Detecting Signatures of Selection Through Haplotype Differentiation Among Hierarchically Structured Populations

The detection of molecular signatures of selection is one of the major concerns of modern population genetics. A widely used strategy in this context is to compare samples from several populations and to look for genomic regions with outstanding genetic differentiation between these populations. Genetic differentiation is generally based on allele frequency differences between populations, which are measured by F_ST or related statistics. Here we introduce a new statistic, denoted hapFLK, which focuses instead on the differences of haplotype frequencies between populations. In contrast to most existing statistics, hapFLK accounts for the hierarchical structure of the sampled populations. Using computer simulations, we show that each of these two features—the use of haplotype information and of the hierarchical structure of populations—significantly improves the detection power of selected loci and that combining them in the hapFLK statistic provides even greater power. We also show that hapFLK is robust with respect to bottlenecks and migration and improves over existing approaches in many situations. Finally, we apply hapFLK to a set of six sheep breeds from Northern Europe and identify seven regions under selection, which include already reported regions but also several new ones. We propose a method to help identifying the population(s) under selection in a detected region, which reveals that in many of these regions selection most likely occurred in more than one population. Furthermore, several of the detected regions correspond to incomplete sweeps, where the favorable haplotype is only at intermediate frequency in the population(s) under selection.     

Process model comparison and transferability across bioreactor scales and modes of operation for a mammalian cell bioprocess

A Monod kinetic model, logistic equation model, and statistical regression model were developed for a Chinese hamster ovary cell bioprocess operated under three different modes of operation (batch, bolus fed‐batch, and continuous fed‐batch) and grown on two different bioreactor scales (3 L bench‐top and 15 L pilot‐scale). The Monod kinetic model was developed for all modes of operation under study and predicted cell density, glucose glutamine, lactate, and ammonia concentrations well for the bioprocess. However, it was computationally demanding due to the large number of parameters necessary to produce a good model fit. The transferability of the Monod kinetic model structure and parameter set across bioreactor scales and modes of operation was investigated and a parameter sensitivity analysis performed. The experimentally determined parameters had the greatest influence on model performance. They changed with scale and mode of operation, but were easily calculated. The remaining parameters, which were fitted using a differential evolutionary algorithm, were not as crucial. Logistic equation and statistical regression models were investigated as alternatives to the Monod kinetic model. They were less computationally intensive to develop due to the absence of a large parameter set. However, modeling of the nutrient and metabolite concentrations proved to be troublesome due to the logistic equation model structure and the inability of both models to incorporate a feed. The complexity, computational load, and effort required for model development has to be balanced with the necessary level of model sophistication when choosing which model type to develop for a particular application. © 2012 American Institute of Chemical Engineers Biotechnol. Prog., 2013     

Quantative analysis and paleoecology of Middle to Upper Eocene Ostracods from Jebel Jebil,central Tunisia

One hundred and seventy collected samples from Jebil section have been carefully studied for their ostracod content and referred to 41 species belonging to 20 genera. Their vertical distribution allowed to distinguish five successive associations of ostracod assemblages; two of which are correlated with the Early Lutetian, one with the Late Lutetian, another association with the Bartonian and the last one with the Priabonian. Community structure of the collected ostracod fauna has been studied; three indices have been calculated for each sample: Shannon (diversity), Margalef (richness) and Equitability indexes. In the lower and the middle part of the Formation, they indicate a stable environment supporting high diversity ostracod communities; whereas in the upper portion the environmental conditions were unstable characterized by low diversity. The results of a multivariate statistical method, using the cluster analysis and the Detrended Correspondence Analysis of the 41 ostracod species and the 170 samples, have led to conclude that the most effective environmental factor in the study area is the paleodepth and of less importance oxygenation and salinity. Thus, it allowed to distinguish four palaeoenvironmental intervals within the Cherahil Formation: the first one represented by taxa that are known from the shallower parts of the shelf; the second interval includes the majority of the encountered species of inner neritic shelf with normal salinity; the third one, corresponding to an outer neritic domain; and the last interval refers to a circalittoral environment, is comprised mainly of Cytherella angulata and of Soudanella laciniosa triangulata.     

Polarization of Myosin II Refines Tissue Material Properties to Buffer Mechanical Stress

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Sensitivity of stress and strain calculations to passive material parameters in cardiac mechanical models using unloaded geometries

Cardiac stress (load) and strain (stretch) are widely studied indicators of cardiac function and outcome, but are difficult or impossible to directly measure in relation to the cardiac microstructure. An alternative approach is to estimate these states using computer methods and image-based measurements, but this still requires knowledge of the tissue material properties and the unloaded state, both of which are difficult to determine. In this work, we tested the sensitivity of these two interdependent unknowns (reference geometry and material parameters) on stress and strain calculations in cardiac tissue. Our study used a finite element model of the human ventricle, with a hyperelastic passive material model, and was driven by a cell model mediated active contraction. We evaluated 21 different published parameter sets for the five parameters of the passive material model, and for each set we optimised the corresponding unloaded geometry and contractility parameter to model a single pressure-volume loop. The resulting mechanics were compared, and calculated systolic stresses were largely insensitive to the chosen parameter set when an unloading algorithm was used. Meanwhile, material strain calculations varied substantially depending on the choice of material parameters. These results indicate that determining the correct material and unloaded configuration may be highly important to understand strain driven processes, but less so for calculating stress estimates.     

Label‐free multi‐parametric imaging of single cells: dual picosecond optoacoustic microscopy

Advances in microscopy with new visualization possibilities often bring dramatic progress to our understanding of the intriguing cellular machinery. Picosecond optoacoustic micro‐spectroscopy is an optical technique based on ultrafast pump‐probe generation and detection of hypersound on time durations of picoseconds and length scales of nanometers. It is experiencing a renaissance as a versatile imaging tool for cell biology research after a plethora of applications in solid‐state physics. In this emerging context, this work reports on a dual‐probe architecture to carry out real‐time parallel detection of the hypersound propagation inside a cell that is cultured on a metallic substrate, and of the hypersound reflection at the metal/cell adhesion interface. Using this optoacoustic modality, several biophysical properties of the cell can be measured in a noncontact and label‐free manner. Its abilities are demonstrated with the multiple imaging of a mitotic macrophage‐like cell in a single run experiment.      

Assessment of a large number of empirical plant species niche models by elicitation of knowledge from two national experts

Quantitative models play an increasing role in exploring the impact of global change on biodiversity. To win credibility and trust, they need validating. We show how expert knowledge can be used to assess a large number of empirical species niche models constructed for the British vascular plant and bryophyte flora. Key outcomes were (a) scored assessments of each modeled species and niche axis combination, (b) guidance on models needing further development, (c) exploration of the trade‐off between presenting more complex model summaries, which could lead to more thorough validation, versus the longer time these take to evaluate, (d) quantification of the internal consistency of expert opinion based on comparison of assessment scores made on a random subset of models evaluated by both experts. Overall, the experts assessed 39% of species and niche axis combinations to be “poor” and 61% to show a degree of reliability split between “moderate” (30%), “good” (25%), and “excellent” (6%). The two experts agreed in only 43% of cases, reaching greater consensus about poorer models and disagreeing most about models rated as better by either expert. This low agreement rate suggests that a greater number of experts is required to produce reliable assessments and to more fully understand the reasons underlying lack of consensus. While area under curve (AUC) statistics showed generally very good ability of the models to predict random hold‐out samples of the data, there was no correspondence between these and the scores given by the experts and no apparent correlation between AUC and species prevalence. Crowd‐sourcing further assessments by allowing web‐based access to model fits is an obvious next step. To this end, we developed an online application for inspecting and evaluating the fit of each niche surface to its training data.     

Homology modeling and examination of the effect of the D92E mutation on the H5N1 nonstructural protein NS1 effector domain

Virulent H5N1 strains of influenza virus often harbor a D92E point mutation in the nonstructural protein NS1. This crucial mutation has been correlated with increased virulence and/or cytokine resistance, but the structural implications of such a change are still unclear. Furthermore, NS1 protein could also be a potential target for the development of novel antiviral agents against H5N1 strains. Therefore, a reasonable 3D model of H5N1 NS1 is important for the understanding of the molecular basis of increased virulence and the design of novel antiviral agents. Based on the crystal structure of a non-H5N1 NS1 protein, a model of H5N1 NS1 was developed by homology modeling, molecular mechanics and molecular dynamics simulations. It was found that the D92E mutation could result in weakened interactions of the carboxylate side chain with other phosphorylated residues, thereby activating phosphorylation of NS1. Figure Superposition of snapshots picked from the two molecular dynamic (MD) trajectories: a H5N1 NS1 homology model and b non-H5N1 NS1 crystal structure after 0 (green ribbon), 5 (blue ribbon) and 10 ns (pink ribbon) MD simulation     

Bovine annulus fibrosus hydration affects rate-dependent failure mechanics in tension

The high water content of the intervertebral disc is essential to its load bearing function and viscoelastic mechanical behavior. One of the primary biochemical changes associated with disc degeneration is the loss of proteoglycans, which leads to tissue dehydration. While previous studies have reported the effects of in vivo degeneration on annulus fibrosus (AF) failure mechanics, the independent role of water remains unclear, as does the tissue’s rate-dependent failure response. Our first objective was to determine the effect of loading rate on AF failure properties in tension; our second objective was to quantify the effect of water content on failure properties. Water content was altered through enzymatic digestion of glycosaminoglycans (GAGs) and through osmotic loading. Bovine AF specimens were tested monotonically to failure along the circumferential direction at 0.00697%/s or 6.97%/s. Increased loading rate resulted in a ∼50% increase in linear-region modulus, failure stress, and strain energy density across all treatment groups (p < 0.001). Decreased GAG and water contents resulted in decreased modulus, failure stress, and strain energy density; however, these differences were only observed at the low loading rate (p < 0.05; no changes at high rate). Osmotic loading was used to evaluate the effect of hydration independently from GAG composition, resulting in similar decreases in water content, modulus, and strain energy density. This suggests that hydration is essential for maintaining tissue stiffness and energy absorption capacity, rather than strength, and that GAGs contribute to tissue strength independently from mediating water content.