Integrating Genomic Signatures with Functional Analysis of DNA repair

PROJECT SUMMARY Genome instability is the underlying cause of many diseases including premature aging, neurodegeneration, cancer, and immunodeficiency. Genome integrity is maintained by at least six major DNA repair pathways, each of which specializes in the repair of distinct types of DNA damage or replication

errors. Inefficient DNA repair in any of these pathways can lead to the accumulation of DNA damage, mutations, and disease. Thus, to study the mechanisms by which DNA repair protects against disease, we need to know the status of all DNA repair pathways in human cells. Mutational signatures provide valuable

insights into DNA repair, but they have several important limitations. Mutational signatures may not reflect the current status of DNA repair, and the bulk sequencing most commonly used to measure mutational signatures can miss important cell-to-cell heterogeneity. Furthermore, the relationship to the functional status of DNA

repair remains poorly understood for many mutational signatures. Direct measurements of DNA repair would overcome these obstacles, but technology capable of the necessary large-scale functional analyses of DNA repair have not been available. We will address this long unmet need by developing high-throughput functional

assays and an advanced analytical framework for single-cell resolution measurements of all major DNA repair pathways. Our strategy is based on our well-established and widely applied fluorescence multiplex host cell reactivation (FM-HCR) assays, which report the ability of cells to repair site-specific DNA lesions incorporated

into fluorescent reporter plasmids. Using a sequencing approach (HCR-Seq) that is firmly established in our preliminary data, we will generate a library of reporter plasmids that can signal DNA repair capacity by a change in the abundance or sequence of a reporter transcript, instead of a fluorescent signal. Following

transient transfection of 500 cell lines (transfected in 20 pools of approximately 25 cell lines each), reporter transcripts and host cell transcriptomes will be analyzed by single-cell RNAseq. The resulting dataset will generate an unprecedented resource: comprehensive multi-pathway DNA repair analyses with single-cell

resolution in 500 highly characterized cell lines that are part of the Cancer Cell Line Encyclopedia. This dataset will be integrated with existing sequencing and proteomics data to identify relationships of DNA repair capacity with mutational signatures, genomic and epigenomic somatic alterations, and gene and drug dependencies.

The dataset will also provide an unprecedented view of cell-to-cell heterogeneity with respect to DNA repair that can be interpreted in the context of host cell transcriptomes, as we have shown for cell cycle-dependent regulation of DNA repair. Our dataset and approach will be shared with the scientific community in the Broad

DepMap Portal to advance future projects aimed at understanding the biological mechanisms underlying genome instability and the potential for translational work aimed at predicting and preventing its consequences for human health.