Biology subjects

Lonnerberg, P.

Publications and source records attributed to Lonnerberg, P..

7 recordsLinked to original sources

bioRxiv2025

Cell atlas of the developing human meninges reveals a dura origin of meningioma

The vertebrate central nervous system is enveloped by the meninges, consisting of the pia, arachnoid, and dura layers. The arachnoid is hypothesised to give rise to the most common primary intracranial tumours, meningiomas. However, molecular evidence supporting this hypothesis is lacking. There are no effective medical therapies to treat meningiomas that are resistant to local interventions, encumbered by our limited understanding of their cellular origin. To address this limitation in our understanding of meningioma biology, we generated a comprehensive reference single cell and spatial transcriptomic atlas of human fetal meninges at post-conceptional weeks 5-13. We found that the meningeal layers develop concurrently, and identified an inner CDH1-positive dura cell layer expressing tight junction genes consistent with barrier function. We show that transcriptionally, meningioma cells resemble dura-lineage cells, and that common meningioma driver genes were expressed preferentially in the dura lineage. Our findings suggest that meningiomas originate from dura lineage cells. HIGHLIGHTSO_LIscRNA-seq and spatial transcriptomics reveals architecture of human fetal meninges development C_LIO_LIMeningeal layers are formed concurrently, by a gradual refinement of cell states C_LIO_LIA CDH1+ inner dura sublayer expresses tight junction genes like the arachnoid barrier C_LIO_LIMeningioma tumours likely originate from inner dura lineage cells, not arachnoid C_LI

developmental biology↗

bioRxiv2023

Dynamics of chromatin accessibility during human first-trimester neurodevelopment

The human brain is capable of highly complex functions that develops through a tightly organized cascade of patterning events, expressed transcription factors and changes in chromatin accessibility. While extensive datasets exist describing gene expression across the developing brain with single-cell resolution, similar atlases of chromatin accessibility have been primarily focused on the forebrain. Here, we focus on the chromatin landscape and paired gene expression across the developing human brain to provide a comprehensive single cell atlas during the first trimester (6 - 13 post-conceptional weeks). We identified 135 clusters across half a million nuclei and using the multiomic measurements linked candidate cis-regulatory elements (cCREs) to gene expression. We found an increase in the number of accessible regions driven both by age and neuronal differentiation. Using a convolutional neural network we identified putative functional TF-binding sites in enhancers characterizing neuronal subtypes and we applied this model to cCREs upstream of ESRRB to elucidate its activation mechanism. Finally, by linking disease-associated SNPs to cCREs we validated putative pathogenic mechanisms in several diseases and identified midbrain-derived GABAergic neurons as being the most vulnerable to major depressive disorder related mutations. Together, our findings provide a higher degree of detail to some key gene regulatory mechanisms underlying the emergence of cell types during the first trimester. We anticipate this resource to be a valuable reference for future studies related to human neurodevelopment, such as identifying cell type specific enhancers that can be used for highly specific targeting in in vitro models.

developmental biology↗

bioRxiv2020

Single cell transcriptomics of primate sensory neurons identifies cell types associated with human chronic pain

Distinct types of dorsal root ganglion sensory neurons may have unique contributions to chronic pain. Identification of primate sensory neuron types is critical for understanding the cellular origin and heritability of chronic pain. However, molecular insights into the primate sensory neurons are missing. Here we classify non-human primate dorsal root ganglion sensory neurons based on their transcriptome and map human pain heritability to neuronal types. First, we identified cell correlates between two major datasets for mouse sensory neuron types. Machine learning exposes an overall cross-species conservation of somatosensory neurons between primate and mouse, although with differences at individual gene level, highlighting the importance of primate data for clinical translation. We map genomic loci associated with chronic pain in human onto primate sensory neuron types to identify the cellular origin of human chronic pain. Genome-wide associations for chronic pain converge on two different neuronal types distributed between pain disorders that display different genetic susceptibilities, suggesting both unique and shared mechanisms between different pain conditions.

neuroscience↗

bioRxiv2020

Spatial tissue profiling by imaging-free molecular tomography

Genomics techniques are currently being adapted to provide spatially resolved omics profiling. However, the adaptation of each new method typically requires the setup of specific detection strategies or specialized instrumentation. A generic approach to spatially resolve different types of high throughput data is missing. Here, we describe an imaging-free framework to localize high throughput readouts within a tissue by combining compressive sampling and image reconstruction. We implemented this framework to transform a low-input RNA sequencing protocol into an imaging-free spatial transcriptomics technique (STRP-seq) and validated this method with a transcriptome profiling of the murine brain. To verify the broad applicability of STRP-seq, we applied the technique on the brain of the Australian bearded dragon Pogona vitticeps. Our results reveal the molecular anatomy of the telencephalon of this lizard, providing evidence for a marked regionalization of the reptilian pallium and subpallium. Overall, the proposed framework constitutes a new approach that allows upgrading in a generic fashion conventional genomic assays to spatially resolved techniques.

genomics↗

bioRxiv2020

Molecular architecture of the developing mouse brain

The mammalian brain develops through a complex interplay of spatial cues generated by diffusible morphogens, cell-cell interactions, and intrinsic genetic programs that result in the generation of likely more than a thousand distinct cell types. Therefore, a complete understanding of mammalian brain development requires systematic mapping of cell states covering the entire relevant spatiotemporal range. Here we report a comprehensive single-cell transcriptome atlas of mouse brain development spanning from gastrulation to birth. We identified almost a thousand distinct cellular states, including the initial emergence of the neuroepithelium, a rich set of region-specific secondary organizers and a complete developmental program for the functional elements of the brain and its enclosing membranes. We used the atlas to directly test the hypothesis that human glioblastoma reflects a return to a developmental cell state. In agreement, most aneuploid tumor cells matched embryonic rather than adult types, while karyotypically normal cells predominantly matched adult immune cell types.Competing Interest StatementThe authors have declared no competing interest.View Full Text

developmental biology↗

bioRxiv2018

Molecular architecture of the mouse nervous system

The mammalian nervous system executes complex behaviors controlled by specialised, precisely positioned and interacting cell types. Here, we used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy. Neurons were the most diverse, and were grouped by developmental anatomical units, and by the expression of neurotransmitters and neuropeptides. Neuronal diversity was driven by genes encoding cell identity, synaptic connectivity, neurotransmission and membrane conductance. We discovered several distinct, regionally restricted, astrocytes types, which obeyed developmental boundaries and correlated with the spatial distribution of key glutamate and glycine neurotransmitters. In contrast, oligodendrocytes showed a loss of regional identity, followed by a secondary diversification. The resource presented here lays a solid foundation for understanding the molecular architecture of the mammalian nervous system, and enables genetic manipulation of specific cell types.

neuroscience↗

bioRxiv2017

RNA velocity in single cells

RNA abundance is a powerful indicator of the state of individual cells, but does not directly reveal dynamic processes such as cellular differentiation. Here we show that RNA velocity--the time derivative of RNA abundance--can be estimated by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. We show that RNA velocity is a vector that predicts the future state of individual cells on a timescale of hours. We validate the accuracy of RNA velocity in the neural crest lineage, demonstrate its use on multiple technical platforms, reconstruct the branching lineage tree of the mouse hippocampus, and measure RNA kinetics in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.

genomics↗