes contain fixed-length nucleotide sequences located at fixed positions within reads, overlooking any positional variability. Consequently, reads containing truncated or mispositioned barcodes are discarded during initial data processing steps leading to significant data loss. To solve this limitation and maximise the retention of sequencing reads from single-cell combinatorial barcoding experiments, we introduce scarecrow. Our tool screens a subsample of reads to generate position-specific barcode profiles, which are then used to flexibly identify barcode sequences in each read whilst accounting for positional errors, a phenomenon we refer to as jitter. Barcode matches are then prioritised to minimise nucleotide mismatches and the degree of jitter. These initial profiles are subsequently used to extract and error correct barcode combinations in high throughput sequencing libraries. By incorporating jitter into barcode error correction, scarecrow enables greater data recovery and improved downstream single-cell analyses. Scarecrow is fully open access, implemented in Python, and generates output files using standardised sequence file formats for maximal interoperability. A detailed explanation of the scarecrow workflow can be found in the supplementary materials.

bioinformatics↗

bioRxiv2025

anndataR improves interoperability between R and Python in single-cell transcriptomics

SummaryMany single-cell transcriptomics datasets are stored in the HDF5-backed AnnData (H5AD) file format, as popularised by the Python scverse ecosystem. However, accessing these datasets from R, allowing users to take advantage of the strengths of each language, can be difficult. anndataR facilitates this access by allowing users to natively read and write H5AD files in R, convert them to and from SingleCellExperiment or Seurat objects, or even work with the resulting R AnnData object directly. We perform rigorous testing to ensure compatibility between Python-written and R-written H5AD files, guaranteeing long-term interoperability between languages. AvailabilityanndataRs source code is available on GitHub at scverse/anndataR under the MIT license. It is compatible with R version 4.5, has been archived at 10.5281/zenodo.18775712 and included within Bioconductor: 10.18129/B9.bioc.anndataR. Installation instructions and tutorials can be found in the online documentation at anndatar.scverse.org. Issues can be reported at the GitHub repository. Code to reproduce the analyses performed can be found on GitHub at LouiseDck/anndataR-paper, archived at 10.5281/zenodo.18792241. Contactrobrecht.cannoodt@gmail.com

bioinformatics↗

bioRxiv2025

Assessment of pharmacokinetics, safety, and neuroprotective efficacy of an adjunct intramuscular verapamil therapy in a rat model of organophosphate DFP-induced status epilepticus

Lethal organophosphate (OP) exposure leads to status epilepticus (SE), which, despite standard-of-care therapy, is associated with acute mortality and long-term morbidities. Neuronal injury and inflammation are reported following OP-SE, and drugs targeted at these processes have produced beneficial outcomes. Verapamil (VPM) is a calcium-channel blocker used as an antihypertensive drug. It exhibits neuroprotective and anti-inflammatory actions in experimental models of CNS injuries. Here, we investigated the feasibility of an adjunctive intramuscular (i.m.) VPM therapy in OP Diisopropyl Fluorophosphate (DFP)-induced SE. We also investigated the safety and toxicity of i.m. VPM and compared its pharmacokinetic (PK) profile to oral (p.o.) administration. Rats were injected with DFP (4 mg/kg, s.c.). One minute later, atropine (0.5 mg/kg, i.m.) and 2-PAM (25 mg/kg, i.m.) were injected, and at 1-hour post-SE, midazolam (1.78 mg/kg, i.m.) was administered. Rats were then treated with VPM (10 mg/kg, i.m, 3 days). Histological analysis was conducted to assess neuronal injury and injection-site pathology. In a separate group of rats, PK studies were conducted on blood and brain homogenates treated once with saline or VPM (10 mg/kg, p.o. or i.m.). Our data demonstrated that following DFP-SE, i.m. VPM achieved higher blood and brain levels and exhibited a favorable PK profile compared to p.o. route. VPM therapy did not cause significant muscle pathology and produced a robust neuroprotective response. Our studies provide evidence that the i.m. route is an effective method for delivering VPM following SE producing significant neuroprotective outcomes compared to treatment with the standard-of-care alone in OP-SE.

pharmacology and toxicology↗

bioRxiv2025

EMMAi: fast enzyme-allocation constraints in GEMs for improved biomass prediction across carbon sources

Genome-scale metabolic models (GEMs) predict emergent phenotypes by modeling the metabolic networks encoded in genomes. While GEMs have significantly advanced systems biology, metabolic engineering, biomedicine, and environmental science, they require extensive time and resources for manual curation, which can limit their utility in rapidly evolving research landscapes. Recent findings suggest that manually curated reactions can sometimes reduce prediction accuracy, indicating that integrating additional biologically grounded constraints may better capture emergent phenotypes. One promising approach is the incorporation of enzyme allocation constraints, which has been shown to enhance the predictive accuracy in metabolic models. Enzymatically constrained GEMs (ecGEMs) rely on enzyme turnover rates (kcat) and protein molecular weights (MWs) to account for intracellular resource limitations by introducing an enzyme pool variable and assigning costs to reactions, thereby simulating enzymatic resource constraints. Tools such as GECKO, AutoPACMEN, and ECMpy provide computational pipelines for ecGEM generation. However, these pipelines are often limited by their reliance on experimentally measured kcat values or deep learning-predicted values, such as those generated by DLKcat, which face challenges in predicting kinetics for enzymes dissimilar to their training data. Additionally, these methods frequently require extensive manual curation of kcat values based on empirical data, a time-intensive process that hampers scalability and applicability to non-model organisms. To address these limitations, we introduce EMMAi (Enzyme-constrained Metabolic Models with AI), a pipeline that fully automates the incorporation of enzyme constraints into GEMs. Unlike existing pipelines, EMMAi exclusively utilizes kcat values predicted by UniKP, an AI framework with improved accuracy over DLKcat, particularly for enzymes not present in training datasets. UniKP achieves a 13% improvement in correlation for unseen enzymes, enabling EMMAi to deliver ecGEMs with enhanced prediction accuracy without manual curation requirements. We evaluated EMMAi by applying it to three GEMs: two manually curated models, iJO1366 (Escherichia coli str. K-12 substr. MG1655) and iMO1056 (Pseudomonas aeruginosa PAO1), and one draft GEM constructed and gap-filled using CarveMe. EMMAi-generated ecGEMs showed an average Pearson Correlation Coefficient (PCC) improvement of 0.27 for manually curated GEMs when compared to predicted and experimentally measured growth rates and Biolog readings. Notably, for the draft GEM of Pseudomonas aeruginosa PAO1, the PCC improved dramatically from -0.3 to 0.6. EMMAi demonstrates that automating the integration of enzyme allocation constraints using AI-predicted kinetic parameters significantly enhances the prediction accuracy of GEMs, even in the absence of manual curation. These results underscore EMMAis potential as a scalable, efficient, and accurate tool for advancing GEM-based research in systems biology, metabolic engineering, and beyond.

systems biology↗

bioRxiv2025

Native epitranscriptome sequencing reveals Hepatitis B virus RNA stability protected by heavy m6A modification

Although the RNA of Hepatitis B virus (HBV) is known to be regulated by the epitranscriptomic modification N6-methyladenosine (m6A), it remains controversial whether if m6A is beneficial or detrimental for viral replication. Here, we employ Nanopore direct RNA sequencing (DRS) to analyze the HBV m6A epitranscriptome on a single molecule level and elucidate how m6A regulates the HBV replication cycle. We found more than 60% of all HBV RNA in cells are m6A methylated, [~]3x more methylated than host mRNAs. Previously unreported m6A sites were found in pol gene, which when mutated reduced viral production. A sizable proportion of HBV RNAs carry poly(A) tails at least twice as long (>120nt) as cellular mRNAs, with the shorter-tailed population more pronounced among m6A-free transcripts. In contrast, encapsidated RNAs have shorter poly(A) tails and less m6A. Concordantly, pharmacological reduction of viral m6A using the m6A methyltransferase inhibitor STM2457, shortens viral poly(A) tails and reduces viral RNA stability. Our findings thus suggest that the abundance of m6A on viral RNAs protects the surprisingly long viral poly(A) tails and thus enhances RNA stability. Overall, m6A strongly enhances HBV viral replication, in support of RNA modification machinery as a promising class of antiviral targets.

microbiology↗

bioRxiv2025

TENT5C extends Odf1 poly(A) tail to sustain sperm morphogenesis and fertility

Changes in the poly(A) tail length of Odf1 and other transcripts critical for male fertility have been linked to translational activation during sperm formation 1-3. The mRNA poly(A) polymerase TENT5C is required for fastening the flagellum to the sperm head, but its role in shaping the poly(A) tail profile of the spermatid transcriptome remains limited 4,5. Here, we comprehensively document how changes in mRNA poly(A) tail length across the transcriptome reflect transcript metabolism in spermatids. In the absence of TENT5C polymerase activity, the poly(A) tail length of Odf1 transcripts is reduced, and the local distribution of ODF1 proteins in spermatids is disrupted. We show that mice expressing a catalytically inactive TENT5C produce headless spermatozoa with outer dense fibers detached from the axoneme, and other flagellar abnormalities associated with ODF1 deficiency 6. We propose that TENT5C poly(A) polymerase activity regulates the spatial translation of Odf1 mRNAs during spermiogenesis, a process critical for sperm morphogenesis and fertility. These findings highlight the power of poly(A) tail profiling to identify abnormal mRNA processing causative of infertility.

developmental biology↗

bioRxiv2024

HuBMAPR: an R Client for the HuBMAP Data Portal

SummaryThe Human BioMolecular Atlas Program (HuBMAP) constructs the worldwide available platform to research the human body at the cellular level. The HuBMAP Data Portal encompasses a wide range of data resources measured on emerging experimental technologies at a spatial resolution. To broaden access to the HuBMAP Data Portal, we introduce an R client called HuBMAPR available on Bioconductor. This gives an efficient and programmatic interface, enabling researchers to discover and retrieve HuBMAP data easier and faster. AvailabilityThis package is available on GitHub (https://github.com/christinehou11/HuBMAPR) and has been submitted to Bioconductor.

bioinformatics↗

bioRxiv2024

Morpho-physiological and transcriptomic responses of field pennycress to waterlogging

Field pennycress (Thlaspi arvense) is a new biofuel winter annual crop with extreme cold hardiness and a short life cycle, enabling off-season integration into corn and soybean rotations across the Midwest. Pennycress fields are susceptible to winter snow melt and spring rainfall, leading to waterlogged soils. The objective of this research was to determine if waterlogging during the reproductive stage had a significant effect on gene expression, morphology, physiology, recovery, and yield of two pennycress lines (SP32-10 and MN106). In a controlled environment, total pod number, shoot/root dry weight, and total seed count/weight were significantly reduced in SP32-10 in response to waterlogging, whereas primary branch number, shoot dry weight, and single seed weight were significantly reduced in MN106. This indicated waterlogging had a greater negative impact on seed yield in SP32-10 than MN106. The number of differentially expressed genes (DEGs) between waterlogged and control roots were doubled in MN106 (3,424) compared to SP32-10 (1,767). Functional enrichment analysis of upregulated DEGs revealed Gene Ontology (GO) terms associated with hypoxia and decreased oxygen, with genes in these categories involved in alcoholic fermentation and glycolysis. Interestingly, MN106 waterlogged roots exhibited significant stronger upregulation of these genes than SP32-10. Additionally, downregulated DEGs revealed GO terms associated with cell wall biogenesis and secondary metabolite biogenesis, indicating suppressed growth and energy conservation. Together, these results reveal the reconfiguration of cellular and metabolic processes in response to the severe energy crisis invoked by waterlogging in pennycress.

plant biology↗

bioRxiv2024

E. coli phylogeny drives co-amoxiclav resistance through variable expression of blaTEM-1

Co-amoxiclav resistance in E. coli is a clinically important phenotype associated with increased mortality. The class A beta-lactamase blaTEM-1 is often carried by co- amoxiclav-resistant pathogens, but exhibits high phenotypic heterogeneity, making genotype-phenotype predictions challenging. We present a curated dataset of n=377 E. coli isolates representing all 8 known phylogroups, where the only acquired beta- lactamase is blaTEM-1. For all isolates, we generate hybrid assemblies and co-amoxiclav MICs, and for a subset (n=67/377), blaTEM-1 qPCR expression data. First, we test whether certain E. coli lineages are intrinsically better or worse at expressing blaTEM-1, for example, due to lineage differences in regulatory systems, which are challenging to directly quantify. Using genotypic features of the isolates (blaTEM-1 promoter variants and copy number), we develop a hierarchical Bayesian model for blaTEM-1 expression that controls for phylogeny. We establish that blaTEM-1 expression intrinsically varies across the phylogeny, with some lineages (e.g. phylogroups B1 and C, ST12) better at expression than others (e.g. phylogroups E and F, ST372). Next, we test whether phylogenetic variation in expression influences the resistance of the isolates. With a second model, we use genotypic features (blaTEM-1 promoter variants, copy number, duplications; ampC promoter variants; efflux pump AcrF presence) to predict isolate MIC, again controlling for phylogeny. Lastly, we use a third model to demonstrate that the phylogenetic influence on blaTEM-1 expression causally drives the variation in co- amoxiclav MIC. This underscores the importance of incorporating phylogeny into genotype-phenotype predictions, and the study of resistance more generally.

microbiology↗

bioRxiv2024

MENTOR: Multiplex Embedding of Networks for Team-Based Omics Research

While the proliferation of data-driven omics technologies has continued to accelerate, methods of identifying relationships among large-scale changes from omics experiments have stagnated. It is therefore imperative to develop methods that can identify key mechanisms among one or more omics experiments in order to advance biological discovery. To solve this problem, here we describe the network-based algorithm MENTOR - Multiplex Embedding of Networks for Team-Based Omics Research. We demonstrate MENTORs utility as a supervised learning approach to successfully partition a gene set containing multiple ontological functions into their respective functions. Subsequently, we used MENTOR as an unsupervised learning approach to identify important biological functions pertaining to the host genetic architectures in Populus trichocarpa associated with microbial abundance of multiple taxa. Moreover, as open source software designed with scientific teams in mind, we demonstrate the ability to use the output of MENTOR to facilitate distributed interpretation of omics experiments.

bioinformatics↗

bioRxiv2024

RWRtoolkit: multi-omic network analysis using random walks on multiplex networks in any species

Leveraging the use of multiplex multi-omic networks, key insights into genetic and epigenetic mechanisms supporting biofuel production have been uncovered. Here, we introduce RWRtoolkit, a multiplex generation, exploration, and statistical package built for R and command line users. RWRtoolkit enables the efficient exploration of large and highly complex biological networks generated from custom experimental data and/or from publicly available datasets, and is species agnostic. A range of functions can be used to find topological distances between biological entities, determine relationships within sets of interest, search for topological context around sets of interest, and statistically evaluate the strength of relationships within and between sets. The command-line interface is designed for parallelisation on high performance cluster systems, which enables high throughput analysis such as permutation testing. Several tools in the package have also been made available for use in reproducible workflows via the KBase web application.

bioinformatics↗

bioRxiv2024

Application of chimeric antigens to paper-based diagnostics for detection of West Nile virus infections of Crocodylus porosus: a novel animal test case

Laboratory-based diagnostics like plaque reduction neutralization tests (PRNT) and ELISA are commonly used to detect seroconversion to flavivirus infections. However, faster, qualitative screening methods are needed for quicker diagnosis and better patient outcomes. Lateral flow assays (LFAs) can provide rapid results (5-15 mins) at the point-of-care, yet few commercial flavivirus antibody detection LFAs are available. We developed an LFA using novel chimeric viral antigens produced by genetically modifying the mosquito restricted Binjari virus (BinJV) to display the outer virion proteins of pathogenic viruses such as West Nile virus (WNV). The BinJV chimeric platform offers various advantages for diagnostic assay development, including rapid construction of new chimeras in response to emerging viral variants, safe, scalable antigen manufacturing, and structural indistinguishability to the wild-type pathogenic virion. As a demonstration of feasibility, we applied chimeric WNV (BinJV/WNV) antigen to LFA as the capture/test line reagent for detection of seroconversion of crocodilians to WNV - a virus affecting crocodilians on multiple continents. We verified the antigenic conservation of the chimera when applied to the LFA detection surface using monoclonal antibodies. Using well-characterised sera (n=60) from WNV seropositive or flavivirus naive Australian saltwater crocodiles (Crocodylus porosus), we illustrated 100% sensitivity and specificity, with results achieved in less than 15 minutes. The LFA further accurately detected seroconversion in animals experimentally infected with WNV. This qualitative screening method can be performed both inside and outside of a laboratory, and the assay design will guide the optimization of similar tests for vector borne virus infection detection in both humans and other animals.

biochemistry↗

bioRxiv2024

DERIVATION OF ELEPHANT INDUCED PLURIPOTENT STEM CELLS

The crisis of biodiversity loss in the anthropogenic era requires new tools for studying non-model organisms. Elephants, for example, are both an endangered species and excellent models studying complex phenotypes like size, social behavior, and longevity, but they remain severely understudied. Here we report the first derivation of elephant (Elephas maximus) induced pluripotent stem cells (emiPSCs) achieved via a two-step process of chemical-media induction and colony selection, followed by overexpression of elephant transcription factors OCT4, SOX2, KLF4, MYC {+/-} NANOG and LIN28A, and modulation of the TP53 pathway. Since the seminal discovery of reprogramming by Shinya Yamanaka, iPSCs from many species including the functionally extinct northern white rhinocerous have been reported, but emiPSCs have remained elusive. While for multiple species the reprogramming protocol was adopted with little changes compared to model organisms like mouse and human, our emiPSC protocol requires a longer timeline and inhibition of TP53 expansion genes that are hypothesized to confer unique cancer resistance in elephants. iPSCs unlock tremendous potential to explore cell fate determination, cell and tissue development, cell therapies, drug screening, disease modeling, cancer development, gametogenesis and beyond to further our understanding of this iconic megafauna. This study opens new frontiers in advanced non-model organism cellular models for genetic rescue and conservation.

cell biology↗

bioRxiv2024

Ubiquitinated histone H2B as gatekeeper of the nucleosome acidic patch

Monoubiquitination of histones H2B-K120 (H2BK120ub) and H2A-K119 (H2AK119ub) play opposing roles in regulating transcription and chromatin compaction. H2BK120ub is a hallmark of actively transcribed euchromatin, while H2AK119ub is highly enriched in transcriptionally repressed heterochromatin. Whereas H2BK120ub is known to stimulate the binding or activity of various chromatin-modifying enzymes, this post-translational modification (PTM) also interferes with the binding of several proteins to the nucleosome H2A/H2B acidic patch via an unknown mechanism. Here we report cryoEM structures of an H2BK120ub nucleosome showing that ubiquitin adopts discrete positions that occlude the acidic patch. Molecular dynamics simulations show that ubiquitin remains stably positioned over this nucleosome region. By contrast, our cryoEM structures of H2AK119ub nucleosomes show ubiquitin adopting discrete positions that minimally occlude the acidic patch. Consistent with these observations, H2BK120ub, but not H2AK119ub, abrogates nucleosome interactions with acidic patch-binding proteins RCC1 and LANA, and single-domain antibodies specific to this region. Our results suggest a mechanism by which H2BK120ub serves as a gatekeeper to the acidic patch and point to distinct roles for histone H2AK119 and H2BK120 ubiquitination in regulating protein binding to nucleosomes.

biophysics↗

bioRxiv2023

The tidyomics ecosystem: Enhancing omic data analyses

The growth of omic data presents evolving challenges in data manipulation, analysis, and integration. Addressing these challenges, Bioconductor1 provides an extensive community-driven biological data analysis platform. Meanwhile, tidy R programming2 offers a revolutionary standard for data organisation and manipulation. Here, we present the tidyomics software ecosystem, bridging Bioconductor to the tidy R paradigm. This ecosystem aims to streamline omic analysis, ease learning, and encourage cross-disciplinary collaborations. We demonstrate the effectiveness of tidyomics by analysing 7.5 million peripheral blood mononuclear cells from the Human Cell Atlas3, spanning six data frameworks and ten analysis tools.

bioinformatics↗