# Sexually dimorphic regulation of neuronal identity in C.elegans

> **NIH NIH R37** · COLUMBIA UNIV NEW YORK MORNINGSIDE · 2021 · $380,794

## Abstract

   
DESCRIPTION (provided by applicant): Synaptic connectivity constitutes an integral part of neuronal identity. The recent reconstruction of the connectome of the C.elegans male and its comparison to the long known connectome of the hermaphrodite (a derived female) reveal a sexually dimorphic dimension of neuronal identity: Some defined neuron types that are present in both hermaphrodites and males show sexually dimorphic synaptic connectivity patterns. We propose to dissect the regulatory programs that specify sexual dimorphic identity, as manifested by dimorphic synaptic connectivity features. Specifically, we propose here to (1) reliably and easily visualize sexually dimorphic synaptic connectivity patterns in transgenic animals using GFP-based reporter systems; (2) study aspects of the establishment, maintenance and autonomy of these dimorphic synapses and (3) identify molecules through a candidate gene approach and unbiased profiling approach that genetically program these dimorphic patterns of connectivity and identity. We expect that our studies will provide novel insights into the currentl little explored sexual dimension of neuronal identity.

## Key facts

- **NIH application ID:** 10166958
- **Project number:** 5R37NS039996-21
- **Recipient organization:** COLUMBIA UNIV NEW YORK MORNINGSIDE
- **Principal Investigator:** Oliver Hobert
- **Activity code:** R37 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $380,794
- **Award type:** 5
- **Project period:** 2001-04-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10166958

## Citation

> US National Institutes of Health, RePORTER application 10166958, Sexually dimorphic regulation of neuronal identity in C.elegans (5R37NS039996-21). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10166958. Licensed CC0.

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