Biology subjects

Thodberg, M.

Publications and source records attributed to Thodberg, M..

5 recordsLinked to original sources

bioRxiv2026

multiomeR: a pipeline for reproducible analysis of large-scale single-nucleus Epi Multiome datasets

The 10x Genomics Epi Multiome assay measures gene expression and chromatin accessibility in the same nuclei, and studies increasingly profile many samples. Yet analysis after Cell Ranger ARC is usually assembled by hand from separate tools, which makes it slow to revise, hard to reproduce and memory-intensive for large studies. multiomeR addresses these problems with a configurable R pipeline for quality control, processing and integration of both data types, and cell-type annotation across many samples. Plain-text configuration files record every analytical choice, each step is tracked so that a change reruns only what it affects, and data stay on disk rather than in memory. Optional modules compare groups of donors, link accessible regions to the genes they may regulate, and test which cell types are enriched for genetic associations with a trait. In a benchmark on 31 public samples (375,757 nuclei), multiomeR had a shorter estimated run time than a Seurat v5.6/Signac v2 workflow (2.2 versus 5.6 h), because it runs independent steps in parallel. It also used fewer memory gigabyte-hours (87 versus 114 GB-hours), with similar total CPU time. multiomeR thus makes large multi-sample multiome studies practical to analyze, revise and extend.

bioinformatics↗

bioRxiv2026

Mapping active cis-regulatory elements from transcription initiation events

Determining the activity of cis-regulatory elements (CREs) is essential for modeling gene regulation and interpreting genetic variation. Yet, current methods often lack the specificity to distinguish active regulation from permissive chromatin, the sensitivity to detect unstable enhancer RNAs, or the scalability required to profile limited input material and primary cells. Here, we introduce nucCAGE, a transcription start site (TSS) assay for profiling nuclear, capped RNAs, and PRIME, a computational framework for identifying active CREs from TSS data. Together, these methods increase sensitivity to low-abundance RNAs and enable robust detection of active regulatory elements across diverse contexts. Across multiple orthogonal functional and genetic benchmarks, including fine-mapped eQTLs, ClinVar variants, GWAS loci, and CRISPRi-tested elements, nucCAGE-derived PRIME predictions achieve superior recall compared to state-of-the-art methods while maintaining strong enrichment for phenotype-associated variation. Applying PRIME to the FANTOM5 dataset yields a comprehensive, cell-type-resolved atlas of active CREs that recapitulates known tissue-trait relationships. We demonstrate how this atlas can be used to nominate causal noncoding variants, linking immune-cell enhancer regulation of SMAD3 to asthma and NCOR2 to premature separation of placenta. Together, nucCAGE and PRIME provide a framework for high-sensitivity genome-wide discovery of active CREs and a resource for variant-to-function studies.

genomics↗

bioRxiv2021

Genome-wide association study on 13,167 individuals identifies regulators of hematopoietic stem and progenitor cell levels in human blood

Understanding how hematopoietic stem and progenitor cells (HSPCs) are regulated is of central importance for the development of new therapies for blood disorders and stem cell transplantation. To date, HSPC regulation has been extensively studied in vitro and in animal models, but less is known about the mechanisms in vivo in humans. Here, in a genome-wide association study on 13,167 individuals, we identify 9 significant and 2 suggestive DNA sequence variants that influence HSPC (CD34+) levels in human blood. The identified loci associate with blood disorders, harbor known and novel HSPC genes, and affect gene expression in HSPCs. Interestingly, our strongest association maps to the PPM1H gene, encoding an evolutionarily conserved serine/threonine phosphatase never previously implicated in stem cell biology. PPM1H is expressed in HSPCs, and the allele that confers higher blood CD34+ cell levels downregulates PPM1H. By functional fine-mapping, we find that this downregulation is caused by the variant rs772557-A, which abrogates a MYB transcription factor binding site in PPM1H intron 1 that is active in specific HSPC subpopulations, including hematopoietic stem cells, and interacts with the promoter by chromatin looping. Furthermore, rs772557-A selectively increases HSPC subpopulations in which the MYB site is active, and PPM1H shRNA- knockdown increased CD34+ and CD34+90+ cell proportions in umbilical cord blood cultures. Our findings represent the first large-scale association study on a stem cell trait, illuminating HSPC regulation in vivo in humans, and identifying PPM1H as a novel inhibition target that can potentially be utilized clinically to facilitate stem cell harvesting for transplantation.

genomics↗

bioRxiv2018

CAGEfightR: Cap Analysis of Gene Expression (CAGE) in R/Bioconductor

We developed the CAGEfightR R/Biconductor-package for analyzing CAGE data. CAGEfightR allows for fast and memory efficient identification of transcription start sites (TSSs) and predicted enhancers. Downstream analysis, including annotation, quantification, visualization and TSS shape statistics are implemented in easy-to-use functions. The package is freely available at https://bioconductor.org/packages/CAGEfightR

bioinformatics↗

bioRxiv2018

Comprehensive profiling of the fission yeast transcription start site activity during stress and media response

Fission yeast, Schizosaccharomyces pombe, is an attractive model organism for transcriptional and chromatin biology research. Such research is contingent on accurate annotation of transcription start sites (TSSs). However, comprehensive genome-wide maps of TSSs and their usage across commonly applied laboratory conditions and treatments for S. pombe are lacking. To this end, we profiled TSS activity genome-wide in S. pombe cultures exposed to heat shock, nitrogen starvation, hydrogen peroxide and two commonly applied media, YES and EMM2, using Cap Analysis of Gene Expression (CAGE). CAGE-based annotation of TSSs is substantially more accurate than existing PomBase annotation; on average, CAGE TSSs fall 50-75 bp downstream of PomBase TSSs and co-localize with nucleosome boundaries. In contrast to higher eukaryotes, S. pombe does not show sharp and dispersed TSS distributions. Our data recapitulate known S. pombe stress expression response patterns and identify stress- and mediaresponsive alternative TSSs. Notably, alteration of growth medium induces changes of similar magnitude as some stressors. We show a link between nucleosome occupancy and genetic variation, and that the proximal promoter region is genetically diverse between S. pombe strains. Our detailed TSS map constitute a central resource for S. pombe gene regulation research.

genomics↗