Search

Your search keyword '"Guillaume Achaz"' showing total 18 results
Start Over Author "Guillaume Achaz" Publisher hal ccsd
18 results on '"Guillaume Achaz"'

1. Simulation of bacterial populations with SLiM

Author

Guillaume Achaz, Flora Jay, Benjamin C. Haller, Jean Cury, Laboratoire de Recherche en Informatique (LRI), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Cornell University [New York], Éco-Anthropologie (EAE), Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), TAckling the Underspecified (TAU), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), BioInformatique (BioInfo), Laboratoire Interdisciplinaire des Sciences du Numérique (LISN), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Science des Données (SDD), Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Éco-Anthropologie (EA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Jay, Flora, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0106 biological sciences, Computer science, Population genetics, Genomic data, Distributed computing, [SDV.GEN] Life Sciences [q-bio]/Genetics, computer.software_genre, 010603 evolutionary biology, 01 natural sciences, 03 medical and health sciences, Documentation, Protocol (object-oriented programming), [SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology, SLiM, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], 030304 developmental biology, Flexibility (engineering), 0303 health sciences, [SDV.GEN]Life Sciences [q-bio]/Genetics, SIMPLE (military communications protocol), Bacteria, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Scripting language, Key (cryptography), Simulator, [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], computer, Simulation
Abstract

Simulation of genomic data is a key tool in population genetics, yet, to date, there is no forward-in-time simulator of bacterial populations that is both computationally efficient and adaptable to a wide range of scenarios. Here we demonstrate how to simulate bacterial populations with SLiM, a forward-in-time simulator built for eukaryotes. SLiM has gained many users in recent years, due to its speed and power, and has extensive documentation showcasing various scenarios that it can simulate. This paper focuses on a simple demographic scenario, to explore unique aspects of modeling bacteria in SLiM’s scripting language. In addition, we illustrate the flexibility of SLiM by simulating the growth of bacteria on a Petri dish with antibiotic. To foster the development of bacterial simulations based upon this recipe, we explain the inner workings of its code. We also validate the simulator, by extensively testing the results of simulations against existing simulators, and against theoretical expectations for some summary statistics. This protocol, with the flexibility and power of SLiM, will enable the community to simulate bacterial populations efficiently under a wide range of evolutionary scenarios.

Published
2021
Full Text
View/download PDF

2. The rapid divergence of the Antarctic crinoid species Promachocrinus kerguelensis

Author

Yacine Ben Chehida, Guillaume Achaz, Cyril Gallut, Marc Eléaume, Groningen Institute for Evolutionary Life Sciences [Groningen] (GELIFES), University of Groningen [Groningen], Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), and Fontaine lab

Subjects
0106 biological sciences, Species complex, Lineage (evolution), Speciation, [SDV]Life Sciences [q-bio], Biodiversity, Allopatric speciation, Biology, 010603 evolutionary biology, 01 natural sciences, 03 medical and health sciences, Genetic drift, Species delimitation, 14. Life underwater, Endemism, Southern Ocean, Promachocrinus kergulensis, 030304 developmental biology, 0303 health sciences, Ecology, Florometra mawsoni, Marine invertebrates, Crinoid, biology.organism_classification, Crinoids, "apparent" drift, Cryptic species, Recent divergence, [SDE]Environmental Sciences
Abstract

Climatic oscillations in Antarctica caused a succession of expansion and reduction of the ice sheets covering the continental shelf of the Southern Ocean. For marine invertebrates, these successions are suspected to have driven allopatric speciation, endemism and the prevalence of cryptic species, leading to the so-called Antarctic ‘biodiversity pump’ hypothesis. Here we took advantage of the recent sampling effort influenced by the International Polar Year (2007-8) to test for the validity of this hypothesis for 1,797 samples of two recognized crinoid species:Promachocrinus kerguelensisandFlorometra mawsoni. Species delimitation analysis identified seven phylogroups. As previously suggested,Promachocrinus kerguelensisforms a complex of six cryptic species. Conversely, despite the morphological differences, our results show thatFlorometra mawsoniis a lineage nested withinPromachocrinus kerguelensis. It suggests thatFlorometra mawsoniandPromachocrinus kerguelensisbelong to the same complex of species. Furthermore, this study indicates that over time and space the different sectors of the Southern Ocean show a remarkable rapid turn-over in term of phylogroups composition and also of genetic variants within phylogroups. We argue that strong “apparent” genetic drift causes this rapid genetic turn-over. Finally, we dated the last common ancestor of all phylogroups at less than 1,000 years, raising doubts on the relevance of the Antarctic “biodiversity pump” for this complex of species. This work is a first step towards a better understanding of how life is diversifying in the Southern Ocean.

Published
2020

3. The quiescent X, the replicative Y and the Autosomes

Author

Serge Gangloff, Benoit Arcangioli, Guillaume Achaz, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Dynamique du Génome - Dynamics of the genome, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), This work was supported by the grants ANR-13-BSV8-0018 and ANR-12-BSV7-0012 Demochips from the Agence Nationale de la Recherche (France) to BA and GA, respectively., ANR-13-BSV8-0018,quiescenceDNA,stabilité génétique en quiescence(2013), ANR-12-BSV7-0012,demochips,Inférence de l'histoire démographique à partie des grands jeux de données de polymorphisme A.D.N.(2012), Gangloff, Serge, Blanc 2013 - stabilité génétique en quiescence - - quiescenceDNA2013 - ANR-13-BSV8-0018 - Blanc 2013 - VALID, BLANC - Inférence de l'histoire démographique à partie des grands jeux de données de polymorphisme A.D.N. - - demochips2012 - ANR-12-BSV7-0012 - BLANC - VALID, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), This work was supported by the grants ANR-13-BSV8-0018 and ANR-12-BSV7-0012 Demochips from the Agence Nationale de la Recherche(France) to BA and GA, respectively., Muséum national d'Histoire naturelle (MNHN)-École Pratique des Hautes Études (EPHE), Génétique des génomes - Genetics of Genomes (UMR 3525), Département de Génomes et Génétique - Department of Genomes and Genetics, and Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité)

Subjects
Genetics, 0303 health sciences, Mutation, Autosome, Lineage (genetic), [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [SDV]Life Sciences [q-bio], food and beverages, Biology, medicine.disease_cause, [SDV] Life Sciences [q-bio], 03 medical and health sciences, 0302 clinical medicine, Anisogamy, medicine, Human genome, 1000 Genomes Project, Indel, 030217 neurology & neurosurgery, X chromosome, 030304 developmental biology
Abstract

From the analysis of the mutation spectrum in the 2,504 sequenced human genomes from the 1000 genomes project (phase 3), we show that sexual chromosomes (X and Y) exhibit a different proportion of indel mutations than autosomes (A), ranking them X>A>Y. We further show that X chromosomes exhibit a higher ratio of deletion/insertion when compared to autosomes. This simple pattern shows that the recent report that non-dividing quiescent yeast cells accumulate relatively more indels (and particularly deletions) than replicating ones also applies to metazoan cells, including humans. Indeed, the X chromosomes display more indels than the autosomes, having spent more time in quiescent oocytes, whereas the Y chromosomes are solely present in the replicating spermatocytes. From the proportion of indels, we have inferred that de novo mutations arising in the maternal lineage are twice more likely to be indels than mutations from the paternal lineage. Our observation, consistent with a recent trio analysis of the spectrum of mutations inherited from the maternal lineage, is likely a major component in our understanding of the origin of anisogamy.

Published
2020
Full Text
View/download PDF

4. The genomic view of diversification

Author

Julie Marin, Amaury Lambert, Guillaume Achaz, Anton Crombach, Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Éco-Anthropologie (EA), Muséum national d'Histoire naturelle (MNHN)-Centre National de la Recherche Scientifique (CNRS), Artificial Evolution and Computational Biology (BEAGLE), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Probabilités, Statistique et Modélisation (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Éco-Anthropologie (EAE), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2), Laboratoire de Probabilités, Statistiques et Modélisations (LPSM (UMR_8001)), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), and Crombach, Anton

Subjects
0301 basic medicine, 0106 biological sciences, Genetic Speciation, [SDV]Life Sciences [q-bio], introgression, Population genetics, Inference, Diversification (marketing strategy), Biology, phylogeny, 010603 evolutionary biology, 01 natural sciences, species tree, Gene flow, Coalescent theory, 03 medical and health sciences, Genetic drift, Genetic algorithm, Gene, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, coalescent theory, 0303 health sciences, Genome, Hierarchy (mathematics), Models, Genetic, Gene tree, population genetics, Reproductive isolation, [SDV] Life Sciences [q-bio], Tree (data structure), multispecies coalescent, 030104 developmental biology, gene tree, speciation, Evolutionary biology, gene‐based diversification model, gene flow
Abstract

Evolutionary relationships between species are traditionally represented in the form of a tree, called the species tree. The reconstruction of the species tree from molecular data is hindered by frequent conflicts between gene genealogies. A standard way of dealing with this issue is to pos-tulate the existence of a unique species tree where disagreements between gene trees are explained by incomplete lineage sorting (ILS) due to random coalescences of gene lineages inside the edges of the species tree. This paradigm, known as the multi-species coalescent (MSC), is constantly violated by the ubiquitous presence of gene flow revealed by empirical studies, leading to topological incon-gruences of gene trees that cannot be explained by ILS alone. Here we argue that this paradigm should be revised in favor of a vision acknowledging the importance of gene flow and where gene histories shape the species tree rather than the opposite. We propose a new, plastic framework for modeling the joint evolution of gene and species lineages relaxing the hierarchy between the species tree and gene trees. As an illustration, we implement this framework in a mathematical model called the genomic diversification (GD) model based on coalescent theory, with four parameters tuning repli-cation, genetic differentiation, gene flow and reproductive isolation. We use it to evaluate the amount of gene flow in two empirical data-sets. We find that in these data-sets, gene tree distributions are better explained by the best fitting GD model than by the best fitting MSC model. This work should pave the way for approaches of diversification using the richer signal contained in genomic evolution-ary histories rather than in the mere species tree.

Published
2020
Full Text
View/download PDF

5. No HIV-1 molecular evolution on long-term antiretroviral therapy initiated during primary HIV-1 infection

Author

Aude Jary, Lambert Assoumou, Vincent Calvez, Cathia Soulié, Nathalie Désiré, Guillaume Achaz, Romain Palich, Roland Tubiana, Anne Simon, Christine Katlama, Sophie Brouillet, Thuy Van Nguyen, Basma Abdi, Marc-Antoine Valantin, Sophie Sayon, Anne-Geneviève Marcelin, Marc Wirden, Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Service de Virologie [CHU Pitié-Salpêtrière], CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Service de Maladies Infectieuses et Tropicales [CHU Pitié-Salpêtrière], Service de médecine interne [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Gestionnaire, Hal Sorbonne Université, Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de virologie [CHU Pitié-Salpêtrière], and Service des maladies infectieuses et tropicales [CHU Pitié-Salpêtrière]

Subjects
0301 basic medicine, Anti-HIV Agents, [SDV]Life Sciences [q-bio], Immunology, Population, HIV Infections, medicine.disease_cause, Evolution, Molecular, 03 medical and health sciences, 0302 clinical medicine, Molecular evolution, medicine, Humans, Immunology and Allergy, 030212 general & internal medicine, education, Sida, Phylogeny, Retrospective Studies, Mutation, education.field_of_study, Phylogenetic tree, biology, business.industry, Viral Load, biology.organism_classification, Antiretroviral therapy, Virology, 3. Good health, [SDV] Life Sciences [q-bio], 030104 developmental biology, Infectious Diseases, Viral evolution, HIV-1, business, Viral load
Abstract

International audience; Objective: Most studies about HIV-1 molecular evolution have shown the lack of viral evolution on effective antiretroviral therapy (ART), although controversial results have been documented. We therefore aimed to look for evidence of HIV-1 evolution in patients who initiated ART at the time of primary HIV-1 infection (PHI).Design: We included retrospectively 20 patients diagnosed at PHI, treated at the time of acute infection and with subsequent effective long-term suppressive ART (HIV viral load

Published
2020
Full Text
View/download PDF

6. Correction: The landscape of epilepsy-related GATOR1 variants

Author

Johannes R. Lemke, Thomas Dorn, Laura Hernandez-Hernandez, Giuseppe d'Orsi, Eveline Hagebeuk, Annapurna Poduri, Douglas R. NordliJr, Hélène Catenoix, Melanie Jennesson, Veronique Darmency, Kevin Rostasy, Thomas Becher, Laura Licchetta, Peter Uldall, Lysa Boissé Lomax, Bianca Berghuis, Ilona Krey, Gaetan Lesca, Anne de Saint Martin, Boudewijn Gunning, Anne Fabienne Lepine, Renske Oegema, Brigitte Ricard-Mousnier, Sarah Ferrand-Sorbets, Arnaud Biraben, Charles Deckers, An Sofie Schoonjans, Martin Zenker, Simona Balestrini, Inga Talvik, Julitta de Bellescize, Christopher J. Yuskaitis, Georg Dorfmüller, Erik H. Niks, Guillaume Achaz, Laurence Faivre, Pasquale Striano, Shifteh Sattar, Karen Müller-Schlüter, Sanjay M. Sisodiya, Caroline Nava, Pia Zacher, Fabrice Bartolomei, Kristin Lindstrom, Sophie Julia, Eric LeGuern, Thomas Cloppenborg, Rikke S. Møller, Antonio Gambardella, Mathilde Chipaux, Sara Baldassari, Pavel Krsek, Marie Line Jacquemont, Ilse Wegner, Christian Brandt, Barbora Benova, Valerio Conti, Gabrielle Rudolf, Floor E. Jansen, Edouard Hirsch, S. Krithika, Jamel Chelly, Katrien Stouffs, Daniëlle de Jong, Courtney Kiss, Tilman Polster, Eva H. Brilstra, Tommaso Pippucci, Markus Wolff, Cécile Marchal, Giovanni Crichiutti, Kees P.J. Braun, Paolo Tinuper, Stéphanie Baulac, Valentin Sander, Anne-Sophie Lebre, Nienke E. Verbeek, Anna Jansen, Francesca Bisulli, Fabienne Picard, Natasha E. Schoeler, Julien Thevenon, Marjan J. A. van Kempen, Guido Rubboli, Sarah Weckhuysen, Renzo Guerrini, Eleni Panagiotakaki, Meral Balci, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Hôpital Universitaire de Genève, Department of Genetics [Utrecht, the Netherlands], University Medical Center [Utrecht], Children's Hospital A. Meyer, Department of Clinical and Experimental Epilepsy, University College of London [London] (UCL), Molecular Cell Biology, Leiden University Medical Center (LUMC), Danish Epilepsy Centre, Denmark and Aarhus University, Aarhus, Centre Hospitalier Universitaire de La Réunion (CHU La Réunion), Service de Génétique Cytogénétique et Embryologie [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Neurogénétique Moléculaire et Cellulaire, Institut Naltional de la Santé et de la Recherche Médicale, Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Regional Epilepsy Center, Reggio Calabria, Centre de génétique - Centre de référence des maladies rares, anomalies du développement et syndromes malformatifs (CHU de Dijon), Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), FHU TRANSLAD (CHU de Dijon), Département de Sociologie [université de Bourgogne], UFR de sciences humaines [Université de Bourgogne], Université de Bourgogne (UB)-Université de Bourgogne (UB), Service de Neurophysiologie Clinique (CHU Dijon), Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de génétique [Reims], Centre Hospitalier Universitaire de Reims (CHU Reims), Universitair Ziekenhuis Brussel, Equipe GAD (LNC - U1231), Lipides - Nutrition - Cancer [Dijon - U1231] (LNC), Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université de Bourgogne (UB)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Université Bourgogne Franche-Comté [COMUE] (UBFC), Département d'Epilepsie, Sommeil et Neurophysiologie Pédiatrique [HCL, Lyon], Hospices Civils de Lyon (HCL), Institute of Human Genetics, University Hospital Magdeburg, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), University of Southern Denmark (SDU), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Hôpital Universitaire de Genève = University Hospitals of Geneva (HUG), Universiteit Leiden-Universiteit Leiden, Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Muséum national d'Histoire naturelle (MNHN)-École Pratique des Hautes Études (EPHE), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)

Subjects
0303 health sciences, business.industry, Published Erratum, MEDLINE, medicine.disease, computer.software_genre, Spelling, 03 medical and health sciences, Epilepsy, 0302 clinical medicine, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, medicine, Artificial intelligence, business, Psychology, computer, 030217 neurology & neurosurgery, Genetics (clinical), Natural language processing, 030304 developmental biology
Abstract

International audience; The original version of this article contained an error in the spelling of the author Erik H. Niks, which was incorrectly given as Erik Niks. This has now been corrected in both the PDF and HTML versions of the article.

Published
2019
Full Text
View/download PDF

7. Is convergence an evidence for positive selection?

Author

Guillaume Achaz, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and guillemaud, thomas

Subjects
0106 biological sciences, 0303 health sciences, Positive selection, [SDV.BID.EVO]Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], General Medicine, 010603 evolutionary biology, 01 natural sciences, 3. Good health, 03 medical and health sciences, Convergent evolution, [SDV.BID.EVO] Life Sciences [q-bio]/Biodiversity/Populations and Evolution [q-bio.PE], Convergence (relationship), Mathematical economics, Selection (genetic algorithm), 030304 developmental biology, Mathematics
Abstract

International audience; A recommendation of the preprint: Frederic Bertels, Karin J Metzner, Roland R Regoes. Convergent evolution as an indicator for selection during acute HIV-1 infection (2018), bioRxiv, 168260, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/168260

Published
2018
Full Text
View/download PDF

8. A Molecular Portrait of De Novo Genes in Yeasts

Author

Joshua J. Coon, Nikolaos Vakirlis, Dana A. Opulente, Chris Todd Hittinger, Gilles Fischer, Alexander S. Hebert, Guillaume Achaz, Ingrid Lafontaine, Biology of Genomes [LCQB] (LCQB-BiG), Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology (LCQB), Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Biologie Paris Seine (IBPS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Systématique, adaptation, évolution (SAE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Department of Chemistry, and University of Wisconsin-Madison

Subjects
0301 basic medicine, Computational biology, Biology, [SDV.BID.SPT]Life Sciences [q-bio]/Biodiversity/Systematics, Phylogenetics and taxonomy, Conserved sequence, Evolution, Molecular, Fungal Proteins, 03 medical and health sciences, Saccharomyces, 0302 clinical medicine, Intergenic region, Phylogenetics, Genetics, Selection, Genetic, Promoter Regions, Genetic, Molecular Biology, Gene, Ecology, Evolution, Behavior and Systematics, Discoveries, Conserved Sequence, ComputingMilieux_MISCELLANEOUS, Recombination, Genetic, Fungal protein, Base Sequence, Age Factors, Promoter, Phenotype, 030104 developmental biology, Homologous recombination, 030217 neurology & neurosurgery
Abstract

New genes, with novel protein functions, can evolve "from scratch" out of intergenic sequences. These de novo genes can integrate the cell's genetic network and drive important phenotypic innovations. Therefore, identifying de novo genes and understanding how the transition from noncoding to coding occurs are key problems in evolutionary biology. However, identifying de novo genes is a difficult task, hampered by the presence of remote homologs, fast evolving sequences and erroneously annotated protein coding genes. To overcome these limitations, we developed a procedure that handles the usual pitfalls in de novo gene identification and predicted the emergence of 703 de novo gene candidates in 15 yeast species from 2 genera whose phylogeny spans at least 100 million years of evolution. We validated 85 candidates by proteomic data, providing new translation evidence for 25 of them through mass spectrometry experiments. We also unambiguously identified the mutations that enabled the transition from noncoding to coding for 30 Saccharomyces de novo genes. We established that de novo gene origination is a widespread phenomenon in yeasts, only a few being ultimately maintained by selection. We also found that de novo genes preferentially emerge next to divergent promoters in GC-rich intergenic regions where the probability of finding a fortuitous and transcribed ORF is the highest. Finally, we found a more than 3-fold enrichment of de novo genes at recombination hot spots, which are GC-rich and nucleosome-free regions, suggesting that meiotic recombination contributes to de novo gene emergence in yeasts.

Published
2018
Full Text
View/download PDF

9. Comparative Genomics of Tenacibaculum dicentrarchi and 'Tenacibaculum finnmarkense' Highlights Intricate Evolution of Fish-Pathogenic Species

Author

Ruben Avendaño-Herrera, Guillaume Achaz, Jean François Bernardet, Sébastien Bridel, Anne Berit Olsen, Hanne Nilsen, Eric Duchaud, Unité de recherche Virologie et Immunologie Moléculaires (VIM), Institut National de la Recherche Agronomique (INRA), FINALAB, Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Norwegian Veterinary Institute, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE)-Centre National de la Recherche Scientifique (CNRS), Universidad Andrés Bello - UNAB (CHILE), Universidad de Concepción [Chile], Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Norwegian Veterinary Institute [Oslo], Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Universidad Andrés Bello [Santiago] (UNAB), EU EMIDA ERA-NET project 'Control Flavobacteriaceae Infections in European Fish farms', Agence Nationale pour la Recherche [ANR-14-CE19-0020], National Infrastructure 'France Genomique' funded as part of the Investissement d'avenir program managed by Agence Nationale pour la Recherche [ANR-10-INBS-09], Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT, Chile) [FONDECYT 1150695, CONICYT/FONDAP/15110027], and Duchaud, Eric

Subjects
0301 basic medicine, Tenacibaculum, tenacibaculosis, genomes, fish pathogens, virulence, evolution, Genome evolution, Evolution, Fish farming, [SDV]Life Sciences [q-bio], Zoology, Genomics, Biology, Genome, Fish Diseases, 03 medical and health sciences, Flavobacteriaceae Infections, Phylogenetics, Genetics, Animals, 14. Life underwater, Genomes, Sea bass, Fish pathogens, Phylogeny, Ecology, Evolution, Behavior and Systematics, Comparative genomics, Tenacibaculosis, Virulence, Fishes, Genome Report, 030104 developmental biology, Genome, Bacterial
Abstract

Data deposition: All genome sequencing data have been deposited at the European Nucleotide Archive under the accessions GCA_900239455, GCA_900239305, GCA_900239485, GCA_900239185, GCA_900239505, GCA_900239345, and GCA_900239495.; International audience; The genus Tenacibaculum encompasses several species pathogenic for marine fish. Tenacibaculum dicentrarchi and " Tenacibaculum finnmarkense " (Quotation marks denote species that have not been validly named.) were retrieved from skin lesions of farmed fish such as European sea bass or Atlantic salmon. They cause a condition referred to as tenacibaculosis and severe outbreaks and important fish losses have been reported in Spanish, Norwegian, and Chilean marine farms. We report here the draft genomes of the T. dicentrarchi and " T. finnmarkense " type strains. These genomes were compared with draft genomes from field isolates retrieved from Chile and Norway and with previously published Tenacibaculum genomes. We used Average Nucleotide Identity and core genome-based phylogeny as a proxy index for species boundary delineation. This work highlights evolution of closely related fish-pathogenic species and suggests that homologous recombination likely contributes to genome evolution.

Published
2018
Full Text
View/download PDF

10. Quiescence unveils a novel mutational force in fission yeast

Author

Serge Gangloff, Guillaume Achaz, Stefania Francesconi, Adrien Villain, Samia Miled, Claire Denis, Benoit Arcangioli, Génétique des génomes - Genetics of Genomes (UMR 3525), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Dynamique du Génome - Dynamics of the genome, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Atelier de BioInformatique (ABI), Université Pierre et Marie Curie - Paris 6 (UPMC), Institut Pasteur [Paris] (IP), Conseil national de la recherche scientifique du Liban (CNRS Liban), National Council for Scientific Research [Lebanon] (CNRS-L), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), This work was supported by the grants ANR-13-BSV8-0018 and ANR-12-BSV7-0012 Demochips from the Agence Nationale de la Recherche (France) to BA and GA, respectively., ANR-13-BSV8-0018,quiescenceDNA,stabilité génétique en quiescence(2013), ANR-12-BSV7-0012,demochips,Inférence de l'histoire démographique à partie des grands jeux de données de polymorphisme A.D.N.(2012), Génétique des génomes, UMR 3525, Centre National de la Recherche Scientifique (CNRS), Génétique des génomes (GG), Institut Pasteur [Paris], Département de Génomes et Génétique - Department of Genomes and Genetics, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), and Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Time Factors, MESH: Mutation, QH301-705.5, Science, MESH: Selection, Genetic, [SDV]Life Sciences [q-bio], stem cells, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Schizosaccharomyces, evolution, genomics, Selection, Genetic, Biology (General), postmitotic, evolutionary biology, MESH: Time Factors, molecular clock, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, mutations, MESH: Biological Variation, Population, MESH: Schizosaccharomyces, Biological Variation, Population, Genomics and Evolutionary Biology, Mutation, Medicine, Research Article, S. pombe
Abstract

International audience; To maintain life across a fluctuating environment, cells alternate between phases of cell division and quiescence. During cell division, the spontaneous mutation rate is expressed as the probability of mutations per generation (Luria and Delbrü ck, 1943; Lea and Coulson, 1949), whereas during quiescence it will be expressed per unit of time. In this study, we report that during quiescence, the unicellular haploid fission yeast accumulates mutations as a linear function of time. The novel mutational landscape of quiescence is characterized by insertion/deletion (indels) accumulating as fast as single nucleotide variants (SNVs), and elevated amounts of deletions. When we extended the study to 3 months of quiescence, we confirmed the replication-independent mutational spectrum at the whole-genome level of a clonally aged population and uncovered phenotypic variations that subject the cells to natural selection. Thus, our results support the idea that genomes continuously evolve under two alternating phases that will impact on their size and composition.

Published
2017
Full Text
View/download PDF

11. Testing for independence between evolutionary processes

Author

Guillaume Achaz, Joël Pothier, Abdelkader Behdenna, Sophie S. Abby, Amaury Lambert, Adaptation aux milieux extrêmes, Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Atelier de BioInformatique (ABI), Université Pierre et Marie Curie - Paris 6 (UPMC), Génomique évolutive des Microbes / Microbial Evolutionary Genomics, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Systématique, adaptation, évolution (SAE), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Université Pierre et Marie Curie - Paris 6 (UPMC), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), and Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Biology, phylogeny, 03 medical and health sciences, 0302 clinical medicine, statistal test, Genetics, Computer Simulation, Ecology, Evolution, Behavior and Systematics, Independence (probability theory), Probability, Statistical hypothesis testing, Event (probability theory), Phylogenetic tree, Null model, Classification, Biological Evolution, [MATH.MATH-PR]Mathematics [math]/Probability [math.PR], Tree (data structure), 030104 developmental biology, Data Interpretation, Statistical, coevolution, Epistasis, Probability distribution, Algorithm, 030217 neurology & neurosurgery
Abstract

International audience; Evolutionary events co-occurring along phylogenetic trees usually point to complex adaptive phenomena, sometimes implicating epistasis. While a number of methods have been developed to account for co-occurrence of events on the same internal or external branch of an evolutionary tree, there is a need to account for the larger diversity of possible relative positions of events in a tree. Here we propose a method to quantify to what extent two or more evolutionary events are associated on a phylogenetic tree. The method is applicable to any discrete character, like substitutions within a coding sequence or gains/losses of a biological function. Our method uses a general approach to statistically test for significant associations between events along the tree, which encompasses both events inseparable on the same branch, and events genealogically ordered on different branches. It assumes that the phylogeny and themapping of branches is known without errors. We address this problem from the statistical viewpoint by a linear algebra representation of the localization of the evolutionary events on the tree.We compute the full probability distribution of the number of paired events occurring in the same branch or in different branches of the tree, under a null model of independence where each type of event occurs at a constant rate uniformly inthephylogenetic tree. The strengths andweaknesses of themethodare assessed via simulations;we then apply the method to explore the loss of cell motility in intracellular pathogens.

Published
2016
Full Text
View/download PDF

12. MicNeSs: genotyping microsatellite loci from a collection of (NGS) reads

Author

Marie Suez, Sophie Brouillet, Paula Graça, Dominique Higuet, Guillaume Achaz, Abdelkader Behdenna, Evolution des Génomes Eucaryotes (EGE), Evolution Paris Seine, Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Cofiroute and the Parc Naturel Regional de la Haute Vallee de Chevreuse, Demochips from the Agence Nationale de la Recherche (France) [ANR-12-BSV7-0012], Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)

Subjects
0301 basic medicine, Genetics, Genotyping Techniques, Population genetics, Computational Biology, High-Throughput Nucleotide Sequencing, Locus (genetics), Computational biology, [SDV.BID]Life Sciences [q-bio]/Biodiversity, Biology, microsatellite loci, 03 medical and health sciences, 030104 developmental biology, genotyping, Genotype, Microsatellite, Pyrosequencing, Allele, next-generation sequencing (NGS), Genotyping, Ecology, Evolution, Behavior and Systematics, Biotechnology, Microsatellite Repeats
Abstract

International audience; Microsatellites are widely used in population genetics to uncover recent evolutionary events. They are typically genotyped using capillary sequencer, which capacity is usually limited to 9, at most 12 loci for each run, and which analysis is a tedious task that is performed by hand. With the rise of next-generation sequencing (NGS), a much larger number of loci and individuals are available from sequencing: for example, on a single run of a GS Junior, 28 loci from 96 individuals are sequenced with a 30X cover. We have developed an algorithm to automatically and efficiently genotype microsatellites from a collection of reads sorted by individual (e.g. specific PCR amplifications of a locus or a collection of reads that encompass a locus of interest). As the sequencing and the PCR amplification introduce artefactual insertions or deletions, the set of reads from a single microsatellite allele shows several length variants. The algorithm infers, without alignment, the true unknown allele(s) of each individual from the observed distributions of microsatellites length of all individuals. MicNeSs, a python implementation of the algorithm, can be used to genotype any microsatellite locus from any organism and has been tested on 454 pyrosequencing data of several loci from fruit flies (a model species) and red deers (a nonmodel species). Without any parallelization, it automatically genotypes 22 loci from 441 individuals in 11 hours on a standard computer. The comparison of MicNeSs inferences to the standard method shows an excellent agreement, with some differences illustrating the pros and cons of both methods.

Published
2016
Full Text
View/download PDF

13. The Impact of Selection, Gene Conversion, and Biased Sampling on the Assessment of Microbial Demography

Author

Marguerite Lapierre, Eduardo P. C. Rocha, Guillaume Achaz, Camille Blin, Amaury Lambert, Eduardo, Rocha, BLANC - Inférence de l'histoire démographique à partie des grands jeux de données de polymorphisme A.D.N. - - demochips2012 - ANR-12-BSV7-0012 - BLANC - VALID, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Génomique évolutive des Microbes / Microbial Evolutionary Genomics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC), Thales Services, THALES [France], This project was financed by the Centre National de la Recherche Scientifique (CNRS) and the Institut Pasteur. G.A. and M.L. acknowledge support from the grant ANR-12-BSV7-0012 Demochips from the Agence Nationale de la Recherche (France). M.L. is funded by the PhD program Interfaces for Life of the University Pierre and Marie Curie (Paris). C.B. is funded by the PhD program Complexité du Vivant of the University Pierre and Marie Curie (Paris)., ANR-12-BSV7-0012,demochips,Inférence de l'histoire démographique à partie des grands jeux de données de polymorphisme A.D.N.(2012), Institut de Systématique, Evolution, Biodiversité (ISYEB), Muséum National d'Histoire Naturelle (MNHN) - Université Pierre et Marie Curie - Paris 6 (UPMC) - École pratique des hautes études (EPHE) - Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS) - Institut National de la Santé et de la Recherche Médicale (INSERM) - Collège de France, Génomique évolutive des Microbes, Institut Pasteur [Paris] - Centre National de la Recherche Scientifique (CNRS), Laboratoire de Probabilités et Modèles Aléatoires (LPMA), Université Pierre et Marie Curie - Paris 6 (UPMC) - Université Paris Diderot - Paris 7 (UP7) - Centre National de la Recherche Scientifique (CNRS), Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS Paris), Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), and THALES

Subjects
0106 biological sciences, 0301 basic medicine, population size, population genomics, media_common.quotation_subject, Population, Biology, 010603 evolutionary biology, 01 natural sciences, Coalescent theory, Evolution, Molecular, 03 medical and health sciences, Negative selection, Statistics, Genetics, Escherichia coli, Selection, Genetic, education, bacteria, Molecular Biology, [SDV.MP] Life Sciences [q-bio]/Microbiology and Parasitology, Selection Bias, Discoveries, Ecology, Evolution, Behavior and Systematics, Selection (genetic algorithm), Sampling bias, media_common, Selection bias, education.field_of_study, Natural selection, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Models, Genetic, gene conversion, Genetic Variation, Sampling (statistics), natural selection, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Genetics, Population, 030104 developmental biology, 13. Climate action, [SDV.GEN.GPO] Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], Metagenomics, [SDV.MP.BAC] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, Genome, Bacterial
Abstract

International audience; Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present.

Published
2016
Full Text
View/download PDF

14. Mutations of DEPDC5 cause autosomal dominant focal epilepsies

Author

Guillaume Achaz, Emeline Mundwiller, Fabienne Picard, Richard B. Miles, Pierre Thomas, Edouard Hirsch, Pierre Genton, Michel Baulac, Stéphanie Baulac, Saeko Ishida, Eric Noé, Eric LeGuern, Markus Wolff, Christian Marescaux, Gabrielle Rudolf, Evolution des Génomes Eucaryotes (EGE), Evolution Paris Seine, Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), French government, program Investissements d'Avenir [ANR-10-IAIHU-06], Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS)

Subjects
Adult, Exome/genetics, Male, Adolescent, Genotype, Guanine Nucleotide Exchange Factors/genetics, Mutation/genetics, Genetic Linkage, Nonsense mutation, Molecular Sequence Data, Autosomal dominant nocturnal frontal lobe epilepsy, [SDV.BID]Life Sciences [q-bio]/Biodiversity, Biology, Frameshift mutation, Cohort Studies, 03 medical and health sciences, Epilepsy, Young Adult, 0302 clinical medicine, Genetics, medicine, Missense mutation, Humans, Amino Acid Sequence, Child, Exome sequencing, 030304 developmental biology, 0303 health sciences, Sequence Homology, Amino Acid, Genome, Human, Genetic Predisposition to Disease/genetics, Computational Biology, Middle Aged, medicine.disease, NPRL3, DEPDC5, ddc:616.8, Epilepsies, Partial/diagnosis/genetics, Pedigree, Case-Control Studies, Brain/metabolism/pathology, Female, 030217 neurology & neurosurgery
Abstract

International audience; The main familial focal epilepsies are autosomal dominant nocturnal frontal lobe epilepsy, familial temporal lobe epilepsy and familial focal epilepsy with variable foci. A frameshift mutation in the DEPDC5 gene (encoding DEP domain-containing protein 5) was identified in a family with focal epilepsy with variable foci by linkage analysis and exome sequencing. Subsequent pyrosequencing of DEPDC5 in a cohort of 15 additional families with focal epilepsies identified 4 nonsense mutations and 1 missense mutation. Our findings provided evidence of frequent (37%) loss-of-function mutations in DEPDC5 associated with a broad spectrum of focal epilepsies. The implication of a DEP (Dishevelled, Egl-10 and Pleckstrin) domain-containing protein that may be involved in membrane trafficking and/or G protein signaling opens new avenues for research.

Published
2013
Full Text
View/download PDF

15. Evolution of Coding Microsatellites in Primate Genomes

Author

Etienne Loire, Pierre Netter, Dominique Higuet, Guillaume Achaz, Evolution des Génomes Eucaryotes (EGE), Evolution Paris Seine, Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS), Groupement des Entreprises Francaises dans la lutte contre le Cancer (GEFLUC), CNRS through a Projets Exploratoires/Premier Soutien grant, Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS), and COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles et de la Guyane (UAG)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Nice Sophia Antipolis (... - 2019) (UNS)

Subjects
Primates, Context (language use), [SDV.BID]Life Sciences [q-bio]/Biodiversity, Biology, phylogeny, Genome, microsatellites, Evolution, Molecular, 03 medical and health sciences, Open Reading Frames, 0302 clinical medicine, INDEL Mutation, Phylogenetics, Genetics, Coding region, Animals, Humans, primate genomes, Frameshift Mutation, Gene, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, 0303 health sciences, Phylogenetic tree, Genome, Human, Computational Biology, food and beverages, SSR, Human genome, 030217 neurology & neurosurgery, Microsatellite Repeats, Research Article
Abstract

International audience; Microsatellites (SSRs) are highly susceptible to expansions and contractions. When located in a coding sequence, the insertion or the deletion of a single unit for a mono-, di-, tetra-, or penta(nucleotide)-SSR creates a frameshift. As a consequence, one would expect to find only very few of these SSRs in coding sequences because of their strong deleterious potential. Unexpectedly, genomes contain many coding SSRs of all types. Here, we report on a study of their evolution in a phylogenetic context using the genomes of four primates: human, chimpanzee, orangutan, and macaque. In a set of 5,015 orthologous genes unambiguously aligned among the four species, we show that, except for tri- and hexa-SSRs, for which insertions and deletions are frequently observed, SSRs in coding regions evolve mainly by substitutions. We show that the rate of substitution in all types of coding SSRs is typically two times higher than in the rest of coding sequences. Additionally, we observe that although numerous coding SSRs are created and lost by substitutions in the lineages, their numbers remain constant. This last observation suggests that the coding SSRs have reached equilibrium. We hypothesize that this equilibrium involves a combination of mutation, drift, and selection. We thus estimated the fitness cost of mono-SSRs and show that it increases with the number of units. We finally show that the cost of coding mono-SSRs greatly varies from function to function, suggesting that the strength of the selection that acts against them can be correlated to gene functions.

Published
2013
Full Text
View/download PDF

16. Kin discrimination and outer membrane exchange in Myxococcus xanthus : A comparative analysis among natural isolates

Author

Sébastien Wielgoss, Yuen-Tsu Nicco Yu, Olaya Rendueles, Francesca Fiegna, Gregory J. Velicer, Department of Integrative Biology [Zurich], Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Génomique évolutive des Microbes / Microbial Evolutionary Genomics, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), This work was supported by a EU Marie Curie PEOPLE Postdoctoral Fellowship for Career Development grant (FP7‐PEOPLE‐2012‐IEF‐331824) to S.W. and an EMBO Long‐Term Fellowship to O.R., We thank Guillaume Achaz and the three independent reviewers for helpful comments, European Project: 331824,EC:FP7:PEOPLE,FP7-PEOPLE-2012-IEF,MICROSOCIOGENOMYX(2013), and Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Myxococcus xanthus, 030106 microbiology, Population, outer membrane exchange, Biology, Balancing selection, phylogeny, 03 medical and health sciences, Phylogenetics, Genetics, Allele, education, Ecology, Evolution, Behavior and Systematics, Alleles, education.field_of_study, biology.organism_classification, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, behaviour, colony-merger incompatibility, Multicellular organism, 030104 developmental biology, Natural population growth, myxobacteria, sociobiogeography, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Bacterial outer membrane, Bacterial Outer Membrane Proteins
Abstract

Individual data sets for statistical analyses are provided at the Dryad Digital Repository: https://doi.org/10.5061/dryad.m5f7b44. Correspondence and request for materials should be addressed to G.J.V (gregory.velicer@env.ethz.ch) or S.W. (sebastien.wielgoss@env.ethz.ch).; International audience; Genetically similar cells of the soil bacterium Myxococcus xanthus cooperate at multiple social behaviours, including motility and multicellular development. Another social interaction in this species is outer membrane exchange (OME), a behaviour of unknown primary benefit in which cells displaying closely related variants of the outer membrane protein TraA transiently fuse and exchange membrane contents. Functionally incompatible TraA variants do not mediate OME, which led to the proposal that TraA incompatibilities determine patterns of intercellular cooperation in nature, but how this might occur remains unclear. Using natural isolates from a centimetre-scale patch of soil, we analyse patterns of TraA diversity and ask whether relatedness at TraA is causally related to patterns of kin discrimination in the form of both colony-merger incompatibilities (CMIs) and interstrain antagonisms. A large proportion of TraA functional diversity documented among global isolates is predicted to be contained within this cm-scale population. We find evidence of balancing selection on the highly variable PA14-portion of TraA and extensive transfer of traA alleles across genomic backgrounds. CMIs are shown to be common among strains identical at TraA, suggesting that CMIs are not generally caused by TraA dissimilarity. Finally, it has been proposed that interstrain antagonisms might be caused by OME-mediated toxin transfer. However, we predict that most strain pairs previously shown to exhibit strong antagonisms are incapable of OME due to TraA dissimilarity. Overall, our results suggest that most documented patterns of kin discrimination in a natural population of M. xanthus are not causally related to the TraA sequences of interactants.

Published
2018
Full Text
View/download PDF

17. Extensions of the standard neutral model relevant for the analysis of genetic diversity

Author

Lapierre, Marguerite, Institut de Systématique, Evolution, Biodiversité (ISYEB ), Muséum national d'Histoire naturelle (MNHN)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris VI, Guillaume Achaz, Amaury Lambert, STAR, ABES, Muséum national d'Histoire naturelle (MNHN)-Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[SDV.GEN]Life Sciences [q-bio]/Genetics, Génétique des populations, Démographie, Population genetics, Site frequency spectrum, Processus de branchement, [SDV.GEN] Life Sciences [q-bio]/Genetics, Théorie neutraliste, Coalescence, Spectre de fréquence, Demography
Abstract

The general setting of this thesis is the analysis of evolutionary forces that generate polymorphisms and divergence between genomes within a species. The theoretical framework used in the majority of disciplines of molecular evolution is the neutral theory, formulated by Motoo Kimura in 1968. This model is characterized by the hypotheses of neutrality, constant population size and panmixia. First, we investigated how this theoretical framework is used in practice and what are the consequences of these hypotheses on the inferences and predictions made in this framework. To this end, we carried out two studies confronting existing demographic inference methods with data. A first study demonstrated that methods frequently used for bacterial demographic inference, based on a single reconstructed phylogenetic tree, are biased by selection, recombination and sampling bias. We then compared several demographic inference methods, by applying them to an African human population, the Yoruba. This study showed the limits of an existing method, and illustrates the issue of identifiability of demographic histories, when the inference is based on the site frequency spectrum. Finally, in a third study we analyzed several genetic polymorphism datasets with an alternative reference model comprising multiple mergers and demography. We compared how the current reference model and this alternative model can explain the observed genetic diversity., Cette thèse se place dans le cadre de l'analyse des forces évolutives qui génèrent les polymorphismes et les divergences entre les génomes d'une même espèce. Le cadre théorique utilisé dans la majorité des domaines de l'évolution moléculaire est la théorie neutraliste, proposée par Motoo Kimura en 1968. Ce modèle est caractérisé par les hypothèses de neutralité, de taille constante de la population étudiée, et de panmixie. Dans un premier temps nous avons cherché à comprendre comment ce cadre théorique est utilisé en pratique et quelles peuvent être les conséquences de ces hypothèses sur les inférences et les prédictions faites dans ce cadre théorique. Pour cela nous avons mené deux études confrontant des données à des méthodes existantes d'inférence démographique. Une première étude a montré que les méthodes utilisées fréquemment pour l'inférence démographique microbienne, basées sur la reconstruction d'un arbre phylogénétique unique, sont biaisées par la sélection, la recombinaison et les biais d'échantillonnage. Nous avons ensuite comparé plusieurs méthodes d'inférence démographique en les appliquant à une population humaine africaine, les Yoruba. Cette étude a montré les limites d'une méthode existante, et elle illustre le problème d'identifiabilité des histoires démographiques lorsque l'inférence est basée sur le spectre de fréquence. Enfin, dans un troisième temps nous avons analysé plusieurs jeux de données de polymorphisme génétique avec un modèle de référence alternatif à coalescences multiples avec démographie. Nous avons comparé comment le modèle de référence actuel et ce modèle alternatif pouvaient expliquer les données observées de diversité génétique.

Published
2017

18. Inférence des interactions entre processus évolutifs

Author

Behdenna, Abdelkader, Adaptation aux milieux extrêmes, Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris VI, Guillaume Achaz, Amaury Lambert, Biologie des Organismes et Ecosystèmes Aquatiques (BOREA), Université de Caen Normandie (UNICAEN), and Normandie Université (NU)-Normandie Université (NU)-Muséum national d'Histoire naturelle (MNHN)-Institut de Recherche pour le Développement (IRD)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)

Subjects
Computed statistics, [SDV.GEN]Life Sciences [q-bio]/Genetics, Bioinformatique, Tests statistiques, Evolution, Bioinformatics, Co-Evolution, Évolution, Génétique, Vraisemblance
Abstract

In this thesis, we have developed a tool to detect co-evolution, ie the joined evolution of different biological entities (nucleotides, amino acids, organic functions), on different scales (molecular, organ). This tool is applied to phylogenetic trees on which evolutionary events (mutations, gain / loss of biological functions) are placed. We consider an abstract framework in order to work on the processes leading to the emergence of evolutionary events along the lineages of a phylogenetic tree. This tool consists of two separate parts, each with its own specificities.On the one hand, we have produced a first simple, highly effective method to detect from a very large number of such processes, which pairs events seem to appear jointly in the tree. Using a mathematical formalism using the properties of the bilinear algebra, exact calculations of expectancy, variance and even probability distributions are possible and allow to associate exact p-values to these pairs, making this method very precise.On the other hand, we have developed a model of coevolution between such evolutionary processes. This mathematical model severely limits the number of parameters used and allows us to calculate and maximize a likelihood function. This optimization is similar to searching the parameters of a model explaining the best the observed contemporary data, and allows us as well, according to our model, to determine the most likely scenario that led to the observed data.This second method requires more computing time, which invites to combine the two methods in a pipeline allowing us to efficiently process a large number of pairs before proceeding further in our study and test the most promising pairs using our mathematical model in order to describe a scenario interpreted in a biological context. We have tested this tool by using simulations, before applying it to two very different biological examples: the link between intracellularity and loss of flagellum in Escherichia coli, and the study of all the pairs of nucleotides in sequences 16S rRNA of a sample of gamma-Enterobacteria.; Au cours de cette thèse, nous avons développé un outil pour détecter la coévolution, c'est à dire l'évolution conjointe de différentes entités biologiques (nucléotides, acides aminés, fonctions biologiques), à différentes échelles (moléculaire, organe). Cet outil s'applique sur des arbres phylogénétiques sur lesquels des évènements évolutifs (mutations, gains/pertes de fonctions biologiques) sont placés. Nous nous plaçons dans un cadre abstrait dans le but de travailler sur les processus conduisant à l'apparition d'évènements évolutifs au sens large le long des lignées d'un arbre phylogénétique. Cet outil est constitué de deux parties distinctes, chacune ayant ses propres spécificités.D'une part, nous avons produit une première méthode simple, très efficace, permettant de détecter parmi un très grand nombre de tels processus, quelles paires d'évènements semblent apparaître de manière conjointe dans l'arbre. Grâce à un formalisme mathématique utilisant les propriétés de l'algèbre bilinéaire, des calculs exacts d'espérance, de variance et même de distributions de probabilités sont possibles et permettent d'associer à ces paires détectées des p-values exactes, rendant cette méthode très précise.D'autre part, nous avons développé un modèle de coévolution entre de tels processus évolutifs. Ce modèle mathématique limite considérablement le nombre de paramètres utilisés et nous a permis de calculer et d'optimiser une fonction de vraisemblance. Cette optimisation revient à rechercher les paramètres du modèles expliquant au mieux les données contemporaines observées, et nous permet ainsi, toujours selon notre modèle, d'établir le scénario le plus probable ayant mené aux données observées.Cette seconde méthode est plus gourmande en temps de calcul, ce qui invite à associer les deux méthodes dans un pipeline nous permettant de traiter efficacement un grand nombre de paires avant d'aller plus loin dans notre étude et tester les paires les plus encourageantes à l'aide de notre modèle mathématique, dans le but de décrire un scénario interprétable dans un contexte biologique. Nous avons testé cet outil à l'aide de simulations, avant de l'appliquer à deux exemples biologiques très différents : le lien entre intracellularité et perte de flagelle chez Escherichia coli, et l'étude de toutes les paires de nucléotides dans des séquences d'ARNr 16S d’un échantillon de gamma-entérobactéries.

Published
2016

Catalog

Books, media, physical & digital resources
See catalog results