<p>HIV has presented some of the greatest biomedical challenges in recent decades, and an understanding of how the virus behaves when it is in the human body is critical to addressing many of these challenges. One avenue through which to do this is the study of host genetics, which investigates the human genetic variants that modify the interactions between the HIV-1 virus and the human body. In my graduate work, I performed several different investigations that have furthered our understanding of the human genetic variants that either modulate the response to HIV-1 infection or play a role in the acquisition of an HIV-1 infection. This work took place at a time of transition in human genetics, and spanned both the era of genome-wide association studies as well as the beginning of the sequencing and rare variant eras. </p><p>The earliest HIV-1 host genetics findings were made through candidate gene studies, which reflected the state of human genetics research in the 1990s and early 2000s. The draft sequence of the human genome was released in 2001, and HIV host genetics, as well as human genetics in general, has changed considerably since then. Chapter 1 describes the basics of HIV-1 biology and the HIV-1 epidemic, as well as some crucial findings in HIV-1 host genetics. This chapter also gives a brief recent history of human genetics and describes some of the current challenges in the field. </p><p>Chapters 2 and 3 describe the identification of human genetic variants that associate with viral load set point. Chapter 2 describes a copy number variable region (CNV) in the KIR region of the genome that associates with a change in set point, and Chapter 3 describes an allele of HLA-B (HLA-B*5703) that is the largest determinant of viral control in an African American population. Both chapters use data from genotyping chips as a starting point.</p><p>In the past several years, the cost to sequence a genome has plummeted, and it is now possible for a single group to sequence and align an entire human genome in just a few weeks. This "next-generation" sequencing has dramatically changed the field of human genetics, and Chapter 4 will discuss this new technology and provide an early analysis of the patterns of variation that are observed across multiple human genomes. Notably, this new technology allows for an unprecedented amount of variant discovery, including the possibility of identifying low frequency and rare variants. </p><p>Chapter 5 describes two different projects that make use of next-generation sequencing technology to investigate variants that influence HIV-1 disease acquisition and progression. Both projects are extreme phenotype whole-genome sequencing projects. For the first project, we have sequenced individuals who have hemophilia and were highly exposed to contaminated blood products but who remained uninfected. For the second project, we have sequenced African American individuals whose disease progressed very quickly or very slowly. I compare the variants in these individuals to the variants in control populations and describe follow-up genotyping results. I have not identified a causative variant in either of these studies, although a list of candidate variants is still being pursued. These analyses have shown that there is substantial heterogeneity in the genetic basis for both phenotypes. </p><p>Overall, my work has identified two common variants that are playing a role in modulating HIV-1 infection, as well as provided the first assessment of the patterns of variation across a set of unrelated human genomes. This thesis also describes some of the early attempts to apply the next-generation sequencing technique to HIV-1 host genetics. In the Conclusion, I discuss the future of HIV-1 host genetics research and the clinical applications of human genetics.</p> / Dissertation

currently DNA and RNA sequencing are performed as standard parts of many scientific experiments. While the majority of the reads produced in these experiments do map to the genome of the organism of interest there are a significant fraction that do not. These reads have often been viewed as uninteresting and thus discarded, sometimes explained as errors created in the sequencing process. However, there may be a real possibility that these reads actually contain genomic sequences belonging to, but not currently in the genome ofthe organism investigated, as well as information about other organisms which live and thrivein the sample material. Considering this, it is of great interest to investigate these reads to see if they contain any usable information. In this project the unmapped reads from SOLiD sequencing of blood and saliva from a twin pair were assembled. The assembled parts were thencompared to different blast databases to investigate if similar genomic regions are reported inother species. We can conclude that indeed a large fraction of the contigs found in this assemblyhave homology to bacterial genes while other contigs share similarity to genomic regions foundin apes and other species closely related to us. All in all the results show that there is more to the unmapped reads than just sequencing errors.

The Assembly sequencing problem (ASP) is part of the assembly planning process. The ASP is basically a large scale, combinatorial problem which is highly constrianed. The aim of this thesis is to automatically generate assembly sequence(s) for mechanical products. In this thesis, the CAD model of an assembly is represented or modeled as a label-rich graph. The assembly sequences are generated using graph grammar rules that are applied on the graph. The sequences are stored in a search tree and to find an optimal sequence multiple evaluation criteria like time, subassembly stability and accessibility measures are used. This research implements a novel tree search algorithm called "Ordered Depth First Search" (ODFS) to find an optimal assembly sequence in very low processing time. The software has successfully generated an optimized assembly sequence for an assembly with 14 parts. / text

The fungal pathogen Ophiostoma novo-ulmi is the causal agent of Dutch elm disease (DED) and has been responsible for the catastrophic decline of elms in North America and Europe. Double-stranded RNA (dsRNA) viruses are common to all fungal classes and although these viruses do not always cause disease symptoms, the presence of certain dsRNA viruses have been associated with reduced virulence (hypovirulence) in O. novo-ulmi. A new mitovirus was found in a Canadian isolate of O. novo-ulmi (93-1224) and has been named Ophiostoma mitovirus 1c (OMV1c). The positive strand of the dsRNA of OMV1c was 3,003 nucleotides in length and when the mitochondrial codon usage pattern was employed (mitochondria use UGA to encode tryptophan rather than as a chain terminator), a single large open reading frame (ORF) was found. This ORF had the potential to encode a protein of 784 amino acids, and revealed a high degree of nucleotide identity to genes encoding RNA-dependent RNA polymerase (RdRp) in other mitoviruses. The putative RdRp region of the newly characterized virus had the highest sequence similarity to Ophiostoma mitovirus 1b. The 5’- terminal sequence of the positive strand could potentially be folded into a double-stranded stem-loop structure with a free energy of 16.6 kcal/mol. Attempts to cure the O. novo-ulmi isolate 93-1224 of virus were unsuccessful. Screening of the re-cultured isolates for the presence of OMV1c revealed that it was still present in the fungus despite repeated hyphal tip transfer, a method known to cure cytoplasmic but not mitochondrial viruses. Based on the genome size, phylogenetic analysis, and the observation that infected isolates could not be cured, it was surmised that the virus was a member of the genus Mitovirus (family Narnaviridae). To assess the distribution of the virus in O. novo-ulmi at the disease front in Winnipeg, a small sample of thirteen isolates were screened for the presence of the new mitovirus. All proved to be negative for OMV1c, which indicated this dsRNA virus was rare and that isolate 93-1224 was the only isolate identified to date infected with OMV1c. It was also discovered that the isolate O. novo-ulmi 93-1224 potentially harboured more than one virus. Electron microscopy of fractionated cells revealed the presence of two flexuous rod-shaped particles that may represent additional novel viruses. / Graduate

Methods to map small-molecule interactions with cellular RNAs are important for understanding endogenous activation, such as in riboswitches, as well as the potential for exogenous compounds to target RNA. Cisplatin is one of the most widely used of the platinum anticancer drugs that are prescribed in approximately 40-50% of all chemotherapy treatments (Dyson and Sava, 2006; Harper et al., 2010). Despite nearly 40 years of experience with this class of drugs, we still lack a comprehensive understanding of the targets of Pt compounds and their effects on cells. Pt(II) compounds are well-known DNA and RNA crosslinking agents, but the latter area is under-studied. In order to better understand the impacts of cisplatin and other platinum(II)-derived small molecules on cellular RNA, we have developed a technique we call “Platinum-seq,” which couples reverse transcription mapping of platinated RNAs to high-throughput sequencing. Chapter 1 is a study of cisplatin and a novel click-functionalized platinum compound (2-ADAP Pt) binding to the HDV ribozyme, a small catalytic RNA. Chapter 2 moves our platinum mapping approaches from low-throughput, sequencing gel based methods into next-generation sequencing for high-throughput analysis of all platinum sites in cellular RNA, a method we have named “Platinum-seq.” Chapter 3 is a study of differential gene expression of Saccharomyces cerevisiae treated with cisplatin and a second novel platinum(II) compound (azaplatin), using data acquired from the work in Chapter 2. Chapter 4 describes recent efforts to implement pre-enrichment of sequencing targets using click chemistry followed by DNA hybridization, in order to enrich for platinated fragments before sequencing library construction. Together, this work represents a significant step forward in advancing analysis of Pt(II) binding to cellular RNA, a potentially important target for this widely used class of anticancer compounds. Methods developed here are broadly applicable to genome-wide identification of platinum accumulation on DNA as well, which has not been pursued despite the extensive use of these compounds.

No description available.

Submitted by Milena Leite de Oliveira null (milaolive@tupa.unesp.br) on 2017-01-05T10:58:25Z No. of bitstreams: 1 TESE Milena Leite de Oliveira.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2017-01-09T16:28:44Z (GMT) No. of bitstreams: 1 oliveira_ml_dr_bot.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) / Made available in DSpace on 2017-01-09T16:28:44Z (GMT). No. of bitstreams: 1 oliveira_ml_dr_bot.pdf: 83084301 bytes, checksum: 403f45f944124e6f1f0686e2b91f36a4 (MD5) Previous issue date: 2016-11-11 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / A alface pode ser infectada por diferentes tipos de vírus. O Lettuce mosaic virus- LMV foi por muitos anos considerado um dos mais frequentes e amplamente distribuídos mundialmente, podendo ocorrer em infecções simples e/ou mistas com Lettuce mottle virus, LeMoV, um provável sequivirus. A falta de informações a respeito dos aspectos biológicos e moleculares relacionados à classificação taxonômica e à transmissão do LeMoV, motivou a testar sua transmissão com afídeos e por sementes, avançar no sequenciamento do genoma viral e avaliar a incidência do vírus em importantes áreas produtoras de alface no estado de São Paulo. Em 2014, dentre um total de 118 plantas sintomáticas analisadas, 63 (53%) foram positivas para a presença de tospovírus, 11 (9%) foram positivas para LMV e, apenas 6 amostras (5%) foram positivas para LeMoV. Em 2015, 40 plantas (80%) estavam infectadas com tospovírus, e o LMV e LeMoV não foram detectados, indicando que o LeMoV não está limitando a produção de alface, pelo menos não durante o ano de 2014 e 2015. A transmissão desse vírus por sementes não foi verificada nas 832 sementes provenientes de plantas de alface infectadas com LeMoV, o que indica que este vírus provavelmente não seja transmitido por semente. Myzus persicae e Aphis gossypii não foram capazes de transmitir o LeMoV de uma planta de alface para outra. Quase toda a sequencia completa do genoma do LeMoV foi obtida e a presença de domínios conservados verificados na região da capa proteica (CP), da helicase (HEL) e da RNA- dependente de RNA polimerase (RdRp), indicando que o LeMoV é membro da família Secoviridae e está estreitamente relacionado com membros do gênero Sequivirus. Durante o período do doutorado sanduíche na Universidade do Hawaii em Manoa, plantas de jasmim estrelado, coletadas no Hawaii, exibindo sintomas foliares característicos aos provocados pelos vírus, foram analisadas por sequenciamento de nova geração (SNG), a fim de identificar os patógenos relacionados com a doença. Sequencias relacionadas aos vírus da família Tombusviridae como o Rosa rugosa leaf distortion virus, Pelargonium ringspot virus, Pelargonium chlorotic ring pattern virus e Elderberry latent virus foram identificados nas plantas de jasmim estrelado, indicando infecção mista por diferentes vírus.

The rapidly advancing high-throughput and next generation sequencing technologies facilitate deeper insights into the molecular mechanisms underlying the expression of phenotypes in living organisms. Experimental data and scientific publications following this technological advancement have rapidly accumulated in public databases. Meaningful analysis of currently available data in genomic databases requires sophisticated computational tools and algorithms, and presents considerable challenges to molecular biologists without specialized training in bioinformatics. To study their phenotype of interest molecular biologists must prioritize large lists of poorly characterized genes generated in high-throughput experiments. To date, prioritization tools have primarily been designed to work with phenotypes of human diseases as defined by the genes known to be associated with those diseases. There is therefore a need for more prioritization tools for phenotypes which are not related with diseases generally or diseases with which no genes have yet been associated in particular. Chromatin immunoprecipitation followed by next generation sequencing (ChIP-Seq) is a method of choice to study the gene regulation processes responsible for the expression of cellular phenotypes. Among publicly available computational pipelines for the processing of ChIP-Seq data, there is a lack of tools for the downstream analysis of composite motifs and preferred binding distances of the DNA binding proteins. This thesis is aimed to address the gap existing in the tools available to process high-throughput ChIP-Seq data to provide rapid analysis and interpretation of large lists of poorly characterized genes. Additionally, programs for the analysis of preferred binding distances of transcription factors were integrated into the pipeline for expedited results. A gene prioritization algorithm linking genes to non-disease phenotypes described by meaningful keywords was developed. This algorithm can be used to process candidate genetic targets of a transcription factor produced by a computational pipeline for ChIP-Seq data analysis.

In this thesis, we classified user comments posted on online forums related to “Newborn Genome Sequencing” (NGS). User comments were annotated as irrelevant, positive, negative, or mixed by two annotators. The objective was to create a classification model that could predict the sentiment of each user comment with a high accuracy. To compare classifiers, a baseline classifier (Accuracy 52%) was created. We created a single classifier (called flat comment-level classifier with accuracy of 65.14%) to classify comments into irrelevant, positive, negative, or mixed. A more sophisticated classifier, named two-level comment classifier, consisting of two classifiers, was created (Accuracy 69.81%): - The first classifier that classified each comment into relevant or irrelevant ones. - The second classifier that classified each relevant comment (predicted by the first classifier) as positive, negative, or mixed. 18 extra features were generated to improve the accuracy of the flat classification compared to baseline classifier (from 52% to 65.14% for flat comment classification, and 69.48% to 69.81% for two-level comment classification). Attempts were made to enhance the result of the two-level comment classifier by using the discourse structure of each sentence in a comment. The accuracy achieved by this enhanced two-level classifier was 64.24%. Therefore, removing irrelevant EDUs did not improve the accuracy. To achieve the above-mentioned enhancement, all comments were segmented into their consisting elementary discourse units (EDUs). We removed irrelevant EDUs from the relevant comments before running the second classifier. Furthermore, we performed EDU-level classification by creating two classifiers: - A flat classifier: classified all EDUs into irrelevant, positive, negative, or neutral - A two-level EDU: classified EDUs, first, into relevant or irrelevant and then classified the relevant EDUs (predicted by the first classifier) into positive, negative, or neutral ones. The accuracy achieved for the flat EDU-level classifier was 81.84%. However, due to the highly imbalanced nature of the EDU dataset, the F-measure for positive, negative, and neutral class was very low. Under-sampling was performed to improve the F-measure for positive, negative, and neutral class. Another topic investigated was to know why forum users supported or rejected NGS. To extract the arguments, the comments were segmented into EDUs. Following segmenting, each EDU was annotated as relevant or irrelevant to NGS. Each relevant EDU was annotated as for or against NGS. Topic related EDUs were selected as well as two EDUs before and after the topic-related EDUs. Bigrams, trigrams, four-grams and five-grams were created from extracted EDUs. Five-grams were more meaningful for human annotators, and were therefore favoured and ranked based on frequency in the dataset. Following ranking of the five grams, the top five were selected as the possible arguments.

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has become a promising tool for targeted gene editing in a variety of organisms including plants. In this system, a 20 nt sequence on a single guide RNA (sgRNA) is the only gene-specific information required to modify a target gene. Fusarium head blight (FHB) is a devastating disease in wheat caused by the fungus Fusarium graminearum. The trichothecene it produces, deoxynivalenol (DON), is a major mycotoxin contaminant causing food production loss both in quality and yield. In this project, we used the CRISPR/Cas9 system to modify three wheat genes identified in previous experiments, including an ABC transporter (TaABCC6), and the Nuclear Transcription Factor X box-binding-Like 1 (TaNFXL1), both associated with FHB susceptibility, and a non-specific Lipid Transfer Protein (nsLTP) named TansLTP9.4 which correlates with FHB resistance. Two sgRNAs were designed to target each gene and were shown in an in vitro CRISPR/Cas9 assay to guide the sequence-specific cleavage with high efficiency. Another assay for CRISPR/Cas9 was established by the optimization of a wheat protoplast isolation and transformation system. Using a construct expressing a green fluorescent protein (GFP) as a positive control, estimated transformation efficiencies of about 60% were obtained with different batches of protoplasts. High-throughput sequencing of PCR amplicons from protoplasts transformed with editing constructs clearly showed that the three genes have been successfully edited with efficiencies of up to 42.2%. In addition, we also characterized by RT-qPCR the expression pattern of 10 genes in DON-treated protoplasts; seven of the genes were induced by DON in the protoplasts, consistent with their previously identified DON induction in treated wheat heads, while three genes expressed differentially between DON-treated wheat heads and protoplasts. Preliminary bioinformatics analyses showed that these differentially expressed genes are involved in different plant defense mechanisms.