Highly scalable and sensitive spatial transcriptomic and epigenomic sequencing of brain tissues from human and non-human primate

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SUMMARY The human nervous system is possibly the most complex biological tissue, organized into multiple functionally distinct regions and comprised of over 200 billion neural and non-neural cells, requiring novel scalable tools to profile cell types and relationships in the tissue context with high spatial resolution. Recently, we developed DBiT-seq (high-spatial-resolution multi-omics sequencing via deterministic barcoding in tissue), which has demonstrated (i) high sensitivity (~5,000 UMIs per 10µm pixel), (ii) versatility as it does not require micropatterned DNA barcode arrays but only a set of reagents, and (iii) adoptability by potential users with no experience in advanced single molecule imaging or microfluidics. This BICCN project is capitalized on this novel technology developed by PI Rong Fan (Biomedical Engineer) and the long-standing experience of MPI Nenad Sestan (Neuroscience) in genomic analysis of human and non-human primate brain tissues, to further develop DBiT-seq into a highly scalable tool for BICCN to perform high-throughput, high-sensitivity, high- spatial-resolution, genome-wide mapping of brain tissues. Uniquely, we propose to develop a groundbreaking first-of-its-kind spatial epigenome sequencing technology based on deterministic barcoding in tissue, which may open up a new direction in the field of spatial omics research. We will apply spatial transcriptomics and spatial epigenomics to the mapping of 6 brain regions in human and non-human primate. Spatial omics data will be integrated with single-nucleus RNA-seq and ATAC-seq to generate spatially-resolved transcriptomic and epigenomic cell census at an unprecedented level. The contributions of this project to the BICCN consortium include: (1) fundamental knowledge on diverse cell types and their transcriptional and epigenomic characteristics in the context of 3D tissue organization in the brain and (2) validated high throughput and scalable approaches to characterizing cell diversity in human and/or non-human primate brain tissues. The resulting data will lead to a better understanding of the relationship between brain tissue organization, function, and epigenetic underpinnings. The technologies can be readily adopted by a BRAIN Initiative community and the data can be compared or integrated with datasets generated by other BICCN investigators