Date of Graduation
Master of Science in Mathematics
gene expression profiling, residual analysis, data transformation and normalization, split-plot experiment design, repeated-measures experiment design, hypothesis testing.
The purpose of this thesis is to analyze gene expression in grapevine under different treatments using a mixed linear statistical model. The experiment involves two Vitis species (V. vinifera Cabernet sauvignon and V. aestivalis Norton) and applies two different treatments to them (inoculation with Erysiphe necator conidiospores and mock inoculation). There are three biological replicates measured at each of the following six assigned time points: 0, 4, 8, 12, 24, and 48 hours. By setting up split-plot model for the data, statistical hypotheses concerning gene expressions, especially gene expressions in terms of treatment effect, are tested. The result of the analysis identify those genes expressed differently, and further experiments will indicate biological properties of those specific genes. After performing the analysis by using the split-plot model, discussions about another possible model, repeated measures design, is introduced at the end of this thesis in order to incorporate the potential biological property, such as diurnal pattern, into the modeling and analysis. By these series of analysis, certain genes are found with different expression, such as the gene with ID 000002 and ID 000004. This result will be useful in further biological researches.
© Yin Yin
Yin, Yin, "Vitis Gene Expression Profiling Using Mixed Models" (2015). MSU Graduate Theses. 1659.