Bayesian flux balance analysis applied to a skeletal muscle metabolic model

In this article, the steady state condition for the multi-compartment models for cellular metabolism is considered. The problem is to estimate the reaction and transport fluxes, as well as the concentrations in venous blood when the stoichiometry and bound constraints for the fluxes and the concentrations are given. The problem has been addressed previously by a number of authors, and optimization-based approaches as well as extreme pathway analysis have been proposed. These approaches are briefly discussed here. The main emphasis of this work is a Bayesian statistical approach to the flux balance analysis (FBA). We show how the bound constraints and optimality conditions such as maximizing the oxidative phosphorylation flux can be incorporated into the model in the Bayesian framework by proper construction of the prior densities. We propose an effective Markov chain Monte Carlo (MCMC) scheme to explore the posterior densities, and compare the results with those obtained via the previously studied linear programming (LP) approach. The proposed methodology, which is applied here to a two-compartment model for skeletal muscle metabolism, can be extended to more complex models.     

FDR control by the BH procedure for two-sided correlated tests with implications to gene expression data analysis

The multiple testing problem attributed to gene expression analysis is challenging not only by its size, but also by possible dependence between the expression levels of different genes resulting from coregulations of the genes. Furthermore, the measurement errors of these expression levels may be dependent as well since they are subjected to several technical factors. Multiple testing of such data faces the challenge of correlated test statistics. In such a case, the control of the False Discovery Rate (FDR) is not straightforward, and thus demands new approaches and solutions that will address multiplicity while accounting for this dependency. This paper investigates the effects of dependency between bormal test statistics on FDR control in two-sided testing, using the linear step-up procedure (BH) of Benjamini and Hochberg (1995). The case of two multiple hypotheses is examined first. A simulation study offers primary insight into the behavior of the FDR subjected to different levels of correlation and distance between null and alternative means. A theoretical analysis follows in order to obtain explicit upper bounds to the FDR. These results are then extended to more than two multiple tests, thereby offering a better perspective on the effect of the proportion of false null hypotheses, as well as the structure of the test statistics correlation matrix. An example from gene expression data analysis is presented.     

An unexpected influence of widely used significance thresholds on the distribution of reported P-values

We consider the problematic relationship between publication success and statistical significance in the light of analyses in which we examine the distribution of published probability (P) values across the statistical 'significance' range, below the 5% probability threshold. P-values are often judged according to whether they lie beneath traditionally accepted thresholds (< 0.05, < 0.01, < 0.001, < 0.0001); we examine how these thresholds influence the distribution of reported absolute P-values in published scientific papers, the majority in biological sciences. We collected published P-values from three leading journals, and summarized their distribution using the frequencies falling across and within these four threshold values between 0.05 and 0. These published frequencies were then fitted to three complementary null models which allowed us to predict the expected proportions of P-values in the top and bottom half of each inter-threshold interval (i.e. those lying below, as opposed to above, each P-value threshold). Statistical comparison of these predicted proportions, against those actually observed, provides the first empirical evidence for a remarkable excess of probability values being cited on, or just below, each threshold relative to the smoothed theoretical distributions. The pattern is consistent across thresholds and journals, and for whichever theoretical approach used to generate our expected proportions. We discuss this novel finding and its implications for solving the problems of publication bias and selective reporting in evolutionary biology.     

Squamate richness in the Brazilian Cerrado and its environmental–climatic associations

We investigate patterns of species richness of squamates (lizards, snakes, and amphisbaenians) in the Brazilian Cerrado, identifying areas of particularly high richness, and testing predictions of large‐scale richness hypotheses by analysing the relationship between species richness and environmental climatic variables. We used point localities from museum collections to produce maps of the predicted distributions for 237 Cerrado squamate species, using niche‐modelling techniques. We superimposed distributions of all species on a composite map, depicting richness across the ecosystem. Then, we performed a multiple regression analysis using eigenvector‐based spatial filtering (Principal Coordinate of Neighbour Matrices) to assess environmental–climatic variables that are best predictors of species richness. We found that the environmental–climatic and spatial filters multiple regression model explained 78% of the variation in Cerrado squamate richness (r² = 0.78; F = 32.66; P < 0.01). Best predictors of species richness were: annual precipitation, precipitation seasonality, altitude, net primary productivity, and precipitation during the driest quarter. A model selection approach revealed that several mechanisms related to the different diversity hypothesis might work together to explain richness variation in the Cerrado. Areas of higher species richness in Cerrado were located mainly in the south‐west, north, extreme east, and scattered areas in the north‐west portions of the biome. Partitioning of energy among species, habitat differentiation, and tolerance to variable environments may be the primary ecological factors determining variation in squamate richness across the Cerrado. High richness areas in northern Cerrado, predicted by our models, are still poorly sampled, and biological surveys are warranted in that region. The south‐western region of the Cerrado exhibits high species richness and is also undergoing high levels of deforestation. Therefore, maintenance of existing reserves, establishment of ecological corridors among reserves, and creation of new reserves are urgently needed to ensure conservation of species in these areas.     

Reconstructing community relationships: the impact of sampling error, ordination approach, and gradient length

Effectively summarizing complex community relationships is an important feature in studies such as biodiversity, global change, and invasion ecology. The reliability of such community summaries depends on the degree of sampling variability that is present in the data, the structure of the data, and the choice of ordination method, but the relative importance of these factors is not understood. We compared the validity of results from different ordination methods by applying five levels of sampling error to a simulated coenoplane model at two gradient lengths using two types of data (abundance and presence–absence). The multivariate methods we compared were correspondence analysis (CA), detrended correspondence analysis (DCA), non-metric multidimensional scaling (NMDS), principal component analysis (PCA) and principal coordinates analysis (PCoA). Our results showed CA and PCA using presence–absence data were the most successful methods regardless of sampling error and gradient length, closely followed by the other methods using presence–absence data. With abundance data, PCA and CA were the most successful approaches with the short and long gradients, respectively. Approaches based on PCoA and NMDS using abundance data did not perform well regardless of the choice of distance measure used in the analysis. Both of these methods, along with the PCA using abundance data, were strongly affected by the longer gradient, leading to more distorted results.     

Food habits of the longnose skate, <Emphasis Type="Italic">Raja rhina</Emphasis> (Jordan and Gilbert, 1880), in central California waters

Feeding studies can provide researchers with important insights towards understanding potential fishery impacts on marine systems. Raja rhina is one of the most common elasmobranch species landed in central and northern California demersal fisheries, yet life history information is extremely limited for this species and aspects of its diet are unknown. Specimens of R. rhina were collected between September, 2002 and August, 2003 from fisheries-independent trawl surveys. Percent Index of Relative Importance values indicated that the five most important prey items in 618 stomachs of R. rhina were unidentified teleosts (31.6% IRI), unidentified shrimps (19.6% IRI), unidentified euphausiids (10.9% IRI), Crangonidae (7.4% IRI), and Neocrangon resima (6.0% IRI). There were significant dietary shifts with increasing skate total length and with increasing depths. Smaller skates ate small crustaceans and larger skates ate larger fishes and cephalopods. With increasing depths, diet included bentho-pelagic teleosts and more cephalopods and euphausiids. The findings of this study are consistent with previous researchers that report similar diet shifts in skate species with size and depth.     

Microsatellite null alleles and estimation of population differentiation

Microsatellite null alleles are commonly encountered in population genetics studies, yet little is known about their impact on the estimation of population differentiation. Computer simulations based on the coalescent were used to investigate the evolutionary dynamics of null alleles, their impact on F(ST) and genetic distances, and the efficiency of estimators of null allele frequency. Further, we explored how the existing method for correcting genotype data for null alleles performed in estimating F(ST) and genetic distances, and we compared this method with a new method proposed here (for F(ST) only). Null alleles were likely to be encountered in populations with a large effective size, with an unusually high mutation rate in the flanking regions, and that have diverged from the population from which the cloned allele state was drawn and the primers designed. When populations were significantly differentiated, F(ST) and genetic distances were overestimated in the presence of null alleles. Frequency of null alleles was estimated precisely with the algorithm presented in Dempster et al. (1977). The conventional method for correcting genotype data for null alleles did not provide an accurate estimate of F(ST) and genetic distances. However, the use of the genetic distance of Cavalli-Sforza and Edwards (1967) corrected by the conventional method gave better estimates than those obtained without correction. F(ST) estimation from corrected genotype frequencies performed well when restricted to visible allele sizes. Both the proposed method and the traditional correction method have been implemented in a program that is available free of charge at http://www.montpellier.inra.fr/URLB/. We used 2 published microsatellite data sets based on original and redesigned pairs of primers to empirically confirm our simulation results.     

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.     

祁连山青海云杉林群落结构的空间异质性

以动态监测样地(340 m×300 m)的网格(5 m×5 m)为基本单元,选择5个群落结构属性变量,采用分形几何学和地统计学方法对祁连山大野口流域青海云杉林群落结构的空间异质性进行研究.结果表明: 青海云杉林5个结构属性的变异程度大小依次为:密度＞平均冠幅＞显著度＞盖度＞平均树高,变异系数为43.7%～79.6%.Moran I系数表明,各个结构属性均有不同程度的空间自相关性,自相关大小顺序为:密度＞平均树高＞盖度＞平均冠幅＞显著度,变化范围为-0.047～0.382.指数理论变异函数模型能很好地拟合不同结构属性的空间变异,变程为24.6～68.1 m,各属性变量的结构比除盖度表现为中等空间相关,其他指标均为强烈空间相关,各属性指标分维数接近2,空间依赖性较小.植被密度和盖度空间分布呈带状结构和斑块结构叠加的特点,其他指标呈较强的斑块状空间结构,密度和盖度对平均冠幅、显著度和平均树高有一定的空间依赖性.青海云杉林群落结构空间异质性适宜的采样间隔和采样面积分别为10 m和0.5 hm².