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

doi:10.1038/s41586-021-04217-4

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

Nature. 2022 Jan;601(7891):85-91. doi: 10.1038/s41586-021-04217-4. Epub 2021 Dec 15.

Authors

Tongtong Zhao^#^{1

2}, Zachary D Chiang^#^{1

2

3}, Julia W Morriss^{1

2}, Lindsay M LaFave^{2

4

5}, Evan M Murray^{1

2}, Isabella Del Priore^{4

5}, Kevin Meli^{4

5}, Caleb A Lareau^{1

2}, Naeem M Nadaf¹, Jilong Li¹, Andrew S Earl^{1

2

3}, Evan Z Macosko^{1

6}, Tyler Jacks^{1

4

5}, Jason D Buenrostro^{7

8

9}, Fei Chen^{10

11

12}

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
³ Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁴ Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ David H. Koch Institute, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁶ Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
⁷ Broad Institute of MIT and Harvard, Cambridge, MA, USA. jason_buenrostro@harvard.edu.
⁸ Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. jason_buenrostro@harvard.edu.
⁹ Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. jason_buenrostro@harvard.edu.
¹⁰ Broad Institute of MIT and Harvard, Cambridge, MA, USA. chenf@broadinstitute.org.
¹¹ Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. chenf@broadinstitute.org.
¹² Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA. chenf@broadinstitute.org.

^# Contributed equally.

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^1-4 as well as the makeup of the tumour microenvironment^5,6. 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.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Animals
Clone Cells / metabolism*
Clone Cells / pathology
Colorectal Neoplasms / genetics*
Colorectal Neoplasms / pathology*
DNA Copy Number Variations / genetics
Genomics / methods*
Humans
Mice
Phenotype
RNA-Seq
Sequence Analysis, DNA
Transcription, Genetic
Transcriptome

Abstract

Publication types

MeSH terms

Grants and funding