PRJNA768453
Spatial genomics enables multi-modal study of clonal heterogeneity in tissues
The state and behavior of a cell can be influenced by both genetic and environmental factors. In particular, tumor progression is determined by underlying genetic aberrations as well as the makeup of the tumor microenvironment. Quantifying the contributions of these factors requires new technologies that can accurately measure the spatial location of genomic sequence together with phenotypic readouts. Here we developed slide-DNA-seq, a method for capturing spatially-resolved DNA sequences from intact tissue sections. We demonstrate that this method accurately preserves local tumor architecture and enables de novo discovery of distinct tumor clones and their copy number alterations. We then apply slide-DNA-seq to a mouse metastasis model and a primary human cancer, revealing that clonal populations are confined to distinct spatial regions. Moreover, through integration with spatial transcriptomics, we uncover distinct sets of genes that are associated with clone-specific genetic aberrations, the local tumor microenvironment, or both. Together, this multi-modal spatial genomics approach provides a versatile platform for quantifying how cell-intrinsic and extrinsic factors contribute to gene expression, protein abundance, and other cellular phenotypes.