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SMT trajectory data for “Chromatin confinement enhances target search of pioneer transcription factors in live cells” Zuhui Wang1,2†, Di Niu1,2,3†, Bo Wang1,2,3†, Ying Bi1,2, Chao Yin1,2,3, Claudia Cattoglio4,5, Kyle M Loh6, Hao Ge1, Wulan Deng1,2,3, * 1Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China. 2Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China. 3Peking-Tsinghua Center for Life Sciences (CLS), Peking University, Beijing 100871, China. 4Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA. 5Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA. 6 Institute for Stem Cell Biology and Regenerative Medicine and Ludwig Center for Cancer Stem Cell Biology and Medicine, Departments of Pathology and Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. † These authors contributed equally to this work. *Corresponding author: wdeng@pku.edu.cn Overview This repository contains all the SMT trajectory data associated with “Confined target search powers FOXA2 transcription activity”. In the repository, there are two main folders. The folder ‘slowSMT_trajectories_pooled’ contains pooled slowSMT trajectories that we used to calculate residence times. The folder ‘spaSMT_trajectories_single_cells’ contains spaSMT single-cell trajectories, with hESC/APS/DE, MEF and U2OS trajectories in the separate folders. We used the spaSMT data in the “hESC_APS_DE” and “MEF” folder for both Spot-On analysis and Anisotropy analysis, while for the spaSMT data in the “U2OS” folder, we used indicated subfolders for Spot-On analysis and/or Anisotropy analysis. For each pooled trajectory file in the folder ‘slowSMT_trajectories_pooled’, it contains two matlab variables. trackedPar: each element represents one trajectory containing one or more localizations xy: x- and y-coordinates in micrometers of the molecule localizations Frame: frame indexes of the molecule localizations. TimeStamp: timepoints in seconds of the molecule localizations. sampleinfo: names of individual cell samples. For each single cell trajectory file in the folder ‘spaSMT_trajectories_single_cells’, it contains two matlab variables. trackedPar: same as above. settings: contains file information, image acquisition settings, the algorithm settings used in MTT localization and tracking software. For detailed explanation, please see the MTT code at https://gitlab.com/tjian-darzacq-lab/SPT_LocAndTrack. The document does not contain information about how the data was analyzed. For details on how the data was analyzed and for codes to reproduce our figure, please go to our github repository. For the slowSMT analysis, we deposit the code under: https://github.com/denglabpku/slowSMT. For the anisotropy analysis, we deposit the code under: https://github.com/denglabpku/anisotropy. For the Spot-On analysis, please visit the Spot-On website: https://spoton.berkeley.edu/. Our trajectory file format is directly available as the input of the Spot-On software. &nbsp

SMT trajectory data for "Confined target search powers FOXA2 transcription activity" Zuhui Wang1,2†, Di Niu1,2,3†, Claudia Cattoglio4,5, Ying Bi1,2, Luke D Lavis6, Kyle M Loh7, Wulan Deng1,2,3, * 1Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing 100871, China. 2Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China. 3Peking-Tsinghua Center for Life Sciences (CLS), Peking University, Beijing 100871, China. 4Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA. 5Howard Hughes Medical Institute, University of California, Berkeley, Berkeley, CA 94720, USA. 6Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia. 7Institute for Stem Cell Biology and Regenerative Medicine and Ludwig Center for Cancer Stem Cell Biology and Medicine, Departments of Pathology and Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA. † These authors contributed equally to this work. *Corresponding author: wdeng@pku.edu.cn Overview This repository contains all the SMT trajectory data associated with "Confined target search powers FOXA2 transcription activity". In the repository, there are two main folders. The folder 'slowSMT_trajectories_pooled' contains pooled slowSMT trajectories that we used to calculate residence times. The folder 'spaSMT_trajectories_single_cells' contains spaSMT single-cell trajectories, with DE/APS and U2OS trajectories in the separate folders. We used the spaSMT data in the 'DE/APS'folder for both Spot-On analysis and Anisotropy analysis, while for the spaSMT data in the 'U2OS'folder, we used indicated subfolders for Spot-On analysis and/or Anisotropy analysis. For each pooled trajectory file in the folder 'slowSMT_trajectories_pooled', it contains two matlab variables. trackedPar: each element represents one trajectory containing one or more localizations xy: x- and y-coordinates in micrometers of the molecule localizations Frame: frame indexes of the molecule localizations. TimeStamp: timepoints in seconds of the molecule localizations. sampleinfo: names of individual cell samples. For each single cell trajectory file in the folder 'spaSMT_trajectories_single_cells', it contains two matlab variables. trackedPar: same as above. settings: contains file information, image acquisition settings, the algorithm settings used in MTT localization and tracking software. For detailed explanation, please see the MTT code at https://gitlab.com/tjian-darzacq-lab/SPT_LocAndTrack. The document does not contain information about how the data was analyzed. For details on how the data was analyzed and for codes to reproduce our figure, please go to our github repository. For the slowSMT analysis, we deposit the code under: https://github.com/denglabpku/slowSMT. For the anisotropy analysis, we deposit the code under: https://github.com/denglabpku/anisotropy. For the Spot-On analysis, please visit the Spot-On website: https://spoton.berkeley.edu/. Our trajectory file format is directly available as the input of the Spot-On software. &nbsp