Data

We believe in openly sharing the major datasets supporting our work. Most of our publications and preprints should already contain a section detailing where and how the relevant data is available. For Code or Reagents, which we will also freely share, please see the other relevant sections.
Most of the imaging data will be available in the form of trajectories and the genomics data is available in the standard formats. If you have any trouble locating a dataset or believe one to be missing, please Contact Us, and we will make sure to get back to you.
Click on the relevant publication name for more information:

Region Capture Micro-C reveals coalescence of enhancers and promoters into nested microcompartments
Dynamics of CTCF- and cohesin-mediated chromatin looping revealed by live-cell imaging
DNA double-strand break end synapsis by DNA loop extrusion
Promoters adopt distinct dynamic manifestations depending on transcription factor context
An RNA-binding region in CTCF regulates clustering and chromatin looping
Guided nuclear exploration increases CTCF target search efficiency
Determining cellular CTCF and cohesin abundances to constrain 3D genome models
Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation
CTCF sites display cell cycle dependent dynamics in factor binding and nucleosome positioning
RNA polymerase II clustering through carboxy-terminal domain phase separation
Phase-separation mechanism for C-terminal  hyperphosphorylation of RNA polymerase II
Robust model-based analysis of single-particle tracking experiments with Spot-On
CTCF and Cohesin Regulate Chromatin Loop Stability with Distinct Dynamics
cis Determinants of Promoter Threshold and Activation Timescale
Limits on information transduction through amplitude and frequency regulation of transcription factor activity
Promoter decoding of transcription factor dynamics involves a trade-off between noise and control of gene expression

 

Region Capture Micro-C reveals coalescence of enhancers and promoters into nested microcompartments

Goel VY, Huseyin MK, Hansen AS^. Region Capture Micro-C reveals coalescence of enhancers and promoters into nested microcompartments. Nature Genetics, 2023.
The raw data and code is freely available:

 

Dynamics of CTCF- and cohesin-mediated chromatin looping revealed by live-cell imaging

Gabriele M*, Brandão HB*, Grosse-Holz S*, Jha A, Dailey GM, Cattoglio C, Hsieh THS, Mirny L^, Zechner C^, Hansen AS^. Dynamics of CTCF and cohesin mediated chromatin looping revealed by live-cell imaging. Science, 2022.
The raw data can be found here:
  • The raw trajectory data is on Zenodo.
  • The raw genomics data (Micro-C, ChIP-Seq) can be found at NCBI GEO under accession number GSE187487.

 

DNA double-strand break end synapsis by DNA loop extrusion

Yang, HY, Brandão HB, Hansen AS. DNA double-strand break end synapsis by DNA loop extrusion. Nature Communications, 2023
Please see the links below for the raw data:
  • All the raw data can be found on GitHub.

 

Promoters adopt distinct dynamic manifestations depending on transcription factor context

Hansen AS^; Zechner C^. Promoters adopt distinct dynamic manifestations depending on transcription factor context. bioRxiv, 2019, 650762.
Please see the links below for the raw data:
  • All the raw data (single-cell trajectories of gene expression dynamics calibrated to obtain absolute copy numbers of YFP reporter per cell per timepoint) can be found on Zenodo.

 

Distinct classes of chromatin loops revealed by deletion of an RNA-binding region in CTCF

Hansen AS*; Hsieh THS*; Cattoglio C*; Pustova I; Saldana-Meyer R; Reinberg D; Darzacq X^; Tjian R^. Distinct Classes of Chromatin Loops Revealed by Deletion of an RNA-Binding Region in CTCF. Molecular Cell, 2019, DOI:https://doi.org/10.1016/j.molcel.2019.07.039.
Please see the links below for the data:
  • Imaging data can be found on Zenodo.
  • The genomics data (Micro-C, ChIP-Seq, RNA-Seq) is available at GEO under accesssion number GSE123636.

 

Guided nuclear exploration increases CTCF target search efficiency

Hansen AS*; Amitai A*; Cattoglio C; Tjian R; Darzacq X. Guided nuclear exploration increases CTCF target search efficiency. bioRxiv, 2018, 495457.
For this paper, we conducted 1693 spaSPT experiments (so single-molecule tracking experiments in 1693 single cells). All the raw trajectory data is freely available on Zenodo and all the code is available from GitLab:
  • Raw and processed spaSPT data is on Zenodo.
  • MATLAB version of Spot-On can be downloaded at GitLab.
  • The code used for simulating SPT data, simSPT, can be downloaded from GitLab.
  • The anisotropy data-processing pipeline is also on GitLab.

 

Determining cellular CTCF and cohesin abundances to constrain 3D genome models

Cattoglio C; Pustova I; Walther N; Ho JJ; Hantsche-Grininger M; Inouye CJ; Hossain MJ; Dailey GM; Ellenberg J; Darzacq X; Tjian R; Hansen AS: Determining cellular CTCF and cohesin abundances to constrain 3D genome models. eLife 2019, 40164.
  • The raw Flow Cytometry data, as well as the MATLAB code used to analyze the data, is available at GitLab.
  • The Fluorescence Correlation Spectroscopy (FCS) code is available here.
  • The raw FCS data is available through the BioStudies Database.

 

Transient DNA binding induces RNA Polymerase II compartmentalization during Herpesviral infection distinct from phase separation

McSwiggen DT; Hansen AS; Marie-Nelly H; Teves SS; Heckert A; Hao Y; Umemoto K; Dugast-Darzacq C; Tjian R^; Darzacq X^. Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation. eLife 2019, e47098.
  • The ATAC-Seq data is available at GEO: GSE117335.
  • The spaSPT data can is available at Zenodo.

 

 

CTCF sites display cell cycle dependent dynamics in factor binding and nucleosome positioning

Oomen ME; Hansen AS; Liu Y; Darzacq X; Dekker J. CTCF sites display cell cycle dependent dynamics in factor binding and nucleosome positioning. Genome Research 2019 29, 236-249
All the raw SPT data for this paper is freely available on Zenodo. The data was analyzed with Spot-On Matlab (please see the paper for full details on parameters), which is freely available from GitLab.

 

RNA polymerase II clustering through carboxy-terminal domain phase separation

Boehning M; Dugast-Darzacq C; Rankovic M; Hansen AS; Yu TK; Marie-Nelly H; Kokic G; Dailey GM; Cramer P; Darzacq X;  Zweckstetter M. RNA polymerase II clustering through carboxy-terminal domain phase separation. Nature Structural and Molecular Biology 2018, 25, 833–840.
The raw PALM and spaSPT data is available at Zenodo. The spaSPT data was analyzed with Spot-On Matlab (please see the paper for full details on parameters), which is freely available from GitLab.

 

Phase-separation mechanism for C-terminal  hyperphosphorylation of RNA polymerase II

Lu H; Yu D; Hansen AS; Ganguly S; Liu R; Heckert A; Darzacq X; Zhou Q; 2018. Phase-separation mechanism for C-terminal  hyperphosphorylation of RNA polymerase II. Nature 2018 558, 318–323
All the raw SPT data for this paper is freely available on Zenodo. The data was analyzed with Spot-On Matlab (please see the paper for full details on parameters), which is freely available from GitLab.

 

Robust model-based analysis of single-particle tracking experiments with Spot-On

Hansen AS*; Woringer M*; Grimm J; Lavis LD; Tjian R; Darzacq X. Robust model-based analysis of single-particle tracking experiments with Spot-On. eLife 2018 e33125
For this paper, we conducted 1064 spaSPT experiments (so single-molecule tracking experiments in 1064 single cells). All the raw trajectory data is freely available on Zenodo and all the code is available from GitLab:
  • The Spot-On website: https://spoton.berkeley.edu/
  • The Matlab version also comes with example CTCF data. Please download this from GitLab.
  • Please download the MATLAB version of Spot-On here.
  • Please download the Python version of Spot-On here.
  • All the experimental spaSPT trajectory data in both Matlab and CSV data formats can be downloaded from Zenodo.
  • All the simulated SPT data used for validating Spot-On can be downloaded from Zenodo.
  • Instructions and code for reproducing the simulations can be downloaded from Zenodo.
  • Additional code with instructions used for the methods comparison can also be downloaded from Zenodo.
  • Finally, the code used for simulating SPT data, simSPT, can be downloaded from GitLab.

 

CTCF and Cohesin Regulate Chromatin Loop Stability with Distinct Dynamics

Hansen AS; Pustova I; Cattoglio C; Tjian R; Darzacq X. CTCF and Cohesin Regulate Chromatin Loop Stability with Distinct Dynamics. eLife 2017. e25776
  • ChIP-Seq for CTCF and Rad21 (Cohesin) in both wild-type and double-homozygous knock-in (FLAG-Halo-mCTCF / mRad21-SNAPf-V5) JM8.N4 mouse embryonic stem cells is available at GEO under accession code GSE90994 and can be found here.
  • We generated the following knock-in cell lines and are also happy to share these (see Reagents):
    • C87: JM8.N4 mESC homozygous FLAG-Halo-mCTCF
    • C45: JM8.N4 mESC homozygous mRad21-Halo-V5
    • C59: JM8.N4 mESC homozygous FLAG-Halo-mCTCF & homozygous mRad21-SNAPf-V5
    • C32: human osteosarcoma U2OS homozygous FLAG-Halo-mCTCF.

 

Cis-determinants of promoter threshold and activation timescale

Hansen AS; O’Shea EK. Cis-determinants of promoter threshold and activation timescale. Cell Reports 2015, 12(8), 1226-1233
  • All the raw single-cell expression data time-course data is available as Supplemental Source Data and can be downloaded here.
  • The source data also contains a Read-Me file explaining the data organization.

 

Limits on information transduction through amplitude and frequency regulation of transcription factor activity

Hansen AS; O’Shea EK. Limits on information transduction through amplitude and frequency regulation of transcription factor activity. eLife 2015 e06559

 

Promoter decoding of transcription factor dynamics involves a trade-off between noise and control of gene expression

Hansen AS; O’Shea EK. Promoter decoding of transcription factor dynamics involves a trade-off between noise and control of gene expression. Molecular Systems Biology 2013, 9.