Biology subjects

Marini, F.

Publications and source records attributed to Marini, F..

At least 19 recordsLinked to original sources

bioRxiv2026

Comparative Transcriptional Responses of Human Blood to Neutron and Photon Irradiation

Despite the well-known health risks of neutron exposures, key gaps remain in understanding neutron-induced molecular responses and identifying reliable biodosimetric markers that distinguish neutrons from photon exposure. We provide the first genome-wide analysis of the human blood transcriptional response to an accelerator-derived fission-like spectrum of neutrons versus photons, evaluating transcriptomic relative biological effectiveness (RBE) and radiation quality-discriminating gene signatures. Whole blood from healthy donors was irradiated ex vivo with X-rays (140 kV, 0-4 Gy, n = 3) or neutrons (0.1-8 MeV, 0-1 Gy, n = 2), incubated for 6 h or 24 h, and processed for RNA sequencing from peripheral blood mononuclear cells (PBMCs). Neutrons were markedly more potent than X-rays at inducing differentially expressed genes (DEGs) at equal doses, showing a peak response 6 h post-irradiation followed by a decline. In contrast, X-rays caused a continuous increase in DEGs up to 24 h (neutrons vs. X-rays at 1 Gy: 1,449 vs. 121 DEGs at 6 h; 996 vs. 621 DEGs at 24 h). A universal p53-centered 34-gene signature, including FDXR, EDA2R, GADD45A, and ZMAT3, showed highly monotonic dose responses (Spearman correlation coefficient {approx} 1) across donors, radiation qualities, and timepoints. Additionally, difference-in-differences analysis identified radiation quality-discriminating genes only at 6 h, with transcriptional convergence observed by 24 h, suggesting a very narrow time window for biodosimetric differentiation. We identified a neutron-specific gene signature driven by cGAS-STING-NF-{kappa}B signaling (RELB, NFKB1, C3, MALAT1) and suppression of B-cell and myeloid identity genes (IGHD, TCL1A, CLEC7A, TLR2), defining a biologically coherent neutron quality index with distinct immunomodulatory effects. For the first time, we assessed neutron RBEs at the gene, pathway, and global transcriptomic levels in a human blood model, reporting a global transcriptomic neutron RBE of 1.30 (95% CI: 1.14-1.49) at 6 h and 1.21 (95% CI: 1.14-1.28) at 24 h, providing a valuable basis for biodosimetry in mixed-field exposure scenarios. Our findings advance the mechanistic understanding of neutron radiation responses and support the development of biodosimetric approaches for mixed-field exposure scenarios.

biophysics↗

bioRxiv2026

Menin-Inhibition Sensitizes Acute Myeloid Leukemia to CLEC12A-Directed CAR Cell Therapy

Menin inhibitors targeting the Menin-KMT2A chromatin complex have emerged as highly selective therapies for KMT2A-rearranged (KMT2A-r) and NPM1-mutated (NPM1mut) acute myeloid leukemia (AML), with recent regulatory approval and increasing interest in combination strategies. In contrast, CAR cell therapies have not yet been successfully established for AML. Here, we show that menin-inhibition primes KMT2A-r and NPM1mut AML for CAR-based targeting by inducing robust and uniform expression of the myeloid antigen CLEC12A (CLL-1). Menin inhibitors did not impair T or NK cell viability, phenotype, or effector function. We engineered second-generation CLEC12A-directed CAR T cells that efficiently eliminated CLEC12A-positive AML. Across in vitro systems and xenograft models, the combination therapy consistently outperformed either monotherapy, resulting in profound disease control and significantly prolonged survival, with evidence of near-complete leukemia eradication in vivo. These findings support epigenetic priming with menin inhibitors to enhance CLEC12A-directed CAR cell-therapy in these AML subtypes. SignificanceMenin inhibitors, now approved for AML treatment, induce the immune target CLEC12A in NPM1mut and KMT2A-r AML subtypes and sensitize AML cells to CLEC12A-directed CAR T cells without compromising immune function. As CLEC12A-CARs are already in clinical testing, this combination is immediately actionable for clinical investigation.

cancer biology↗

bioRxiv2026

Decoding Radiation-Induced Transcriptomic Signatures of Whole Blood Using Long-Read RNA-Seq: Clinical and Biodosimetric Implications

Background: Gene expression profiling in radiation-exposed blood is a valuable tool for biodosimetry and clinical research. Evaluating the blood's transcriptomic radiation response provides insight into absorbed dose, hematotoxicities, and immune reactions. However, detailed analysis using long-read RNA sequencing is currently limited in its diffusion, despite the potential additional insights that could be extracted, including novel isoform discovery and on-the-field gene expression studies, owing to its portability. Results: In this study, we utilized Oxford Nanopore Technologies' long-read RNA sequencing on human peripheral blood leukocytes from three healthy donors 6 hours after exposure of whole peripheral blood to 4 Gy of X-rays. Compared to sham-irradiated (0 Gy) blood samples, gene-level differential expression analysis identified 117 upregulated and 66 downregulated genes, including canonical DNA damage repair and inflammatory responses. At the transcript level, 102 transcripts were significantly upregulated, and 17 were downregulated, revealing isoform-specific regulation that was not captured at the gene level. Notably, IL32, which was not detected as significantly changed at the gene level, exhibited significant upregulation of two transcript isoforms (log2 fold-changes of 1.19 and 1.99), while WDR74, ITM2B, AK2, and RPS19 displayed changes in transcript usage following irradiation. Leveraging long-read RNA sequencing, we further identified novel candidate isoforms, including protein-coding isoforms of PHPT1 and FBXO22 as well as non-coding candidates. Notably, the FBXO22 isoform showed evidence of altered protein domain architecture relative to the reference isoform. Conclusions: This study is the first to systematically investigate differential transcript usage in the leukocyte fraction of irradiated human whole blood using long-read RNA sequencing. We confirmed known radiation-response signatures at the gene level and identified isoform-level transcriptomic changes, including several isoforms that were undetectable in our previously generated matched short-read dataset. These findings demonstrate the potential of long-read RNA sequencing to provide a more detailed view of radiation-induced transcriptomic alterations, with potential applications in biodosimetry and clinical settings.

biophysics↗

bioRxiv2025

DoReMiTra: An R/Bioconductor data package for orchestrating the analysis of radiation transcriptomic studies

SummaryUnderstanding the molecular impact of ionizing radiation exposure is essential for both biomedical research and public health. Among the possible approaches to study this phenomenon, gene expression profiling via transcriptomics assays has been a valuable approach over the last decades to unravel the mechanisms of cellular responses to radiation. To our knowledge, there is no data package gathering well-curated radiation transcriptomic datasets covering microarrays and, more recently, RNA sequencing. Therefore, we present DoReMiTra, an R/Bioconductor data package that represents the first unified radiation transcriptomics dataset collection integrated with Bioconductors ExperimentHub for efficient distribution. DoReMiTra standardizes and harmonizes sample-level metadata and provides pre-processed SummarizedExperiment (SE) objects to facilitate comparative analyses. Additionally, we introduce a lightweight Shiny app interface for interactive visualization and preliminary exploration. DoReMiTra serves as a valuable resource and tool in radiation research for benchmarking, integrative analyses, and biomarker discovery. Availability and ImplementationDoReMiTra is available under the MIT license at https://bioconductor.org/packages/DoReMiTra.

bioinformatics↗

bioRxiv2025

KDM6B inhibition modulates monocyte activation and alleviates IMQ-psoriasis skin inflammation

Inflammatory monocytes are increasingly recognized as key amplifiers of psoriasis, yet the epigenetic drivers of their pathogenic signature remain unclear. Here, we demonstrate that the histone demethylase KDM6B is markedly upregulated and catalytically active in classical monocytes during the imiquimod (IMQ)-induced psoriasis model. This is associated with reduced levels of the repressive histone mark H3K27me3, an epigenetic modification linked to chromatin compaction and transcriptional silencing, at the Il1b, Tnf, Pgam1, Pgk1, and Aldoa promoters, together with an enhanced inflammatory and glycolytic gene signature. Pharmacological blockade of KDM6B after disease onset using GSK-J4, a cell-permeable prodrug that is intracellularly converted to the active KDM6B inhibitor GSK-J1, restores H3K27me3 at inflammatory and metabolic loci, suppresses Il1b/Tnf transcription, normalizes bioenergetic profiles, and reduces monocyte and neutrophil recruitment to the inflamed skin. Single-cell transcriptomic profiling further reveals that KDM6B inhibition represses cytokine-mediated signaling, glycolysis, and chemotaxis pathways in monocytes, yet enriches antigen presentation modules, consistent with a shift toward a homeostatic, antigen-presenting surveillance program in myeloid cells and a Treg-supportive milieu. Collectively, our data identify KDM6B as an epigenetic-metabolic switch that sustains monocyte-driven inflammation in the IMQ-induced psoriasis model. Importantly, we provide preclinical evidence that targeting KDM6B can reduce maladaptive inflammatory response even in progressed diseases. These findings propose KDM6B inhibitors as a promising adjunct to current biologics for psoriasis and other myeloid-driven autoinflammatory disorders. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=178 HEIGHT=200 SRC="FIGDIR/small/682023v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@efef15org.highwire.dtl.DTLVardef@395983org.highwire.dtl.DTLVardef@123e832org.highwire.dtl.DTLVardef@615f84_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

GeDi: Simplifying Gene Set Distances for Enhanced Omics Interpretation in R/Bioconductor

BackgroundFunctional enrichment analysis is a standard component in many omics data analysis workflows, supported by a variety of methods and algorithms. However, despite their utility and wide application, these methods often return the results as an extensive and redundant list of gene sets, impeding interpretation and hypothesis generation. Moreover, network based information can provide additional biological context through functional interaction data, yet this is often overlooked by existing tools. ResultsWe developed GeDi, an R/Bioconductor package designed to streamline and standardize the interpretation of functional enrichment results. GeDi aggregates gene sets into biologically meaningful clusters using a suite of gene set distance metrics and clustering algorithms, aimed to reduce redundancy and improve clarity. GeDi also enables the integration of protein-protein interaction (PPI) data, through the implementation of a weighted distance metric, providing a richer biological context by capturing functional connectivity between pathways and their components. The package offers visualizations, aggregation, and automated reporting, and is available as both a stand-alone R-package and an interactive Shiny application. ConclusionGeDi facilitates clearer, faster interpretation of enrichment results by combining clustering and network context. Application to a public RNA-seq dataset revealed coherent biological themes, supporting both experimental and computational research. GeDi is freely available in the Bioconductor project under the MIT license (https://bioconductor.org/packages/GeDi), and a demo instance is accessible on the Shiny server (http://shiny.imbei.uni-mainz.de:3838/GeDi).

bioinformatics↗

bioRxiv2025

Target-site Dynamics and Alternative Polyadenylation Explain Large Share of Apparent MicroRNA Differential Expression

MicroRNA (miRNA) abundance reflects a dynamic balance between biogenesis, target engagement, and decay, yet differential expression analyses typically ignore changes in target-site availability driven by alternative polyadenylation (APA). We introduce MIRNAPEX, an expression-stratification-based machine learning framework that quantifies miRNA regulatory effect sizes from RNA-seq data by integrating target-gene expression with 3'UTR isoform usage to infer effective binding-site dosage. Using pan-cancer training sets, we train models that learn relationships between transcriptomic features and miRNA log-fold changes, with APA patterns providing predictive information beyond gene expression alone. When applied to knockdowns of core APA regulators, MIRNAPEX captured widespread 3'UTR shortening and accurately anticipated miRNA-specific shifts whose direction and magnitude mirrored APA-driven changes in binding-site availability. Analysis of target-directed miRNA degradation interactions further showed that loss of distal decay-trigger sites coincides with increased miRNA abundance, consistent with reduced degradation. Together, these findings demonstrate that apparent miRNA differential expression can arise from dynamic target-site landscapes rather than altered miRNA transcription, and that neglecting this dimension can lead to misestimation of regulatory effect sizes.

bioinformatics↗

bioRxiv2025

Characterization of the TREM-1 Signaling Landscape in Human Neutrophils

The Triggering Receptor Expressed on Myeloid Cells (TREM)-1 is a member of the Immunoglobulin superfamily, and an activating receptor mainly expressed on myeloid cells. Beyond its role in acute and chronic inflammatory processes, TREM-1 is also involved in cancer emergence and progression probably by alteration of the tumor-associated neutrophils (TAN) and macrophages (TAM). Advanced information about the TREM-1 signaling cascade may reveal novel targets for treating inflammatory and cancer diseases. As many specific kinase inhibitors are approved for treating various diseases, targeting kinases being active after TREM-1 ligation serves as a promising approach. Therefore, we investigated the protein tyrosine kinome (PTK) and serine threonine kinome (STK) by kinome activity profiling of purified human neutrophils after TREM-1 activation. As TREM-1 interacts with Toll-like receptor (TLR) 4 signaling, we used TLR4-activation by LPS to define TREM-1 specific pathways. We found an increased kinome activity after receptor ligation and could predict individual kinases. To gain further insights into the signaling cascade, we additionally investigated the transcriptomic profile that made us available to link the kinome activity to the resulting transcriptomic profile. In sum, we revealed several signaling pathways being active after TREM-1 ligation that are associated with various biological processed and diseases. This study facilitates selecting kinase inhibitors for further validation with the aim of targeting TREM-1 signaling in various inflammatory or cancer disease conditions.

immunology↗

bioRxiv2025

Predicting GD2 expression across cancer types by the integration of pathway topology and transcriptome data

The disialoganglioside GD2 is a key cancer therapy target due to its overexpression in several cancer types and limited expression in normal tissues. We developed a computational framework integrating reaction activity scores derived from transcriptomic data with glycosphingolipid biosynthesis pathway to predict GD2 expression. We labeled specific reactions as GD2-promoting or -mitigating, and used their cumulative activity as features to distinguish neuroblastoma from normal tissue. Predicted GD2 scores were validated by comparing them with literature-reported values and by assessing GD2 expression through flow cytometry in clear cell sarcoma of the kidney, which express GD2 at high level according to the GD2 scores. GD2 expression heterogeneity across cancer subtypes indicated patient subgroups potentially suitable for targeted therapy, and a role of B4GALNT1 amplification as a GD2 promoting factor. We offer our approach via the R package GD2Viz including also an interactive Shiny application and enable an enhanced processing of custom datasets.

cancer biology↗

bioRxiv2025

Single-cell chromatin landscape and DNA methylation patterns reveal shared molecular programs in human tumor and non-tumor tissue CCR8+ Treg cells

Regulatory T (Treg) cells, a subset of CD4+ T cells, play a crucial role in immunoregulation. Notably, CCR8-expressing Treg cells in tissues also contribute to organ homeostasis and repair. To determine whether these tissue-regenerative programs are active in the tumor microenvironment, we employed single-cell chromatin accessibility and genome-wide DNA methylation analyses to investigate CCR8+ tissue Treg cells isolated from human tumor and adjacent tumor-free tissues. Our findings indicate that CCR8+ tissue Treg cells from tumor and corresponding tumor-free tissues exhibit a high degree of similarity, suggesting that the tumor microenvironment may harbor highly activated tissue Treg cells. This observation was consistent across various tumor types and origins, including primary tumors and metastases. Using quantitative proteomics, we identified several candidate factors associated with the regenerative and suppressive programs of Treg cells, which may serve as potential reservoir of druggable targets for future therapeutic interventions.

immunology↗

bioRxiv2025

Genome-wide transcriptomic response of whole blood to radiation

The hematological system is impacted in nearly all ionizing radiation exposure scenarios. Whole transcriptome data offer detailed insights into bloods radiation response, crucial for radiotherapy and biodosimetry. We conducted genome-wide RNA-seq analysis on blood from three donors irradiated ex vivo with X-rays and incubated for 2h and 6h. Gene expression was subject to strong inter-donor variation and time post-exposure. After 0.5, 1, 2, and 4 Gy X-rays, 5, 33, 84, and 364 genes (2h) and 72, 99, 274, and 607 genes (6h) were differentially expressed (DEG), compared to 0 Gy. The corresponding number of the inferred transcription factors was 255, 253, 274, and 292 after 2h and 214, 245, 262, and 279 after 6h. In sham-irradiated blood, 924 DEGs and 165 transcription factors were affected by ex vivo incubation alone. We identified 34 radioresponsive DEGs not previously described, 8 and 9 showing significant positive or negative correlations with dose, respectively, including GPN1, MRM2, G0S2, and PTPRS. DNA damage signaling pathways were affected from the lowest dose, with doses [≥] 2 Gy additionally triggering proinflammatory responses. This first genome-wide RNA-seq study of ex vivo X-ray-exposed human blood reveals novel radiosensitive genes, transcription factors, and pathways, enhancing the understanding of the consequences of diagnostic, therapeutic, or accidental exposures on the highly radioresponsive hematological system.

biophysics↗

bioRxiv2025

Overflooding Ratios in the Sterile Insect Technique: Toward Sustainable Management of Bagrada hilaris

The Sterile Insect Technique (SIT) is an eco-friendly control method that may prove effective against Bagrada hilaris, a pest native to India, Southeast Asia, and Middle and central Africa and reported as invasive in the southwestern USA, Hawaii, Mexico, South America, and two Mediterranean islands. This insect causes significant crop damage due to its intense feeding behavior and is currently managed almost exclusively with synthetic insecticides. In this context, SIT offers a promising alternative for controlling B. hilaris populations, provided that sufficient numbers of sterile males are continuously released. Based on this premise, we conducted a preliminary laboratory study to evaluate the overflooding ratio (OFR)--the proportion of non-irradiated to irradiated males required to suppress the populations fertility. We tested various OFRs (1:1, 1:2, 1:5, and 1:10), monitoring both the number of eggs laid and hatching rates. Our results show a significant decrease in fertility as the percentage of irradiated males increases. Among the ratios examined, 1:5 emerged as the most advantageous in terms of both reducing fertility and ease of application. Although further validation under field conditions is needed, our findings suggest that SIT could effectively contribute to an integrated management strategy for B. hilaris, reducing the reliance on chemical pesticides and supporting a more sustainable approach.

ecology↗

bioRxiv2025

Biphasic inflammation control by dedifferentiated fibroblasts enables axon regeneration after spinal cord injury in zebrafish

Fibrosis and persistent inflammation are interconnected processes that inhibit axon regeneration in the mammalian central nervous system (CNS). In zebrafish, by contrast, fibroblast-derived extracellular matrix deposition and inflammation facilitate regeneration. However, the regulatory cross-talk between fibroblasts and the innate immune system in the regenerating CNS is not understood. Here, we show that zebrafish fibroblasts possess a dual role in inducing and subsequently resolving inflammation, which are both essential for regeneration. We identify a transient, injury-specific cthrc1a+ fibroblast state with an inflammation-associated, less differentiated, and non-fibrotic profile. Induction of this fibroblast state precedes and contributes to the initiation of the inflammatory response. At the peak of neutrophil influx, cthrc1a+ fibroblasts coordinate the resolution of inflammation. Disruption of these inflammation dynamics inhibits axon regeneration and alters the mechano-structural properties of the lesion environment. This establishes the biphasic inflammation control by dedifferentiated fibroblasts as a pivotal mechanism for CNS regeneration. ONE SENTENCE SUMMARYDedifferentiated fibroblasts sequentially induce and resolve neutrophil-driven inflammation through cytokine release to facilitate axon regeneration after spinal cord injury in zebrafish. HIGHLIGHTSO_LITime-resolved single-cell transcriptomics of zebrafish spinal cord regeneration. C_LIO_LISpinal cord injury induces fibroblast dedifferentiation. C_LIO_LIDedifferentiated fibroblasts sequentially induce and resolve inflammation. C_LIO_LIDysregulation of inflammation dynamics alters mechano-structural tissue properties. C_LI

neuroscience↗

bioRxiv2025

Cholangiocytes contribute to hepatocyte regeneration after partial liver injury during growth spurt in zebrafish

The livers regenerative ability depends on injury extent. Minor injuries are repaired by hepatocyte self-duplication, while severe damage triggers cholangiocyte involvement in hepatocyte recovery. This paradigm is well-documented for adult animals but is less explored during rapid growth. We design two new partial liver injury models in zebrafish, which were investigated during growth spurts: 1) partial ablation, killing half the hepatocytes; and 2) partial hepatectomy, removing half a liver lobe. In both injuries, de novo hepatocytes emerged alongside existing ones. Single-cell transcriptomics and lineage tracing with Cre-driver lines generated by genome editing identified cholangiocytes as the source of de novo hepatocytes. We further identify active mTORC1 signalling in the uninjured liver of growing animal to be a regulator of the enhanced plasticity of cholangiocytes. Our study suggests cholangiocyte-to-hepatocyte transdifferentiation as the primary mechanism of liver regeneration during periods of rapid growth.

developmental biology↗

bioRxiv2024

A comprehensive workflow for allele-specific immune gene quantification and expression analysis in single-cell RNA-seq data

MotivationImmune molecules such as B and T cell receptors, human leukocyte antigens (HLAs), or killer Ig-like receptors (KIRs) are encoded in the most genetically diverse loci of the human genome. Many of these immune genes exhibit remarkable allelic diversity across populations. While computational methods for HLA typing from bulk RNA sequencing data have emerged, streamlined solutions for allele-specific quantification in single-cell RNA sequencing (scRNA-seq) are lacking. Moreover, no standardized data structure or analytical framework has been established to handle allele-specific immune gene expression data at single-cell level. ResultsWe present a comprehensive workflow to (1) automate allele-typing and allele-specific expression quantification of HLA transcripts in scRNA-seq data using a Snakemake workflow, scIGD (single-cell ImmunoGenomic Diversity), and (2) represent and interactively explore immune gene expression at different annotation levels using a multi-layer data structure implemented as an R/Bioconductor software package, SingleCellAlleleExperiment. We validated our approach on a diverse spectrum of scRNA-seq datasets, and found that it performs consistently across different sequencing platforms and experimental setups. We illustrate how our method can be utilized to study loss of HLA expression in tumor cells or discover differential HLA allele expression in specific immune cell subtypes. By capturing such allele-specific expression patterns and their variation, our workflow offers novel insights into human immunogenomic diversity. Availability and implementationscIGD is available under the MIT license at: https://github.com/AGImkeller/scIGD. SingleCellAlleleExperiment is available under the MIT license at: https://bioconductor.org/packages/SingleCellAlleleExperiment. scaeData provides validation datasets and is available under the MIT license at: https://bioconductor.org/packages/scaeData. Data processed with scIGD are available at: https://doi.org/10.5281/zenodo.14033960. ContactKatharina Imkeller. E-mail: imkeller@rz.uni-frankfurt.de. Supplementary informationSupplementary data are available within the same submission.

bioinformatics↗

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

Benchmarking second-generation methods for cell-type deconvolution of transcriptomic data

BackgroundIn silico cell-type deconvolution from bulk transcriptomics data is a powerful technique to gain insights into the cellular composition of complex tissues. While first-generation methods used precomputed expression signatures covering limited cell types and tissues, second-generation tools use single-cell RNA sequencing data to build custom signatures for deconvoluting arbitrary cell types, tissues, and organisms. This flexibility poses significant challenges in assessing their deconvolution performance. ResultsHere, we comprehensively benchmark second-generation tools, disentangling different sources of variation and bias using a diverse panel of real and simulated data. Our results reveal substantial differences in accuracy, scalability, and robustness across methods, depending on factors such as cell-type similarity, reference composition, and dataset origin. Conclusions.Our study highlights the strengths, limitations, and complementarity of state-of-the-art tools, shedding light on how different data characteristics and confounders impact deconvolution performance. We provide the scientific community with an ecosystem of tools and resources, omnideconv, simplifying the application, benchmarking, and optimization of deconvolution methods.

bioinformatics↗

bioRxiv2023

Extensible benchmarking of methods that identify and quantify polyadenylation sites from RNA-seq data

The tremendous rate with which data is generated and analysis methods emerge makes it increasingly difficult to keep track of their domain of applicability, assumptions, and limitations and consequently, of the efficacy and precision with which they solve specific tasks. Therefore, there is an increasing need for benchmarks, and for the provision of infrastructure for continuous method evaluation. APAeval is an international community effort, organized by the RNA Society in 2021, to benchmark tools for the identification and quantification of the usage of alternative polyadenylation (APA) sites from short-read, bulk RNA-sequencing (RNA-seq) data. Here, we reviewed 17 tools and benchmarked eight on their ability to perform APA identification and quantification, using a comprehensive set of RNA-seq experiments comprising real, synthetic, and matched 3'-end sequencing data. To support continuous benchmarking, we have incorporated the results into the OpenEBench online platform, which allows for seamless extension of the set of methods, metrics, and challenges. We envisage that our analyses will assist researchers in selecting the appropriate tools for their studies. Furthermore, the containers and reproducible workflows generated in the course of this project can be seamlessly deployed and extended in the future to evaluate new methods or datasets.

bioinformatics↗