A novel method for the genome-wide high resolution analysis of DNA damage.

DNA damage occurs via endogenous and exogenous genotoxic agents and compromises a genome's integrity. Knowing where damage occurs within a genome is crucial to understanding the repair mechanisms which protect this integrity. This paper describes a new development based on microarray technology which uses ultraviolet light induced DNA damage as a paradigm to determine the position and frequency of DNA damage and its subsequent repair throughout the entire yeast genome.

Integrated Microarray-based Tools for Detection of Genomic DNA Damage and Repair Mechanisms.

The genetic information contained within the DNA molecule is highly susceptible to chemical and physical insult, caused by both endogenous and exogenous sources that can generate in the order of thousands of lesions a day in each of our cells (Lindahl, Nature 362(6422):709-715, 1993). DNA damages interfere with DNA metabolic processes such as transcription and replication and can be potent inhibitors of cell division and gene expression. To combat these regular threats to genome stability, a host of DNA repair mechanisms have evolved. When DNA lesions are left unrepaired due to defects in the repair pathway, mutations can arise that may alter the genetic information of the cell. DNA repair is thus fundamental to genome stability and defects in all the major repair pathways can lead to cancer predisposition. Therefore, the ability to accurately measure DNA damage at a genomic scale and determine the level, position, and rates of removal by DNA repair can contribute greatly to our understanding of how DNA repair in chromatin is organized throughout the genome. For this reason, we developed the 3D-DIP-Chip protocol described in this chapter. Conducting such measurements has potential applications in a variety of other fields, such as genotoxicity testing and cancer treatment using DNA damage inducing chemotherapy. Being able to detect and measure genomic DNA damage and repair patterns in individuals following treatment with chemotherapy could enable personalized medicine by predicting response to therapy.