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      A high-throughput DNA FISH protocol to visualize genome regions in human cells

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          Summary

          Here, we describe an end-to-end high-throughput imaging protocol to visualize genomic loci in cells at high throughput using DNA fluorescence in situ hybridization, automated microscopy, and computational analysis. This is particularly useful for quantifying patterns of heterogeneity in relative gene positioning or differences within subpopulations of cells. We focus on important experimental design and execution steps in this one-week protocol, suggest ways to ensure and verify data quality, and provide practical solutions to common problems.

          For complete details on the generation and use of this protocol, please refer to Finn et al. (2019).

          Graphical abstract

          Highlights

          • DNA fluorescence in situ hybridization technique for high-content imaging

          • Optimized for use in a 384-well plate format with cultured cells

          • One-week protocol to assess thousands of cells per condition in tens of conditions

          • Thorough discussion of troubleshooting for new probes, probe types, and cell types

          Abstract

          Here, we describe an end-to-end high-throughput imaging protocol to visualize genomic loci in cells at high throughput using DNA fluorescence in situ hybridization, automated microscopy, and computational analysis. This is particularly useful for quantifying patterns of heterogeneity in relative gene positioning or differences within subpopulations of cells. We focus on important experimental design and execution steps of this one-week protocol, suggest ways to ensure and verify data quality, and provide practical solutions to common problems.

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          Most cited references14

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          Cellpose: a generalist algorithm for cellular segmentation

          Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datasets. Here we introduce a generalist, deep learning-based segmentation method called Cellpose, which can precisely segment cells from a wide range of image types and does not require model retraining or parameter adjustments. Cellpose was trained on a new dataset of highly varied images of cells, containing over 70,000 segmented objects. We also demonstrate a three-dimensional (3D) extension of Cellpose that reuses the two-dimensional (2D) model and does not require 3D-labeled data. To support community contributions to the training data, we developed software for manual labeling and for curation of the automated results. Periodically retraining the model on the community-contributed data will ensure that Cellpose improves constantly.
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            Visualizing DNA folding and RNA in embryos at single-cell resolution

            Establishment of cell types during development requires precise interactions between genes and distal regulatory sequences. Our understanding of how these interactions look in three dimensions, vary across cell types in complex tissue, and relate to transcription remains limited. Here we describe optical reconstruction of chromatin architecture (ORCA), a method to trace the DNA path in single cells with nanoscale accuracy and genomic resolution reaching 2 kilobases. We applied ORCA to a Hox gene cluster in cryosectioned Drosophila embryos and labelled ~30 RNA species in parallel. We identified cell-type-specific physical borders between active and Polycomb-repressed DNA, and unexpected Polycomb-independent borders. Deletion of Polycomb-independent borders led to ectopic enhancer-promoter contacts, aberrant gene expression, and developmental defects. Together, these results illustrate an approach for high-resolution, single-cell DNA domain analysis in vivo, reveal domain structures that change with cell identity, and show that border elements contribute to formation of physical domains in Drosophila.
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              Spatial organization of chromatin domains and compartments in single chromosomes.

              The spatial organization of chromatin critically affects genome function. Recent chromosome-conformation-capture studies have revealed topologically associating domains (TADs) as a conserved feature of chromatin organization, but how TADs are spatially organized in individual chromosomes remains unknown. Here, we developed an imaging method for mapping the spatial positions of numerous genomic regions along individual chromosomes and traced the positions of TADs in human interphase autosomes and X chromosomes. We observed that chromosome folding deviates from the ideal fractal-globule model at large length scales and that TADs are largely organized into two compartments spatially arranged in a polarized manner in individual chromosomes. Active and inactive X chromosomes adopt different folding and compartmentalization configurations. These results suggest that the spatial organization of chromatin domains can change in response to regulation.
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                Author and article information

                Contributors
                Journal
                STAR Protoc
                STAR Protoc
                STAR Protocols
                Elsevier
                2666-1667
                16 August 2021
                17 September 2021
                16 August 2021
                : 2
                : 3
                : 100741
                Affiliations
                [1 ]Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MA, 20892, USA
                Author notes
                []Corresponding author Elizabeth.Finn@ 123456nih.gov
                [∗∗ ]Corresponding author Mistelit@ 123456mail.nih.gov
                [2]

                Technical contact

                [3]

                Lead contact

                Article
                S2666-1667(21)00448-2 100741
                10.1016/j.xpro.2021.100741
                8377592
                34458868
                f8588588-af44-4736-85ae-0118b88b1a5f

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                Categories
                Protocol

                cell biology,single cell,cell-based assays,high throughput screening,microscopy,molecular biology,in situ hybridization

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