Genetic and epigenetic mechanisms of adaptation in stony corals

In this dissertation, I used genomic techniques to examine interrelationships between genotype, gene expression, DNA methylation and environmental conditions in the model coral Acropora millepora. I present three major findings: 1) populations in the Great Barrier Reef have the potential for rapid genetic adaptation to climate change 2) patterns of DNA methylation predict gene expression plasticity 3) patterns of DNA methylation can predict fitness under environmental change.Cellular and Molecular Biolog

On quantitative issues pertaining to the detection of epistatic genetic architectures

Converging empirical evidence portrays epistasis (i.e., gene-gene interaction) as a ubiquitous property of genetic architectures and protagonist in complex trait variability. While researchers employ sophisticated technologies to detect epistasis, the scarcity of robust instances of detection in human populations is striking. To evaluate the empirical issues pertaining to epistatic detection, we analytically characterize the statistical detection problem and elucidate two candidate explanations. The first examines whether population-level manifestations of epistasis arising in nature are small; consequently, for sample-sizes employed in research, the power delivered by detectors may be disadvantageously small. The second considers whether gene-environmental association generates bias in estimates of genotypic values diminishing the power of detection. By simulation study, we adjudicate the merits of both explanations and the power to detect epistasis under four digenic architectures. In agreement with both explanations, our findings implicate small epistatic effect-sizes and gene-environmental association as mechanisms that obscure the detection of epistasis

Cancer, DNA repair and chromatin structure

Colorectal cancer, the most common cancer in males and females who do not smoke, is diagnosed in approximately 3,500 Scots each year. Despite having a large environmental contribution, the substantial genetic basis of colorectal tumours is still poorly understood. In this project we have adopted a number of approaches to try and further characterise this genetic contribution of colorectal cancer.To begin to understand tumour progression, we first characterised the gene ex¬ pression changes observed in various tumours using SAGE, EST and microarray data. Although many genes were identified as differentially expressed in cancers, little congruence was observed between tumour types and even expression platforms. We next compared gene expression changes observed along chromosomes to local chromatin structure, and showed that regions of constit.utively open structure generally show an increase in gene expression in cancer. Despite the lack of congruence between expression data shown previously, we illustrated that such a correlation between gene expression change in tumours and chromatin structure can be observed using various expression platforms and across a variety of tumours.congruence was observed between tumour types and even expression platforms. We next compared gene expression changes observed along chromosomes to local chromatin structure, and showed that regions of constit.utively open structure generally show an increase in gene expression in cancer. Despite the lack of congruence between expression data shown previously, we illustrated that such a correlation between gene expression change in tumours and chromatin structure can be observed using various expression platforms and across a variety of tumours.To further characterise the role of chromatin structure in tumours, we also investigated the rates of mutation and selection across chromatin categories. DNA damage and repair is a key process in cancer progression and we have shown, through inter species alignments, that although chromosomal regions of a relatively more open chromatin structure undergo lower rates of mutation, levels of purifying selection on synonymous sites are highest in regions of closed chromatin.As part of the COGS/SOCCS group the role of DNA repair in colorectal cancer was finally further investigated through a case-control association study. Tagging SNPs in genes predicted to be associated with DNA repair were selected and subsequently typed by the group in approximately 1000 cases and 1000 controls. The nature of SNPs with evidence of an association with colorectal cancer was finally characterised

Predicting Influenza Antigenicity by Matrix Completion With Antigen and Antiserum Similarity

The rapid mutation of influenza viruses especially on the two surface proteins hemagglutinin (HA) and neuraminidase (NA) has made them capable to escape from population immunity, which has become a key challenge for influenza vaccine design. Thus, it is crucial to predict influenza antigenic evolution and identify new antigenic variants in a timely manner. However, traditional experimental methods like hemagglutination inhibition (HI) assay to select vaccine strains are time and labor-intensive, while popular computational methods are less sensitive, which presents the need for more accurate algorithms. In this study, we have proposed a novel low-rank matrix completion model MCAAS to infer antigenic distances between antigens and antisera based on partially revealed antigenic distances, virus similarity based on HA protein sequences, and vaccine similarity based on vaccine strains. The model exploits the correlations of viruses and vaccines in serological tests as well as the ability of HAs from viruses and vaccine strains in inferring influenza antigenicity. We also compared the effects of comprehensive 65 amino acids substitution matrices in predicting influenza antigenicity. As a result, we applied MCAAS into H3N2 seasonal influenza virus data. Our model achieved a 10-fold cross validation root-mean-squared error (RMSE) of 0.5982, significantly outperformed existing computational methods like antigenic cartography, AntigenMap and BMCSI. We also constructed the antigenic map and studied the association between genetic and antigenic evolution of H3N2 influenza viruses. Finally, our analyses showed that homologous structure derived amino acid substitution matrix (HSDM) is most powerful in predicting influenza antigenicity, which is consistent with previous studies