Project description:Current gene-expression databases for the haematopoietic system provide information on gene expression profiles present in bulk populations. Although informative, these studies lack the resolution that can be gained at a single-cell level. In particular, population-average data assumes homogeneity within the population and may as such obscure the ability to detect the heterogeneity of decision-making processes in individual cells. Here we report 1656 single cell transcriptomes analysed by single-cell RNA sequencing. Cells were FACS sorted on broad gates encompassing haematopoietic stem and progenitor populations (HSPCs), with index sorting data collected to permit retrospective identification of populations by surface marker expression. Our dataset thus represents the gene expression landscape of HSPCs at single-cell resolution, capturing the heterogeneity in and between cell populations. Pseudotime analysis visualized haematopoietic stem (HSC) to progenitor transitions, identified HSC as well as lineage-specific transcriptional programs, and also highlighted putative lineage branching points. To provide access to the wider scientific community, a user-friendly website was developed with intuitive search and display functionality. Single cell RNA sequencing of haematopoeitic stem and progenitor cells
Project description:Single cell sequencing technologies are powerful tools for the dissection of large regulatory networks and their role in directing developmental trajectories. The goal of this project is to profile the transcriptional landscape of germ cell development in the mouse male embryo at single cell resolution, and to examine the dynamic regulation of the molecular networks directing epigenetic reprogramming in these cells.