Biology subjects

Bagger, F. O.

Publications and source records attributed to Bagger, F. O..

9 recordsLinked to original sources

bioRxiv2026

Extrachromosomal circular DNA formation follows a 10.5-bp periodicity reflecting the minor groove orientation around nucleosomes

Extrachromosomal circular DNA is increasingly recognized as a central feature of somatic evolution in cancer, yet the structural determinants of eccDNA formation remain poorly understood. Here, we systematically analysed eccDNA length distributions and breakpoint organization across 25 datasets spanning multiple species, tissues and experimental approaches. Applying a short-time Fourier transform to eccDNA length distributions enabled us to resolve recurrent periodicities at approximately 180 bp and 10.5 bp, consistent with nucleosome length and the helical repeat of DNA, respectively. Mapping eccDNA breakpoints relative to nucleosome dyads revealed preferential breakpoint formation in linker DNA and, within nucleosome-bound DNA, at positions where the minor groove faces towards the histone surface. Our results show that eccDNA formation is shaped not only by nucleosome positioning but also by the rotational orientation of the DNA double helix around the nucleosome. Together, these findings identify chromatin geometry as a determinant of eccDNA biogenesis and provide a structural basis for the length periodicities that characterize eccDNA formation.

genomics↗

bioRxiv2026

Acquired resistance to immune checkpoint inhibitors is associated with hypoxia and ECM remodeling in colorectal cancer

Acquired resistance to immune checkpoint inhibitors (ICIs) limits the durability of therapeutic responses across multiple cancer types, yet the underlying mechanisms remain poorly defined. Using the murine MC38 colorectal cancer model, we established an in vivo model recapitulating clinical response patterns, including complete regression, primary resistance, and acquired resistance. Tumors with acquired resistance progressed after initial benefit from combined anti-PD-1 and anti-CTLA-4 therapy and maintained resistance upon retransplantation into naive hosts, indicating a cancer cell-intrinsic driver of resistance. Whole-genome sequencing showed no mutations in antigen presentation or IFN-{gamma} signaling pathways previously described in single clinical cases of acquired resistance, and functional assays confirmed preserved antigenicity and IFN-{gamma} responsiveness. Transcriptomic and metabolic profiling of resistant cancer cells instead revealed metabolic reprogramming characterized by enhanced mitochondrial respiration and enrichment of hypoxia-related gene signatures, suggesting cancer cell-intrinsic adaptations that reshape the tumor microenvironment. Tumors with acquired resistance exhibited an increase in tumor-associated macrophages, and these macrophages displayed enriched transcriptional signatures of hypoxia, angiogenesis, and extracellular matrix (ECM) remodeling. Proteomic analysis of ECM-enriched tumor fragments showed accumulation of proteoglycans and enzymes such as lysyl oxidase, consistent with active matrix-remodeling. These changes coincided with altered T cell activation characterized by reduced cytotoxic gene expression and decreased CD44 expression on tumor-infiltrating T cells, suggesting impaired effector functions within the resistant microenvironment. This study identifies non-genetic mechanisms of acquired resistance to ICIs and highlights metabolic and ECM remodeling programs as promising therapeutic targets to prevent or reverse acquired resistance to ICIs.

cancer biology↗

bioRxiv2024

Recommendations for Bioinformatics in Clinical Practice

Next Generation Sequencing (NGS) is increasingly used in clinical diagnostics, largely driven by the success and robustness of Whole Genome Sequencing (WGS). Whereas updated guidelines exist for how to interpret and report on variants that are identified from NGS using bioinformatics pipelines, there is a need for standardised bioinformatics practices for diagnostics to ensure clinical consensus, accuracy, reproducibility and comparability of the results. This article presents consensus recommendations developed by 13 clinical bioinformatics units taking part in the Nordic Alliance for Clinical Genomics (NACG), by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations. Key recommendations include adopting the hg38 genome build as the reference and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics production should operate under the ISO 15189 standard, utilising off-grid clinical-grade high-performance computing systems, standardised file formats, and strict code version control. Containerized software containers or environment management systems are needed to ensure reproducibility. Pipelines should be rigorously documented and tested for accuracy and reproducibility, minimally covering unit, integration, and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of previously validated clinical cases. Data integrity must be verified using file hashing, and sample identity should be checked via sample fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical bioinformatics teams should encompass diverse skills, including software development, data management, quality assurance, and domain expertise in human genetics. These recommendations provide a consensus framework for standardising bioinformatics practices across clinical WGS applications and can serve as a practical guide to facilities that are new to large-scale sequencing-based diagnostics, or as a reference for those who already run high-volume clinical production using NGS.

bioinformatics↗

bioRxiv2023

Building flexible and robust analysis frameworks for molecular subtyping of cancers

Molecular subtyping is essential to infer tumor aggressiveness and predict prognosis. In practice, tumor profiling requires in-depth knowledge of bioinformatics tools involved in the processing and analysis of the generated data. Additionally, data incompatibility (e.g., microarray vs. RNA sequencing data) and technical and uncharacterized biological variance between training and test data can pose challenges in classifying individual samples. In this article, we provide a roadmap for implementing bioinformatics frameworks for molecular profiling of human cancers in a clinical diagnostic setting. We describe a framework for integrating several methods for quality control, normalization, batch correction, classification, and reporting and a use case of the framework in breast cancer.

bioinformatics↗

bioRxiv2021

A comparison of tools for copy-number variation detection in germline whole exome and whole genome sequencing data

BackgroundCopy-number variations (CNVs) have important clinical implications for several diseases and cancers. The clinically relevant CNVs are hard to detect because CNVs are common structural variations that define large parts of the normal human genome. CNV calling from short-read sequencing data has the potential to leverage available cohort studies and allow full genomic profiling in the clinic without the need for additional data modalities. Questions regarding performance of CNV calling tools for clinical use and suitable sequencing protocols remain poorly addressed, mainly because of the lack of good reference data sets. MethodsWe reviewed 50 popular CNV calling tools and included 11 tools for benchmarking in a unique reference cohort encompassing 39 whole genome sequencing (WGS) samples paired with analysis by the current clinical standard --SNP-array based CNV calling. Additionally, for nine of these samples we performed whole exome sequencing (WES) performed, in order to address the effect of sequencing protocol on CNV calling. Furthermore, we included Gold Standard reference sample NA12878, and tested 12 samples with CNVs confirmed by multiplex ligation-dependent probe amplification (MLPA). ResultsTool performance varied greatly in the number of called CNVs and bias for CNV lengths. Some tools had near-perfect recall of CNVs from arrays for some samples, but poor precision. Filtering output by CNV ranks from tools did not salvage precision. Several tools had better performance patterns for NA12878, and we hypothesize that this is the result of overfitting during the tool development. ConclusionsWe suggest combining tools with the best recall: GATK gCNV, Lumpy, DELLY, and cn.MOPS. These tools also capture different CNVs. Further improvements in precision requires additional development of tools, reference data sets, and annotation of CNVs, potentially assisted by the use of background panels for filtering of frequently called variants.

bioinformatics↗

bioRxiv2020

Benchmarking full-length transcript single cell mRNA sequencing protocols

Single cell mRNA sequencing technologies have transformed our understanding of cellular heterogeneity and identity. For sensitive discovery or clinical marker estimation where high transcript capture per cell is needed only plate-based techniques currently offer sufficient resolution. Here, we present a performance evaluation of three different plate-based scRNA-seq protocols. Our evaluation is aimed towards applications requiring high gene detection sensitivity, reproducibility between samples, and minimum hands-on time, as is required, for example, in clinical use. We included two commercial kits, NEBNext(R) Single Cell/ Low Input RNA Library Prep Kit (NEB(R)), SMART-seq(R) HT kit (Takara(R)), and the non-commercial protocol Genome & Transcriptome sequencing (G&T). G&T delivered the highest detection of genes per single cell, at the absolute lowest price. Takara(R) kit presented similar high gene detection per single cell, and high reproducibility between sample, but at the absolute highest price. NEB(R) delivered a lower detection of genes but remain an alternative to more expensive commercial kits.

molecular biology↗

bioRxiv2020

COVID-19 Vaccine Candidates: Prediction and Validation of 174 SARS-CoV-2 Epitopes

The recent outbreak of SARS-CoV-2 (2019-nCoV) virus has highlighted the need for fast and efficacious vaccine development. Stimulation of a proper immune response that leads to protection is highly dependent on presentation of epitopes to circulating T-cells via the HLA complex. SARS-CoV-2 is a large RNA virus and testing of all overlapping peptides in vitro to deconvolute an immune response is not feasible. Therefore HLA-binding prediction tools are often used to narrow down the number of peptides to test. We tested 19 epitope-HLA-binding prediction tools, and using an in vitro peptide MHC stability assay, we assessed 777 peptides that were predicted to be good binders across 11 MHC allotypes. In this investigation of potential SARS-CoV-2 epitopes we found that current prediction tools vary in performance when assessing binding stability, and they are highly dependent on the MHC allotype in question. Designing a COVID-19 vaccine where only a few epitope targets are included is therefore a very challenging task. Here, we present 174 SARS-CoV-2 epitopes with high prediction binding scores, validated to bind stably to 11 HLA allotypes. Our findings may contribute to the design of an efficacious vaccine against COVID-19.

immunology↗

bioRxiv2019

Single mRNP analysis by super-resolution microscopy and fluorescence correlation spectroscopy reveals that small mRNP granules represent mRNA singletons

Small cytoplasmic mRNP granules are implicated in mRNA transport, translational control and decay. Employing Super-resolution Microscopy and Fluorescence Correlation Spectroscopy, we analyzed the molecular composition and dynamics of single cytoplasmic YBX1_IMP1 mRNP granules in live cells. Granules appeared elongated and branched with patches of IMP1 and YBX1 distributed along mRNA, reflecting the attachment of the two RNA-binding proteins in cis. Particles form at the nuclear pore and are spatially segregated from translating ribosomes, so the mRNP is a repository for mRNAs awaiting translation. Individual mRNPs contain a single mRNA and 5 to 15 molecules of YBX1 and IMP1, which is in agreement with the average number of mRNA-binding sites calculated from CLIP analyses. We conclude that small cytoplasmic mRNP granules are mRNA singletons, thus depicting the cellular transcriptome. Consequently, expression of functionally related mRNAs in RNA regulons is unlikely to result from coordinated assembly. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Graphical abstract C_FIG_DISPLAY

molecular biology↗

bioRxiv2016

Genome-wide Analysis of Differential Transcriptional and Epigenetic Variability Across Human Immune Cell Types

BackgroundA healthy immune system requires immune cells that adapt rapidly to environmental challenges. This phenotypic plasticity can be mediated by transcriptional and epigenetic variability.\n\nResultsWe applied a novel analytical approach to measure and compare transcriptional and epigenetic variability genome-wide across CD14+CD16- monocytes, CD66b+CD16+ neutrophils, and CD4+CD45RA+ naive T cells, from the same 125 healthy individuals. We discovered substantially increased variability in neutrophils compared to monocytes and T cells. In neutrophils, genes with hypervariable expression were found to be implicated in key immune pathways and to associate with cellular properties and environmental exposure. We also observed increased sex-specific gene expression differences in neutrophils. Neutrophil-specific DNA methylation hypervariable sites were enriched at dynamic chromatin regions and active enhancers.\n\nConclusionsOur data highlight the importance of transcriptional and epigenetic variability for the neutrophils key role as the first responders to inflammatory stimuli. We provide a resource to enable further functional studies into the plasticity of immune cells, which can be accessed from: http://blueprint-dev.bioinfo.cnio.es/WP10/hypervariability.

molecular biology↗