Biology subjects

Heinen, T.

Publications and source records attributed to Heinen, T..

5 recordsLinked to original sources

bioRxiv2026

Mapping trans-eQTLs at single-cell resolution using Latent Interaction Variational Inference.

Single-cell expression quantitative trait loci (eQTL) studies hold promise for linking genetic variants to changes in gene expression in individual cells, thereby offering deeper insights into the genetic basis of human traits and diseases. Existing methods for mapping cis effects rely on predefined cell types, pseudobulk aggregation, or single-gene association tests, and are thus limited in their ability to detect complex trans effects that act across gene networks and cell-type subpopulations. Here, we present Latent Interaction Variational Inference (LIVI), an interpretable deep learning framework for efficient mapping of trans genetic effects at cellular resolution. LIVI employs a structured sparse variational autoencoder architecture to decompose observed gene expression profiles into cell-state- and donor-specific variation. The model enables efficient donor-level association testing while retaining single-cell resolution and interpretation. Applied to the OneK1K dataset, LIVI discovered a greater number of trans-eQTLs than alternative latent variable methods, yielded trans-eQTLs missed by conventional single-gene testing strategies and revealed the cell types and genes implicated in polygenic risk for autoimmune diseases. All in all, we demonstrate that LIVI is a powerful approach for linking genetics to gene regulation and through to human traits.

genomics↗

bioRxiv2024

Mapping Motor Preparation in the Developing Brain: Insights from Contingent Negative Variation and Event-related Mu Rhythm Modulation

IntroductionThe motor system shows a pronounced development throughout childhood and adolescence. The analysis of the contingent negative variation (CNV) provides valuable insights into various cognitive and motor processes, underlying cortical sources, and their development across the lifespan. MethodsWe investigated the maturation of motor preparation, pre-activation and post-processing in children and adolescents aged 5- to 16- years. EEG Data of 46 healthy right-handed subjects were recorded, using a 64-electrode high density sensor array. Subjects performed a CNV task with a directional warning cue. To assess age related developmental differences of cortical activation, analyses of event-related potentials (ERPs), mu-rhythm (de)synchronization and source analysis were applied. ResultsChildren showed increased reaction times and committed more errors than adolescent subjects. Motor preparation and post-processing were characterized by a developmental increase of cortical activity related to the supplementary motor area (SMA). Young children showed a pronounced sensory post processing during orienting response (early CNV) that decreased with age. In contrast to previous research in young adults, adolescent subjects showed no contralateral activation of motor areas during motor preparation (late CNV) yet. Furthermore, there was an observed decline in motor post processing with maturation. ConclusionThe results indicate a prolonged maturation of cortical scalp areas associated with motor control up into late adolescence or early adulthood. With age, the activation of mid-frontocentral regions associated with the SMA becomes more pronounced during motor planning and response evaluation. Qualitatively distinct cortical activation patterns of young subjects suggest immature supplementary-, pre- and primary motor areas and might be a primary cause for age-related increasing efficiency of motor action control.

developmental biology↗

bioRxiv2021

Evolution of a new testis-specific functional promotor within the highly conserved Map2k7 gene of the mouse

Map2k7 (synonym Mkk7) is a conserved regulatory kinase gene and a central component of the JNK signaling cascade with key functions during cellular differentiation. It shows complex transcription patterns and different transcript isoforms are known in the mouse (Mus musculus). We have previously identified a newly evolved testis specific transcript for the Map2k7 gene in the subspecies M. m. domesticus. Here, we identify the new promotor that drives this transcript and find that its transcript codes for an open reading frame (ORF) of 50 amino acids. The new promotor was gained in the stem lineage of closely related mouse species, but was secondarily lost in the subspecies M. m. musculus and M. m. castaneus. A single mutation can be correlated with its transcriptional activity in M. m. domesticus and cell culture assays demonstrate the capability of this mutation to drive expression. A mouse knock-out line in which the promotor region of the new transcript is deleted reveals a functional contribution of the newly evolved promotor to sperm motility and to the spermatid transcriptome. Our data show that a new functional transcript (and possibly protein) can evolve within an otherwise highly conserved gene, supporting the notion of regulatory changes contributing to the emergence of evolutionary novelties.

evolutionary biology↗

bioRxiv2021

CellRegMap: A statistical framework for mapping context-specific regulatory variants using scRNA-seq

Single cell RNA sequencing (scRNA-seq) enables characterizing the cellular heterogeneity in human tissues. Technological advances have enabled the first population-scale scRNA-seq studies in hundreds of individuals, allowing to assay genetic effects with single-cell resolution. However, existing strategies to perform genetic analyses using scRNA-seq remain based on principles established for bulk RNA-seq. In particular, current methods depend on a priori definitions of discrete cell types, and hence cannot assess allelic effects across subtle cell types and cell states. To address this, we propose Cell Regulatory Map (CellRegMap), a statistical framework to test for and quantify genetic effects on gene expression in individual cells. CellRegMap provides a principled approach to identify and characterize heterogeneity in allelic effects across cellular contexts of different granularity, including cell subtypes and continuous cell transitions. We validate CellRegMap using simulated data and apply it to two recent studies of differentiating iPSCs, where we uncover a previously underappreciated heterogeneity of genetic effects across cellular contexts. Finally, we identify fine-grained genetic regulation in neuronal subtypes for eQTL that are colocalized with human disease variants.

bioinformatics↗

bioRxiv2021

scDALI: Modelling allelic heterogeneity of DNA accessibility in single-cells reveals context-specific genetic regulation

While the functional impact of genetic variation can vary across cell types and states, capturing this diversity remains challenging. Current studies, using bulk sequencing, ignore much of this heterogeneity, reducing discovery and explanatory power. Single-cell approaches combined with F1 genetic designs provide a new opportunity to address this problem, however suitable computational methods to model these complex relationships are lacking. Here, we developed scDALI, an analysis framework that integrates single-cell chromatin accessibility for unbiased cell state identification with allelic quantifications to assay genetic effects. scDALI builds on Gaussian process regression and can differentiate between homogeneous (pervasive) allelic imbalances and cell state-specific regulation. As a proof-of-principle, we applied scDALI to whole Drosophila embryos from F1 crosses, profiling sciATAC-seq at three embryonic stages. Even in these very complex samples, scDALI discovered hundreds of peaks with heterogeneous allelic imbalance, having effects in specific lineages and/or developmental stages. Our study provides a general strategy to identify the cellular context of allelic imbalance, a crucial step in linking genetic traits to cellular phenotypes.

genomics↗