Biology subjects

Schubeler, D.

Publications and source records attributed to Schubeler, D..

5 recordsLinked to original sources

bioRxiv2025

The genetic architecture of the human bZIP family

Generative biology holds the promise to transform our ability to design and understand living systems by creating novel proteins, pathways, and organisms with tailored functions that address challenges in medicine, sustainability, and technology. However, training generative models requires large quantities of data that captures the genetic architecture of protein function in all its complexity, but these are currently scarce. Here, we systematically mutagenized all 54 human basic-leucine zipper (bZIP) domains and quantified their interactions with each other using bindingPCA, a quantitative deep mutational scanning assay. This resulted in [~]2 million interaction measurements, capturing the effect of all single amino acid substitutions at each of the 35 interfacial positions. We found that mutation effects are largely additive in the vicinity of each wild-type bZIPs, but diverge across the family, indicating strong context dependency. A global additive thermodynamic model provided moderate prediction of mutation effects, while individual models per bZIP achieved higher performance, supporting a model of local simplicity and global complexity. Our results therefore suggest that the genetic architecture of protein function is more complex than previously anticipated, which could hinder predictability. However, a convolutional neural network trained on this dataset could accurately predict binding scores from sequence alone. Furthermore, the model enabled the design of synthetic bZIPs with high target specificity, demonstrating practical applicability for bioengineering purposes. Our study shows that capturing family-wide diversity is essential to reveal context dependencies and train accurate quantitative models of protein-protein interactions.

biophysics↗

bioRxiv2025

A novel deep learning-based framework reveals a continuum of chromatinsensitivities across transcription factors

The genome-wide binding of many transcription factors (TFs) depends not only on the presence of their recognition motifs, but also on the surrounding chromatin context. This raises the question of how binding specificity is achieved, which is essential for the proper activation of regulatory regions during developmental and differentiation processes. Two competing hypotheses have been proposed: either opening is a hierarchical process, whereby chromatin-insensitive TFs bind initially and make the DNA accessible for other TFs; or multiple chromatin-sensitive TFs bind cooperatively, enabling them to overcome the chromatin barrier. Here, using complementary genomic- and deep-learning-based techniques, we provide a quantitative framework to assess chromatin sensitivity of individual TFs, and hone in on the definitions and implications of such sensitivity. Our findings demonstrate that the degree of chromatin sensitivity is a continuum across TFs, showing that regulatory regions are activated neither by a purely hierarchical nor purely cooperative mechanism, but by a mixture of both mechanisms. The presented framework allows for a locus-specific as well as global, quantitative assessment of chromatin sensitivity and should help in understanding the binding behaviour of individual TFs as well as their potential contribution to gene regulation.

genomics↗

bioRxiv2024

Chromatin-dependent motif syntax defines differentiation trajectories

Transcription factors recognizing short DNA sequences within gene regulatory regions are crucial drivers of cell identity. Despite recent advances, their specificity remains incompletely understood. Here, we address this by contrasting two TFs, NGN2 and MyoD1, which recognize ubiquitous E-box motifs yet instigate distinct cell fates--neurons and muscles, respectively. Following controlled induction in embryonic stem cells, we monitor binding across differentiation trajectories, employing an interpretable machine-learning approach integrating pre-existing DNA accessibility data. This reveals a chromatin-dependent motif syntax, delineating both common and factor-specific binding and predicting genome engagement with high precision. Shared binding sites reside in open chromatin, locally influenced by nucleosomes. In contrast, factor-specific binding in closed chromatin involves NGN2 and MyoD1 acting as pioneer-factors, influenced by multi-motifs, rotational spacing, flanking sequences, and specific interaction partners, accounting for subsequent lineage divergence. Extending our methodology to other models demonstrates how such combination of opportunistic-binding and context-specific chromatin opening underpin transcription factor specificity driving differentiation trajectories.

genomics↗

bioRxiv2021

monaLisa: an R/Bioconductor package for identifying regulatory motifs

Proteins binding to specific nucleotide sequences, such as transcription factors, play key roles in the regulation of gene expression. Their binding can be indirectly observed via associated changes in transcription, chromatin accessibility, DNA methylation and histone modifications. Identifying candidate factors that are responsible for these observed experimental changes is critical to understand the underlying biological processes. Here we present monaLisa, an R/Bioconductor package that implements approaches to identify relevant transcription factors from experimental data. The package can be easily integrated with other Bioconductor packages and enables seamless motif analyses without any software dependencies outside of R. AvailabilitymonaLisa is implemented in R and available on Bioconductor at https://bioconductor.org/packages/monaLisa with the development version hosted on GitHub at https://github.com/fmicompbio/monaLisa. Contactmichael.stadler@fmi.ch

bioinformatics↗

bioRxiv2021

ZFP462 targets heterochromatin to transposon-derived enhancers restricting transcription factor binding and expression of lineage-specifying genes

ZNF462 haploinsufficiency is linked to Weiss-Kruszka Syndrome, a genetic disorder characterized by a range of neurodevelopmental defects including Autism. Though it is highly conserved in vertebrates and essential for embryonic development the molecular functions of ZNF462 are unclear. We identified its murine homolog ZFP462 in a screen for epigenetic gene silencing in mouse embryonic stem cells (mESCs). Here, we show ZFP462 safeguards neural lineage specification by targeting the H3K9-specific histone methyltransferase complex G9A/GLP to mediate epigenetic silencing of endodermal genes. ZFP462 binds to thousands of transposable elements (TEs) that harbor ESC- and endoderm-specific transcription factor (TF) binding sites and act as enhancers. Through physical interaction with G9A/GLP, ZFP462 seeds heterochromatin at TE-derived enhancers restricting the binding of core pluripotency TFs OCT4 and SOX2. Loss of ZFP462 in ESCs results in increased chromatin accessibility at target sites and ectopic expression of endodermal genes. Taken together, ZFP462 restricts TF binding and subsequent endodermspecific gene activation by conferring lineage and locus-specificity to the broadly expressed epigenetic regulator G9A/GLP. Our results suggest that aberrant activation of endodermal genes in the neuronal lineage underlies ZNF462-associated neurodevelopmental pathology.

genetics↗