Skip to main content
Kent Academic Repository

Inferring Biological Mechanisms from Spatial Analysis: Prediction of a Local Inhibitor in the Ovary

da Silva-Buttkus, P., Marcelli, Gianluca, Franks, S., Stark, J., Hardy, K. (2009) Inferring Biological Mechanisms from Spatial Analysis: Prediction of a Local Inhibitor in the Ovary. Proceedings of the National Academy of Sciences, 106 (2). pp. 456-461. ISSN 0027-8424. (doi:10.1073/pnas.0810012106) (KAR id:30202)


Female mammals are born with a lifetime's supply of oocytes individually enveloped in flattened epithelial cells to form primordial follicles. It is not clear how sufficient primordial follicles are maintained to sustain the reproductive lifespan, while providing an adequate supply of mature oocytes for ovulation. Locally produced growth factors are thought to be critical regulators of early follicle growth, but knowledge of their identity and source remains incomplete. Here, we have used a simple approach of spatial analysis of structures in histological tissue sections to identify likely sources of such regulatory molecules, narrowing the field for future screening for candidate growth factors or antagonists. We have quantified the relative spatial positions of primordial (resting) follicles and growing follicles in mice on days 4, 8, and 12 after birth, and calculated interfollicular distances. Follicles were significantly less likely to have started growing if they had 1 or more primordial follicles close by (within 10 ?m), predicting that primordial follicles inhibit each other. This approach allows us to hypothesize that primordial follicles produce a diffusible inhibitor that prevents neighboring primordial follicles from growing. Such an approach has wide applicability within many branches of developmental and cell biology for studying spatial signaling within tissues and cells.

Item Type: Article
DOI/Identification number: 10.1073/pnas.0810012106
Uncontrolled keywords: Diffusing inhibitor, follicle growth, signal gradient
Subjects: Q Science > QH Natural history > QH324.2 Computational biology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: J. Harries
Date Deposited: 20 Aug 2012 09:03 UTC
Last Modified: 16 Nov 2021 10:08 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

  • Depositors only (login required):

Total unique views for this document in KAR since July 2020. For more details click on the image.