The role of individual soil microorganisms changes over the course of a plant's life - microorganisms that have no discernable role at one developmental stage may affect the plant later in its growth. Traditional analysis of the soil microbiome, which has focused principally on the relative abundances (RA) of individual organisms, may be incomplete, as underlying differences in population size cannot be addressed. We conducted a metagenomic analysis of soil microorganisms from various maize (Zea mays L.) fields at two depths, accompanied by crop yield components, to provide insight into influences of edaphic microbes on maize productivity under commercial maize production systems in Missouri. This study assesses the influence of fungi and bacteria, not only in terms of RA, but also in their estimated absolute abundances (EAA), derived by combining the results of Illumina HiSeq sequencing data and phospholipid fatty acid abundance data. Significant interactions were identified between maize yield components and soil microbes at critical developmental states. Most interactions between fungi and yield components were negative, with notable exceptions. Bacterial interactions were more complex, with most interactions during early ear development identified as positive, and most interactions during tasseling identified as negative. In addition to the effects that microbial populations have on yield, plant populations reciprocally changed the microbial community. Plant developmental state was the greatest predictor of bacteria, with the microbial communities present during the active growing season being most similar to each other, whereas the preplant microbiome and post-reproductive microbiome being most similar to each other. Fungal communities were primarily dependent on location.
College and Department
Life Sciences; Plant and Wildlife Sciences
BYU ScholarsArchive Citation
Sullivan, Madsen Paul, "Effects of and Influences on Microbial Populations of Missouri Maize Fields" (2018). Theses and Dissertations. 7706.
soil microbiome, DNA sequencing, yield components, relative abundance, estimated absolute abundance, differential abundance