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      Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+

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          Abstract

          Imaging the transcriptome in situ with high accuracy has been a major challenge in single cell biology, particularly hindered by the limits of optical resolution and the density of transcripts in single cells 15 . Here, we demonstrate seqFISH+, that can image the mRNAs for 10,000 genes in single cells with high accuracy and sub-diffraction-limit resolution, in the mouse brain cortex, subventricular zone, and the olfactory bulb, using a standard confocal microscope. The transcriptome level profiling of seqFISH+ allows unbiased identification of cell classes and their spatial organization in tissues. In addition, seqFISH+ reveals subcellular mRNA localization patterns in cells and ligand-receptor pairs across neighboring cells. This technology demonstrates the ability to generate spatial cell atlases and to perform discovery-driven studies of biological processes in situ.

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          Most cited references16

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          Computer control of microscopes using µManager.

          With the advent of digital cameras and motorization of mechanical components, computer control of microscopes has become increasingly important. Software for microscope image acquisition should not only be easy to use, but also enable and encourage novel approaches. The open-source software package µManager aims to fulfill those goals. This unit provides step-by-step protocols describing how to get started working with µManager, as well as some starting points for advanced use of the software. © 2010 by John Wiley & Sons, Inc.
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            Visualization of single RNA transcripts in situ.

            Fluorescence in situ hybridization (FISH) and digital imaging microscopy were modified to allow detection of single RNA molecules. Oligodeoxynucleotide probes were synthesized with five fluorochromes per molecule, and the light emitted by a single probe was calibrated. Points of light in exhaustively deconvolved images of hybridized cells gave fluorescent intensities and distances between probes consistent with single messenger RNA molecules. Analysis of beta-actin transcription sites after serum induction revealed synchronous and cyclical transcription from single genes. The rates of transcription initiation and termination and messenger RNA processing could be determined by positioning probes along the transcription unit. This approach extends the power of FISH to yield quantitative molecular information on a single cell.
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              Single-cell phenotyping within transparent intact tissue through whole-body clearing.

              Understanding the structure-function relationships at cellular, circuit, and organ-wide scale requires 3D anatomical and phenotypical maps, currently unavailable for many organs across species. At the root of this knowledge gap is the absence of a method that enables whole-organ imaging. Herein, we present techniques for tissue clearing in which whole organs and bodies are rendered macromolecule-permeable and optically transparent, thereby exposing their cellular structure with intact connectivity. We describe PACT (passive clarity technique), a protocol for passive tissue clearing and immunostaining of intact organs; RIMS (refractive index matching solution), a mounting media for imaging thick tissue; and PARS (perfusion-assisted agent release in situ), a method for whole-body clearing and immunolabeling. We show that in rodents PACT, RIMS, and PARS are compatible with endogenous-fluorescence, immunohistochemistry, RNA single-molecule FISH, long-term storage, and microscopy with cellular and subcellular resolution. These methods are applicable for high-resolution, high-content mapping and phenotyping of normal and pathological elements within intact organs and bodies. Copyright © 2014 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                26 April 2019
                25 March 2019
                April 2019
                25 September 2019
                : 568
                : 7751
                : 235-239
                Affiliations
                [1. ]Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena USA 91125
                [2. ]Division of Biology and Biological Engineering, California Institute of Technology, Pasadena USA 91125
                [3. ]Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard T.H.Chan School of Public Health, Boston, MA 02215, USA
                Author notes

                Contributions:

                C.-H.L.E. and L.C. conceived of the idea and designed experiments. C.-H.L.E. performed all the experiments. M.L. performed image analysis. C.-H.L.E., M.L., Q.Z., R.D., and L.C. performed data analysis. L.C. and G.-C.Y. supervised the analysis process. C.-H.L.E. and N.K. performed cell segmentation and generated the primary probes. Y.T. designed the readout probes. C.-H.L.E., Y.T., and J.Y. validated the readout probes. C.C. and C.K. built the automated fluidic delivery system. C.-H.L.E., M.L, Q.Z., R.D., and Y.T. provided inputs for L.C. when writing the manuscript. L.C. supervised all aspects of the project.

                Corresponding author: Correspondence and requests for materials should be addressed to lcai@ 123456caltech.edu .
                Article
                NIHMS1522797
                10.1038/s41586-019-1049-y
                6544023
                30911168
                fd58ddf5-077f-46a9-9f62-485c11ff9be4

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