Spatial genomics enables multi-modal study of clonal heterogeneity in tissues
Author(s)
Zhao, Tongtong; Chiang, Zachary D; Morriss, Julia W; LaFave, Lindsay M; Murray, Evan M; Del Priore, Isabella; Meli, Kevin; Lareau, Caleb A; Nadaf, Naeem M; Li, Jilong; Earl, Andrew S; Macosko, Evan Z; Jacks, Tyler; Buenrostro, Jason D; Chen, Fei; ... Show more Show less
DownloadAccepted version (4.729Mb)
Open Access Policy
Open Access Policy
Creative Commons Attribution-Noncommercial-Share Alike
Terms of use
Metadata
Show full item recordAbstract
The state and behaviour of a cell can be influenced by both genetic and environmental factors. In particular, tumour progression is determined by underlying genetic aberrations1-4 as well as the makeup of the tumour microenvironment5,6. 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 tumour architecture and enables the de novo discovery of distinct tumour clones and their copy number alterations. We then apply slide-DNA-seq to a mouse model of metastasis 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 tumour microenvironment, or both. Together, this multi-modal spatial genomics approach provides a versatile platform for quantifying how cell-intrinsic and cell-extrinsic factors contribute to gene expression, protein abundance and other cellular phenotypes.
Date issued
2022Department
Massachusetts Institute of Technology. Department of BiologyJournal
Nature
Publisher
Springer Science and Business Media LLC
Citation
Zhao, Tongtong, Chiang, Zachary D, Morriss, Julia W, LaFave, Lindsay M, Murray, Evan M et al. 2022. "Spatial genomics enables multi-modal study of clonal heterogeneity in tissues." Nature, 601 (7891).
Version: Author's final manuscript