Protocol for image-based monitoring of de novo RNA synthesis at DNA double-strand breaks in human cell lines

Summary

DNA double-strand breaks (DSBs) halt canonical transcription and simultaneously trigger local non-canonical RNA synthesis. Despite its significance, existing approaches to monitor this process are limited. Here, we present a protocol to monitor and quantify nascent transcription on DSBs in the nucleus. We describe steps for employing UV-A laser to induce site-specific DSBs. We then detail procedures for supplementation of the ablated cells with 5-bromouridine 5′-triphosphate (BrUTP) to label nascent RNA.

For complete details on the use and execution of this protocol, please refer to Pappas et al.¹

Graphical abstract

Highlights

• •Protocol for quantification of nascent transcription at DSBs
• •Guidance on BrUTP incorporation assay and site-specific UV-A laser ablation
• •Steps for immunochemical staining of DSBs and incorporated BrUTP
• •Instructions for analysis of de novo RNA synthesis on DSBs

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

DNA double-strand breaks (DSBs) halt canonical transcription and simultaneously trigger local non-canonical RNA synthesis. Despite its significance, existing approaches to monitor this process are limited. Here, we present a protocol to monitor and quantify nascent transcription on DSBs in the nucleus. We describe steps for employing UV-A laser to induce site-specific DSBs. We then detail procedures for supplementation of the ablated cells with 5-bromouridine 5′-triphosphate (BrUTP) to label nascent RNA.

Before you begin

Transcription is a tightly regulated process catalyzed by three distinct RNA polymerases in eukaryotes. RNA polymerase I (RNAPI) and RNA polymerase III (RNAPIII) are responsible for the synthesis of ribosomal RNAs and structural RNAs, respectively, whereas RNA polymerase II (RNAPII) catalyzes the synthesis of protein-coding pre-mRNAs, as well as other types of non-coding RNAs.² DNA double-strand break (DSB) formation halts ongoing “canonical” transcription at the proximal genomic regions while triggering a “non-canonical” wave of RNA synthesis driven by RNAPII at the damaged sites,³ with several proteins of the DNA damage response (DDR) network facilitating this process,⁴ including MDC1.¹

Here, we delineate an image-based method for monitoring this non-canonical transcription dynamics in adherent human cell lines. This approach combines BrUTP, a thymidine analog incorporated into nascent transcripts, with localized DSB induction by UV-A laser microirradiation, enabling the detection of de novo RNA synthesis by RNAPII at sites of chromatin relaxation associated with DNA damage.

While the protocol described below outlines the specific steps using the osteosarcoma cell line U2OS, it has been also optimized across various other 2D cell lines, including non-transformed (HBEC-3KT and RPE-1) and cancerous (HeLa) cells. However, before initiating the experiment, ensure that each step of the protocol is refined according to the specific cellular model being used, particularly when working with cell lines not listed above.

Innovation

Our approach enables the monitoring of nascent transcription at DNA damage sites, by optimizing the BrUTP incorporation assay originally described by Wansink et al.,⁵ and integrating this method with UV-A laser microirradiation to induce site-specific DSBs. This combined strategy allows for spatially and temporally resolved investigation of transcriptional dynamics at DSBs. While similar investigations have employed EU Click-iT chemistry in tandem with UV-A laser ablation,⁶ BrUTP offers distinct advantages. Specifically, BrUTP incorporation enables rapid visualization of non-canonical transcription at DSBs (within 8 min of incubation), compared to the lengthier incubation period required for EU (20–30 min of incubation). This difference arises from their biochemical properties: EU nucleosides undergo processing through the ribonucleoside salvage pathway (conversion to 5′-ribonucleotide phosphates EUMP, EUDP, and EUTP) before integration into nascent transcripts.⁷ In contrast, BrUTP is directly incorporated by chromatin-engaged RNAPII complexes following cell permeabilization.⁵ This permeabilization step ensures that only chromatin-bound RNAPII complexes can incorporate BrUTP, making the intensity of the BrUTP signal a direct indicator of RNAPII engagement at DSBs. Another thymidine nucleotide analog, 5′- Ethynyl UTP (5-EUTP), has been developed to bypass the salvage pathway prior to its incorporation,^8,9 however, its incubation time (60 min) and concentration (100–500 μM) are much longer and higher than those for BrUTP. Nevertheless, it may represent a viable alternative upon further optimization.

Optimization of the BrUTP incorporation assay

Timing: 2 days

Note: During these steps we validate the efficacy of the BrUTP incorporation assay by including specific controlled conditions. Using specific inhibitors that target nuclear or nucleolar transcription, we then monitor BrUTP incorporation to confirm the reliability and validity of our experimental setup. These validation steps are critical and should always be performed before proceeding to the main method.

Fibrillarin is used as a marker of the dense fibrillar component (DFC), delineating the nucleolar compartment (Figure 1B). To inhibit CDK7, which phosphorylates serine 5 residues on the C-terminal domain (CTD) of RNAPII and is required for transcription initiation, cell are treated with 1 μM THZ1 for 1 h prior to the experiment.¹⁰ As expected, RNAPII-mediated transcription is downregulated under these conditions, while nucleolar transcription mediated by RNAPI exhibits only minor, non-significant alterations (Figures 1B–1F). Additionally, Triptolide (TLP), an inhibitor of the ATPase activity of the XPB subunit of TFIIH, is employed to block DNA unwinding at promoter sites, thereby inhibiting RNAPII transcription initiation. Cells are treated with 5 μM TLP for 12 h, followed by BrUTP incorporation analysis. As anticipated, TLP efficiently inhibits RNAPII activity without affecting RNAPI function (Figures 1B–1F). Under TLP treatment, fibrillarin shows a diffuse pattern, suggesting DFC disruption and nucleolar stress.¹¹ This observation aligns with previously published data, which demonstrate that prolonged TLP treatment affects nucleolar integrity, though without reporting on nascent nucleolar RNA synthesis.¹² In our experimental setup, nucleolar transcription remains active, potentially as a survival mechanism to mitigate cellular stress (Figures 1B and 1F). To further validate the BrUTP incorporation assay, Actinomycin D (ActD) is used at two concentrations to selectively inhibit RNAPI activity (0.1 μg/mL) or the activity of all three RNAPs (5 μg/mL) (Figures 1B–1F).^1,13,14 Additionally, the sensitivity of the BrUTP incorporation assay to RNase A treatment is assessed (Figures 1B–1D and 1F). Consistent with early studies on BrUTP immunodetection,¹⁵ treating fixed cells with 100 μg/mL RNase A for 45 min eliminates all BrUTP nuclear labeling. This provides robust evidence that BrUTP incorporation exclusively reflects newly synthesized RNA by the three RNAPs (Figures 1B–1F).

• 1.Seed 3.5 × 10⁵ U2OS cells in 60 mm diameter cell culture dishes (one for each treatment condition) with coverslips at their bottom.

Note: Include extra coverslips for each condition to increase the number of technical replicates and thus verify that the experimental setup is reliable and reproducible.

Note: Make sure the coverslips are firmly attached to the bottom of the culture dish to prevent floating and loss of attached cells. Proper attachment also ensures that cells do not grow on the underside of the coverslip, which can create significant issues during image acquisition. To properly attach the coverslips, place them in an empty dish and carefully add media. Use a pipette tip, preferably bent to provide a larger, less sharp surface, to gently press down on the coverslip and remove any bubbles underneath. Add the appropriate number of cells to the dish and distribute them evenly by gently moving the dish. Always double check that the coverslips remain well attached after cell distribution, and if necessary, press them down again as previously described.

Note: If preferable, a 6-well, 12-well or 24-well plate can also be used for seeding on the coverslips (with accordingly less cells).

• 2.Place the cells in the incubator for 48 h.

Note: By the day of the experiment cells need to be at 70%–80% confluency.

CRITICAL: It is important that the cells are not too confluent as this can affect cell proliferation and, in turn, the transcription and the incorporation of the BrUTP.

• 3.
  On the day of the experiment, ensure everything is prepared before starting the assay:

  • a.
    Mix the transcription extraction buffer (TEB) and transcription buffer and place them in the incubator at 37°C for ∼30 min.

    CRITICAL: Place the medium and PBS in the incubator at 37°C to minimize cellular stress and subsequent impairment of transcription dynamics during the BrUTP incorporation assay.

    Note: We recommend not to exceed 1 h of incubation of TEB and transcription buffer at 37°C prior to the experiment.

  • b.
    Prepare a glass plate covered with parafilm.
  • c.
    Prepare a 24-well plate by adding 0.5 mL of 4% paraformaldehyde (PFA) (w/v) to each well for each coverslip and transfer the plate to the fridge (4°C) to keep it cold.

    Note: The maximum number of coverslips that can be processed per round of the BrUTP incorporation assay is four. Processing more than four coverslips in a single round may introduce experimental error due to variations in incubation times between coverslips, potentially leading to increased deviation in the measured values and biased conclusions. Therefore, we recommend dividing the coverslips into independent rounds of BrUTP incorporation assays when necessary.

    Note: It is ideal to carry out the remaining steps up to fixation near the incubator to minimize potential biases caused by slight variations in incubation times.

• 4.Remove the cell culture dishes from the incubator, wash the coverslips once with 37°C PBS and transfer them to the prepared glass surface covered with parafilm.

Optional: It is recommended to use a culture dish filled with 37°C PBS, allowing the coverslip to be gently ‘dipped’ into the PBS using a tweezer for more effective washing.

• 5.Gently add 80 μL of TEB to each coverslip and incubate for 2 min at room temperature (RT, 20°C).

Note: Optimize the concentration of the Triton X-100 in the TEB based on the specific cell line. Different concentrations ranging from 0.02% to 0.1% should be tested to achieve optimal labeling of newly synthesized transcripts while using the minimal effective concentration of detergent.

CRITICAL: After adding TEB, cells become easily detached from the surface of the coverslip. Handle the coverslips gently throughout the remainder of the BrUTP incorporation assay and the subsequent staining procedure.

• 6.Remove TEB completely by tilting the glass surface and aspirating gently with a P1000 pipette, adjusted to 1000 μL.
• 7.Gently add 80 μL of the transcription buffer. Transfer the glass plate to the incubator and incubate for 8 min at 37°C.

Note: The duration of the incubation with the transcription buffer depends on the research purpose, and the cell type used. Specifically, labeling nucleolar RNAPI-mediated nascent transcription requires a shorter incubation time than labeling nuclear RNAPII-mediated transcription. This observation aligns with the nucleolus being the subnuclear compartment with the highest transcription activity during the S and G2 cell cycle phases.^16,17 In our recent publication,¹ 4 min of incubation with the transcription buffer in U2OS cells was sufficient for optimal labeling of nucleolar transcription. For nuclear transcription, however, 8 min of incubation was required. Notably, an 8-min incubation allows for the simultaneous acquisition of information on both nucleolar and nuclear transcription.

Figure 1.

Validation of the BrUTP incorporation assay in U2OS cells

(A) Schematic representation of the BrUTP incorporation assay workflow. U2OS cells are treated with different inhibitors, permeabilized for 2 min and incubated with BrUTP for 8 min. Red dots indicate newly synthesized transcripts where BrUTP has been incorporated into the ribonucleotide chain during transcription. Cells are fixed and stained, and images are acquired via confocal microscope for subsequent analysis.

(B) Representative images of nascent RNA synthesis in U2OS cells under different treatments with the indicated transcription inhibitors (concentrations and incubation times: THZ1, 1 μM, 1 h; RNase A, 100 μg/mL, 45 min; Actinomycin D - low concentration (ActD-Low), 0.1 μg/mL, 1 h; Actinomycin D - high concentration (ActD-High), 5 μg/mL, 1 h; Triptolide (TPL), 5 μM, 12 h). Cells were stained with fibrillarin, a marker of nucleolar compartments (Ncl), and BrUTP, and were analyzed by immunofluorescence. BrUTP incorporation in both nuclear (Nuc) and nucleolar compartments (Ncl) is depicted, indicating nascent ongoing transcription. Scale bar: 10 μm.

(C–F) BrUTP intensity distribution and quantification of BrUTP signal in the nuclear and nucleolar compartments after the indicated treatments. (C and E) Distribution of datasets for each treatment. The values corresponding to BrUTP mean intensity in the nuclear (Nuc) and nucleolar (Ncl) compartments follow a normal distribution, which was verified by Shapiro-Wilk test (W close to 1 and p ≥ 0.05). Outlier removal was performed using the interquartile approach (IQR) with a strict threshold k=0.5. (D and F) The mean intensity of BrUTP signal (was quantified from three regions of the nuclear compartment (Nuc) and one region of the nucleolar compartment (Ncl) per cell using ZEN (Blue Edition) software. Then, it was subtracted from the mean background intensity and relative fluorescence intensity was calculated (RFI). A total of 150 cells per treatment were analyzed. The dots corresponding to each bar represent individual biological replicates (three independent biological replicates per condition). Error bars represent the standard error of the mean (SEM). Statistical significance was determined using t-test. NS: non-significant, ∗p < 0.05, ∗∗p < 0.01, ∗∗∗∗p < 0.0001.

When using different cell types, optimization of incubation time should be considered, as transcription dynamics vary depending on the proliferation rate and metabolic state. As initial labeling times, we suggest 5, 10, and 15 min of incubation at 37°C. Longer incubation times may be required for cell lines with slower proliferation rates. An intense nucleolar BrUTP signal serves as a reliable marker of successful BrUTP incorporation, while the nuclear signal is expected to be significantly lower.

• 8.Completely remove the transcription buffer by tilting the glass surface and aspirating it gently with a P1000 pipette set to 1000 μL.
• 9.Gently wash the coverslips with COLD PBS (4°C) by submerging the coverslip into the PBS using tweezers.
• 10.After the wash, transfer the coverslips directly into a 24-well plate already containing 0.5 mL of 4% PFA (w/v) and incubate for 15 min at RT.
• 11.Remove the 4% PFA (w/v) by tilting the 24-well plate and aspirating it gently with a P1000 pipette, set to 1000 μL.
• 12.Gently add 1 mL of COLD PBS and keep the coverslips at 4°C until processing for immunofluorescence (IF).

Note: We recommend storing the coverslips in PBS at 4°C no longer than a week before further processing. Ensure that enough PBS is added to prevent the coverslips from drying out.

Immunofluorescence staining of BrUTP

Timing: 1–2 days

• 13.Aspirate the COLD PBS (4°C) by tilting the 24-well plate containing the coverslips using a P1000 pipette set to 1000 μL (the pipette is used instead of the standard vacuum-based aspiration system to ensure gentler handling of the cells).
• 14.Add 500 μL of permeabilization buffer (COLD PBS (4°C) containing 0.5% Triton X-100) to each well and incubate the coverslips for 10 minutes at RT.

Note: The permeabilization step (TEB-mediated) during the BrUTP incorporation assay enriches the chromatin-bound fraction of cellular proteins and allows nuclear accessibility of the BrUTP ribonucleotide. However, cells undergo a second permeabilization step at the beginning of the staining process using a 5-fold higher concentration of Triton X-100, which is optimal for ensuring intranuclear antibody accessibility and revealing the Bromo-domain epitope of BrUTP, enabling recognition by anti-BrdU.

• 15.Aspirate the permeabilization buffer by tilting the 24-well plate containing the coverslips and using a P1000 pipette set to 1000 μL.
• 16.Wash the coverslips three times with 500 μL of COLD PBS (4°C) to ensure complete removal of the permeabilization buffer.
• 17.Add 500 μL of COLD PBS+ blocking buffer (4°C) to each well and incubate the coverslips for 15 min at RT.

Note: While waiting, prepare a staining box by covering a glass slide with parafilm and marking it to distinguish the different coverslips. Fill the bottom of the staining box with H₂O to maintain a humid atmosphere and prevent the coverslips from drying out. We recommend using the StainTray Black Lid. However, a box covered with aluminum foil to block the light is also sufficient.

• 18.Aspirate the COLD PBS+ blocking buffer (4°C) by tilting the 24-well plate and using a P1000 pipette set to 1000 μL.
• 19.Using tweezers, transfer the coverslips to the parafilm-covered glass plate in the dark staining box, ensuring that the blocking buffer has been removed.
• 20.Add 100 μL of the primary antibody, diluted in COLD PBS+ blocking buffer (4°C), and incubate the coverslips for 1 h at RT.

Note: The concentration and incubation time for the anti-BrdU antibody should be optimized depending on the antibody type and cell line. In our case, a 1:500 dilution of the mouse monoclonal anti-BrdU antibody was used. Additionally, rat monoclonal anti-BrdU has also been successfully applied at the same dilution. However, commercially available anti-BrdU antibodies may differ in sensitivity depending on the manufacturer or batch, requiring fine-tuning for optimal performance. In our setup, U2OS cells were incubated with either mouse or rat monoclonal anti-BrdU antibodies for 1 h at RT.

• 21.Aspirate the primary antibodies by tilting the staining box and using a P1000 pipette set to 1000 μL.
• 22.Wash the coverslips three times with 150 μL of COLD PBS (4°C), with a 5-min incubation per wash.
• 23.Add 150 μL of COLD PBS+ blocking buffer (4°C) while preparing the secondary antibodies (∼5 min).
• 24.Add 100 μL of the secondary antibody diluted in COLD PBS + blocking buffer (4°C), along with Hoechst (1:2000), and incubate the coverslips for 1 h at RT.
• 25.Aspirate the secondary antibodies by tilting the staining box and using a P1000 pipette set to 1000 μL.
• 26.Wash the coverslips three times with 500 μL of COLD PBS (4°C), with 5-min incubation per wash.
• 27.Add 150 μL of double-distilled H₂O (ddH₂O) to each coverslip.
• 28.Aspirate the ddH₂O by tilting the staining box and using a P1000 pipette set to 1000 μL.
• 29.Allow the coverslips to dry in the dark for approximately 30 min before mounting.
• 30.Mount the stained coverslips on a glass slide using 5 μL of Vectashield per coverslip as a mounting medium. Seal the coverslips with nail polish and store them at 4°C overnight.
• 31.Perform microscopic observation using a Zeiss LSM 800 Confocal Laser Scanning Microscope equipped with a 63× oil immersion objective to acquire high-resolution images essential for subsequent analysis.

Analysis of nuclear and nucleolar BrUTP incorporation using the ZEN 2.6 Blue Edition software

Note: Global transcription is transiently suppressed upon DSB formation.¹⁸ This can be quantitatively assessed using ZEN 2.6 Blue edition software (hereafter referred as ZEN).

• 32.Open the ZEN analysis software.
• 33.
  Upload a czi-file for quantification.

  • a.
    Click on ‘File’ and choose ‘Open’.
• 34.
  Choose the areas for quantification.

  • a.
    Click ‘Dimensions’ and uncheck the BrUTP channel (AF568 channel). Use only the DAPI channel (Hoechst) and the Fibrillarin channel (AF488 channel) to identify the nuclear and nucleolar areas for BrUTP quantification, respectively.
  • b.
    Click ‘Graphics’, select a shape tool, and activate ‘Keep Tool’. In this protocol, the circle tool is used to create measurement frames (Figure 2B).
  • c.
    To quantify nuclear BrUTP incorporation, create three circular measurement frames per nucleus, explicitly avoiding Fibrillarin-positive regions (which represent nucleolar BrUTP incorporation) (Figure 2B, red circular frames).
  • d.
    Quantify ∼150 cells per experimental replicate to increase statistical robustness.

    Note: For nucleolar BrUTP intensity, place measurement frames directly on Fibrillarin-positive regions (Figure 2B, yellow dashed circular frames) for the same number of cells.

  • e.
    Using the same shape tool, place three additional measurement frames in areas of the image that do not contain any nuclei.

    Note: These three additional measurements of sub-step ‘e’ serve as background controls. The mean intensity values from these frames will be subtracted from the nuclear and nucleolar measurements for background correction.

• 35.
  Analyze BrUTP intensity values (AF568):

  • a.
    Click on ‘Measure’.
  • b.
    Copy the mean AF568 intensity values into an empty Excel spreadsheet.
  • c.
    Calculate the average background intensity from the three background frames and subtract it from each nuclear/nucleolar intensity value.

    Note: Background regions should be redefined for each image.

  • d.
    Following background correction, import the excel working sheets in R to carry out the statistical analysis and data visualization (Figures 1D and 1F).

    Note: You can also perform the analysis and data visualization in Graphpad Prism.

  • e.
    Download R-studio which is an integrated development environment (IDE) designed for R, to visualize and analyze your data in R.

    > # Bar plots generation

    > # Step 1: Load the necessary libraries

    > library(ggplot2)

    > library(rstatix)

    > library(dplyr)

    > # Step 2: Imported excel sheet

    > data <- Excel_working-sheet

    > # Step 3: Shape your data to long format

    > tidy_data <- data %>%

    +  pivot_longer(cols = everything(),

    +     names_to = "Condition",

    +     values_to = "Value")

    > # Step4: Calculate compute mean and SEM

    > summary_data <- tidy_data %>%

    +  group_by(Condition) %>%

    +  summarise(

    +   mean_value = mean(Value),

    +   sem_value = sd(Value) / sqrt(n()) # Standard error of the mean

    +  )

    > # Step 5: Order of the 'Condition' factor

    > summary_data$Condition <- factor(summary_data$Condition,

    +         levels = c("DMSO", "RNaseA", "THZ1", "ActD_Low", "ActD_High", "TPL"))

    > # Step 6: Generate the bar plot with SEM (No p-value annotation)

    > Your_data_name<- ggplot(summary_data, aes(x = Condition, y = mean_value, fill = Condition)) +

    +  geom_bar(stat = "identity", position = position_dodge(0.8), width = 0.6,

    +     color = "black", fill = "#800020") + # Bordeaux color and black outline

    +  geom_errorbar(aes(ymin = mean_value - sem_value, ymax = mean_value + sem_value),

    +      position = position_dodge(0.8), width = 0.25) +

    +  geom_point(data = tidy_data, aes(x = Condition, y = Value),

    +     color = "black", shape = 16, position = position_jitterdodge(jitter.width = 0.1, dodge.width = 0.8)) + # Add points

    +  labs(

    +   title = "Bar Plot with SEM and Individual Points",

    +   x = "Condition",

    +   y = "Mean Value"

    +  ) +

    +  theme_minimal() +

    +  theme(

    +   legend.position = "none",   # Remove legend

    +   panel.grid = element_blank(),  # Remove grid lines

    +   axis.line = element_line()     # Keep axes visible

    +  )

    > Your_data_name

    >

    > # Step 7: Save your data to your directory as .svg file

    > ggsave(Your_data_name,

    +   filename="/path/to/your/data/Your_data_name.svg",

    +   device="svg")

    Saving 6.18 x 5.6 in image

    > # Visualization of data distribution

    > # Step 1: Load the necessary libraries

    > library(readxl)

    > library(tidyr)

    > library(ggplot2)

    > library(ggridges)

    > # Step 2: Imported excel sheet

    > data <- Excel_working-sheet

    > # Step 3: shape the data to a long format

    > tidy_data <- data %>%

    +  pivot_longer(cols = everything(),

    +    names_to = "Condition",

    +    values_to = "Value") %>%

    +  drop_na()

    > # Step 4: Remove outliers based on the IQR method

    > remove_outliers <- function(x) {

    +  Q1 <- quantile(x, 0.25)

    +  Q3 <- quantile(x, 0.75)

    +  IQR <- Q3 - Q1

    +  x[x >= (Q1 - 0.5 ∗ IQR) & x <= (Q3 + 0.5 ∗ IQR)]

    + }

    > tidy_data <- tidy_data %>%

    +  group_by(Condition) %>%

    +  mutate(Value = ifelse(Value %in% remove_outliers(Value), Value, NA)) %>%

    +  drop_na()

    > # Step 5: Set the desired order of conditions

    > tidy_data$Condition <- factor(tidy_data$Condition,

    +         levels = c("DMSO", "RNaseA", "THZ1", "ActD_L", "ActD_H", "Trp"))

    > # Step 6: Plot the data with density ridges

    > Your_data_name <- ggplot(tidy_data, aes(x = Value, y = Condition, fill = Condition)) +

    +  geom_density_ridges(scale = 0.9, bandwidth = 1500, alpha = 0.6) +

    +  theme_minimal() +

    +  labs(

    +   title = "Density Distribution of Values by Condition (Outliers Excluded)",

    +   x = "BrUTP Intensity (RFI)",

    +   y = "Condition"

    +  ) +

    +  theme(legend.position = "none")

    > # Step 7: Save your data to your directory as .svg file

    > ggsave("Your_data_name.svg",

    +   plot = Your_data_name,

    +   path = "/ path/to/your/data/”

    +   device = "svg")

    Saving 6.18 x 5.6 in image

    > # Shapiro-Wilk normality test

    > # Step 1: Load the necessary libraries

    > library(ggplot2)

    > library(nortest)

    > library(tseries)

    > # Step 2: Load your data

    > data <- Excel_working-sheet # the values of your excel sheet correspond to a single condition.

    > # Step 3: Shape data to long format

    > tidy_data <- data %>%

    +  pivot_longer(cols = everything(),

    +     names_to = "Condition",

    +     values_to = "Value") %>%

    +  drop_na() # Remove NA values

    >

    > # Step 4: Extract the "Value" column

    > values <- tidy_data$Value    # Replace 'Value' with the column name

    > # Step 5: Visualize the distribution: Histogram with a Normal Curve

    > ggplot(tidy_data, aes(x = Value)) +

    +  geom_histogram(aes(y = ..density..), bins = 30, fill = "blue", alpha = 0.5) +

    +  stat_function(fun = dnorm, args = list(mean = mean(values), sd = sd(values)), color = "red") +

    +  labs(title = "Histogram with Normal Curve", x = "Values", y = "Density") +

    +  theme_minimal()

    > shapiro.test(values)

    > # t-test parametric statistical approach

    > # Step 1: Imported excel sheet

    > data <- Excel_working-sheet

    > # Step 2: Shape data to long format

    > tidy_data <- data %>%

    +  pivot_longer(cols = everything(),

    +     names_to = "Condition",

    +     values_to = "Value")

    > # Step 3: Compute mean and SEM

    > summary_data <- tidy_data %>%

    +  group_by(Condition) %>%

    +  summarise(

    +   mean_value = mean(Value),

    +   sem_value = sd(Value) / sqrt(n()) # Standard error of the mean

    +  )

    > # Step 4: Calculate the mean value for each condition

    > mean_data <- tidy_data %>%

    +  group_by(Condition) %>%

    +  summarise(mean_value = mean(Value, na.rm = TRUE))

    > # View the mean values

    > print(mean_data)

    # A tibble: 6 × 2

     Condition mean_value

     <chr>       <dbl>

    1 ActD_High     0.0875

    2 ActD_Low     0.106

    3 DMSO        1

    4 RNaseA     0.0741

    5 THZ1     1.08

    6 TPL       1.56

    > # Step 5: Perform t-test comparing DMSO mean to other conditions' means

    > t_test_results <- tidy_data %>%

    +  filter(Condition != "DMSO") %>% # Exclude DMSO from comparison

    +  group_by(Condition) %>%

    +  summarise(mean_value = mean(Value, na.rm = TRUE)) %>%

    + mutate(p_value = sapply(Condition, function(cond) {

    +  # Perform t-test for DMSO vs each condition

    +  t.test(tidy_data$Value[tidy_data$Condition == "DMSO"],

    +    tidy_data$Value[tidy_data$Condition == cond])$p.value

    +  }))

    > # step 6: View t-test results

    > print(t_test_results)

Figure 2.

Analysis of BrUTP mean intensity signal in nuclear and nucleolar regions using ZEN 2.6 Blue Edition software

(A) The ZEN interface, where images acquired using the Zeiss LSM 800 and exported as .czi files are uploaded for analysis via the File → Open command. At the bottom of the figure, the image tools are displayed, including options for dimensions and graphics.

(B) The red square in the image tool area highlights the available shape tools in the graphics section. Specifically, the circle tool is used to create measurement frames over nuclear regions defined by the Hoechst signal, where the mean intensity of BrUTP is quantified. Fibrillarin staining (green fluorescence) is used to delineate nucleolar compartments. Measurement frames are placed as follows: (1) Dashed circular frames, overlapping with fibrillarin-positive regions, are used to measure nucleolar BrUTP mean intensity. (2) Red circular frames, positioned in regions excluding nucleoli, are used to measure nuclear BrUTP mean intensity and background signal. The ‘Keep Tool’ function remains activated to allow repeated use of the same shape tool when framing multiple regions within the image. Objects that fall entirely within the defined measurement frames are included in the analysis. By selecting the Measure function (left-hand side of the interface), mean intensity values for each fluorescence channel are displayed in a table, highlighted by the red box on the right-hand side of the figure.

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies
Mouse anti-BrdU (pure B44 100T) (used 500 times diluted)	BD Biosciences	Cat#347580; RRID: AB_10015219
Rat anti-BrdU (used 500 times diluted)	AbD Serotec	Cat#OBT0030; RRID: AB_609568
Mouse monoclonal anti-H2A.X (pS140) (used 1,000 times diluted)	Abcam	Cat#ab22551; RRID: AB_447150
Alexa Fluor 568 goat anti-mouse (used 10,000 times diluted)	Invitrogen	Cat#A-11031; RRID: AB_144696
Alexa Fluor 488 goat anti-rabbit (used 10,000 times diluted)	Invitrogen	Cat#A-11034; RRID: AB_2576217
Goat anti-rat IgG (H+L) cross-absorbed secondary antibody, DyLight 555 (Used 500 times diluted)	Invitrogen	Cat#A-21434; RRID: AB_141733
Chemicals, peptides, and recombinant proteins
THZ1	Calbiochem	Cat#532372
Hoechst 33342 trihydrochloride, trihydrate (used 2,000 times diluted)	Invitrogen	Cat#H3570
VECTASHIELD	Vector Laboratories	Cat#H1000
Paraformaldehyde (PFA)	VWR Chemicals BDH	Cat#9713.1000
Triton X-100	Sigma	T8787-250
MgCl2 powder	Sigma	208337
PMSF	Sigma	10837091001
5-Bromouridine 5′-triphosphate sodium salt (BrUTP)	Sigma	Cat#B7166
Adenosine 5′-triphosphate (ATP) lithium salt	Roche	Cat#11140965001
Guanosine 5′-triphosphate lithium salt (GTP)	Sigma	Cat#G5884-25MG
Cytidine 5′-triphosphate disodium solution (CTP)	Sigma	Cat#C8552-25UMO
RNase inhibitor	Thermo Fisher Scientific	Cat#N8080119
Gibco DMEM, high glucose, GlutaMAX supplement	Thermo Fisher Scientific	Cat#10566016
Actinomycin D (ActD)	Thermo Fisher Scientific	Cat#A7592
PureLink RNase A (20 mg/mL)	Thermo Fisher Scientific	Cat# 12091021
CO2 independent medium	Thermo Fisher Scientific	Cat#18045088
Fetal bovine serum (BSA)	Thermo Fisher Scientific	Cat#10270106
Penicillin-streptomycin	Thermo Fisher Scientific	Cat#15070063
Tween 20	Biochemica	Cat#A1389.1000
NaN3 (sodium azide)	Merck	Cat#2002
Experimental models: Cell lines
Human: U2OS	ATCC	Cat#HTB-96
Software and algorithms
Fiji (ImageJ)	NIH	N/A
GraphPad Prism 8	GraphPad	https://www.graphpad.com/
Palm Robo Software 4.5	Zeiss	N/A
ZEN (Blue edition)	Zeiss	N/A
Other
Glass slides, 7 × 26 mm StarFrost white	Hounisen Laboratorieudstyr A/S	Cat#2510.1201HV
12 mm coverslips	Menzel-Glaser	631–0713
StainTray black lid	Carl Roth	Cat#HA51.1
24-well culture dish, Nunclon, Delta surface	Thermo Scientific	Cat#142475
60 mm culture dish, Nunclon, Delta surface	Thermo Scientific	Cat#150288
PALM UV-A pulsed nitrogen laser (30 Hz, λ=377 nm)	P.A.L.M. Microlaser	N/A
Zeiss Axiovert 200 microscope	Zeiss	N/A

Materials and equipment

• •ATP, lithium salt: 100 mM solution of lithium salt (pH 7).

Stored at −20°C for several months.

• •CTP, disodium solution: 95–105 mM in H₂O (adjusted to pH 7 with Sodium Hydroxide).

Stored at −20°C for several months.

• •GTP, lithium salt: 25 mg of GTP, lithium salt.

Stored at −20°C for several months.

• •BrUTP, sodium salt: powder.

Stored at −20°C for several months.

• •THZ1: 1 mM in DMSO.

Stored at −20°C for several months.

• •ActD: 10 mM in DMSO.

Stored at −20°C for several months.

• •TLP: 10 mM in DMSO.

Stored at −20°C for several months.

• •RNase A: 20 mg/mL in 50 mM Tris-HCl (pH 8.0), 10 mM EDTA.

Stored at 4°C for several months.

PBS+ blocking buffer

Reagent	Final concentration	Amount
PBS	N/A	500 mL
Tween 20	0.1% v/v	500 μL
NaN3 (stock 10%)	0.05% v/v	10 μL
BSA	1% w/v	5 g
Total	N/A	500 mL

Stored at 4°C for several months.

Note: Since Tween-20 is a highly viscous substance, a useful trick is to cut the tip of a 1000 μL pipette tip before aspirating to facilitate accurate dispensing.

CRITICAL: Always prepare TEB and transcription buffer fresh on the day of the experiment. The total volumes provided in the recipes (0.5 mL or 1 mL) are sufficient for one or two experiments, based on a typical setup where four coverslips are processed per experiment.

CRITICAL: Keep the reagents on ice while preparing the buffers.

Transcription Extraction Buffer (TEB)

Reagent	Final concentration	Amount
Tris pH 7.4 (stock 1 M)	20 mM	20 μL
MgCl2 (stock 50 mM)	5 mM	100 μL
EGTA (stock 0.5 M)	0.5 mM	1 μL
Glycerol (stock 100%)	25% v/v	250 μL
Triton X-100 (stock 20%)	0.1%	5 μL
PMSF (stock 100 mM)	1 mM	10 μL
RNase Inhibitor (stock 2000 U)	2 U	1 μL
ddH2O	N/A	613 μL
Total	N/A	1 mL

This buffer needs to be freshly made before each experiment, so long storage is not recommended. Can be stored at 37 from 30 min–1 h before experiment is performed.

CRITICAL: 20% Triton X-100 is harmful for the eyes and can cause skin irritation. Gloves and appropriate eye protection is necessary.

Transcription buffer

Reagent	Final concentration	Amount
KCl (stock 1 M)	100 mM	100 μL
Tris pH 7.4 (stock 1 M)	50 mM	50 μL
MgCl2 (stock 50 mM)	10 mM	200 μL
EGTA (stock 0.5 M)	0.5 mM	1 μL
Glycerol (stock 100%)	25% v/v	250 μL
PMSF (stock 100 mM)	1 mM	10 μL
RNase Inhibitor (stock 2000U)	2U	1 μL
ddH2O	N/A	372 μL
ATP (stock 100 mM)	1 mM	10 μL
CTP (stock 95-105 mM)	200 nM	2 μL
GTP (stock 100 mM)	200 nM	2 μL
BrUTP (stock 100 mM)	200 nM	2 μL
Total	N/A	1 mL

This buffer needs to be freshly made before each experiment, so long storage is not recommended. Can be stored at 37 from 30 min–1 h before the experiment is performed.

Step-by-step method details

BrUTP incorporation in UV-A laser-ablated DNA regions

Timing: 2 days

This step enables time-resolved monitoring of de novo RNA synthesis at defined DNA damage sites.

Note: UV-A laser ablation was selected over other DNA-damaging agents and ionizing irradiation (e.g., γ-irradiation) because it provides specific advantages in terms of temporal resolution, spatial precision, and minimized cellular stress.¹⁹ In particular, UV-A laser-induced DSBs allow immediate monitoring of nascent RNA synthesis at damaged sites, offering an early snapshot of the first wave of non-canonical transcription. Capturing this narrow time window is challenging with ionizing radiation or chemical DNA-damaging agents, where DNA damage is more diffuse and less temporally defined. Additionally, UV-A ablation permits precise subnuclear targeting, enabling localized DNA damage and focused BrUTP monitoring. In contrast, γ-irradiation and chemical agents result in widespread nuclear damage, complicating transcriptional analyses at defined foci. Importantly, localized DSBs induced by UV-A laser ablation reduce global cellular stress and help preserve pools of DNA damage response proteins involved in transcription-associated repair. BrUTP incorporation at these laser-induced sites can be quantified using Fiji (ImageJ) software.

• 1.Seed 3.5 × 10⁵ U2OS cells in 60 mm diameter cell culture dishes (one for each treatment condition) with coverslips at their bottom.

Note: By the day of the experiment cells need to be around 75-80% of confluency.

Note: UV-A microirradiation targets a single 20× field of view, so 70–80% confluency ensures sufficient cell density. Overconfluency may alter cell cycle progression and impair specific DNA repair pathways.²⁰

Note: A BrdU pre-sensitization step is commonly used to enhance DSB formation by reducing laser power. However, due to the shared bromodomain between BrdU and BrUTP, we omit this step to prevent false-positive signals from anti-BrdU antibodies. Instead, higher laser power is applied to induce DSBs effectively.

• 2.On the day of the experiment, replace the culture medium with CO₂-independent medium, unless the microscope has an integrated CO₂ incubation chamber.

Note: UV-A ablation is performed at 37°C and 5% CO₂. In the absence of a CO₂ chamber, CO₂-independent medium maintains cellular homeostasis during live-cell imaging.

• 3.Prepare all BrUTP assay reagents, including the transcription buffer and TEB, and pre-warm them to 37°C in an incubator for ∼30 min, along with PBS.
• 4.Prepare a glass plate covered with parafilm and a 24-well plate containing 0.5 mL of 4% PFA (4°C) per well for coverslip fixation.
• 5.Switch on the microscope in advance to allow the chamber to reach 37°C.

Note: Zeiss Axiovert 200 microscope with PALM Microbeam Workstation (P.A.L.M. Technologies) and an Axiocam ICc1 camera was used for the UV-A laser microirradiation in our experimental setup.

• 6.Transfer dishes to the microscope. At 20× magnification, locate a single field containing the desired cell density.
• 7.Use PALMRobo V4.5 and navigate to your desired field on the coverslip and set the UV-A laser parameters: Pulsed Nitrogen Laser→ 377 nm, Pulse Frequency→ 30 Hz, Pulse Energy→ >270 μJ and Laser Output→ 56%.

Note: Select a field near the center of the coverslip to avoid edge detachment during subsequent staining steps. Knowing the position of the irradiated area helps later detection on the confocal microscope.

Note: For non-pre-sensitized cells, increase the laser output to 56% (vs. 50% for BrdU-sensitized cells) to maintain DSB efficiency corresponding to the average energy power of approximately 4.54 (AverageEnergyPower(W)=PulseEnergy(j)×PulseFrequency(Hz)).

• 8.Use the line tool in PALMRobo to design the UV-A laser path, ensuring each nucleus in the frame is targeted once.

Note: Cells are visualized in bright field via Axiocam ICc1 while designing the laser path, ensuring precise targeting.

• 9.Click ‘Start cutting laser’ to perform UV-A ablation. After irradiation, immediately transfer cells back to the incubator and begin timing the recovery period.
• 10.After the desired recovery time, proceed directly with the BrUTP incorporation assay as described in the “optimization of the BrUTP incorporation assay” section.

Immunochemical staining of DSBs and incorporated BrUTP

• 11.Follow the same steps as described in “immunofluorescence staining of BrUTP” section.

Note: There is one modification of the workflow described in “immunofluorescence staining of BrUTP”: replace the anti-fibrillarin antibody with anti-γH2AX to detect UV-A-induced DSBs. In particular, the primary antibody solution should contain both anti-BrdU (for BrUTP detection) and anti-γH2AX (for DSB detection). γH2AX acts as a surrogate marker for DSBs. Measuring BrUTP incorporation within γH2AX-positive areas provides a robust readout of DSB-induced de novo RNA synthesis. Imaging is performed using a Zeiss LSM 800 confocal microscope equipped with a 63× oil immersion objective.

Quantification and analysis of BrUTP incorporation at DSB sites using Fiji (ImageJ)

Timing: 1–2 days

Note: BrUTP signal quantification is performed in Fiji (ImageJ) using γH2AX as a mask for UV-A-induced DSBs.

• 12.Open Fiji (ImageJ) and load an image of UV-A-irradiated cells.
• 13.Split the channels: go to Image→ Color→ Split channels. You will get three windows: BrUTP, γH2AX, and Hoechst (Figure 3A).
• 14.In the γH2AX channel, zoom in on a single cell.
• 15.Use the selection tool (Figure 3B) to mark the γH2AX-positive region.
• 16.Copy the selection to the BrUTP channel by clicking that window and pressing Ctrl+Shift+E.

Note: Avoid including nucleolar regions in the selection, as they may show BrUTP signal unrelated to DNA damage. This is likely due to UV-A off-focus effects, as nucleolar regions are not directly targeted by the laser and remain transcriptionally active.

• 17.Set the measurements: go to Analyze→ Set measurements, and check ‘Mean gray value’ to record the mean pixel intensity.
• 18.Open the ROI manager (Analyze→ Tools→ ROI manager), click ‘Add’, then ‘Measure’. The mean BrUTP intensity for the selected γH2AX region will appear in the results window (Figure 3C).
• 19.Analyze and visualize your data using either R (via RStudio IDE) or GraphPad Prism. R scripts used for the nuclear/nucleolar quantification (see ZEN section) can be reused here.

Note: You may also use the Stripenator v1 plugin in Fiji for high-throughput BrUTP quantification. It automates ROI generation based on Hoechst for nuclei and thresholded γH2AX stripes for damaged regions.²¹ Be cautious of nucleolar BrUTP overlap in γH2AX-positive regions, which may bias quantification.

Figure 3.

Analysis of BrUTP mean intensity at DSBs using Fiji (ImageJ)

(A) The Fiji (ImageJ) toolbar interface after splitting multichannel images into 8-bit grayscale. Shown are the γH2AX and BrUTP channels from UV-A-irradiated cells. The freehand selection tool, used to define regions of interest (ROIs) based on γH2AX staining, is highlighted with an arrow. A single cell is zoomed in, and a ROI has been drawn on the γH2AX channel and copied to the BrUTP channel using Ctrl + Shift + E. Scale bar: 10 μm.

(B) The ROI Manager plugin, where the selected ROI is added from the BrUTP channel for quantification.

(C) The Measurements window displaying quantification parameters. Area: size of the ROI in pixels. Min / Max: minimum and maximum pixel intensities within the ROI (ranging from 0 [black] to 255 [white] in 8-bit images). Mean: average pixel intensity across all pixels in the ROI, representing the mean BrUTP signal intensity.

Quantification and analysis of global nuclear BrUTP incorporation using the ZEN 2.6 Blue Edition software

Note: Global transcription is transiently suppressed upon DSB formation.¹⁸ This suppression can be measured by quantifying BrUTP incorporation using ZEN 2.6 Blue Edition software.

• 20.Open the ZEN analysis software.
• 21.
  Upload a .czi file for quantification:

  • a.
    Click on ‘File’ and select ‘Open’.
• 22.
  Define the areas for quantification:

  • a.
    Click ‘Dimensions’ and deselect the BrUTP channel (AF568). Use only the DAPI channel (Hoechst) and the γH2AX channel (AF488) to identify regions for BrUTP quantification. This approach minimizes potential bias during manual analysis.

    Note: Since this is a manual analysis, we recommend performing it using blinded sample labels to reduce subjective bias.

  • b.
    As previously described in “analysis of nuclear and nucleolar BrUTP incorporation using the ZEN 2.6 Blue Edition software”, click on ‘Graphics’, choose a shape tool, and activate ‘Keep Tool’.
  • c.
    Create three circular measurement frames per irradiated nucleus, avoiding nucleoli and γH2AX-positive DSB sites.
  • d.
    Create three additional measurement frames in nucleus-free areas of the image for background correction.

    Note: Highly transcribed nucleoli appear as dark cavities in the nucleus in the DAPI channel, due to their lower DNA density relative to the surrounding nucleoplasm.

• 23.Analyze AF568 signal intensity within the selected regions:

Note: Follow the same steps outlined in the section “analysis of nuclear and nucleolar BrUTP incorporation using the ZEN 2.6 Blue Edition software”. After background subtraction, statistical analysis and data visualization can be performed using either R (with the provided scripts) or GraphPad Prism.

Expected outcomes

This protocol is expected to generate image-based data reflecting de novo RNA synthesis at DSB sites. A representative outcome is shown in Figure 5. UV-A-ablated cells were subjected to confocal microscopy, and BrUTP incorporation was quantified in both irradiated and non-irradiated nuclear regions (Figure 4). As anticipated, nascent transcription in non-irradiated regions is downregulated in a time-dependent manner following DSB induction. In line with our previously published data,¹ an early wave of nascent transcription can be detected within the first 5 min after DSB formation (Figure 5). However, increased variability in BrUTP incorporation is also observed at this time point. This heterogeneity is likely due to differences in cell cycle stage and local chromatin conformation at the genomic loci where DSBs occur, both of which can influence transcriptional activity and repair dynamics.

Figure 5.

BrUTP incorporation at UV-A laser-induced DNA damage sites

(A) Representative confocal images of U2OS cells following UV-A laser ablation and BrUTP incorporation assay at various time points. Cells were fixed at the indicated intervals post-irradiation and subjected to immunofluorescence staining for γH2AX (a marker of DNA double-strand breaks) and BrUTP (marking nascent RNA synthesis). Irradiated regions are outlined in white, denoting sites where BrUTP incorporation was quantified. BrUTP signal was also measured in γH2AX-negative, non-nucleolar nuclear regions of irradiated cells to assess global nuclear transcription. Scale bar: 10 μm.

(B and D) Distribution of BrUTP mean intensity values at the indicated time points post-UV-A ablation: (B) In γH2AX-positive regions (irradiated areas), BrUTP intensity distributions significantly deviated from normality, as determined by the Shapiro-Wilk test (W ≈ 1, p < 0.05). However, due to large sample sizes (n > 30), statistical comparisons were performed using a t-test, as justified by the Central Limit Theorem (CLT). A Mann-Whitney U test was also used and showed consistent significance levels. (D) In γH2AX-negative nuclear regions, BrUTP signal distributions followed a normal distribution (p ≥ 0.05), with the exception of the 0- and 10-min time points (p < 0.05). Again, large sample sizes allowed the use of parametric t-tests in accordance with the CLT.

(C and E) Quantification of BrUTP signal intensity at DSB sites and in undamaged nuclear areas: (C) BrUTP mean intensity in γH2AX-positive areas was measured using the Fiji ROI Manager plug-in and subtracted from the mean background intensity to calculate RFI. Values were collected from >15 cells per replicate across three biological replicates and pooled for each time point. (E) In parallel, three γH2AX-negative regions per irradiated nucleus were analyzed using ZEN (Blue Edition) software, and mean intensity values were similarly processed across replicates to extract RFI. Error bars represent the standard error of the mean (SEM). Statistical significance was determined using t-tests or Mann-Whitney U tests, as appropriate. NS: not significant; ∗∗∗∗ p < 0.0001.

Figure 4.

Analysis of BrUTP mean intensity signal in non-irradiated nuclear regions using ZEN 2.6 Blue Edition software

(A) The ZEN interface displaying the analysis workspace. Images acquired using the Zeiss LSM 800 and exported as .czi files are opened via the File → Open command. The bottom panel shows the image tools, including options for Dimensions and Graphics.

(B) The red square highlights the shape tools available in the Graphics section. For this analysis, the circular tool is used to draw measurement frames in non-irradiated nuclear regions to quantify BrUTP mean intensity. The ‘Keep Tool’ function is activated to allow repeated use of the same shape for multiple regions of interest (ROIs) across the image. Only objects fully enclosed within the circular measurement frames are included in the analysis. By clicking Measure (indicated on the left side of the interface), mean intensity values for each fluorescence channel are generated and displayed in the results table, highlighted by the red frame on the right.

Limitations

The BrUTP incorporation assay is labor-intensive, particularly for short time-course experiments, where even minor variations in handling can introduce experimental bias. Moreover, the assay is performed in vitro on permeabilized nuclei, enabling ribonucleotide incorporation by chromatin-bound RNA polymerases. However, the permeabilization and in vitro transcription steps may impose stress on the cells, potentially affecting transcriptional phenotypes. To compensate for the absence of BrdU pre-sensitization, the UV-A laser microirradiation is applied at increased pulse energy, which efficiently induces DSBs, as verified by γH2AX staining. Nevertheless, this setup also generates other types of DNA damage, including cyclobutane pyrimidine dimers, 6-4 photoproducts, single-strand breaks, and oxidative lesions such as 8-oxoG, thereby activating multiple DNA repair pathways.¹⁹ The image analysis protocol relies on manual quantification. While this approach is accessible using standard laboratory equipment, it is time-consuming; future implementation of automated pipelines and AI-based tools is expected to enhance both throughput and reproducibility. It should also be noted that this protocol has been optimized for adherent 2D cell cultures but may require further adjustment for use in 3D systems such as organoids or spheroids. Additionally, certain adherent cell lines, such as HeLa, may be especially prone to detachment during permeabilization, particularly when confluency exceeds 70%. Finally, while BrUTP incorporation provides a useful snapshot of transcriptional activity, it offers limited temporal resolution. Therefore, complementary approaches, such as high-content microscopy and transcriptomic profiling (e.g., DRB/TTchem-seq),^1,22 are recommended for a more comprehensive analysis of transcriptional responses at DNA damage sites.

Troubleshooting

Problem 1

Cell loss during permeabilization with TEB (low yield of cells on coverslips) (steps 5–10 as described in “immunofluorescence staining of BrUTP”).

Potential solution

• •Reduce cell confluency on the day of the experiment. For sensitive lines such as HeLa, seeding fewer cells to reach ∼60% confluency improves adherence.
• •Pre-coat coverslips with extracellular matrix components (e.g., Matrigel) to improve cell adhesion.

Note: This condition has not yet been tested in this protocol.

Problem 2

Low BrUTP signal intensity (steps 31 as described in “immunofluorescence staining of BrUTP”).

Potential solution

Always use freshly prepared buffers and reagents. The permeabilization and transcription buffers should be prepared on ice and on the same day as the experiment. Additionally, prepare a fresh Triton X-100 solution to ensure maximal reagent efficacy.

Problem 3

High variability in BrUTP signal at γH2AX-positive DSB sites (steps 12-19 “BrUTP incorporation in UV-A laser-ablated DNA regions”).

Potential solution

Perform cell cycle synchronization prior to UV-A laser ablation and BrUTP incorporation. Different cell cycle phases affect transcription dynamics and chromatin structure, potentially altering BrUTP incorporation and DSB response.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Panagiotis Galanos, panos@bmb.sdu.dk.

Technical contact

Technical questions on executing this protocol should be directed to and will be answered by the technical contacts, Panagiotis Galanos, panos@bmb.sdu.dk, and Georgios Pappas, georgios.pappas@cpr.ku.dk.

Materials availability

This study did not generate new unique reagents.

Data and code availability

Pappas et al.¹ includes all the datasets generated and analyzed using this protocol.

Acknowledgments

P.G. is funded by The Lundbeck Foundation (R445-2023-788) and the Danish Cancer Society (R364-A21079). J.B. and the members of his groups were funded by the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement 722729 and by grants from the Danish Cancer Society (R322-A17482), The Lundbeck Foundation (R453-2024-326), the Novo Nordisk Foundation (NNF20OC0060590), the Swedish Research Council (VR-MH 2014-46602-117891-30), the Danish Council for Independent Research (DFF-7016-00313), and the Danish National Research Foundation (project CARD, DNRF 125). The schematics in the graphical abstract and Figures 1 and 5 were created with BioRender.com.

Author contributions

G.P., H.G.G., and P.G. conducted the experiments and the data analysis. G.P., H.G.G., J.B., and P.G. wrote the manuscript.

Declaration of interests

The authors declare no competing interests.