High-dimensional, spatially resolved analysis of intact tissue samples promises to transform biomedical research and diagnostics, but existing spatial omics technologies are costly and labor-intensive. We present FISHnCHIPs for highly sensitive in situ profiling of cell types and gene expression programs. FISHnCHIPs achieves this by simultaneously imaging ~2-35 co-expressed genes that are spatially co-localized in tissues, resulting in similar spatial information as single-gene FISH, but at ~2-20-fold higher sensitivity. Using FISHnCHIPs, we imaged up to 53 gene modules from the mouse kidney and mouse brain, and demonstrated high-speed, large field-of-view profiling of a whole tissue section. FISHnCHIPS also revealed spatially restricted localizations of cancer-associated fibroblasts in a human colorectal cancer biopsy. Overall, FISHnCHIPs enables robust and scalable spatial transcriptomics analysis of tissues with normal physiology or undergoing pathogenesis.
The version of this article initially published did not include the probe design software in the Code Availability statement. The statement has been updated to note the availability of probe design software at https://github.com/khchenLab/split-fish. In addition, as a result of a publisher error, the source data for Fig. 1 were provided as .xls files. These have been corrected to .tif files. The errors have been corrected in the HTML and PDF versions of the article.
In the version of Supplementary Table 3 originally posted for this article, an extra G nucleotide was inserted in error into all of the bridge sequences. The error has been corrected online.
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