Dissecting Early Differentially Expressed Genes in a Mixture of Differentiating Embryonic Stem Cells

The differentiation of embryonic stem cells is initiated by a gradual loss of pluripotency-associated transcripts and induction of differentiation genes. Accordingly, the detection of differentially expressed genes at the early stages of differentiation could assist the identification of the causal genes that either promote or inhibit differentiation. The previous methods of identifying differentially expressed genes by comparing different cell types would inevitably include a large portion of genes that respond to, rather than regulate, the differentiation process. We demonstrate through the use of biological replicates and a novel statistical approach that the gene expression data obtained without prior separation of cell types are informative for detecting differentially expressed genes at the early stages of differentiation. Applying the proposed method to analyze the differentiation of murine embryonic stem cells, we identified and then experimentally verified Smarcad1 as a novel regulator of pluripotency and self-renewal. We formalized this statistical approach as a statistical test that is generally applicable to analyze other differentiation processes

Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types.

Many subtypes of cortical interneurons (CINs) are found in adult mouse cortices, but the mechanism generating their diversity remains elusive. We performed single-cell RNA sequencing on the mouse embryonic medial ganglionic eminence (MGE), the major birthplace for CINs, and on MGE-like cells differentiated from embryonic stem cells. Two distinct cell types were identified as proliferating neural progenitors and immature neurons, both of which comprised sub-populations. Although lineage development of MGE progenitors was reconstructed and immature neurons were characterized as GABAergic, cells that might correspond to precursors of different CINs were not identified. A few non-neuronal cell types were detected, including microglia. In vitro MGE-like cells resembled bona fide MGE cells but expressed lower levels of Foxg1 and Epha4. Together, our data provide detailed understanding of the embryonic MGE developmental program and suggest how CINs are specified

Dissecting the dynamics of signaling events in the BMP, WNT, and NODAL cascade during self-organized fate patterning in human gastruloids.

During gastrulation, the pluripotent epiblast self-organizes into the 3 germ layers-endoderm, mesoderm and ectoderm, which eventually form the entire embryo. Decades of research in the mouse embryo have revealed that a signaling cascade involving the Bone Morphogenic Protein (BMP), WNT, and NODAL pathways is necessary for gastrulation. In vivo, WNT and NODAL ligands are expressed near the site of gastrulation in the posterior of the embryo, and knockout of these ligands leads to a failure to gastrulate. These data have led to the prevailing view that a signaling gradient in WNT and NODAL underlies patterning during gastrulation; however, the activities of these pathways in space and time have never been directly observed. In this study, we quantify BMP, WNT, and NODAL signaling dynamics in an in vitro model of human gastrulation. Our data suggest that BMP signaling initiates waves of WNT and NODAL signaling activity that move toward the colony center at a constant rate. Using a simple mathematical model, we show that this wave-like behavior is inconsistent with a reaction-diffusion-based Turing system, indicating that there is no stable signaling gradient of WNT/NODAL. Instead, the final signaling state is homogeneous, and spatial differences arise only from boundary effects. We further show that the durations of WNT and NODAL signaling control mesoderm differentiation, while the duration of BMP signaling controls differentiation of CDX2-positive extra-embryonic cells. The identity of these extra-embryonic cells has been controversial, and we use RNA sequencing (RNA-seq) to obtain their transcriptomes and show that they closely resemble human trophoblast cells in vivo. The domain of BMP signaling is identical to the domain of differentiation of these trophoblast-like cells; however, neither WNT nor NODAL forms a spatial pattern that maps directly to the mesodermal region, suggesting that mesoderm differentiation is controlled dynamically by the combinatorial effect of multiple signals. We synthesize our data into a mathematical model that accurately recapitulates signaling dynamics and predicts cell fate patterning upon chemical and physical perturbations. Taken together, our study shows that the dynamics of signaling events in the BMP, WNT, and NODAL cascade in the absence of a stable signaling gradient control fate patterning of human gastruloids.R01 GM126122 - NIGMS NIH HHSPublished versio

Designing signaling environments to steer transcriptional diversity in neural progenitor cell populations

Stem cell populations within developing embryos are diverse, composed of many different subpopulations of cells with varying developmental potential. The structure of stem cell populations in cell culture remains poorly understood and presents a barrier to differentiating stem cells for therapeutic applications. In this paper we develop a framework for controlling the architecture of stem cell populations in cell culture using high-throughput single cell mRNA-seq and computational analysis. We find that the transcriptional diversity of neural stem cell populations collapses in cell culture. Cell populations are depleted of committed neuron progenitor cells and become dominated by a single pre-astrocytic cell population. By analyzing the response of neural stem cell populations to forty distinct signaling conditions, we demonstrate that signaling environments can restructure cell populations by modulating the relative abundance of pre-astrocyte and pre-neuron subpopulations according to a simple linear code. One specific combination of BMP4, EGF, and FGF2 ligands switches the default population balance such that 70% of cells correspond to the committed neurons. Our work demonstrates that single-cell RNA-seq can be applied to modulate the diversity of in vitro stem cell populations providing a new strategy for population-level stem cell control

Dissecting Transcriptional Network in Mouse Embryonic Stem Cells

Ph.DDOCTOR OF PHILOSOPH

Defining Developmental Potency and Cell Lineage Trajectories by Expression Profiling of Differentiating Mouse Embryonic Stem Cells

Biologists rely on morphology, function and specific markers to define the differentiation status of cells. Transcript profiling has expanded the repertoire of these markers by providing the snapshot of cellular status that reflects the activity of all genes. However, such data have been used only to assess relative similarities and differences of these cells. Here we show that principal component analysis of global gene expression profiles map cells in multidimensional transcript profile space and the positions of differentiating cells progress in a stepwise manner along trajectories starting from undifferentiated embryonic stem (ES) cells located in the apex. We present three ‘cell lineage trajectories’, which represent the differentiation of ES cells into the first three lineages in mammalian development: primitive endoderm, trophoblast and primitive ectoderm/neural ectoderm. The positions of the cells along these trajectories seem to reflect the developmental potency of cells and can be used as a scale for the potential of cells. Indeed, we show that embryonic germ cells and induced pluripotent cells are mapped near the origin of the trajectories, whereas mouse embryo fibroblast and fibroblast cell lines are mapped near the far end of the trajectories. We suggest that this method can be used as the non-operational semi-quantitative definition of cell differentiation status and developmental potency. Furthermore, the global expression profiles of cell lineages provide a framework for the future study of in vitro and in vivo cell differentiation

Role of the Transcriptional Corepressor Bcor in Embryonic Stem Cell Differentiation and Early Embryonic Development

Bcor (BCL6 corepressor) is a widely expressed gene that is mutated in patients with X-linked Oculofaciocardiodental (OFCD) syndrome. BCOR regulates gene expression in association with a complex of proteins capable of epigenetic modification of chromatin. These include Polycomb group (PcG) proteins, Skp-Cullin-F-box (SCF) ubiquitin ligase components and a Jumonji C (Jmjc) domain containing histone demethylase. To model OFCD in mice and dissect the role of Bcor in development we have characterized two loss of function Bcor alleles. We find that Bcor loss of function results in a strong parent-of-origin effect, most likely indicating a requirement for Bcor in extraembryonic development. Using Bcor loss of function embryonic stem (ES) cells and in vitro differentiation assays, we demonstrate that Bcor plays a role in the regulation of gene expression very early in the differentiation of ES cells into ectoderm, mesoderm and downstream hematopoietic lineages. Normal expression of affected genes (Oct3/4, Nanog, Fgf5, Bmp4, Brachyury and Flk1) is restored upon re-expression of Bcor. Consistent with these ES cell results, chimeric animals generated with the same loss of function Bcor alleles show a low contribution to B and T cells and erythrocytes and have kinked and shortened tails, consistent with reduced Brachyury expression. Together these results suggest that Bcor plays a role in differentiation of multiple tissue lineages during early embryonic development

Aligning Single-Cell Developmental and Reprogramming Trajectories Identifies Molecular Determinants of Myogenic Reprogramming Outcome

Cellular reprogramming through manipulation of defined factors holds great promise for large-scale production of cell types needed for use in therapy and for revealing principles of gene regulation. However, most reprogramming systems are inefficient, converting only a fraction of cells to the desired state. Here, we analyze MYOD-mediated reprogramming of human fibroblasts to myotubes, a well-characterized model system for direct conversion by defined factors, at pseudotemporal resolution using single-cell RNA-seq. To expose barriers to efficient conversion, we introduce a novel analytic technique, trajectory alignment, which enables quantitative comparison of gene expression kinetics across two biological processes. Reprogrammed cells navigate a trajectory with branch points that correspond to two alternative decision points, with cells that select incorrect branches terminating at aberrant or incomplete reprogramming outcomes. Analysis of these branch points revealed insulin and BMP signaling as crucial molecular determinants of reprogramming. Single-cell trajectory alignment enables rigorous quantitative comparisons between biological trajectories found in diverse processes in development, reprogramming, and other contexts