Cited by 273Single-cell and spatial transcriptomicsCancer Genomics and DiagnosticsGenomic variations and chromosomal abnormalities

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

Open access
Zhao, Tongtong, Chiang, Zachary D., Morriss, Julia W., LaFave, Lindsay M., Murray, Evan M., Del Priore, Isabella, Meli, Kevin, Lareau, Caleb A. +7 more·2022·Nature

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.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41586-021-04217-4

Cites

51 of 51 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • slide-DNA-seq preserved local tumour architecture, enabling discovery of distinct tumour clones and their copy number variations.

    “Very recently, a newly developed spatial technology, slide-DNA-seq, was used to preserve local tumour architecture, enabling the discovery of distinct tumour clones and their copy number variations157.”

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

1 retracted

Flagged first, then by citations

2 of the 53 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Authors
Zhao, T., Chiang, Z. D., Morriss, J. W., LaFave, L. M., Murray, E. M., Del Priore, I., Meli, K., Lareau, C. A., Nadaf, N. M., Li, J., Earl, A. S., Macosko, E. Z., Jacks, T., Buenrostro, J. D., & Chen, F.
Affiliations
  • Broad Institute (US)
  • Harvard University (US)
  • Massachusetts Institute of Technology (US)
Corresponding author
  • Buenrostro, Jason D.
  • Chen, Fei
Venue
Nature
Published
2021-12-15
Volume
601
Issue
7891
Pages
85-91
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W4200559225
Cited by
268
References
53
Citations by year
2026: 51 · 2025: 51 · 2024: 75 · 2023: 53 · 2022: 37
FWCI
13.34
Type
journal article
Language
en
Open access
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
  • RePEc: Research Papers in Economics (submittedVersion)
Funders
  • Wellcome Trust
  • National Institutes of Health (DP5OD024583)
  • National Heart, Lung, and Blood Institute (DP2HL151353)
  • National Human Genome Research Institute (R21HG009749, T32HG002295, R01HG010647)
  • National Cancer Institute (UH3CA246632, R33CA246455)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomic variations and chromosomal abnormalities
Keywords
spatial genomics, tumor microenvironment, copy number alterations, tumor architecture, metastasis, spatial transcriptomics, tumor progression, gene expression regulation
MeSH terms
RNA-Seq, Animals, Clone Cells, Humans, Phenotype, Transcription, Genetic, Colorectal Neoplasms, Sequence Analysis, DNA, Genomics, Mice, DNA Copy Number Variations, Transcriptome

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review