# Deep Phenotyping of 3D Data for Candidate Gene Selection from Kids First Studies

> **NIH NIH R03** · SEATTLE CHILDREN'S HOSPITAL · 2021 · $329,875

## Abstract

Abstract/Project Summary
This project will pilot a process to explore the role of genes contributing to abnormal asymmetry in
developmental disorders by combining knowledge of genotype/phenotype interactions derived from the
Common Fund Knockout Mouse Phenotyping Program (KOMP2) and the Genotype-Tissue Expression (GTEx)
project with family cohort data from two Gabriella Miller Kids First Pediatric Research Projects (KF): Genomic
Studies of Orofacial Cleft Birth Defects and Genomics of Orofacial Cleft Birth Defects in Latin American
Families. Asymmetry is a key feature of numerous developmental disorders including major structural birth
defects as well as neurological disorders. A better understanding of the genetic basis of asymmetry and its
relationship to disease susceptibility will help unravel the complex genetic and environmental factors and their
interactions that increase risk in a wide range of developmental disorders. The KOMP2 project aims to provide
comprehensive mouse knockout phenotype data, including 3D fetal imaging of sub-viable and lethal lines that
are likely to play a significant role in development. In this project, automated, dense quantification of
asymmetry of 3D embryonic microCT images will be used to build statistical models of asymmetry in normal
development. Knockout strains will be screened for phenotypes with asymmetric structures or organs with the
goal of detecting genes associated with abnormally heightened asymmetry. The functional significance of the
selected genes will be validated by comparing regions impacted in knockout strain phenotypes from the
KOMP2 dataset to tissue expression data from the GTEx project. Candidate genes identified using biological
information from the KOMP2 and GTEx datasets will be explored f or association with the KF whole genome
sequencing data from OFC parent-case trios with the aim of identifying genetic variants that are enriched in
these groups compared to a control population. Identification of these variants will help shed light on the
mechanisms linking congenital asymmetry and OFC risk. The outcomes of this study will include (1) statistical
models of normal anatomy and asymmetry from the KOMP2 fetal 3D imaging data, (2) an open -source
software to produce detailed phenotype descriptions from dense morphometric analysis of 3D images from the
KOMP2 dataset, (3) correlations between phenotype descriptions from the KOMP2 knockout strains and tissue
expression data from the GTEx project, and (4) analysis of the contribution of rare variants on candidate genes
towards OFC risk.

## Key facts

- **NIH application ID:** 10355998
- **Project number:** 1R03OD032627-01
- **Recipient organization:** SEATTLE CHILDREN'S HOSPITAL
- **Principal Investigator:** Ali Murat Maga
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $329,875
- **Award type:** 1
- **Project period:** 2021-09-22 → 2023-09-21

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10355998

## Citation

> US National Institutes of Health, RePORTER application 10355998, Deep Phenotyping of 3D Data for Candidate Gene Selection from Kids First Studies (1R03OD032627-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10355998. Licensed CC0.

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