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Most phylogenetic trees are inferred using time-reversible evolutionary models that assume that the relative rates of substitution for any given pair of nucleotides are the same regardless of the direction of the substitutions. However, there is no reason to assume that the underlying biochemical mutational processes that cause substitutions are similarly symmetrical. Here, we evaluate the effect on phylogenetic inference in empirical viral and simulated data of incorporating non-reversibility into models of nucleotide substitution processes. I consider two non-reversible nucleotide substitution models: (1) a 6-rate nonreversible model (NREV6) that is applicable to analyzing mutational processes in double-stranded genomes in that complementary substitutions occur at identical rates; and (2) a 12-rate non-reversible model (NREV12) that is applicable to analyzing mutational processes in single-stranded (ss) genomes in that all substitution types are free to occur at different rates. Using likelihood ratio and Akaike Information Criterion-based model tests, we show that, surprisingly, NREV12 provided a significantly better fit than the General Time Reversible (GTR) and NREV6 models to 21/31 dsRNA and 20/30 dsDNA datasets. As expected, however, NREV12 provided a significantly better fit to 24/33 ssDNA and 40/47 ssRNA datasets. I tested how non-reversibility impacts the accuracy with which phylogenetic trees are inferred. As simulated degrees of non-reversibility (DNR) increased, the tree topology inferences using both NREV12 and GTR became more accurate, whereas inferred tree branch lengths became less accurate. I conclude that while non-reversible models should be helpful in the analysis of mutational processes in most virus species, there is no pressing need to use these models for routine phylogenetic inference. Finally, I introduce a web application, RpNRM, that roots phylogenetic trees using a non-reversible nucleotide substitution model. The phylogenetic tree is rooted on every branch and the likelihoods of each rooting are determined and compared with the highest likelihood tree being identified as that with the most plausible rooting. The rooting accuracy of RpNRM was compared to that of the outgroup rooting method, the midpoint rooting method and another non-reversible model-based rooting method implemented in the program IQTREE. I find that although the RpNRM and IQTREE reversible model-based methods are not as accurate on their own as outgroup or midpoint rooting methods, they nevertheless provide an independent means of verifying the root locations that are inferred by these other methods.

Le genre Quercus comprend plus de 500 espèces et est réparti sur l’ensemble de l’hémisphère nord. La phylogénie du genre, faite à ce jour à partir d’un nombre très limité de marqueurs nucléaires, n’était pas résolue. Des incertitudes demeuraient au niveau des nœuds profonds où ont divergé les principaux groupes taxonomiques aujourd’hui reconnus. L’objectif de cette thèse était d’explorer de manière plus exhaustive les ressources génomiques nucléaires et chloroplastiques pour affiner la phylogénie du genre. Les travaux sont basés sur les séquences de six gènes nucléaires et de l’ensemble du génome chloroplastique. Ces travaux confirment le caractère diffus du signal phylogénétique et le gain de résolution obtenu par l’adjonction de séquences nouvelles. Ils confirment également la subdivision du genre en six groupes infragénériques (Cyclobalanopsis, Ilex, Cerris, Lobatae, Quercus s.s. et Protobalanus), dont les relations phylogénétiques ont été précisées, même si certaines irrésolutions persistent. La thèse met très clairement en évidence l’empreinte phylogéographique dans le génome chloroplastique au niveau du genre et de sa distribution mondiale. Le signal phylogéographique chloroplastique ajouté à la phylogénie nucléaire permet d’échafauder un scénario biogéographique de diversification du genre. Ce scénario devra être corroboré par des apports d’autres disciplines (paléontologie et géologie historique). / The genus Quercus comprises more than 500 species, and is widely distributed across the Northern hemisphere. Phylogenetic reconstructions based on traditional molecular sequences were so far irresolutive at the deeper nodes where the major extant taxonomic groups have diverged. This thesis aims at improving the phylogeny of the genus by exploring the current nuclear and chloroplastic genomic resources. The phylogenetic investigations are based on sequences of six nuclear genes and the entire chloroplastic genome. The results confirm that the phylogenetic signal is rather diluted and that substantial improvements can be obtained by adding sequences from additional genes. They also confirm that the genus can be subdivided in six infrageneric groups (Cyclobalanopsis, Ilex, cerris, Lobatae, Quercus s.s. et Protobalanus). Phylogenetic relationships among these groups are refined, although not fully clarified. There is a very clear phylogeographic imprint in the chloroplast genome that extends at the macroevolutionary level at the whole genus across its entire distribution. The phylogeographic structure together with the phylogeny at the nuclear level allows to elaborate an historical scenario of the radiation of the genus. Additional elements coming from other disciplines (paleontology, historical geology) are however necessary to confirm this scenario.

Un des buts principaux de la biologie évolutive et de la médecine moléculaire consiste à reconstruire les relations phylogénétiques entre organismes à partir de leurs séquences moléculaires. En littérature, cette question est connue sous le nom d’inférence phylogénétique et a d'importantes applications dans la recherche médicale et pharmaceutique, ainsi que dans l’immunologie, l’épidémiologie, et la dynamique des populations. L’accumulation récente de données de séquences d’ADN dans les bases de données publiques, ainsi que la facilité relative avec laquelle des données nouvelles peuvent être obtenues, rend l’inférence phylogénétique particulièrement difficile (l'inférence phylogénétique est un problème NP-Hard sous tous les critères d’optimalité connus), de telle manière que des nouveaux critères et des algorithmes efficaces doivent être développés. Cette thèse a pour but: (i) d’analyser les limites mathématiques et biologiques des critères utilisés en inférence phylogénétique, (ii) de développer de nouveaux algorithmes efficaces permettant d’analyser de plus grands jeux de données.

Tumour development has long been recognised as an evolutionary process during which cells accumulate mutations and evolve into a mix of genetically distinct cell subpopulations. The resulting genetic intra-tumour heterogeneity poses a major challenge to cancer therapy, as it increases the chance of drug resistance. To study tumour evolution in more detail, reliable approaches to infer the life histories of tumours are needed. This dissertation focuses on computational methods for inferring trees of tumour evolution from single-cell and multi-sample sequencing data. Recent advances in single-cell sequencing technologies have promised to reveal tumour heterogeneity at a much higher resolution, but single-cell sequencing data is inherently noisy, making it unsuitable for analysis with classic phylogenetic methods. The first part of the dissertation describes OncoNEM, a novel probabilistic method to infer clonal lineage trees from noisy single nucleotide variants of single cells. Simulation studies are used to validate the method and to compare its performance to that of other methods. Finally, OncoNEM is applied in two case studies. In the second part of the dissertation, a comprehensive collection of existing multi-sample approaches is used to infer the phylogenies of metastatic breast cancers from ten patients. In particular, shallow whole-genome, whole exome and targeted deep sequencing data are analysed. The inference methods comprise copy number and point mutation based approaches, as well as a method that utilises a combination of the two. To improve the copy number based inference, a novel allele-specific multi-sample segmentation algorithm is presented. The results are compared across methods and data types to assess the reliability of the different methods. In summary, this thesis presents substantial methodological advances to understand tumour evolution from genomic profiles of single cells or related bulk samples.

Os caranguejos de água doce estão alocados em cinco famílias e apenas duas tem ocorrência para o Brasil: Pseudothelphusidae e Trichodactylidae. Trichodactylus , gênero-tipo da família Trichodactylidae e alocado em Trichodactylinae, foi descrito por Latreille, 1828 para acomodar uma única espécie, T. fluviatilis. Baseado na hipótese de que Trichodactylus não é um grupo monofilético foi realizada uma extensiva amostragem morfológica e molecular. A Inferência filogenética com dois genes mitocondriais (16S rRNA e COI) e um nuclear (Histona 3) mostrou claramente que Trichodactylus não é monofilético. Foram encontradas três grandes linhagens em ambas as análises (Inferência Bayesiana e Máxima Verossimilhança), sendo T. quinquedentatus mais proximamente relacionado com espécies de Avotrichodactylus. O tempo de divergência entre essas linhagens foi estimado em 38 a 53 Ma. Nesse estudo, dez novas espécies pertencentes ao complexo Trichodactylus foram descritas. Adicionalmente, uma espécie e um gênero revalidado. Nesse estudo, portanto, a subfamília Trichodactylinae é composta pelos seguintes gêneros: Avotrichodactylus , Mikrotrichodactylus , Rodriguezia e Trichodactylus . Além disso, a designação de neótipo para T. fluviatilis é de fundamental importância, uma vez que, a série tipo foi perdida. O uso em conjunto e comparativo de diferentes ferramentas, tais como a molecular e morfológica, permitiu reconhecer que a biodiversidade de caranguejos de água doce no Brasil ainda está subestimada / The freshwater crabs are allocated in five families and only two of them have occurrence for Brazil: Pseudothelphusidae and Trichodactylidae. Trichodactylus , the genus-type of the family Trichodactylidae and allocated in Trichodactylinae, was described by Latreille, 1828 to accommodate a single species, T. fluviatilis. Based on the hypothesis that Trichodactylus is not a monophyletic group we realized an extensive morphological and molecular sampling. Phylogenetic inference based on two mitochondrial (16S rRNA e COI) and one nuclear (Histone 3) genes clearly indicated that Trichodactylus is not monophyletic. Were found three great lineages in both analysis (Bayesian Inference and Maximum Likelihood), being T. quinquedentatus more closely related to species of Avotrichodactylus . The time of divergence between these lineages was estimated at 38 to 53 Ma. In this study, nine new species belonging to the T. fluviatilis complex were described. Additionally, one species and one genus were revalidated. Therefore, in this study, the subfamily Trichodactylinae is composed by the following genus: Avotrichodactylus , Mikrotrichodactylus , Rodriguezia e Trichodactylus . Furthermore, we show that the designation of a neotype for T. fluviatilis is strongly needed, since that its type series has been lost. The joint and comparative use of different tools, such as molecular and morphological, allowed us to recognize that the biodiversity of freshwater crabs in Brazil is still very underestimated

One of the most relevant issues in the field of biology is the unveiling of the evolutionary history of different species and organisms. The evolutionary relationships of these species and organisms are explained by constructing phylogenetic trees whose leaves represent species and whose internal nodes represent hypothesized ancestors. The tree reconstruction process is known as Phylogenetic Inference. Phylogenies can be used not only for explaining the evolutionary history of organisms but also for many other purposes such as the design of new drugs by tracking the evolution of diseases. In the last few years, the amount of genetic data collected from organisms and species has increased greatly. Based on this, biologists have sought methods that are capable of computing phylogenies of small, medium, and even large datasets in a reasonable time and with accuracy. The neighbor-joining method is one used most for phylogenetic inference because of its computation efficiency. Since the increase of datasets, novel neighbor-joining- based approaches have been developed with the goal of computing efficiency and accurate phylogenies of thousands of sequences. Therefore, this study compared the canonical neighbor-joining method represented by MEGA software with two novel neighbor-joining-based approaches--the NINJA method and the FastTree method--to identify the most efficient and effective method for the computational performance, topological accuracy, and topological similarity through the scalability of the sequences size. The study was accomplished by executing experiments using small, medium, and large protein and nucleotide sequences. The FastTree method was the most successful at balancing the trade-off among the Computational Performance, Topological Accuracy, and Topological Similarity when scaling up the number of sequences in this study.

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Central to the study of Life is knowledge both about the underlying relationships among living things and the processes that have molded them into their diverse forms. Phylogenetics provides a powerful toolkit for investigating both aspects. Bayesian phylogenetics has gained much popularity, due to its readily interpretable notion of probability. However, the posterior probability of a phylogeny, as well as any dependent biological inferences, is conditioned on the assumed model of evolution and its priors, necessitating care in model formulation. In Chapter 1, I outline the Bayesian perspective of phylogenetic inference and provide my view on its most outstanding questions. I then present results from three studies that aim to (i) improve the accuracy of Bayesian phylogenetic inference and (ii) assess when the model assumed in a Bayesian analysis is insufficient to produce an accurate phylogenetic estimate. As phylogenetic data sets increase in size, they must also accommodate a greater diversity of underlying evolutionary processes. Partitioned models represent one way of accounting for this heterogeneity. In Chapter 2, I describe a simulation study to investigate whether support for partitioning of empirical data sets represents a real signal of heterogeneity or whether it is merely a statistical artifact. The results suggest that empirical data are extremely heterogeneous. The incorporation of heterogeneity into inferential models is important for accurate phylogenetic inference. Bayesian phylogenetic estimates of branch lengths are often wildly unreasonable. However, branch lengths are important input for many other analyses. In Chapter 3, I study the occurrence of this phenomenon, identify the data sets most likely to be affected, demonstrate the causes of the bias, and suggest several solutions to avoid inaccurate inferences. Phylogeneticists rarely assess absolute fit between an assumed model of evolution and the data being analyzed. While an approach to assessing fit in a Bayesian framework has been proposed, it sometimes performs quite poorly in predicting a model’s phylogenetic utility. In Chapter 4, I propose and evaluate new test statistics for assessing phylogenetic model adequacy, which directly evaluate a model’s phylogenetic performance. / text