Our RAEFISH spatial transcriptomics technology is now published in Cell @CellCellPress! RAEFISH enables sequencing-free whole genome spatial transcriptomics at single molecule resolution. This work represents the first time that transcripts from more than 23,000 genes were directly probed and imaged in situ with any technology, and the first time numerous different gRNAs were directly probed and distinguished by imaging in a high-content CRISPR screen. The challenge: Recent breakthroughs in spatial transcriptomic technologies, from us and others, have greatly improved our ability to profile cell types, states, cellular interactions, and the underlying gene programs within the native tissue contexts. However, these technologies have limitations. Methods based on 2D-array-capture/tagging and ex situ sequencing offer genome-scale coverage, but lack the resolution needed to accurately study fine spatial organization. In contrast, image-based methods that rely on highly multiplexed fluorescence in situ hybridization or in situ sequencing provide single-molecule resolution and resolve fine spatial organization, but require pre-selecting a limited set of target genes (typically hundreds to a few thousand genes), which limits discovery and sometimes leads to only validations of prior knowledge due to the pre-selected targets being well studied in the context. The solution: RAEFISH, our lab's new flagship image-based spatial transcriptomics technology, simultaneously enables single-molecule spatial resolution and whole-genome level coverage of long and short, endogenous and engineered RNA species in cell cultures and intact tissues. The results: 🔥 We performed RAEFISH targeting 23,312 human genes in cell cultures, and demonstrated hypothesis-free discovery of cell cycle associated genes and subcellular localization patterns of transcripts, including nearly the entire protein coding transcriptome and additional long noncoding RNAs. 🔥 We performed RAEFISH targeting 21,955 mouse genes in mouse liver, placenta, and lymph node tissues. Our analyses on immediately neighboring cells uncovered intriguing cell-cell interactions and previously unknown gene expression programs underlying the interactions, such as those between cholangiocytes and immune cells. 🔥 Finally, we further developed RAEFISH to directly read out guide RNAs (gRNAs), demonstrating Perturb-RAEFISH in an image-based high-content CRISPR screen. The capacity of Perturb-RAEFISH to directly read out gRNAs addresses a crucial limitation of previous techniques that read out a barcode/identifier sequence paired with each gRNA species, as the pairing can be shuffled due to RNA recombination intrinsic to lentivirus used in such screens, which limits screen sensitivity and accuracy. In summary, RAEFISH provides the biomedical research community with a generalizable research tool, which will bring more spatial and mechanistic insights across health and disease. This work was co-led by my postdocs Drs. @ChengYubao, Shengyuan Dang, and Yuan Zhang, and was supported by the @NIH, @genome_gov, @sennetresearch, and @psscra. I would like to thank our co-authors, funding agencies, editor, reviewers, and my whole lab @YaleGenetics @YaleCellBio @YaleCancer @YaleMed @Yale. Link to paper: cell.com/cell/fulltext/S0092…