Showing results 5481 to 5500 on 6429 in total
(travail en collaboration avec A. Arribas-Gil, Univ. Carlos III, Madrid) Dans cet exposé, je parlerai tout d'abord de l'alignement statistique de 2 séquences, qui permet d'aligner ces séquences sans choisir a priori les paramètres de l'alignement. Ces paramètres sont en fait déterminés par maximum de vraisemblance, dans un modèle d'évolution de ces deux séquences. Dans un second temps, je montrerai commen on peut modifier l'algorithme d'alignement statistique pour prendre en compte la non indépendance dans l'évolution des sites de la séquence. J'illustre ces résultats sur une paire de séquences "jouet" (alpha-globine humaine HBA1 et pseudo-gène HBPA1).
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http://www.beldade.nl/
Mammals show a broad array of different life history strategies. Theory suggests that this diversity has evolved because organisms are constrained in their ability to invest in two or more life history traits, and so must trade-off investment in different components. The proximate underlying causes for these trade-offs are largely unknown. I will first present results from experiments that test whether oxidative stress, a pathological process involved in ageing, is a physiological cost of reproduction in house mice (Mus musculus domesticus). I explore whether oxidative stress increases during energetically demanding reproductive periods, such as lactation in females, or accumulates after a long period of reproductive investment. I will then discuss a recent comparative study across mammals. Here I explore how the placenta, an organ that exhibits great morphological diversity, has evolved in relation to different life history strategies.
Le Cancer Survival Group (London School of Hygiene and Tropical Medicine) concentre ses efforts de recherche des 10 dernières années sur les inégalités de survie du cancer et les mécanismes sous-jacents. Nous nous sommes particulièrement intéressés aux inégalités géographiques et socio-économiques au Royaume-Uni. Cette présentation décrira les méthodes utilisées, les principaux résultats et leurs présentations dans un format utilisable en santé publique et par les responsables des soins de santé.
http://compgen.bscb.cornell.edu/~acs/Quelques références représentatives:• Guertin MJ*, Martins AL*, Siepel A, Lis JT. Accurate prediction of inducible transcription factor binding intensities in vivo. PLoS Genetics, 2012;8(3):e1002610.• Lindblad-Toh K, Garber M, Zuk O, Lin MF, Parker BJ, et. al. (63 co-authors). A high-resolution map of evolutionary constraint in the human genome based on 29 eutherian mammals. Nature 478(7370):476-482, 2011.• Gronau I, Hubisz MJ, Gulko B, Danko CG, Siepel A. Bayesian inference of ancient human demography from individual genome sequences. Nature Genetics 43(10):1031-1034, 2011.• Lowe CB, Kellis M, Siepel A, Raney B, Clamp M, Salama SR, Kingsley D, Lindblad-Toh K, Haussler D. Three different periods of regulatory innovation during vertebrate evolution. Science 333(6045):1019-1024, 2011.• Hubisz MJ, Pollard KS, Siepel A. PHAST and RPHAST: Phylogenetic analysis with space/time models. Briefings in Bioinformatics 12(1):41-51, 2011.• Vinar T, Brejova B, Song G, Siepel A. Reconstructing histories of complex gene clusters on a phylogeny. J Comput Biol 17(9):1267-1279, 2010.• Pollard KS, Hubisz MJ, Rosenboom K, Siepel A. Detection of non-neutral substitution rates on Mammalian phylogenies. Genome Res, 20:110-121, 2010.• Siepel A. Phylogenomics of primates and their ancestral populations. Genome Res, 19:1929-1941, 2009.• Kosiol C, Vinar T, da Fonseca RR, Hubisz MJ, Bustamante CD, Nielsen R, Siepel A. Patterns of positive selection in six mammalian genomes. PLoS Genet, 4(8):e1000144, 2008..
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Background. Recovering the structure of ancestral genomes can be formalized in terms of properties of binary matrices such as the Consecutive-Ones Property (C1P). The Linearization Problem asks to extract, from a given binary matrix, a maximum weight subset of rows that satisfies such a property. This problem is in general intractable, and in particular if the ancestral genome is expected to contain only linear chromosomes or a unique circular chromosome. In the present work, we consider a relaxation of this problem, which allows ancestral genomes that can contain several chromosomes, each either linear or circular.Result. We show that, when restricted to binary matrices of degree two, which correspond to adjacencies, the genomic characters used in most ancestral genome reconstruction methods, this relaxed version of the Linearization Problem is polynomially solvable using a reduction to a matching problem. This result holds in the more general case where columns have bounded multiplicity, which models possibly duplicated ancestral genes. We also prove that for matrices with rows of degrees 2 and 3, without multiplicity and without weights on the rows, the problem is NP-complete, thus tracing sharp tractability boundaries. I also give a preliminary result on a method for generating these binary matrices of degree 2, i.e., a method for inferring ancestral adjacencies, and how the Linearization Problem fits into this larger context.Conclusion. As it happened for the breakpoint median problem, also used in ancestral genome reconstruction, relaxing the definition of a genome turns an intractable problem into a tractable one. The relaxation is adapted to some biological contexts, such as bacterial genomes with several replicons, possibly partially assembled. Algorithms can also be used as heuristics for hard variants. More generally, this work opens a way to better understand linearization results for ancestral genome structure inference.
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Apres une introduction aux modeles de Hawkes multivaries, j'expliquerai en detail en quoi ces processus peuvent etre pertinents pour modeliser les distances evitees ou favorisees entre motifs (ou elements regulateurs de la transcription) le long de la chaine d'ADN, mais aussi pour modeliser les interactions entre trains de potentiels d'action en neurosciences. Apres avoir explique quels sont les principaux moyens pour estimer de maniere parametrique dans ces modeles les fonctions d'interaction, je detaillerai comment s'affranchir d'hypotheses parametriques sur ces fonctions et obtenir une methode statistique qui s'adapte aux donnees sans que l'on ait aucune hypothese majeure a faire. Je finirai en expliquant que l'on peut tester que ces modeles sont valides sur les donnees en question.
Francisella tularensis is a Gram-negative bacterium causing tularemia in humans. This zoonotic agent can infect a wide range of hosts including amoebae, arthropods and mammals. The ability of Francisella to cause disease is linked to its ability to replicate within host cells. Upon phagocytosis by macrophages, Francisella escapes from the phagosome to reach the host cytosol where it can replicate to very high numbers. I will present both the virulence factors controlling the intracellular life cycle and the host factors that detect Francisella in the host cytosol leading to the mounting of an efficient immune response.
En apparence, il s'agit d'une question relativement simple dont on attend une réponse tout aussi simple. Dans le langage courant, ou en tout cas médiatique, la question est parfois posée sous la forme « le cancer aujourd'hui, une épidémie ? ». Le mode de vie actuel, les modifications environnementales, les expositions à des sources polluantes multiples alimentent, de manière légitime, les craintes de la population. Le vieillissement de la population induit également une augmentation du nombre de personnes atteintes de cancer, ce qui accentue la perception, réelle ou supposée, de la maladie : on rappelle que le cancer est, depuis 2004, la première cause de décès en France. Il n'existe pas de réponse universelle à la question initiale, pour de multiples raisons. La première réponse, d'ordre technique, est qu'il n'existe, pour répondre à la question, que des données observationnelles. Il n'est de ce fait pas aisé de faire le lien entre une cause et un effet. Or, parler de risque, au sens scientifique du terme, suppose la mise en évidence de facteurs de risque. Une seconde raison est que le cancer est une maladie qui a des composantes très différentes, et dont les causes possibles sont la résultante de différents facteurs (maladie multifactorielle). Une autre façon d'aborder cette question serait de décliner la problématique en trois questions : quel est le risque d'avoir un cancer (question initiale), le risque d'avoir un diagnostic de cancer (cas des localisations à forte prévalence), le risque de décéder d'un cancer. Notre exposé n'aura pas pour objectif de fournir une réponse définitive à la question posée mais plutôt de fournir des indications sur la difficulté d'y répondre. Les données du registre du cancer de l'Isère, mais aussi d'autres registres ainsi que les estimations nationales d'incidence et de mortalité serviront de support à la présentation.
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Symbiotic associations are widespread in nature, and constitute a driving force in the evolution of organisms. However, the interactions between partners that lead to the establishment, the specificity and the evolution of the association are oftentimes difficult to study. We used the binary mutualistic association between the squid Euprymna scolopes and the luminescent bacterium Vibrio fischeri as a natural model to study the dialogue between partners that facilitates the selection and colonization of the symbiont into host tissues, but also its maintenance over a strong diel rhythm. We coupled comparative transcriptomics analyses and functional characterizations to better understand how the initial molecular conversation between the two partners plays a role in determining the specificity of the association. We also studied the influence of the presence of a persistent luminous bacterium on the gene expression and physiology of its host. These studies reveal that a very limited number of symbionts is sufficient to reprogram host gene expression, leading to the specific establishment of the interaction and the building of its extended phenotype.
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Structural variation in general, and copy number variants (CNV) in particular, has emerged as an important source of genetic variation. The genetic history and the extraordinary morphological, physiological and behavioral variation of dogs, make them an ideal mammal in which to study the effects of CNV on biology and disease. The dog genome revealed the existence of more than one thousand of CNV that overlap ≈ 400 genes, which are enriched for defense/immunity, oxidoreductase, protease, receptor, signaling molecule and transporter genes. Furthermore, CNV can have significant impacts on a wide range of phenotypes including breed-definiting traits and showed to be appropriate markers to analyze genetic relationships between dog populations. This finding implies that most of the surveyed CNVs were present in the pool of canine breed founders. In order to understand the ancestral dog genome organization, we designed a high density custom 720K probes NimbleGen aCGH chip based on all known dog CNV and segmental duplication and genotyped 15 wolves from 11 populations, with a wide distribution (including Europe, Asia and America), 5 dogs (Dingo, Basenji, Beagle, Boxer and Dachshund) and three outgroups (red wolf, coyote and golden jackal). The dataset analyzed in this study allow us to identify selected CNV during early dog domestication.
The organization of genes along a genome is not random. There exists various proofs of specific rearrangements such that operon for procaryote organisms.In the goal to better understand how this organization can explain the correlation between chromosomic mutation in cancer, we studied the organization of co-functional genes on the human genome (pathways, protein complexes, RNAt, etc). Using statistics, we observed significant concentrations (or dispersions) for sets of co-functioning genes. We evaluated the organization of these sets of genes through three aspects: number of chromosomes involved, genomic distance, spatial intra-chromosomic distance. This organization seems to depend on the functional category (FunCat) of each set of genes. From this results, we start to work on the evolution of these concentrations and dispersions among various species.Moreover, in order to observe some (dis)similarities between genomes, it is necessary to define realistic models and measures. We have implemented models (based of graph theory and mathematic programming) to compute in particular common adjacencies between genomes. These models take into account increasingly biologic information despite the complexity of the studied problems.
Cancer is a disease that affects the majority of metazoan species and prior to directly causing host death, is likely to influence the competitive abilities of individuals, their susceptibility to pathogens, their vulnerability to predators and their ability to disperse. Despite the potential importance of these ecological impacts, cancer is rarely incorporated into model ecosystems. In this talk, I will describe the diversity of ways in which oncogenic phenomena, from precancerous lesions to generalized metastatic cancers, may affect ecological processes that govern biotic interactions. I will argue that oncogenic phenomena, despite their complexity, have predictable ecological consequences. Our aim is to provide a new perspective on the ecological and evolutionary significance of cancer in wildlife, and to stimulate research on this topic.