Phenology of Zamia boliviana (Zamiaceae), a threatened species from a seasonally dry biodiversity hotspot in South America

Dioecy, a character common to all cycads, requires obligatory outcrossing. The absence of potential reproductive mates of the opposite sex renders individuals effectively sterile. Therefore, reproductive synchrony is essential for the reproductive success of cycads. Here, we describe the reproductive phenology, morphology, and lifespan of strobili of Zamia boliviana (Cycadales, Zamiaceae), an endemic cycad in South America. We examined the variation in timing of maturation between polliniferous and ovuliferous individuals in two Z. boliviana populations. Lifespan of polliniferous and ovuliferous strobili was based on direct observations and systematic measurements of strobili development. Phenological study covered three reproductive cohorts in two distinct cycad populations. Lifespan of polliniferous strobili was comprised of four phases and lasted 50 days until the cycle's completion, while ovuliferous strobili underwent seven phases that extended over 330 days until seed dehiscence. Both sexes produced strobili during the dry season. We identified a seasonally synchronous pattern in the reproductive phenology of Z. boliviana, with a major overlap in the phases of emergence, pollen release, and strobili receptivity between sexes, populations, and subsequent years. Reproductive events of Z. boliviana followed the seasonality of the Cerrado vegetation and climate. Synchrony between the period of strobili production and reproductive activity peaks was found in both sexes, but seed dehiscence occurred in the dry season. Our study provides relevant and new biological data for Z. boliviana in its natural habitat, demonstrating a temporal distinction between the lifespan of polliniferous and ovuliferous strobili and the necessary overlap between the release and receptivity of pollen.     

Measuring population differentiation using GST or D? A simulation study with microsatellite DNA markers under a finite island model and nonequilibrium conditions

The genetic differentiation of populations is a key parameter in population genetic investigations. Wright's F(ST) (and its relatives such as G(ST) ) has been a standard measure of differentiation. However, the deficiencies of these indexes have been increasingly realized in recent years, leading to some new measures being proposed, such as Jost's D (Molecular Ecology, 2008; 17, 4015). The existence of these new metrics has stimulated considerable debate and induced some confusion on which statistics should be used for estimating population differentiation. Here, we report a simulation study with neutral microsatellite DNA loci under a finite island model to compare the performance of G(ST) and D, particularly under nonequilibrium conditions. Our results suggest that there exist fundamental differences between the two statistics, and neither G(ST) nor D operates satisfactorily in all situations for quantifying differentiation. D is very sensitive to mutation models but G(ST) noticeably less so, which limits D's utility in population parameter estimation and comparisons across genetic markers. Also, the initial heterozygosity of the starting populations has some important effects on both the individual behaviours of G(ST) and D and their relative behaviours in early differentiation, and this effect is much greater for D than G(ST) . In the early stages of differentiation, when initial heterozygosity is relatively low (<0.5, if the number of subpopulations is large), G(ST) increases faster than D; the opposite is true when initial heterozygosity is high. Therefore, the state of the ancestral population appears to have some lasting impacts on population differentiation. In general, G(ST) can measure differentiation fairly well when heterozygosity is low whatever the causes; however, when heterozygosity is high (e.g. as a result of either high mutation rate or high initial heterozygosity) and gene flow is moderate to strong, G(ST) fails to measure differentiation. Interestingly, when population size is not very small (e.g. N ≥ 1000), G(ST) measures differentiation quite linearly with time over a long duration when gene flow is absent or very weak even if mutation rate is not low (e.g. μ = 0.001). In contrast, D, as a differentiation measure, performs rather robustly in all these situations. In practice, both indexes should be calculated and the relative levels of heterozygosities (especially H(S) ) and gene flow taken into account. We suggest that a comparison of the two indexes can generate useful insights into the evolutionary processes that influence population differentiation.     

Junker: An Intergenic Explorer for Bacterial Genomes

In the past few decades, scientists from all over the world have taken a keen interest in novel functional units such as small regulatory RNAs, small open reading frames, pseudogenes, transposons, integrase binding attB/attP sites, repeat elements within the bacterial intergenic regions (IGRs) and in the analysis of those junk regions for ge- nomic complexity. Here we have developed a web server, named Junker, to facilitate the in-depth analysis of IGRs for examining their length distribution, four-quadrant...     

Correction of a bootstrap approach to testing for evolution along lines of least resistance

Testing for an association between the leading vectors of multivariate trait (co)variation within populations (the ‘line of least resistance’) and among populations is an important tool for exploring variational bias in evolution. In a recent study of stickleback fish populations, a bootstrap‐based test was introduced that takes into account estimation error in both vectors and hence improves the previously available bootstrap method. Because this test was implemented incorrectly, however, I here describe the correct test protocol and provide a reanalysis of the original data set. The application of this new test protocol should improve future investigations of evolution along lines of least resistance and other vector comparisons.     

Statistical hypothesis testing in intraspecific phylogeography: nested clade phylogeographical analysis vs. approximate Bayesian computation

Nested clade phylogeographical analysis (NCPA) and approximate Bayesian computation (ABC) have been used to test phylogeographical hypotheses. Multilocus NCPA tests null hypotheses, whereas ABC discriminates among a finite set of alternatives. The interpretive criteria of NCPA are explicit and allow complex models to be built from simple components. The interpretive criteria of ABC are ad hoc and require the specification of a complete phylogeographical model. The conclusions from ABC are often influenced by implicit assumptions arising from the many parameters needed to specify a complex model. These complex models confound many assumptions so that biological interpretations are difficult. Sampling error is accounted for in NCPA, but ABC ignores important sources of sampling error that creates pseudo-statistical power. NCPA generates the full sampling distribution of its statistics, but ABC only yields local probabilities, which in turn make it impossible to distinguish between a good fitting model, a non-informative model, and an over-determined model. Both NCPA and ABC use approximations, but convergences of the approximations used in NCPA are well defined whereas those in ABC are not. NCPA can analyse a large number of locations, but ABC cannot. Finally, the dimensionality of tested hypothesis is known in NCPA, but not for ABC. As a consequence, the 'probabilities' generated by ABC are not true probabilities and are statistically non-interpretable. Accordingly, ABC should not be used for hypothesis testing, but simulation approaches are valuable when used in conjunction with NCPA or other methods that do not rely on highly parameterized models.     

Contemporary gene flow and the spatio-temporal genetic structure of subdivided newt populations (Triturus cristatus, T. marmoratus)

Gene flow and drift shape the distribution of neutral genetic diversity in metapopulations, but their local rates are difficult to quantify. To identify gene flow between demes as distinct from individual migration, we present a modified Bayesian method to genetically test for descendants between an immigrant and a resident in a nonmigratory life stage. Applied to a metapopulation of pond-breeding European newts (Triturus cristatus, T. marmoratus) in western France, the evidence for gene flow was usually asymmetric and, for demes of known census size (N), translated into maximally seven reproducing immigrants. Temporal sampling also enabled the joint estimation of the effective demic population size (Ne) and the immigration rate m (including nonreproductive individuals). Ne ranged between 4.1 and 19.3 individuals, Ne/N ranged between 0.05 and 0.65 and always decreased with N; m was estimated as 0.19-0.63, and was possibly biased upwards. We discuss how genotypic data can reveal fine-scale demographic processes with important microevolutionary implications.     

基于质谱技术筛选差异表达蛋白的统计学策略研究进展

随着质谱技术的快速发展,蛋白质组学已成为继基因组学、转录组学之后的又一研究热点,寻找可靠的差异表达蛋白对于生物标记物的发现至关重要.因此,如何准确、灵敏地筛选出差异蛋白已成为基于质谱的定量蛋白质组学的主要研究内容之一.目前,针对该问题的研究方法众多,但这些方法策略的适用范围不尽相同.总体来说,基于质谱技术筛选差异蛋白的统计学策略可以分为3类:基于经典统计学派的策略、基于贝叶斯学派的统计检验策略和其他策略,这3类方法有各自的应用范围、特点及不足.此外,筛选过程还将产生部分假阳性结果,可以采用其他方法对差异表达蛋白的质量进行控制,以提高统计检验结果的可靠性.     

生态工业园共生网络的脆弱性

工业生态系统的稳定可持续运行是生态工业园区实现环境效益、经济效益和社会效益的重要保障,对生态工业共生网络脆弱性分析是工业生态学领域值得探讨的重要问题。运用复杂网络理论,从网络拓扑结构出发,论证该工业园具有小世界性和无标度性,为网络脆弱性分析奠定基础;通过攻击负载最大节点,利用网络效率和最大连通子图对网络的脆弱性进行分析,从而衡量节点失效对整个网络造成的破坏性。指出复杂网络在生态工业园共生网络中进一步研究的方向。     

Topological model of the division process of cellular and subcellular compartments

The application of the theory of homeomorphic transformations of topological manifolds and the operation of the connected sum of manifolds for a formation of a topological model of membrane transformations during the division process of cellular and subcellular compartments, has been shown. The biological cell and the subcellular structures in the form of vesicles are modelled by an arrangement of two concentric spheres corresponding to the inner and outer layer of the membrane bounding the vesicle. The analysis shows eight succeeding topological stages of membrane transformations during the division process and these stages are characterised. It is concluded that there is a vectorial translocation of lipid molecules from the inner layer of the membrane bounding the vesicle before the division process to the outer layer of the membranes after the division process and there is no lipid translocation from the outer layer to the inner layers during the division process.