# Otic Guidance

> **NIH NIH R21** · STANFORD UNIVERSITY · 2022 · $275,450

## Abstract

Project Summary / Abstract
The first aim of this research proposal is to use single-cell transcriptomics to describe the changes in gene
expression that happen during otic guidance from pluripotent stem cells. It builds on known principles of
inner ear development and utilizes single-cell RNA-Seq and computational modeling for extracting the
differentiation pathway of cells towards non-neural ectoderm, pre-placodal ectoderm, and ultimately otic
induction and the sensory hair cell lineage. In a second aim, it is proposed to comparatively investigate the
distinct steps when otic guidance from embryonic stem cells fails, which is a common problem. The
generation of inner ear cells from embryonic stem cells is an unreliable enterprise and has hampered research
for more than a decade. Computational comparisons of gene expression changes in successfully guided
inner ear lineage cells with lineages that stray from otic differentiation will result in the identification of specific
signaling pathways that contribute to cell differentiation failures. Based on computational modeling, testable
hypotheses will be generated and experimentally validated. The ultimate goal of the proposed research is the
elimination of experimental variations of otic guidance from stem cells towards establishing a reliable otic
guidance protocol that can be widely utilized by many laboratories.

## Key facts

- **NIH application ID:** 10336252
- **Project number:** 1R21DC019910-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** Stefan Heller
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $275,450
- **Award type:** 1
- **Project period:** 2021-12-01 → 2023-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10336252

## Citation

> US National Institutes of Health, RePORTER application 10336252, Otic Guidance (1R21DC019910-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10336252. Licensed CC0.

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