@phdthesis {KNZ001216,
	title = {Ecological genomics of nematode responses to different bacterial environments},
	volume = {PhD Dissertation},
	year = {2008},
	school = {Kansas State University},
	type = {Ph.D. Thesis},
	address = {Manhattan, KS},
	abstract = {<p>Determining the genetic mechanisms involved in organismal response to environmental change is essential for understanding the effects of anthropogenic disturbance. The composition of the bacterial-feeding nematode community is an excellent biological indicator of disturbance, particularly in grassland ecosystems. We have previously shown that grassland soil nematodes are responsive to perturbations in the field including the addition of nitrogen fertilizer. We are interested in how this perturbation affects the microbial community and downstream effects on the next trophic level, the bacterial-feeding nematodes. To determine the effects of disturbance on soil bacterial communities we used massively parallel sequencing and found that chronic nitrogen addition on tallgrass prairie significantly impacts overall bacterial community diversity and the abundance of specific bacterial taxa. Because native soil nematodes lack well developed genomic tools, we employed Caenorhabditis elegans as a model for native soil nematode taxa and used transcriptional profiling to identify 204 candidate genes regulated in response to altered bacterial diets isolated from grassland soils. To biologically validate our results we used mutations that inactivate 21 of the identified genes and showed that most contribute to fitness or lifespan in a given bacterial environment. Although these bacteria may not be natural C. elegans food sources, this study aimed to show how changes in food source, as can occur in environmental disturbance, has large effects on gene expression and those genes whose expression are affected, contribute to fitness. Furthermore, we identified new functions for genes of unknown function as well as previously well-characterized genes, demonstrating the utility of this approach to further describe C. elegans genome. We also investigated the function of previously well-characterized C. elegans defense pathways in our grassland soil bacterial environments and found that some are environment specific. Additionally, we found that cuticular collagen genes are important for lifespan, and appear to function downstream of known defense pathways. Overall, our results suggest that anthropogenic disturbance in grasslands alters the most basal components of the soil food web, bacteria and bacterial-feeding nematodes through the genes they possess and how they are expressed, and resultant bottom-up effects could have profound consequences on ecosystem health and function.</p>},
	keywords = {LTER-KNZ, Caenorhabditis elegans, Ecological genomics, Innate immunity, Soil bacteria},
	url = {http://hdl.handle.net/2097/2750},
	author = {Coolon, J.D.}
}
@article {KNZ001199,
	title = {Experimentaldesign for two-color microarrays applied in a pre-existing split-plotexperiment},
	journal = {Statistical Applications in Genetics and Molecular Biology},
	volume = {6},
	year = {2007},
	abstract = {Microarray applications for the study of gene expression are becoming accessible for researchers in more and more systems. Applications from field or laboratory experiments are often complicated by the need to superimpose sample pairing for two-color arrays on experimental designs that may already be complex. For example, split-plot designs are commonly used in biological systems where experiments involve two types of treatments that are not readily applied at the same scale. We demonstrate how effects that are confounded with arrays can still be estimated when there is sufficient replication. To illustrate, we evaluate three methods of sample pairing superimposed on a split-plot design with two treatments, deriving the variance associated with parameter estimates for each. Design A has levels of the whole plot treatment paired on the same microarray within a level of the subplot treatment. Design B has crossed levels paired on the same microarray. Design C has levels of the treatment applied to subplots paired on the same microarray within a whole plot. Designs A and B have lower variance than design C for comparing the levels of the whole plot treatment. Designs B and C have lower variance for comparing the levels of the subplot treatment and design C has lower variance for comparing the levels of the subplot treatment within each level of the whole plot treatment. We provide SAS code for the analyses of variance discussed.},
	keywords = {LTER-KNZ, Ecological genomics, experimental design, gene expression, microarray analysis, split-plot design},
	doi = {10.2202/1544-6115.1245},
	url = {http://www.bepress.com/sagmb/vol6/iss1/art20},
	author = {Milliken, G.A. and Garrett, K.A. and Travers, S.E.}
}
