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

Authors :
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
Source :
Nature; 20210101, Issue: Preprints p1-7, 7p
Publication Year :
2021

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 aberrations1–4as 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.

Details

Language :
English
ISSN :
00280836 and 14764687
Issue :
Preprints
Database :
Supplemental Index
Journal :
Nature
Publication Type :
Periodical
Accession number :
ejs58495549
Full Text :
https://doi.org/10.1038/s41586-021-04217-4