Hannah A. Pliner

Aging is accompanied by a host of social and biological changes that correlate with behavior, cognitive health and susceptibility to neurodegenerative disease. To understand trajectories of brain aging in a primate, we generated a multiregion bulk (N = 527 samples) and single-nucleus (N = 24 samples) brain transcriptional dataset encompassing 15 brain regions and both sexes in a unique population of free-ranging, behaviorally phenotyped rhesus macaques. We demonstrate that age-related changes in the level and variance of gene expression occur in genes associated with neural functions and neurological diseases, including Alzheimer’s disease. Further, we show that higher social status in females is associated with younger relative transcriptional ages, providing a link between the social environment and aging in the brain. Our findings lend insight into biological mechanisms underlying brain aging in a nonhuman primate model of human behavior, cognition and health.

The genomics of human development: Understanding the trajectory of a developing human requires an understanding of how genes are regulated and expressed. Two papers now present a pooled approach using three levels of combinatorial indexing to examine the single-cell gene expression and chromatin landscapes from 15 organs in fetal samples. Cao et al. focus on measurements of RNA in broadly distributed cell types and provide insights into organ specificity. Domcke et al. examined the chromatin accessibility of cells from these organs and identify the regulatory elements that regulate gene expression. Together, these analyses generate comprehensive atlases of early human development. Science , this issue p. eaba7721 , p. eaba7612

The genomics of human development: Understanding the trajectory of a developing human requires an understanding of how genes are regulated and expressed. Two papers now present a pooled approach using three levels of combinatorial indexing to examine the single-cell gene expression and chromatin landscapes from 15 organs in fetal samples. Cao et al. focus on measurements of RNA in broadly distributed cell types and provide insights into organ specificity. Domcke et al. examined the chromatin accessibility of cells from these organs and identify the regulatory elements that regulate gene expression. Together, these analyses generate comprehensive atlases of early human development. Science , this issue p. eaba7721 , p. eaba7612

Single-cell chemical transcriptomics: Single-cell transcriptomic technologies have emerged as powerful tools to explore cellular heterogeneity at the resolution of individual cells. Srivatsan et al. now add another layer of information and complexity by combining single-cell transcriptomics with oligo hashing and small molecule screening in a method called sci-Plex. Because screening many chemical compounds requires the ability to profile many cells, and because screens perturb cells in many different ways, the authors demonstrate the effects of 188 compounds in three cancer lines. The sci-Plex method can capture gene expression profiles from thousands of experimental conditions in a single experiment. Science , this issue p. 45

Single-cell molecular profiling technologies are gaining rapid traction, but the manual process by which resulting cell types are typically annotated is labor intensive and rate-limiting. We describe Garnett, a tool for rapidly annotating cell types in single-cell transcriptional profiling and single-cell chromatin accessibility datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.

Here we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of a single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq); a software suite, scitools, for the rapid processing and visualization of single-cell combinatorial indexing data sets; and a valuable resource of hippocampal regulatory networks at single-cell resolution. We used sci-ATAC-seq to produce 2346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. By using this data set, we identified eight distinct major clusters of cells representing both neuronal and nonneuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. Within pyramidal neurons, we identified four major clusters, including CA1 and CA3 neurons, and three additional subclusters. We then applied a recently described coaccessibility framework, Cicero, which identified 146,818 links between promoters and putative distal regulatory DNA. Identified coaccessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we performed an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared with nuclei from hippocampal tissue. This data set and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.

Single cell technologies for profiling tissues or even entire organisms are rapidly being adopted. However, the manual process by which cell types are typically annotated in the resulting data is labor-intensive and increasingly rate-limiting for the field. Here we describe Garnett, an algorithm and accompanying software for rapidly annotating cell types in scRNA-seq and scATAC-seq datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.

Single-cell chromatin and RNA analysis: Single-cell analyses have begun to provide insight into the differences among and within the individual cells that make up a tissue or organism. However, technological barriers owing to the small amount of material present in each single cell have prevented parallel analyses. Cao et al. present sci-CAR, a pooled barcode method that jointly analyzes both the RNA transcripts and chromatin profiles of single cells. By applying sci-CAR to lung adenocarcinoma cells and mouse kidney tissue, the authors demonstrate precision in assessing expression and genome accessibility at a genome-wide scale. The approach provides an improvement over bulk analysis, which can be confounded by differing cellular subgroups. Science , this issue p. 1380

Here we present a comprehensive map of the accessible chromatin landscape of the mouse hippocampus at single-cell resolution. Substantial advances of this work include the optimization of single-cell combinatorial indexing assay for transposase accessible chromatin (sci-ATAC-seq), a software suite, scitools , for the rapid processing and visualization of single-cell combinatorial indexing datasets, and a valuable resource of hippocampal regulatory networks at single-cell resolution. We utilized sci-ATAC-seq to produce 2,346 high-quality single-cell chromatin accessibility maps with a mean unique read count per cell of 29,201 from both fresh and frozen hippocampi, observing little difference in accessibility patterns between the preparations. Using this dataset, we identified eight distinct major clusters of cells representing both neuronal and non-neuronal cell types and characterized the driving regulatory factors and differentially accessible loci that define each cluster. We then applied a recently described co-accessibility framework, Cicero , which identified 146,818 links between promoters and putative distal regulatory DNA. Identified co-accessibility networks showed cell-type specificity, shedding light on key dynamic loci that reconfigure to specify hippocampal cell lineages. Lastly, we carried out an additional sci-ATAC-seq preparation from cultured hippocampal neurons (899 high-quality cells, 43,532 mean unique reads) that revealed substantial alterations in their epigenetic landscape compared to nuclei from hippocampal tissue. This dataset and accompanying analysis tools provide a new resource that can guide subsequent studies of the hippocampus.