Establishing optimum DNA annotation methods to investigate the impacts of flooding on microbial communities and functions
Year: 2016
Type: dissertation
Abstract: Environmental change will have significant impacts on microbial ecosystems. Microorganisms dominate most biogeochemical pathways, and environmental perturbations may alter these functions. Such functions include nutrient cycling, pollution abatement and greenhouse gas emission, and it is paramount that the impact of environmental change on ecosystems is understood. High throughput DNA sequencing provides a window into complex microbial communities and their functional potential, thus allowing us to empirically study how such communities respond to predicted future environments. There are, however, caveats and challenges associated with such technologies, particularly with converting billions of sequencing base calls into species and function counts. This thesis firstly quantifies the performances of sequence annotation tools and parameters using a simulated metagenome. It is found that tools differ in performance, and that parameter selection can significantly reduce annotation accuracy e.g. One Codex correctly annotated many sequences at the genus level, whereas MG-RAST RefSeq produced many false positive annotations. The results provide a guideline to quantitatively inform researchers about the impacts of certain choices on annotation performance, and show that some published studies may be drawing incorrect conclusions. \n \nThis thesis also investigates the impacts of increased flooding frequency and duration on soil microbial ecosystems, in line with predicted climate change. Increased frequency has significant impacts on biodiversity, community composition and potential function. SkyLine, a novel, continuous gas flux measuring system, was used to record CO2 and CH4 fluxes. Increased flooding duration significantly reduced CH4 oxidation and increased CO2 assimilation, with the combined global warming potential of these gasses reduced.
Author: Richard J. Randle‐Boggis
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
SDG: Climate action
Open Access status: green
OpenAlex ID: W2575318341