A Comprehensive De Novo Variant Callset for the Gabriella Miller Kids First Pediatric Research Program Birth Defect Data

Project Summary/Abstract Birth defects occur in 1 in 33 individuals and result in yearly healthcare costs in the United States of America of >$23 billion. Understanding genetic causes of birth defects can provide insights into molecular pathways and ultimately provide a path towards therapeutics. The Gabriella Miller Kids First Pediatric Research Program with

its short name of “Kids First” is a program that was created to investigate cancer and birth defects in children. In this program, whole-genome sequencing (WGS) has been generated in combination with collection of phenotype(s). The R03 PAR-23-075 on “Small Research Grants for Analyses of Gabriella Miller Kids First

Pediatric Research Data” encourages submission of applications focused on analyzing Kids First. In this proposal, we specifically focus on detection and analyses of de novo variants (DNVs) in the cohorts with birth defects. DNVs are important in human diseases and have been shown to contribute to birth defects. We have

developed several tools to detect, quality check, and statistically assess DNVs in both the nuclear and mitochondrial genome. The Kids First Data Portal does not currently have DNV callsets from either the nuclear or mitochondrial genomes. DNVs are likely contributors to the birth defects represented in Kids First and it is

critical to generate a comprehensive high quality DNV callset for this dataset. Through this R03 mechanism, we will generate nuclear and mitochondrial DNV callsets for all 6,080 families with birth defects in Kids First for use by others and ourselves. Once we have the DNV callsets we will test for enrichment of protein-coding DNVs in

relation to birth defects. Protein-coding DNVs are the most straightforward to interpret and we are well prepared to perform these analyses as evidenced by our previous work. The two aims we will pursue in this grant include comprehensive DNV calling and assessment of protein-coding DNVs in the nuclear genome (Aim 1) and the

mitochondrial genome (Aim 2). There are three expected outcomes of our study including 1) identification of new genes involved in birth defects, 2) comprehensive DNV callsets for use by others with interest in birth defects, and 3) integration of our DNV tools (HAT, EGP) in the Kids First Data Portal for use as additional families are

added to the portal. Overall, our work will make substantial progress in understanding genetic aspects of birth defects.