Étude de l’évolution des génomes par duplications, pertes et réarrangements

La duplication est un des évènements évolutifs les plus importants, car elle peut mener à la création de nouvelles fonctions géniques. Durant leur évolution, les génomes sont aussi affectés par des inversions, des translocations (incluant des fusions et fissions de chromosomes), des transpositions et des délétions. L'étude de l'évolution des génomes est importante, notamment pour mieux comprendre les mécanismes biologiques impliqués, les types d'évènements qui sont les plus fréquents et quels étaient les contenus en gènes des espèces ancestrales. Afin d'analyser ces différents aspects de l'évolution des génomes, des algorithmes efficaces doivent être créés pour inférer des génomes ancestraux, des histoires évolutives, des relations d'homologies et pour calculer les distances entre les génomes. Dans cette thèse, quatre projets reliés à l'étude et à l'analyse de l'évolution des génomes sont présentés : 1) Nous proposons deux algorithmes pour résoudre des problèmes reliés à la duplication de génome entier : un qui généralise le problème du genome halving aux pertes de gènes et un qui permet de calculer la double distance avec pertes. 2) Nous présentons une nouvelle méthode pour l'inférence d'histoires évolutives de groupes de gènes orthologues répétés en tandem. 3) Nous proposons une nouvelle approche basée sur la théorie des graphes pour inférer des gènes in-paralogues qui considère simultanément l'information provenant de différentes espèces afin de faire de meilleures prédictions. 4) Nous présentons une étude de l'histoire évolutive des gènes d'ARN de transfert chez 50 souches de Bacillus.Gene duplication is one of the most important types of events affecting genomes during their evolution because it can create novel gene function. During the evolution process, genomes are also affected by inversions, translocations (including chromosome fusions and fissions), transpositions and deletions. Studying the evolution of genomes is important to get a better understanding of the biological mechanisms involved, which types of events are more frequent than others and what was the gene content in the ancestral species just to name a few. In order to analyze these different aspects of genome evolution, efficient algorithms need to be developed to infer ancestral genomes, evolutionary histories, homology relationships between genes and to compute distances between genomes. In this thesis, four different projects related to the study and analysis of genome evolution are presented: 1) We developed two algorithms to solve problems related to whole genome duplication: one that generalizes the genome halving problem to gene losses, and one that allows to compute the double distance with losses. 2) We developed a new method to infer evolutionary histories of orthologous tandemly arrayed gene clusters. 3) We proposed a new graph-theoretic approach to infer inparalogs that simultaneously considers the information given by multiple species in order to make better inferences of inparalogous gene pairs. 4) We studied the evolutionary history of the tRNA genes of 50 Bacillus strains

Reconstruction of ancestral RNA sequences under multiple structural constraints

Abstract Background Secondary structures form the scaffold of multiple sequence alignment of non-coding RNA (ncRNA) families. An accurate reconstruction of ancestral ncRNAs must use this structural signal. However, the inference of ancestors of a single ncRNA family with a single consensus structure may bias the results towards sequences with high affinity to this structure, which are far from the true ancestors. Methods In this paper, we introduce achARNement, a maximum parsimony approach that, given two alignments of homologous ncRNA families with consensus secondary structures and a phylogenetic tree, simultaneously calculates ancestral RNA sequences for these two families. Results We test our methodology on simulated data sets, and show that achARNement outperforms classical maximum parsimony approaches in terms of accuracy, but also reduces by several orders of magnitude the number of candidate sequences. To conclude this study, we apply our algorithms on the Glm clan and the FinP-traJ clan from the Rfam database. Conclusions Our results show that our methods reconstruct small sets of high-quality candidate ancestors with better agreement to the two target structures than with classical approaches. Our program is freely available at: http://csb.cs.mcgill.ca/acharnement

Additional file 1 of Reconstruction of ancestral RNA sequences under multiple structural constraints

The file contains the algorithms of CalculateScores-1struct and CalculateScores- 2structs. It is followed by the running times of Fitch, Sankoff, CalculateScores-1struct and CalculateScores- 2structs on the simulated data sets. It also contains the list of bacterial strains used in the biological analysis. We also present additional results on the Glm and FinP-traJ clans reconstructions. (425 KB PDF

The effective reproductive number: Modeling and prediction with application to the multi-wave Covid-19 pandemic

Classical compartmental models of infectious disease assume that spread occurs through a homogeneous population. This produces poor fits to real data, because individuals vary in their number of epidemiologically-relevant contacts, and hence in their ability to transmit disease. In particular, network theory suggests that super-spreading events tend to happen more often at the beginning of an epidemic, which is inconsistent with the homogeneity assumption. In this paper we argue that a flexible decay shape for the effective reproductive number (Rt) indexed by the susceptible fraction (St) is a theory-informed modeling choice, which better captures the progression of disease incidence over human populations. This, in turn, produces better retrospective fits, as well as more accurate prospective predictions of observed epidemic curves. We extend this framework to fit multi-wave epidemics, and to accommodate public health restrictions on mobility. We demonstrate the performance of this model by doing a prediction study over two years of the SARS-CoV2 pandemic

Violence conjugale commise et subie : profils personnologiques de personnes avec un trouble de personnalité limite

Objectif Les troubles de la personnalité et la violence conjugale (VC) sont deux problématiques reconnues comme des enjeux majeurs en santé publique associées à de graves répercussions individuelles et sociétales. Plusieurs études ont documenté les liens entre le trouble de personnalité limite (TPL) et la VC, mais nous en connaissons très peu quant aux traits pathologiques spécifiques contribuant à la VC. L’étude vise à documenter le phénomène de VC commise et subie chez des personnes souffrant de TPL et à dresser des profils à partir des facettes de la personnalité du Modèle alternatif pour les troubles de la personnalité du DSM-5.Méthode Cent huit participants/participantes avec un TPL (83,3 % femmes ; Mâge = 32,39, É.-T. = 9) référées à un programme d’hôpital de jour à la suite d’un épisode de crise ont rempli une batterie de questionnaires comprenant les versions françaises du Revised Conflict Tactics Scales, évaluant la VC psychologique et physique, commise et subie, et du Personality Inventory for the DSM-5 — FacetedBrief Form, évaluant 25 facettes pathologiques de la personnalité.Résultats Parmi les participants/participantes, 78,7 % rapportent avoir déjà commis de la VC psychologique, alors que 68,5 % en auraient été victimes, ce qui est plus que les estimations publiées par l’Organisation mondiale de la santé (27 %). De plus, 31,5 % auraient commis de la VC physique, alors que 22,2 % en auraient été victimes. La VC semble bidirectionnelle puisque 85,9 % des personnes ayant commis de la VC psychologique rapportent aussi en subir et 52,9 % des personnes ayant commis de la VC physique rapportent en être également victimes. Des comparaisons de groupes non paramétriques indiquent que les facettes Hostilité, Méfiance, Duplicité, Prise de risques et Irresponsabilité distinguent les personnes violentes physiquement et psychologiquement des personnes non violentes. Des résultats élevés aux facettes Hostilité, Dureté/Insensibilité, Manipulation et Prise de risque caractérisent les participants/participantes victimes de VC psychologique, alors qu’une élévation aux facettes Hostilité, Retrait, Évitement de l’intimité et Prise de risque et un résultat faible à la facette Tendance à la soumission distinguent les participants/participantes victimes de VC physique des non-victimes. Des analyses de régression mettent en évidence que la facette Hostilité explique à elle seule une variance significative des résultats de VC commise, alors que la facette Irresponsabilité contribuerait de façon substantielle à la variance des résultats de VC subie.Conclusion Les résultats font état de la prévalence élevée de VC chez des personnes aux prises avec un TPL ainsi que de son caractère bidirectionnel. Au-delà du diagnostic de TPL, certaines facettes spécifiques de la personnalité (dont l’Hostilité et l’Irresponsabilité) permettent de cibler les personnes plus à risque de commettre de la VC psychologique et physique et d’en subir.Objective Personality disorders and intimate partner violence (IPV) are two problems recognized as major public health issues associated with serious individual and societal repercussions. Several studies have documented the links between borderline personality disorder (BPD) and IPV; however, we know very little about the specific pathological traits contributing to IPV. The study aims to document the phenomenon of IPV committed and suffered in persons with BPD and to draw profiles from the personality facets of the DSM-5 Alternative Model for Personality Disorders (AMPD).Method One hundred and eight BPD participants (83.3% female; Mage = 32.39, SD = 9.00) referred to a day hospital program following a crisis episode completed a battery of questionnaires including the French versions of the Revised Conflict Tactics Scales, evaluating physical and psychological IPV committed and suffered, and the Personality Inventory for the DSM-5- Faceted Brief Form, evaluating 25 pathological facets of personality.Results Among the participants, 78.7% report having committed psychological IPV, while 68.5% have been victims, which is more than the estimates published by the World Health Organization (27%). In addition, 31.5% would have committed physical IPV, while 22.2% would have been victims. IPV appears to be bidirectional since 85.9% of participants who are perpetrators of psychological IPV also report suffering from it and 52.9% of participants who are perpetrators of physical IPV report being also victims. Nonparametric group comparisons indicate that Hostility, Suspiciousness, Duplicity, Risk-Taking, and Irresponsibility facets distinguish physically and psychologically violent participants from nonviolent participants. High results on Hostility, Callousness, Manipulation, and Risk-taking facets characterize participants who are victims of psychological IPV, while an elevation in Hostility, Withdrawal, Avoidance of intimacy, and Risk-taking facets and a low result on the Submission facet distinguish participants who are victims of physical IPV from non-victims. Regression analyzes show that the Hostility facet alone explains a significant variance in the results of IPV perpetrated, while the Irresponsibility facet contributes substantially to the variance of the results of IPV experienced.Conclusion Results show the high prevalence of IPV in a sample of persons with BPD, as well as its bidirectional nature. Beyond the diagnosis of BPD, certain specific facets of the personality (including Hostility and Irresponsability) make it possible to target persons at greater risk of committing and suffering from psychological and physical IPV

Evolution of orthologous tandemly arrayed gene clusters

<p>Abstract</p> <p>Background</p> <p>Tandemly Arrayed Gene (TAG) clusters are groups of paralogous genes that are found adjacent on a chromosome. TAGs represent an important repertoire of genes in eukaryotes. In addition to tandem duplication events, TAG clusters are affected during their evolution by other mechanisms, such as inversion and deletion events, that affect the order and orientation of genes. The DILTAG algorithm developed in <abbrgrp><abbr bid="B1">1</abbr></abbrgrp> makes it possible to infer a set of optimal evolutionary histories explaining the evolution of a single TAG cluster, from an ancestral single gene, through tandem duplications (simple or multiple, direct or inverted), deletions and inversion events.</p> <p>Results</p> <p>We present a general methodology, which is an extension of DILTAG, for the study of the evolutionary history of a set of orthologous TAG clusters in multiple species. In addition to the speciation events reflected by the phylogenetic tree of the considered species, the evolutionary events that are taken into account are simple or multiple tandem duplications, direct or inverted, simple or multiple deletions, and inversions. We analysed the performance of our algorithm on simulated data sets and we applied it to the protocadherin gene clusters of human, chimpanzee, mouse and rat.</p> <p>Conclusions</p> <p>Our results obtained on simulated data sets showed a good performance in inferring the total number and size distribution of duplication events. A limitation of the algorithm is however in dealing with multiple gene deletions, as the algorithm is highly exponential in this case, and becomes quickly intractable.</p