Whole Genome Sequencing (WGS) on IVF Embryos and Individual Patients

This project proposes a paired non-inferiority trial utilizing the retrospective testing of research embryos to establish the optimized parameters for amplified trophectoderm biopsy and whole genome sequencing compared to traditional preimplantation genetic testing for aneuploidy (PGT-A). The primary outcome is the de novo mutation rate, which will be compared between embryos subjected to trophectoderm biopsy and whole genome sequencing versus reanalysis with Sanger sequencing. Trio testing will be performed for each embryo using DNA from the genetic parents in addition to embryo. The study will compare cases that include couples with at least one embryo deemed unsuitable for transfer. A paired study design will be used, with embryos from each couple split into two arms - one subjected to trophectoderm biopsy and whole genome sequencing, the other to reanalysis with targeted sequencing. Biopsied trophectoderm samples and the remaining embryo tissues from the whole genome sequencing arm will undergo sequencing. Sequencing will also be performed on DNA samples from each genetic parent. Derivation of de novo mutation rates is a key goal, as these provide insights into effects of paternal age and other factors on germline mutations in preimplantation embryos, increasing the knowledge of the risks associated with advanced paternal age. Secondary metrics will be investigated to supplement the analysis, including clean reads and clean bases indicating the amount of high-quality data for the source templates. Mapping rate, unique rate and duplicate rate, assessing data accuracy and quality. Comparison of multiple metrics will determine the optimized parameters for performing amplified trophectoderm biopsy and whole genome sequencing. This can then inform future research and clinical studies. The de novo mutation rate will be derived by modelling the observed mutation rate as a function of parental ages, specifically the paternal age. Whole genome sequencing of embryo samples as well as both parents will identify raw numbers of de novo mutations. The paternal age coefficient for the de novo mutation rate will be calculated using a regression model with the number of de novo mutations as the dependent variable and paternal age as the key independent variable. Covariates like maternal age and sequencing quality metrics will also be included to account for potential confounding factors. The regression model will determine the increase in de novo mutations per year of paternal age, providing the paternal age coefficient. Comparing embryos from older and younger males will reveal differences in mutation rates. The overall model will establish the quantitative relationship between paternal age and de novo mutations in preimplantation embryos based on the study's whole genome sequencing data.