Development of a statistical framework for the analysis of single-cell multiomics datasets: towards a molecular atlas of the development of human preimplantation embryos.

The first cell cycles of human life are commonly subject to genome instability. However, the causes and consequences of the genetic alterations in the cells of the developing embryo remain to be investigated. Also the epigenetic landscape –i.e. modifications to the DNA that do not change the DNA-sequence but which can be heritable and control the expression of genes in the cells– is remodeled during early development of a human embryo. This project aims to develop a statistical and computation framework which allows for the integration of information of the different molecular layers of a single cell (the genome, the epigenome and the transcriptome). By applying this method on human data acquired from human embryos we will be able to answer questions regarding how different perturbations at a particular layer can affect mechanisms on the other functional layers. This will allow us to tackle unanswered questions on how developing human embryos deal with certain type of cellular chromosomal instability events in the first cell divisions. This will provide fundamental novel insights on the impact of acquired (epi)genetic modifications on the cell’s gene expression profile and hence on the function and potential fate of that cell. Additionally, the technology will reveal epigenetic and transcriptomic perturbations that may underlie the instability of the genome following fertilization.