Data availability<\/h2>\n
The 3D localizations, calibration files and raw blinking videos for all series in Fig. 2<\/a>, and Cell no. 1, no. 2,504, no. 5,735, no. 8,041, no. 9,577 and no. 11,160 from the lamin-NPM1 dataset in Fig. 4<\/a> (and 3D localizations for the remaining cells), are publicly available through the 4D Nucleome data portal at https:\/\/data.4dnucleome.org\/publications\/7d9fad19-54c4-419e-8d99-8157f5c1904b\/<\/a>. Any additional data from this work can be obtained through the authors upon request.<\/p>\n<\/div>\n The code for automated acquisition, distributed data storage and analysis is released under the GNU General Public License v.3 as part of the python-microscopy project and is available at github.com\/python-microscopy\/python-microscopy<\/a>. The quantized compression software can be installed independently, with instructions for use with third-party software additionally available at github.com\/python-microscopy\/pymecompress<\/a>. Code for GPU acceleration of single-molecule fitting is available under an academic use license from github.com\/barentine\/pyme-warp-drive<\/a>. The LabVIEW acquisition software used in phase 1 can be obtained from the authors; however, it is not actively maintained. Please contact the authors for alternative licensing arrangements.<\/p>\n<\/div>\n Baddeley, D. & Bewersdorf, J. Biological insight from super-resolution microscopy: what we can learn from localization-based images. Annu. Rev. Biochem.<\/i> 87<\/b>, 965\u2013989 (2018).<\/p>\n Article<\/a>\u00a0 Xu, K., Zhong, G. & Zhuang, X. Actin, spectrin, and associated proteins form a periodic cytoskeletal structure in axons. Science<\/i> 339<\/b>, 452\u2013456 (2013).<\/p>\n Article<\/a>\u00a0 Szymborska, A. et al. Nuclear pore scaffold structure analyzed by super-resolution microscopy and particle averaging. 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Proc. IRE<\/i> 40<\/b>, 1098\u20131101 (1952).<\/p>\n Article<\/a>\u00a0 Balazs, B., Deschamps, J., Albert, M., Ries, J. & Hufnagel, L. A real-time compression library for microscopy images. Preprint at bioRxiv https:\/\/www.biorxiv.org\/content\/10.1101\/164624v1<\/a> (2017).<\/p>\n<\/li>\n Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res.<\/i> 12<\/b>, 2825\u20132830 (2011).<\/p>\n Download references<\/a><\/p>\n<\/div>\n<\/div>\n We thank A. Wrogg for contributing the timeline in Fig. 1<\/a>. We thank L. Schroeder and Y. Zhang for helpful discussions and technical assistance. This work was primarily supported by a 4D Nucleome grant from the National Institutes of Health (NIH) (grant no. U01 DA047734 to J.B. and D.B.). J.B. acknowledges support from NIH grant no. P30 DK045735 (to R. Sherwin). A.E.S.B. acknowledges support by an NIH training grant (no. T32 GM008283) and training on the Computational Image Analysis in Cellular and Developmental Biology Course of the Marine Biology Laboratory (which was supported by NIH grant no. R25 GM103792). We are also grateful for funding from NIH awards no. U01CA200147 TCPA-2017-Neugebauer and OPAS (to K.M.N.) and no. 1R01NS128358-1 (to K.M.N. and J.B.). This work is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.<\/p>\n<\/div>\n Author notes<\/span><\/p>\n These authors contributed equally: Andrew E. S. Barentine, Yu Lin.<\/p>\n<\/li>\n<\/ol>\n Department of Cell Biology, Yale School of Medicine, New Haven, CT, USA<\/p>\n Andrew E. S. Barentine,\u00a0Yu Lin,\u00a0Edward M. Courvan,\u00a0Phylicia Kidd,\u00a0Leonhard Balduf,\u00a0Timy Phan,\u00a0Felix Rivera-Molina,\u00a0Michael R. Grace,\u00a0Zach Marin,\u00a0Mark Lessard,\u00a0Juliana Rios Chen,\u00a0Siyuan Wang,\u00a0Karla M. Neugebauer,\u00a0Joerg Bewersdorf\u00a0&\u00a0David Baddeley<\/p>\n<\/li>\n Department of Biomedical Engineering, Yale University, New Haven, CT, USA<\/p>\n Andrew E. S. Barentine,\u00a0Yu Lin,\u00a0Zach Marin\u00a0&\u00a0Joerg Bewersdorf<\/p>\n<\/li>\n Department of Molecular Biophysics and Biochemistry, Yale School of Medicine, New Haven, CT, USA<\/p>\n Edward M. Courvan\u00a0&\u00a0Karla M. Neugebauer<\/p>\n<\/li>\n Department of Genetics, Yale School of Medicine, New Haven, CT, USA<\/p>\n Miao Liu\u00a0&\u00a0Siyuan Wang<\/p>\n<\/li>\n Department of Computer Science and Mathematics, University of Applied Sciences, Munich, Germany<\/p>\n Leonhard Balduf\u00a0&\u00a0Timy Phan<\/p>\n<\/li>\n Auckland Bioengineering Institute at University of Auckland, Auckland, New Zealand<\/p>\n Zach Marin\u00a0&\u00a0David Baddeley<\/p>\n<\/li>\n Department of Physics, Yale University, New Haven, CT, USA<\/p>\n Joerg Bewersdorf<\/p>\n<\/li>\n Nanobiology Institute, Yale University, West Haven, CT, USA<\/p>\n Joerg Bewersdorf\u00a0&\u00a0David Baddeley<\/p>\n<\/li>\n<\/ol>\n Y.L. and J.B. designed the optical hardware of the microscope which Y.L. built. A.E.S.B., Y.L., D.B., Z.M., T.P. and J.R.C. developed acquisition control software. M.R.G., A.E.S.B. and D.B. designed and implemented the computer cluster. D.B. designed the distributed the storage architecture and compression algorithm. D.B. and L.B. designed and implemented the cluster task distribution. A.E.S.B. and D.B. developed the GPU acceleration code. S.W. and M. Liu designed the FISH probes. E.M.C., P.K., M. Lessard, F.R.-M., M. Liu, S.W. and K.M.N. optimized sample preparation protocols and prepared samples. A.E.S.B., Y.L. and E.M.C. performed imaging experiments. A.E.S.B., Y.L. and D.B. performed post-localization analysis. All authors contributed to writing the manuscript.<\/p>\n Correspondence to J.B. discloses a financial interest in Bruker Corp. and Hamamatsu Photonics. All other authors declare no competing interests.<\/p>\n<\/p><\/div>\n<\/div>\n Nature Biotechnology<\/i> thanks Bogdan Bintu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.<\/p>\n<\/p><\/div>\n<\/div>\n Publisher\u2019s note<\/b> Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.<\/p>\n<\/div>\n Supplementary Figs. 1\u201310, Notes 1\u20138 and Tables 1\u20134.<\/p>\n<\/div>\n \n Video showing a reconstruction of each of the 11,145 nuclei contributing to Fig. 4<\/a>.<\/p>\n<\/div>\n Video showing an automated acquisition using simulated hardware in PYMEAcquire with a \u2018cluster of one\u2019 for automated localization and recipe-based analysis.<\/p>\n<\/div>\n LAD probe design including sequences of PCR primers, reverse transcription primers and activator oligos. The worksheet lists the sequences of the forward and reverse PCR primers and the reverse transcription primers used in the synthesis of each LAD probe library. The \/5Alex647N\/ in the sequences indicates 5\u2032 Alexa Fluor 647 modifications of the DNA oligos.<\/p>\n<\/div>\n Template sequences for LAD probe library syntheses. All oligonulceotide sequences in each template LAD probe library are compiled as a list. Different LAD libraries are placed in different worksheets labeled with the names of the LADs that the libraries target.<\/p>\n<\/div>\n TAD probe design information including sequences of PCR primers and reverse transcription primers. The worksheet lists the sequences of the forward and reverse PCR primers and the reverse transcription primers used in the synthesis of the Chr22 probe library. The \/5Biosg\/ in the sequence indicates 5\u2032 biotin modifications of the DNA oligos.<\/p>\n<\/div>\n Template sequences for TAD probe library syntheses. All oligonulceotide sequences in each template LAD probe library are compiled as a list. Different LAD libraries are placed in different worksheets labeled with the names of the LADs that the libraries target.<\/p>\n<\/div>\n<\/div>\n<\/div>\n Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.<\/p>\n Reprints and Permissions<\/a><\/p>\n<\/div>\n<\/div>\nCode availability<\/h2>\n
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\n Joerg Bewersdorf<\/a> or David Baddeley<\/a>.<\/p>\n<\/div>\n<\/div>\nEthics declarations<\/h2>\n
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