TY - JOUR TI - Use of traditional and metagenomic methods to study fungal diversity in dogwood and switchgrass. DO - https://doi.org/doi:10.7282/T3DR2XGM PY - 2015 AB - Fungi are the second largest kingdom of eukaryotic life, composed of diverse and ecologically important organisms with pivotal roles and functions, such as decomposers, pathogens, and mutualistic symbionts. Fungal endophyte studies have increased rapidly over the past decade, using traditional culturing or by utilizing Next Generation Sequencing (NGS) to recover fastidious or rare taxa. Despite increasing interest in fungal endophytes, there is still an enormous amount of ecological diversity that remains poorly understood. In this dissertation, I explore the fungal endophyte biodiversity associated within two plant hosts (Cornus L. species) and (Panicum virgatum L.), create a NGS pipeline, facilitating comparison between traditional culturing method and culture-independent metagenomic method. The diversity and functions of fungal endophytes inhabiting leaves of woody plants in the temperate region are not well understood. I explored the fungal biodiversity in native Cornus species of North American and Japan using traditional culturing techniques. Samples were collected from regions with similar climate and comparison of fungi was done using two years of collection data. To evaluate the use of metagenomic analysis in assessing fungal diversity from enviromental samples, I first developed a pipeline to analyze Illumina metagenomic data for fungi. I created a mock fungal community in triplicate and ran it on an Illumina MiSeq. I also compared the results from Illumina metagenomic analysis with those from culture methods for switchgrass root samples. I found the developed pipeline yielded high reproducibility among the three mock communities and a high correlation with the traditional culture method for the environmental samples. These results suggest that the developed pipeline is suitable for fungal metagenomic analysis and can capture more diversity than the culture-based methods. However, there still are software limitations and problems in taxonomy that need further improvement. KW - Plant Biology KW - Fungi KW - Dogwoods KW - Switchgrass LA - eng ER -