RESUMEN
Neuroblastoma is a pediatric cancer arising from the developing sympathoadrenal lineage with complex inter- and intra-tumoral heterogeneity. To chart this complexity, we generated a comprehensive cell atlas of 55 neuroblastoma patient tumors, collected from two pediatric cancer institutions, spanning a range of clinical, genetic, and histologic features. Our atlas combines single-cell/nucleus RNA-seq (sc/scRNA-seq), bulk RNA-seq, whole exome sequencing, DNA methylation profiling, spatial transcriptomics, and two spatial proteomic methods. Sc/snRNA-seq revealed three malignant cell states with features of sympathoadrenal lineage development. All of the neuroblastomas had malignant cells that resembled sympathoblasts and the more differentiated adrenergic cells. A subset of tumors had malignant cells in a mesenchymal cell state with molecular features of Schwann cell precursors. DNA methylation profiles defined four groupings of patients, which differ in the degree of malignant cell heterogeneity and clinical outcomes. Using spatial proteomics, we found that neuroblastomas are spatially compartmentalized, with malignant tumor cells sequestered away from immune cells. Finally, we identify spatially restricted signaling patterns in immune cells from spatial transcriptomics. To facilitate the visualization and analysis of our atlas as a resource for further research in neuroblastoma, single cell, and spatial-omics, all data are shared through the Human Tumor Atlas Network Data Commons at www.humantumoratlas.org.
RESUMEN
Previous studies have demonstrated the dynamic changes in chromatin structure during retinal development that correlate with changes in gene expression. However, a major limitation of those prior studies was the lack of cellular resolution. Here, we integrate single-cell (sc) RNA-seq and scATAC-seq with bulk retinal data sets to identify cell type-specific changes in the chromatin structure during development. Although most genes' promoter activity is strongly correlated with chromatin accessibility, we discovered several hundred genes that were transcriptionally silent but had accessible chromatin at their promoters. Most of those silent/accessible gene promoters were in the Müller glial cells. The Müller cells are radial glia of the retina and perform a variety of essential functions to maintain retinal homeostasis and respond to stress, injury, or disease. The silent/accessible genes in Müller glia are enriched in pathways related to inflammation, angiogenesis, and other types of cell-cell signaling and were rapidly activated when we tested 15 different physiologically relevant conditions to mimic retinal stress, injury, or disease in human and murine retinae. We refer to these as "pliancy genes" because they allow the Müller glia to rapidly change their gene expression and cellular state in response to different types of retinal insults. The Müller glial cell pliancy program is established during development, and we demonstrate that pliancy genes are necessary and sufficient for regulating inflammation in the murine retina in vivo. In zebrafish, Müller glia can de-differentiate and form retinal progenitor cells that replace lost neurons. The pro-inflammatory pliancy gene cascade is not activated in zebrafish Müller glia following injury, and we propose a model in which species-specific pliancy programs underly the differential response to retinal damage in species that can regenerate retinal neurons (zebrafish) versus those that cannot (humans and mice).
RESUMEN
More than 8,000 genes are turned on or off as progenitor cells produce the 7 classes of retinal cell types during development. Thousands of enhancers are also active in the developing retinae, many having features of cell- and developmental stage-specific activity. We studied dynamic changes in the 3D chromatin landscape important for precisely orchestrated changes in gene expression during retinal development by ultra-deep in situ Hi-C analysis on murine retinae. We identified developmental-stage-specific changes in chromatin compartments and enhancer-promoter interactions. We developed a machine learning-based algorithm to map euchromatin and heterochromatin domains genome-wide and overlaid it with chromatin compartments identified by Hi-C. Single-cell ATAC-seq and RNA-seq were integrated with our Hi-C and previous ChIP-seq data to identify cell- and developmental-stage-specific super-enhancers (SEs). We identified a bipolar neuron-specific core regulatory circuit SE upstream of Vsx2, whose deletion in mice led to the loss of bipolar neurons.