We have recently developed intron seqFISH (sequential Fluorescence in situ hybridization) to multiplex 10,421 genes directly in single cells. We showed that the 10,421 gene nascent transcriptome profile can identify cell types as well as capture the trajectory of the cells. We further demonstrated that we can perform mRNA seqFISH as well as immunostaining in the same cells following the 10,421 gene intron seqFISH measurement. We propose to develop this technology as a potential alternative approach to single cell RNAseq for the HuBMAP to characterize cell types directly in situ in tissues. In particular, we will adept in situ amplification methods such as hybridization chain reaction (HCR) to intron seqFISH. We had previously shown that mRNA seqFISH with HCR amplification performs exceptionally in tissues in overcoming autofluorescence background and enable robust decoding seqFISH barcodes. We will validate the integrated intron and mRNA seqFISH protocol in the mouse hippocampus in the UG3 phase of the project. Also in UG3 phase, we will develop computational tools to integrate intron seqFISH data with mRNA seqFISH as well as single cell RNAseq data. In the UH3 phase, we will translate the technology to human tissues, with a focus on human mammary tissues provided by Dr. Seewaldt at City of Hope. We will also work with the tissue mapping centers in the HuBMAP program to accelerate the translation of this technology to many tissue types. In the UH3 phase, we will generate million cell spatial atlas of human tissues containing intron profiles, mRNA profiles and protein abundances in each single cell. We will further develop computational tools to analyze for spatial enrichment of genes in the tissue and generate a pseudotime of developmental trajectories using the nascent transcriptome data. Taken together, we will develop a high throughput in situ imaging based platform to characterize cell types and future trajectories of cells using intron and mRNA seqFISH technologies.
Transcriptome profiling in situ at the single cell level has transformative potential for understanding healthy versus diseased tissues in the human body. We propose an integrative approach profiling the nascent transcriptome as well as hundreds of mature transcripts in single cells in tissues. We will generate million cell spatial atlas for the mouse hippocampus as well as the human mammary tissue. We will gain unprecedented insight into the developmental of neurons in the brain as well as the duct cells in the breast. At the same time we will develop the computational tools to analyze the spatial genomics data.
