Synonymous codon usage bias has been extensively studied in Bacteria and Eukaryotes and yet there has been little investigation in the third domain of life, the Archaea. In this thesis I therefore examine the coding sequences of nearly 70 species of Archaea to explore patterns of codon bias. Heterogeneity in codon usage among genes was initially explored for a single species, Methanococcus maripaludis, where patterns were explained by a single major trend associated with expression level and attributed to natural selection. Unlike the bacterium Escherichia coli, selection was largely restricted to two-fold degenerate sites. Analyses of patterns of codon usage bias within genomes were extended to the other species of Archaea, where variation was more commonly explained by heterogeneity in G+C content and asymmetric base composition. By comparison with bacterial genomes, far fewer trends were found to be associated with expression level, implying a reduced prevalence of translational selection among Archaea. The strength of selected codon usage bias (S) was estimated for 67 species of Archaea, and revealed that natural selection has had less impact in shaping patterns of codon usage across Archaea than across many species of Bacteria. Variation in S was explained by the combined effects of growth rate and optimal growth temperature, with species growing at high temperatures exhibiting weaker than expected selection given growth rate. Such a relationship is expected if temperature kinetically modulates growth rate via its impact upon translation elongation, since rapid elongation rates at high temperatures reduce the selective benefit of optimal codon usage for the efficiency of translation. Consistent with this, growth temperature is negatively correlated with minimal generation time, and numbers of rRNA operons and tRNA genes are reduced at high growth temperatures. The large fraction of thermophilic Archaea relative to Bacteria account for the lower values of S observed. Two major trends were found to describe variation in codon usage among archaeal genomes; the first was attributed to GC3s and the second was associated with arginine codon usage and was linked both with growth temperature and the genome-wide excess of G over C content. The latter is unlikely to reflect thermophilic adaptation since the codon primarily underlying the trend appears to be selectively disfavoured. No correlations were observed with genome wide GC3s and optimal growth temperature and neither was GC3s associated with aerobiosis. The identities of optimal codons were explored and found to be invariant across U and C-ending two-fold degenerate amino acid groups. The identity of optimal codons and anticodons across four and six-fold degenerate amino acid groups was found to vary with mutational bias. As was first observed in M. maripaludis, selected codon usage bias was consistently greater across two-fold relative to four-fold degenerate amino acid groups across Archaea. This broad pattern could reflect ancestral patterns of optimal codon divergence, prevalent among four-fold but not two-fold degenerate amino acid groups. Consistent with this, the strength of selected codon usage bias was found to be reduced following the divergence of optimal codons, and implies that optimal codon divergence typically proceeds following the relaxation of selection. Finally, a method was developed to partition the strength of selection (S) into separate components reflecting selection for translational efficiency (Seff) and selection for translational accuracy (Sacc) by comparing the codon usage across conserved and nonconserved amino acid residues. While estimates of Sacc are somewhat sensitive to the designation of conserved sites, a general pattern emerged whereby accuracy-selected codon usage bias was consistently strongest across a subset of the most highly conserved sites. Several estimates of Sacc were consistently higher than the 95% range of null values regardless of the dataset, providing evidence for accuracy-selected codon usage bias in these species.

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The genetic code is redundant, with most amino acids coded by multiple codons. In many organisms, codon usage is biased towards particular codons. A variety of adaptive and non-adaptive explanations have been proposed to explain these patterns of codon usage bias. Using mechanistic models of protein translation and population genetics, I explore the relative importance of various evolutionary forces in shaping these patterns. This work challenges one of the fundamental assumptions made in over 30 years of research: codons with higher tRNA abundances leads to lower error rates. I show that observed patterns of codon usage are inconsistent with selection for translation accuracy. I also show that almost all the variation in patterns of codon usage in S. cerevisiae can be explained by a model taking into account the effects of mutational biases and selection for efficient ribosome usage. In addition, by sampling suboptimal mRNA secondary structures at various temperatures, I show that melting of ribosomal binding sites in a special class of mRNAs known as RNA thermometers is a more general phenomenon.

In this study we have focused on the codon usage bias in E. coli. In chapter 3, we use the population genetics model and the data available on the protein and mRNA levels of the E. coli genes to understand the pattern of codon usage in different genes with different expression levels and see which measure best explains the codon usage pattern. Besides codon bias, by testing for the over-parametrization of the model, we are able to test for the existence of context dependent mutation. We have also fitted the model for the codon usage patter in the Yeast and also tested for the context dependent mutation in this organism. In chapter 4, we focus on the first 10-15 codons in the genes of E. coli. Motivated by the fact that in this region we observe two phenomena, reduction in translation efficiency and suppression of mRNA secondary structures, we investigate whether the former is a side effect of selection for the latter. For this matter we have generated a set of synonymous randomized sequences, and then by selecting the ones which show weak secondary structures in the mentioned region, we would be able to test the theory. We will also look at the frequencies of the amino acids in E. coli genes and see whether the selection for weak secondary structures in the translation initiation region could be strong enough to not only affect the codon usage, but also the choice of amino acids. We would also provide information on the correlation between the strength of the mRNA secondary structure in the first 13 codons and the overall translation efficiency of the genes. / Thesis / Master of Science (MSc)

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Le code génétique est la table de correspondance entre codons (unité structurelle d'un gène) et acides aminés (brique élémentaire des protéines). Le code génétique est (1) universel, tous les êtres vivants ou presque partagent le même code; (2) univoque, chaque codon spécifie un seul acide aminé et (3) dégénéré, les acides aminés peuvent être codés par plusieurs codons. Ce code dégénéré est donc utilisé par l'ensemble du vivant mais pas de la même manière, certains codons synonymes étant utilisés préférentiellement chez des espèces et pas d'autres. Pour comprendre l'émergence des biais d'usage du code (BUC) génétique entre espèces, je me place dans un contexte évolutif.Dans ce manuscrit, je présente mes travaux de recherche en quatre parties. La première partie introductive décrit la mise en évidence et les propriétés du code génétique, son biais d'usage et les diverses caractéristiques de précédents modèles de codons. La deuxième partie présente le modèle d'évolution de codons SENCA pour Sites Evolution at the Nucleotides, Codons and Amino-acids layers que j'ai développé durant ma thèse. SENCA prend en compte la structure du code génétique. Je valide sa paramétrisation par des simulations numériques et une étude sur des espèces bactériennes ou archées. La partie suivante décrit deux extensions de SENCA qui modélisent plusieurs hypothèses d'origines évolutives du BUC et une application de SENCA sur les conséquences génomiques d'adaptations environnementales. La dernière partie étudie les origines de variations de BUC le long du génome humain par une approche de génomique comparative / In this manuscript, I introduce my doctoral research in four parts. The first introductive part highlights the properties of the genetic code and its usage bias but also the caracteristics of previous published codons models. The second part presents an evolutionary codons models named SENCA for Sites Evolution at the Nucleotides, Codons and Amino-acids layers that I developped. SENCA takes into account the genetic code structure. I perform simulations and study prokaryotes species to confirm its parametrization. The following part provides two extensions of SENCA to test the hypotheses concerning the evolutive origins of CUB and an application of SENCA to study the genomic consequences of an environmental adaptation. The last part studies the origins of CUB variation within the human genome using a comparative genomic strategy

Although codon usage bias has been shown to persist through non-random mutations and selection, many avenues of research into the applications of codon usage bias have remained unexplored. In this dissertation, we present several new applications of codon usage bias and their practical uses in a phylogenetic construct. We first review the literature and provide background into other software applications of codon usage bias in Chapter 1. In Chapter 2, we show that in tetrapods, codon aversion in orthologs is phylogenetically conserved. We further this analysis in Chapter 3 by exploring codon use and aversion across the Tree of Life, providing frameworks for other researchers to analyze different species subsets. We present a novel algorithm to recover species relationships using codon aversion, without regard to orthologous relationships in Chapter 4. We present several other algorithms in Chapter 5 to also recover species relationships using biases in codon pairing. Chapter 6 analyzes the relationship between codon usage bias in viruses that infect humans and proteins found in tissues that they infect. In Chapter 7, we present our discovery of a conservation in coding sequence lengths in orthologous genes that allowed us to accurately recover orthologous gene relationships and reduce overall ortholog identification runtime by over 96%. In Chapter 8 we discuss a novel algorithm for extracting a ramp of slowly-translated codons located at the beginning of gene sequences, allowing researchers to quickly identify translational bottlenecks. Finally, Chapter 9 touches on future applications of codon usage bias in phylogenetics. This dissertation represents a major vertical leap in phylogenetics by providing a framework and paradigm shift toward utilizing codon usage and coding sequence length biases in future analyses.

In evolution alternative genetic trajectories can potentially lead to similar phenotypic outcomes. However, certain trajectories are preferred over others. These preferences bias the genomes of living organisms and the underlying processes can be observed in ongoing evolution. We have studied a variety of biases that can be found in bacterial chromosomes and determined the selective causes and functional consequences for the cell. We have quantified codon usage bias in highly expressed genes and shown that it is selected to optimise translational speed. We further demonstrated that the resulting differences in decoding speed can be used to regulate gene expression, and that the use of ‘non-optimal’ codons can be detrimental to reading frame maintenance. Biased gene location on the chromosome favours recombination between genes within gene families and leads to co-evolution. We have shown that such recombinational events can protect these gene families from inactivation by mobile genetic elements, and that chromosome organization can be selectively maintained because inversions can lead to the formation of unstable hybrid operons. We have used the development of antibiotic resistance to study how different bacterial lifestyles influence evolutionary trajectories. For this we used two distinct pairs of antibiotics and disease-causing bacteria, namely (i) Mycobacterium tuberculosis that is treated with rifampicin and (ii) Escherichia coli that is treated with ciprofloxacin. We have shown that in the slow-growing Mycobacterium tuberculosis, resistance mutations are selected for high-level resistance. Fitness is initially less important, and over time fitness costs can be ameliorated by compensatory mutations. The need for rapid growth causes the selection of ciprofloxacin resistance in Escherichia coli not only to be selected on the basis of high-level resistance but also on high fitness. Compensatory evolution is therefore not required and is not observed. Taken together, our results show that the evolution of a phenotype is the product of multiple steps and that many factors influence which trajectory is the most likely to occur and be most beneficial. Over time, selection will favour this particular trajectory and lead to biased evolution, affecting genome sequence and organization.