Spatial genomics enables multi-modal study of clonal heterogeneity in tissues

Tongtong Zhao, Zachary D. Chiang, Julia W. Morriss, Lindsay M. LaFave, Evan M. Murray, Isabella Del Priore, Kevin Meli, Caleb A. Lareau, Naeem M. Nadaf, Jilong Li, Andrew S. Earl, Evan Z. Macosko, Tyler Jacks, Jason D. Buenrostro, Fei Chen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

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 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.

Original languageEnglish (US)
Pages (from-to)85-91
Number of pages7
JournalNature
Volume601
Issue number7891
DOIs
StatePublished - Jan 6 2022
Externally publishedYes

ASJC Scopus subject areas

  • General

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