Identification of pathway and gene markers using enhanced directed random walk for multiclass cancer expression data

Cancer markers play a significant role in the diagnosis of the origin of cancers and in the detection of cancers from initial treatments. This is a challenging task owing to the heterogeneity nature of cancers. Identification of these markers could help in improving the survival rate of cancer patients, in which dedicated treatment can be provided according to the diagnosis or even prevention. Previous investigations show that the use of pathway topology information could help in the detection of cancer markers from gene expression. Such analysis reduces its complexity from thousands of genes to a few hundreds of pathways. However, most of the existing methods group different cancer subtypes into just disease samples, and consider all pathways contribute equally in the analysis process. Meanwhile, the interaction between multiple genes and the genes with missing edges has been ignored in several other methods, and hence could lead to the poor performance of the identification of cancer markers from gene expression. Thus, this research proposes enhanced directed random walk to identify pathway and gene markers for multiclass cancer gene expression data. Firstly, an improved pathway selection with analysis of variances (ANOVA) that enables the consideration of multiple cancer subtypes is performed, and subsequently the integration of k-mean clustering and average silhouette method in the directed random walk that considers the interaction of multiple genes is also conducted. The proposed methods are tested on benchmark gene expression datasets (breast, lung, and skin cancers) and biological pathways. The performance of the proposed methods is then measured and compared in terms of classification accuracy and area under the receiver operating characteristics curve (AUC). The results indicate that the proposed methods are able to identify a list of pathway and gene markers from the datasets with better classification accuracy and AUC. The proposed methods have improved the classification performance in the range of between 1% and 35% compared with existing methods. Cell cycle and p53 signaling pathway were found significantly associated with breast, lung, and skin cancers, while the cell cycle was highly enriched with squamous cell carcinoma and adenocarcinoma

The evolution of the mammal placenta — a computational approach to the identification and analysis of placenta-specific genes and microRNAs.

The presence of a placenta is an important synapomorphy that defines the mammal clade. From the fossil record we know that the first placental mammal lived approximately 125 million years ago, with the chorioallantoic placenta evolving not long after. In this thesis a set of 22 complete genomes from Eutherian, non-Eutherian and outgroup species are compared, the aim being to identify protein-coding and regulatory alterations that are likely to be implicated in the emergence of mammal placenta in the fossil record. To this end we have examined the roles played by positive selection and miRNA regulation in the evolution of the placenta. We have identified those genes that underwent functional shift uniquely in the ancestral placental mammal lineage and that are also heavily implicated in disorders of the placenta. Carrying out a thorough analysis of non-coding regions of the 22 genomes included in the study we identified a cohort of miRNAs that exist only in placental mammals. Many of the placenta related genes described above have multiple predicted “placenta-specific” miRNA binding sites. Together these results indicate a role for both adaptation in protein-coding regions and emergence of novel noncoding regulators in the origin and evolution of mammal placentation

Mechanisms Underlying Freeze Tolerance in the Spring Field Cricket, \u3cem\u3eGryllus veletis\u3c/em\u3e

Freeze tolerance has evolved repeatedly across insects, facilitating survival in low temperature environments. Internal ice formation poses several challenges, but the mechanisms that mitigate these challenges in freeze-tolerant insects are not well understood. To better understand how insects survive freezing, I describe a novel laboratory model, the spring field cricket Gryllus veletis (Orthoptera: Gryllidae). Following acclimation to six weeks of decreasing temperature and photoperiod (mimicking autumn), G. veletis juveniles becomes moderately freeze-tolerant, surviving freezing at -8 °C for up to one week, and surviving temperatures as low as -12 °C. Acclimation is associated with increased control of the temperature and location of ice formation, accumulation of cryoprotectant molecules (myo-inositol, proline, and trehalose) in hemolymph and fat body tissue, metabolic rate suppression, and differential expression of more than 3,000 genes in fat body tissue. To test cryoprotectant function, I increase their concentration in G. veletis hemolymph (via injection) and freeze isolated fat body tissue with exogenous cryoprotectants. I show that cryoprotectants improve survival of freeze-tolerant G. veletis (proline), their fat body cells (myo-inositol), or both (trehalose) under otherwise lethal conditions, suggesting limited functional overlap of these cryoprotectants. However, no cryoprotectant (alone or in combination) can confer freeze tolerance on freeze-intolerant G. veletis or their cells. During acclimation, G. veletis upregulates genes encoding cryoprotectant transmembrane transporters, antioxidants, and molecular chaperones, which may protect cells during freezing and thawing. In addition, acclimated G. veletis upregulates genes encoding lipid metabolism enzymes, and cytoskeletal proteins and their regulators, which I hypothesize promote membrane and cytoskeletal remodelling. To investigate the function of these genes in freeze tolerance, I develop a method to knock down gene expression in G. veletis using RNA interference. I knock down expression of three genes (encoding a cryoprotectant transporter, an antioxidant, and a cytoskeletal regulator), laying the ground work for others to test whether and how these genes contribute to mechanisms underlying freeze tolerance. By using a combination of descriptive and manipulative experiments in an appropriate laboratory model, I improve our understanding of the factors that contribute to insect freeze tolerance