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.

Global genome nucleotide excision repair is organized into domains that promote efficient DNA repair in chromatin.

The rates at which lesions are removed by DNA repair can vary widely throughout the genome, with important implications for genomic stability. To study this, we measured the distribution of nucleotide excision repair (NER) rates for UV-induced lesions throughout the budding yeast genome. By plotting these repair rates in relation to genes and their associated flanking sequences, we reveal that, in normal cells, genomic repair rates display a distinctive pattern, suggesting that DNA repair is highly organized within the genome. Furthermore, by comparing genome-wide DNA repair rates in wild-type cells and cells defective in the global genome-NER (GG-NER) subpathway, we establish how this alters the distribution of NER rates throughout the genome. We also examined the genomic locations of GG-NER factor binding to chromatin before and after UV irradiation, revealing that GG-NER is organized and initiated from specific genomic locations. At these sites, chromatin occupancy of the histone acetyl-transferase Gcn5 is controlled by the GG-NER complex, which regulates histone H3 acetylation and chromatin structure, thereby promoting efficient DNA repair of UV-induced lesions. Chromatin remodeling during the GG-NER process is therefore organized into these genomic domains. Importantly, loss of Gcn5 significantly alters the genomic distribution of NER rates; this has implications for the effects of chromatin modifiers on the distribution of mutations that arise throughout the genome.

Sandcastle: software for revealing latent information in multiple experimental ChIP-chip datasets via a novel normalisation procedure.

ChIP-chip is a microarray based technology for determining the genomic locations of chromatin bound factors of interest, such as proteins. Standard ChIP-chip analyses employ peak detection methodologies to generate lists of genomic binding sites. No previously published method exists to enable comparative analyses of enrichment levels derived from datasets examining different experimental conditions. This restricts the use of the technology to binary comparisons of presence or absence of features between datasets. Here we present the R package Sandcastle ­ Software for the Analysis and Normalisation of Data from ChIP-chip AssayS of Two or more Linked Experiments ­ which allows for comparative analyses of data from multiple experiments by normalising all datasets to a common background. Relative changes in binding levels between experimental datasets can thus be determined, enabling the extraction of latent information from ChIP-chip experiments. Novel enrichment detection and peak calling algorithms are also presented, with a range of graphical tools, which facilitate these analyses. The software and documentation are available for download from http://reedlab.cardiff.ac.uk/sandcastle.

Site-specific management of nematodes pitfalls and practicalities.

The greatest constraint to potato production in the United Kingdom (UK) is damage by the potato cyst nematodes (PCN) Globodera pallida and G. rostochiensis. Management of PCN depends heavily on nematicides, which are costly. Of all the inputs in UK agriculture, nematicides offer the largest potential cost savings from spatially variable application, and these savings would be accompanied by environmental benefits. We mapped PCN infestations in potato fields and monitored the changes in population density and distribution that occurred when susceptible potato crops were grown. The inverse relationship between population density before planting and multiplication rate of PCN makes it difficult to devise reliable spatial nematicide application procedures, especially when the pre-planting population density is just less than the detection threshold. Also, the spatial dependence found suggests that the coarse sampling grids used commercially are likely to produce misleading distribution maps.