Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

A comparative study of life history and gene flow in darters (Pisces: Percidae)

Gene flow, or the exchange of genes between populations, is important because it determines the evolutionary trajectory of a species, including the relative influences of genetic drift and natural selection in the process of population differentiation. Gene flow differs among species because of variation in dispersal capability and abundances across taxa, and historical forces related to geological or lineage history. Both history and ecology influence gene flow in potentially complicated ways, and accounting for their effects remains an important problem in evolutionary biology. This research is a comparative study of gene flow and life-history in a monophyletic group of stream fishes, the darters. As a first step in disentangling historical and ecological effects, I reconstructed the phylogenetic relationships of the study species from nucleotide sequences in the mtDNA control region. I then used this phylogeny and regional glaciation history to infer historical effects on life-history evolution and gene flow in 15 species of darters. Gene flow was estimated indirectly, using information from 20 resolvable and polymorphic allozyme loci. When I accounted for historical effects, comparisons across taxa revealed that gene flow rates were closely associated with differences in clutch sizes and reproductive investment patterns. I hypothesized that differences in larval dispersal among taxa explained this relationship. Results from a field study of larval drift were consistent with this hypothesis. Finally, I asked whether there was an interaction between species' ecology and genetic differentiation across biogeographically distinct regions. Information from allozymes and mtDNA sequences revealed that life history plays an important role in the magnitude of species divergence across biogeographic boundaries. These results suggested an important association between life histories and rates of speciation following an allopatric isolation event. This research, along with other studies from the literature, further illustrates the enormous potential of North American freshwater fishes as a system for studying speciation processes. ^

High natural gene expression variation in the reef-building coral Acropora millepora: potential for acclimative and adaptive plasticity

Background: Ecosystems worldwide are suffering the consequences of anthropogenic impact. The diverse ecosystem of coral reefs, for example, are globally threatened by increases in sea surface temperatures due to global warming. Studies to date have focused on determining genetic diversity, the sequence variability of genes in a species, as a proxy to estimate and predict the potential adaptive response of coral populations to environmental changes linked to climate changes. However, the examination of natural gene expression variation has received less attention. This variation has been implicated as an important factor in evolutionary processes, upon which natural selection can act. Results: We acclimatized coral nubbins from six colonies of the reef-building coral Acropora millepora to a common garden in Heron Island (Great Barrier Reef, GBR) for a period of four weeks to remove any site-specific environmental effects on the physiology of the coral nubbins. By using a cDNA microarray platform, we detected a high level of gene expression variation, with 17% (488) of the unigenes differentially expressed across coral nubbins of the six colonies (jsFDR-corrected, p < 0.01). Among the main categories of biological processes found differentially expressed were transport, translation, response to stimulus, oxidation-reduction processes, and apoptosis. We found that the transcriptional profiles did not correspond to the genotype of the colony characterized using either an intron of the carbonic anhydrase gene or microsatellite loci markers. Conclusion: Our results provide evidence of the high inter-colony variation in A. millepora at the transcriptomic level grown under a common garden and without a correspondence with genotypic identity. This finding brings to our attention the importance of taking into account natural variation between reef corals when assessing experimental gene expression differences. The high transcriptional variation detected in this study is interpreted and discussed within the context of adaptive potential and phenotypic plasticity of reef corals. Whether this variation will allow coral reefs to survive to current challenges remains unknown.