Parent–offspring conflict and selection on egg size in turtles

The trade‐off between offspring size and number can present a conflict between parents and their offspring. Because egg size is constrained by clutch size, the optimal egg size for offspring fitness may not always be equivalent to that which maximizes parental fitness. We evaluated selection on egg size in three turtle species (Apalone mutica, Chelydra serpentina and Chrysemys picta) to determine if optimal egg sizes differ between offspring and their mothers. Although hatching success was generally greater for larger eggs, the strength and form of selection varied. In most cases, the egg size that maximized offspring fitness was greater than that which maximized maternal fitness. Consistent with optimality theory, mean egg sizes in the populations were more similar to the egg sizes that maximized maternal fitness, rather than offspring fitness. These results provide evidence that selection has maximized maternal fitness to achieve an optimal balance between egg size and number.     

Selection efficiency and effective population size in Drosophila species

A corollary of the nearly neutral theory of molecular evolution is that the efficiency of natural selection depends on effective population size. In this study, we evaluated the differences in levels of synonymous polymorphism among Drosophila species and showed that these differences can be explained by differences in effective population size. The differences can have implications for the molecular evolution of the Drosophila species, as is suggested by our results showing that the levels of codon bias and the proportion of adaptive substitutions are both higher in species with higher levels of synonymous polymorphism. Moreover, species with lower synonymous polymorphism have higher levels of nonsynonymous polymorphism and larger content of repetitive sequences in their genomes, suggesting a diminished efficiency of selection in species with smaller effective population size.     

A neutral model of edge effects

In this paper a spatially implicit neutral model for explaining the edge effects between habitats is proposed. To analyze this model we use two different approaches: a discrete approach that is based on the Master equation for a one step jump process and a continuous approach based on the approximation of the discrete jump process with the Kolmogorov-Fokker-Planck forward and backward equations. The discrete and continuous approaches are applied to analyze the species abundance distributions and the time to species extinction. Moreover, with the aid of the continuous approach a realistic classification of the behavior of species in local communities is developed. The species abundance dynamics at the edge between two distinct habitats is compared with those located in the homogeneous interior habitats using species abundance distributions and the first time to species extinction. We show that the structure of the links between local community and the metacommunity plays an important role on species persistence. Specifically, species at the edge between two distinct metacommunities have higher extinction rate than those in the interior habitats connected only to one metacommunity. Moreover, the same species might be persistent in the homogeneous interior habitat, but its probability of extinction from the edge local community could be very high.     

Spontaneous behavioural changes in response to epidemics

We study how spontaneous reduction in the number of contacts could develop, as a defensive response, during an epidemic and affect the course of infection events. A model is proposed which couples an SIR model with selection of behaviours driven by imitation dynamics. Therefore, infection transmission and population behaviour become dynamical variables that influence each other. In particular, time scales of behavioural changes and epidemic transmission can be different. We provide a full qualitative characterization of the solutions when the dynamics of behavioural changes is either much faster or much slower than that of epidemic transmission. The model accounts for multiple outbreaks occurring within the same epidemic episode. Moreover, the model can explain “asymmetric waves”, i.e., infection waves whose rising and decaying phases differ in slope. Finally, we prove that introduction of behavioural dynamics results in the reduction of the final attack rate.     

Asymptotic properties of infinite Leslie matrices

The stable population theory is classically applicable to populations in which there is a maximum age after which individuals die. Demetrius [1972. On an infinite population matrix. Math. Biosci. 13, 133-137] extended this theory to infinite Leslie matrices, in which the longevity of individuals is potentially infinite. However, Demetrius had to assume that the survival probability per time step tends to 0 with age. We generalise here the conditions of application of the stable population theory to infinite Leslie matrix models and apply these results to two examples, including or not senescence.     

Stochastic sampling of interaction partners versus deterministic payoff assignment

Evolutionary game dynamics describes how successful strategies spread in a population. In well-mixed populations, the usual assumption, e.g. underlying the replicator dynamics, is that individuals obtain a payoff from interactions with a representative sample of the population. This determines their fitness. Here, we analyze a situation in which payoffs are obtained through a single interaction, so that individuals of the same type can have different payoffs. We show analytically that for weak selection, this scenario is identical to the usual approach in which an individual interacts with the whole population. For strong selection, however, differences arise that are reflected in the fixation probabilities and lead to deviating evolutionary dynamics.     

Mutation-selection equilibrium in games with multiple strategies

In evolutionary games the fitness of individuals is not constant but depends on the relative abundance of the various strategies in the population. Here we study general games among n strategies in populations of large but finite size. We explore stochastic evolutionary dynamics under weak selection, but for any mutation rate. We analyze the frequency dependent Moran process in well-mixed populations, but almost identical results are found for the Wright-Fisher and Pairwise Comparison processes. Surprisingly simple conditions specify whether a strategy is more abundant on average than 1/n, or than another strategy, in the mutation-selection equilibrium. We find one condition that holds for low mutation rate and another condition that holds for high mutation rate. A linear combination of these two conditions holds for any mutation rate. Our results allow a complete characterization of n×n games in the limit of weak selection.     

Generalized lattice graphs for 2D-visualization of biological information

Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein-protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.     

随机矩阵理论在肝癌基因功能模块识别中的应用

采用随机矩阵理论方法研究了肝癌的基因表达网络。通过标准误差分析,得到了从富含噪声的肝癌基因网络中分离出真实肝癌基因网络的、去躁最充分的关联系数,分析了由此获得的基因表达网络的13个基因功能模块,发现这些模块与肝癌的产生和发展有密切关系。基于随机矩阵理论的方法克服了以往模块识别方法带有主观因素且不能去除噪声因子的缺陷,是一种有效去除随机噪声、识别基因模块、简化基因网络的方法。由于基因数目的众多及细胞生物过程的复杂性,从整体的角度系统研究肝癌基因表达谱,对理解肝癌分子机制和探索新的治疗方法有重要的现实意义。