Radiation-induced DNA damage and repair effects on 3D genome organization

The three-dimensional structure of chromosomes plays an important role in gene expression regulation and also influences the repair of radiation-induced DNA damage. Genomic aberrations that disrupt chromosome spatial domains can lead to diseases including cancer, but how the 3D genome structure responds to DNA damage is poorly understood. Here, we investigate the impact of DNA damage response and repair on 3D genome folding using Hi-C experiments on wild type cells and ataxia telangiectasia mutated (ATM) patient cells. We irradiate fibroblasts, lymphoblasts, and ATM-deficient fibroblasts with 5 Gy X-rays and perform Hi-C at 30 minutes, 24 hours, or 5 days after irradiation. We observe that 3D genome changes after irradiation are cell type-specific, with lymphoblastoid cells generally showing more contact changes than irradiated fibroblasts. However, all tested repair-proficient cell types exhibit an increased segregation of topologically associating domains (TADs). This TAD boundary strengthening after irradiation is not observed in ATM deficient fibroblasts and may indicate the presence of a mechanism to protect 3D genome structure integrity during DNA damage repair.


Statistics
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Software and code
Policy information about availability of computer code Data collection Attune Nxt V 2.1 was used for flow cytometry data collection.

Data analysis
Hi-C mapping and iterative correction scripts are available through the github cMapping pipeline. Hi-C analysis scripts are available through the cworld-dekker pipeline version 1.01 available on github. Cell cycle analysis was done using Flowing Software 2.5.1, Hicratio and reproducibility calculations were performed with custom scripts that are available on github: https://github.com/rpmccordlab/ XrayHiCAnalysis. ImageJ version 1.51i was used for average fluorescence intensity calculations.
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Data
Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability All relevant data supporting the key findings of this study are available within the article and its Supplementary Information files or from the corresponding author on reasonable request. The Hi-C data generated in this study have been deposited in Gene Expression Omnibus (GEO) under accession number GSE136899. A source data file is provided with the manuscript.

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Life sciences study design
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Sample size
The sample size for each Hi-C experiment ranged from ~5-20 million cells, as suggested in accepted protocols such as Golloshi et al. Methods, 2018Methods, (10.1016Methods, /j.ymeth.2018. This sample size allowed sufficient library complexity for good dynamic range in contact counts. The sample size for each microscopy experiment was 15-40 nuclei per condition which provided us sufficient power to detect differences in DNA damage marker intensity. Western blots were loaded with at least 10 micrograms, consistent with previously published experimental protocols.
Data exclusions Hi-C experiments with dangling end percentages above 35% were excluded due to excessive potential noise and loss of valid pair data. One BJ5ta Hi-C replicate experiment was also excluded due to excessive local inward facing pairs, leading to concerns about digestion efficiency.

Replication
Each Hi-C experiment was repeated twice with different biological samples that were obtained on different dates at various passages. The only exceptions were for BJ1-hTERT (which were limited in availability and reproduced results of very similar BJ5ta cells), MRC-5 (which were only used to confirm the consistent effects observed in BJ cells in a different cell type) and ATMi (which served to confirm results from ATM mutant cells Randomization Groups of cells were separated into experimental conditions of exposure or lack of exposure to X-rays. The cell populations were identical before they were split into X-ray and control groups, preventing any systematic bias in group assignment.

Blinding
Blinding was not necessary for this study because all samples were processed in parallel with identical treatments, and clear labeling of conditions was necessary to avoid mis-assignment of results.

Reporting for specific materials, systems and methods
We require information from authors about some types of materials, experimental systems and methods used in many studies. Here, indicate whether each material, system or method listed is relevant to your study. If you are not sure if a list item applies to your research, read the appropriate section before selecting a response. ThermoScientific: Invitrogen antibodies that have been verified using independent antibodies are indicated with a "verified specificity" symbol in search results and on relevant product pages. The data showing the verification will be provided on each Authentication Cells were used directly after purchase from ATCC or Coriell; no authentication was performed in our laboratory.
Mycoplasma contamination MRC-5, BJ-1 hTERT, GM12878, and AG04405 were tested for mycoplasma by use of PCR with primers designed to detect mycoplasma contamination. All cell lines tested negative for mycoplasma contamination. Primers were derived from Uphoff CC, Drexler HG. (2004)  The axis labels state the marker and fluorochrome used (e.g. CD4-FITC).
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Methodology
Sample preparation Cells were fixed before or after irradiation and fixed with 70% ethanol for 30 minutes at 4°C. Cells were then centrifuged for 10 minutes at 800×g for 10 minutes and resuspended with Guava® Cell Cycle Reagent (Luminex, 4500-0220).

Instrument
Attune Nxt Acoustic Focusing Cytometer Software Attune Nxt software version 2.1 and Flowing Software 2.5.1 Cell population abundance Cells were only analyzed, not sorted

Gating strategy
The detailed gating strategy is described in Supplementary Figure 1b. Initial cell population gating was manually applied on FSC v SSC to exclude evident debris. Then this same gate was placed on the scatter plot for the blue detector vs. SSC to eliminate doublets. Single cell gating was then plotted in a histogram and cell cycle phases were determined manually, followed by the software's Gaussian fit function. The GM gating of cell cycle phases was transposed to all other conditions for quantitation.
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