Bridging Space and Time: Resolving the Temporal Dynamics of the Seminiferous Epithelial Cycle Using Spatial Transcriptomics

Citation

Chakravorty, Arun (2025) Bridging Space and Time: Resolving the Temporal Dynamics of the Seminiferous Epithelial Cycle Using Spatial Transcriptomics. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/2rcd-0v79. https://resolver.caltech.edu/CaltechTHESIS:05112025-035044867

Abstract

Biology is inherently spatial, with tissue architecture and cell–cell interactions shaping dynamic developmental and homeostatic processes. In this thesis, we harness high-resolution spatial transcriptomics via RNA seqFISH+ to show how spatial information can be used to resolve temporal information in complex tissues, using adult mouse spermatogenesis as a model. By profiling 2,638 genes in over 216,000 cells, we find that each seminiferous tubule cross-section represents a distinct timepoint of the seminiferous epithelial cycle, and collectively all tubules form a circular topology in gene expression space that precisely aligns with the known 12-stage progression. Intriguingly, Sertoli cells exhibit a robust cyclic transcriptional program synchronized with germ cell differentiation, raising the question of whether this cycle is driven solely by germ cells or whether Sertoli cells display an intrinsic cyclic expression profile. To address this, we ablate differentiating germ cells using a DNA alkylating agent, busulfan. In this model, despite the lack of differentiating germ cells, Sertoli cells maintain much of their cyclic expression suggesting an autonomous cycle that partially dephases without germ cell input. Integrative analyses suggest that the underlying mechanism of this oscillation may involve an innate retinoic acid metabolic cycle and/or an interconnected transcription factor network. Finally, we discuss how these findings broaden our understanding of tissue processes and propose that spatial transcriptomics can be adopted to reconstruct temporal dynamics for many tissues from static snapshots.

Thesis Files