Biology subjects

Edenhofer, F. C.

Publications and source records attributed to Edenhofer, F. C..

2 recordsLinked to original sources

bioRxiv2025

CroCoNet: a novel framework for cross-species network analysis reveals POU5F1 (OCT4) rewiring

BACKGROUNDGene regulatory changes play a central role in shaping cellular phenotypes across species. To understand how these phenotypes evolve, it is essential to investigate the underlying gene regulatory networks (GRNs). However, most comparative analyses of GRNs remain qualitative and are therefore sensitive to false positives and false negatives. RESULTSTo address this limitation, we introduce CroCoNet (Cross-species Comparison of Networks), an R package for the quantitative comparison of GRNs across species. CroCoNet constructs comparable network modules centered on known transcriptional regulators and quantifies the variability in module topology within and between species. By contrasting these levels of variability, CroCoNet can distinguish true evolutionary divergence from technical and biological confounders. Applying CroCoNet to scRNA-seq data from the early neural differentiation of human, gorilla, and cynomolgus macaque, we identified 20 conserved and 24 diverged modules. Despite the conserved expression pattern of the pluripotency factor POU5F1 (OCT4), its associated module was among the most diverged. This result was independently confirmed through cross-species CRISPRi perturbations coupled with single-cell RNA-seq as a readout. Moreover, we found that great ape- and human-specific LTR7 elements are enriched near POU5F1 module genes, potentially contributing to the cross-species differences in network topology. CONCLUSIONSThese findings demonstrate that CroCoNet can resolve regulatory rewiring and provides a robust framework for studying GRN evolution across closely related species. CroCoNet is available as an open-source R package at https://hellmann-lab.github.io/CroCoNet/.

evolutionary biology↗

bioRxiv2024

Identification and comparison of orthologous celltypes from primate embryoid bodies shows limits of marker gene transferability

The identification of cell types remains a major challenge. Even after a decade of single-cell RNA sequencing (scRNA-seq), reasonable cell type annotations almost always include manual non-automated steps. The identification of orthologous cell types across species complicates matters even more, but at the same time strengthens the confidence in the assignment. Here, we generate and analyze a dataset consisting of embryoid bodies (EBs) derived from induced pluripotent stem cells (iPSCs) of four primate species: humans, orangutans, cynomolgus, and rhesus macaques. This kind of data includes a continuum of developmental cell types, multiple batch effects (i.e. species and individuals) and uneven cell type compositions and hence poses many challenges. We developed a semi-automated computational pipeline combining classification and marker based cluster annotation to identify orthologous cell types across primates. This approach enabled the investigation of cross-species conservation of gene expression. Consistent with previous studies, our data confirm that broadly expressed genes are more conserved than cell type-specific genes, raising the question how conserved - inherently cell type-specific - marker genes are. Our analyses reveal that human marker genes are less effective in macaques and vice versa, highlighting the limited transferability of markers across species. Overall, our study advances the identification of orthologous cell types across species, provides a well-curated cell type reference for future in vitro studies and informs the transferability of marker genes across species.

cell biology↗