# A Screen for Identifying Insomnia Genes.

> **NIH NIH R21** · FLORIDA ATLANTIC UNIVERSITY · 2021 · $14,482

## Abstract

Project Summary
Evolutionary medicine leverages the power of naturally occurring phenotypic differences derived through
adaptation to investigate genetic mechanisms underlying diseases, including neurological disorders. The
Mexican cavefish exhibits a dramatic evolution of sleep loss compared to ancestral surface fish of the same
species, providing a unique and powerful model to identify genetic factors regulating sleep. The proposed
experiments will implement genetic technology in Mexican cavefish to identify novel regulators of naturally
occurring insomnia-like phenotypes in cavefish. This proposal will also apply a newly developed
neuroanatomical brain atlas and whole-brain calcium imaging to determine how novel sleep genes impact
brain structure and function. These experiments will provide critical insight into the mechanistic basis of sleep
regulation and identify naturally occurring genetic variants that contribute to sleep regulation. Further, the
genetic tools and methodology established in these studies will provide valuable resources that can be applied
to address questions beyond the scope in this proposal, including diseases such as eye-degeneration, obesity,
hyperphagia and aggression that are commonly studied in this system.

## Key facts

- **NIH application ID:** 10228112
- **Project number:** 1R21NS122166-01
- **Recipient organization:** FLORIDA ATLANTIC UNIVERSITY
- **Principal Investigator:** Alex C Keene
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $14,482
- **Award type:** 1
- **Project period:** 2021-05-15 → 2021-08-06

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10228112

## Citation

> US National Institutes of Health, RePORTER application 10228112, A Screen for Identifying Insomnia Genes. (1R21NS122166-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10228112. Licensed CC0.

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