As sequencing technologies advance genome studies are becoming a basic tool for studying an organism, and with more genomes available comparative genomics is maturing into a powerful tool for biological research. This thesis demonstrates the strength of a comparative genomics approach on a group of understudied eukaryotes, the diplomonads. Diplomonads are a group of single cell eukaryotic flagellates living in oxygen-poor environments. Most diplomonads are intestinal parasites, like the well-studied human parasite Giardia intestinalis. There are seven different G. intestinalis assemblages (genotypes) affecting different hosts, and it’s under debate whether these are one species. A genome-wide study of three G. intestinalis genomes from different assemblages reveals little inter-assemblage sexual recombination, supporting that the different G. intestinalis assemblages are genetically isolated and thus different species. A genomic comparison between the fish parasite S. salmonicida and G. intestinalis reveals genetic differences reflecting differences in their parasitic lifestyles. There is a tighter transcriptional regulation and a larger metabolic reservoir in S. salmonicida, likely adaptations to the fluctuating environments it encounters during its systemic infection compared to G. intestinalis which is a strict intestinal parasite. The S. salmonicida genome analysis also discovers genes involved in energy metabolism. Some of these are experimentally shown to localize to mitochondrion-related organelles in S. salmonicida, indicating that they possess energy-producing organelles that should be classified as hydrogenosomes, as opposed to the mitosomes in G. intestinalis. A transcriptome analysis of the free-living Trepomonas is compared with genomic data from the two parasitic diplomonads. The majority of the genes associated with a free-living lifestyle, like phagocytosis and a larger metabolic capacity, are of prokaryotic origin. This suggests that the ancestor of the free-living diplomonad was likely host-associated and that the free-living lifestyle is a secondary adaptation acquired through horizontal gene transfers.  In conclusion, this thesis uses different comparative genomics approaches to broaden the knowledge on diplomonad diversity and to provide more insight into how the lifestyle differences are reflected on the genetic level. The bioinformatics pipelines and expertise gained in these studies will be useful in other projects in diplomonads and other organismal groups.

Black Cottonwood (Populus trichocarpa) is a fast-growing, economically important tree species. P. trichocarpa was the first tree to have its genome fully sequenced and is considered the model organism for genomic research in trees. Of the macronutrients in plants, Nitrogen (N) is required in the greatest amounts and is generally the limiting nutrient in terrestrial ecosystems. Inorganic N-transport is performed by four families of transporter proteins, AMT1 and AMT2 for ammonium (NH4+) and NRT1 and NRT2 for nitrate (NO3-). I have created phylogenetic reconstructions of each of these transporter families in 22 members of Viridiplantae whose genomes have been fully sequenced. Based on these phylogenies, I have introduced a new classification system for the transporter families that better represents the evolutionary and functional relatedness of the proteins. These phylogenies were supplemented with topology predictions, subcellular localization predictions, and in silico expression profiling in order to suggest functional characterization of the groups. This facilitated candidate gene selection for NH4+ and NO3- uptake transporters from P. trichocarpa. Expression profiling was performed on two of these candidates. Results suggest that PtAMT1-1 may be a high-affinity, root-localized NH4+ transporter. In contrast, PtNRT2-6 is a high-affinity NO3- transporter localized to the dormant bud, but its physiological functions remain largely enigmatic. Flux profiles of NH4+, NO3-, and H+ in the first 1.4 cm of root tips of three-week-old P. trichocarpa seedlings and cuttings were measured using the Microelectrode Ion Flux mEasurement (MIFE) system to demonstrate the activity of AMTs and NRTs under nutrient-abundant and nutrient-deficient conditions. I found mainly N-efflux from roots of cuttings while seedling roots exhibited N-uptake. This is the first report of such a difference. This highlights an unexpected but clear physiological difference between seedling and cutting roots, which are frequently used in experimental setups. / Graduate / 0817 / 0369 / 0715 / neilvonw@gmail.com

Comparative genomics provides a tool to investigate large biological datasets, i.e. genomic datasets. In my thesis I focused on inferring patterns of selection in coding and non-coding regions of avian genomes. Until recently, large comparative studies on selection were mainly restricted to model species with sequenced genomes. This limitation has been overcome with advances in sequencing technologies and it is now possible to gather large genomic data sets for non-model species.  Next-generation sequencing data was used to study patterns of nucleotide substitutions and from this we inferred how selection has acted in the genomes of 10 non-model bird species. In general, we found evidence for a negative correlation between neutral substitution rate and chromosome size in birds. In a follow up study, we investigated two closely related bird species, to study expression levels in different tissues and pattern of selection. We found that between 2% and 18% of all genes were differentially expressed between the two species. We showed that non-coding regions adjacent to genes are under evolutionary constraint in birds, which suggests that noncoding DNA plays an important functional role in the genome. Regions downstream to genes (3’) showed particularly high level of constraint. The level of constraint in these regions was not correlated to the length of untranslated regions, which suggests that other causes play also a role in sequence conservation. We compared the rate of nonsynonymous substitutions to the rate of synonymous substitutions in order to infer levels of selection in protein-coding sequences. Synonymous substitutions are often assumed to evolve neutrally. We studied synonymous substitutions by estimating constraint on 4-fold degenerate sites of avian genes and found significant evolutionary constraint on this category of sites (between 24% and 43%). These results call for a reappraisal of synonymous substitution rates being used as neutral standards in molecular evolutionary analysis (e.g. the dN/dS ratio to infer positive selection). Finally, the problem of sequencing errors in next-generation sequencing data was investigated. We developed a program that removes erroneous bases from the reads. We showed that low coverage sequencing projects and large genome sequencing projects will especially gain from trimming erroneous reads.

Autoimmune diseases are endemic, but the disease mechanisms are poorly understood. A way to better understand these are to find disease-regulating genes. However, this is difficult as the diseases are complex, with several genes as well as environmental factors influencing the development of disease. A way to facilitate the search for genes responsible for the diseases is to use comparative genomic studies. Animal models are relatively easy to analyze since control of environment and breeding are obtained. The University of California at Davies – line 200 (UCD-200) chickens have a hereditary disease that is similar to systemic sclerosis. Using a backcross between UCD-200 chickens and red junglefowl (RJF) chickens we identified three loci linked to the disease. The loci contained immune-regulatory genes suggested to be involved in systemic sclerosis in humans, as well as a previously unidentified linkage between systemic sclerosis in UCD-200 chickens and IGFBP3. The Dark brown (Db) gene enhances red pheomelanin and restricts expression of eumelanin in chickens. The Db phenotype is regulated by an 8 kb deletion upstream of SOX10. Pigmentation studies are potentially useful when trying to identify pathogenic mechanisms and candidate genes in vitiligo The Obese strain (OS) of chickens spontaneously develops an autoimmune thyroiditis which closely resembles human Hashimoto’s thyroiditis. By using an intercross between OS chickens and RJF chickens, we found several disease phenotypes that can be used in an ongoing linkage analysis with the goal to find candidate genes for autoimmune disease. An important phenotype to record and add to the linkage analysis is autoantibodies against thyroid peroxidase, since this phenotype is a key feature in Hashimoto’s thyroiditis. Previous attempts to measure these titres in OS chickens have failed, hence an assay was developed for this purpose.

The genome sequencing projects have generated a wealth of genomic data and the analysis of this data has provided many interesting findings. However, genome wide analysis of bacteria for promoters has lagged behind, because it has been difficult to accurately predict the promoters with so much background noise that are found in bacterial genomes. One approach to overcome this problem is to predict phylogenetically conserved promoters across multiple genomes of different bacteria, thus filtering out many of the false positives, which are predicted by the current methods. However, there are no programmes capable of doing this. Therefore, the work presented in this thesis has developed a position weight matrix (PWM) based programme called Multiscan that predicts conserved promoters across multiple bacterial genomes. Since Chlamydia is one of the most sequenced bacterial genera and has a high level of conservation of genes and large-scale conservation of gene order between species, Multiscan was developed and tested on Chlamydia. When Multiscan analysed a genome wide dataset of equivalent non-coding regions (NCRs) upstream of genes, from Chlamydia trachomatis, Chlamydia pneumoniae and Chlamydia caviae for σ66 promoters that are phylogenetically conserved, Multiscan predicted 42 promoters. Since only one of the 42 promoters predicted by Multiscan had previously available biological data to confirm its prediction, an additional subset of 10 of the remaining 41 σ66 promoters were analysed in C. trachomatis by mapping the 5' end of the transcripts. The primer extension assay synthesised cDNA products of the correct length for seven of the 10 genes chosen. When the performance of Multiscan was compared to one of the accepted method for genome wide prediction of promoters in bacteria, the &quotstandard PWM method", Multiscan predicted 32 more promoters than the &quotstandard PWM method" in Chlamydia. Furthermore, the promoters predicted by Multiscan were up to three more mismatches from the Escherichia coli σ70 consensus sequence than the promoters predicted by the standard PWM method. Although Multiscan predicted 42 promoters that were well conserved across the three chlamydial species, the analysis was unable to identify the 14 known σ66 promoters in C. trachomatis. These promoters were missed (1) because they were dissimilar to the E. coli σ70 consensus sequence and/or (2) because the promoters were poorly conserved across the three chlamydial species. To address the second possibility, the 14 false negatives were analysed by another phylogenetic footprinting method. Fourteen sets of equivalent NCRs located upstream of the homologous genes from the three chlamydiae were aligned with the computer programme Clustal W and the alignment analysed &quotby eye" for evidence of phylogenetic footprints containing the 14 false negatives. The analysis identified that seven of the 14 false negatives were poorly conserved across the chlamydial species. Analysis of two of the seven promoters that could not be footprinted, the promoters of ltuA and ltuB, by mapping the transcriptional start sites in C. caviae, confirmed their poor conservation across C. trachomatis and C. caviae. This analysis showed that substantial differences exist in chlamydial σ66 promoters from equivalent NCRs upstream of genes. This study has developed a new computer programme for genome wide prediction of promoters that are phylogenetically conserved and has shown the value of this programme by identifying seven new well conserved promoters and seven candidate poorly conserved promoters in Chlamydia.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Understanding transcriptional regulation quantitatively is a crucial step towards uncovering and ultimately utilizing the regulatory semantics encoded in the genome. Transcription of a gene is induced by the binding of site-specific transcription factors (TFs) to so-called cis-regulatory-modules (CRMs). The frequency and duration of the binding events are influenced by the concentrations of the TFs, the binding affinities and location of the transcription factor binding sites (TFBSs) in the CRM as well as the properties of the TFs themselves (e.g. effectiveness, competitive interaction with other TFs). Modeling these interactions using a mathematical approach, based on sound biochemical and thermodynamic foundations, enables the understanding and quantitative prediction of transcriptional output of a target gene. In the thesis I introduce the developed framework for modeling, visualizing, and predicting the regulation of the transcription rate of a target gene. Given the concentrations of a set of TFs, the TFBSs in a regulatory DNA region, and the transcription rate of the target gene, the method will optimize its parameters to generate a predictive model that incorporates the regulatory mechanism of the observed gene. I demonstrate the generalization ability of the model by subjecting it to standard machine learning and hypothesis testing procedures. Furthermore, I demonstrate the potential of the approach by training the method on a gene in D. melanogaster and predicting the output of the homologous genes in 12 other Drosophila species where the regulatory sequence has evolved substantially but the regulatory mechanism was conserved. Finally, I investigate the proposed role-switching behaviour of TFs regulating the development of D. melanogaster, which suggests that SUMOylation is the biological mechanism facilitating the switch.

Submitted by Amanda Carolina Paulino de Oliveira (amanda@posgrad.fcav.unesp.br) on 2018-07-30T23:45:45Z No. of bitstreams: 1 Dissertação final - ACPO - Versão online.pdf: 8789441 bytes, checksum: a845ac98a1435e414423acdc29c30ff5 (MD5) / Approved for entry into archive by Karina Gimenes Fernandes null (karinagi@fcav.unesp.br) on 2018-07-31T11:04:06Z (GMT) No. of bitstreams: 1 oliveira_acp_me_iabo.pdf: 8789441 bytes, checksum: a845ac98a1435e414423acdc29c30ff5 (MD5) / Made available in DSpace on 2018-07-31T11:04:06Z (GMT). No. of bitstreams: 1 oliveira_acp_me_iabo.pdf: 8789441 bytes, checksum: a845ac98a1435e414423acdc29c30ff5 (MD5) Previous issue date: 2018-07-04 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Xanthomonas citri subsp. citri 306 (XccA) é o agente causal do cancro cítrico (CC), doença endêmica que afeta a citricultura. Durante a interação patógeno-hospedeiro o sistema de secreção tipo três (SST3) codificado pela XccA age na translocação de efetores e no estabelecimento da doença. A montagem do aparato de SST3 depende da síntese, remodelagem e degradação da parede celular bacteriana, sendo este processo realizado pela ação enzimática de transglicosilases líticas de mureína (LTs). XccA codifica diversas LTs, porém, pouco é conhecido sobre a diversidade de famílias e relação com a virulência. Dentre as LTs com provável relação com a virulência, duas ORFs parálogas presentes no cromossomo e plasmídeo pXAC64, respectivamente; são genes passageiros do TnXax1, um transposon da família Tn3, relacionado a evolução e emergência da patogenicidade nas Xanthomonadales. Portanto, este estudo objetivou elucidar o provável papel e diversidade das LTs presentes no genoma de XccA, caracterizando funcionalmente as LTs presentes em TnXax1 pela técnica de mutação sítio dirigida. Foram identificadas no genoma de XccA 13 LTs, sendo 12 pertencentes às famílias: 1A, 1B, 1C, 1D, 1F, 1G, 3A, 3B (2 cópias), 5A e 6A, e uma não classificada. A LT não classificada, é exclusiva do gênero Xanthomonas e relacionada à família 3B, porém contém um domínio adicional relacionado ao metabolismo de carboidratos. As LTs classificadas em famílias apresentam provável função relacionada com a remodelagem da parede celular para inserção de sistemas de secreção tipo 3, 4 e 6, inserção de flagelo, divisão celular, reciclagem da parede celular e degradação e controle da produção do peptidoglicano. As LTs do TnXax1 pertencem a família 3B, não são essenciais para XccA e desenvolvimento do CC, porém estão relacionadas ao aumento da virulência, diminuição da formação de biofilme, agregação e aumento na produção de goma xantana, corroborando o papel do TnXax1 como agente propagador da patogenicidade e virulência em Xanthomonadales. Em resumo, os resultados lançam novos conhecimentos frente ao papel das LTs com o metabolismo do peptidoglicano e relação com os mecanismos de transferência lateral, virulência e patogenicidade de XccA. / Xanthomonas citri subsp. citri 306 (XccA) is a causal agent of type A citrus canker (CC), one of the most devastating citriculture diseases. Type 3 Secretion Systems (T3SS) play a fundamental role in XccA pathogenicity. T3SS components are embedded in the bacterial inner and outer membrane and act as a channel for injection of effector proteins directly into the plant host cell cytosol. T3SS assembly and installation relies on bacterial cell wall synthesis, remodeling and degradation. Murein lytic transglycosylases (LT) are important in this process and are responsible for peptidoglycan cleavage and its remodeling. Information about the XccA LT arsenal is scarce: little is known about family diversity, their exact role and their connection to virulence in this bacterium. Among the LTs with probable relation to virulence, two paralogue ORFs (one in chromosome, one in pXAC64 plasmid) are passenger genes of the Tn3 family transposon TnXax1, known to play a significant role for evolution and emergence of pathogenicity in Xanthomonadales. This study addresses LT diversity in the XccA genome and examines the role of plasmid and chromosomal TnXax1 LT passenger genes using site-directed deletion mutagenesis and functional characterization. We identified 13 XccA LTs: 12 belong to families 1A, 1B, 1C, 1D (2 copies), 1F, 1G, 3A, 3B (2 copies), 5A, 6A and one which is non-categorized. This noncategorized gene, is exclusive to the Xanthomonas genus and related to the 3B family but contains an additional domain linked to carbohydrate metabolism, whilst the other catalyzes peptidoglycan biosynthesis, and is widely distributed in gammaproteobacteria. The categorized LTs are probably involved in cell wall remodeling to allow insertion of type 3, 4 and 6 secretion systems, flagellum assembly, division and recycling of cell wall and degradation and control of peptidoglycan production. The TnXax1 passenger LTs (3B family) are not essential to XccA and CC development but are implicated in virulence, biofilm production and aggregation decrease and xanthan gum production increase, corroborating the role of TnXax1 transposon as a virulence and pathogenicity propagating agent in XccA. These findings also suggest that LTs acquisition by horizontal gene transfer mediated by TnXax1 improved bacterial fitness, bringing adaptive advantages to the plant-pathogen interaction process. / 33004102070P6