Genetic variation and evolutionary divergence within and among populations, species, and genera of the Cambarinae

Seven crayfish species from three genera of the subfamily Cambarinae were electrophoretically examined for genetic variation at a total of twenty-six loci. Polymorphism was detected primarily at three loci: Ao-2, Lap, and Pgi. The average heterozygosities over-all loci for each species were found to be very low when compared to most other invertebrate species that have been examined electrophoretically. With the exception of Cambarus bartoni, the interpopulation genetic identities are high within any given species. The average interspecific identities are somewhat lower and the average intergeneric identities are lower still. Populations, species and genera conform to the expected taxonomic progression. The two samples of ~ bartoni show high genetic similarity at only 50 percent of the loci compared. Locus by locus identity comparisons among species yield U-shaped distributions of genetic identities. Construction of a phylogenetic dendrogram using species mean genetic distances values shows that species grouping is in agreement with morphological taxonomy with the exception of the high similarity between Orconectespropinquus and Procambarus pictus. This high similarity suggests the possibility of a regulatory change between the two species. It appears that the low heterozygosities, high interpopulation genetic identities, and taxonomic mispositioning can all be explained on the basis of low mutation rates.

Genetic and Electrophysiological Correlates of Self-Regulation in Adolescence

Self-regulation is considered a powerful predictor of behavioral and mental health outcomes during adolescence and emerging adulthood. In this dissertation I address some electrophysiological and genetic correlates of this important skill set in a series of four studies. Across all studies event-related potentials (ERPs) were recorded as participants responded to tones presented in attended and unattended channels in an auditory selective attention task. In Study 1, examining these ERPs in relation to parental reports on the Behavior Rating Inventory of Executive Function (BRIEF) revealed that an early frontal positivity (EFP) elicited by to-be-ignored/unattended tones was larger in those with poorer self-regulation. As is traditionally found, N1 amplitudes were more negative for the to-be-attended rather than unattended tones. Additionally, N1 latencies to unattended tones correlated with parent-ratings on the BRIEF, where shorter latencies predicted better self-regulation. In Study 2 I tested a model of the associations between selfregulation scores and allelic variations in monoamine neurotransmitter genes, and their concurrent links to ERP markers of attentional control. Allelic variations in dopaminerelated genes predicted both my ERP markers and self-regulatory variables, and played a moderating role in the association between the two. In Study 3 I examined whether training in Integra Mindfulness Martial Arts, an intervention program which trains elements of self-regulation, would lead to improvement in ERP markers of attentional control and parent-report BRIEF scores in a group of adolescents with self-regulatory difficulties. I found that those in the treatment group amplified their processing of attended relative to unattended stimuli over time, and reduced their levels of problematic behaviour whereas those in the waitlist control group showed little to no change on both of these metrics. In Study 4 I examined potential associations between self-regulation and attentional control in a group of emerging adults. Both event-related spectral perturbations (ERSPs) and intertrial coherence (ITC) in the alpha and theta range predicted individual differences in self-regulation. Across the four studies I was able to conclude that real-world self-regulation is indeed associated with the neural markers of attentional control. Targeted interventions focusing on attentional control may improve self-regulation in those experiencing difficulties in this regard.

Disease-Gene Association Using Genetic Programming

As a result of mutation in genes, which is a simple change in our DNA, we will have undesirable phenotypes which are known as genetic diseases or disorders. These small changes, which happen frequently, can have extreme results. Understanding and identifying these changes and associating these mutated genes with genetic diseases can play an important role in our health, by making us able to find better diagnosis and therapeutic strategies for these genetic diseases. As a result of years of experiments, there is a vast amount of data regarding human genome and different genetic diseases that they still need to be processed properly to extract useful information. This work is an effort to analyze some useful datasets and to apply different techniques to associate genes with genetic diseases. Two genetic diseases were studied here: Parkinson’s disease and breast cancer. Using genetic programming, we analyzed the complex network around known disease genes of the aforementioned diseases, and based on that we generated a ranking for genes, based on their relevance to these diseases. In order to generate these rankings, centrality measures of all nodes in the complex network surrounding the known disease genes of the given genetic disease were calculated. Using genetic programming, all the nodes were assigned scores based on the similarity of their centrality measures to those of the known disease genes. Obtained results showed that this method is successful at finding these patterns in centrality measures and the highly ranked genes are worthy as good candidate disease genes for being studied. Using standard benchmark tests, we tested our approach against ENDEAVOUR and CIPHER - two well known disease gene ranking frameworks - and we obtained comparable results.