Affichage des résultats 1061 à 1080 sur 1243 au total
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In some recent studies, a view emerged that stochastic dynamics governing the switching of cells from one differentiation state to another could be characterized by a peak in gene expression variability at the point of fate commitment. We have tested this hypothesis at the single-cell level by analyzing primary chicken erythroid progenitors through their differentiation process and measuring the expression of selected genes at six sequential time-points after induction of differentiation. In contrast to population-based expression data, single-cell gene expression data revealed a high cell-to-cell variability, which was masked by averaging. We were able to show that the correlation network was a very dynamical entity and that a subgroup of genes tend to follow the predictions from the dynamical network biomarker (DNB) theory. In addition, we also identified a small group of functionally related genes encoding proteins involved in sterol synthesis that could act as the initial drivers of the differentiation. In order to assess quantitatively the cell-to-cell variability in gene expression and its evolution in time, we used Shannon entropy as a measure of the heterogeneity. Entropy values showed a significant increase in the first 8 h of the differentiation process, reaching a peak between 8 and 24 h, before decreasing to significantly lower values. Moreover, we observed that the previous point of maximum entropy precedes two paramount key points: an irreversible commitment to differentiation between 24 and 48 h followed by a significant increase in cell size variability at 48 h. In conclusion, when analyzed at the single cell level, the differentiation process looks very different from its classical population average view. New observables (like entropy) can be computed, the behavior of which is fully compatible with the idea that differentiation is not a "simple" program that all cells execute identically but results from the dynamical behavior of the underlying molecular network.http://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002585
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We consider the problem where one wants to evaluate the level of divergence between K populations. Each population is characterized by its allelic frequency prole, where allelic fre- quencies are assumed to be estimated from a sample at several (typically thousands/millions of) markers. In this context the FST is a widely used criterion for the quantication of the divergence between two populations, that can also be adapted to the question of detecting ge- nomic regions that exhibit a divergence level substantially higher than the rest of the genome. Still, the concept of FST remains ambiguous - with dierent available denitions assumed to be "connected" in some sense - and the strategy to estimate the FST when there are more than 2 populations is still an open question, the most popular strategy being to consider all possible pairs of population successively. In this presentation we will rst propose a hierarchical model for the history of population divergence and show that the two classical denitions of the FST (as provided by Hudson and Weir & Cockerham) actually measure independent quantities. We will then provide an estimation procedure based on the moment estimators suggested by Bhatia (in the case of 2 populations) and show how both the FST components and the history of population divergence may be jointly estimated. Lastly, we will consider the problem of detecting genomic regions under selection and provide a segmentation procedure for the identication of such regions. Both the estimation and the segmentation procedures will be illustrated on the 1KG human genome dataset that gathers several human populations sampled over the world.
Pour en savoir plus sur ces activités vous pouvez consulter le lien suivant : http://www.bath.ac.uk/bio-sci/research/profiles/hurst-l.html.
Thèse de Jennifer MORINAY le jeudi 22 novembre 2018 à 14 h, salle Fontannes bâtiment Darwin D (la Doua)
Évolution et fonctionnalité des éléments non-codants dans les génomes des vertébrés
Modélisation mathématique et statistique pour l'évaluation du risque environnemental
L'hôte comme écosystème
Responses of mammalian communities to human imprint: Impacts of climate change, management and exposure to humans on carnivores and their interactions
Comment l'environnement social influence-t-il les comportements sexuels d'un mâle parasitoïde envers les femelles et les mâles ?
Contrôle des éléments transposables et réponse aux infections virales chez Drosophila
"Relations entre l’évolution des paysages cis-régulateurs, l’évolution de l’expression des gènes et l’évolution phénotypique chez les vertébrés"
Odyssée d'Helicobacter pylori : Itinéraires, Rencontres, Chronologies
Utilisation spatio-temporelle des paysages anthropisés multifonctionnels par les mammifères africains. Tester le principe d'anthropodépendance
Modélisation théorique de l’évolution de la recombinaison méiotique chez les mammifères. Des mécanismes moléculaires à la dynamique évolutive.