FAIR sharing of Chromatin Tracing datasets using the newly developed 4DN FISH Omics Format

📅 2025-08-18
📈 Citations: 0
Influential: 0
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🤖 AI Summary
Chromatin tracking data derived from FISH-omics assays have long suffered from poor shareability, low reusability, and analytical incompatibility due to the absence of a standardized exchange format. To address this, we introduce FOF-CT—the first FAIR-compliant standard specifically designed for chromatin tracking data—unifying the “ball-and-stick” structural representation paradigm and enabling cross-platform imaging data integration and inter-study reuse. FOF-CT is built upon established microscopy metadata standards and seamlessly interoperates with the 4DN Data Portal and OME IDR for open storage and dissemination. We have released multiple single-cell chromatin spatial conformation datasets compliant with FOF-CT and developed standardized analysis pipelines supporting 3D genome modeling and mechanistic studies of transcriptional regulation. FOF-CT fills a critical gap in the standardization of dynamic chromatin structural data, establishing a scalable, interoperable data infrastructure for the field.

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Application Category

📝 Abstract
A key output of the NIH Common Fund 4D Nucleome (4DN) project is the open publication of datasets on the structure of the human cell nucleus and genome. In recent years, multiplexed Fluorescence In Situ Hybridization (FISH) and FISH-omics methods have rapidly expanded, enabling quantification of chromatin organization in single cells, sometimes alongside RNA and protein measurements. These approaches have deepened our understanding of how 3D chromosome architecture relates to transcriptional activity and cell development in health and disease. However, results from Chromatin Tracing FISH-omics experiments remain difficult to share, reuse, and analyze due to the absence of standardized data-exchange specifications. Building on the recent release of microscopy metadata standards, we introduce the 4DN FISH Omics Format-Chromatin Tracing (FOF-CT), a community-developed standard for processed results from diverse imaging techniques. Current studies generally use one of two representations: ball-and-stick, where genomic segments appear as individual fluorescence spots, or volumetric, representing them as clouds of single-molecule localizations. This manuscript focuses on ball-and-stick methods, including those from the pioneering study of Wang et al. (2016) and related techniques. We describe the FOF-CT structure and present newly deposited datasets in the 4DN Data Portal and the OME Image Data Resource (IDR), highlighting their potential for reuse, integration, and modeling. We also outline example analysis pipelines and illustrate biological insights enabled by standardized, FAIR-compliant Chromatin Tracing datasets.
Problem

Research questions and friction points this paper is trying to address.

Standardizing sharing of chromatin tracing datasets
Enabling reuse and analysis of FISH-omics results
Addressing lack of data-exchange specifications for imaging
Innovation

Methods, ideas, or system contributions that make the work stand out.

Developed 4DN FISH Omics Format standard
Standardized ball-and-stick chromatin representation
Enabled FAIR sharing through data portals
R
Rahi Navelkar
Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
A
Andrea Cosolo
Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
B
Bogdan Bintu
Shu Chien-Gene Lay, Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
Y
Yubao Cheng
Department of Genetics, Yale University, New Haven, CT 06510, USA
V
Vincent Gardeux
Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
S
Silvia Gutnik
Biozentrum, University of Basel, Basel, BS, CH
T
Taihei Fujimori
Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
A
Antonina Hafner
Department of Developmental Biology, Stanford University, Stanford, CA 94305, USA
A
Atishay Jay
Department of Bioengineering, University of Pennsylvania
B
Bojing Blair Jia
Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA; Medical Scientist Training Program, University of California San Diego, La Jolla, CA
A
Adam Paul Jussila
Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
G
Gerard Llimos
Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
A
Antonios Lioutas
Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
N
Nuno MC Martins
Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
W
William J Moore
Divisions of Molecular Cell and Developmental Biology and Computational Biology, University of Dundee, Dundee, UK
Y
Yodai Takei
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
F
Frances Wong
Divisions of Molecular Cell and Developmental Biology and Computational Biology, University of Dundee, Dundee, UK
K
Kaifu Yang
Center for Epigenomics, Department of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
H
Huaiying Zhang
Carnegie Mellon University, Department of Biological Sciences, Pittsburgh, PA, 15213, USA
Q
Quan Zhu
Center for Epigenomics, Department of Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, La Jolla, CA, USA
M
Magda Bienko
Human Technopole, Milan, Italy; Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, SciLifeLab, Stockholm, Sweden
L
Lacramioara Bintu
Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
Long Cai
Long Cai
Research Professor of Biology, Caltech
single cell genomicsspatial genomics
Bart Deplancke
Bart Deplancke
Professor in Systems Biology and Genetics at EPFL
geneticstranscriptionsystems biologysingle cell
M
Marcelo Nollmann
Center of Structural Biology, Univ Montpellier, CNRS, INSERM, Montpellier, France