Untangling long branches: identifying conflicting phylogenetic signals using spectral analysis, neighbor-net, and consensus networks

Long-branch attraction is a well-known source of systematic error that can mislead phylogenetic methods; it is frequently invoked post hoc, upon recovering a different tree from the one expected based on prior evidence. We demonstrate that methods that do not force the data onto a single tree, such as spectral analysis, Neighbor-Net, and consensus networks, can be used to detect conflicting signals within the data, including those caused by long-branch attraction. We illustrate this approach using a set of taxa from three unambiguously monophyletic families within the Pelecaniformes: the darters, the cormorants and shags, and the gannets and boobies. These three families are universally acknowledged as forming a monophyletic group, but the relationship between the families remains contentious. Using sequence data from three mitochondrial genes (12S, ATPase 6, and ATPase 8) we demonstrate that the relationship between these three families is difficult to resolve because they are separated by a short internal branch and there are conflicting signals due to long-branch attraction, which are confounded with nonhomogeneous sequence evolution across the different genes. Spectral analysis, Neighbor-Net, and consensus networks reveal conflicting signals regarding the placement of one of the darters, with support found for darter monophyly, but also support for a conflicting grouping with the outgroup, pelicans. Furthermore, parsimony and maximum-likelihood analyses produced different trees, with one of the two most parsimonious trees not supporting the monophyly of the darters. Monte Carlo simulations, however, were not sensitive enough to reveal long-branch attraction unless the branches are longer than those actually observed. These results indicate that spectral analysis, Neighbor-Net, and consensus networks offer a powerful approach to detecting and understanding the source of conflicting signals within phylogenetic data.     

Analysis of possibility of genotypic correlation between fear and anxiety

Special features of anxious behavior in the elevated plus maze test and acoustic startle response were analyzed in 11 inbred mouse strains. A significant influence of the genotype both on the startle amplitude and behavior in the elevated plus maze was found. However, analysis of covariance did not reveal a genotype-related association between anxiety and startle amplitude. The data indicates that the fear-induced acoustic startle response and anxious behavior in the elevated plus maze (agoraphobia) are not genetically related.     

Untangling above‐ and belowground mycorrhizal fungal networks in tropical orchids

Orchids typically depend on fungi for establishment from seeds, forming mycorrhizal associations with basidiomycete fungal partners in the polyphyletic group rhizoctonia from early stages of germination, sometimes with very high specificity. This has raised important questions about the roles of plant and fungal phylogenetics, and their habitat preferences, in controlling which fungi associate with which plants. In this issue of Molecular Ecology, Martos et al. (2012) report the largest network analysis to date for orchids and their mycorrhizal fungi, sampling a total of over 450 plants from nearly half the 150 tropical orchid species on Reunion Island, encompassing its main terrestrial and epiphytic orchid genera. The authors found a total of 95 operational taxonomic units of mycorrhizal fungi and investigated the architecture and nestedness of their bipartite networks with 73 orchid species. The most striking finding was a major ecological barrier between above‐ and belowground mycorrhizal fungal networks, despite both epiphytic and terrestrial orchids often associating with closely related taxa across all three major lineages of rhizoctonia fungi. The fungal partnerships of the epiphytes and terrestrial species involved a diversity of fungal taxa in a modular network architecture, with only about one in ten mycorrhizal fungi partnering orchids in both groups. In contrast, plant and fungal phylogenetics had weak or no effects on the network. This highlights the power of recently developed ecological network analyses to give new insights into controls on plant–fungal symbioses and raises exciting new hypotheses about the differences in properties and functioning of mycorrhiza in epiphytic and terrestrial orchids.     

Developmental regulation of fear learning and anxiety behavior by endocannabinoids

The developing brain undergoes substantial maturation into adulthood and the development of specific neural structures occurs on differing timelines. Transient imbalances between developmental trajectories of corticolimbic structures, which are known to contribute to regulation over fear learning and anxiety, can leave an individual susceptible to mental illness, particularly anxiety disorders. There is a substantial body of literature indicating that the endocannabinoid (eCB) system critically regulates stress responsivity and emotional behavior throughout the life span, making this system a novel therapeutic target for stress‐ and anxiety‐related disorders. During early life and adolescence, corticolimbic eCB signaling changes dynamically and coincides with different sensitive periods of fear learning, suggesting that eCB signaling underlies age‐specific fear learning responses. Moreover, perturbations to these normative fluctuations in corticolimbic eCB signaling, such as stress or cannabinoid exposure, could serve as a neural substrate contributing to alterations to the normative developmental trajectory of neural structures governing emotional behavior and fear learning. In this review, we first introduce the components of the eCB system and discuss clinical and rodent models showing eCB regulation of fear learning and anxiety in adulthood. Next, we highlight distinct fear learning and regulation profiles throughout development and discuss the ontogeny of the eCB system in the central nervous system, and models of pharmacological augmentation of eCB signaling during development in the context of fear learning and anxiety.     

Genes and neurons: molecular insights to fear and anxiety

Experimental animal models provide an important tool for the identification of inheritable components of fear and anxiety. 'Pavlovian' fear conditioning has been tremendously successful to characterize the neuronal circuitry and cellular mechanisms of the formation, consolidation and extinction of fear memories. Here we summarize recent progress that has led to the identification of gene products contributing to such experience-dependent changes in fear and anxiety and may guide the search for genetic factors involved in the development and treatment of human anxiety disorders.     

A genetic study of panic disorder pedigrees.

Pedigree analysis is done on 19 kindreds of panic disorder, and the results suggest that this disorder is transmitted as an autosomal dominant trait. Seven of these 19 kindreds were ascertained through a panic disorder proband with mitral valve prolapse. When the analysis is done omitting these seven kindreds, the results also suggest that panic disorder without prolapse is transmitted as an autosomal dominant trait.     

Simultaneous modelling of metabolic, genetic and product-interaction networks

The creation of cell models from annotated genome information, as well as additional data from other databases, requires both a format and medium for its distribution. Standards are described for the representation of the data in the form of Document Type Definitions (DTDs) for XML files. Separate DTDs are detailed for genetic, metabolic and gene product-interaction networks, which can be used to hold information on individual subsystems, or which may be combined to create a whole cell DTD. In the execution of this work, a fifth DTD was also created for a metabolite thesaurus, which allows incorporation of metabolite synonyms and generic nomenclature data into the models. A gene-regulation classification scheme was also created, to facilitate incorporation of gene regulatory information in an efficient manner. The work is described with particular reference to the metabolic network of Escherichia coli, which contains 808 individual enzymes. The assignment of confidence levels to these data, through the use of Gene Ontology evidence codes, is highlighted. In silico investigations may now be performed using the mathematical simulation workbench, DBsolve, which incorporates the facility to introduce data directly from XML.     

Cat odor causes long-lasting contextual fear conditioning and increased pituitary-adrenal activation, without modifying anxiety

A single exposure to a cat or cat odors has been reported by some groups to induce contextual and auditory fear conditioning and long-lasting changes in anxiety-like behaviour, but there is no evidence for parallel changes in biological stress markers. In the present study we demonstrated in male rats that exposure to a novel environment containing a cloth impregnated with cat fur odor resulted in avoidance of the odor, lower levels of activity and higher pituitary-adrenal (PA) response as compared to those exposed to the novel environment containing a clean cloth, suggesting increased levels of stress in the former animals. When re-exposed 9 days later to the same environment with a clean cloth, previously cat fur exposed rats again showed avoidance of the cloth area and lower levels of activity, suggesting development of contextual fear conditioning, which again was associated with a higher PA activation. In contrast, unaltered both anxiety-like behaviour and PA responsiveness to an elevated plus-maze were found 7 days after cat odor exposure. It is concluded that: (i) PA activation is able to reflect both the stressful properties of cat fur odor and odor-induced contextual fear conditioning; (ii) development of cat odor-induced contextual fear conditioning is independent of the induction of long-lasting changes in anxiety-like behaviour; and (iii) greater PA activation during exposure to the odor context is not explained by non-specific sensitization of the PA axis caused by previous exposure to cat fur odor.     

Untangling individual variation in natural populations: ecological, genetic and epigenetic correlates of long-term inequality in herbivory

Individual variation in ecologically important features of organisms is a crucial element in ecology and evolution, yet disentangling its underlying causes is difficult in natural populations. We applied a genomic scan approach using amplified fragment length polymorphism (AFLP) markers to quantify the genetic basis of long‐term individual differences in herbivory by mammals at a wild population of the violet Viola cazorlensis monitored for two decades. In addition, methylation‐sensitive amplified polymorphism (MSAP) analyses were used to investigate the association between browsing damage and epigenetic characteristics of individuals, an aspect that has been not previously explored for any wild plant. Structural equation modelling was used to identify likely causal structures linking genotypes, epigenotypes and herbivory. Individuals of V. cazorlensis differed widely in the incidence of browsing mammals over the 20‐year study period. Six AFLP markers (1.6% of total) were significantly related to herbivory, accounting altogether for 44% of population‐wide variance in herbivory levels. MSAP analyses revealed considerable epigenetic variation among individuals, and differential browsing damage was significantly related to variation in multilocus epigenotypes. In addition, variation across plants in epigenetic characteristics was related to variation in several herbivory‐related AFLP markers. Statistical comparison of alternative causal models suggested that individual differences in herbivory are the outcome of a complex causal structure where genotypes and epigenotypes are interconnected and have direct and indirect effects on herbivory. Insofar as methylation states of MSAP markers influential on herbivory are transgenerationally heritable, herbivore‐driven evolutionary changes at the study population will involve correlated changes in genotypic and epigenotypic distributions.     

Identification of genetic networks

In this report, we propose the use of structural equations as a tool for identifying and modeling genetic networks and genetic algorithms for searching the most likely genetic networks that best fit the data. After genetic networks are identified, it is fundamental to identify those networks influencing cell phenotypes. To accomplish this task we extend the concept of differential expression of the genes, widely used in gene expression data analysis, to genetic networks. We propose a definition for the differential expression of a genetic network and use the generalized T2 statistic to measure the ability of genetic networks to distinguish different phenotypes. However, describing the differential expression of genetic networks is not enough for understanding biological systems because differences in the expression of genetic networks do not directly reflect regulatory strength between gene activities. Therefore, in this report we also introduce the concept of differentially regulated genetic networks, which has the potential to assess changes of gene regulation in response to perturbation in the environment and may provide new insights into the mechanism of diseases and biological processes. We propose five novel statistics to measure the differences in regulation of genetic networks. To illustrate the concepts and methods for reconstruction of genetic networks and identification of association of genetic networks with function, we applied the proposed models and algorithms to three data sets.     

转录因子Egr-1参与长期性恐惧记忆和焦虑

锌指转录因子点Egr-1在将细胞外信号和胞内基因表达的变化相耦联过程中发挥重要的作用。海马和杏仁体是记忆形成和储存的两个主要的脑区。在海马和杏仁体中,Egr-1可被长时程增强（long-term potentiation,LTP）和学习过程上调。在Egr-1敲除小鼠上观察到晚时相声音恐惧记忆受损,而短时的痕迹和场景记忆却不受影响;另外,在Egr-1敲除小鼠上,用theta burst刺激杏仁体和听觉皮层所引起的突触增强被明显减弱或完全阻断。因此,我们的研究表明,转录因子Egr-1选择性地在晚时相听觉恐惧记忆中发挥作用。     

Dynamic modeling of genetic networks using genetic algorithm and S-system

MOTIVATION: The modeling of system dynamics of genetic networks, metabolic networks or signal transduction cascades from time-course data is formulated as a reverse-problem. Previous studies focused on the estimation of only network structures, and they were ineffective in inferring a network structure with feedback loops. We previously proposed a method to predict not only the network structure but also its dynamics using a Genetic Algorithm (GA) and an S-system formalism. However, it could predict only a small number of parameters and could rarely obtain essential structures. In this work, we propose a unified extension of the basic method. Notable improvements are as follows: (1) an additional term in its evaluation function that aims at eliminating futile parameters; (2) a crossover method called Simplex Crossover (SPX) to improve its optimization ability; and (3) a gradual optimization strategy to increase the number of predictable parameters. RESULTS: The proposed method is implemented as a C program called PEACE1 (Predictor by Evolutionary Algorithms and Canonical Equations 1). Its performance was compared with the basic method. The comparison showed that: (1) the convergence rate increased about 5-fold; (2) the optimization speed was raised about 1.5-fold; and (3) the number of predictable parameters was increased about 5-fold. Moreover, we successfully inferred the dynamics of a small genetic network constructed with 60 parameters for 5 network variables and feedback loops using only time-course data of gene expression.     

Untangling metabolic and communication networks: interactions of enterics with phytobacteria and their implications in produce safety

Recent outbreaks of vegetable-borne gastrointestinal illnesses across the globe demonstrate that human enteric pathogens can contaminate produce at any stage of production. Interactions of enterics with native plant-associated microbiota influence the microbiological safety of produce by affecting the attachment, persistence and proliferation of human pathogens on plants. Supermarket surveys have revealed that bacteria, but not fungi or mechanical damage, promote the growth of Salmonella enterica on produce. Field and laboratory studies have indicated that some plant pathogenic bacteria and fungi facilitate the entry and internalization of human pathogens in plants. Conversely, some phytobacteria, including those involved in biocontrol of plant diseases, significantly inhibit attachment and plant colonization by non-typhoidal Salmonella and enterovirulent Escherichia coli by producing antibiotics or competing for nutrients in the phyllosphere. In this review, we attempt to elucidate the mechanisms of interactions between human enteric pathogens and plant-associated microbiota, and describe how these interactions affect produce safety.     

Common genetic origins for EEG, alcoholism and anxiety: the role of CRH-BP

The resting EEG is a dynamic index of cortical activation, cognitive function and consciousness and is therefore an intermediate phenotype for many behaviors in which arousal is implicated such as anxiety and alcoholism. We performed a dense whole genome linkage scan using 3878 unlinked SNPs in a large pedigree derived from a population isolate sample of 328 Plains American Indians. Alpha (8-13 Hz), theta (4-8 Hz) and beta (13-30 Hz) EEG power was heritable (0.58-0.27) and stable over a 2 year period (r = 0.82-0.53). Genetic correlations between frequency bands were high (0.75). Linkage peaks for EEG power in all three frequency bands converged on chromosome 5q13-14 with genome-wide significant LOD scores of 3.5 (empirical p<0.0001) for alpha and beta power. A logical candidate gene, corticotropin releasing hormone-binding protein (CRH-BP), was located at the apex of these convergent linkage peaks. CRH-BP was significantly associated with alpha power in the Plains Indians and also in a replication sample of 188 Caucasians. Moreover, the same SNPs and haplotypes, located within the CRH-BP haplotype block, were also associated with anxiety disorders in the Plains Indians and alcohol use disorders in the Caucasians. CRH-BP modulates CRH which influences cortical and hippocampal EEG activity and is the primary mediator of the neuroendocrine stress response. Our results suggest a likely role for CRH-BP in stress-related alcoholism and highlight the use of the resting EEG as an intermediate phenotype for arousal-related behaviors such as anxiety and addiction.