A Kolmogorov-Smirnov test for the molecular clock on Bayesian ensembles of phylogenies

Divergence date estimates are central to understand evolutionary processes and depend, in the case of molecular phylogenies, on tests of molecular clocks. Here we propose two non-parametric tests of strict and relaxed molecular clocks built upon a framework that uses the empirical cumulative distribution (ECD) of branch lengths obtained from an ensemble of Bayesian trees and well known non-parametric (one-sample and two-sample) Kolmogorov-Smirnov (KS) goodness-of-fit test. In the strict clock case, the method consists in using the one-sample Kolmogorov-Smirnov (KS) test to directly test if the phylogeny is clock-like, in other words, if it follows a Poisson law. The ECD is computed from the discretized branch lengths and the parameter $\lambda$ of the expected Poisson distribution is calculated as the average branch length over the ensemble of trees. To compensate for the auto-correlation in the ensemble of trees and pseudo-replication we take advantage of thinning and effective sample size, two features provided by Bayesian inference MCMC samplers. Finally, it is observed that tree topologies with very long or very short branches lead to Poisson mixtures and in this case we propose the use of the two-sample KS test with samples from two continuous branch length distributions, one obtained from an ensemble of clock-constrained trees and the other from an ensemble of unconstrained trees. Moreover, in this second form the test can also be applied to test for relaxed clock models. The use of a statistically equivalent ensemble of phylogenies to obtain the branch lengths ECD, instead of one consensus tree, yields considerable reduction of the effects of small sample size and provides again of power.Comment: 14 pages, 9 figures, 8 tables. Minor revision, additin of a new example and new title. Software: https://github.com/FernandoMarcon/PKS_Test.gi

Scaling and variability of embryoid symmetry breaking

  Motivation: The formation of the main embryonic axis in mouse is thought to be controlled by extra-embryonic signals. Recent studies however, have shown that three-dimensional aggregates of mouse embryonic stem cells – embryoids – can spontaneously break their initial symmetry to establish an axis in the absence of extra-embryonic signals. This process is characterized by a moving front of mesendodermal fates marked by a region of high Nodal and Wnt signaling. Theoretical analysis suggests that this propagating front is established by a self-organizing bistable reaction-diffusion system. However, it is still unclear how a self-organizing system can robustly generate an embryonic axis independently of size and temporal variability. Methods: To address this question, we are using a multi-disciplinary approach that complements experiments with modeling to understand and predict the dynamics of axis self-organization. On the theoretical side, we use mathematical analysis and simulations to identify parameters that control axis-formation scalability. In addition, we are exploring how external signals can control axis self-organization and reduce its variability. On the experimental side, we perform high-throughput live imaging of embryoids to monitor axis formation in normal situations and upon perturbations. Results: Our model predicts that activating external signals can promote the emergence of a propagating mesendodermal front with an intrinsic temporal variability. In normal conditions, the front expands across the whole embryoid. In contrast, when inhibitory signals are added, the propagation of the mesendodermal front can be stopped. Crucially, the model predicts that the time between activation and inhibition determines the final extension of the axis. To test this prediction, we are imaging embryoids generated with a reporter cell line of Brachyury, one of the earliest markers of axis formation. In agreement with the model, our data shows that the axis emerges with an intrinsic variability of ten hours and propagates over the whole embryoid. Upon application of a small-molecule inhibitor of Nodal, the propagation of the axis is stopped at different positions depending on the time of axis formation. Conclusions: To reduce this variability, we are devising an automated image analysis approach to apply the pharmacological inhibitor of Nodal depending on the time of axis formation. This project will demonstrate how external signals and self-organization are coupled together to achieve robust axis-formation during embryonic development

RTOS Scheduler Implementation in Hardware and Software for Real Time Applications

Abstrac

Virtual meeting, real and sound science: report of the 17 th Meeting of the Spanish Society for Developmental Biology (SEBD-2020)

The Spanish Society for Developmental Biology (SEBD) organized its 17th meeting in November 2020 (herein referred to as SEBD2020).This meeting, originally programmed to take place in the city of Bilbao, was forced onto an online format due to the SARS-CoV2, COVID-19 pandemic. Although, we missed the live personal interactions and missed out on the Bilbao social scene, we were able to meet online to pres- ent our work and discuss our latest results. An overview of the activities that took place around the meeting, the different scientific sessions and the speakers involved are presented here. The pros and cons of virtual meetings are discussed

A Computational Clonal Analysis of the Developing Mouse Limb Bud

A comprehensive spatio-temporal description of the tissue movements underlying organogenesis would be an extremely useful resource to developmental biology. Clonal analysis and fate mappings are popular experiments to study tissue movement during morphogenesis. Such experiments allow cell populations to be labeled at an early stage of development and to follow their spatial evolution over time. However, disentangling the cumulative effects of the multiple events responsible for the expansion of the labeled cell population is not always straightforward. To overcome this problem, we develop a novel computational method that combines accurate quantification of 2D limb bud morphologies and growth modeling to analyze mouse clonal data of early limb development. Firstly, we explore various tissue movements that match experimental limb bud shape changes. Secondly, by comparing computational clones with newly generated mouse clonal data we are able to choose and characterize the tissue movement map that better matches experimental data. Our computational analysis produces for the first time a two dimensional model of limb growth based on experimental data that can be used to better characterize limb tissue movement in space and time. The model shows that the distribution and shapes of clones can be described as a combination of anisotropic growth with isotropic cell mixing, without the need for lineage compartmentalization along the AP and PD axis. Lastly, we show that this comprehensive description can be used to reassess spatio-temporal gene regulations taking tissue movement into account and to investigate PD patterning hypothesis

Prevalência de HPV no sul do Brasil

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