PROJECT SUMMARY Congenital abnormalities affect 3-4% of pregnancies and cause 20-30% of neonatal deaths worldwide. Prenatal diagnosis can lead to significant improvements in newborn health and development for a growing number of genetic conditions, especially as treatment options, such as gene therapy, continue to increase. Non-invasive prenatal testing (NIPT) is now widely available for chromosomal abnormalities, and more recently, for identifying paternally-inherited/de novo autosomal dominant conditions in the fetus. Additionally, more and more women are being offered whole-exome sequencing (WES) on amniocentesis or chorionic villus samples after structural abnormalities in the fetus are identified on ultrasound. However, current WES paradigms lack the power to detect exon-level CNV and NIPT options for recessive single-gene disorders do not exist. Recessive conditions constitute over half of single-gene disorders, and the vast majority of known single-gene conditions are caused by single-nucleotide polymorphisms (SNPs). While large-scale sequencing efforts are better defining the prevalence of SNPs, the genome-wide prevalence of exon-level copy number variation (CNV) remains largely unknown. Research on a limited number of genes would suggest small CNVs represent roughly 1% of variants, but over 9% of pathogenic variants. We are collecting two cohorts of clinical samples: (1) mother-father-fetus trios when structural abnormalities are found on ultrasound; (2) maternal blood during pregnancy and cord blood at time of delivery. Using these clinical samples, the Specific Aims of this proposal are: (1) Demonstrate multiplexed exome capture utility and novel analysis for exon-level CNV detection and (2) Develop analysis framework and novel probes for fetal genotyping from maternal cell-free DNA. Aim 1 will employ the CNV algorithm (mcCNV) in trios to identify exon-level de novo variation, increasing the diagnostic yield and ideally identifying new candidate genes for understanding human development. Aim 2 greatly expands the possible utility of NIPT with the novel inclusion of recessive single-gene disorders. Through this research proposal and associated training plan, I will gain a unique and interdisciplinary skill-set that combines data science and biostatistics with population genetics in an innovative manner that is at the forefront of maternal-fetal medicine. This training will provide me with the technical, statistical, and professional skills I need to become a leader at an academic center and to pursue my goals of practicing maternal-fetal medicine and research as a physician-scientist.