Single cell transcriptional and epigenomic atlas of the macaque brain across the lifespan

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ABSTRACT / SUMMARY New technologies are enabling molecular profiling of single brain cells at remarkable throughput. However, these new methods have yet to be extensively applied to the brains of model organisms that bridge the evolutionary distance between mouse and human, including the most common nonhuman primate model system - the rhesus macaque. Here we propose to generate an anatomically resolved, single cell atlas of the epigenome (5.5 million cells) and transcriptome (11 million cells) of the rhesus macaque brain. We will apply two methods, recently developed in our labs, that rely on “combinatorial indexing” to cost-effectively profile the epigenomes (sci-ATAC-seq) and transcriptomes (sci-RNA-seq) of large numbers of cells or nuclei. As our first aim, we will generate high resolution, single cell epigenetic and transcriptional atlases of one male and one female rhesus macaque brain. Specifically, we will profile chromatin accessibility in 750,000 nuclei (sci-ATAC- seq) and transcription in 1,500,000 nuclei (sci-RNA-seq) from each of two macaque brains (for a total of 4.5 million cells). These will be obtained from 25 anatomically dissected brain regions (30,000 sci-ATAC-seq and 60,000 sci-RNA-seq profiles per region per brain). As our second aim, we will extend these atlases to span the primate lifespan. Specifically, we will perform single cell epigenetic and transcriptional profiling of the brains of 50 additional rhesus macaques (25 regions per brain; 3,200 sci-ATAC-seq and 6,400 sci-RNA-seq profiles per individual/region, for a total of 12 million molecularly profiled cells). This large sample size will allow us to characterize natural variation in chromatin accessibility and transcription within each cell type, between individuals, sexes, and across the natural lifespan of rhesus macaques. At 16.5 million cells, our rhesus macaque brain atlas will comprise the largest transcriptional and epigenomic single cell dataset of any primate organ to date. Our data will be rapidly shared with BICCN and the broader community. We anticipate it will be an essential resource, complementary to other efforts, for identifying the distribution and function of key cell types across the primate brain, allowing for the development of cell type- and region-specific molecular interventions that will help us understand brain function and the etiology, and potentially the treatment, of brain disorders.