Lineages and molecular heterogeneity in the developing nervous system

Information in the genome unfolds through a dynamic process leading to the molecular and anatomical organization of a physiologically functional organism. The nervous system is the most diverse and intricate architecture generated by this process. It is composed of hundreds of millions of cells of hundreds of different cell types, whose connectivity and interactions are the physiological underpinnings of our capacity to respond to stimuli, our ability to learn and our cognitive capabilities. In this thesis, I explore the formation of tissues in the nervous system during embryonic development. In particular, I focus on changes in molecular composition that lead progenitor cells to generate a complex mix of cell types. The specific aim of this work is to address the lack of complete and systematic knowledge of the heterogeneity of neural tissues and to describe the progression of a cell through different molecular states. To achieve this, I took advantage of the new opportunities offered by single-cell expression profiling technologies to gain a holistic view of a developing tissue. To contextualize the work, I review the relevant literature and conceptual framework. Starting with a historical perspective, I discuss the concept of cell type and how it relates to developmental dynamics and evolution. I then review different aspects of developmental neuroscience, starting with general principles and then focusing on the main areas of interest: the ventral midbrain, the sympathetic nervous system, and postnatal development. Then the technological advances instrumental for this thesis are reviewed, with a focus on analysis methods for single-cell RNA sequencing. Finally, I discuss the relationship between lineages and gene regulation, and I introduce the reader to the idea of a global time derivative of gene expression through traditional systems biology modeling. Then I present the results of three different studies. In paper I, we used single-cell RNA sequencing to describe the cell-type heterogeneity of sympathetic ganglia. We found seven distinct kinds of neurons, where only two had been previously described. Using lineage tracing, we shed light on the developmental origin of the new types. We linked their molecular profile to function and described how they innervate the erector muscles. Paper II describes the embryonic development of the ventral midbrain at the single-cell level. We characterized human and mouse embryonic tissues, identifying cell types and their homologies. We found an uncharacterized heterogeneity among radial glial cells and gained new insight into the timing of dopaminergic neurons specification. Finally, we presented a data-driven strategy to assess the quality of in vitro differentiation protocols. In paper III we addressed the major limitation of studying development with single-cell RNA sequencing: the absence of a temporal dimension. We described an analysis framework that uses the ratio of spliced to unspliced RNA abundance to estimate the time derivative of gene expression. The method was used to predict the future molecular states of cells and to determine their fate bias. In these studies, we produced a rich description of tissue heterogeneity and answered different biological questions. The results were achieved by harnessing the information contained in the data through analysis approaches inspired by developmental or physical principles. In summary, this thesis provides new insight into several aspects of mammalian nervous-system development, and it presents analytical approaches that I predict will inspire future investigation of the developmental dynamics of single-cells

Molecular analysis of the midbrain dopaminergic niche during neurogenesis

Midbrain dopaminergic (mDA) neurons degenerate in Parkinson’s disease and are one of the main targets for cell replacement therapies. However, a comprehensive view of the signals and cell types contributing to mDA neurogenesis is not yet available. By analyzing the transcriptome of the mouse ventral midbrain at a tissue and single-cell level during mDA neurogenesis we found that three recently identified radial glia types 1-3 (Rgl1-3) contribute to different key aspects of mDA neurogenesis. While Rgl3 expressed most extracellular matrix components and multiple ligands for various pathways controlling mDA neuron development, such as Wnt and Shh, Rgl1-2 expressed most receptors. Moreover, we found that specific transcription factor networks explain the transcriptome and suggest a function for each individual radial glia. A network controlling neurogenesis was found in Rgl1, progenitor maintenance in Rgl2 and the secretion of factors forming the mDA niche by Rgl3. Our results thus uncover a broad repertoire of developmental signals expressed by each midbrain cell type during mDA neurogenesis. Cells identified for their emerging importance are Rgl3, a niche cell type, and Rgl1, a neurogenic progenitor that expresses ARNTL, a transcription factor that we find is required for mDA neurogenesis

Molecular Diversity of Midbrain Development in Mouse, Human, and Stem Cells.

Understanding human embryonic ventral midbrain is of major interest for Parkinson's disease. However, the cell types, their gene expression dynamics, and their relationship to commonly used rodent models remain to be defined. We performed single-cell RNA sequencing to examine ventral midbrain development in human and mouse. We found 25 molecularly defined human cell types, including five subtypes of radial glia-like cells and four progenitors. In the mouse, two mature fetal dopaminergic neuron subtypes diversified into five adult classes during postnatal development. Cell types and gene expression were generally conserved across species, but with clear differences in cell proliferation, developmental timing, and dopaminergic neuron development. Additionally, we developed a method to quantitatively assess the fidelity of dopaminergic neurons derived from human pluripotent stem cells, at a single-cell level. Thus, our study provides insight into the molecular programs controlling human midbrain development and provides a foundation for the development of cell replacement therapies.All authors were supported by EU FP7 grant DDPDGENES. S.L. was supported by European Research Council grant 261063 (BRAINCELL), Knut and Alice Wallenberg Foundation grant 2015.0041, Swedish Research Council (STARGET), and the Swedish Foundation for Strategic Research (RIF14-0057). A.Z. was supported by the Human Frontier Science Program. E.A. was supported by Swedish Research Council (VR projects: 2011-3116 and 2011-3318), Swedish Foundation for Strategic Research (SRL program), and Karolinska Institutet (SFO Thematic Center in Stem cells and Regenerative Medicine). E.A. and R.A.B. were supported by the EU FP7 grant NeuroStemcellRepair. R.A.B. was also supported by an NIHR Biomedical Research Centre award to the University of Cambridge/Addenbrookes Hospital. iCell dopaminergic neurons were a generous gift from Cellular Dynamics International. Single-cell RNA-seq servic0es were provided by the Eukaryotic Single-cell Genomics facility and the National Genomics Infrastructure at Science for Life Laboratory.This is the final version of the article. It first appeared from Elsevier via https://doi.org/10.1016/j.cell.2016.09.02

Specious Art Metadata for Developing Mouse Brain Data

Metadata csv from dev_all.loom from La Manno et al., 202

Specious Art Raw Counts for Developing Mouse Brain Data

Raw count matrix from dev_all.loom from La Manno et al., 202

Specious Art Count Matrix for Developing Mouse Brain (La Manno et al 2020)

Log-normalized count matrix for dev_all.loom from La Manno et al 2020

The emergence and promise of single-cell temporal-omics approaches

Single-cell transcriptomics enables the measurement of gene expression in complex biological systems at the resolution of individual cells. Multivariate analysis of single-cell data helps describe the variation in expression accompanying cellular processes during embryonic development, disease progression and in response to stimuli. Likewise, new methods have extended the possibilities of single-cell analysis by measuring the transcriptome while simultaneously capturing information on lineage or past molecular events. These emerging approaches have the common strategy of querying a static snapshot for information related to different temporal stages. Single-cell temporal-omics methods open new possibilities such as extrapolating the future or correlating past events to present gene expression. We highlight advancements in the single-cell field, describe novel toolkits for investigation, and consider the potential impact of temporal-omics approaches for the study of disease progression

Single-cell transcriptional logic of cell-fate specification and axon guidance in early-born retinal neurons

Retinal ganglion cells (RGCs), cone photoreceptors (cones), horizontal cells and amacrine cells are the first classes of neurons produced in the retina. However, an important question is how this diversity of cell states is transcriptionally produced. Here, we profiled 6067 single retinal cells to provide a comprehensive transcriptomic atlas showing the diversity of the early developing mouse retina. RNA velocities unveiled the dynamics of cell cycle coordination of early retinogenesis and define the transcriptional sequences at work during the hierarchical production of early cell-fate specification. We show that RGC maturation follows six waves of gene expression, with older-generated RGCs transcribing increasing amounts of guidance cues for young peripheral RGC axons that express the matching receptors. Spatial transcriptionally deduced features in subpopulations of RGCs allowed us to define novel molecular markers that are spatially restricted. Finally, the isolation of such a spatially restricted population, ipsilateral RGCs, allowed us to identify their molecular identity at the time they execute axon guidance decisions. Together, these data represent a valuable resource shedding light on transcription factor sequences and guidance cue dynamics during mouse retinal development