Two separate phylogenetic studies were performed for two different taxonomic levels within Hymenoptera. The first study examined the utility of expressed sequence tags for resolving relationships among hymenopteran superfamilies. Transcripts were assembled from 14,000 sequenced clones for 6 disparate Hymenopteran taxa, averaging over 660 unique contigs per species. Orthology and gene determination were performed using modifications to a previously developed computerized pipeline and compared against annotated insect genomes. Sequences from additional taxa were added from public databases with a final dataset of 24 genes for 16 taxa. The concatenated dataset recovered a robust and well-supported topology; however, there was extreme incongruity among individual gene trees. Analyses of sequences indicated strong compositional and transition biases, particularly in the third codon positions. The use of filtered supernetworks aided visualization of the existing congruent phylogenetic signal that existed across the individual gene trees. Additionally, treeness triangle plots indicated a strong residual signal in several gene trees and across codon positions in the concatenated dataset. However, most analyses of the concatenated dataset recovered expected relationships, known from other independent analyses. Thus, ESTs provide a powerful source of information for phylogenetic analysis, but results are sensitive to low taxonomic sampling and missing data. The second study examined subfamilial relationships within the parasitoid family Braconidae, using over 4kb of sequence data for 139 taxa. Bayesian inference of the concatenated dataset recovered a robust phylogeny, particularly for early divergences within the family. There was strong evidence supporting two independent lineages within the family: one leading to the noncyclostomes and one leading to the cyclostomes. Ancestral state reconstructions were performed to test the theory of ectoparasitism as the ancestral condition for all taxa within the family. Results indicated an endoparasitic ancestor for the family and for the non-cyclostome lineage, with an early transition to ectoparasitism for the cyclostome lineage. However, reconstructions of some nodes were sensitive to outgroup coding and will also be impacted with increased biological knowledge.

Questions have been raised about the genomic complexity of the human genome, since it was reported that it only consisted of 32,000 genes. Alternative splicing is considered the explanation of the enormous difference between the number of genes and the number of proteins. Aligning expressed sequence tags (ESTs) to the genomic sequence has become a popular approach for gene prediction, revealing alternative splice variants. The aim in this thesis is to identify and analyse splice variants of the adhesion family of G protein-coupled receptors using EST data. 75% of the genes in the data set of 33 sequences were found to have a total of 51 splice variants. About half of the variants were considered functional.

<p>Questions have been raised about the genomic complexity of the human genome, since it was reported that it only consisted of 32,000 genes. Alternative splicing is considered the explanation of the enormous difference between the number of genes and the number of proteins. Aligning expressed sequence tags (ESTs) to the genomic sequence has become a popular approach for gene prediction, revealing alternative splice variants. The aim in this thesis is to identify and analyse splice variants of the adhesion family of G protein-coupled receptors using EST data. 75% of the genes in the data set of 33 sequences were found to have a total of 51 splice variants. About half of the variants were considered functional.</p>

This project focuses on the use of sponge genetic transcripts in the form of expressed sequence tags (ESTs) readily available in Genbank to search for novel genes using bioinformatics analysis tools. Marine sponge species are known to house a diversity of marine microbes and are known as the ‘living fossils’ of the animal kingdom because of the large number of ancient genes they house. Genomic mining can be a useful tool in discovering these orthologous genes. This study utilized the techniques of genomic mining of 11 previously described sponge species transcripts. The results of this study provide a better understanding of the genomic structure of the organisms studied by creating a more detailed genetic map and examining a specific environmental snapshot of the genes in each sponge. Novel methods for dissecting beneficial information from large scale data sets available in genomic libraries utilizing bioinformatics search tool MGRAST were examined. The results of this study indicate that sponges house numerous genes that are likely to be evolutionary predecessors of genes in higher eukaryotes. Support was also given to the notion that microbial communities play a role in metabolic pathways of sponges.