Our new preprint is now out!
Dynamic transcriptional heterogeneity in pituitary corticotrophs
https://www.biorxiv.org/content/10.1101/2025.04.04.645979v1
We analysed publicly available single-cell RNA sequencing data of pituitary gland tissue and looked at corticotrophs, cells that are central to mediate stress responses.
We identified several transcriptional states in these cells that are related to how they respond to stress. Cells are able to transition between these states and this might be helpful for them to respond to stress coming at unpredictable times.
We also highlight issues related to using scRNAseq to look at functional subpopulations of cells.
bioRxiv · Dynamic transcriptional heterogeneity in pituitary corticotrophsA large body of evidence has shown that corticotrophs, the anterior pituitary cells central to the generation of hormonal stress responses, exhibit heterogeneous functional behavior, suggesting the presence of functional sub-populations of corticotrophs. We investigated whether this was the case at the transcriptomic level by conducting a comprehensive analysis of scRNA-seq datasets from rodent pituitary cells. We envisaged two alternative scenarios, one where robust subtypes of corticotrophs exist, and the other where these subpopulations were only transient states, possibly transitioning into one another. Our findings suggest that corticotrophs transition between multiple transcriptional states rather than existing as rigidly defined subpopulations. We employed marker gene-based comparisons and whole transcriptome label transfer approaches to analyze transcriptional signatures across datasets. Marker-based clustering revealed strikingly low similarity in the identified subpopulations across datasets. This analysis evidenced the presence of transcriptional states with different functional relevance, related to different stages of hormonal signalling. Similarly, the label transfer approach, which considers non-linear interactions across the entire transcriptome showed that transcriptional states could be detected across independent datasets. This classification relied on broader gene expression patterns rather than conventional marker genes, reinforcing the notion of continuous rather than discrete cell states. Furthermore, trajectory analysis by RNA velocity indicated dynamic transitions between transcriptional states, suggesting the presence of transcriptional mechanisms facilitating rapid recruitment of corticotrophs in response to physiological demands. Our findings align with evidence from other endocrine cell types, such as lactotrophs and pancreatic β-cells, where hormone secretion is linked to fluctuating transcriptional activity. The observed transitions in corticotroph states suggest a mechanism allowing flexible hormonal responses to unpredictable and time-varying stressful events. Additionally, this study highlights the challenges associated with scRNA-seq methodologies, including data sparsity, batch effects, and pseudoreplication, underscoring the need for rigorous experimental design and reproducibility in single-cell transcriptomics research. These insights contribute to a broader understanding of pituitary cell plasticity and endocrine adaptation mechanisms.
### Competing Interest Statement
The authors have declared no competing interest.
Because nothing screams 
Maybe next time, try a to-do list instead of a fictitious ticking clock. 
Rebooting Petabyte Control Node 
