生物
计算生物学
基因组学
肿瘤异质性
基因
DNA测序
转录组
基因组
表型
遗传异质性
遗传学
癌症
基因表达
作者
Tongtong Zhao,Zachary Chiang,Julia W. Morriss,Lindsay M. LaFave,Evan Murray,Isabella Del Priore,Kevin Meli,Caleb A. Lareau,Naeem Nadaf,Jilong Li,Andrew Earl,Evan Z. Macosko,Tyler Jacks,Jason D. Buenrostro,Fei Chen
出处
期刊:Nature
[Springer Nature]
日期:2021-12-15
卷期号:601 (7891): 85-91
被引量:206
标识
DOI:10.1038/s41586-021-04217-4
摘要
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.
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