Plant-parasitic nematodes are the cause of devastating yield loss in vital agricultural crops around the world. Heterodera glycines, also referred to as soybean cyst nematode, is the main pathogen of Glycine max (soybean) causing more loss than all other pathogens of G. max combined. The resultant economic impact due to H. glycines in United States soybean production alone is estimated to account for an annual one-billion-dollar loss. Natural resistant genotypes have been found in trials to combat this pathogen. Of the resistant varieties identified, G. max[Peking/PI 548402] and G. max[PI 88788] are the major sources of resistance. Identification of genes expressed in the cells of which the nematode parasitizes, the syncytia, exclusively undergoing the resistant/incompatible reaction from the two major sources of resistance mentioned previously have identified a number of candidate genes presumed to function in defense to H. glycines parasitism. Prior to this work, success has been obtained by selection of a number of these candidate genes in functional analysis to show involvement in defense. This work is aimed at functionally identifying signaling components involved in the defense reaction. Reverse genetic studies of NON-RACE SPECIFIC DISEASE RESISTANCE 1 Glycine max homolog, Gm-NDR1-1, has confirmed a functional role in the defense to H. glycines to G. max. Gene expression studies revealed both effector-triggered immunity (ETI) and pattern-triggered immunity (PTI) components to be regulated by Gm-NDR1-1. Furthermore, induction in the heterologous expression of Gm-NDR1-1 in Gossypium hirsutum (cotton) suppressed Meloidogyne incognita parasitism. Harpin treatment has been evaluated due to the knowledge of NDR1’s capability of being harpin-induced (HIN1). Expression studies of the harpin treatment did in fact induce Gm-NDR1-1. The analysis further provides evidence of NDR1 role in defense by displaying the harpin-induced response of NDR1 in resistance to infection of Rotylenchulus reniformis. Receptors are known to function through signaling components in plant defense. Therefore, the conserved downstream signaling component of multiple diverse stimuli, mitogen-activated protein kinases (MAPKs) were functionally characterized in G. max for their role in resistance to H. glycines via the reverse genetic parasitism assays and evaluated to observe the effect on defense gene expression.

No description available.

Both microarray and RNA-seq technologies are powerful tools which are commonly used in differential expression (DE) analysis. Gene expression levels are compared across treatment groups to determine which genes are differentially expressed. With both technologies, filtering and normalization are important steps in data analysis. In this thesis, real datasets are used to compare current analysis methods of two-color microarray and RNA-seq experiments. A variety of filtering, normalization and statistical approaches are evaluated. The results of this study show that although there is still no widely accepted method for the analysis of these types of experiments, the method chosen can largely impact the number of genes that are declared to be differentially expressed.

No description available.

No description available.

No description available.

Reported here is the isolation and molecular characterization of two novel alleles of the DIP 1 gene; GE89 and GE77. As well, a third deletion of the DIP 1 gene, EY*4, isolated by our collaborators in France was characterized. PCR and sequencing analysis confirms all three alleles to be molecular deletions of the DIP 1 gene. However, in none of these cases is the entire gene excised. Also, immunohistochemistry of ovaries from each of these strains does not demonstrate a complete lack of DIPl protein expression in any of the deletion strains. Thus, it appears that some protein product is being formed in each case. However, it is not clear whether this protein is functional. An assay was also conducted to investigate a function for DIPl in mechanisms of epigenetic gene silencing. Although the findings of these experiments are incomplete, it appears that DIPl may play a functional role in heterochromatin formation and/or post-transcriptional gene silencing. Interestingly, appendage formation phenotypes were observed in the original P-element insertion line as well as a female sterility phenotype in the GE77 allele. Overall, DIP 1 is an interesting double stranded RNA binding protein. Newly isolated alleles of the DIP 1 gene will be useful tools for further investigation of the functional role of this gene. / Thesis / Master of Science (MSc)

DNA microarray technology makes it possible to analyze the expression levels of many thousands of genes simultaneously. One of the goals of microarray data analysis is to understand the multiple biological roles of genes and their interactions in complex biological processes. Genes with similar expression patterns are likely to share similar functions or biological processes. Therefore, analysis of changes in gene expression of a certain biological processes over time is of particular interest. Unsupervised clustering methods provide an efficient way of finding overall patterns and tendencies by clustering microarray gene expression data. The genes in the same cluster are regulated in a similar manner based on the assumption above. But traditional unsupervised clustering methods usually end up with clusters of genes with similar expression patterns but without interpretations describing the clusters in terms of gene functions or processes involved. In this project, some statistical techniques are applied to analyze the data set from microarray experiments of sporulation in yeast. These techniques include LOWESS data normalization, which is intended to remove the systematic variations from the data; a partitional clustering method, K-means, is used with initial centroids obtained from hierarchical clustering method of DIANA; the "gap statistic" technique is implemented to estimate the "optimal" number of clusters in the data set; and finally multiple hypothesis testing is used to determine whether biologically related genes are statistically over-represented in the gene clusters using the web query tool FatiGO. These methods are combined with graphical representation of cluster profile shape and colour maps of up and down regulation via heat maps. Application of these methods to a yeast sporulation time-course data set [Chu 𝘦𝘵 𝘢𝘭. 1998] demonstrates the utility of cluster analysis to such data sets and provides an automated method for including biological information about gene function and characteristics. / Thesis / Master of Science (MSc)

The missing heritability in genome-wide association studies (GWAS) is an intriguing open scientific problem which has attracted great recent interest. The interaction effects among risk factors, both genetic and environmental, are hypothesized to be one of the main missing heritability sources. Moreover, detection of multilocus interaction effect may also have great implications for revealing disease/biological mechanisms, for accurate risk prediction, personalized clinical management, and targeted drug design. However, current analysis of GWAS largely ignores interaction effects, partly due to the lack of tools that meet the statistical and computational challenges posed by taking into account interaction effects. Here, we propose a novel statistically-based framework (Significant Conditional Association) for systematically exploring, assessing significance, and detecting interaction effect. Further, our SCA work has also revealed new theoretical results and insights on interaction detection, as well as theoretical performance bounds. Using in silico data, we show that the new approach has detection power significantly better than that of peer methods, while controlling the running time within a permissible range. More importantly, we applied our methods on several real data sets, confirming well-validated interactions with more convincing evidence (generating smaller p-values and requiring fewer samples) than those obtained through conventional methods, eliminating inconsistent results in the original reports, and observing novel discoveries that are otherwise undetectable. The proposed methods provide a useful tool to mine new knowledge from existing GWAS and generate new hypotheses for further research. Microarray gene expression studies provide new opportunities for the molecular characterization of heterogeneous diseases. Multiclass gene selection is an imperative task for identifying phenotype-associated mechanistic genes and achieving accurate diagnostic classification. Most existing multiclass gene selection methods heavily rely on the direct extension of two-class gene selection methods. However, simple extensions of binary discriminant analysis to multiclass gene selection are suboptimal and not well-matched to the unique characteristics of the multi-category classification problem. We report a simpler and yet more accurate strategy than previous works for multicategory classification of heterogeneous diseases. Our method selects the union of one-versus-everyone phenotypic up-regulated genes (OVEPUGs) and matches this gene selection with a one-versus-rest support vector machine. Our approach provides even-handed gene resources for discriminating both neighboring and well-separated classes, and intends to assure the statistical reproducibility and biological plausibility of the selected genes. We evaluated the fold changes of OVEPUGs and found that only a small number of high-ranked genes were required to achieve superior accuracy for multicategory classification. We tested the proposed OVEPUG method on six real microarray gene expression data sets (five public benchmarks and one in-house data set) and two simulation data sets, observing significantly improved performance with lower error rates, fewer marker genes, and higher performance sustainability, as compared to several widely-adopted gene selection and classification methods. / Ph. D.

Thesis (M.A.)--Boston University / PLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at open-help@bu.edu. Thank you. / The gene Myh9 encodes non-muscle myosin heavy chain I lA, an essential podocyte cytoskeleton structural protein. Abnormalities in the MYH9 gene are associated with chronic kidney disease (common in people of African ancestry) and rare hereditary autosomal dominant syndromes. In the current study, preexisting heterozygous Myh9 knockout mice aged 9 and 17 months were investigated to assess the biological role of the gene Myh9 product, non-muscle myosin IIA, in kidney structure and function. The objective was to determine the effects of potentially decreased expression of Myh9 genetic alteration and the role of Myh9 in the pathogenesis of chronic kidney disease (especially focal segmental glomerulosclerosis), and to develop a model to further study Myh9- related kidney disorders. Our results demonstrated that deletion of one allele of Myh9 in 129/Sv mice had no effect on the kidney structure compared with wildtype mice despite a significant decrease in expression of Myh9 in the heterozygous mice. / 2999-01-01