Dynamic transcriptional heterogeneity in pituitary corticotrophs

Abstract

A 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 {beta}-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.