The identification and characterization of inter- and intra-species genetic diversity derived from retrotransposons in humans

Retrotransposons, which used to be considered as “junk DNA”, have begun to reveal their immense value to genome evolution and human biology due to recent studies. They consist of at least ~45% of the human genome and are more or less the same in other mammalian genomes. Retrotransposon elements (REs) are known to affect the human genome through many different mechanisms, such as generating insertion mutations, genomic instability, and alteration in gene expression. Previous studies have suggested several RE subfamilies, such as Alu, L1, SVA and LTR, are currently active in the human genome, and they are an important source of genetic diversity between human and other primates, as well as among humans. Although several groups had used Retrotransposon Insertion Polymorphisms (RIPs) as markers in studying primate evolutionary history, no study specifically focused on identifying Human-Specific Retrotransposon Element (HS-RE) and their roles in human genome evolution. In this study, by computationally comparing the human genome to 4 primate genomes, we identified a total of 18,860 HS-REs, among which are 11,664 Alus, 4,887 L1s, 1,526 SVAs and 783 LTRs (222 full length entries), representing the largest and most comprehensive list of HS-REs generated to date. Together, these HS-REs contributed a total of 14.2Mb sequence increase from the inserted REs and Target Site Duplications (TSDs), 71.6Kb increase from transductions, and 268.2 Kb sequence deletion of from insertion-mediated deletion, leading to a net increase of ~14 Mb sequences to the human genome. Furthermore, we observed for the first time that Y chromosome might be a hot target for new retrotransposon insertions in general and particularly for LTRs. The data also allowed for the first time the survey of frequency of TE insertions inside other TEs in comparison with TE insertion into none-TE regions. In summary, our data suggest that retrotransposon elements have played a significant role in the evolution of Homo sapiens.

HUMAN GENOME VARIATIONS AND EVOLUTION WITH A FOCUS ON THE ANALYSIS OF TRANSPOSABLE ELEMENTS

Genome sequence varies in numerous ways among individuals although the gross architecture is fixed for all humans. Retrotransposons create one of the most abundant structural variants in the human genome and are divided in many families, with certain members in some families, e.g., L1, Alu, SVA, and HERV-K, remaining active for transposition. Along with other types of genomic variants, retrotransponson-derived variants contribute to the whole spectrum of genome variants in humans. With the advancement of sequencing techniques, many human genomes are being sequenced at the individual level, fueling the comparative research on these variants among individuals. In this thesis, the evolution and functional impact of structural variations is examined primarily focusing on retrotransposons in the context of human evolution. The thesis comprises of three different studies on the topics that are presented in three data chapters. First, the recent evolution of all human specific AluYb members, representing the second most active subfamily of Alus, was tracked to identify their source/master copy using a novel approach. All human-specific AluYb elements from the reference genome were extracted, aligned with one another to construct clusters of similar copies and each cluster was analyzed to generate the evolutionary relationship between the members of the cluster. The approach resulted in identification of one major driver copy of all human specific Yb8 and the source copy of the Yb9 lineage. Three new subfamilies within the AluYb family – Yb8a1, Yb10 and Yb11 were also identified, with Yb11 being the youngest and most polymorphic. Second, an attempt to construct a relation between transposable elements (TEs) and tandem repeats (TRs) was made at a genome-wide scale for the first time. Upon sequence comparison, positional cross-checking and other relevant analyses, it was observed that over 20% of all TRs are derived from TEs. This result established the first connection between these two types of repetitive elements, and extends our appreciation for the impact of TEs on genomes. Furthermore, only 6% of these TE-derived TRs follow the already postulated initiation and expansion mechanisms, suggesting that the others are likely to follow a yet-unidentified mechanism. Third, by taking a combination of multiple computational approaches involving all types of genetic variations published so far including transposable elements, the first whole genome sequence of the most recent common ancestor of all modern human populations that diverged into different populations around 125,000-100,000 years ago was constructed. The study shows that the current reference genome sequence is 8.89 million base pairs larger than our common ancestor’s genome, contributed by a whole spectrum of genetic mechanisms. The use of this ancestral reference genome to facilitate the analysis of personal genomes was demonstrated using an example genome and more insightful recent evolutionary analyses involving the Neanderthal genome. The three data chapters presented in this thesis conclude that the tandem repeats and transposable elements are not two entirely distinctly isolated elements as over 20% TRs are actually derived from TEs. Certain subfamilies of TEs themselves are still evolving with the generation of newer subfamilies. The evolutionary analyses of all TEs along with other genomic variants helped to construct the genome sequence of the most recent common ancestor to all modern human populations which provides a better alternative to human reference genome and can be a useful resource for the study of personal genomics, population genetics, human and primate evolution.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

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.

Inverse Illumination Design with Genetic Programming

Interior illumination is a complex problem involving numerous interacting factors. This research applies genetic programming towards problems in illumination design. The Radiance system is used for performing accurate illumination simulations. Radiance accounts for a number of important environmental factors, which we exploit during fitness evaluation. Illumination requirements include local illumination intensity from natural and artificial sources, colour, and uniformity. Evolved solutions incorporate design elements such as artificial lights, room materials, windows, and glass properties. A number of case studies are examined, including many-objective problems involving up to 7 illumination requirements, the design of a decorative wall of lights, and the creation of a stained-glass window for a large public space. Our results show the technical and creative possibilities of applying genetic programming to illumination design.