Development of a Microsatellite Library in \u3cem\u3eLolium Perenne\u3c/em\u3e

Lolium perenne, as one of the most important forage grasses of temperate regions, combines a number of very useful characteristics, e.g., good seedling establishment, with a low resistance to drought and limited winter hardiness. Trait selection and introgression can be greatly enhanced by the use of molecular markers in a genetic linkage map. The aim of this project was the generation of a genomic microsatellite library which when combined with microsatellites developed from a Genethresher database would give good genome coverage coupled to high levels of marker polymorphism

Biological Interactions in Grassland Soils and Productivity

This paper describes research on interactions between grassland plant species and soil microorganisms. Both parasitic and symbiotic microorganisms modify nutrient transfers between plants and soil. Experiments are described in which nematode infection of clover increased nitrogen transfer to companion ryegrass plants. Infection of clover enhanced activity of soil bacterial and fungal communities. Legume genotypes differing only in responses to symbionts (rhizobium and arbuscular mycorrhizal fungi) and pathogens are being developed for studies of gene expression during establishing and functional symbioses. Such plants can be used in experiments as defined perturbations that will provide information on the interactions and functions of symbiotic and pathogenic microorganisms. Such studies, related to field observations, may have value for defining biological attributes of sustainable grassland soil systems

Deciphering Diseases and Biological Targets for Environmental Chemicals using Toxicogenomics Networks

Exposure to environmental chemicals and drugs may have a negative effect on human health. A better understanding of the molecular mechanism of such compounds is needed to determine the risk. We present a high confidence human protein-protein association network built upon the integration of chemical toxicology and systems biology. This computational systems chemical biology model reveals uncharacterized connections between compounds and diseases, thus predicting which compounds may be risk factors for human health. Additionally, the network can be used to identify unexpected potential associations between chemicals and proteins. Examples are shown for chemicals associated with breast cancer, lung cancer and necrosis, and potential protein targets for di-ethylhexyl-phthalate, 2,3,7,8-tetrachlorodibenzo-p-dioxin, pirinixic acid and permethrine. The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types