Citation

Zhao T, Chiang ZD, Morriss JW, LaFave LM, Murray EM, Del Priore I, Meli K, Lareau CA, Nadaf NM, Li J, Earl AS, Macosko EZ, Jacks T, Buenrostro JD, Chen F. 2022. Spatial genomics enables multi-modal study of clonal heterogeneity in tissues. Nature. 601(7891):85-91. Pubmed: 34912115 DOI:10.1038/s41586-021-04217-4

Abstract

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 aberrations as well as the makeup of the tumour 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 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.
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.

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The Buenrostro lab is broadly dedicated to advancing our knowledge of gene regulation and the downstream consequences on cell fate decisions.

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