Biology subjects

Schmid, K.

Publications and source records attributed to Schmid, K..

11 recordsLinked to original sources

bioRxiv2026

XplainTDA: Explaining the topological structure of single-cell multi-omics data through perturbation

Single-cell experiments have improved our ability to study biological systems by profiling thousands of cells simultaneously. The data can be viewed as a point cloud in a proper experimental space, whose shape is defined by the gene regulatory network. Persistent homology has been proposed as a method for studying the intrinsic structure of data and has shown the potential to reveal novel insights. Existing approaches focus on detecting topological features or groups of cells, without a focus on explainability and interpretability. Here, we introduce an explainable topological data analysis framework for single-cell data (XplainTDA) that identifies molecular determinants underlying the topological structure of the data via a perturbation-based approach. Across omics and data sets, we show that the method is stable, reproducible, and interpretable, extending persistent homology from topological description to molecular interpretation.

bioinformatics↗

bioRxiv2026

The Nature of Centromeric Repeat Turnovers in the genus Arabidopsis

Centromeres are critical for accurate segregation of chromosomes and are often composed of megabases of tandemly arranged satellite repeats. Yet, despite their conserved function, the DNA sequence of centromeres is, paradoxically, rapidly evolving. To understand the nature of centromeric sequence turnover, we assembled 417 centromeres from nine species representing the entire Arabidopsis genus. In the genus, centromeres are formed by four main satellite repeats with homologous sequences forming central arrays and minor repeat types. We identify the ancestral centromeric repeat type for the Arabidopsis genus and three independent turnovers to different repeats: (1) a complete turnover in A. thaliana, (2) a turnover of seven out of the eight centromeres in the ancestor of A. cebennensis and A. pedemontana, (3) turnovers of three to five centromeres in the genomes of A. halleri and A. lyrata. Most centromeric repeats are also present throughout the genome with shared syntenic locations between Arabidopsis species, and some being similar to parts of transposable elements and genes, suggesting that centromeric repeats originate outside of the centromeres. In allotetraploid A. suecica we find that the repeats from centromeric arrays on one subgenome can transpose and invade the other, likely via transposable element activity. All four main centromeric repeats can recruit the CENH3 (CENP-A) histone variant, however, when a new repeat successfully proliferates in an old array, CENH3 is primarily recruited to the new array marking functional take over. Complete centromeric turnovers occurred in species that experienced severe bottlenecks in their evolutionary history, where new centromeric alleles may have been fixed by genetic drift. Yet, we also observe segregation distortion between two different centromeric repeat types in A. lyrata, suggestive of centromere drive and we propose that both drift and drive contribute to centromeric repeat turnover. Together, our findings reveal the origin of centromeric repeats, mechanisms of repeat proliferation and spread, and the evolutionary dynamics of centromeric repeat turnovers in the Arabidopsis genus.

evolutionary biology↗

bioRxiv2026

Prolonged TGF-β locks NK cells in a dysfunctional state through persistent epigenetic remodeling of IRF, T-bet and EOMES binding sites

TGF-{beta} signaling is a major regulator of immune cell differentiation and function, yet whether prolonged signaling can durably imprint dysfunctional immune states independently of continued pathway engagement remains unclear. Here, we identify signal duration as a critical determinant of human natural killer (NK) cell fate: short-term TGF-{beta} exposure induces largely reversible transcriptional, chromatin and functional changes, whereas prolonged exposure establishes persistent effector dysfunction independent of continued signaling. Mechanistically, prolonged TGF-{beta} drives durable loss of chromatin accessibility at effector-associated regulatory elements, particularly those enriched for IRF, EOMES, and T-bet binding motifs, resulting in stable restriction of NK cell effector programs despite reversibility of active histone marks. In contrast, tissue residency-associated programs remain largely reversible, revealing that distinct NK cell fate programs differ fundamentally in their susceptibility to epigenetic fixation downstream of the same cytokine signal. SMAD4 CUT&RUN and knockout experiments further demonstrate that canonical TGF-{beta} signaling acts primarily through rewiring of upstream transcriptional regulatory networks rather than direct targeting of effector loci. Finally, NK cells from patients with hepatocellular carcinoma recapitulate key functional and epigenetic features of the persistent TGF-{beta}-associated state defined in vitro. Together, these findings identify signal duration as a critical determinant of TGF-{beta}-driven cell fate and demonstrate that prolonged TGF-{beta} exposure can induce epigenetically stabilized dysfunctional states that persist after signal withdrawal, with important implications for therapeutic strategies aimed at reversing chronic TGF-{beta}-mediated dysfunction.

immunology↗

bioRxiv2024

Inference of alveolar capillary network connectivity from blood flow dynamics

The intricate structure of the lungs is essential for the gas exchange within the alveolar region. Despite extensive research on the pulmonary vasculature, there are still unresolved questions regarding the connection between capillaries and the vascular tree. A major challenge is obtaining comprehensive experimental data that integrates morphological and physiological aspects. We propose a computational approach that combines data-driven 3D morphological modeling with computational fluid dynamics simulations. This method enables investigating the connectivity of the alveolar capillary network with the vascular tree based on the dynamics of blood flow. We developed 3D sheet-flow models to accurately represent the morphology of the alveolar capillary network and conducted computational fluid dynamics simulations to predict flow velocities and pressure distributions. Our approach focuses on leveraging functional features to identify the most plausible architecture of the system. For given capillary flow velocities and arteriole-to-venule pressure drops, we deduce details about arteriole connectivity. Preliminary connectivity analyses for non-human species indicate that their alveolar capillary network of a single alveolus is linked to at least two arterioles with diameters of 20 {micro}m or a single arteriole with a minimum diameter of 30 {micro}m. Our study provides insights into the structure of the pulmonary microvasculature by evaluating blood flow dynamics. This inverse approach represents a new strategy to exploit the intricate relationship between morphology and physiology, applicable to other tissues and organs. In the future, the availability of experimental data will play a pivotal role in validating and refining the hypotheses analyzed with our computational models. New and noteworthyThe alveolus is pivotal for gas exchange. Due to its complex morphology and dynamic nature, structural experimental studies are challenging. Computational modeling offers an alternative. We developed a databased 3D model of the alveolar capillary network and performed blood flow simulations within it. Choosing a novel perspective, we inferred structure from function. We systematically varied properties of vessels connected to our capillary network and compared simulation results with experimental data to obtain plausible vessel configurations.

physiology↗

bioRxiv2023

Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

The combination of brain organoid and single cell omic technologies holds transformative potential to dissect human neurobiology at high resolution and with mechanistic precision. Delivering this promise in the context of human neurodiversity, physiological and pathological alike, requires however a major leap in scalability, given the need for experimental designs that include multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we implemented and benchmarked complementary strategies to multiplex brain organoids. Following an extended longitudinal design with a uniquely informative set of timepoints, we pooled cells from different induced pluripotent stem cell lines either during organoids generation (upstream multiplexing in mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We developed a new method, SCanSNP, and an aggregated call to deconvolve organoids cell identities, overcoming current criticalities in doublets prediction and low quality cells identification and improving accuracy over state of the art algorithms. Integrating single cell transcriptomes and analysing cell types across neurodevelopmental stages and multiplexing modalities, we validated the feasibility of both multiplexing methods in charting neurodevelopmental trajectories at high resolution, linking their specificity to genetic variation between individual lines. Together, this multiplexing suite of experimental and computational methods provides an enabling resource for disease modelling at scale and paves the way towards an in vitro epidemiology paradigm.

neuroscience↗

bioRxiv2023

GGoutlieR: an R package to identify and visualize unusual geo-genetic patterns of biological samples

Landscape genomics is an emerging field of research that integrates genomic and environmental information to explore the drivers of evolution. Reliable data on the geographical origin of biological samples is a prerequisite for accurate landscape genomics studies. Traditionally, researchers discover potentially questionable samples using visualization-based tools. However, such approaches cannot handle large sample sizes due to overlapping data points on a graph and can hinder reproducible research. To address this shortcoming, we developed Geo-Genetic outlier (GGoutlieR), an R package of a heuristic framework for detecting and visualizing samples with unusual geo-genetic patterns. Outliers are identified by calculating empirical p-values for each sample, allowing users to identify them in data sets with thousands of samples. The package also provides a plotting function to display the geo-genetic patterns of outliers on a geographical map. GGoutlieR could significantly reduce the amount of data cleaning that researchers need to do before carrying out landscape genomics analyses.

bioinformatics↗

bioRxiv2022

Deep haplotype analyses of target-site resistance locus ACCase in blackgrass enabled by pool-based amplicon sequencing

Rapid adaptation of weeds to herbicide applications in agriculture through resistance development is a widespread phenomenon. In particular, the grass Alopecurus myosuroides is an extremely problematic weed in cereal crops with the potential to manifest resistance in the course of only a few generations. Target-site resistances (TSRs), with their strong phenotypic response, play an important role in this rapid adaptive response. Recently, using PacBios long-read amplicon sequencing technology in hundreds of individuals, we were able to decipher the genomic context in which TSR mutations occur. However, sequencing individual amplicons is both costly and time consuming, thus impractical to implement for other resistance loci or applications. Alternatively, pool-based approaches overcome these limitations and provide reliable allele frequencies, albeit at the expense of not preserving haplotype information. In this proof-of-concept study, we sequenced with PacBio High Fidelity (HiFi) reads long-range amplicons (13.2 kb) encompassing the entire ACCase gene in pools of over hundred individuals, and resolved them into haplotypes using the clustering algorithm PacBio amplicon analysis (pbaa), a new application for pools and for plants. From these amplicon pools, we were able to recover most haplotypes from previously sequenced individuals of the same population. In addition, we analyzed new pools from a Germany-wide collection of A. myosuroides populations and found that TSR mutations originating from soft sweeps of independent origin were common. Forward-in-time simulations indicate that TSR haplotypes will persist for decades even at relatively low frequencies and without selection, pointing to the importance of accurate measurement of TSR haplotype prevalence for weed management.

genomics↗

bioRxiv2021

Standing genetic variation fuels rapid evolution of herbicide resistance in blackgrass

Repeated herbicide applications exert enormous selection on blackgrass (Alopecurus myosuroides), a major weed in cereal crops of the temperate climate zone including Europe. This inadvertent large-scale experiment gives us the opportunity to look into the underlying genetic mechanisms and evolutionary processes of rapid adaptation, which can occur both through mutations in the direct targets of herbicides and through changes in other, often metabolic, pathways, known as non-target-site resistance. How much either type of adaptation relies on de novo mutations versus pre-existing standing variation is important for developing strategies to manage herbicide resistance. We generated a chromosome-level reference genome for A. myosuroides for population genomic studies of herbicide resistance and genome-wide diversity across Europe in this species. Bulked-segregant analysis evidenced that non-target-site resistance has a complex genetic architecture. Through empirical data and simulations, we showed that, despite its simple genetics, target-site resistance mainly results from standing genetic variation, with only a minor role for de novo mutations.

evolutionary biology↗

bioRxiv2021

Interactive, visual simulation of a spatio-temporal model of gas exchange in the human alveolus

In interdisciplinary fields such as systems biology, close collaboration between experimentalists and theorists is crucial for the success of a project. Theoretical modeling in physiology usually describes complex systems with many interdependencies. On one hand, these models have to be grounded on experimental data. On the other hand, experimenters must be able to penetrate the model in its dependencies in order to correctly interpret the results in the physiological context. When theorists and experimenters collaborate, communicating results and ideas is sometimes challenging. We promote interactive, visual simulations as an engaging way to communicate theoretical models in physiology and to thereby advance our understanding of the process of interest. We defined a new spatio-temporal model for gas exchange in the human alveolus and implemented it in an interactive simulation software named Alvin. In Alvin, the course of the simulation can be traced in a three-dimensional rendering of an alveolus and dynamic plots. The user can interact by configuring essential model parameters. Alvin allows to run and compare multiple simulation instances simultaneously. The mathematical model was developed with the aim of visualization and the simulation software was engineered based on a requirements analysis. Our work resulted in an integrative gas exchange model and an interactive application that exceed the current standards. We exemplified the use of Alvin for research by identifying unknown dependencies in published experimental data. Employing a detailed questionnaire, we showed the benefits of Alvin for education. We postulate that interactive, visual simulation of theoretical models, as we have implemented with Alvin on respiratory processes in the alveolus, can be of great help for communication between specialists and thereby advancing research.

bioinformatics↗

bioRxiv2020

Genome-wide association study in the pseudocereal quinoa reveals selection pattern typical for crops with a short breeding history

Quinoa germplasm preserves useful and substantial genetic variation, yet it remains untapped due to a lack of implementation of modern breeding tools. We have integrated field and sequence data to characterize a large diversity panel of quinoa. Whole-genome sequencing of 310 accessions revealed 2.9 million polymorphic high confidence SNP loci. Highland and Lowland quinoa were clustered into two main groups, with FST divergence of 0.36 and fast LD decay of 6.5 and 49.8 Kb, respectively. A genome-wide association study uncovered 600 SNPs stably associated with 17 agronomic traits. Two candidate genes are associated with thousand seed weight, and a resistance gene analog is associated with downy mildew resistance. We also identified pleiotropically acting loci for four agronomic traits that are highly responding to photoperiod hence important for the adaptation to different environments. This work demonstrates the use of re-sequencing data of an orphan crop, which is partially domesticated to rapidly identify marker-trait association and provides the underpinning elements for genomics-enabled quinoa breeding.

genomics↗

bioRxiv2020

Structural basis for decoding active histone methylation marks by Polycomb Repressive Complex 2

Repression of genes by Polycomb requires that PRC2 modifies their chromatin by trimethylating lysine 27 on histone H3 (H3K27me3). At transcriptionally active genes, di- and trimethylated H3K36 inhibit PRC2. Here, the cryo-EM structure of PRC2 on dinucleosomes reveals how binding of its catalytic subunit EZH2 to nucleosomal DNA orients the H3 N-terminus via an extended network of interactions to place H3K27 into the active site. Unmodified H3K36 occupies a critical position in the EZH2-DNA interface. Mutation of H3K36 to arginine or alanine inhibits H3K27 methylation by PRC2 on nucleosomes in vitro. Accordingly, Drosophila H3K36A and H3K36R mutants show reduced levels of H3K27me3 and defective Polycomb repression of HOX genes. The relay of interactions between EZH2, the nucleosomal DNA and the H3 N-terminus therefore creates the geometry that permits allosteric inhibition of PRC2 by methylated H3K36 in transcriptionally active chromatin.

biochemistry↗