Advances in high-throughput genomic technologies have facilitated the collection of DNA information for thousands of individuals, providing unprecedented opportunities to explore the genetic architecture of complex disease. One important finding has been that the majority of variants in the human genome are low in frequency or rare. It has been hypothesised that recent explosive growth of the human population afforded unexpectedly large amounts of rare variants with potentially deleterious effects, suggesting that rare variants may play a role in disease predisposition. But, importantly, rare variants embody a source of information through which we may learn more about our recent evolutionary history. In this thesis, I developed several statistical and computational methods to address problems associated with the analysis of rare variants and, foremost, to leverage the genealogical information they encode. First, one constraint in genome-wide association studies is that lower-frequency variants are not well captured by genotyping methods, but instead are predicted through imputation from a reference dataset. I developed the meta-imputation method to improve imputation accuracy by integrating genotype data from multiple, independent reference panels, which outperformed imputations from separate references in almost all comparisons (mean correlation with masked genotypes r²>0.9). I further demonstrated in simulated case-control studies that meta-imputation increased the statistical power to identify low-frequency variants of intermediate or high penetrance by 2.2-3.6%. Second, rare variants are likely to have originated recently through mutation and thereby sit on relatively long haplotype regions identical by descent (IBD). I developed a method that exploits rare variants as identifiers for shared haplotype segments around which the breakpoints of recombination are detected using non-probabilistic approaches. In coalescent simulations, I show that such breakpoints can be inferred with high accuracy (r²>0.99) around rare variants at frequencies <0.05%, using either haplotype or genotype data. Third, I show that technical error poses a major problem for the analysis of whole-genome sequencing or genotyping data, particularly for alleles below 0.05% frequency (false positive rate, FPR=0.1). I therefore propose a novel approach to infer IBD segments using a Hidden Markov Model (HMM) which operates on genotype data alone. I incorporated an empirical error model constructed from error rates I estimated in publicly available sequencing and genotyping datasets. The HMM was robust in presence of error in simulated data (r²>0.98) while nonprobabilistic methods failed (r²<0.02). Lastly, the age of an allele (the time since its creation through mutation) may provide clues about demographic processes that resulted in its observed frequency. I present a novel method to estimate (rare) allele age based on the inferred shared haplotype structure of the sample. The method operates in a Bayesian framework to infer pairwise coalescent times from which the age is estimated using a composite posterior approach. I show in simulated data that coalescent time can be inferred with high accuracy (rank correlation >0.91) which resulted in a likewise high accuracy for estimated age (>0.94). When applied to data from the 1000 Genomes Project, I show that estimated age distributions were overall conform with frequency-dependent expectations under neutrality, but where patterns of low frequency and old age may hint at signatures of selection at certain sites. Thus, this method may prove useful in the analysis of large cohorts when linked to biomedical phenotype data.

The population level bias towards right-handedness in humans implies left-hemisphere dominance for fine motor control. Left-handedness and reduced cerebral asymmetry have been linked to neurodevelopmental disorders such as dyslexia. Understanding the biology of these traits at a genetic level is crucial for understanding the relationship between handedness and neurodevelopmental disorders. Here I present genome-wide association study (GWAS) meta-analyses for both relative hand skill (handedness, n = 728) and reading-related traits (n = 548) in individuals with dyslexia. I uncovered a genome-wide significant association in an intron of PCSK6 associated with relative hand skill. PCSK6 is a protease that cleaves NODAL proprotein into an active form, and NODAL determines the development of left/right (LR) asymmetry in bilaterians. I performed pathway analyses of the GWAS data that revealed handedness is determined in part by the mechanisms that establish left/right (LR) asymmetry early in development, such as NODAL signalling and ciliogenesis. This finding replicated in a general population cohort unaffected with neurodevelopmental disorders (n = 2,666). A key stage in LR asymmetry development is the rotation of cilia that creates a leftward flow of NODAL. Candidate genes for dyslexia are involved in both neuronal migration and ciliogenesis. Ciliopathies can cause not only LR body asymmetry phenotypes, but also cerebral midline phenotypes such as an absent corpus callosum. Furthermore, I identified a genome-wide significant association with non-word reading located in an intron of MAP1B, a gene involved in neuronal migration that causes an absent corpus callosum when disrupted in mice. However, this finding did not replicate in two independent cohorts with dyslexia (n = 156 & 199), or in the general population cohort (n = 2,359). Though these cohorts had inadequate reading measures and poorly matched ascertainment for dyslexia. I also performed copy number variation (CNV) pathway and burden analyses of 920 individuals with dyslexia and 1,366 unselected controls, but did not find that rare CNVs play a major role in the etiology of dyslexia. Based on these results I propose that common variants in genes responsible for ciliogenesis and corpus callosum development influence traits such as handedness and reading ability.

Characterising and understanding factors that affect the rate of molecular evolution in proteins has played a major part in the development of evolutionary theory. The early analyses of amino acid substitutions stimulated the development of the neutral theory of molecular evolution, which later evolved into the nearly neutral theory. More recent work has lead to a better understanding of the role selection plays at the molecular level, but there is still limited understanding of how higher levels of protein organisation affect the way natural selection acts. The investigation of this question is the central aim of this thesis, which is addressed via the analysis of selective pressures in secondary protein structures in insects, mammals and fungi. The analyses for the first two groups were conducted using publically available datasets. To conduct the analyses in fungi, genome sequence data from the fungal genus Microbotryum (sequenced in our laboratory) was assembled and annotated, resulting in the development of a number of bioinformatics tools which are described here. The fungal, insect and mammalian datasets were interrogated with regard to a number of structural features, such as protein secondary structure, position of a site with regard to adaptively evolving sites, hydropathy and solvent-accessibility. These features were correlated with the signals of positive and purifying selection detected using phylogenetic maximum likelihood and Bayesian approaches. I conclude that all of the factors examined can have an effect on the rate of molecular evolution. In particular, disordered and hydrophilic regions of the protein are found to experience fewer physiochemical constraints and contain a higher proportion of adaptively evolving sites. It is also revealed that positively selected residues are ‘clustered’ together spatially, and these trends persist in the three taxa. Finally, I show that this variation in adaptive evolution is a result of both selective events and physiochemical constraint.

Evolution occurs and can be conceptualized along a spectrum, bounded on one extreme by the relationships between deep lineages – such as phyla, classes, and orders – and on the other by the molecular dynamics of operational taxonomic units within a species, defined as population genetics. The purpose of this dissertation was to better understand the evolutionary and population dynamics of crustaceans within the Gulf of Mexico. In the second chapter of my dissertation, I provide a guide to best phylogenetic practice while reviewing infraordinal relationships within Decapoda, including the promise held by next-generation sequencing (NGS) approaches such as Anchored Hybrid Enrichment. Chapter III is a phylogenetic study of species relationships within the economically important shrimp genus, Farfantepenaeus, targeting three mitochondrial genes and uncovering an intriguing pattern of latitudinal speciation. As the first inclusive molecular phylogeny of the genus, we find support for the newly described species F. isabelae, but a lack of support for the species status of F. notialis. Additionally, our results suggest the existence of two distinct subspecies of F. brasiliensis. Chapter IV investigates the relative impacts of habitat heterogeneity and the presence of a possible glacial refugium in determining population dynamics of the Giant Deep-Sea Isopod, Bathynomus giganteus in the northern Gulf of Mexico. Through hybrid population genetics/genomics analyses and Bayesian testing of population models, we find strong evidence for habitat heterogeneity determining population dynamics for this charismatic deep-sea invertebrate. Chapter V further investigates the role of environment in determining and maintaining genetic diversity and population connectivity, specifically focused on establishing biological baselines with which we can diagnose health and resilience of the Gulf of Mexico. This was accomplished through a comparative NGS population genomics study of three species of mesopelagic crustaceans: Acanthephyra purpurea, Systellaspis debilis, and Robustosergia robusta. While diversity and connectivity differs in each species, the comparative results bespeak the importance of access to the Gulf Loop Current in determining and maintaining population dynamics. Overall, my work significantly contributes to our knowledge of Crustacea at the phylogenetic- and population genetic-level.

Background: Direct-to-consumer (DTC) genetic tests are tests sold directly to consumers, normally without the involvement of healthcare professionals, which aim to provide consumers with their relative genetic risk for various complex diseases. Providers claim that this information will enable and encourage consumers to improve their health behaviour in order to reduce their likelihood of contracting diseases for which they are at an increased genetic risk. However, there are many criticisms and concerns about DTC genetic tests in the literature. Two common concerns are the lack of positive effects, and possible negative effects, that the information generated by the tests may have on consumers health behaviour and health anxiety, and the identified poor quality of information provision on the websites of providers of DTC genetic tests. Although the literature contains some research in these areas it is noticeably limited and occasionally contradictory. Aim and Methods: The aim of the research was to investigate the informational aspects of direct-to-consumer genetic tests, including the provision of information by the companies, consumers information needs and information-seeking behaviour and the effect of the information generated by the tests on health behaviour and health anxiety. The research consisted of three studies: a survey of 275 consumers and potential consumers of DTC genetic tests, in-depth email interviews with 36 consumers of DTC genetic tests and a content analysis of the information provided on all identified providers websites. Results: Positive or neutral changes in health behaviour were identified in a large minority of respondents who had been exposed to genetic risk information, along with the mechanisms by which the information prompted or contributed to change. A minority reported a change in health anxiety, mainly but not exclusively a decrease, with mechanisms again identified. Consumers reported a wide variety of information needs, the most common of which were information to do with the coverage and accuracy of the tests. The provision of information on providers websites varied considerably, both between and within providers, but was generally poor. However, most consumers used other sources alongside these websites, the most common of which was blogs. Conclusions: The results suggest that concerns about possible negative effects of the information generated by the tests are unfounded and that a large minority of consumers have improved health behaviour and decreased health anxiety after purchase. The results also suggest that concern about information provision on providers websites is justified; although this is mitigated by consumers general use of other sources alongside the websites, it is likely that a substantial number of consumers do not have access to enough information to give fully informed consent to the test.