# Symmetry Breaking and Collective Cell Growth in Drosophila Oogenesis

> **NIH NIH F31** · PRINCETON UNIVERSITY · 2020 · $39,120

## Abstract

PROJECT SUMMARY
In many studied animal species, including mammals, the future oocyte develops within a cluster of cells that
exchange molecules and organelles through a network of cytoplasmic bridges, which are formed by stabilized
and reinforced cytokinetic furrows. While the formation and structure of this interesting class of multicellular
systems has been extensively studied, their dynamics is poorly understood, leaving many critical questions about
oocyte determination and development unanswered. I will investigate two of these questions in Drosophila, an
experimental model that continues to provide valuable insights into general mechanisms of animal oogenesis.
Using experimental, modeling, and computational approaches, I will investigate how one cell within the germline
cell cluster is chosen to be the future oocyte and how the germline cell cluster comprising the oocyte and
supporting nurse cells grows during development. Specifically, Aim 1 is designed to evaluate the differential
contributions of the prepatterning and self-organizing mechanisms of oocyte determination. Focusing on
the fusome, a membranous structure that is essential for intercellular communication in early oogenesis, and on
a recently discovered positive feedback loop involving mRNA localization and translation, I will establish data-
driven mathematical models for oocyte selection. In parallel, Aim 2 will investigate growth of the oocyte and
supporting cells, using the germline cluster as a tractable system for exploring how the scaling laws
established by studies of single cell growth are altered when cells grow together. In particular, I will focus
on size regulation of nuclei and nucleoli, aiming to understand how their sizes adjust to rapidly increasing cell
volumes within the germline cell cluster. The completion of these proposed studies, which are supported by
strong preliminary results, including a machine learning approach for 3D image reconstructions and
morphometric analysis, should provide new insights into some of the first steps of animal oogenesis.

## Key facts

- **NIH application ID:** 9910741
- **Project number:** 1F31HD098835-01A1
- **Recipient organization:** PRINCETON UNIVERSITY
- **Principal Investigator:** Rocky Diegmiller
- **Activity code:** F31 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $39,120
- **Award type:** 1
- **Project period:** 2020-09-01 → 2022-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9910741

## Citation

> US National Institutes of Health, RePORTER application 9910741, Symmetry Breaking and Collective Cell Growth in Drosophila Oogenesis (1F31HD098835-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9910741. Licensed CC0.

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