A study of computational methods to analyze gene expression data

The recent advent of new technologies has led to huge amounts of genomic data. With these data come new opportunities to understand biological cellular processes underlying hidden regulation mechanisms and to identify disease related biomarkers for informative diagnostics. However, extracting biological insights from the immense amounts of genomic data is a challenging task. Therefore, effective and efficient computational techniques are needed to analyze and interpret genomic data. In this thesis, novel computational methods are proposed to address such challenges: a Bayesian mixture model, an extended Bayesian mixture model, and an Eigen-brain approach. The Bayesian mixture framework involves integration of the Bayesian network and the Gaussian mixture model. Based on the proposed framework and its conjunction with K-means clustering and principal component analysis (PCA), biological insights are derived such as context specific/dependent relationships and nested structures within microarray where biological replicates are encapsulated. The Bayesian mixture framework is then extended to explore posterior distributions of network space by incorporating a Markov chain Monte Carlo (MCMC) model. The extended Bayesian mixture model summarizes the sampled network structures by extracting biologically meaningful features. Finally, an Eigen-brain approach is proposed to analyze in situ hybridization data for the identification of the cell-type specific genes, which can be useful for informative blood diagnostics. Computational results with region-based clustering reveals the critical evidence for the consistency with brain anatomical structure.

A decrease in dkk1, a Wnt inhibitor, contributes to placental and fetal lipid accumulation in an obesity-prone rat model

Placenta, as the sole transport mechanism between mother and fetus, links the maternal physical state and the immediate and life-long outcomes of the offspring. The present study examined the mechanisms behind the effect of maternal obesity on placental lipid accumulation and metabolism. Pregnant Obese Prone (OP) and Obese Resistant (OR) rat strains were fed a control diet throughout gestation. Placentas were collected on gestational d21 for analysis and frozen placental sections were analyzed for fat accumulation as well as β-Catenin and Dkk1 localization. Additionally, DKK1 was overexpressed in JEG3 trophoblast cells, followed by treatment with NEFA and Oil Red O stain quantification and mRNA analysis to determine the relationship between placental DKK1 and lipid accumulation. Maternal plasma and placental NEFA and TG were elevated in OP dams, and offspring of OP dams were smaller than OR. Placental Dkk1 mRNA content was 4-fold lower in OP placentas, and there was a significant increase in β-Catenin accumulation as well as mRNA content of fat transport and TG synthesis enzymes, including Ppar-delta, Fatp1, Fat/Cd36, Lipin1, and Lipin3. There was significant lipid accumulation within the decidual zones in OP but not OR placentas, and the thickness of the decidual and junctional zones was significantly smaller in OP than OR placentas. Overexpression of DKK1 in JEG3 cells decreased lipid accumulation and the mRNA content of PPAR-Delta, FATP1, FAT/CD36, LIPIN1, and LIPIN3. Our results indicate that Dkk1 may be regulating placental lipid metabolism through Wnt-mediated mechanisms. Additionally, recent studies have suggested that maternal obesity may also program early development of non-alcoholic fatty liver disease (NAFLD), rates of which have correlated with the increase in the obesity epidemic. In the current study, livers of OP offspring had significantly increased TG content (P<0.05) and lipid accumulation when compared to offspring of OR dams. Additionally, hepatic Dkk1 mRNA content was significantly decreased in OP livers when compared to OR (P<0.05), and treating H4IIECR rat hepatocyte cells with NEFA showed that Dkk1 mRNA was also decreased in NEFA-treated cells (P<0.05) that also had lipid accumulation. Chromatin Immunoprecipitation (ChIP) analysis of the Dkk1 promoter in fetal livers showed a pattern of histone modifications associated with decreased gene transcription in OP offspring, which agrees with our gene expression data. These results demonstrate that the hepatic Dkk1 gene is epigenetically regulated via histone modification in neonatal offspring in the current model of gestational obesity, and future studies will be needed to determine whether these changes contribute to excessive hepatic lipid accumulation in offspring of obese dams.