A549 Epitherapy scCUT&Tag

Transposable elements (TEs) provide a vast source of cis-regulatory potential that becomes derepressed in cancer and can be further potentiated through epigenetic modifying enzyme inhibition. This derepression generates TE-chimeric transcripts, whose expression is modulated by p53 mutational status. However, the relationship between p53 and transposable element expression in the context of epitherapy remains poorly understood, limiting the potential for clinical translation. In this study, we combine DNA methyltransferase inhibition and histone deacetylase inhibition to perturb the epigenomes of three isogenic cancer cell lines and demonstrate that transcripts derived from ERV1-family members are regulated in a p53-dependent manner. Using single-cell data, we show that this regulation is maintained across cell populations, including those most highly derepressed by treatment. Together, these findings underscore the importance of p53 in suppressing LTR-derived transcription under epitherapy, informing the future application of epigenetic therapies in p53 WT and mutant cancer. This dataset contains raw sequencing files (.fastq) for the scCUT&Tag experiment performed in this study. On days 1, 3, and 5 post-seeding, cells in the treatment arm were given fresh media containing 300 nM decitabine, and cells in the control arm were given the same volume of 0.9% NaCl. On day 6 post-seeding, A549 and RKO cells in the treatment arm were given fresh media containing 300 nM decitabine and 40 nM panobinostat, and HCT116 cells in the treatment arm were given fresh media containing 300 nM decitabine and 20 nM panobinostat. 100k cells per sample underwent light fixation and nuclear extraction. Resulting nuclei were bound to Concanavalin A beads followed by binding to primary antibodies targeting histone PTMs of interest, secondary antibody and pAG-Tn5. After tagmentation with Tn5, nuclei were dispensed on the ICELL8 cx Single-Cell System (Takara Bio 640188) and single nuclei candidates were selected. Next, nuclei were lysed and barcodes were added by PCR to generate sequencing ready libraries. Libraries from all nuclei were pooled, cleaned up using NucleoMag NGS Clean-up and Size Select beads (Takara Bio, Cat. No. 744970.5) and quantified using Qubit (Invitrogen, Q33231) and Tapestation (Agilent, 5067-5589). Individual cell sequence files were aligned to the GENCODE v46 hg38 primary assembly using Bowtie 2 v2.5.1 and filtered for properly paired and high-quality reads using SAMtools v1.18. To generate consensus peaksets for each histone mark, individual cell alignment files were concatenated using SAMtools into a single pseudobulked alignment file which were then used to call peaks using MACS2 v2.1.2, with H3K27ac peaks called with summits and H3K27me3 peaks called using the --broad flag. Individual cell alignment files were converted to fragment files using SnapATAC2 v2.8.0, which were subsequently imported into R for downstream analysis in ArchR. Dimensionality reduction through iterative latent semantic indexing and clustering were done in ArchR, and these matrices were then extracting and used to generate objects in Signac/Seurat for plotting. Normalized signal coverage of histone marks at TEs and CCREs were calculated using the AddChromatinModule function in Signac for the corresponding genomic annotation.