Understanding how genetic variation propagate to differences in phenotypes in individuals is an ongoing challenge in genetics. Genome-wide association studies have allowed for the identification of many trait-associated genomic loci. However, they are limited in their inability to explain the altered cellular mechanism. Genetic variation can drive disease by altering a range of mechanisms, including signalling networks, TF binding, and protein folding. Understanding the impact of variants on such processes has key implications in therapeutics, drug development, and more. This thesis aims to utilise computational predictors to shed light on how cellular mechanisms are altered in the context of genetic variation and better understand how they drive both molecular and organism-level phenotypes. Many binding events in the cell are mediated by short stretches of sequence motifs. The ability to discover these underlying rules of binding could greatly aid our understanding of variant impact. Kinase–substrate phosphorylation is one of the most prominent post-translational modifications (PTMs) which is mediated by such motifs. We first describe a computational method which utilises interaction and phosphorylation data to predict sequence preferences of kinases. Our method was applied to 57% of human kinases capturing known well-characterised and novel kinase specificities. We experimentally validate four understudied kinases to show that predicted models closely resemble true specificities. We further demonstrate that this method can be applied to different organisms and can be used for other phospho-recognition domains. The described approach allows for an extended repertoire of sequence specificities to be generated, particularly in organisms for which little data is available. TF-DNA binding is another mechanism driven by sequence motifs, which is key for the tight regulation of gene expression and can be greatly altered by genetic variation. We have comprehensively benchmarked current methods used to predict non-coding variant effects on TF-DNA binding by employing over 20,000 compiled allele-specific ChIP-seq variants across 94 TFs. We show that machine learning-based approaches significantly outperform more rudimentary methods such as the position weight matrix. We further note that models for many TFs with distinct binding specificities were unable to accurately assess the impact of variants. For these TFs, we explore alternative mechanisms underlying TF-binding, such as methylation, co-operative binding, and DNA shape that drive poor performance. Our results demonstrate the complexity of predicting non-coding variant effects and the importance of incorporating alternative mechanisms into models. Finally, we describe a comprehensive effort to compile and benchmark state-of-the-art sequence and structure-based predictors of mutational consequences and predict the effect of coding and non-coding variants in the reference genomes of human, yeast, and E. coli. Predicted mechanisms include the impact on protein stability, interaction interfaces, and PTMs. These variant effects are provided through mutfunc, a fast and intuitive web tool by which users can interactively explore pre-computed mechanistic variant impact predictions. We validate computed predictions by analysing known pathogenic disease variants and provide mechanistic hypotheses for causal variants of unknown function. We further use our predictions to devise gene-level functionality scores in human and yeast individuals, which we then used to perform gene-phenotype associations and uncover novel gene-phenotype associations.

Advances in DNA synthesis technology have led to rapid growth in the field of synthetic biology, heralding a nascent era of synthetic genomics. Sc2.0 (Saccharomyces cerevisiae version 2.0) is an international consortium with the aim of designing and constructing a fully‐synthetic eukaryotic genome. Fundamental design changes to the synthetic genome include the removal of unstable tRNA genes and their intended collation onto a “tRNA neochromosome”, with the aim of producing a more robust and stable synthetic genome structure. To maintain viability of a synthetic yeast, the tRNA neochromosome is therefore considered an important if not essential aspect of this project. The application of engineering principles is synonymous with synthetic biology, regularly employing the recursive Design‐Build‐Test cycle to improve experimental approach. This doctoral study explores the design, construction and characterisation of a tRNA neochromosome in Saccharomyces cerevisiae. A series of design principles influenced by engineering concepts were used to rationalise the complexities of de novo chromosome engineering, maximise its stability and ensure function in vivo. A methodology based on in vivo homologous recombination was then developed and shown to reliably construct the neochromosome from its constituent parts. Experimental characterisation revealed that genetic elements function as expected, and that the parental strain can tolerate the sole presence of one each of three single‐copy, essential tRNA genes (SUP61, TRT2 and TRR4), although Northern blot revealed potential precursor accumulation of the SUP61 tRNA caused by the presence of a synthetic 5’ flanking sequence. Following the addition of synthetic telomere seed sequences, pulsed‐field gel electrophoresis (PFGE) and deep sequencing revealed complex structure variations in two independent strain backgrounds. Except for these structural variations, successful neochromosome construction demonstrated the applicability of the approaches used and the remarkable ability of the yeast model to support the presence of a 17th chromosome housing an additional 275 tRNA genes. The research in this thesis has for the first time described the design, construction and characterisation of a eukaryotic neochromosome de novo. It is hoped that the findings presented will further our understanding of tRNA biology and enhance the aims of the Sc2.0 project.

xi, 52 p. ; ill. (some col.) A print copy of this title is available through the UO Libraries under the call number: SCIENCE QH445.2 .B35 2008 / Activation of Heat shock proteins (Hsps) is critical to adaptation to low oxygen levels (hypoxia) and enduring the oxidative stress of reoxygenation. Hsps are known to be regulated by Heat shock factor (Hsf), but my results demonstrate an unexpected regulatory link between the oxygen sensing and heat shock pathways. Hsf transcription is upregulated during hypoxia due to direct binding by Hypoxia-inducible Factor-1 (HIF-1) to HIF-1 response elements in an Hsf intron. This increase in Hsf transcripts is necessary for full Hsp induction during hypoxia and reoxygenation. The HIF-1-dependent increase in Hsps has a functional impact, as reduced production of Hsps decreases viability of adult flies exposed to hypoxia and reoxygenation. Thus, HIF-1 control of Hsf transcriptional levels is a regulatory mechanism for sensitizing heat shock pathway activity in order to maximize production of protective Hsps. This cross-regulation represents a mechanism by which the low oxygen response pathway has assimilated complex new functions by regulating the heat shock pathway's key transcriptional activator. Beyond studying the regulation of specific genes. I have also developed a method to identify small, yet important, changes within entire genomes. Genetic variation is the foundation of phenotypic traits, as well as many disease states. Variation can be caused by inversions, insertions, deletions, duplications, or single nucleotide polymorphisms (SNPs) within a genome. However, identifying a genetic change that is the cause of a specific phenotype or disease has been a difficult and laborious task for researchers. I developed a technique to quickly and accurately map genetic changes due to natural phenotypic variation or produced by genetic screens. I utilized massively parallel, high-throughput sequencing and restriction site associated DNA (RAD) markers, which are short tags of DNA adjacent to the restriction sites. These RAD markers generate a genome-wide signature of fragments for any restriction enzyme. Taken together with the fact that the vast majority of organisms have SNPs that disrupt restriction site sequences, the differences in the restriction fragment profiles between individuals can be compared. In addition, by using bulk segregant analysis, RAD tags can be used as high-density genetic markers to identify a genetic region that corresponds to a trait of interest. This dissertation includes both previously published and unpublished co-authored materials. / Adviser: Eric Johnson

The advent of high-throughput DNA and RNA sequencing has made possible the assay of millions of nucleic acid molecules in parallel. This allows functional genomic elements to be identified from background in single-tube experiments. This dissertation discusses the development of two such functional screens as well as work implementing a third that was previously developed in my thesis laboratory. Restriction-Associated DNA sequencing (RAD-Seq) is a complexity reduction sequencing method that allows the same subset of genomic sequence to be read across multiple samples. Differences in sample collection and data analysis allow manifold applications of RAD-Seq. Here we use RAD-Seq to identify mutant genes responsible for altered phenotypes in Caenorhabditis elegans and to identify hyper-invasive alleles in trout population admixtures. Apart from acquiring genomic sequence data, massively-parallel sequencing can be used for counting applications that quantify activity across a large number of test molecules. This dissertation describes the development of a technique for simultaneously quantifying the activity of a restriction enzyme across all possible DNA substrates by linking digest of a sequenced genome to Illumina-sequencing in an unbiased fashion. Finally, a powerful approach to analyze transcriptional activation is described. This method quantifies output from millions of potential DNA transcriptional enhancers via RNA amplicon sequencing of covalently-linked randomer tags and is used in conjunction with RNA-Seq to provide a mechanistic view of hypoxic gene regulation in Drosophila. This dissertation includes previously published, co-authored material

Genetic variation is the raw material of evolution. The sources of this variation within a population, and its maintenance within a species, have been mysterious since the birth of the field of evolutionary genetics. In this work, I study divergently adapted freshwater and marine populations of the threespine stickleback (Gasterosteus aculeatus) as an evolutionary model to track the origin of adaptive genetic variation and to describe the evolutionary processes maintaining variation across the genome. The stickleback is a small fish with a large geographic range encompassing the northern half of the Northern Hemisphere and composed of coastal marine habitats, freshwater lakes, and river systems. Populations of stickleback adapt rapidly to changes in habitat, and fossil evidence suggests that similar adaptive transitions have been ongoing in this lineage for at least ten million years. In this work, I develop a significant extension of restriction site-associated DNA sequencing (RAD-seq) to generate phased haplotype information to estimate gene tree topologies and divergence times at thousands of loci simultaneously. I find anciently derived clades of variation associated with marine and freshwater habitats in genomic regions involved in recent adaptive divergence; some divergence times extend to over ten million years ago. This history of adaptive divergence has had profound effects on genetic variation elsewhere in the genome: chromosomes harboring freshwater-adaptive variants retain anciently derived variation in linked genomic regions, while marine chromosomes have much more recent ancestry. I present a conceptual model of asymmetric selective and demographic processes to explain this result, which will form a nucleus for future research in this species. Lastly, by incorporating genome-wide recombination rates estimated from multiple genetic maps, I describe a recombination landscape that is favorable to the maintenance of marine-freshwater genomic divergence. Low recombination rates in key chromosomal regions condense widespread divergence of the physical genome, encompassing many megabases, into a small number of Mendelian loci. Combined, my results demonstrate the interconnectedness of evolutionary processes taking place on ecological and geological timescales. The genetic variation available for adaptive evolution today is a product of the long-term evolutionary history of a species.

Viral sequence data are increasingly being used to estimate evolutionary and epidemiological parameters to understand the dynamics of viral diseases. This thesis focuses on developing novel and improved computational methods for high-throughput analysis of large viral sequence datasets. I have developed a novel computational pipeline, Pipelign, to detect potentially unrelated sequences from groups of viral sequences during sequence alignment. Pipelign detected a large number of unrelated and mis-annotated sequences from several viral sequence datasets collected from GenBank. I subsequently developed ANVIL, a machine learning-based recombination detection and subtyping framework for pathogen sequences. ANVIL's performance was benchmarked using two large HIV datasets collected from the Los Alamos HIV Sequence Database and the UK HIV Drug Resistance Database, as well as on simulated data. Finally, I present a computational pipeline named Phlow, for rapid phylodynamic inference of heterochronous pathogen sequence data. Phlow is implemented with specialised and published analysis tools to infer important phylodynamic parameters from large datasets. Phlow was run with three empirical viral datasets and their outputs were compared with published results. These results show that Phlow is suitable for high-throughput exploratory phylodynamic analysis of large viral datasets. When combined, these three novel computational tools offer a comprehensive system for large scale viral sequence analysis addressing three important aspects: 1) establishing accurate evolutionary history, 2) recombination detection and subtyping, and 3) inferring phylodynamic history from heterochronous sequence datasets.

Made available in DSpace on 2016-03-07T19:20:17Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-07-31. Added 1 bitstream(s) on 2016-03-07T19:23:57Z : No. of bitstreams: 1 000858103.pdf: 6986071 bytes, checksum: 61cc82fb4f22cd71ec70c868dc8f37e5 (MD5) / Objetivou-se com este estudo realizar associação genômica ampla, visando detectar regiões cromossômicas associadas a características indicadoras de precocidade sexual de bovinos da raça Nelore, bem como avaliar metodologias para a predição de valores genômicos visando à seleção destas características. Foram utilizados dados de animais da raça Nelore, pertencentes a fazendas que integram os programas de melhoramento genético da DeltaGen® e Paint® (CRV Lagoa). As características associadas à precocidade sexual utilizadas neste estudo foram a idade ao primeiro parto (IPP), a ocorrência de prenhez precoce de novilhas (P16) e o perímetro escrotal (PE). Após o controle de qualidade e consistência dos dados fenotípicos, permaneceram para as análises informações de 68.170, 72.675 e 83.911 animais com fenótipo e de 1.738, 1.770 e 1.680 animais genotipados para IPP, P16 e PE, respectivamente, e 412.993 SNPs. No Capítulo 2, as estimativas dos efeitos dos SNPs foram obtidas utilizando-se a metodologia single-step (WssGBLUP). Todos os animais foram utilizados aplicando-se modelo animal unicaracterística para predizer os valores genéticos e, posteriormente, as soluções dos efeitos dos SNPs foram obtidas a partir destes valores genéticos. Foram identificadas as 10 janelas de 150 SNPs que capturaram a maior proporção da variância explicada pelos marcadores. As 10 janelas de maior efeito obtidas para a P16 estão localizadas nos cromossomos 5, 6, 7, 14, 18, 21 e 27 e somadas explicaram 7,91% da variância genética total. Para o PE, estas janelas estão nos cromossomos 4, 8, 11, 13, 14, 19, 22 e 23, explicando 6,78% da variância total. Com as análises de GWAS foi possível identificar regiões cromossômicas associadas com P16 e PE. A identificação dessas regiões possibilita o melhor entendimento e avaliação destas características, além de indicar genes candidatos para estudos futuros de investigação de... / The objective of this study was to perform genome-wide association to detect chromosomal regions associated with indicator traits of sexual precocity of Nellore cattle, and evaluating methodologies for prediction of genomic values to use for selection of these traits. Data from Nellore animals belonging to farms integrating animal breeding programs of DeltaGen® and Paint® (CRV Lagoa), were used. Age at first calving (AFC), the occurrence of early pregnancy of heifers (EP) and scrotal circumference (SC) were used as traits associated with sexual precocity. After quality control and consistency of phenotypic data, information of 68,170; 72,675 and 83,911 animals with phenotype, and of 1,738; 1,770 and 1,680 genotypes for AFC, EP and SC, respectively, and 412,993 SNPs, remained for analysis. In chapter 2, the estimates of the SNP effects were obtained using the single-step method (WssGBLUP). All animals were used applying single trait animal model to predict the genetic values and, subsequently, the solutions of the SNP effects were obtained from these genetic values. The 10 windows of 150 SNPs that captured the greatest proportion of variance explained by markers were identified. The 10 windows with greater effect obtained for EP are located on chromosomes 5, 6, 7, 14, 18, 21 and 27 and together explained 7.91% of the total genetic variance. For SC, these windows are on chromosomes 4, 8, 11, 13, 14, 19, 22 and 23, explaining 6.78% of the total variance. With GWAS analysis it was possible to identify chromosomal regions associated with EP and SC. Identifying these regions enables better understanding and evaluation of these traits, besides indicating candidate genes for future research studies of causal mutations. In Chapter 3, two multi-step methods were used to estimate the marker effects - GBLUP and IBLASSO; besides the single-step method (ssGBLUP). Observed phenotype was used as the dependent variable to estimate the genomic value ...

Made available in DSpace on 2016-03-07T19:20:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-07-29. Added 1 bitstream(s) on 2016-03-07T19:24:25Z : No. of bitstreams: 1 000858097.pdf: 325868 bytes, checksum: b5d70c189e8328bfce207cd5135d7627 (MD5) / Para o capítulo 2 o objetivo do trabalho foram avaliar a qualidade das predições de mérito genético entre os métodos BLUP e GBLUP na presença de imprecisão nos dados. Para o capítulo 3 o objetivo do trabalho foi comparar os métodos BLUP, GBLUP e BAYESR considerando ou não a interação genótipoambiente em ovinos multirraciais. Os dados utilizados para a realização do capítulo 2 foram simulados com três níveis de imprecisão nos dados fenotípicos, 0%, 25% e 50% em três características com magnitude de herdabilidade de 0,02, 0,15 e 0,30, respectivamente, as metodologias BLUP e GBLUP foram aplicadas nesse dados e seus desempenhos foram comparados. Para a comparação das metodologias os parâmetros de erro quadrático médio, variância do erro de predição, viés, acurácia e eficiência de seleção foram utilizados. Melhores resultados foram obtidos pelo método BLUP em relação ao método GBLUP. O método GBLUP não apresentou vantagem em relação ao método BLUP, exceto quando a magnitude da herdabilidade foi de 0,02 e não houve imprecisão nos dados fenotípicos. Para o capítulo 3 foram utilizados 4.288 fenótipos e genótipos de dois rebanhos núcleos de informação (Information Nucleus Flock) oriundos do Australian Sheep Cooperative Research Center program (CRC). Para acessar a acurácia das estimativas, foi utilizada a validação cruzada. Os métodos BLUP, GBLUP e BAYESR, foram utilizados para estimar os valores genéticos sob dois modelos, univariado, o qual não considera a interação genótipo-ambiente e o modelo bivariado com o efeito da interação é considerado. As acurácias dos modelos univariados variaram de 0,17 à 0,27 para o ambiente 1 e de 0,19 à 0,20 para o ambiente 2. As acurácias dos modelos bivariados variam de 0,14 à 0,23 para o ambiente 1 e para o ambiente 2 as acurácias foram de 0,19. Não houve benefício da aplicação da seleção genômica sobre o método BLUP no ambiente 2 para... / In Chapter 2 the objective of the work was to evaluate the quality of the genetic merit of predictions between BLUP and GBLUP methods in the presence of uncertainty in the data. In chapter 3 the objective was to compare the BLUP methods, GBLUP and BAYESR considering whether or not to genotypeenvironment interaction in multi-racial sheep. The data used for the realization of Chapter 2 were simulated with three levels of inaccuracy in phenotypic data, 0%, 25% and 50% in three features with magnitude of heritability of 0.02, 0.15 and 0.30, respectively, the BLUP and GBLUP methodologies were applied this data and their performances were compared. To compare the methodologies the mean square error parameters, prediction error variance, bias, accuracy and selection efficiency were used. Better results were obtained by BLUP method over the GBLUP method. The GBLUP method showed no advantage over the BLUP method, except when the magnitude of heritability was 0.02 and there was no inaccuracy in phenotypic data. For chapter 3 we were used 4,288 phenotypes and genotypes dual-core herds of information (Information Nucleus Flock) coming from the Australian Sheep Cooperative Research Center program (CRC). To access the accuracy of the estimates, cross-validation was used. Methods BLUP, GBLUP and BAYESR, were used to estimate breeding values under two models, univariate, which does not consider the genotype-environment interaction and the bivariate model with the interaction effect is considered. The accuracies of the univariate models ranged from 0.17 to 0.27 for the environment 1 and 0.19 to 0.20 for the environment 2. The accuracies of bivariate models ranging from 0.14 to 0.23 for the environment 1 to the environment and the accuracies were 0.19. There was no benefit from the application of genomic selection on BLUP method in environment 2 for gastrointestinal resistance feature. On the other hand, for the application of 1 atmosphere genomic ...

Made available in DSpace on 2016-03-07T19:21:18Z (GMT). No. of bitstreams: 0 Previous issue date: 2015-08-21. Added 1 bitstream(s) on 2016-03-07T19:25:30Z : No. of bitstreams: 1 000858092.pdf: 1898150 bytes, checksum: e3ce9484168acf98f02ece6694eaec3c (MD5) / Painéis comerciais contendo milhares de SNPs a custo acessível revolucionaram os estudos genéticos na pecuária, principalmente por meio das análises de associação ampla e seleção genômica. A seleção genômica tem um aspecto prático, por ser diretamente aplicado aos programas de melhoramento, possibilitando aumento de acurácia das avaliações para as características quantitativas, como a produção de leite e seus constituintes. Como base nisso objetivou-se com esta tese verificar a distribuição das frequências dos polimorfismos e calcular o desequilíbrio de ligação (DL) dos segmentos cromossômicos no genoma de bovinos da raça Guzerá; estudar a associação dos marcadores com a produção de leite e seus constituintes; e comparar diferentes modelos para avaliação genômica com diferentes distribuições a priori para o efeito dos marcadores. Dessa forma, foi avaliado o DL entre marcadores de um painel de 50 k da Illumina® e estimado o tamanho efetivo populacional. Para isto foram utilizados 50 touros e 853 vacas Guzerá que também participaram dos estudos de associação e seleção genômica. A média de r2 foi de 0,16 para a distância 100 kb no genôma destes animais. A densidade do painel de 50 k foi considerada suficiente para proporcionar DL entre os segmentos cromossômicos para a predição de valores genéticos genômicos. Já as estimativas do tamanho efetivo populacional foram reduzidas com o decorrer das gerações, indicando aumento da intensidade de seleção para a raça ao longo das gerações. O baixo tamanho efetivo observado para as gerações recentes (137) indicaram a importância de se considerar a endogamia nas decisões de acasalamentos para manter a diversidade genética da raça. As avaliações genômicas foram realizadas pelos métodos GBLUP, BayesC, BayesCπ, Lasso e por meio de dois modelos multicaracterística para a produção de leite (PL), gordura (PG) e proteína (PP). As acurácias... / Commercial panels containing thousands of SNPs revolutionized genetic studies in livestock, especially with the genome-wide association study and genomic selection. The genomic selection is also directly applied to breeding programs enabling increasing on accuracy of the genetic evaluation for quantitative traits such as milk yield and its constituents. Thus, the aim of this thesis was to study the distribution of frequencies of polymorphisms and the linkage disequilibrium (LD) in the Guzerá cattle; was also to study the association of the markers with the dairy traits and to compare different models for genomic evaluation with different prior distributions for the effect of markers. The LD and the effective size were estimated using a 50 k Illumina® panel for 50 sires and 853 cows. For 100 kb the average of r2 was 0.16. The density of this 50 k panel was considered sufficient to provide LD between chromosomal segments for estimation of genomic breeding values. The effective size was reduced over the course of generations, indicating increase intensity of selection. The low estimate for effective size for recent generations indicated the importance of considering inbreeding for mating to maintain the genetic diversity of this breed. Genomic evaluations were performed by GBLUP, BayesC, BayesCπ, Lasso and two multi-trait models for milk yield (MY), fat (MF) and protein (MP). The accuracies for predictions ranged from 0.65 to 0.80. Bayesian prediction, GBLUP and multi-traits models were equivalent for predict the genomic breeding values. However, the best option was GBLUP considering overall fit, lower computational requirement and facility of convergence. The results indicated that genomic predictions were adequate to assist animal selection. In other study, the percentages of explained variance for each SNP were calculated. Windows, composed of seven adjacent SNPs deviated substantially from the other genomic regions were ...

Made available in DSpace on 2014-06-11T19:26:06Z (GMT). No. of bitstreams: 0 Previous issue date: 2012-03-13Bitstream added on 2014-06-13T20:33:37Z : No. of bitstreams: 1 bizari_dc_me_jabo.pdf: 336489 bytes, checksum: 0801c01531c7ce877e08321205d11d07 (MD5) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / No presente estudo, cinco novos genes codificantes de proteínas foram selecionados para o mapeamento do cromossomo 6 bubalino (BBU6). Os novos genes (muc1, ppp1r7, psmd4, tshb e gtf2b) foram testados com a tecnologia de PCR resultando em produtos de PCR adequados ao mapeamento utilizando-se um painel de células somáticas híbridas irradiadas, denominado BBURH5000. Os resultados obtidos mostraram uma freqüência de retenção (FR) do produto de PCR de cada gene nas diferentes linhagens do painel com variação de 13,3% (gtf2b) a 26,6% (psmd4). A análise comparativa entre os mapas RH do BBU6 e a sequência do cromossomo 3 bovino permitiu indicar a localização dos novos genes no cromossomo 6 bubalino / In this study, five new protein coding genes were select for mapping buffalo chromosome 6. The new genes (muc1, ppp1r7, psmd4, tshb and gtf2b) were tested using PCR technology resulting in PCR products suitable for mapping using a radiation hybrid panel (BBURH5000). The retention frequency of the PCR products in each hybrid cell line of the panel showed the percentage from 13,3% (gtf2b) to 26,6% (psmd4). Comparative analysis between the buffalo chromosome 6 RH map and the sequence from bovine chromosome 3 allowed to assign the location of the new genes on buffalo chromosome 6