Single-cell Joint Profiling of Single- and Double-Stranded DNA Breaks with Transcriptome

/Abstract Both genome instability and epigenetic dysregulation are hallmarks of cancer, and the interact with each other in complex ways. Defects in DNA repair pathways is a near-universal feature of cancer and drives a cascade of detrimental effects. This reliance also presents as an opportunity for cancer therapy: by deliberately introduce DNA damage, e.g., single- and double- strand DNA breaks (SSBs and DSBs), to promote tumor cell death. Genome-wide DNA damage sequencing methods were developed for bulk cell populations analysis and significantly advanced our knowledge. However, the intrinsic heterogeneity of cancer environments represents a formidable challenge. Understanding the interplay between different types of DNA strand breaks and their impacts on gene regulation is critical for developing effective and personalized cancer therapies; however, which is hindered by the lack of proper single-cell technologies. Single-cell multiomics methods, by measuring multiple molecular layers simultaneously from single cells, enabled the characterization of complex relationships between biological distinct modalities in heterogeneous cellular populations. Recently, we developed Paired-Damage-seq for simultaneous analysis of oxidative and single-strand DNA breaks with gene expression. This work revealed that hotspots of DNA damage are also vulnerable regions for epigenetic memory loss, exhibiting cell-type specific distribution patterns and linking dysregulated gene programs to disease risks. To elucidate their combinatorial roles of multiple types of DNA damage in complex cellular processes, new methods are still desired. To fill this technical gap, in this proposal we will develop and validate Paired-Break-seq, a novel high-throughput single- cell multiomics sequencing technique for joint analysis of DNA DSBs, SSBs, and transcriptome. Firstly, we will parallelly test and compare two approaches for orthogonal labeling of DNA DSBs and SSBs on bulk cultured cells (Aim 1). Next, we will couple the optimal one with transcriptome profiling and combinatorial indexing and validate its performances in single-cell analysis (Aim 2). Finally, to justify the feasibility for R33 transition, we will apply Paired-Break-seq to three cancer cell lines treated with DNA damage-inducing drugs (Aim 3). Paired- Break-seq can be widely adopted to study drug responses, to reveal how cancer cells’ epigenome remodeled for drug resistance. The integrated single-cell toolkit creates opportunities for identifying novel biomarkers to predict treatment responses and maximize efficacy and minimize toxicity for individual patients. The outcome of this project will also be complementary to other IMAT initiatives focusing on different aspects of cancer genomics. Project Number: 1R61CA309705-01 | Fiscal Year: 2026 | NIH Institute/Center: National Cancer Institute (NCI) | Principal Investigator: Chenxu Zhu | Institution: NEW YORK GENOME CENTER, NEW YORK, NY | Award Amount: $270,683 | Activity Code: R61 | Study Section: Special Emphasis Panel[ZRG1 BTC-N (55)] View on NIH RePORTER: https://reporter.nih.gov/project-details/11311609