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Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 μm. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency ~50% that of single-cell RNA-seq data (~10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts. An improved method for spatial transcriptomics with detection efficiency approaching that of droplet-based single-cell RNA-seq techniques.

Diverse types of glutamatergic pyramidal neurons mediate the myriad processing streams and output channels of the cerebral cortex 1 , 2 , yet all derive from neural progenitors of the embryonic dorsal telencephalon 3 , 4 . Here we establish genetic strategies and tools for dissecting and fate-mapping subpopulations of pyramidal neurons on the basis of their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen temporally inducible mouse Cre and Flp knock-in driver lines to enable the combinatorial targeting of major progenitor types and projection classes. Combinatorial strategies confer viral access to subsets of pyramidal neurons defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for understanding the hierarchical organization and developmental trajectory of subpopulations of pyramidal neurons that assemble cortical processing networks and output channels. A combination of genetic strategies and tools is used to define and fate-map different subtypes of glutamatergic pyramidal neurons according to their developmental and molecular programs, providing insight into the assembly of cortical processing networks.

The mammalian cerebral cortex has an unparalleled diversity of cell types, which are generated during development through a series of temporally orchestrated events that are under tight evolutionary constraint and are critical for proper cortical assembly and function 1 , 2 . However, the molecular logic that governs the establishment and organization of cortical cell types remains unknown, largely due to the large number of cell classes that undergo dynamic cell-state transitions over extended developmental timelines. Here we generate a comprehensive atlas of the developing mouse neocortex, using single-cell RNA sequencing and single-cell assay for transposase-accessible chromatin using sequencing. We sampled the neocortex every day throughout embryonic corticogenesis and at early postnatal ages, and complemented the sequencing data with a spatial transcriptomics time course. We computationally reconstruct developmental trajectories across the diversity of cortical cell classes, and infer their spatial organization and the gene regulatory programs that accompany their lineage bifurcation decisions and differentiation trajectories. Finally, we demonstrate how this developmental map pinpoints the origin of lineage-specific developmental abnormalities that are linked to aberrant corticogenesis in mutant mice. The data provide a global picture of the regulatory mechanisms that govern cellular diversification in the neocortex. A single-cell atlas of the developing mouse cortex provides a temporal and spatial assessment of the molecular logic that drives the establishment and organization of cortical cell types.

Interindividual genetic variation affects the susceptibility to and progression of many diseases 1 , 2 . However, efforts to study how individual human brains differ in normal development and disease phenotypes are limited by the paucity of faithful cellular human models, and the difficulty of scaling current systems to represent multiple people. Here we present human brain Chimeroids, a highly reproducible, multidonor human brain cortical organoid model generated by the co-development of cells from a panel of individual donors in a single organoid. By reaggregating cells from multiple single-donor organoids at the neural stem cell or neural progenitor cell stage, we generate Chimeroids in which each donor produces all cell lineages of the cerebral cortex, even when using pluripotent stem cell lines with notable growth biases. We used Chimeroids to investigate interindividual variation in the susceptibility to neurotoxic triggers that exhibit high clinical phenotypic variability: ethanol and the antiepileptic drug valproic acid. Individual donors varied in both the penetrance of the effect on target cell types, and the molecular phenotype within each affected cell type. Our results suggest that human genetic background may be an important mediator of neurotoxin susceptibility and introduce Chimeroids as a scalable system for high-throughput investigation of interindividual variation in processes of brain development and disease. An analysis in 3D multidonor Chimeroids—a scalable multidonor human brain organoid model—shows that human genetic background may be an important mediator of neurotoxin susceptibility.

Single-cell RNA sequencing (scRNAseq) has transformed our ability to explore biological systems. Nevertheless, proficient expertise is essential for handling and interpreting the data. In this article, we present scX, an R package built on the Shiny framework that streamlines the analysis, exploration, and visualization of single-cell experiments. With an interactive graphic interface, implemented as a web application, scX provides easy access to key scRNAseq analyses, including marker identification, gene expression profiling, and differential gene expression analysis. Additionally, scX seamlessly integrates with commonly used single-cell Seurat and SingleCellExperiment R objects, resulting in efficient processing and visualization of varied datasets. Overall, scX serves as a valuable and user-friendly tool for effortless exploration and sharing of single-cell data, simplifying some of the complexities inherent in scRNAseq analysis. Source code can be downloaded from https://github.com/chernolabs/scX. A docker image is available from dockerhub as chernolabs/scx.

Background: Cerebellar atrophy is a neuroradiological definition that categorizes conditions heterogeneous for clinical findings, disease course, and genetic defect. Most of the papers proposing a diagnostic workup for pediatric ataxias are based on neuroradiology or on the literature and experimental knowledge, with a poor participation of clinics in the process of disease definition. Our study aims to offer a different perspective on the way we approach cerebellar atrophy in developmental age, building a clinical-based diagnostic workup to guide molecular diagnosis. Methods: we recruited 52 patients with pediatric-onset cerebellar atrophy and definite disease categorization. Children underwent brain MRI, neurophysiological exams, metabolic investigations, and muscle biopsy with respiratory chain complex study. Single-gene sequencing, next-generation sequencing NGS panels, whole-exome sequencing (WES), and disease-specific techniques have been used to reach genetic confirmation. Results: Brain MRI is the main method of diagnosis, followed by tests on muscle biopsy and peripheral nervous system study. Other exams (e.g., metabolic investigations or evoked potentials) may be useful to narrow the list of diagnostic possibilities. Conclusions: We propose a diagnostic approach to cerebellar atrophy in children based on clinical findings, and support the evidence that a precise phenotypic definition may lead to the formulation of a definite diagnosis or otherwise guide the back phenotyping process derived from large molecular data.

Franco Taroni and colleagues report the identification of mutations in AFG3L2 that cause dominant spinocerebellar ataxia type 28. Along with paraplegin, AFG3L2 forms a protein complex with ATPase and metalloprotease activities and functions in the maintenance of the mitochondrial proteome. Autosomal dominant spinocerebellar ataxias (SCAs) are genetically heterogeneous neurological disorders characterized by cerebellar dysfunction mostly due to Purkinje cell degeneration. Here we show that AFG3L2 mutations cause SCA type 28. Along with paraplegin, which causes recessive spastic paraplegia, AFG3L2 is a component of the conserved m -AAA metalloprotease complex involved in the maintenance of the mitochondrial proteome. We identified heterozygous missense mutations in five unrelated SCA families and found that AFG3L2 is highly and selectively expressed in human cerebellar Purkinje cells. m -AAA–deficient yeast cells expressing human mutated AFG3L2 homocomplex show respiratory deficiency, proteolytic impairment and deficiency of respiratory chain complex IV. Structure homology modeling indicates that the mutations may affect AFG3L2 substrate handling. This work identifies AFG3L2 as a novel cause of dominant neurodegenerative disease and indicates a previously unknown role for this component of the mitochondrial protein quality control machinery in protecting the human cerebellum against neurodegeneration.

Mutations targeting distinct domains of the neuron-specific kinesin KIF5A associate with different neurodegenerative/neurodevelopmental disorders, but the molecular bases of this clinical heterogeneity are unknown. We characterised five key mutants covering the whole spectrum of KIF5A -related phenotypes: spastic paraplegia (SPG, R17Q and R280C), Charcot-Marie-Tooth disease (CMT, R864*), amyotrophic lateral sclerosis (ALS, N999Vfs*40), and neonatal intractable myoclonus (NEIMY, C975Vfs*73) KIF5A mutants. CMT-R864*-KIF5A and ALS-N999Vfs*40-KIF5A showed impaired autoinhibition and peripheral localisation accompanied by altered mitochondrial distribution, suggesting transport competence disruption. ALS-N999Vfs*40-KIF5A formed SQSTM1/p62-positive inclusions sequestering WT-KIF5A, indicating a gain of toxic function. SPG-R17Q-KIF5A and ALS-N999Vfs*40-KIF5A evidenced a shorter half-life compared to WT-KIF5A, and proteasomal blockage determined their accumulation into detergent-insoluble inclusions. Interestingly, SPG-R280C-KIF5A and ALS-N999Vfs*40-KIF5A both competed for degradation with proteasomal substrates. Finally, NEIMY-C975Vfs*73-KIF5A displayed a similar, but more severe aberrant behaviour compared to ALS-N999Vfs*40-KIF5A; these two mutants share an abnormal tail but cause disorders on the opposite end of KIF5A -linked phenotypic spectrum. Thus, our observations support the pathogenicity of novel KIF5A mutants, highlight abnormalities of recurrent variants, and demonstrate that both unique and shared mechanisms underpin KIF5A -related diseases.