Chemical Engineering Seminar
Regulation of transcription is coordinated by several layers of the epigenome to ensure precise cell type-specific gene expression programs. These layers of the epigenome span several orders of length scales, ranging from the 3-dimensional organization of chromosomes and the packaging of chromatin to chemical modifications of DNA. However, our understanding of how cell-to-cell heterogeneity in the epigenome influences gene expression variability and cell fate decisions remains limited. To address this question, our group has recently developed several technologies that I will describe in this talk. First, I will describe a method to strand-specifically detect DNA methylation in single cells that enabled us to uncover the mechanisms responsible for the global erasure of the methylome during preimplantation mouse/human development. Further, to gain deeper insights into genomic location- and cell state-specific reprogramming of the methylome during mammalian development, we have developed a method that can quantify all combinations of DNA methylation and DNA hydroxymethylation at the resolution of individual CpG dinucleotides together with the transcriptome in single cells. Next, I will discuss a method to simultaneously quantify DNA methylation, DNA accessibility and mRNA in single cells. When applied to embryoids mimicking early human development, we identify how changes in the epigenome are involved in the emergence of distinct cell types, including primordial germ cells, during gastrulation. Finally, I will describe a method to simultaneously map protein-DNA interactions and mRNA from the same cell. By profiling lamina-associated domains, we identify different dependencies between genome-nuclear lamina association and gene expression heterogeneity in single cells. Furthermore, by quantifying the binding patterns of a polycomb-group protein, RING1B, and the associated transcriptome, we map the dynamics of X chromosome inactivation during early development. In summary, these novel technologies are enabling us to map gene regulatory landscapes in different cell types within heterogeneous tissues.