Search

Bacterial genomes can be highly variable, with genetic material being frequently gained, lost, altered, and exchanged. Modern sequencing capabilities have enabled the sequencing of tens of thousands of genomes, and large-scale computational analysis can now be leveraged to explore how genetic variation is linked to virulence, niche adaptation, antibiotic resistance, and host transition events. Understanding the dynamics that underpin the movement of genetic material; the factors that influence gene gain and loss; and the associations between accessory genes and ecology is of importance to monitor pathogen emergence, develop new therapeutic strategies, and to steward antibiotic usage for the benefit of both humans and animals. This study began by exploring how the latest graph-based analysis and visualisation methods could be utilised in the analysis of the increasingly large and complex datasets available for key pathogen species. Using exemplar datasets from Staphylococcus aureus and Legionella pneumophila, we demonstrated the construction and analysis of genome- genome and gene-gene similarity networks, and gene synteny networks. This approach yields interactive and visually informative graphical representations of large-scale genomic data, allowing rapid insight and exploration of the bacterial pangenome, particularly when combined with information from existing analysis tools. A large-scale analysis was then conducted to investigate the pangenome diversity of S. aureus, a major human and animal pathogen. We first established a dataset of over 50,000 S. aureus genome sequences, then downsampled the best-represented 20 lineages. Through comparison of fundamental genome characteristics, we identified significant pseudogene accumulation in some ecologically restricted clones. We tested the extent to which lineages shared accessory genes, finding that certain groups are more likely to exchange genes, and some genes are independent of any lineage restriction. Consistent with this, we also identify unique combinations of known restriction-modification systems in each lineage. These data provide broad insight into the population-level exchange of genetic material between major S. aureus lineages. Finally, we applied our graph-based methods alongside standard large-scale analysis techniques to study the pangenome of S. aureus in the context of bovine mastitis, a major burden on the global dairy industry. Using a globally distributed and population-wide dataset of 4,841 genomes, we identified sets of accessory genes associated with the bovine host. Many of these genes were carried in different lineages, with limited sharing of such genes between key lineages. There was also limited evidence for any geographical impact on the accessory genome. Analysis of genome structure revealed that many bovine- associated genes are enriched in specific genomic locations, and further analysis of these regions revealed additional host-related gene combinations. Together, these data present evidence for multiple routes to bovine colonisation, and further elucidate the role of the accessory genome in host transition and colonisation. Overall, the studies presented in this thesis utilise the latest analysis and visualisation techniques to better understand the pangenome dynamics of S. aureus through the study of large-scale genome sequence datasets. In particular, we have investigated how the differing pangenome characteristics of distinct S. aureus lineages may relate to their diverse ecologies, especially in regard to adaptation to the bovine host. Our findings will be of relevance to monitoring the outbreaks of pathogenic lineages, the rise of antimicrobial resistance, and in determining the risk and management of emergent novel clones.

Sexually selected traits show large variation and rapid evolution across the aniaml kingdom. The genetic variation underlying sexually selected traits is often maintained despite apparent directional selection, with proposed explanations including sexually antagonistic selection or trade-offs with other life-history traits, such as survival. A key step in uncovering evolutionary drivers and constraints of these traits is to understand them at the genomci level. However, few empirical studies have attempted to investigate this aspect in the wild. Using long-term data from a population of red deer on the Isle of Rum, Scotland, this thesis both investigates the genomic basis of antler morphology, an important sexually selected trait, and genome-wide signals of sexually antagonistic selection through viability selection across the genome. Antlers are a form of sexual weaponry in male red deer and are assocaited with increased breeding success. I show that antler morphology is highly repeatable over an individual's lifetime, heritable and that almost all examined antler morphology traits are positively genetically correleated. The investigation of causative loci underlying antler morphology showed that it has a highly polygenic architecure, with some loci identified as having potential pleiotropic effects. The finding suggest that a large mutational target and genetic covariances among antler traits, in part maintained by pleiotropy, are lifely to contribute to the maintenance of genetic variation in antler morphology in this population. In species with two sexes, males and females largely share the same genome. However, due to differing biology and life histories, the sexes can have divergent itness optima for the same traits, thus resulting in sexually antagonistic selection, i.e., sexual conflict. Evidence for sex-specific transmission distortion was found in the deer, which pointed towards sexually divergent selection on parental gametes and prenatal viability. No genetic loci underlying differntial mortality between males and females at later life stages could be identified. Among the loci under sex-specific selection, several showed evidence of balancing selection could be linked to candidate genes. These results support onging sex-specific, but not sexually antagonistic. selection on parental haplotypes and offspring genotype during prenatal development, with potential trans-generational effects. These selection patterns likely contribute to the maintenance of genetic variance and thus eveolutionary potential in this population of red deer.

Idiopathic Pulmonary Fibrosis (IPF) is a rare lung disease characterised by inflammation and scarring of the alveoli. Although genetic and environmental factors have been reported in IPF, the biological processes underlying IPF development remain unclear. The largest genetic risk factor for IPF is a common variant in mucin gene 'MUC5B'. It is believed that IPF develops because of microinjury in the lung from for example cigarette smoke or viral infection. The Human leukocyte antigen (HLA) and Killer immunoglobulin-like receptor (KIR) molecules play a vital role in immune response against infection. HLA allele, 'HLA-DQB1*06:02' has evidence for association with fibrotic idiopathic interstitial pneumonias (fIIP) (including IPF). The HLA and KIR regions harbour complex variation and although there are links between IPF and viral infection, these regions have not been studied in depth. The aims of this thesis were to investigate the contribution of complex genetic variation in these regions to IPF susceptibility. The HLA-wide association meta-analysis identified a common novel signal near 'ZNRD1ASP' as associated with IPF susceptibility. Bioinformatic investigation highlighted associations with immunity and respiratory traits and differential expression of HLA and non-HLA genes. The 'HLA-DQB1*06:02' variant did not replicate in three independent IPF datasets suggesting that the originally reported association may have been driven by the inclusion of non-IPF fIIPs. The 'MUC5B*HLA' interaction analysis in IPF susceptibility did not present any novel signals but identified some suggestively significant signals that warrant further investigation. The KIR-wide association meta-analysis did not identify any novel signals and highlighted concerns in the KIR imputation. Overall, this thesis did not support the previously reported association of 'HLA-DQB1*06:02' with IPF susceptibility. Also, there was no evidence the regions exhibit a large genetic effect on IPF risk, however the analyses were limited by sample size and the imputation quality in the KIR region.

The human intelectin protein 1 (hItln1), coded by the ITLN1 gene, is expressed in the intestine. It recognizes and binds with multiple glycans that found solely on bacteria. A genome wide association study (GWAS) identified SNP, rs2274910, found in the ITLN1 gene that contributes to the risk of having Crohn's disease (CD). However, the variant functionally responsible for this association with CD has not yet been identified. Several copy number variants (CNV) overlapping ITLN1 have already been identified. However, a putative duplication and a deletion were not validated, suggesting these were false positive calls. Another deletion was confirmed to be an in-frame deletion found in the African population. However, it is rare, and it does not explain the GWAS signal found in Europeans. The C57BL/6, the reference mouse genome, has a single Itln gene, yet the 129S7 strain has 6 Itln genes. Thus, any variation within the Itln locus were not able to be identified (except Itln1). To investigate the variation of these Itln genes, we realigned Illumina short read sequence reads from several inbred mouse strains and wild-caught mice to the BAC contig spanning the highly repetitive Itln locus generated from a single 129S7 strain mouse. Using sequence read depth, a deletion in the C57BL/6 strains was confirmed and several distinct deletions were identified. Analysis of sequence variation also suggested polymorphic variants introducing early stop codons in particular Itln genes. Several studies demonstrated the ITLN1 gene shows the highest expression level in mesothelioma tissue samples, compared to normal tissues and it could therefore be a potential tumour biomarker for mesothelioma. To validate this, an expression analysis of ITLN1 was carried out on several mesothelioma tissues and correlated with clinical parameters in a small patient cohort. A significant relationship between the expression level of ITLN1 and the survival time after surgery was revealed.

In this thesis, I explore variation-aware algorithms for analyzing cancer genomes. The scientific community has extensively catalogued millions of mutations present in cancer cells. This information is rarely used during read alignment and variant calling because of a lack of algorithms for doing so. Rediscovering these variants wastes significant computational time and negatively impacts the sensitivity of detection, motivating the development of new solutions. The variants in malignant cells can arise from a number of genetic and environmental sources. In the years after the Chernobyl nuclear disaster, thousands of individuals in areas where radionuclides were deposited developed thyroid cancer. The excess relative risk of thyroid cancer has been estimated to be between fifteen and thirty fold higher following ¹³¹I exposure. In Chapter 2, I analyze more than 300 thyroid cancer cases from children and young adults exposed to ionizing radiation from increased levels of ¹³¹I originating from Chernobyl. I characterize the mutational landscape of these tumors across the variant size spectrum and compare it to sporadic thyroid cancer cases. I investigate possible signs of radiation exposure in the genome, especially large balanced structural variants and small indels. In Chapter 3, I develop methods for working with structural variants in variation graphs. Variation graphs have been shown to reduce reference bias and improve alignment to variant sites, though previous work has primarily focused on variants less than fifty base pairs in size. I describe the tradeoffs of various representations of large variants in the graph. I then develop several methods for genotyping and calling large variants in graphs. I construct graphs of both germline and somatic variation and describe how to work with these structures. I develop a method for fast structural variant genotyping using graph mappings and show that this significantly outperforms standard structural variant callers for certain types of variation. I describe how to locate structural variant mismapping signatures on variation graphs and how variation graphs can improve calling of structural variants. Lastly in Chapter 4, I demonstrate a new application of an alignment-free algorithm for genome analysis. I describe a MinHash toolkit for viral coinfection analysis and its application to Human Papillomavirus (HPV) samples. This toolkit is able to classify individual reads from multiple sequencing technologies and accurately detect clinically- relevant HPV coinfections. Finally, I dicuss how these approaches can be applied in other genomic analyses.

The advent of next generation sequencing technologies has had a major impact on inference methods for population genetics. For example, community ecology studies can now assess species interactions using population history parameters estimated from genomic scale data. Figs and their pollinating fig wasps are obligate mutualists thought to have coevolved for some 75 million years. This relationship, along with additional interactions with many species of non-pollinating fig wasps (NPFW), makes this system an excellent model for studying multi-trophic community interactions. A common way of investigating the population histories of a community's component species is to use genetic markers to estimate demographic parameters such as divergence times and effective population sizes. The extent to which histories are congruent gives insights into the way in which the community has assembled. Because of coalescent variance, using thousands of loci from the genomes of a small number of individuals gives more statistical power and more realistic estimates of population parameters than previous methods using just a handful of loci from many individuals. In this thesis, I use genomic data from eleven fig wasp species, which are associated with three fig species located along the east coast of Australia, to characterise community assembly in this system. The first results chapter describes the laboratory and bioinformatic protocols required to generate genomic data from individual wasps, and assesses the level of genetic variation present across populations using simple summaries. The second results chapter presents a detailed demographic analysis of the pollinating fig wasp, Pleistodontes nigriventris. The inferences were made using a likelihood modelling framework and the pairwise sequentially Markovian coalescent (PSMC) method. The final results chapter characterises community assembly by assessing congruence between the population histories inferred for eight fig wasp species. The population histories were inferred using a new composite likelihood modelling framework. I conclude by discussing the implications of the results presented along with potential future directions for the research carried out in this thesis.

The distribution of epidermal hairs (trichomes) is an important taxonomic character in the genus Antirrhinum. Most species in subsection Antirrhinum produce trichomes from lower internodes and leaves, then have bald stems and leaf blades after the third node and resume trichomes production again in the inflorescence (the "bald" phenotype). All species in subsection Kickxiella produce trichomes throughout development (the "hairy" phenotype). Populations of some species are polymorphic for trichome distribution-both bald and hairy individuals were observed in A. australe, A. graniticum, A. latifolium and A. meonanthum. Antirrhinum species also varied in trichome morphology. Five types were recognized according to length and the presence or absence of a secretory gland. Some types were present in all species and had similar distributions-for example short glandular trichomes were found on the adaxial midribs of all leaves in all species, and the lower leaves and internodes of all species shared longer glandular and long eglandular trichomes. However, the trichomes on leaf blades and stems at higher vegetative nodes of hairy species and in the inflorescences differed in morphology between species, suggesting that they are regulated differently from trichomes at more basal positions. Other species in the tribe Antirrhineae showed similar variation in trichome morphology and distribution to Antirrhinum, suggesting that the control of trichome development might be conserved within the tribe. To understand the genetic basis for variation in trichome distribution, a near-isogenic line (NIL) was generated by introducing regions of the genome of A. charidemi (hairy, subsection Kickxiella) into the genetic background of A. majus subsp. majus (bald, subsection Antirrhinum). One NIL segregated bald and hairy progeny, with the same trichome distributions as the parent species, in a ratio that suggested a single locus is responsible for the differences and baldness is dominant. The locus was named as Hairy and assumed to act as a suppressor of trichome formation. Progeny of the NIL were used in genome resequencing of bulked phenotype pools (Pool-seq) to map Hairy. No recombination between Hairy and a candidate gene (GRX1) from the Glutaredoxin gene family, was detected in the mapping population. In addition, RNA-seq revealed that GRX1 was expressed in bald parts of bald progeny, but not in the same parts of hairy progeny, and in situ hybridisation showed GRX1 RNA was restricted to epidermal cells, which form trichomes in the absence of Hairy activity. A virus-induced gene silencing (VIGS) method was also developed to test GRX1 function further. Reducing GRX1 activity allowed ectopic trichome formation in the bald NIL. Together, this evidence strongly supported Hairy being GRX1. To investigate evolution of Hairy and its relationship to variation in trichome distribution, the NIL was crossed to other Antirrhinum species. These allelism tests suggested that Hairy underlies variation in trichome distribution throughout the genus, with the exception of A. siculum, which has a bald phenotype but might lack activity of hairy and a gene needed for trichome formation. Hairy sequences were obtained from representative of 24 Antirrhinum species and two related species in the tribe Antirrhineae. The conserved trichome-suppressing function of the sequence from one of these species (Misopates orontium, bald phenotype) was confirmed by VIGS. Gene phylogenies combined with RNA expression analysis suggested that the ancestral Antirrhinum had a bald phenotype, that a single mutation could have given rise to the hairy alleles in the majority of Kickxiella species, that these alleles were also present in polymorphic populations in the other subsections, consistent with transfer from Kickxiella by hybridisation, and that multiple, independent mutations had been involved in parallel evolution of the hairy phenotype in a minority of Kickxiella species. Phylogenetic analysis of GRX proteins suggested that Hairy gained its trichome-repressing function relatively late in the evolutionary history of eudicots, after the Antirrhineae-Phrymoideae split, but before divergence of the lineages leading to Antirrhinum and Misopates. A yeast two-hybrid screen identified members of the TGA and HD-Zip IV transcription factors as potential substrates of the Hairy GRX.

Over the last ten years, genome-wide association studies (GWAS) have been used to identify genetic variants associated with many diseases as well as quantitative phenotypes, by exploiting naturally occurring genetic variation in large cohorts of individuals. More recently, the GWAS approach has also been applied to highthroughput RNA sequencing (RNA-seq) data in order to find loci associated with different levels of gene expression, called expression quantitative trait loci (eQTL). Because of the large amount of data that is required for such high-resolution eQTL studies, most of them have so far been carried out in humans, where the cost of data collection could be justified by a possible future impact in human health. However, due to the rapidly falling price of high-throughput sequencing it is now also becoming feasible to perform high-resolution eQTL studies in higher model organisms. This enables the study of gene regulation in biological contexts that have so far been beyond our reach for practical or ethical reasons, such as early embryonic development. Taking advantage of these new possibilities, we performed a high-resolution eQTL study on 80 inbred fruit fly lines from the Drosophila Genetic Reference Panel, which represent naturally occurring genetic variation in a wild population of Drosophila melanogaster. Using a 3′ Tag RNA-sequencing protocol we were able to estimate the level of expression both of genes as well as of different 3′ isoforms of the same gene. We estimated these expression levels for each line at three different stages of embryonic development, allowing us to not only improve our understanding of D. melanogaster gene regulation in general, but also investigate how gene regulation changes during development. In this thesis, I describe the processing of 3′ Tag-Seq data into both 3′ isoform expression levels and overall gene expression levels. Using these expression levels I call proximal eQTLs both common and specific to a single developmental stage with a multivariate linear mixed model approach while accounting for various confounding factors. I then investigate the properties of these eQTLs, such as their location or the gene categories enriched or depleted in eQTLs. Finally, I extend the proximal eQTL calling approach to distal variants to find gene regulatory mechanisms acting in trans. Taken together, this thesis describes the design, challenges and results of performing a multivariate eQTL study in a higher model organism and provides new insights into gene regulation in D. melanogaster during embryonic development.

Genome-wide association studies in multifactorial diseases have contributed to our understanding of genetic risk and defined specific disease-associated loci in particular populations. However, risk cannot be fully explained by genetics and evidence points to both genetic and environmental factors being important in causation and pathophysiology. The role of vitamin D in calcium homeostasis is well established. Over the last 30 years it has become clear that vitamin D has a wider role in physiology and disease, notably in autoimmune, cancer and infectious conditions. However, the molecular mechanisms and possible causal role of these associations are poorly understood. Here I propose that the role of vitamin D in immune and inflammatory responses is significant, that genetic variation partly determines the response to vitamin D and that integrative analysis can yield important insights for disease mechanisms. For this I investigate the relationship between vitamin D and genetic risk involving the immune system by focusing on multiple sclerosis and sepsis, conditions classically defined as autoimmune and inflammatory respectively. I describe data resolving genetic variation associated with autoimmune diseases in vitamin D receptor binding sites; the association to multiple sclerosis of a genetic variant lying within a VDR binding site; the correlation of plasma vitamin D with genotype and cell specific transcriptomes in healthy volunteers; and the extent of vitamin D deficiency in severe sepsis and septic shock, its association with survival, correlation with gene expression and use in sub-classification to identify patients at higher risk of death. The limitations of each study and future work are discussed. Integrating epidemiological and clinical observations with genetic and functional genomics techniques has the potential to reveal interactions in population specific disease susceptibility that may lead to an improved understanding of disease mechanisms and clinical translation. The work I present here bridges molecular analysis, candidate and genome- wide, with phenotypic observations that are important in our understanding of disease.

A major goal in evolutionary biology is to understand how ecological factors shape the phenotypic and genetic variation that we observe in natural populations and in this thesis I examine how rapid changes in temperature have influenced phenotypic and genetic variation in morphological and life history traits in long-term studies of great tits. In Chapter 1 I review what is known about the effects of environmental change on natural populations, and outline the quantitative genetic framework that is available to study genetic variation in natural populations. Much focus on the effects of climate change has concerned species’ phenology, far less attention has been given to other traits. In Chapter 2 I examine the effects changing environmental conditions have had on the proportion of females that produce second broods. Temperature operates mainly through indirect effects (such as food abundance) but may also have more direct effects. In Chapter 3 I show that over a 36 year period body size have declined in line with predictions from Bergmann’s rule and I explore the genetic basis of this decline and the environmental factors involved. Although we can learn much from population level responses, there is a great deal of additional information to be gained by studying between-individual responses. In Chapter 4 I therefore compare the multivariate pattern of between-individual variation in phenotypic plasticity and its genetic basis for laying date and clutch size, in two great tit populations. Environmental changes may also directly affect the expression of genetic variance as well as the strength of selection acting on a trait, and in Chapter 5 I show that, for laying date, the environment induces a positive covariance between strength of selection and the expression of additive genetic variance, something that may enhance the rate of adaptation. Finally, in Chapter 6 I discuss and summarise the wider implications of the findings from this thesis.

1. I have described a population of children and young adults with asthma in primary and secondary care, in terms of relevant history, medication use and exacerbations. 2. My thesis presents observations reported for the first time that asthmatic children and young adults homozygous for the Arg16 allele on the ß2 adrenergic receptor gene (ADRB2), on frequent doses of on demand short-acting ß2-agonists are at greater risk of asthma exacerbations.I have shown an increase in the risk of exacerbations per copy of Arg16 allele in children and young adults with asthma on the regular long-acting ß2-agonist salmeterol. 4. I have shown that there is an increase in risk of exacerbations per copy of Arg16 allele in children and young adults with asthma on frequent (once daily or more) as required doses of inhaled salbutamol. This effect is not observed on participants with asthma who are not exposed to ß2-agonist on a daily basis. 5. I have shown that the Arg16Arg variant status may be associated with worse airway obstruction, as measured by the FEV1/FVC ratio.6. I have shown that the individuals with FLG null alleles have a significantly increased risk of exacerbations requiring hospital admissions, courses of oral steroids, or experiencing school absences

The maintenance of cooperation and altruism in the face of manipulation by exploitative cheaters that reap the benefits of cooperative acts without paying the associated costs is a conundrum in evolutionary biology. Cheaters should spread through a population causing it to crash, yet cooperation is common. There are many models and theories that attempt to explain this apparent contradiction. The social amoeba Dictyostelium discoideum, like many microbial species has been used as a model organism to test these theories and to begin to understand the genetic mechanisms behind social behaviours. The aim of this PhD project is to quantify the interactions that occur between naturally-occurring genotypes during social competition in order to identify the types of cheating behaviours and to understand the evolutionary consequences of such behaviours. I first demonstrate that there is a social hierarchy of genotypes and that cheaters can increase their own fitness by increasing their own spore allocation or decreasing their partner's allocation the precise nature of which is dependent upon unique interactions between each competing pair. I also show that the outcome of social competition is dependent upon the physical environment where it can be significantly reduced, or even avoided by segregation of genotypes during development. Finally, it is demonstrated in a collaborative project that much of the observed social behaviour can be explained in terms of the production of and response to developmental signals.

Over the last 100 years sexual selection has advanced into a vast field of theoretical and empirical research. While Darwin’s idea of female preference being an integral mechanism of sexual selection is no longer debated, our understanding of female preference is still very limited. For example, we know little about the genetic variation in female preference, and the costs of preference over and above the costs of mating with particular male phenotypes. Additionally, while costs of mate choice are well documented, the benefits of mate choice and their implications are still debated. For example, controversy exists over the inevitability of good gene benefits and their capability to promote adaptive sexual selection. Furthermore, the adaptiveness of sexual selection itself is debated. Our understanding of the traits involved in mate choice is also far from complete. Here I investigated aspects of sexual selection in Drosophila simulans, employing a range of behavioural approaches along with artificial selection and environmental manipulations. The findings presented here indicate that female preference can evolve when directly selected on, and that preference itself is not particularly costly. There was also no conclusive evidence for the good genes benefits of mate choice in D. simulans. These benefits are considered crucial in promoting the adaptiveness of sexual selection, and although we found sexual selection to be adaptive under some test conditions it was not adaptive in other conditions. Our investigations into traits involved in mate choice established sex-specific genetic variation in cuticular hydrocarbons and the genetic architecture of this trait was found to sex-specific evolution of cuticular hydrocarbons under natural and sexual selection. Additionally, we found that a secondary sexual character, the sex combs was positively allometric – just like most signalling and weapon traits, and there was no association between trait fluctuating asymmetry and trait size. These findings collectively indicate that sexual selection in D. simulans is consistent with classical models of this process.

The research assessed the potential of developing a selective breeding programme for the UK rainbow trout industry. Levels of genetic variation at 12 microsatellite loci were first compared in seven different commercial strains. The Observed heterozygosity ranged from Ho = 48.1% in a gold rainbow trout strain (GTR) to Ho = 66.4% in a newly derived broodstock population constructed from a number of different sources (GIT). The Expected Heterozygosity (He) was highest in GIM1 (He= 79.5%) and lowest in the GTR strain (He = 56.9%). The Effective number of alleles (Mae) showed that the GIM1, GIM2, GIM3, and GIT strain (5.4; 5.2; 4.8; 4.2) were significantly more variable than the other strains and that GTR strain had the lowest value (2.5). There appears to be substantial genetic variability within the commercial United Kingdom rainbow trout strains surveyed in this study. This appears to be the case despite very different management histories and levels of record keeping. The strains appear to be genetically distinct (based on population genetic analyses), though the reasons for this remain unclear (and possibly unanswerable given the poor records kept by the different companies). The Glenwyllin farm strains (GIM) were chosen to form the base population for the project because of their high genetic variability, disease free status and because the farm produced around 20 million ova per year, so any genetic gains would have a widespread impact. The farm has an early (Strain A) and a late spawning (Strain B) and these were mated in a partial factorial design, 20 females and 20 neomales per strain (A & B) were chosen on the basis of maturity and gamete quality in November 2002 so that each male was crossed to 4 females (2 in the same strain and 2 in the other), a total of 160 families were created. All broodstock were biopsied to enable them to be genotyped. The families were reared separately up to the eyed stage at which point the eggs from each family were divided into three to generate three communal replicate populations. One of these was sent to a fingerling producer (Iwerne Spring) for ongrowing to fingerling size and formed the basis of a commercial production trial at Test Valley Trout farm (TVT) in Hampshire. When the fish reached an average weight of 5 g they were transferred from Iwerne Spring to TVT and 1500 were randomly selected, PIT tagged and biopsied to enable them to be assigned to their family using 11 multiplexed microsatellite loci. Parental assignment was based on exclusion (FAP) but the results were compared with another parental assignment based on likelihood (PAPA). Of the 1500 offspring (OIM) PIT tagged 1242 82.8% could be assigned to a single family utilizing different combinations of more than 6 loci (6 to 11). The growth of the 1500 OIM fish was tracked throughout the grow out period before they were finally harvested and fully processed. The results of OIM strain at the end of the trial period were mean weight of 415.5 g, and a mean length of 314.5 mm. The visual measurement of colour gave a mean flesh colour values of 26.01 on the 20-34 scale (SalmoFan™), and 11.0 with the colotimetry evaluation of colour (a*). The heritability results for the IOM strain were 43 ± 9% for weight, 42 ± 9% for gutted, and 28 ± 8% for length. The heritability estimates for the visual colour variables were 19 ± 7% and when using the colorimeter, the red chromaticity (a*) heritability was 14 ± 6%. Therefore, the heritability results of the IOM strain indicate that there are opportunities of substantial and rapid improvement of the growth rate and flesh colour traits. Also no line effects were observed or indications of non-additive genetic variation. In contrast to these last results, the overall survival of the GIM strain from the time of the physical tagging with PIT until harvest was 52.8%, and survival heritability was extremely low, 3 ± 2%, hardly significant.

Background: Pain is common in cancer patients, particularly in the advanced stage of the disease when the prevalence is estimated to be more than 70%, contributing to poor physical and emotional well‐being. Despite the presence of increased attention regarding cancer research and pain management the ability of clinicians to predict and manage cancer patients’ pain has not changed significantly. A recent evidence‐based review into the pain associated polymorphisms and opioids stated that the clinical benefits of opioid analgesics are dependent on substantial variations in the responses to opioids, insufficient drug dosing and/or a high rate of adverse events. This wide interindividual variability in sensitivity to opioids leads to unpredictable clinical responses to opioid treatment and adverse events. This is troublesome to clinicians given the narrow therapeutic window in which treatment may be beneficial or harmful to the patient. Method: The aim of this study was to investigate how selected SNPs in KCNJ6, ARRB2 and BDNF affect fentanyl dose requirements and response. This was a sub‐study of a prospective, open label, dose individualisation study on the use of fentanyl for pain management in advanced cancer. Adult in‐patients or outpatients of the oncology and palliative care services of Mater Adults Hospital in Brisbane were eligible for inclusion. Fentanyl was administered via the transdermal route with the dose titrated according to clinical need by the palliative care specialists. Participant characteristics including age, height, weight, type of cancer, liver and renal function, and fentanyl doses were recorded. Participants were required to rate their pain on a numerical rating scale from 0 to 10, with a score of 0 representing “no pain” and 10 representing “pain as bad as you can imagine” using the Brief Pain Inventory questionnaire. Pain scores were recorded each time blood and saliva was collected for the dose individualisation study. Genotyping was conducted using pyrosequencing for KCNJ6 and BDNF, and TaqMan assays were used for ARRB2. Regression analysis was used to examine whether outcomes were dependent on nongenetic patient characteristics. Deviation of Hardy‐Weinberg equilibrium was determined by comparing the observed genotype frequencies with the expected values using the chisquare test. The Kruskal‐Wallis H test was used to determine whether genotypes were associated with fentanyl dose or pain score. 2 analysis was used to determine significant associations for low (3.0/10) pain score and low (50 mcg/hr), when outcomes were categorised. Results: Fifty‐six adults with advanced cancer receiving transdermal fentanyl were recruited to the study. The median fentanyl dose was 50 mcg/hr, with a range of 12 to 300 mcg/hr, and the mean pain score was 3.0/10.0 with a standard deviation of 2.3. No association was found between patient characteristics, fentanyl dose, and pain score. As each of the P values for age, gender, cancer diagnosis, BMI, BSA, weight, liver function, kidney function, and blood cell counts were above that of 0.05. KCNJ6 rs2070995, ARRB2 (rs34230287, rs3786047, rs1045280, rs2036657), and BDNF (rs7934165, rs10835210, rs1491850) were determined to have no association in relation to dose and pain score. Conclusion: There is so little understanding in the effect of genetics on the pharmacodynamic effect of medications in advanced cancer pain. While clinical studies in palliative care are challenging, we encourage continued research in the area to provide evidence to support clinicians in achieving better treatment outcomes and quality of life for their patients. In the case of this study, no association of SNPs in KCNJ6, ARRB2 and BDNF on fentanyl dose requirements or response was identified. However, any contribution to the evidence base will allow for continued development of gene‐drug dosing guidelines provided by the Clinical Pharmacogenetics Implementation Consortium (CPIC), thereby expediting the translation of research findings to clinical practice. This coupled with increasing technological advancement of low‐cost genetic mapping that is accessible to the general public, and the accessibility of patient electronic records, will allow gene‐based prescription of medications to become a reality.

Structural variants (SVs), defined as any rearrangement of ≥50 DNA nucleotides, are a major source of human genetic diversity that determines the content, order, and orientation of the six billion nucleotides in every human genome. Despite their outsized impact on genome biology and human phenotypes, surprisingly little is known about SVs compared to better-studied classes of genetic variation, such as single-nucleotide variants. In this dissertation, I examine the patterns and consequences of SVs in the global human population by aggregating and analyzing large genomic datasets. In Chapter 1, I review the foundational properties of SVs that were established at the outset of my dissertation research. In Chapter 2, I present GATK-SV, a scalable computational pipeline for jointly discovering and genotyping SVs in whole-genome sequencing (WGS) of large cohorts, which we subsequently applied 14,891 individuals from five major continental populations to construct a new reference catalog of SVs as part of the Genome Aggregation Database. In Chapter 3, I recap four parallel efforts to probe the roles of SVs in human disease, including a meta-analysis of rare deletions and duplications in nearly one-million individuals across 54 disorders. In Chapter 4, I investigate the predicted consequences of SVs on coding and noncoding functional loci and document how natural selection shapes the distributions of these SVs in human populations. I conclude by proposing how extensions of this dissertation may eventually enable genome-wide maps of evolutionary constraint against changes in DNA copy number—also known as dosage sensitivity—at kilobase resolution, present a prototype computational framework for dosage sensitivity mapping, and describe ongoing genomic data aggregation efforts towards this goal. Taken collectively, this work sheds new light on a variety of topics in contemporary human genomics, which I hope will provide value to the basic, translational, and clinical research communities.

Sequence variation in enhancers, a class of cis-regulatory elements (CREs) that control cell type-specific gene transcription, contributes significantly to phenotypic variation within human populations, including the risk of developing diseases. Enhancers are short DNA sequences (~200 bp) composed of multiple binding sites (~4-10 bp each) for transcription factors (TFs). The transcriptional regulatory activity of an enhancer is encoded by the type, number, and distribution of TF-binding sites present. Active enhancers in different cell types generally lack shared, stereotypical sequence features and TF binding preferences are often not fully captured from in vitro binding assays. Therefore, the sequence determinants of TF binding to enhancers and the relationship between TF binding and enhancer activity in the native genomic context remain poorly understood. Hence, it remains difficult to reliably predict in silico the effect of any given sequence variant on enhancer function without a direct sequence-to-function relationship for well-defined cell or tissue types. To address this gap in knowledge, I generated allele-specific maps of TF binding and enhancer activity in fibroblasts derived from a panel of F1-hybrid mice, which contain a higher frequency of sequence variants than observed between maternal and paternal alleles of human cells. I identified thousands of enhancers that exhibit significant differences in TF binding and/or enhancer activity between alleles and I used these loci to define features of sequence variants that are most likely to impact enhancer function. My dataset demonstrates a critical role for AP-1 TFs at many fibroblast enhancers, reveals a hierarchical relationship between AP-1 and TEAD TFs, and delineates the nature of sequence variants that contribute to AP-1 binding. These data described herein represents one of the most comprehensive assessments to date on the impact of sequence variation on enhancer function in chromatin, with implications for pinpointing functional cis-regulatory variation in human populations.

As the planet changes at an alarming rate, there is a great need to understand why some populations are better equipped to rapidly adapt to their new environment than others. Many factors contribute, but populations are ultimately limited in their pace by their genetic makeup—they either have variants that allow them to survive or they do not. But, in the race to adapt, all sources of variation are not equal, and standing genetic variation is theorized to be of the most benefit in contributing to rapid adaptation. Here I explore the role of standing variation, both in a population’s ability to adapt at a rapid pace and in the potential long term evolutionary consequences that occur as a result. My work confirms expectations that increased standing variation in a population allows for a faster rate of adaptation, but although these populations are able to succeed in the short term, but this achievement comes at a significant cost to long term viability. All populations, across all experiments, that utilize standing variation as the genetic basis for rapid adaptation lose the ability to undergo sexual recombination, and therefore lose an important mechanism for maintaining variation in the long term. I begin by determining how the amount of standing variation present in a population correlates to the timing and rate of a successful adaptive response to a stressful environment. I assess how this result is intertwined with loss of sex and explore the mechanism for that loss. Then, I explore how the dynamics of the system change if the environmental shift occurs gradually rather than as a dramatic climactic event. Finally, I compare the variety of evolutionary strategies that develop in populations that began with standing variation versus mutation as their genetic substrate and evaluate their potential for success in the long term. Taken together, these results present a different picture of the role of standing variation than might be assumed. It does indeed allow for rapid adaptation, but the increased degree of genetic variation is not an evolutionary panacea and may send populations down evolutionary trajectories that are short-sighted.

Research has previously shown that Rumex (Polygonaceae) species introduced to New Zealand have multiple potential drivers behind their success, such as phenotypic plasticity, enemy release, and niche shift. However, it is not known whether these changes were caused by post-introduction evolution, or what other drivers could explain the success of these agricultural weeds. I combined demo-genetic traits and processes to assess how hybridisation and introgression, genetic differentiation, and breeding system contribute to the invasiveness of three introduced Rumex species. I compared plants from the species’ native (Europe, mainly the UK) and introduced (New Zealand) range and assessed whether the success is more likely due to prior adaptation or post-introduction evolution. Ploidy is associated with increased invasiveness, and if a species has multiple geo-cytotypes, higher ploidies are often found within the introduced range. Similarly, self-compatibility can help introduced populations to counter mate limitation and mixed mating can introduce new alleles to populations. I found no differences in genome sizes or chromosome numbers between plants from the two ranges using flow cytometry and manual chromosome counts. In addition, a comparison between bagged and unbagged Rumex conglomeratus plants showed no consequences from selfing, indicating mixed mating strategies. Surprisingly, the overall seed viability was lower for provenances from the introduced range compared to the native range. Hybridisation and introgression can increase genetic variation and help with adaptation to new environments. In a field survey, hybrid plants were found in New Zealand. However, the majority were likely first-generation hybrids, making introgression an unlikely driver behind the invasiveness. In addition, the parent species co-occurrence was lower in New Zealand compared to the UK. Lastly, genetic differentiation can indicate the origin of the introduction, as well as how likely a post-introduction evolution is a driver behind the invasiveness. A minimal differentiation was revealed by genotyping-by-sequencing both within but also between the native and introduced ranges. The population genetic analyses suggest that the UK is a likely origin for these species but admixture from elsewhere was also found. This would have likely helped the introduced populations to maintain comparable level of genetic variation to the native populations. As limited differences were found between the native and introduced populations, the investigated traits and processes are unlikely to explain the invasiveness in New Zealand. Rather, the success of these species is likely caused by prior adaptation. In addition, as these species are primarily agricultural weeds within both provenances, anthropogenically induced adaptation to invade is likely the main driver behind the success of these species. This method of adaptation, likely coupled with jack-of-all-trades genotypes, have allowed the species to thrive in manmade habitats, all around the globe. Thus, similar weeds within these habitats need to be carefully monitored to prevent further invasions in the future.

Climate change is having profound effects on species distributions. However, much less is understood about how climate change may alter the distribution of genetic variation within species across landscapes. Maintaining genetic diversity within populations is essential for the survival of species in the face of rapid climatic changes, but importantly, losses of genetic variation will also have significant consequences on entire ecosystems. The objective of this dissertation is to understand how genetic variation in a riparian cottonwood species, Populus angustifolia, affects mass and energy exchange between the land and atmosphere across ~1700 km of latitude of the western United States, and how genetic variation may respond to climate change. Specifically, I examine: (1) the potential for large-scale land-atmosphere feedbacks in hydrologic processes driven by geographic differences in plant population traits; (2) the extent to which including genetic population structure into species distribution models alters predictions of suitable conditions and geographic distributions; and (3) the extent to which genetic trait variation in bud break phenology is predicted to change in response to novel climatic conditions. The findings of this dissertation suggest that populations from landscapes with different hydrologic histories will differ in their ability to maintain favorable water balance with changing atmospheric demands for water; that species-range distribution models that do not include genetic information provide overly-broad projections of suitable conditions on the landscape compared to models that include population genetic structure; and, that a net loss of trait variation in future climates is predicted across all populations of P. angustifolia, with the trailing-edge population is predicted to lose the most. These ideas have broad implications for predicting population-level ecological and evolutionary responses to climate change as decreases to genetic variation reduce a species’ ability to adapt to novel conditions and can have profound effects on ecosystem processes like resource cycling (e.g., water, carbon, nitrogen) and on species interactions within ecological communities.

Comprised of more than 160 species, Viburnum is the largest genus in the Viburnaceae (formerly Adoxaceae) alongside Adoxa and Sambucus. The native range of Viburnum species spans much of the Northern Hemisphere and extends into the mountains of South America and Southeastern Asia. Their wide geographic range has made Viburnum particularly interesting to phylogeographers and phylogeneticists. This diverse genus is also horticulturally valuable with varying traits such as fragrance, fruit color, and bud and inflorescence form. There is sufficient morphological diversity in the genus for there to be more than 70 species and intraspecific hybrids in cultivation, and in 2017, viburnums generated $23.2 million in wholesale and retail sales in the U.S. alone. Viburnums’ horticultural value is in large part due to their ornamental qualities varying throughout the year, but also lasting much of the year. Typically, molecular markers are developed only for single species when breeding and assessing genetic diversity. This is despite many markers displaying cross-transferability to other closely related species and genera. Microsatellite markers, also known as simple sequence repeats (SSRs), were previously developed from three of the four large clades of Viburnum (Valvatotinus, Laminotinus, and Porphyrotinus). For markers to span the entire genus, genomic SSRs (gSSRs) were developed from V. farreri, which is a member of the East Asian center of diversity, the fourth large clade (Crenotinus), and a popular ornamental in the United States. The four sets of markers (a total of 49) were then tested on 46 Viburnum species and five closely related species in the rest of the Viburnaceae and the Caprifoliaceae. The markers developed here in conjunction with previous markers eliminate the need to develop markers for each species in this massive genus and closely related taxa. These SSRs are suitable and ready to use for breeding, exploring genetic diversity, and delimiting species and cultivars in Viburnum and possibly select species in the rest of the Viburnaceae and the Caprifoliaceae.

Evidence from Genome Wide Association Studies (GWAS) has provided us with insights into human phenotypes by identifying genetic variation statistically associated with diseases and complex traits. However, the functional consequences of these genetic variants remain unknown in many cases, especially for those in the non-coding regions of the human genome. My dissertation focuses on single nucleotide polymorphisms (SNPs) as the most common genetic variation type. I define some SNPs as regulatory SNPs that can alter the transcription factor binding affinities within the DNA sequences of regulatory elements. This change affects downstream gene expression and plays a role in disease progression and trait development. Characterizing genome-wide regulatory variants is particularly challenging because the gene regulatory network is dynamic across various cell types and environmental conditions. In addition to the DNA sequence context, the gene regulatory network relies on epigenetic factors, such as chromatin accessibility, histone modification, and chromatin looping. In this dissertation, I applied computational approaches to predict regulatory variants by incorporating sequence information and functional genomics annotations from various high-throughput assays. In chapter 2, I developed a computation tool, SURF, to prioritize the regulatory variants within promoters and enhancers with clinical relevance. These variants were validated by massively parallel reporter assays and used as an unbiased test set in CAGI5 “Regulation Saturation” challenge. My algorithm achieved the best performance in this challenge compared to other participant groups. In chapter 3, I extended SURF to TURF, a computational tool to predict tissue-specific functions of regulatory variants and provide a more robust prediction on genome-wide non-coding regions. By leveraging tissue-specific genomic annotations of tissues from the same organ, I also calculated TURF organ-specific scores covering most ENCODE project organs. Many of the GWAS traits showed enrichment of regulatory variants prioritized by TURF scores in their relevant organs, which indicates that these regulatory variants are likely to be involved in the trait developments and can be a valuable source for future studies. In chapter 4, to enable the quick annotation on non-coding variants for the scientific community, I designed some major updates to an online tool, RegulomeDB. With the user's input of query variant, RegulomeDB returns the evidence from diverse functional genomics assays that overlaps the variant’s position, displayed with interactive charts and a genome browser view. The new probabilistic score derived from SURF was also integrated into the query system. To further provide functional hypotheses to putative regulatory variants, I finally explored the pipeline to assign their target genes with evidence from eQTL studies and Hi-C experiments. Together, my dissertation developed computational tools for broad community use on prioritizing and assigning target genes to regulatory variants in non-coding regions of the human genome.

In this dissertation, I investigated biological mechanisms by which reef-building corals (Orbicella faveolata, Acropora millepora, and Acropora hyacinthus) can mitigate the effects of projected increases in sea surface temperatures. Utilizing genomic techniques, I provide new insights about coral biology relevant for predicting responses to climate change. Here I present three major findings: 1) The Caribbean coral Orbicella faveolata has a segregated germline that prevents inheritance of somatic mutations 2) Molecular adaptation of corals collected from a high-temperature reef strongly depends on the type of symbionts that they host 3) Co-recruitment of relatives via cohesive dispersal can lead to emergence of genetic subdivisions amidst an otherwise panmictic coral population.

Tuberculosis (TB) disease, caused by Mycobacterium tuberculosis (Mtb) infection, affects millions of people across the world annually. The best tool for controlling TB in individual patients and preventing transmission in populations is combination antibiotic therapy. Six months of treatment with four first-line antibiotics is sufficient to cure the majority of patients. However, the efficacy of this therapy has been undermined by the evolution of drug resistant Mtb strains, which are able to grow in the presence of clinically utilized antibiotics. The chromosomal mutations that cause drug resistance in Mtb have largely been identified, allowing for rapid genotype-based diagnosis of drug resistance and the selection of appropriate therapy. Nevertheless, even patients with apparent drug susceptible Mtb have a range of outcomes. Some patients appear durably cured with 4 months of therapy while for others even 6 months is not sufficient to prevent relapse after treatment is completed. Studies of Mtb clinical isolates have found that there are a wider range of antibiotic phenotypes than are captured by standard clinical drug resistance assays, which could help explain this phenomenon. In parallel, genomic association studies have identified mutations that are enriched in drug resistant strains without appearing to cause resistance. We are interested in connecting these sets of observations via functional analysis of clinically prevalent, drug resistance-associated genetic variation in Mtb. In Chapter 2, we identify genetic variants that are associated with isoniazid resistance in a cohort of 549 strains from China. From these associations, we select prpR for which we construct a series of isogenic mutants. We find prpR mutations confer conditional multidrug tolerance that is readily measured in infection models of TB, but is not captured by standard drug susceptibility testing. In Chapter 3, we focus on genetic associations with resistance to a second-line antibiotic, ethionamide. Here we find the bacterial monooxygenase Rv0565c is a novel activator of ethionamide and mutations reduce its activity. As one out of three known activators, however, mutation of Rv0565c causes a relatively small shift in drug resistance which has not been previously recognized. In Chapter 4, we characterize the functional impact of single-nucleotide polymorphisms in dnaA using precision genome editing of the native locus of dnaA. We find clinically prevalent variants in dnaA increase resistance to the first-line therapeutic isoniazid. As with Rv0565c, the small magnitude of this effect has prevented prior identification of dnaA as contributing to resistance. Together these studies indicate that prevalent, resistance-associated genetic variation can encode drug tolerance or low-level resistance phenotypes. In Chapter 5, we discuss the further work that will help clarify the effect of these mutations on treatment outcomes in patients. We also explore how these methods could be further refined and expanded to address bacterial variation beyond antibiotic responses.

White clover (Trifolium repens L.) is an integral component of mixed pastures in New Zealand temperate agriculture, providing quality feed and a sustainable source of fixed nitrogen (N) through its symbiosis with strains of Rhizobium leguminosarum bv. trifolii. While there has been much focus on identifying and applying Rhizobium strain inoculants for improved N-fixation, there has been less attention on identifying and exploiting plant genetic factors to develop cultivars that can consistently form effective Rhizobium symbioses. The complexity of the clover-Rhizobium interaction makes for a challenging but valuable breeding target which represents an important strategy for increasing the sustainability of New Zealand’s pasture-based agriculture. In this study, the phenotypic variation of N-fixation capacity across individuals from 17 white clover cultivars, including a wild ecotype (‘Tienshan’) and a T. repens × T. uniflorum interspecific hybrid cultivar (‘AberLasting’), released between 1920 and 2003 and representing three leaf size classes were investigated. N-fixation capacity was assessed by growing plants in vermiculite/McKnight’s solution, where N was provided either by an effective commercial strain (TA1) or partially effective (S12N10) N-fixing Rhizobium strain or supplied mineral N (positive control). Symbiotic traits recorded after 35 days of growth included Shoot and Root dry matter (DM), root to shoot ratio (RSR), and symbiotic potential (SP) which is the proportion of biomass generated through symbiosis relative to plants grown with mineral N. There were significant differences or interactions between and among cultivars and Rhizobium strains. Furthermore, there was a high degree of variability in N-fixation capacities of individuals within the cultivar populations. Multivariate analysis clustered cultivars across an N-availability gradient and identified some cultivars that performed equally well (‘S100’) or equally poorly (‘Barblanca’) or had marked differential performance (‘Dutch’ and ‘Tienshan’) across effective or partially effective strains. In order to derive key quantitative genetic parameters which could be utilised for improving N-fixation in white clover, a genetically structured F3 population of half-sibling (HS) families (n = 120) underwent the same screening assay as in the previous study, with N being provided either by the commerical strain TA1 or supplied mineral N (positive control). Shoot and Root DM, SP as well as RSR were measured and differed considerably among HS families, with 44% of families forming sub-optimal symbioses with TA1. Best linear unbiased predictor (BLUP) means for all traits were derived for each HS family and used to estimate significant additive variation and narrow-sense heritabilities, which ranged from 0.05 (RSR) to 0.33 (Shoot DM). This indicated there is additive genetic variability that can be exploited for improving the symbiotic interactions. These estimates also enabled the genetic gain for the examined traits to be predicted at 20%, 10% and 5% selection pressures while also identifying 24 elite HS families that could be utilised in future selection validation work. The feasibility of applying genomic selection (GS) for improving genetic gain in white clover-Rhizobium associations using a HS family structure was investigated. The phenotypes of 118 HS families and a genomic relationship matrix derived from ~155,000 genotyping-by-sequencing single nucleotide polymorphism markers of the HS families’ corresponding maternal parents were used for genomic prediction (GP) using five models. Cross-validation predictive ability (PA) of symbiotic traits ranged from 0.14 (Root SP) to 0.36 when two traits (Shoot DM and Shoot SP) were combined into a multi-trait Smith-Hazel selection index. The PAs of the five GP models were similar across all traits and therefore the computationally efficient GP model Kinship using GBS with depth adjustment-GBLUP (KGD-GBLUP) was selected. Different parameters influencing PA were assessed and identified a minimum of 94 HS families using a training: test combination of 80: 20%, respectively, over 100 iterations was sufficient for generating PAs in this population. This work provides an ideal foundation to assess genomic selection for breeding white clover germplasm for improved N-fixation and productivity by undertaking among-(using phenotype) and-within (using GS) HS family selection. To determine relationships between performance with pure strains and soil communities, a subset of cultivars (n = 4) and HS families (n = 4) screened previously for differential N-fixation capacities were assessed with two pure strains (TA1 and S12N10) and five soil rhizobia extracts. Differences in the N-fixation capacities with pure strains reflected those from the previous experiments. While there was considerable variation in symbiotic traits among populations with the five soil extracts, performance with the effective Rhizobium strain TA1 was often indicative of performance with the soil communities. Using multivariate pattern analysis, distinct clusters among the white clover populations were identified, which appeared to be driven by the number and appearance of nodules. In summary, the findings of this thesis will provide valuable information for facilitating the improvement of N-fixation in white clover in future breeding efforts.

Common leopard (Panthera pardus Linnaeus, 1758) populations are in serious decline throughout the range of the species. The leopard is considered a vulnerable species globally and is critically endangered in Pakistan, although there is little scientific information available from this area. The leopard shows morphological and genetic variation across its species range, which has resulted in the classification of nine different subspecies globally. Despite extensive research to clarify its genetic structure across the geographic range, the leopard in South Asia, particularly in Pakistan, has had very little sampling carried out, resulting in a limited understanding of the local subspecies in this region. The knowledge gap of the leopard’s genetic structure and its current geographical distribution has impeded the conservation of leopards in Pakistan. This study was carried out between 2016-2019 to better understand the species status, ecology, and the conservation of leopards in northern Pakistan. We investigated the presence, distribution and abundance of leopards in northern Pakistan. Leopard presence was confirmed in the Swat, Dir and Margalla Hills regions, despite local wildlife departments considering them extinct in these areas.Leopard abundance in Ayubia National Park, the Guzara Forest, and the Murree Forest Divisions were assessed via camera-trapping and track surveys. Camera-trapping identified 18 individual leopards (eleven males and seven females). The estimated leopard density from the capture-recapture analysis was 9.5 individuals/100 km², in 2017, and 4.5 individuals/100 km², in 2018. The Pakistani leopard subspecies status was confirmed using mitochondrial NADH-5 gene sequence variation. Three distinct haplotypes were identified: haplotype A, from 23 samples, was identical to two sequences previously identified as Panthera pardus fusca (Accession number: AY035274.1) and P. p. orientalis (Accession number: HQ185550.1); haplotype B, from eleven samples, had identical sequences to P. p. saxicolor; and haplotype C, from a single Pakistani sample, was not the same as any previously identified haplotype. Haplotype diversity among the Pakistani samples was based on three segregation sites with nucleotide variations ranging between 0.003 and 0.006 (the average numbers of nucleotide differences per site). Leopard haplotypes were found in sympatry in northern Pakistan. Morphological traits were used in 3D geometric morphometrics to characterise variations in leopard skulls, particularly with regard to subspecies status. Procrustes shape analysis indicated that variation among individual skulls, crania, and mandibles were not determined by gender, diet or collection location. Multivariate analysis confirmed that gender (P = 0.6) and location (P = 0.6) did not account for any morphological differences. We also observed patterns with a slight variation at the tip of the coronoid process on mandibles, after 3D morphing and species averaging by combining the two surfaces using IDAV landmark. This variation did not match the putative subspecies. This study is a useful addition to knowledge about leopard distributions and status in a region (Pakistan) with little current data. Pakistan hosts a contact zone for subspecies P. p. fusca (near threatened) and P. p. saxicolor (endangered). There is, potentially, an undescribed leopard population in the region. The overlapping distribution of these two subspecies provides the impetus to extend full protection to leopards beyond the limits of regional parks and reserves, to the whole Pakistani territory.

The myostatin gene (MSTN), alternatively known as the growth and differentiation factor 8 gene (GDF8), encodes the myostatin protein (MSTN). It has pleiotropic effects, and it is expressed in skeletal muscle as well as the mammary gland. Its expression has been associated with increased skeletal muscle mass, and decreased adipogenesis as a result of the reduced secretion of leptin. Leptin is a product of the obese (ob) gene. It is a 16-kDa protein hormone mainly secreted from white adipose tissue and it regulates feed intake, energy partitioning and metabolism, as well as lactogenesis. Using Polymerase Chain Reaction (PCR) amplification, coupled with Single Strand Conformation Polymorphism (SSCP) analyses and subsequent nucleotide sequencing, an extended region of the bovine MSTN and leptin (LEP) genes were investigated for genetic variations in a variety of cattle breeds from New Zealand and Nigeria. Five regions of MSTN were investigated. These included exons 1, 2 and 3, and parts of introns 1 and 2; and they were studied in 883 cattle of varied breeds from New Zealand (Hereford, Angus, Charolais, Simmental, Red Poll, South Devon, Shorthorn, Murray Grey, cross-bred Holstein-Friesian × Jersey cattle (NZ HF × J-cross, or Kiwicross™) and from Nigeria (Sokoto Gudali, Red Bororo, White Fulani and cross bred Holstein-Friesian × White Fulani). Eight PCR-SSCP banding patterns were observed in the intron 1 region amplified, four in the intron 2 region amplified and none in the exon regions. A total of seventeen single-nucleotide substitutions (nine in intron 1 and eight in a region spanning the intron 2 - exon 3 boundary) and one nucleotide deletion were detected. For the leptin gene (LEP), three regions (intron 1/exon 2, part of intron 2 and the entire exon 3) were examined in 657 cattle from a variety of breeds farmed in New Zealand and Nigeria. These included NZ Hereford, Angus, Shorthorn, and NZ HF × J-cross cows; and the Nigerian Sokoto Gudali, Red Bororo, White Fulani, and cross-bred Holstein-Friesian × White Fulani cattle. Four PCR-SSCP patterns were detected in the intron 1/exon 2 region with four nucleotide sequence variations, three patterns in intron 2 with three sequence variations, and three patterns in exon 3 with five nucleotide sequence variations. The effect of intron 1 MSTN variation on milk production traits and the composition of milk FA were investigated. The saturated fatty acids (SFAs) were grouped into three groups based on the length of their carbon chain; Short chain fatty acid (SCFA: C4:0 to C8:0), medium chain fatty acid (MCFA: C10:0 to C14:0) and long chain fatty acid (LCFA: C15:0 to C24:0). The unsaturated fatty acids (UFAs) with only one double bond (monounsaturated fatty acid: MUFA) ranged from C10:1 to C22:1 and were grouped as MUFA, whereas those with two or more double bonds (polyunsaturated fatty acid: PUFA) ranged from C18:2 to C22:5 and were grouped as PUFA. Using General Linear Mixed-effect Model (GLMM) analyses, single variant presence/absence models revealed the presence of variant D to be associated with reduced levels of C8:0, C10:0, C12:0, C12:1, and the grouped MCFA level; but an increased level of C16:1 cis-9. Variant B was associated with decreased C15:0 iso level, whereas the presence of C was associated with increased levels of C20:3 cis-8, 11, 14 and C22:1, trans-13. Only the NZ HF × J-cross cows with the following MSTN genotypes; AA (n = 151), AB (n = 92), AC (n = 53) and AD (n = 65) were studied in the milk FA genotype association analyses; with the remaining genotypes, AE (n = 15), BB (n = 7), BC (n = 7), BD (n = 17), CC (n = 6) CD (n = 10) and DD (n = 7) having frequencies less than 5% each, and not being analysed. These genotype model results were consistent with the single variant presence/absence models, with genotype AD being associated with reduced C10:0, C12:0, and C12:1 levels. For the leptin gene, the effect of exon 3 variation on milk production traits and FA composition in NZ HF × J-cross dairy cows were investigated. Association studies using GLMMs revealed the presence of variant A3 (the most common variant) decreased the levels of C15:1 C22:0, C24:0, C18:1 trans-11, C18:1 trans-9, cis-12 and C18:1 all trans. Variant B₃ was revealed to be associated with reduced C6:0, C11:0 level, and C20:0 level, but increased C17:0 iso, C24:0 and C10:1 index. Variant C₃ was associated with decreased C13:0 anteiso. The following genotypes; A₃A₃ (n = 73), A₃B₃ (n = 176) and A₃C₃ (n = 52) were examined for milk FA composition, whereas B₃B₃ (n = 11) and C₃C₃ (n = 3) were excluded from the analyses due to their low frequency of occurrence. In the genotype model, relative to the A₃A₃ genotype, the A₃B₃ genotype was associated with decreased levels of C8:0, C10:0, C11:0, C13:0 and grouped MCFA, but increased C24:0. Genotype A₃C₃ was associated with decrease grouped MCFA level and C10:0, C11:0 and C13:0 levels relative to the A₃A₃ genotype. These associations in NZ HF × J-cross cows suggest that variation in bovine MSTN and LEP could be explored for increasing the concentration of UFAs and decreasing the concentration of SFAs in milk.

The processes of transcriptional regulation have been implicated as key mechanisms by which changes in genotype, whether among human populations or between species, give rise to the diversity of phenotypes observed in nature, but a full understanding of how transcriptional regulation responds to genetic variation remains elusive. In the last decade, the use of high-throughput sequencing to assess read-outs of transcriptional regulatory activity such as transcription factor binding using chromatin immunoprecipitation followed by sequencing (ChIP-seq) and gene expression using RNA-seq has enabled quantitative genome-wide investigations of these processes.Previous studies of differences in transcriptional regulation between species supported a model in which mammalian transcriptional regulation exhibited greater plasticity and rate of change compared to Drosophila, which comported with known differences in population size and generation time. However, by re-analyzing these data with a common framework, we find that gene expression and the binding patterns of all studied transcription factors, except for the chromatin organizer CTCF, diverge at indistinguishable rates in mammals, birds and fruit flies, suggesting the existence of a transcriptional regulatory “clock” in analogy to the molecular clock observed in protein sequences. We next examined the role of the external environment in determining the transcriptional regulatory programs of microglia, a CNS-specific macrophage cell type. In both mice and humans, we find that the signals from the brain environment crucially determine both the enhancer landscape and gene expression programs that are significantly enriched for genes associated with neurological disease in humans. Substantial differences between human and mouse microglia and between ex vivo and in vitro cells argue for improved model systems to understand the role of microglia in human health.Finally, differences in elements of transcriptional regulation such as transcription factor binding, and histone tail modifications have been observed to cluster in contiguous regions called cis-regulatory domains (CRDs). We developed algorithms for efficiently identifying genomic regions that are significantly enriched in quantitative trait differences such as ChIP-seq peak intensity. We applied this algorithm to data from five strains of laboratory mice and observed a concordance of CRD activity levels with clustered differences in chromatin activation state.

Humans are modifying various aspects of the environment, from building roadways, to moving species beyond their range, to purposefully reconstructing plant communities. These actions affect both the current distribution of populations and the potential for populations to persist. In this dissertation, I examine two human-caused impacts to plant populations and one aspect of efforts to support native plant communities. In chapter one, I focus on the impact of sodium chloride, a road de-icing agent. Such agents can damage plants and change dominant species along roadsides. I carried out two experiments, planting a pedigreed population of the native prairie legume Chamaecrista fasciculata into a roadside environment and into four greenhouse salinity treatments. I tracked their survival and reproduction. Using Aster models, I detected potential to adapt both to roadside salinity and to low salinity in the greenhouse. I also detected gene-by-environment interactions in both experiments. These results indicate a potential to adapt, but a potential which may be slowed by gene-by-environment interactions. In chapter two, I focus on the interaction of Echinacea pallida, introduced outside of its range, on local populations of E. angustifolia. I used controlled crosses and monitored their seed set and the survival of the progeny over five years. Crossing of the two species produces offspring capable of surviving multiple years. Comparing conspecific and heterospecific crosses, I found that conspecific crosses of E. angustifolia resulted in lower pollen compatibility and survival to year four than did conspecific crosses with E. pallida or heterospecific crosses. These results demonstrate a risk to E. angustifolia populations by E. pallida populations planted nearby. In chapter three, I focus on efforts to remediate human impacts through restoration of Minnesota prairie plant communities, which depends on the production and use of source-identified seeds. Restoration practice often emphasizes use of seeds sourced from populations near the restoration site, but demand frequently outstrips supply. I conducted focus group interviews with groups of producers and users of locally-sourced seeds to identify strengths and weaknesses with current practices. Participants discussed continued increases in production and use of these plant materials but also identified aspects where improvement is needed.

Researchers from health care to basic science are interested in determining how people can improve their overall eating patterns. This dissertation concerns the roles of genetic variation and exercise in influencing dietary patterns, with three specific aims. 1. Characterize dietary patterns using sparse latent factor models, addressing the methodological shortcomings of the current dietary pattern approach. 2. Examine the influence of a 15-week aerobic exercise training protocol on dietary patterns among young adults. 3. Examine the contribution of genetic variation to the variability of dietary patterns using genome-wide single nucleotide polymorphism (SNP) data. Since foods and beverages are consumed in a variety of combinations under free-living circumstances, analysis performed on a per-food or per-nutrient basis can be misleading. Thus, it is important to consider not only research related individual dietary component, but also research that examines dietary patterns that represent the real-life manner in which foods are consumed in a variety of combinations. With this idea in mind, dietary pattern analysis was performed to identify habitual dietary patterns among young adults. In this research project, sparse latent factor modeling was applied to dietary pattern analysis an alternative approach to overcome the methodological shortcomings of the current dietary pattern methods in which several steps are performed sequentially, and each step involves in an arbitrary decision rule. Once dietary patterns were identified, the influence of exercise on patterns of food consumption was evaluated. Changes in dietary patterns among young adults after 15 weeks of exercise training were examined using the time-varying factor scores of dietary patterns. The results suggest that engaging in regular exercise may motivate individuals to regulate overall food intake as well as pursue healthier dietary preferences. Finally, the SNP-based heritability of dietary patterns was examined using genome-wide SNP data. The proportion of variance in dietary patterns accounted for by genetic variation was calculated, which produced estimates of SNP-based heritability. The heritability of both the Snacking and Western patterns was greater than that of the Prudent pattern, suggesting a stronger biological underpinning for preference of foods high in fat and sugar. Dietary patterns are more than the sum of their part; they represent what people habitually eat and drink in daily lives, and these dietary components act synergistically to affect health. Understanding the roles of exercise and genetic variation in influencing dietary patterns as a whole would be a significant step toward the goal of providing a robust behavioral and biological basis for healthy eating patterns that both reduce risk of preventable chronic disease and promote overall health.

Studies of human genetic variation reveal critical information about genetic and complex diseases such as cancer, diabetes and heart disease, ultimately leading towards improvements in health and quality of life. Moreover, understanding genetic variations in viral population is of utmost importance to virologists and helps in search for vaccines. Next-generation sequencing technology is capable of acquiring massive amounts of data that can provide insight into the structure of diverse sets of genomic sequences. However, reconstructing heterogeneous sequences is computationally challenging due to the large dimension of the problem and limitations of the sequencing technology.This dissertation is focused on algorithms and analysis for two problems in which we seek to characterize genetic variations: (1) haplotype reconstruction for a single individual, so-called single individual haplotyping (SIH) or haplotype assembly problem, and (2) reconstruction of viral population, the so-called quasispecies reconstruction (QSR) problem. For the SIH problem, we have developed a method that relies on a probabilistic model of the data and employs the sequential Monte Carlo (SMC) algorithm to jointly determine type of variation (i.e., perform genotype calling) and assemble haplotypes. For the QSR problem, we have developed two algorithms. The first algorithm combines agglomerative hierarchical clustering and Bayesian inference to reconstruct quasispecies characterized by low diversity. The second algorithm utilizes tensor factorization framework with successive data removal to reconstruct quasispecies characterized by highly uneven frequencies of its components. Both algorithms outperform existing methods in both benchmarking tests and real data.

The red-backed salamander (Plethodon cinereus) has long-served as a model system in ecology, evolution, and behavior, and studies surveying molecular variation in this species have become increasingly common over the past decade. However, difficulties are commonly encountered when extending microsatellite markers to populations that are unstudied from a genetic perspective due to high levels of genetic differentiation across this species’ range. To ameliorate this issue, we used 454 pyrosequencing to identify hundreds of microsatellite loci. We then screened 40 of our top candidate loci in populations in Virginia, Pennsylvania, and Ohio—including an isolated island population ~ 4.5 km off the shore of Lake Erie (South Bass Island). We identified 25 loci that are polymorphic in a well-studied region of Virginia and 11 of these loci were polymorphic in populations located in the genetically unstudied regions of Ohio and Pennsylvania. Use of these loci to examine patterns of variation within populations revealed that South Bass Island has low diversity in comparison to other sites. However, neither South Bass Island nor isolated populations around Cleveland are inbred. Assessment of variation between populations revealed three well defined genetic clusters corresponding to Virginia, mainland Ohio/Pennsylvania, and South Bass Island. Comparisons of our results to those of others working in various parts of the range are consistent with the idea that differentiation is lower in regions that were once glaciated. However, these comparisons also suggest that well differentiated isolated populations in the formerly glaciated portion of the range are not uncommon. This work provides novel genetic resources that will facilitate population genetic studies in a part of the red-backed salamander’s range that has not previously been studied in this manner. Moreover, this work refines our understanding of how neutral variation is distributed in this ecologically important organism.

Emerald ash borer (EAB) has killed millions of trees since its accidental introduction to southeastern Michigan more than 20 years ago. Near the invasion epicenter, nearly all mature ashes have died, reproduction has ceased, and the seed bank depleted, leaving an “orphaned” cohort of established seedlings and saplings. Because of high seedling mortality, it is possible that seedlings that established recently may have lower genetic variation than those that established before the EAB invasion. Insecticides can successfully protect ash trees from EAB and clusters of treated ash trees may slow ash mortality by reducing EAB densities. Therefore, insecticides, in high enough densities, may protect ash trees in order to maintain reproduction, regeneration, and genetic variation. I tested these questions at Five Rivers Metroparks in southwestern Ohio and the Upper Huron River Watershed in southeastern Michigan. From 2014 – 2016, green and white ash mortality differed between parks, with survival higher at Sugarcreek, Englewood, and Germantown Metroparks (low EAB impact) than at Cox Arboretum, Taylorsville, and Twin Creek (high EAB impact). I found that survival of untreated green-white ashes increased with percentage of ash phloem area treated, but only in parks with low EAB impact. Additionally, survival of untreated trees was higher when the nearest treated ash was within 100 m, percentage of ash phloem treated was high, and EAB impact was low. However, this pattern was not observed in parks with high EAB impact. These results suggest that treating ash trees with insecticide may slow the progression of ash mortality if the program is initiated when ash mortality is still low. There were more flowering green and white ash trees (treated and untreated) in plots with higher percentage ash phloem treated. In parks with high EAB impact, seedling density was low and was not affected by insecticide treatment. In parks with low EAB impact, seedling densities increased with percentage of ash phloem treated. Density of seedlings increased with density of flowering ash trees and decreased with height of herbaceous understory vegetation, which may suppress seedling population through competition for resources. Overall, these results show that protecting trees with insecticide can maintains ash reproduction.Patterns of genetic variation of seedling and sapling populations differed in Michigan and Ohio. In Michigan, established seedlings and saplings had similar allelic richness, but there was also less genotypic variation in the larger seedlings and saplings than in smaller seedlings. In Ohio, newly germinated and small established seedlings had higher allelic richness than larger established seedlings, but each population had similar number of effective alleles (high frequency alleles). Larger seedlings had the least genotypic variation and newly established seedlings had the most. Collectively, these results are consistent with a loss of genetic variation in Michigan, but no loss of genetic variation in Ohio. EAB-induced ash mortality and density of treated ash trees also had no effect on genetic variation in populations of ash seedlings, but the impact of the EAB invasion and the conservation benefits of insecticide treated trees may intensify as ash mortality increases over time.

Throughout this dissertation I approach the long-term aim of improving photosynthesis through the lens of natural genetic variation for photosynthesis. To date few studies have directly asked how photosynthetic variation might inform or provide the genetic material required to enhance photosynthesis, despite the clear utility of this strategy for other types of agronomic improvement. Of the many traits underling variation in photosynthesis, mesophyll conductance – the diffusional flux of CO2 through the leaf interior – has potential to improve both photosynthesis and water use efficiency. I assess genetic variation for photosynthesis among ecotypes of the model plant Arabidopsis thaliana and cultivars of soybean (Glycine max). In both species, and across both controlled and field environments in soybean, I find heritable genetic variation for mesophyll conductance that is positively correlated to variation in photosynthetic rate, indicating that selection to enhance mesophyll conductance will increase photosynthesis. Genetic variation in mesophyll conductance though was largely unrelated to variance in water use efficiency as a result of phenotypic correlation between stomatal and mesophyll conductance. If trait variation is to prove useful for crop breeding, that trait must not have already been improved in the varieties currently used by farmers. In soybean, photosynthesis has improved slightly with breeding for yield across a historical set of cultivars. Mesophyll conductance is not responsible for this increase in photosynthesis; it remains unchanged after 75 years of selection for yield. Stomatal conductance is greater in modern varieties and I show that this increase scales from the leaf to the canopy. Greater canopy conductance in modern soybeans resulted in lower canopy temperatures and reduced leaf heat-stress. Few leaf-level photosynthetic traits were improved across this historical set of soybean cultivars. Given that I observed heritable genetic variation for mesophyll conductance among a small sampling of available soybean germplasm, there is substantial opportunity to harness this variation for the improvement of photosynthetic efficiency.

Congenital heart diseases (CHDs), structural abnormalities of the heart that arises during embryonic development, are the most common inborn malformations, affecting up to 1% of the population. Causes for CHD have been attributed to a combination of environmental teratogens and genetic mutations, but cumulatively only 20% of cases can be explained. To date, over 60 genes in human have been implicated in CHD, but considering mutations in over 500 genes in mouse result in CHD, many more are expected to be found in humans. In this respect, this study sought to identify disease-causal gene mutations in families with sporadic or inherited CHD, and to identify potential CHD genes for future in vivo study. 30 Australian families with heterogenous non-syndromic CHDs, 16 familial and 14 sporadic cases, were analysed by Exome sequencing and their variants prioritised for disease-causal candidacy through a novel two-tiered approach: (1) CHD Gene screen, filtering for variants in genes with previous human CHD association; (2) Comprehensive Screen, an unbiased filtering of inherited rare, predicted-damaging, variants according to all possible Mendelian inheritance patterns. This approach identified pathogenic and likely pathogenic variants in 7 of 30 cases when limited to genes with known CHD association, increasing to 16 of 30 by comprehensive analysis. Two novel candidate variants, a KAT6A missense mutation predicted borderline benign by in silico tools, and a PBX1 missense mutation predicted pathogenic, were investigated functionally in vitro, vindicating their predicted disease-causal status. The two-tiered variant filtering approach was applied to an additional three families, of whom genome sequence data was available, successfully identifying pathogenic mutations in each case. In summary, 11 new genes without previous association to human CHD; PBX1, FLT4, TEK, TIE1, TEAD2, ZFP36L2, KDM5A, KMT2C, CNOT1, UPF2, and USP34, could be linked to the cardiac defects of the respective families. Hence, this study highlights that unbiased comprehensive analysis of exome and genome data can substantially increase the success rate of identifying likely disease-causal variants compared to a purely targeted approach. These findings are not only applicable for genetic counselling of affected families, but have potentially uncovered novel signalling pathways necessary for proper cardiac development.

Cardiac fibrosis is a pathological process that contributes to adverse cardiac remodeling. It is a consequence of tissue repair processes driven mainly by cardiac fibroblasts (CFbs). In response to stress, CFbs proliferate and secrete extracellular matrix components which, if excessive, leads to scar formation. Scar tissue can interrupt the connections between cardiomyocytes, ultimately compromising the structural integrity and function of the heart. Functional recovery of the myocardium is not only hindered by the formation of fibrotic tissue but also by the irreversible loss of cardiomyocytes. In addition to the key role of CFbs in scar formation, it has been suggested that a subset of CFbs may be the optimal cell source to generate cardiomyocytes through direct reprogramming. Direct cardiac reprogramming of CFbs represents a promising approach that could lead to regeneration of cardiomyocytes from the endogenous fibroblasts while reducing scar tissue formation. Several studies have demonstrated in vivo direct reprogramming of CFbs leads to an improvement in cardiac function and has been shown to be exceedingly more efficient in the context of recent cardiac injury. Despite the prominent role of CFbs in both scar formation, and in the potential generation of new cardiomyocytes through reprogramming, characterization of these cells is still limited. This is mainly due to lack of reliable markers to identify cardiac fibroblasts, their heterogeneity, and the effects of genetic variation when studying these cells in a diverse population. These constraints prompted us to first identify a panel of surface markers to prospectively identify CFbs. We further performed a comprehensive investigation to identify the developmental heterogeneity of CFbs. We then sought to determine whether developmental origin of CFbs may influence their contribution to formation of scar as well as its effect on their direct reprogramming into iCMs. Finally, by studying CFbs from multiple inbred mouse strains and their response to cardiac insult we aimed to investigate the effect of genetic variation in pathogenesis of cardiac fibrosis. To undertake a comprehensive study of CFbs, we established a panel of surface markers that can efficiently isolate the majority of CFbs from the adult mouse heart. We employed lineage tracing, transplantation studies, and parabiosis to show that most adult CFbs are derived from the epicardium, a minority arises from endothelial cells, with no contribution from bone marrow or circulating cells. Intriguingly, developmentally distinct CFbs showed similar proliferation rates, and similar gene expression profiles in response to pressure overload injury. We next sought to determine whether this heterogeneity of CFbs may affect their efficiency to generate cardiomyocytes via direct reprogramming, mainly in the context of injury. Using genetic fate-mapping techniques, transplantation studies and gene expression profiling, we showed that the majority of CFbs originate from a shared mesodermal ancestor as cardiomyocytes while a minority of the CFb population originates from neural crest-derived precursors. We provide compelling evidence that, regardless of their developmental origin, CFbs are able to be successfully converted to functional iCMs through in vitro direct reprogramming. However, CFbs generated iCMs with higher efficiency compared to fibroblasts of extra-cardiac organs of identical developmental origin, emphasizing the importance of the physiological microenvironment on cell fate. Remarkably, cardiac injury induced unique re-expression of early developmental genes in CFbs that corresponded to their developmental origin. Finally, we studied the contribution of CFbs from multiple inbred mouse strains following insult to the heart. Our data showed that despite similar increases in proliferation within the different strains, fibroblast activation is a response that correlates with the extent of scar formation. Additionally, by comparing CFbs from multiple strains, we were able to identify potential pathways as therapeutic targets with latent TGF-b binding protein-2 (LTBP2) as a promising diagnostic marker for fibrosis, with relevance to patients with underlying myocardial fibrosis.Together, our findings suggest that common signaling mechanisms stimulate the pathological response of different CFb populations. However, in the context of direct cardiac reprogramming after injury, the developmental heterogeneity of CFbs may be an essential contributing factor. Our findings also highlight the importance of genetic variation in cardiac fibrosis. Therefore, therapeutic strategies for reducing pathogenic CFbs should target these common pathways instead of targeting fibroblasts of other sources. It may be crucial to study the effects of injury on different CFb subsets for the development of targeted therapies to promote cardiac repair.

The economic importance of a carcass is determined by the quantity of saleable meat. The quality of a carcass is determined by the lean meat yield and the ratio of lean meat to fat. Therefore, the heightened quality is portrayed by a carcass that is low in subcutaneous fat, high in lean meat yield with a minimum of 3% of intramuscular fat to give the meat marbling, enhancing eating attributes such as, juiciness and tenderness. Diacylglycerol acyltransferase 1 or DGAT1 has shown to have a strong association with fat production as the last committed step to triglyceride synthesis. In this trial, 338 NZ Romney lambs were genotyped using PCR-SSCP to see if variation occurred in DGAT1 intron 1. It was determined that a variation occurred, and following sequencing, the variation was identified to be a C to T substitution at position 171 between primer sites and equated to three genotypes; AA, AB and BB. 190 lambs were further investigated for association between their genotypes and carcass traits. Three data sets were used, 2015, Glenleith progeny 2014 and Doughboy progeny 2014, of these, two (2015 and Glenleith 2014) showed a strong correlation, P=0.040, P=0.027 respectively, between an increase in leg yield and the presence of allele B. With further analysis it showed that the presence of B increased the leg yield by between 670-706g. It may be assumed that this increase is due to heightened intramuscular fat and therefore the identification of the presence of allele B may be incorporated into a selective breeding system to enhance the intramuscular fat in a leg cut in NZ Romney lambs.

Pathogen infection or plant disease cause major losses in crop production across many species. In grapevine, in particular, there is an ongoing need to decrease dependence on chemical agents as a method to control or manage pathogen infection. Therefore, new approaches need to be explored to provide effective methodologies or approaches to minimise the impacts of pathogen infections. Jasmonic acid is known to be an important compound in plants that orchestrates both wound and plant defence responsiveness against a range of plant herbivores and pathogens. Jasmonic acid, via complex signalling cascades, induces plant defence genes such as those encoding proteinase inhibitors (involved in the protection of plant from insect damage), defensins and thionin (involved in the production of antimicrobials), and a raft of biosynthetic genes that lead to the accumulation of antimicrobial secondary metabolite such as alkaloids, terpenoids, flavonoids, and glucosinolates. Furthermore, jasmonic acid also facilitates the interaction between other defence signalling pathways such as those mediated by salicylic acid and ethylene to acquire the most effective ways to combat herbivore and pathogen attacks. Allene oxide synthase is the first committed biosynthetic step in the formation of jasmonic acid. Previous studies indicate that genetic variation within allene oxide synthase that alter its biosynthetic capacity have the potential to confer to the host plant increased resistance to attack from fungal pathogens. Therefore characterisation of grapevine allene oxide synthase function and genetic variation is an important step in ascertaining the potential this enzyme to contribute to increased tolerance to a wide range of fungal pathogens. Allene oxide synthase (hydroperoxide dehydratase; EC 4.2.1.92) is an enzyme belonging to the cytochrome P-450 (CYP74A) that known to catalyse the first step in the biosynthesis of jasmonic acid from lipoxygenase-derived hydroperoxides. A functional study of grapevine allene oxide synthase has not been previously reported. Therefore in this study we focused on the identification and functional characterization of the putative allene oxide synthase from Vitis vinifera L. Sauvignon blanc via complementation of an Arabidopsis allene oxide synthase null mutant. We investigated the relationships between allene oxide synthase and the other members of the CYP74 family in grapevine, in terms of sequence similarities, subcellular localisations and transcriptional regulation, both spatially and in response to mechanical wounding. We also determined the range of genetic variation of the grapevine allene oxide synthase within a commercial grapevine population. Our findings clearly demonstrate that there is a single allene oxide synthase gene in grapevine and that this gene is able to function in a heterologous system (Arabidopsis) to compliment a null mutation in allene oxide synthase. We show that grapevine allene oxide synthase is localised within the chloroplast and likely associated with chloroplast membranes. In addition the remaining members of the grapevine CYP74 family are found to be localised in varying cellular locations, not necessarily those predicted by in silico sequence analysis. The members of the CYP74 family show differential spatial and developmental transcript accumulation in grapevine. In order to assess the potential for increasing allene oxide synthase levels to increase biochemical flux through to jasmonic acid we overexpressed both the grapevine and Arabidopsis allene oxide synthases in a wild type Arabidopsis background. Our findings suggest that grapevine AOS might not be the only limitation in production of enhanced levels of jasmonic acid in response to wounding or pathogen attack. While we obtained increased levels of allene oxide synthase transcription, this did not result in a concomitant increase in jasmonic acid and consequently increases in the transcription of jasmonate regulated genes. However, while the alterations in jasmonate levels in the transgenic lines was below expectations, we did note that increased levels of jasmonate as a result of overexpression of allene oxide synthase did result in a limited and transient increase in tolerance to Botrytis infection. Investigation of the potential levels of genetic diversity of allene oxide synthase locus in grapevine indicated that this locus is highly conserved with no variation being evident among 100 vines in a commercial vineyard. While the levels of genetic variation strongly suggest that identification of suitable genetic variation in allene oxide synthase that would contribute to increased jasmonate accumulation from within existing grapevine populations is uneconomically practical or efficient. In conclusion our data suggests that to increase jasmonate mediated resistance against fungal disease in grapevine would likely require a coordinated alteration in allene oxide synthase as well as downstream genes in the biosynthetic pathway such as allene oxide cyclase and 12-oxophytodienoic acid reductase. To achieve such an alteration without resorting to transgenic approaches would require the use of a hybridization/breeding approach (which is currently unpalatable to industry) or identification of a suitable gain-of-function mutation from the native transposon mutation population that our group is currently producing.

Gene duplication is considered a major contributor to genome evolution and functional diversity. Differences in genomic features (such as structural resemblance, transcriptional orientation, and genomic location) between members of a gene duplicate pair may indicate the possible duplication mechanisms, as well as the evolutionary fates the paralogs may experience. In addition to these genomic features, molecular genetic features, such as differences in codon usage and expression levels may provide further insight into functional changes between paralogs. In this dissertation, multiple genomic analyses were conducted in order to evaluate the differences in genomic and genetic properties between duplicate copies in order to understand the effect duplication mechanisms may have on the divergence of duplicate pairs. Chapter Two focuses on differing patterns of sequence asymmetry, codon usage, and gene expression levels between the members of gene duplicate pairs belonging to two different populations of paralogs in Saccharomyces cerevisiae: ohnologs, which arose via a whole genome duplication (WGD), and small segmental duplication (SSD) paralogs. It is shown that ohnologs have more highly conserved gene order (synteny) relative to SSD paralogs, despite their greater evolutionary age. Within SSD pairs, the derived paralog (the copy with lower synteny) seems to evolve faster, simultaneously exhibiting a lower CIA value and lower expression levels relative to the ancestral copy. While synteny and evolutionary rate differences were not coupled in ohnolog pairs, the relationship between evolutionary rate asymmetry, CAI, and expression levels was similar to that observed in SSD pairs. These results indicate that codon usage contributes to rate asymmetry in the evolution of gene duplicates in both, ohnologs and SSD paralogs, while differences in synteny (as experienced by SSD pairs, but not very young ohnologs) only affects rate asymmetry in SSD pairs. This may imply relaxed selection on codon usage and the expression of derived copies, potentially leading to the acquisition of novel functions over time. Chapters Three and Four focus on the effects of structural resemblance and other genomic features on young gene duplicate pairs within the Homo sapiens (human) and Pan troglodytes (chimpanzee) genomes. The results imply that the majority of gene duplicates in both species are structurally complete duplications, encompassing the entire coding region of a gene. The chimpanzee genome additionally contains a large fraction (46%) of retrotransposed young gene duplicates relative to the human genome (13%) which may be due to differences in genome architecture, such as mobile element content between the two genomes. While RNA-mediated processes lead to a majority of inter-chromosomal paralogs, DNA-mediated paralogs reside largely on the same chromosome, in which case inter-paralog distance does not increase over time. These results in conjunction with results of previous studies in nematodes, yeast, and flies, suggest that the structural resemblance types and location of duplicates are closely linked to the duplication mechanism by which paralog pairs arise. This is also true for closely related species, as illustrated by the comparison of the human and chimpanzee genomes. The above studies illustrate the relationship duplication span (as illustrated in Chapter Two) and mechanisms (illustrated in Chapters Three and Four) have on the location, synteny, structural resemblance types, and functionality of gene duplicates in different genomes. The findings imply that differences in mechanisms between species can have significant effects on the genome evolution and divergence between even closely related taxa.

With the development of sequencing technologies, more and more sequence variants are available for investigation. Different types of variants in the human genome have been identified, including single nucleotide polymorphisms (SNPs), short insertions and deletions (indels), and large structural variations such as large duplications and deletions. Of great research interest is the functional effects of these variants. Although many programs have been developed to predict the effect of SNPs, few can be used to predict the effect of indels or multiple variants, such as multiple SNPs, multiple indels, or a combination of both. Moreover, fine grained prediction of the functional outcome of variants is not available. To address these limitations, we developed a prediction framework, HMMvar, to predict the functional effects of coding variants (SNPs or indels), using profile hidden Markov models (HMMs). Based on HMMvar, we proposed HMMvar-multi to explore the joint effects of multiple variants in the same gene. For fine grained functional outcome prediction, we developed HMMvar-func to computationally define and predict four types of functional outcome of a variant: gain, loss, switch, and conservation of function.

Economically important production traits in the New Zealand sheep meat industry underpin one of the country’s most significant agricultural exports. Polymerase Chain Reaction-Single Strand Conformational Polymorphism (PCR-SSCP) was utilised to detect the variation within two genes in sheep which are hypothesised to have involvement in body growth and compositional traits in sheep (Ovis aries). Variation in the the gene encoding uncoupling protein 1 in both the promoter region and intron 5 region was found to be significantly influenced by congenital effects due to sire and relatedness of the 1125 individuals typed. This casts uncertainty upon previous results indicating that the gene is involved in the partitioning of energy consumed to the production of lean meat as opposed to adipose tissue. The PRKAG3 gene that has shown promising results in terms of skeletal glycogen content and lipogenesis in other species was found to vary significantly (P

Tigers (Panthera tigris tigris) can be viewed as a proxy for intact and healthy ecosystems. Their wild populations have plummeted to fewer than 3,200 individuals in the last four decades and threats to these apex predators are mounting rather than diminishing. Global conservation bodies (Global Tiger Initiative, World Wildlife Fund, Wildlife Conservation Society, Panthera etc.) have recently called for solidarity and scaling up of conservation efforts to save tigers from extinction. In South Asia, tiger habitat ranges from tropical evergreen forests, dry arid regions and sub-tropical alluvial floodplains, to temperate mixed deciduous forest. The churia habitat is relatively unstudied and is considered a young and geologically fragile mountain range in Nepal. The contribution of the churia habitat to tiger conservation has not been considered, since modern conservation started in 1970's. This study focuses on the ecology of the tiger with respect to population density, habitat use, and prey occupancy and density, in the churia habitat of Chitwan National Park. This study also includes the first assessment of genetic diversity, genetic structure, and gene flow of tigers across the Terai Arc Landscape- Nepal. The Terai Arc Landscape harbors the only remaining tiger population found across the foothills of the Himalayas in Nepal and northwest India. I used a combination of camera-trapping techniques, which have been a popular and robust method for monitoring tiger populations across the landscape, combined with a noninvasive genetic approach to gain information on tigers, thus adding new information relevant to global tiger conservation. I investigated tiger, leopard (Panthera pardus fusca), and prey densities, and predicted the tiger density across the Churia habitat in Chitwan National Park. I used a camera-trap grid with 161 locations accumulating 2,097 trap-nights in a 60 day survey period during the winter season of 2010-2011. Additionally, I used distance sampling techniques for estimating prey density in the churia habitat by walking 136 km over 81 different line transects. The team photographed 31 individual tigers and 28 individual leopards along with 25 mammalian species from a sampling area of 536 km² comprising Churia and surrounding areas. Density estimates of tigers and leopards were 2.2 (SE 0.42) tigers and 4.0 (SE 1.00) leopards per 100 km². Prey density was estimated at 62.7 prey animals per 100 km² with contributions from forest ungulates to be 47% (sambar Rusa unicolor, chital Axis axis, barking deer Muntiacus muntjak, and wild pigs Sus scrofa). Churia habitat within Chitwan National Park is capable of supporting 5.86 tigers per 100 km² based on applying models developed to predict tiger density from prey density. My density estimates from camera-traps are lower than that predicted based on prey availability, which indicates that the tiger population may be below the carrying capacity. Nonetheless, the churia habitat supports 9 to 36 tigers, increasing estimates of current population size in Chitwan National Park. Based on my finding, the Churia habitat should no longer remain ignored because it has great potential to harbor tigers. Conservation efforts should focus on reducing human disturbance to boost prey populations to potentially support higher predator numbers in Churia. I used sign surveys within a rigorous occupancy framework to estimate probability of occupancy for 5 focal prey species of the tiger (gaur Bos gaurus, sambar, chital, wild pig, and barking deer); as well as probability of tiger habitat use within 537 km² of churia habitat in Chitwan National Park. Multi-season, auto-correlation models allowed me to make seasonal (winter versus summer) inferences regarding changes in occupancy or habitat use based on covariates influencing occupancy and detection. Sambar had the greatest spatial distribution across both seasons, occupying 431-437 km² of the churia habitat, while chital had the lowest distribution, occupying only 100-158 km². The gaur population showed the most seasonal variation from 318- 413 km² of area occupied, with changes in occupancy suggesting their migration out of the lowland areas in the summer and into the churia in the winter. Wild pigs showed the opposite, moving into the churia in the summer (444 km² area occupied) and having lower occupancy in the winter (383 km²). Barking deer were widespread in both seasons (329 - 349 km²). Tiger probability of habitat use Ψ SE(Ψ) was only slightly higher in winter 0.63 (SE 0.11) than in summer 0.54 (SE 0.21), but confidence intervals overlapped and area used was very similar across seasons, from 337 - 291 km². Fine-scale variation in tiger habitat use showed that tigers intensively use certain areas more often than others across the seasons. The proportion of available habitat positively influenced occupancy for the majority of prey species and tigers. Human disturbance had a strong negative influence on the distribution of the majority of prey species but was positively related to tiger habitat use. Tigers appear to live in areas with high disturbance, thus increasing the risk of human-tiger conflict in the churia habitat. Thus, efforts to reduce human disturbance would be beneficial to reducing human wildlife conflict, enriching prey populations, and would potentially support more tigers in churia habitat of Nepal. Overall, I found high prey occupancy and tiger habitat use, suggesting that the churia is highly valuable habitat for tigers and should no longer be neglected or forgotten in tiger conservation planning. Thirdly, I assessed genetic variation, genetic structure, and gene flow of the tigers in the Terai Arc Landscape, Nepal. I opportunistically collected 770 scat samples from 4 protected areas and 5 hypothesized corridors across the Terai Arc Landscape. Historical landuse change in the Terai Arc was extracted from Anthrome data sets to relate landuse change to potential barriers and subsequent hypothesized bottleneck events in the landscape. I used standard genetic metrics (allelic diversity and heterozygosity) to estimate genetic variation in the tiger population. Using program Structure (non-spatial) and TESS (spatial), I defined the putative genetic clusters present in the landscape. Migrant analysis was carried out in Geneclass and Bayesass for estimating contemporary gene flow. I tested for a recent population bottleneck with the heterozygosity test using program Bottleneck. Of the 700 samples, 396 were positive for tiger (57% success). Using an 8 multilocus microsatellite assay, I identified 78 individual tigers. I found large scale landuse changes across the Terai Arc Landscape due to conversion of forest into agriculture in last two centuries and I identified areas of suspected barriers. I found low levels of genetic variation (expected heterozygosity = 0.61) and moderate genetic differentiation (FST = 0.14) across the landscape, indicative of sub-population structure and potential isolation of sub-populations. I detected three genetic clusters across the landscape consistent with three demographic tiger sub-populations occurring in Chitwan-Parsa, Bardia, and Suklaphanta protected areas. I detected 10 migrants across all study sites confirming there is still some dispersal mediated gene flow across the landscape. I found evidence of a bottleneck signature, especially around the lowland forests in the Terai, likely caused by large scale landuse change in last two centuries, which could explain the low levels of genetic variation detected at the sub-population level. These findings are highly relevant to tiger conservation indicating that efforts to protect source sites and to improve connectivity are needed to augment gene flow and genetic diversity across the landscape. Finally, I compared the abundance and density of tigers obtained using two non-invasive sampling techniques: camera-trapping and fecal DNA sampling. For cameras: I pooled the 2009 camera-trap data from the core tiger population across the lowland areas of Chitwan National Park. I sampled 359 km² of the core area with 187 camera-trap locations spending 2,821 trap-nights of effort. I obtained 264 identifiable photographs and identified a total of 41 individual tigers. For genetics, I sampled 325 km² of the core area along three spatial routes, walking a total of 1,173 km, collecting a total of 420 tiger fecal samples in 2011. I identified 36 tigers using the assay of 8 multilocus genotypes and captured them 42 times. I analyzed both data types separately for estimating density and jointly in an integrated model using both traditional, and spatial, capture-recapture frameworks. Using Program MARK and the model averaged results, my abundance estimates were 46 (SE 1.86) and 44 (SE 9.83) individuals from camera and genetic data, respectively. Density estimates (tigers per 100 km²) via traditional buffer strip methods using half of the Mean Maximum Distance Moved (½ MMDM) as the buffer surrounding survey grids, were 4.01 (SE 0.64) for camera data and 3.49 (SE 1.04) for genetic data. Spatially explicit capture recapture models resulted in lower density estimates both in the likelihood based program DENSITY at 2.55 (SE 0.59) for camera-trap data and 2.57 (SE 0.88) for genetic data, while the Bayesian based program SPACECAP estimates were 2.44 (SE 0.30) for camera-trap data and 2.23 (SE 0.46) for genetic data. Using a spatially explicit, integrated model that combines data from both cameras and genetics, density estimates were 1.47 (SD 0.20) tigers per 100 km² for camera-trap data and 1.89 (SD 0.36) tigers per 100 km² for genetic data. I found that the addition of camera-trap data improved precision in genetic capture-recapture estimates, but not visa-versa, likely due to low numbers of recaptures in the genetic data. While a non-invasive genetic approach can be used as a stand-alone capture-recapture method, it may be necessary to increase sample size to obtain more recaptures. Camera-trap data may provide a more precise estimates, but genetic data returns more information on other aspect of genetic health and connectivity. Combining data sets in an integrated modeling framework, aiding in pinpointing strengths and weaknesses in data sets, thus ultimately improving modeling inference.

Muscle growth is a critical trait in the pig industry, as increased muscle growth results in increased meat yield. In this context, the aim of this study was to investigate genes that may be involved in muscle growth and carcass traits in pigs. A total of 474 commercial pigs from New Zealand and Thailand were investigated using polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) analysis to explore variation in nine candidate genes. These genes included: the myogenic regulatory factor 5 gene (MYF5), the myogenin gene (MYOG), the calpastatin gene (CAST), the calpain 3 gene (CAPN3), the myostatin gene (MSTN), the callipyge gene (CLPG), the leptin gene (LEP), the beta-3 adrenergic receptor gene (ADRB3) and the immunoglobulin heavy alpha chain gene (IGHA). These genes have been reported to influence muscle growth rate, meat production and other production traits in animals. Sequence analyses revealed genetic variation at all the loci tested, with the exception of MSTN, which was not variable in the region tested in the pigs studied. There were two variants of MYOG, CAPN3, CLPG and ADRB3, and three variants of LEP and IGHA, including a new variant, that has not been reported previously. The highest level of variation detected was four variants of MYF5 and CAST. The variation in each gene was tested for its association with production traits in the pigs studied. The presence of variant A of MYF5 exon 3 was associated with increased weaning- weight and decreased fat depth. Variant C of CAST intron 5 was associated with increased live weight, average daily gain (ADG) and lean growth rate. Variant D of CAST intron 5 was associated with increased ADG and increased fat depth, while variant B of CAST exon 6 tended (P=0.064) to be associated with increased lean growth rate. The genotype AB of CAST exon 6 tended (P=0.065) to be associated with increased lean growth rate. Variant B of ADRB3 was associated with increased weaning-weight and hot carcass weight.. Absence of variant A was associated with increased fat depth, but this finding is weak since only two individual pigs carried this genotype. Variant B of IGHA was associated with decreased fat depth. Together, these data suggest that genetic variation in MYF5, CAST, ADRB3 and IGHA may be involved in skeletal muscle growth and meat production in pigs. There was no association observed with variation in LEP and some variants of MYOG, CLPG and CAPN3 were at a low frequency, which precluded further analysis. Given that these results could be of benefit to the pig industry, the genes warrant further investigation.

A series of experiments were conducted to estimate the genetic parameters for an elite breeding population of white clover (Trifolium repens L.) in both an irrigated and dryland environment. Data collected from two environments using spaced-planted and mini-plot trials were used to demonstrate the rationale for pursing various traditional and modern marker-assisted selection breeding methods in white clover. In addition, and under the over-arching theme of investigating breeding strategies, supplementary findings are presented regarding pollination patterns within a white clover population in isolation cages. In an experiment designed to generate half-sib and full-sib families for progeny evaluation, pollen dispersal within isolation cages using wild bumble bees (Bombus sp.) was monitored using simple sequence repeat molecular markers (SSR markers). Within bi-parental crosses, no detectable levels of self-fertilised germinated seedlings were detected, nor were there any detectable levels of foreign pollen sources. Within polycross isolations, no detectable levels of foreign pollen sources were detected, and self-fertilised rates were negligible (

Autism Spectrum Disorders (ASDs) are a group of heritable neruodevlopmental disorders. Both common and rare genetic variants are known to play a role in ASDs. However the functional impact of genetic variants remains largely unexplored. In this study, we conducted transcriptome profiling analysis to uncover the expression alterations that are associated with autism. The transcriptome profiling also aids us exploring the regulatory patterns of genetic variants, and better understanding the genetic models of autism. Since brain tissue is not accessible on a large scale, we profiled mRNAs of lymphoblast cell lines (LCLs) from three independent cohorts to determine whether we could detect a reproducible blood gene expression pattern associated with ASD. RNA from a total of 978 patients, and 651 controls, including 607 unaffected siblings analyzed for differential expression. Although few genes were consistently differentially expressed between ASD and controls, we did find five (CMKOR1, DKFZP564O0823, PITPNC1, PRKCB1 and VIM) that were differentially expressed in at least two cohorts LCLs and previously published brain samples. Similarly, using LCL gene expression to classify subjects by disease status performed only slightly above chance. Using weighted gene co-expression network analysis (WGCNA), we were able to identify a module correlated with ASD in both AGRE and NIMH cohorts that overlapped with genes previously found to be mis-expressed in post mortem brain from ASD cases. eQTL analysis identified SNPs that were associated with LCL gene expression, including several in AHI1, a Joubert Syndrome gene dysregulated in ASD brain and lymphoblasts. Four of the 23 SNPs that were significantly correlated with the expression level of AHI1 reside in the same haplotype block previously associated with ASD, suggesting that risk for ASD is mediated via AHI1 transcript levels. Overall, we found a weak, but consistent signal in LCLs further suggesting that peripheral lymphoblast gene expression may be useful for studying ASD.Rare variants including Copy Number Variants (CNVs) and Single Nucleotide Variants (SNVs) are found to play an important role to the etiology of ASD together with common variants. We next interrogated gene expression in lymphoblasts from 244 families with discordant siblings in the Simons Simplex Collection in order to identify potentially pathogenic variation. Our results reveal that the overall frequency of significantly mis-expressed genes (which we refer to here as outliers) identified in probands and unaffected siblings do not differ. However, in probands, but not their unaffected siblings, the group of outlier genes is significantly enriched in neural-related pathways including neuropeptide signaling, synaptogenesis and cell adhesion. We demonstrate that outlier genes cluster within the most pathogenic CNVs (rare de novo CNVs) and can be used to prioritize rare CNVs of potentially unknown significance. Several non-recurrent CNVs with significant gene expression alterations are identified, including deletions on chromosome 3q27, 3p13 and 3p26, and duplications at 2p15, suggesting these as potential novel ASDs loci. In addition, we identify distinct pathways disrupted in 16p11.2 microdeletions, microduplications and 7q11.23 duplications, and show that specific genes within the 16p CNV interval correlate with differences in head circumference, an ASDs relevant phenotype. This study provides evidence that pathogenic structural variants have functional impact on transcriptome alterations in ASDs at a genome-wide level, and demonstrates the utility of this approach for prioritization of genes for subsequent functional analysis.Genetic studies have identified dozens of ASDs susceptibility genes, yet the interaction between ASD risk genes are pooly understood. In the aim of identify the molecular mechanisms and potential convergening pathways of ASD risk genes, the last chapter of my research utilizes transcriptome profiling to answer two questions: 1) do these genetic loci converge on specific laminar expression patterns, and 2) where does the phenotypic specificity of ASDs arise, given its genetic overlap with intellectual disability (ID)? To answer these, we mapped ASDs and ID risk genes to non-human primate and human brain transcriptome. We found ASDs genes are enriched in superficial cortical layers and glutamatergic projection neurons at the circuit level. Furthermore, we show that the patterns of ASDs and ID risk genes are distinct, providing a novel biological framework for investigating the pathophysiology of ASDs. In this chapter, we demonstrated the importance of understanding ASD gene interaction with systems biology method.

Previous studies have demonstrated that plants may be affected by their interactions with both biotic and abiotic environmental factors. An important biotic factor that usually affects the performance of plants is insect herbivory. In addition, abiotic factors such as light, or more specifically ultraviolet B (UVB) radiation, can also affect growth and physiological processes in plants. Arabidopsis thaliana is an annual herbaceous plant species with documented defense strategies including resistance and tolerance. Studies have also shown that these plant responses to insect herbivory may be modified by other abiotic factors such as UVB radiation. In a series of common garden experiments, the role of insect herbivory per se and in combination with UVB radiation was evaluated. Using a population of recombinant inbred lines of A. thaliana, the first experiment (described in Chapter 1) investigated the role of plant trichomes and size on patterns of plant use by an insect community. In this experiment, it was also evaluated whether insect herbivory imposes selection on trichome production and plant size. In a second experiment (described in Chapters 2 and 3), the effect of UVB radiation on plant resistance and tolerance to insect herbivory as well as on their potential fitness costs was assessed. This experiment also evaluated the role of UVB on patterns of plant utilization by insect herbivores and whether this important abiotic factor may influence plant phenotypic responses. Results from these experiments revealed that plant trichomes influenced levels of herbivore damage and plant size had an effect on colonization of plants by insect herbivores. In addition, results from selection analyses revealed that insect herbivores exerted directional selection on trichome density in A. thaliana. The second study showed that UVB radiation influenced the expression of resistance and tolerance as well as their associated fitness costs. Similarly, patterns of plant utilization by insect herbivores and phenotypic responses of plants to insect herbivory were modified by UVB radiation. Overall, these results highlight the importance of evaluating complex environments, including both abiotic and biotic factors, as it relates to the evolution and maintenance of traits related to plant defense against insect herbivory

One of the greatest challenges facing clinical scientists is a developed understanding of the genetic basis for complex human diseases such as cancer. Despite many technological advances in genetics, progress has been slow. This is owed, in part, to intricate gene-gene interactions as well as poorly understood environmental influences on gene expression and genetic traits. The high level of heterogeneity of the human genome makes identification of these interactions and environmental influences difficult. Recently, the domesticated dog (Canis Lupis Familaris), has demonstrated its powerful applicability to human disease as a new model of genetic variation. Dogs are an excellent model for the study of complex disease in humans for a variety of reasons, including the extensive level of health care they receive, and their phenotypic diversity. Approximately 400 inherited diseases similar to those of humans are characterized in dogs, including complex disorders such as cancers, heart disease, and neurological disorders. The purpose of this dissertation project is to elucidate the role of genetic variation in the domesticated dog as a model for understanding human disease and is comprised of four manuscripts. I establish 1) the utility of the canine model for the study of human disease, 2) the theoretical and empirical establishment of a novel method for genomewide genetic analysis, 3) identification of germline loci associated with the risk for development of Osteosarcoma. Finally, 4) I describe a novel mechanism involving structural variation which results in an epigenetic readout for a highly penetrant Mendelian trait. I discuss how each of these studies stands to broadly accelerate biomedical investigation.