Scalable, non-dissociative single-cell RNA sequencing for mapping the brain in health and disease

ABSTRACT A fundamental goal of the BRAIN Initiative and other neuroscience projects is to map cell types in the brain and study their changes associated with function, disease, and drug treatment. An important avenue toward it is to spatially analyze transcriptome of individual cells in morphologically intact tissues. However, despite recent advances of imaging and omics technologies, brain mapping projects still lack a non-dissociative (or spatial), global transcriptome profiling assay that can simultaneously provide a true single-cell resolution and a high RNA detection sensitivity similar to dissociative assays such as single-cell RNA sequencing (scRNA-seq) and single- nucleus RNA sequencing (snRNA-seq). The overall goal of this collaborative project between TopoGene (a university spinout) and the University of Washington (UW) is to (i) develop and optimize a non-dissociative scRNA-seq method for the brain mapping (Phase I), and (ii) scale it for commercial dissemination (Phase II). The PI in the UW Gu laboratory has recently developed a novel technique PIXEL-seq (polony-indexed library- sequencing) and applied it to spatially profile transcriptome with ≤ 1-µm resolution and high RNA capture efficiency. To realize its potential for the brain mapping with single-cell resolution, two specific aims will be pursued: 1) Optimize PIXEL-seq with various mouse brain tissues for three-dimensional (3D) transcriptome profiling; and 2) Develop and optimize transcript segmentation of PIXEL-seq data to achieve the non-dissociative scRNA-seq analysis. Under the first aim, PIXEL-seq will be optimized using brain tissues with different structures and sizes (Aim 1A) and demonstrated for the 3D transcriptome profiling by assaying consecutive sections and registering the data into a 3D atlas (Aim 1B). For the second aim, two transcript segmentation methods will be developed and optimized: a cell reference image-guided (Aim 2A) and a transcript read-based (Aim 2B) segmentation methods. The two methods will be assessed for the accuracy, reproducibility, and speed for the PIXEL-seq data analysis. This work will be conducted by a team with the expertise on technology development and transfer. The team will be supported by the UW’s commercialization center (CoMotion), the PI’s home institute (UW Institute for Protein Design), and a CoMotion’s incubator on campus (CoMotion Labs) on the IP protection, business development, and technology commercialization. The proposed method is innovative in that it will enable the spatial, global transcriptome profiling of brain tissues with true single-cell resolution. It is significant because by commercialization, this assay platform has the potential to become the standard single- cell transcriptomics or even multi-omics tool for the BRAIN Initiative and other single cell consortia and widely distributed for basic and clinical research.NARRATIVE The proposed research is relevant to public health because it focuses on developing and commercializing a novel technology for mapping the brain in health and disease. This technology will be used to spatially map gene expression in brain cells with high coverage, resolution, and sensitivity. Thus, the proposed research is relevant to the NIH’s mission that pertains to the understanding and treatment of brain disorders.