# GENETIC FACTORS IN BIRTH DEFECTS-GENOMIC TESTING

> **NIH NIH N01** · UNIVERSITY OF MINNESOTA · 2020 · $282,794

## Abstract

Major birth defects are a serious health problem, occurring in approximately two percent of births.  Despite all the research that has been conducted, the cause of most birth defects remains unknown. Large scale genetic investigations offer a new pathway for etiologic investigation. As the technology advances, it becomes possible to do more and more with small samples of DNA. Our group has been active in identifying ways to use very small amounts of DNA (such as is available from filter paper blood spots) to conduct genome-wide studies. This study will examine the entire coding sequence of the genome (the exome) by whole exome sequencing (WES). The exome is an excellent target for genome studies because WES requires sequencing only 1-2% of the genome but provides data on all the coding material. Whole genome sequencing to obtain data on other potentially important areas is far more costly and creates serious challenges in interpreting the data. Therefore, WES is generally considered the best value. The data generated by this process can also be used to identify copy number variants (CNV). Thus, both variants as small as a single nucleotide polymorphism (SNP) change in an exome or as large as a duplication or deletion in a section of a chromosome, will be identified.

## Key facts

- **NIH application ID:** 10268912
- **Project number:** 275201300023I-P00003-27500011-1
- **Recipient organization:** UNIVERSITY OF MINNESOTA
- **Principal Investigator:** MICHAEL TSAI
- **Activity code:** N01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $282,794
- **Award type:** —
- **Project period:** 2017-05-10 → 2024-02-09

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10268912

## Citation

> US National Institutes of Health, RePORTER application 10268912, GENETIC FACTORS IN BIRTH DEFECTS-GENOMIC TESTING (275201300023I-P00003-27500011-1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10268912. Licensed CC0.

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