Transcriptomic cellular diversity of the early human developing brain

The complexity of the mammalian brain is partly reflected in its cell type diversity which influences the function of neurons that encode the behavior of animals. Brain cell type diversity emerges during embryonic stages, a critical period when neurons start to become functionally active and establish their connectivity across the brain. Since the pioneering of single-cell RNA-sequencing (scRNA-seq), we can question when and how cellular diversity arises in the brain in a large-scale manner. This thesis aims to study the human brain during the first trimester by using scRNA-seq to obtain a global view of the basic principles of the developing brain. First, I introduce human embryology from a historical perspective and summarize key concepts in central nervous system (CNS) development. I review few gaps in the field related to our findings, followed by current approaches and nomenclatures used in the field of single-cell genomics that applies to development. To put our work into perspective, I present an overview of the latest efforts to study human brain development at the single-cell level, both in the healthy and diseased brain. Then I present the following two papers and a manuscript: In Paper I we used scRNA-seq to construct a cell taxonomy of the adult mouse nervous system. We describe two major groups: neuronal- and non-neuronal cells that were subdivided into distinct cell types. Overall, the neurons were transcriptionally similar across brain regions, whereas non-neuronal cells such as astrocytes, formed subgroups and were regionally distinct. The whole dataset revealed an organization that reflects the developmental origin of all cell types. Paper II describes a method, RNA velocity, that infers temporal changes from static scRNAseq gene expression measurements. By realigning sequencing reads, this method detects and makes use of the unspliced and spliced mRNA, whose relative abundance is used to measure the change of rate in gene expression (the time derivative) in different tissues. This method is particularly suitable for developmental lineages, which was shown and validated both in vitro and in situ in this study. Paper III presents a single-cell atlas of the human developing CNS across all major brain regions during postconceptional weeks (p.c.w.) 5 to 14. We observe that major cell classes emerge during this period, most of them being regionally diverse and to a surprisingly high degree among glial cells. We display the high resolution of this data by resolving several lineages in the forebrain and validated the spatial location of transcriptional cell types at 5 p.c.w. by using single-molecule FISH. As a whole, this study represents a reference of human brain development during the first critical period in life. To tie these studies together, our findings on glial diversity were partially shared between the adult mouse and developing human CNS. We further showed that an RNA velocity-based method can be used to model the cell cycle dynamics in cortical tissue. To conclude, I discuss advantages and limitations of single-cell transcriptomics, its future challenges and how using this technology sheds light on the early human developing brain as is described in this thesis

Single-cell meta-analysis of SARS-CoV-2 entry genes across tissues and demographics

Angiotensin-converting enzyme 2 (ACE2) and accessory proteases (TMPRSS2 and CTSL) are needed for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cellular entry, and their expression may shed light on viral tropism and impact across the body. We assessed the cell-type-specific expression of ACE2, TMPRSS2 and CTSL across 107 single-cell RNA-sequencing studies from different tissues. ACE2, TMPRSS2 and CTSL are coexpressed in specific subsets of respiratory epithelial cells in the nasal passages, airways and alveoli, and in cells from other organs associated with coronavirus disease 2019 (COVID-19) transmission or pathology. We performed a meta-analysis of 31 lung single-cell RNA-sequencing studies with 1,320,896 cells from 377 nasal, airway and lung parenchyma samples from 228 individuals. This revealed cell-type-specific associations of age, sex and smoking with expression levels of ACE2, TMPRSS2 and CTSL. Expression of entry factors increased with age and in males, including in airway secretory cells and alveolar type 2 cells. Expression programs shared by ACE2+TMPRSS2+ cells in nasal, lung and gut tissues included genes that may mediate viral entry, key immune functions and epithelial-macrophage cross-talk, such as genes involved in the interleukin-6, interleukin-1, tumor necrosis factor and complement pathways. Cell-type-specific expression patterns may contribute to the pathogenesis of COVID-19, and our work highlights putative molecular pathways for therapeutic intervention

Profiling spatiotemporal gene expression of the developing human spinal cord and implications for ependymoma origin

The authors created a comprehensive developmental cell atlas for spatiotemporal gene expression of the human spinal cord, revealed species-specific regulation during development and used the atlas to infer novel markers for pediatric ependymomas. The spatiotemporal regulation of cell fate specification in the human developing spinal cord remains largely unknown. In this study, by performing integrated analysis of single-cell and spatial multi-omics data, we used 16 prenatal human samples to create a comprehensive developmental cell atlas of the spinal cord during post-conceptional weeks 5-12. This revealed how the cell fate commitment of neural progenitor cells and their spatial positioning are spatiotemporally regulated by specific gene sets. We identified unique events in human spinal cord development relative to rodents, including earlier quiescence of active neural stem cells, differential regulation of cell differentiation and distinct spatiotemporal genetic regulation of cell fate choices. In addition, by integrating our atlas with pediatric ependymomas data, we identified specific molecular signatures and lineage-specific genes of cancer stem cells during progression. Thus, we delineate spatiotemporal genetic regulation of human spinal cord development and leverage these data to gain disease insight

RNA velocity of single cells

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput 1 . However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity—the time derivative of the gene expression state—can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans

Spatial Dynamics of the Developing Human Heart

Heart development relies on a topologically defined interplay between a diverse array of cardiac cells. We finely curated spatial and single-cell measurements with subcellular imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. In summary, our study delineates the cellular and molecular landscape of the developing heart’s architecture, offering links to genetic causes of heart disease.QC 20240411</p

Spatial Dynamics of the Developing Human Heart

Heart development relies on a topologically defined interplay between a diverse array of cardiac cells. We finely curated spatial and single-cell measurements with subcellular imaging-based transcriptomics validation to explore spatial dynamics during early human cardiogenesis. Analyzing almost 80,000 individual cells and 70,000 spatially barcoded tissue regions between the 5.5th and 14th postconceptional weeks, we identified 31 coarse- and 72 fine-grained cell states and mapped them to highly resolved cardiac cellular niches. We provide novel insight into the development of the cardiac pacemaker-conduction system, heart valves, and atrial septum, and decipher heterogeneity of the hitherto elusive cardiac fibroblast population. Furthermore, we describe the formation of cardiac autonomic innervation and present the first spatial account of chromaffin cells in the fetal human heart. In summary, our study delineates the cellular and molecular landscape of the developing heart’s architecture, offering links to genetic causes of heart disease.QC 20240411</p

A topographic atlas defines developmental origins of cell heterogeneity in the human embryonic lung

Sountoulidis et al. provide a spatial gene expression atlas of human embryonic lung during the first trimester of gestation and identify 83 cell identities corresponding to stable cell types or transitional states. The lung contains numerous specialized cell types with distinct roles in tissue function and integrity. To clarify the origins and mechanisms generating cell heterogeneity, we created a comprehensive topographic atlas of early human lung development. Here we report 83 cell states and several spatially resolved developmental trajectories and predict cell interactions within defined tissue niches. We integrated single-cell RNA sequencing and spatially resolved transcriptomics into a web-based, open platform for interactive exploration. We show distinct gene expression programmes, accompanying sequential events of cell differentiation and maturation of the secretory and neuroendocrine cell types in proximal epithelium. We define the origin of airway fibroblasts associated with airway smooth muscle in bronchovascular bundles and describe a trajectory of Schwann cell progenitors to intrinsic parasympathetic neurons controlling bronchoconstriction. Our atlas provides a rich resource for further research and a reference for defining deviations from homeostatic and repair mechanisms leading to pulmonary diseases