Human Promoter Recognition Based on Principal Component Analysis

This thesis presents an innovative human promoter recognition model HPR-PCA. Principal component analysis (PCA) is applied on context feature selection DNA sequences and the prediction network is built with the artificial neural network (ANN). A thorough literature review of all the relevant topics in the promoter prediction field is also provided. As the main technique of HPR-PCA, the application of PCA on feature selection is firstly developed. In order to find informative and discriminative features for effective classification, PCA is applied on the different n-mer promoter and exon combined frequency matrices, and principal components (PCs) of each matrix are generated to construct the new feature space. ANN built classifiers are used to test the discriminability of each feature space. Finally, the 3 and 5-mer feature matrix is selected as the context feature in this model. Two proposed schemes of HPR-PCA model are discussed and the implementations of sub-modules in each scheme are introduced. The context features selected by PCA are III used to build three promoter and non-promoter classifiers. CpG-island modules are embedded into models in different ways. In the comparison, Scheme I obtains better prediction results on two test sets so it is adopted as the model for HPR-PCA for further evaluation. Three existing promoter prediction systems are used to compare to HPR-PCA on three test sets including the chromosome 22 sequence. The performance of HPR-PCA is outstanding compared to the other four systems

Human Promoter Recognition Based on Principal Component Analysis

This thesis presents an innovative human promoter recognition model HPR-PCA. Principal component analysis (PCA) is applied on context feature selection DNA sequences and the prediction network is built with the artificial neural network (ANN). A thorough literature review of all the relevant topics in the promoter prediction field is also provided. As the main technique of HPR-PCA, the application of PCA on feature selection is firstly developed. In order to find informative and discriminative features for effective classification, PCA is applied on the different n-mer promoter and exon combined frequency matrices, and principal components (PCs) of each matrix are generated to construct the new feature space. ANN built classifiers are used to test the discriminability of each feature space. Finally, the 3 and 5-mer feature matrix is selected as the context feature in this model. Two proposed schemes of HPR-PCA model are discussed and the implementations of sub-modules in each scheme are introduced. The context features selected by PCA are III used to build three promoter and non-promoter classifiers. CpG-island modules are embedded into models in different ways. In the comparison, Scheme I obtains better prediction results on two test sets so it is adopted as the model for HPR-PCA for further evaluation. Three existing promoter prediction systems are used to compare to HPR-PCA on three test sets including the chromosome 22 sequence. The performance of HPR-PCA is outstanding compared to the other four systems

Isolation and functional characterization of Arabidopsis powdery mildew effector proteins

Plants are resistant to the majority of potential pathogenic microbes. Adapted pathogens can however overcome plant defense and induce susceptibility. The molecular processes underlying this adaptation are only partially understood. Obligate biotrophic pathogens, which require a living host for growth and reproduction, establish especially intimate relationships with their plant hosts. A crucial aspect of this lifestyle is the formation of a specialized infection structure termed the haustorium. Haustoria are believed to represent pivotal sites of nutrient uptake and deliver effectors, proteins that manipulate the host cell during infection to promote susceptibility. While the effector arsenal of pathogenic bacteria has been investigated intensively, the repertoires and host targets of fungal effectors are currently underexplored. The work presented here thus aims at characterizing virulence mechanisms employed by the obligate biotrophic Ascomycete Golovinomyces orontii, the causal agent of the powdery mildew disease in Arabidopsis thaliana (hereafter Arabidopsis). To this end, the haustorial transcriptome of G. orontii was obtained by pyrosequencing of a cDNA library generated from isolated haustorial complexes. Transcripts coding for gene products with roles in protein turnover, detoxification of reactive oxygen species and fungal pathogenesis were abundant, while surprisingly transcripts encoding presumptive nutrient transporters were not highly represented in the haustorial cDNA library. A substantial proportion (~38%) of transcripts encoding predicted secreted proteins comprised effector candidates. These candidates were cloned and found to frequently suppress induced plant cell death. A subset of effectors enhanced bacterial virulence and could suppress callose deposition, indicating a role in defense suppression. Transcript profiling of these effectors suggested their sequential delivery during pathogenesis. Furthermore, subcellular localization revealed diverse target compartments in the host. In a complementing approach, a large-scale yeast 2-hybrid (Y2H) assay was performed on the 84 cloned effector candidates and revealed convergence onto 61 potential host targets. These targets were enriched in transcription factors and components involved in development and cellular trafficking. Bimolecular fluorescence complementation assays confirmed the interaction of selected effectors with their host interactors. Finally, the Y2H targets of effectors were used to construct an integrated protein-protein interaction network of Arabidopsis and the three adapted pathogens Pseudomonas syringae (Psy), Hyaloperonospora arabidopsidis (Hpa) and G. orontii. This network revealed pathogen-specific as well as nine common host targets. These common targets are highly connected in the Arabidopsis cellular network. After the development of suitable quantitative methods, the important role of these common targets in the Arabidopsis immune response was validated by screening respective T-DNA insertion lines. In sum, my work supports the hypothesis that pytopathogenic microbes target hubs in the host cellular network to promote susceptibility. The effector targets identified will therefore form the basis of subsequent effector research in G. orontii

The proteins found at plasmodesmata and the interactions between them

Plasmodesmata are specialised membrane-lined pores that create cell-to-cell connections through the cell wall. This cytoplasmic and membrane continuity allows for communication and co-ordination between cells, a prerequisite for multicellularity. All land plants contain plasmodesmata derived from a single evolutionary event. Plasmodesmata are not passive conduits. Instead, the aperture of plasmodesmata is dynamically regulated by the deposition of a complex carbohydrate, callose. This controls the cell-to-cell flux through plasmodesmata. In this thesis, I explore the protein composition of plasmodesmata. I developed a plasmodesmata extraction protocol for mature plant tissue. This protocol is used to biochemically localise transiently expressed proteins to plasmodesmata in Nicotiana benthamiana. This technique is then extended to define the native plasmodesmal proteome of the bryophyte Physcomitrella patens. I used a comparative phyloproteomic approach to identify conserved protein families at plasmodesmata. This approach identified two classes of structural proteins, C2 lipid-binding proteins and tetraspanins, which may have been present in the plasmodesmata of the last common ancestor between land plants and algae. Secondly, I investigate interactions between PLASMODESMATA-LOCALISED PROTEINs (PDLPs) and other plasmodesmata proteins. PDLP overexpression leads to the misregulation of callose deposition, ultimately dwarfing Arabidopsis thaliana plants. I exploited this phenotype to find novel components in the PDLP-callose deposition pathway. Ultimately, I propose a common pathway downstream of PDLPs which is required for plasmodesmata callose deposition. Overall, the results herein offer candidate proteins that may be ancient components of plasmodesmata. These may have both structural and biochemical functions. I characterised one PDLP interactor, NDR1/HIN1-LIKE 3, and produced a list of other likely interactors, by comparing interaction data with A. thaliana plasmodesmal proteomes. An additional putative genetic interactor with PDLP1, KISS ME DEADLY 2, was identified by a forward genetic screen. This will guide the direction of future investigations

Research and Technology Objectives and Plans Summary (RTOPS)

A compilation of the summary portion of each of the Research and Technology Operating Plans (RTOP) used for management review and control of research currently in progress throughout NASA is presented along with citations and abstracts of the RTOPs. Four indexes are included: (1) subject; (2) technical monitor; (3) responsible NASA organization; and (4) RTOP number