Date of Award
Master of Science
Plant and Soil Science
To our knowledge, this metagenomics study is the first of its kind to determine how cover crops and tillage management practices affect the soil microbiome in southern Illinois. Seven different cover crops were used over the course of two years from 2014 to 2015, and two different forms of tillage were used: Conventional Tillage (CT) and No-Tillage (NT). Four barcodes were used to generate libraries for the phylogenetic identification of fungi, bacteria, oomycetes, and fusaria: the ITS1, EF1a (Elongation Factor 1-a), and the V4 region of the 16s rRNA subunit. Targeted amplicon sequencing using 250 base pair Paired End (PE) reads yielded 14 x 106 base pair reads in total. Using these amplicons, we successfully unveiled the fungal and bacterial constituents of the studied field plots (database limitations considered) using the QIIME and NCBI Blast protocols. Specifically, this study had three goals 1) to determine if cover crops or tillage had a significant impact on the overall microbial diversity found in bulk soil samples taken from cover crop plots; 2) to determine if the incidence and abundance of individual bacterial or fungal taxa were affected by the cover crop or tillage treatment; 3) perform a bioinformatics methodology comparison for fungal identification using the ITS1 region between Qiime, and MEGAN protocols. Our results indicate many instances of cover crop or tillage interacting with one or more groupings of taxa. Significant whole community differences could be detected to the species (P=0.0335) and family (P=0.0001) taxonomic ranks of fungi using with the three most abundant families based on assigned reads being Mortierellaceae, Trichocomaceae, and Botryosphaeriaceae. Significant whole community interactions between tillage types and year at the level of phylum were observed between bacteria and archaea. Three main phyla constituting bacterial reads were Proteobacteria, Actinobacteria, and Acidobacteria. The primary driver in individual differences in bacterial populations appeared to be the year in which samples were taken either 2014 or 2015 (P=0.0001). This was attributed in part due to drastic fluctuations in weather from November 2014 to November 2015. Whole community differences and shifts could be observed based on cover crop down to the species level using both QIIME and NCBI BLAST protocols. The different dispersions and taxa found between cover crops imply that there is a relationship between certain organisms and the type of plant matter present. Tillage type, year, and cover crop were all found to have some degree of clustering based on reads taken from the four amplicons used. For comparison between NCBI and QIIME methodologies using the ITS1 region, the NCBI BLAST protocol provided the most overlap between taxa at the Order and Class taxonomic rankings. An upwards of 70% complementarity of taxa was found comparing the results after using the NCBI or the QIIME protocols. Whole community analysis using PERMANOVA revealed complementarity shifts based on treatment types when comparing both QIIME and NCBI protocols for taxonomic assignments visualized using PCoA plots. This comparison between the two methods for fungal community analysis using the ITS region, highlights the significant discrepancies as well as the complementarity of the two methodologies when analyzing fungal microbiomes.
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