Forest nurseries frequently face on-going issues with root-borne diseases caused by oomycetes. Typically diagnostics is based on soil baiting to isolate the organisms potentially associated with disease. This method, while good for detecting viable and active members of the soil, does have limitations including long processing time, seasonal variations and culture-based isolation bias. Next generation sequencing data provides outstanding opportunities for characterisation of microbial communities and diagnostics. This study aims to develop methods for characterisation of the prevalence of oomycetes such as Pythium and Phytophthora in nursery soils and to investigate the potential for NGS in downstream diagnostics applications. Soil samples were collected from a forest nursery and baiting was used to isolate species of oomycetes using selective media. ITS and Cox2 sequences were used to identify the isolates. Phytophthora cinnamomi, and Pythium mamillatum were the most commonly isolated species from three different nursery beds. Soil samples were also analysed to determine the pH, and total carbon, nitrogen and phosphorus levels, as well as performing DNA extraction for NGS analysis. The ability to detect taxa present but only in low numbers would be beneficial for nursery-based diagnostics, development of nursery hygiene practises and overall better detection of oomycetes from environmental samples. Thus we are currently assessing the ability of soil and root NGS analysis for diagnostic purposes.