Analysis of selection pressure exerted on Plasmopara viticola by organically based fungicides

Downy mildew is one of the most important grape diseases world-wide. The pathogen is a genetically highly diversified organism with a high capacity of adaptation. A monitoring of changes in population structure of P. viticola subjected to new copper replacing products or strategies, studied and developed within REPCO (Replacement of Copper Fungicides in Organic Production of Grapevine and Apple in Europe) is important for assessing selection pressure which could lead to a reduction of efficacy of these new measures. Therefore P. viticola lesions collected on untreated and treated vines were analyzed by means of microsatellite markers. No significant differences in the populations structure were determined among untreated and treated populations, indicating that the applied products didn’t exerted any selection pressure on the P. viticola populations

Nest choice in arboreal ants is an emergent consequence of network creation under spatial constraints

Biological transportation networks must balance competing functional priorities. The selforganizing mechanisms used to generate such networks have inspired scalable algorithms to construct and maintain low-cost and efficient human-designed transport networks. The pheromone-based trail networks of ants have been especially valuable in this regard. Here, we use turtle ants as our focal system: In contrast to the ant species usually used as models for self-organized networks, these ants live in a spatially constrained arboreal environment where both nesting options and connecting pathways are limited. Thus, they must solve a distinct set of challenges which resemble those faced by human transport engineers constrained by existing infrastructure. Here, we ask how a turtle ant colony’s choice of which nests to include in a network may be influenced by their potential to create connections to other nests. In laboratory experiments with Cephalotes varians and Cephalotes texanus, we show that nest choice is influenced by spatial constraints, but in unexpected ways. Under one spatial configuration, colonies preferentially occupied more connected nest sites; however, under another spatial configuration, this preference disappeared. Comparing the results of these experiments to an agent-based model, we demonstrate that this apparently idiosyncratic relationship between nest connectivity and nest choice can emerge without nest preferences via a combination of self-reinforcing random movement along constrained pathways and density-dependent aggregation at nests. While this mechanism does not consistently lead to the de-novo construction of low-cost, efficient transport networks, it may be an effective way to expand a network, when coupled with processes of pruning and restructuring

Microsatellite markers spanning the apple ( Malus x domestica Borkh.) genome

A new set of 148 apple microsatellite markers has been developed and mapped on the apple reference linkage map Fiesta x Discovery. One-hundred and seventeen markers were developed from genomic libraries enriched with the repeats GA, GT, AAG, AAC and ATC; 31 were developed from EST sequences. Markers derived from sequences containing dinucleotide repeats were generally more polymorphic than sequences containing trinucleotide repeats. Additional eight SSRs from published apple, pear, and Sorbus torminalis SSRs, whose position on the apple genome was unknown, have also been mapped. The transferability of SSRs across Maloideae species resulted in being efficient with 41% of the markers successfully transferred. For all 156 SSRs, the primer sequences, repeat type, map position, and quality of the amplification products are reported. Also presented are allele sizes, ranges, and number of SSRs found in a set of nine cultivars. All this information and those of the previous CH-SSR series can be searched at the apple SSR database ( http://www.hidras.unimi.it ) to which updates and comments can be added. A large number of apple ESTs containing SSR repeats are available and should be used for the development of new apple SSRs. The apple SSR database is also meant to become an international platform for coordinating this effort. The increased coverage of the apple genome with SSRs allowed the selection of a set of 86 reliable, highly polymorphic, and overall the apple genome well-scattered SSRs. These SSRs cover about 85% of the genome with an average distance of one marker per 15c

Competition and habitat availability interact to structure arboreal ant communities across scales of ecological organization

Understanding how resource limitation and biotic interactions interact across spatial scales is fundamental to explaining the structure of ecological communities. However, empirical studies addressing this issue are often hindered by logistical constraints, especially at local scales. Here, we use a highly tractable arboreal ant study system to explore the interactive effects of resource availability and competition on community structure across three local scales: an individual tree, the nest network created by each colony and the individual ant nest. On individual trees, the ant assemblages are primarily shaped by availability of dead wood, a critical nesting resource. The nest networks within a tree are constrained by the availability of nesting resources but also influenced by the co-occurring species. Within individual nests, the distribution of adult ants is only affected by distance to interspecific competitors. These findings demonstrate that resource limitation exerts the strongest effects on diversity at higher levels of local ecological organization, transitioning to a stronger effect of species interactions at finer scales. Collectively, these results highlight that the process exerting the strongest influence on community structure is highly dependent on the scale at which we examine the community, with shifts occurring even across fine-grained local scales

Integrated information increases with fitness in the evolution of animats

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent ("animat") evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its "fit" to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data.Comment: 27 pages, 8 figures, one supplementary figure. Three supplementary video files available on request. Version commensurate with published text in PLoS Comput. Bio

Access to RNA-sequencing data from 1,173 plant species: The 1000 Plant transcriptomes initiative (1KP)

The 1000 Plant transcriptomes initiative (1KP) explored genetic diversity by sequencing RNA from 1,342 samples representing 1,173 species of green plants (Viridiplantae).This data release accompanies the initiative's final/capstone publication on a set of 3 analyses inferring species trees, whole genome duplications, and gene family expansions. These and previous analyses are based on de novo transcriptome assemblies and related gene predictions. Here, we assess their data and assembly qualities and explain how we detected potential contaminations.These data will be useful to plant and/or evolutionary scientists with interests in particular gene families, either across the green plant tree of life or in more focused lineages

The Value of Information for Populations in Varying Environments

The notion of information pervades informal descriptions of biological systems, but formal treatments face the problem of defining a quantitative measure of information rooted in a concept of fitness, which is itself an elusive notion. Here, we present a model of population dynamics where this problem is amenable to a mathematical analysis. In the limit where any information about future environmental variations is common to the members of the population, our model is equivalent to known models of financial investment. In this case, the population can be interpreted as a portfolio of financial assets and previous analyses have shown that a key quantity of Shannon's communication theory, the mutual information, sets a fundamental limit on the value of information. We show that this bound can be violated when accounting for features that are irrelevant in finance but inherent to biological systems, such as the stochasticity present at the individual level. This leads us to generalize the measures of uncertainty and information usually encountered in information theory

The Minimal Complexity of Adapting Agents Increases with Fitness

What is the relationship between the complexity and the fitness of evolved organisms, whether natural or artificial? It has been asserted, primarily based on empirical data, that the complexity of plants and animals increases as their fitness within a particular environment increases via evolution by natural selection. We simulate the evolution of the brains of simple organisms living in a planar maze that they have to traverse as rapidly as possible. Their connectome evolves over 10,000s of generations. We evaluate their circuit complexity, using four information-theoretical measures, including one that emphasizes the extent to which any network is an irreducible entity. We find that their minimal complexity increases with their fitness

Data access for the 1,000 Plants (1KP) project

© 2014 Matasci et al.; licensee BioMed Central Ltd. The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets

The iPlant Collaborative: Cyberinfrastructure for Plant Biology

The iPlant Collaborative (iPlant) is a United States National Science Foundation (NSF) funded project that aims to create an innovative, comprehensive, and foundational cyberinfrastructure in support of plant biology research (PSCIC, 2006). iPlant is developing cyberinfrastructure that uniquely enables scientists throughout the diverse fields that comprise plant biology to address Grand Challenges in new ways, to stimulate and facilitate cross-disciplinary research, to promote biology and computer science research interactions, and to train the next generation of scientists on the use of cyberinfrastructure in research and education. Meeting humanity's projected demands for agricultural and forest products and the expectation that natural ecosystems be managed sustainably will require synergies from the application of information technologies. The iPlant cyberinfrastructure design is based on an unprecedented period of research community input, and leverages developments in high-performance computing, data storage, and cyberinfrastructure for the physical sciences. iPlant is an open-source project with application programming interfaces that allow the community to extend the infrastructure to meet its needs. iPlant is sponsoring community-driven workshops addressing specific scientific questions via analysis tool integration and hypothesis testing. These workshops teach researchers how to add bioinformatics tools and/or datasets into the iPlant cyberinfrastructure enabling plant scientists to perform complex analyses on large datasets without the need to master the command-line or high-performance computational services