Abstract

Single-cell RNA-seq (scRNAseq) is a powerful tool to classify cells into molecularly defined cell types. However, information about spatial location within the original tissue is lost. I will present work on developing and applying targeted in situ sequencing (ISS) to build spatial maps of scRNAseq-defined celltypes in cm2 sections of human and mouse tissues. We have applied the method to draw spatial cell maps of human developmental heart tissue, where marker genes were selected from both Spatial Transcriptomics and scRNAseq data (Asp et al. (2019) Cell, 179, 1647-1660). We have continued this work and are currently finalizing human developmental lung maps. We have improved the ISS chemistry to improve signal-to-noise, and detection efficiency which has allowed us to map expression of 160 genes in human brain cortex, samples that are challenging to analyze due to high autofluorescence (Gyllborg, et al. (2020) bioRxiv). We are also using our targeted in situ sequencing to map expression- and mutational heterogeneity in tumors (Lomakin, et al. (2021) bioRxiv). By targeting mutations identified by deep sequencing, we create maps of clones of subtypes of cancer cells across tissue sections. We then overlay these maps with in situ expression profiles of tumor marker genes, as well as, immune celltype- and activity markers, to create oncomaps where we aim to predict treatment responses for different sub-clones of the tumor.