Na última década tem sido possível reconstruir o genoma de bactérias e arquéias presentes em comunidades microbianas de ambientes naturais a partir de dados metagenômicos. Isso tem revolucionado nosso entendimento sobre a topologia da árvore da vida e a descoberta de novas capacidades metabólicas, bem como auxiliado na identificação mais acurada de genes de interesse industrial, visto que os dados estão mais completos e menos fragmentados. Com base neste contexto, o objetivo geral deste projeto foi reconstruir o genoma de bactérias ligadas a degradação de biomassa vegetal em comunidades microbianas da compostagem, focando em análises de diversidade de enzimas de Glicosil Hidrolases (GHs), a partir de dados de sequências metagenômicas gerados no projeto temático processo 11/50870-6. Para alcançar os nossos objetivos, foram desenvolvidos pipelines computacionais com softwares já disponíveis na literatura e foram utilizados dois conjuntos principais de dados de sequenciamento massivo (um conjunto de dados seriados que engloba inúmeros estágios do processamento da compostagem e um conjunto de dados do metagenoma de um consórcio microbiano celulolítico e termofílico construído a partir de amostras da compostagem). Foram reconstruídos 13 genomas (sete genomas em amostras dos dados seriados e seis genomas na amostra do consórcio microbiano), sendo identificado no mínimo quatro novas espécies. As análises baseadas em filogenômica indicam a presença de pelo menos uma nova classe dentro do filo Firmicutes, uma nova espécie da família Paenibacillaceae e a reconstrução pela primeira vez do genoma da espécie Bacillus thermozeamaize. Também foram identificadas 33 lacunas/ilhas metagenômicas (IMs). Essas regiões apresentaram genes diretamente ligados a biossíntese de polissacarídeos do envelope celular, pseudogenes e proteínas hipotéticas. Algumas dessas proteínas estão diretamente ligadas ao reconhecimento de bacteríofagos durante a fase de infecção viral. A presença de IMs também indica uma divergência entre as populações microbianas presentes na compostagem com a espécie de referência. Quanto ao potencial de degradação de biomassa vegetal, todos os microrganismos apresentam genes com potencial para degradação de material lignocelulolítico durante o processamento de diferentes estágios da compostagem, indicando a importância do papel funcional dessas bactérias na compostagem. / In the last decade it has been possible to reconstruct Bacteria and Archaea genomes that are in natural microbial communities from metagenomic samples. This has revolutionized our understanding of the topology of the tree of life and the discovery of new metabolic functions, as well as aided in more accurate identification of industrial bioprospecting genes, since the genomic data are more complete and less fragmented. Based on this background, the aim of this project was to reconstruct the bacterial genomes linked to plant biomass degradation in composting communities, focusing on diversity analysis of Glycosyl Hydrolases (GHs) from metagenomic sequence data generated in the Thematic Project (Process 11/50870-6). To achieve our objectives, computational pipelines have been developed (this pipelines were based on software already available in the literature) and we use these pipelines in two massive data sets generated by high-throughput sequencing (one data set of time series compost sample which includes several stages of the composting process and other data set from a cellu- lolytic and thermophilic microbial consortium). Thirteen genomes were reconstructed (seven genomes from time series metagenomic data and six genomes from microbial consortium). At least four new species have been identified, and the analyzes based on phylogenomic inferences indicate the presence of at least one new class of Firmicutes phylum, and a new Paenibacillaceae family and the reconstruction for the first time the Bacillus thermozeamaize genome. They also identified 33 gaps/metagenomic Islands (IMs). These gaps had genes directly linked to polysaccharide biosynthesis of the cell envelope, pseudogenes and hypothetical proteins. Some of these proteins are directly linked to the bacteriophage during the recognition phase of viral infection. The presence of gaps also indicates a divergence between microbial populations present in the compost with the reference genome. All microbial genomes reconstructed in this studyhave genes linked to lignocellulolytic potential degradation during the different stages of composting process, indicating the functional role this bactéria in this environment.

High fidelity double strand break repair is paramount for the maintenance of genome integrity and faithful passage of genetic information to the following generation. Homologous recombination (HR) and non-homologous end joining (C-NHEJ) have evolved as the two major pathways for the efficient and accurate repair of double strand breaks (DSBs). In addition, a minor Ku- and Ligase IV-independent end-joining pathway has been identified and implicated in the formation of chromosomal translocations. This alternative end-joining pathway occurs by bridging the break ends through annealing between short microhomologies, hence the name microhomology-mediated end joining (MMEJ). In addition to these defined DSB repair pathways, a broken DNA end possesses immense mutagenic potential to generate chromosomal rearrangements. Diverse and complex rearrangements are a commonly observed feature amongst cancer cells. The focus of this thesis is to examine the role of Replication Protein A (RPA) in binding single-stranded DNA (ssDNA) repair intermediates to promote error free repair and to prevent mutagenic chromosomal deletions and rearrangements. RPA is a highly conserved, heterotrimeric ssDNA binding protein with a ubiquitous role in all DNA transactions involving ssDNA intermediates. RPA promotes resection at DSBs to facilitate HR and abrogation of this function has severe consequences. Defective RPA can lead to the formation of secondary structures and impair loading of homology search proteins such as Rad52 and Rad51. Using a chromosomal end-joining assay, we demonstrate that hypomorphic rfa1 mutants exhibit elevated frequencies of MMEJ by up to 350-fold. Biochemical characterization of RPAt33 and RPAt48 complexes show these mutants are compromised for their ability to prevent spontaneous annealing and the removal of secondary structures to fully extend ssDNA. These results demonstrate that annealing between MHs defines a critical control to regulate MMEJ repair. Therefore, RPA bound to ssDNA intermediates shields complementary sequences from annealing to promote error-free HR and prevents repair by mutagenic MMEJ, thereby preserving genomic integrity. RPA also impedes intrastrand annealing between short inverted repeat sequences to prevent the formation of foldback structures. Foldbacks have been proposed to drive palindromic gene amplification, a genome destabilizing rearrangement that can disrupt the protein expression equilibrium and is a prevalent phenomenon within tumor cells. Palindromic duplications are elevated ~1000-fold in rfa1-t33 sae2Δ and rfa1-t33 mre11-H125N mutants compared to sae2Δ or mre11-H125N, yet we did not detect these events in the hypomorphic rfa1-t33 mutant. This suggests that Mre11 and Sae2 play critical roles in preventing palindromic amplification through regulation of the Mre11 structure-specific endonuclease to process DNA foldbacks (also called DNA hairpins). Therefore, Mre11-Sae2 together with RPA prevent palindromic gene amplification. Together, these data focus the spotlight on RPA playing active central and supporting roles to sustain genome stability. This additionally raises that notion that secondary structures are potent instigators and mediators of many genome rearrangements and their prevention by RPA is absolutely crucial.

Knowledge of protein-protein interactions (PPIs) is essential to understanding regulatory processes in a cell. High-throughput experimental methods have made significant contributions to PPI determination, but they are known to have many false positives and fail to identify a signification portion of bona fide interactions. The same is true for the many computational tools that have been developed. Significantly, although protein structures provide atomic details of PPIs, they have had relatively little impact in large-scale PPI predictions and there has been only limited overlap between structural and systems biology. Here in this thesis, I present our progress in combining structural biology and systems biology in the context of studies analyzing, coarse-grained modeling and prediction of protein-protein interactions. I first report a comprehensive analysis of the degree to which the location of a protein interface is conserved in sets of proteins that share different levels of similarities. Our results show that while, in general, the interface conservation is most significant among close neighbors, it is still significant even for remote structural neighbors. Based on this finding, we designed PredUs, a method to predict protein interface simply by "mapping" the interface information from its structural neighbors (i.e., "templates") to the target structure. We developed the PredUs web server to predict protein interfaces using this "template-based" method and a support vector machine (SVM) to further improve predictions. The PredUs webserver outperforms other state-of-the-art methods that are typically based on amino acid properties in terms of both prediction precision and recall. Meanwhile, PredUs runs very fast and can be used to study protein interfaces in a high throughput fashion. Maybe more importantly, it is not sensitive to local conformational changes and small errors in structures and thus can be applied to predict interface of protein homology models, when experimental structures are not available. I then describe a novel structural modeling method that uses geometric relationships between protein structures, including both PDB structures and homology models, to accurately predict PPIs on a genome-wide scale. We applied the method with considerable success to both the yeast and the human genomes. We found that the accuracy and the coverage of our structure-based prediction compare favorably with the methods derived from sequence and functional clues, e.g. sequence similarity, co-expression, phylogenetic similarity, etc. Results further improve when using a naive Bayesian classifier to combine structural information with non-structural clues (PREPPI), yielding predictions of comparable quality to high-throughput experiments. Our data further suggests that PREPPI predictions are substantially complementary to those by experimental methods thus providing a way to dissect interactions that would be hard to identify on a purely high-throughput experimental basis. We have for the first time designed a "template-based" method that predicts protein interface with high precision and recall. We have also for the first time used 3D structure as part of the repertoire of experimental and computational information and find a way to accurately infer PPIs on a large scale. The success of PredUs and PREPPI can be attributed to the exploitation of both the information contained in imperfect models and the remote structure-function relationships between proteins that have been usually considered to be unrelated. Our results constitute a significant paradigm shift in both structural and systems biology and suggest that they can be integrated to an extent that has not been possible in the past.

BRCA1 preserves genome integrity through both homology-directed repair (HDR) and stalled fork protection (SFP). In vivo, BRCA1 exists as a heterodimer with the BARD1 tumor suppressor, and both proteins harbor a C-terminal BRCT domain with a phospho-recognition surface. Most pathogenic lesions of BRCA1 and BARD1 disrupt their respective BRCT domains, and BRCA1 BRCT phospho-recognition is required for its tumor suppression activity. Here we evaluate mice with mutations (Bard1S563F and Bard1K607A) that ablate Bard1 BRCT phospho-recognition. Although not affecting HDR, these mutations impair BRCA1/BARD1 recruitment to stalled replication forks, resulting in stalled fork degradation, chromosomal instability, and sensitivity to PARP inhibitors. However, Bard1S563F/S563F and Bard1K607A/K607A mice are not tumor-prone, indicating that ablation of SFP activity alone is insufficient for spontaneous tumor susceptibility. Nevertheless, since SFP, unlike HDR, is also impaired in Brca1/Bard1 heterozygous-mutant cells, SFP and HDR may contribute to distinct stages of tumor development in BRCA1/BARD1 mutation carriers.

Na última década tem sido possível reconstruir o genoma de bactérias e arquéias presentes em comunidades microbianas de ambientes naturais a partir de dados metagenômicos. Isso tem revolucionado nosso entendimento sobre a topologia da árvore da vida e a descoberta de novas capacidades metabólicas, bem como auxiliado na identificação mais acurada de genes de interesse industrial, visto que os dados estão mais completos e menos fragmentados. Com base neste contexto, o objetivo geral deste projeto foi reconstruir o genoma de bactérias ligadas a degradação de biomassa vegetal em comunidades microbianas da compostagem, focando em análises de diversidade de enzimas de Glicosil Hidrolases (GHs), a partir de dados de sequências metagenômicas gerados no projeto temático processo 11/50870-6. Para alcançar os nossos objetivos, foram desenvolvidos pipelines computacionais com softwares já disponíveis na literatura e foram utilizados dois conjuntos principais de dados de sequenciamento massivo (um conjunto de dados seriados que engloba inúmeros estágios do processamento da compostagem e um conjunto de dados do metagenoma de um consórcio microbiano celulolítico e termofílico construído a partir de amostras da compostagem). Foram reconstruídos 13 genomas (sete genomas em amostras dos dados seriados e seis genomas na amostra do consórcio microbiano), sendo identificado no mínimo quatro novas espécies. As análises baseadas em filogenômica indicam a presença de pelo menos uma nova classe dentro do filo Firmicutes, uma nova espécie da família Paenibacillaceae e a reconstrução pela primeira vez do genoma da espécie Bacillus thermozeamaize. Também foram identificadas 33 lacunas/ilhas metagenômicas (IMs). Essas regiões apresentaram genes diretamente ligados a biossíntese de polissacarídeos do envelope celular, pseudogenes e proteínas hipotéticas. Algumas dessas proteínas estão diretamente ligadas ao reconhecimento de bacteríofagos durante a fase de infecção viral. A presença de IMs também indica uma divergência entre as populações microbianas presentes na compostagem com a espécie de referência. Quanto ao potencial de degradação de biomassa vegetal, todos os microrganismos apresentam genes com potencial para degradação de material lignocelulolítico durante o processamento de diferentes estágios da compostagem, indicando a importância do papel funcional dessas bactérias na compostagem. / In the last decade it has been possible to reconstruct Bacteria and Archaea genomes that are in natural microbial communities from metagenomic samples. This has revolutionized our understanding of the topology of the tree of life and the discovery of new metabolic functions, as well as aided in more accurate identification of industrial bioprospecting genes, since the genomic data are more complete and less fragmented. Based on this background, the aim of this project was to reconstruct the bacterial genomes linked to plant biomass degradation in composting communities, focusing on diversity analysis of Glycosyl Hydrolases (GHs) from metagenomic sequence data generated in the Thematic Project (Process 11/50870-6). To achieve our objectives, computational pipelines have been developed (this pipelines were based on software already available in the literature) and we use these pipelines in two massive data sets generated by high-throughput sequencing (one data set of time series compost sample which includes several stages of the composting process and other data set from a cellu- lolytic and thermophilic microbial consortium). Thirteen genomes were reconstructed (seven genomes from time series metagenomic data and six genomes from microbial consortium). At least four new species have been identified, and the analyzes based on phylogenomic inferences indicate the presence of at least one new class of Firmicutes phylum, and a new Paenibacillaceae family and the reconstruction for the first time the Bacillus thermozeamaize genome. They also identified 33 gaps/metagenomic Islands (IMs). These gaps had genes directly linked to polysaccharide biosynthesis of the cell envelope, pseudogenes and hypothetical proteins. Some of these proteins are directly linked to the bacteriophage during the recognition phase of viral infection. The presence of gaps also indicates a divergence between microbial populations present in the compost with the reference genome. All microbial genomes reconstructed in this studyhave genes linked to lignocellulolytic potential degradation during the different stages of composting process, indicating the functional role this bactéria in this environment.

Porcine Reproductive and Respiratory Syndrome (PRRS) is, globally, one of the costliest of diseases to the pig industry. Despite enormous efforts, methods such as vaccination strategies and herd management have failed to fully control the disease. Exploiting the genetic variation in host response could be included as part of a multifaceted approach to mitigate the devastating impact of this disease. Establishing the presence of genetic variation and its underlying genetic architecture are key to implementing genomic selection, which is considered a viable and safe long-term disease control strategy. This thesis explores the effect of natural PRRSV outbreaks on the reproductive performance of sows, and the underlying genetic influences on it. Litter records were available from two farms, where Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) outbreaks had been confirmed using ELISA. One farm had full pedigree information, but for both farms 60K SNP genotypes were available. In both farms, performance records could be partitioned into an epidemic and non-epidemic phase using a previously established threshold method. The partitioning also identified a period of high reproductive failure not coinciding with a diagnosed PRRSV outbreak on one farm. This period was isolated and analysed separately. Linear mixed models were used to explore both genetic and non-genetic factors contributing to differences in reproductive performance associated with the two phases. This analysis identified five disease indicator traits identified showing significant differences (>95% CI) in least squares means between the epidemic and non-epidemic phase. These were the number of mummified, stillborn, dead and alive piglets per litter and the fraction of the total born dead. Alternative statistical models that accounted for differences in the severity of the individual PRRSV outbreaks were also considered throughout. Despite differences in the estimates associated with different models and farms, in general very low heritability estimates were obtained for these disease indicator traits during the non-epidemic phase, whereas the traits were found moderately heritable during the epidemic phase. Two genome wide association analyses methods were used to explore the distribution of the genetic effects throughout the genome: Family-based Score Test for Association (FASTA) and Genome-wide Rapid Analysis using Mixed Model and Regression (GRAMMAR). In addition, regional associations were studied using Regional Heritability Mapping (RHM). Associations were then further characterised using Measured Genotype (MG) analyses. Genome-wide significant associations were identified for five SNPs and one region. The regional association spans the region previously identified in an experimental challenge experiment of growing pigs, in association with viral load and weight gain. Different patterns of linkage disequilibrium (LD) are observed which may explain why this study and others failed to find single SNP effects at this location. One genome wide significant SNP on SSC15 was found between two previously identified SNPs associated with PRRSV mortality. Five further putative SNP associations are indicated by RHM and subsequent measured genotype analysis, two of which flank previously reported associations and indicate an epistatic effect, observed in several traits. In summary, this study showed that reproductive performance of sow is considerably reduced during PRRSV outbreaks and the genetics of the sow significantly affects variance in survival and mortality. Several novel genomic regions associated with the reproductive performance of sows in the absence and during PRRSV outbreaks have been identified in this study. In addition to these, the results suggest the region on SSC4 previously associated with PRRSV viral load and weight gain may also affect foetal mortality. These results demonstrate the potential for genomic selection to be used to mitigate PRRSV related reproductive losses, the greatest financial exposure faced by the pig industry. In addition, RHM is directly shown to capture genetic variance, where single SNP methods fail to identify an effect, highlighting the usefulness of this tool as a method to identify genomic regions with significant effect on production traits.

Seleção balanceadora é definida como aquela que aumenta a variabilidade genética de populações em relação ao esperado sob neutralidade. Uma expectativa sobre seus efeitos é a redução da diferenciação populacional nos genes onde atua. Contudo, regimes que mantêm conjuntos distintos de alelos em diferentes populações poderiam resultar em aumento de diferenciação populacional. Com o objetivo de compreender melhor os efeitos da seleção balanceadora sobre a distribuição da variação genética entre populações, investigamos a diferenciação populacional em genes dos Antígenos Leucocitários Humanos (HLA, do inglês, Human Leukocyte Antigen), que são os genes mais polimórficos do genoma humano e o exemplo mais clássico de seleção balanceadora em humanos. As proteínas HLA são responsáveis pela apresentação de peptídeos aos linfócitos T, mediando uma etapa crítica da resposta imune. A vantagem da manutenção de variação nesses genes está possivelmente associada à capacidade de resposta a uma maior diversidade de patógenos. Neste estudo, analisamos dados do projeto 1000 Genomas (1000G), que sequenciou indivíduos de diferentes populações usando sequenciamento de nova geração (NGS, do inglês, Next Generation Sequencing). Essa técnica de sequenciamento é conhecidamente problemática quando aplicada a regiões altamente polimórficas, como os genes HLA. Por isso, avaliamos a confiabilidade dos genótipos e frequências alélicas estimados a partir dos dados do 1000G nos genes HLA, utilizando como padrão ouro dados de sequenciamento Sanger de 930 das 1092 amostras do 1000G. Encontramos um viés de superestimativa da frequência do alelo referência em alguns polimorfismos de nucleotídeo único (SNPs, do inglês, Single Nucleotide Polimorphisms), indicando que viés de mapeamento é uma causa importante de erros nos dados do 1000G. Esses resultados são relevantes para a compreensão dos desafios do uso de dados de NGS em outras regiões de alta diversidade. Usando os resultados dessa análise, excluímos de nosso estudo de diferenciação populacional sítios com estimativas de frequências alélicas pouco confiáveis nos dados do 1000G. Em uma segunda etapa de controle metodológico, demonstramos o efeito do uso de dados ricos em variantes raras em estudos de diferenciação populacional. Controlando para esse efeito, e usando apenas sítios que demonstramos ser confiáveis em nossos dados, descobrimos que a diferenciação populacional de SNPs nos genes HLA é menor que a diferenciação de SNPs em outras regiões do genoma. Esse resultado aponta para um papel predominante de pressões seletivas globais na distribuição da variação genética de HLA entre populações. Contudo, apresentamos também evidências de que a diferenciação populacional de haplótipos nos genes HLA pode ser maior do que a observada no nível dos SNPs, sugerindo que pressões locais podem influenciar a distribuição de haplótipos entre populações. Nossos achados indicam que é possível reconciliar baixa diferenciação populacional em SNPs com maior diferenciação em haplótipos, possivelmente sujeitos a pressões seletivas locais. / Balancing selection is defined as any kind of selective regime that increases genetic variability in populations relative to what is expected under neutrality. Theory predicts that balancing selection reduces population differentiation. However, balancing selection regimes in which different sets of alleles are maintained in different populations could increase population differentiation. To better understand the effects of balancing selection on the distribution of genetic variation among populations, we investigated population differentiation at the Human Leukocyte Antigen (HLA) genes, which are the most polymorphic genes in the human genome, and constitute the most striking example of balancing selection in humans. The HLA molecules are responsible for the presentation of peptides to T cells, thus mediating a critical step of the immune response. The advantage of maintaining variation in those genes through balancing selection is possibly related to the increased ability of the immune system to respond to a wider variety of pathogens. In this study, we analysed the public dataset of the 1000 Genomes project (1000G), which sequenced 1092 individuals from different populations using Next Generation Sequencing (NGS) technologies. These sequencing techniques are known to be problematic when applied to highly polymorphic genomic regions, such as the HLA genes. Therefore, we evaluated the reliability of genotype calls and allele frequency estimates of the SNPs reported by 1000G at HLA genes, using Sanger sequencing data of 930 of the 1092 1000G samples as a gold standard. We found a bias towards overestimation of reference allele frequency for some single nucleotide polymorphisms (SNPs), indicating mapping bias is an important cause of error in frequency estimation in the 1000G data. These results provide insights into the challenges of using of NGS data at other genomic regions of high diversity. Using the results of this analysis, we selected a list of sites that have reliable allele frequency estimates in the 1000G data to be used in our population differentiation study. In another methodological control, we demonstrate the effect of using a dataset rich in rare variants in population differentiation studies. Controlling for this effect, and using only the sites which we demonstrated that were reliable, we found that population differentiation of single nucleotide polymorphisms (SNPs) at the HLA genes is lower than that of SNPs in other genomic regions. This suggests a predominant role of global selective pressures in shaping the distribution of variation at the HLA genes among populations. However, we also show evidence that population differentiation of HLA haplotypes may be higher than what we observe at the SNP level, suggesting that local selective pressures may influence the distribution of haplotypes among populations. Altogether, our results indicate that it is possible to reconcile low population differentiation at the SNP level - as predicted by theory - to higher differentiation at haplotypes, which are possibly under local selective pressures.

Thesis (M.S.)--University of Delaware, 2006. / Principal faculty advisor: Calvin L. Keeler, Dept. of Animal & Food Sciences. Includes bibliographical references.

Thesis (M.S.)--University of Wyoming, 2008. / Title from PDF title page (viewed on Mar. 4, 2010). Includes bibliographical references (p. 65-72).

Thesis (Ph.D)--Biology, Georgia Institute of Technology, 2007. / Committee Chair: John F. McDonald ; Committee Members: Jung Choi, King Jordan, and Soojin Yi. Part of the SMARTech Electronic Thesis and Dissertation Collection.