4.7 Article Data Paper

Simultaneous visualization of DNA loci in single cells by combinatorial multi-color iFISH

Journal

SCIENTIFIC DATA
Volume 9, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41597-022-01139-2

Keywords

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Funding

  1. Science for Life Laboratory
  2. Karolinska Institutet KID Funding Program
  3. Swedish Research Council [621-2014-5503]
  4. Human Frontier Science Program (HFSP Career Development Award)
  5. Ragnar Soderberg Foundation
  6. European Research Council [StG-2016_GENOMIS_715727]

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This article describes a single-molecule DNA fluorescence in situ hybridization (FISH) technique for studying the three-dimensional organization of the genome in single cells. The authors provide a dataset of 16 small DNA loci and demonstrate how combinatorial color coding can precisely localize these loci in three dimensions within single cells. The dataset includes raw images and coordinates for nearly 10,000 FISH dots and can be used to further studies of 3D genome organization in single cells and develop automatic analysis algorithms.
Single-molecule DNA fluorescence in situ hybridization (FISH) techniques enable studying the three-dimensional (3D) organization of the genome at the single cell level. However, there is a major unmet need for open access, high quality, curated and reproducible DNA FISH datasets. Here, we describe a dataset obtained by applying our recently developed iFISH method to simultaneously visualize 16 small (size range: 62-73 kilobases, kb) DNA loci evenly spaced on chromosome 2 in human cells, in a single round of hybridization. We show how combinatorial color coding can be used to precisely localize multiple loci in 3D within single cells, and how inter-locus distances scale inversely with chromosome contact frequencies determined by high-throughput chromosome conformation capture (Hi-C). We provide raw images and 3D coordinates for nearly 10,000 FISH dots. Our dataset provides a free resource that can facilitate studies of 3D genome organization in single cells and can be used to develop automatic FISH analysis algorithms.

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