Graduate Thesis Or Dissertation

 

Development of Computational, Visualization, and Molecular Tools for Fungal and Oomycete Community Ecology 公开 Deposited

可下载的内容

下载PDF文件
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/h128nm65q

Header

Attribute Name LabelAttribute Values Label
Creator
Abstract
  • Oomycetes are an important group of organisms with a variety of ecological roles similar to fungi. Although many are well-studied plant pathogens known for their devastating effects on agricultural systems, most are little-studied saprobes and parasites of plants and animals in nearly every ecosystem on earth. The advent of affordable and high-throughput sequencing technologies have resulted in new opportunities for the study of microbial communities, including oomycetes, as well as new challenges associated with analyzing and visualizing the vast amount of data produced. This thesis describes new tools developed for the analysis and visualization of microbial communities, with an emphasis on oomycetes, and studies into the communities of oomycetes and fungi associated with Rhododendron. The widespread adoption of high-throughput molecular community ecology methods is making large data sets classified by taxonomic information common, but additional tools to analyze and visualize these data are needed. Taxonomic classifications are hierarchical, making them much more difficult to analyze compared to typical tabular data. There are many R packages that use taxonomic data to varying degrees but there is currently no cross-package standard for how this information is encoded and manipulated. We developed the R package taxa to provide a robust and flexible solution to storing and manipulating taxonomic data in R and any application-specific information associated with it. It is meant to be a foundation for other packages to build on, so that diverse packages dealing with taxonomic information can be integrated seamlessly. One package that is built on top of taxa is metacoder. Metacoder is an R package for plotting and manipulating data classified by a taxonomy, like the abundance data associated with metabarcoding. Its primary feature is the novel tree-based visualization called “heat trees” that is used to depict data for every taxon in a taxonomy using color and size. Heat-trees provide a more informative alternative to pie charts or stacked bar charts for visualizing communities. Metacoder also provides various functions to do common tasks in microbiome research with data stored in the taxmap format supplied by the taxa package. Both of these packages are open source, version controlled, have unit tests that help detect bugs, and include extensive documentation. Although metabarcoding methods for fungal and bacterial communities are well-developed at this point, no standard and reliable method for oomycete metabarcoding exists. Every currently proposed method for oomycete metabarcoding has at least one flaw; some produce too long an amplicon for Illumina sequencers, some target only a subset of oomycete diversity, some have unacceptable levels of non-target amplification, and some have technical difficulties that make the PCR reactions unreliable. We developed a new method for oomycete metabarcoding targeting the rps10 gene and an associated reference database. Compared to one of the more popular methods currently being used, our method has better taxonomic resolution, less non-target amplification, and a more reliable PCR reaction. A reference database of rps10 sequences for many genera of oomycetes was developed for use in assigning taxonomic classifications to metabarcoding data. Finally, a website was created to host the database that supports searching the database and conducting BLAST searches. Rhododendron is a major ornamental crop in the Pacific Northwest and is known to host both mycorrhizal symbionts and plant pathogens such as Phytophthora ramorum. The fungal and oomycete microbiome in the rhizosphere of rhododendrons from Oregon nurseries was sequenced and differences among cultivars, growth conditions, and nurseries were analyzed. Few oomycetes were found, but this might have been partially due to limitations of the metabarcoding method used. Fungal species found were mostly saprobes and mutualists. Nurseries that grew plants in containers and in-field had a significantly higher diversity of fungi than those that only grew plants in containers. Microbiome composition differed significantly among growth conditions and nurseries, but not among cultivars. This body of work provides novel insights into oomycete communities and novel tools for molecular community ecology that might be of broader interest.
Contributor
License Label
Resource Type
Degree Level
Degree Name
Degree Field
Degree Grantors
Graduation Year
Contributor Advisor
Contributor Committeemember
Academic Affiliation
权利声明
Funding Statement
  • This work was supported in part by funds from USDA Agricultural Research Service Projects 2027-22000-039-00 and 2072-22000-039-15-S to Niklaus Grunwald and an rOpenSci grant to Zachary Foster
  • This project was supported by funds from USDA-Agricultural Research Service CRIS Project 2072-22000-039-00D, 2072-22000-041-03-S, and 2072-22000-043-00-D the USDA-ARS Floriculture Nursery Initiative, the USDA-ARS NW Center for Nursery Crops, and the Oregon Department of Agriculture/Oregon Association of Nurseries (ODA-OAN) research programs.
Publisher
Peerreviewed
Language

关联

Relationships Parent Rows Label

Rows Empty Text

属于 Collection:

单件