Project description:Animals are integrated organ systems composed of interacting cells whose structure and function are in turn defined by their active genes. Understanding what distinguishes physiological and disease states therefore requires systemic knowledge of the gene activities that define the distinct cells that make up an animal. Towards this goal, this study reports the first single-cell resolution transcriptional atlas of a fertile multicellular organism: Caenorhabditis elegans.
Project description:Single-cell technologies have ushered in a new era for Drosophila research, allowing researchers to obtain transcriptomes for all stable cell types and dynamic cell states. Here we present the first release of the adult Fly Cell Atlas (FCA), which includes 580k cells from 15 individually dissected sexed tissues, as well as from the entire head and body. We annotated more than 250 distinct cell types across all tissues. Few cell types were uniquely detected in the entire head and body samples, suggesting high cell-type saturation. We provide an in-depth analysis of gene signatures and transcription factor combinations, as well as sexual dimorphism, across the whole animal. Finally, we studied cell type lineages that are shared between tissues, such as blood cells and muscle cells, allowing the retrieval of rare cell types and tissue- specific subtypes. This atlas provides a valuable resource for the entire Drosophila community as a reference to study genetic perturbations and disease models at single-cell resolution.
Project description:The ciliary body is required for the maintenance of intraocular pressure and immunity as well as vision accommodation. We report a comprehensive cell atlas of human ciliary body from single-cell RNA sequencing (scRNAseq)
Project description:Brain maps are essential for integrating information and interpreting the structure-function relationship of circuits and behavior. We aimed to generate a systematic classification of the adult mouse brain organization based on unbiased extraction of spatially-defining features. Applying whole-brain spatial transcriptomics, we captured the gene expression signatures to define the spatial organization of molecularly discrete subregions. We found that the molecular code contained sufficiently detailed information to directly deduce the complex spatial organization of the brain. This unsupervised molecular classification revealed new area- and layer-specific subregions, for example in isocortex and hippocampus, and a new division of striatum. The whole-brain molecular atlas further supports the identification of the spatial origin of single neurons using their gene expression profile, and forms the foundation to define a minimal gene set - a brain palette – that is sufficient to spatially annotate the adult brain. In summary, we have established a new molecular atlas to formally define the identity of brain regions, and a molecular code for mapping and targeting of discrete neuroanatomical domains.