Toward molecular trait‐based ecology through integration of biogeochemical,geographical and metagenomic data

Using metagenomic ‘parts lists’ to infer global patterns on microbial ecology remains a significant challenge. To deduce important ecological indicators such as environmental adaptation, molecular trait dispersal, diversity variation and primary production from the gene pool of an ecosystem, we integrated 25 ocean metagenomes with geographical, meteorological and geophysicochemical data. We find that climatic factors (temperature, sunlight) are the major determinants of the biomolecular repertoire of each sample and the main limiting factor on functional trait dispersal (absence of biogeographic provincialism). Molecular functional richness and diversity show a distinct latitudinal gradient peaking at 20°N and correlate with primary production. The latter can also be predicted from the molecular functional composition of an environmental sample. Together, our results show that the functional community composition derived from metagenomes is an important quantitative readout for molecular trait‐based biogeography and ecology.     

eggNOG-mapper v2: Functional Annotation,Orthology Assignments,and Domain Prediction at the Metagenomic Scale

Even though automated functional annotation of genes represents a fundamental step in most genomic and metagenomic workflows, it remains challenging at large scales. Here, we describe a major upgrade to eggNOG-mapper, a tool for functional annotation based on precomputed orthology assignments, now optimized for vast (meta)genomic data sets. Improvements in version 2 include a full update of both the genomes and functional databases to those from eggNOG v5, as well as several efficiency enhancements and new features. Most notably, eggNOG-mapper v2 now allows for: 1) de novo gene prediction from raw contigs, 2) built-in pairwise orthology prediction, 3) fast protein domain discovery, and 4) automated GFF decoration. eggNOG-mapper v2 is available as a standalone tool or as an online service at http://eggnog-mapper.embl.de.     

Managing biological control services through multi‐trophic trait interactions: review and guidelines for implementation at local and landscape scales

Ecological studies are increasingly moving towards trait‐based approaches, as the evidence mounts that functions, as opposed to taxonomy, drive ecosystem service delivery. Among ecosystem services, biological control has been somewhat overlooked in functional ecological studies. This is surprising given that, over recent decades, much of biological control research has been focused on identifying the multiple characteristics (traits) of species that influence trophic interactions. These traits are especially well developed for interactions between arthropods and flowers – important for biological control, as floral resources can provide natural enemies with nutritional supplements, which can dramatically increase biological control efficiency. Traits that underpin the biological control potential of a community and that drive the response of arthropods to environmental filters, from local to landscape‐level conditions, are also emerging from recent empirical studies. We present an overview of the traits that have been identified to (i) drive trophic interactions, especially between plants and biological control agents through determining access to floral resources and enhancing longevity and fecundity of natural enemies, (ii) affect the biological control services provided by arthropods, and (iii) limit the response of arthropods to environmental filters, ranging from local management practices to landscape‐level simplification. We use this review as a platform to outline opportunities and guidelines for future trait‐based studies focused on the enhancement of biological control services.     

Ecological genomics meets community‐level modelling of biodiversity: mapping the genomic landscape of current and future environmental adaptation

Local adaptation is a central feature of most species occupying spatially heterogeneous environments, and may factor critically in responses to environmental change. However, most efforts to model the response of species to climate change ignore intraspecific variation due to local adaptation. Here, we present a new perspective on spatial modelling of organism–environment relationships that combines genomic data and community‐level modelling to develop scenarios regarding the geographic distribution of genomic variation in response to environmental change. Rather than modelling species within communities, we use these techniques to model large numbers of loci across genomes. Using balsam poplar (Populus balsamifera) as a case study, we demonstrate how our framework can accommodate nonlinear responses of loci to environmental gradients. We identify a threshold response to temperature in the circadian clock gene GIGANTEA‐5 (GI5), suggesting that this gene has experienced strong local adaptation to temperature. We also demonstrate how these methods can map ecological adaptation from genomic data, including the identification of predicted differences in the genetic composition of populations under current and future climates. Community‐level modelling of genomic variation represents an important advance in landscape genomics and spatial modelling of biodiversity that moves beyond species‐level assessments of climate change vulnerability.     

The value of applying molecular biology tools in environmental engineering: Academic and industry perspective in the USA

The integration of molecular biology tools in environmental engineering is a challenge. We discuss our views on the following four critical issues: (i) faculty career development, (ii) tool standardization, (iii) teaching, and (iv) the application of molecular biology tools in practice. For (i), we suggest that administrators and faculty need to understand the special challenges inherent to research and teaching within this highly interdisciplinary area. Furthermore, we suggest preparing two white papers aimed at educating administrators in universities and agencies. For (ii), we conclude that, because molecular biology tools are still in a state of rapid development, proposing standards at this time is premature. In the future, standards for widely applied tools should be in an on-line, peer-reviewed format. Concerning (iii), we believe that molecular biology should be taught only to the degree needed to achieve program goals. For example, environmental engineering practitioners only need to know the vocabulary and basic concepts of molecular biology tools, not be experts at doing them hands on. To help engineering students gain the right level and type of information, learning modules should be developed for them. Finally, although engineering successes applying molecular biology tools are available (iv), the biggest value will come when the tools are fully integrated with practice. Therefore, we encourage the creation of a demonstration project to document the value of applying molecular biology tools in environmental engineering. This revised version was published online in June 2006 with corrections to the Cover Date.     

Islands as model systems in ecology and evolution: prospects fifty years after MacArthur‐Wilson

The study of islands as model systems has played an important role in the development of evolutionary and ecological theory. The 50th anniversary of MacArthur and Wilson's (December 1963) article, ‘An equilibrium theory of insular zoogeography’, was a recent milestone for this theme. Since 1963, island systems have provided new insights into the formation of ecological communities. Here, building on such developments, we highlight prospects for research on islands to improve our understanding of the ecology and evolution of communities in general. Throughout, we emphasise how attributes of islands combine to provide unusual research opportunities, the implications of which stretch far beyond islands. Molecular tools and increasing data acquisition now permit re‐assessment of some fundamental issues that interested MacArthur and Wilson. These include the formation of ecological networks, species abundance distributions, and the contribution of evolution to community assembly. We also extend our prospects to other fields of ecology and evolution – understanding ecosystem functioning, speciation and diversification – frequently employing assets of oceanic islands in inferring the geographic area within which evolution has occurred, and potential barriers to gene flow. Although island‐based theory is continually being enriched, incorporating non‐equilibrium dynamics is identified as a major challenge for the future.     

Drawing ecological inferences from coincident patterns of population‐ and community‐level biodiversity

Biodiversity is comprised of genetic and phenotypic variation among individual organisms, which might belong to the same species or to different species. Spatial patterns of biodiversity are of central interest in ecology and evolution for several reasons: to identify general patterns in nature (e.g. species–area relationships, latitudinal gradients), to inform conservation priorities (e.g. identifying hotspots, prioritizing management efforts) and to draw inferences about processes, historical or otherwise (e.g. adaptation, the centre of origin of particular clades). There are long traditions in ecology and evolutionary biology of examining spatial patterns of biodiversity among species (i.e. in multispecies communities) and within species, respectively, and there has been a recent surge of interest in studying these two types of pattern simultaneously. The idea is that examining both levels of diversity can materially advance the above‐stated goals and perhaps lead to entirely novel lines of inquiry. Here, we review two broad categories of approach to merging studies of inter‐ and intraspecific variation: (i) the study of phenotypic trait variation along environmental gradients and (ii) the study of relationships between patterns of molecular genetic variation within species and patterns of distribution and diversity across species. For the latter, we report a new meta‐analysis in which we find that correlations between species diversity and genetic diversity are generally positive and significantly stronger in studies with discrete sampling units (e.g. islands, lakes, forest fragments) than in studies with nondiscrete sampling units (e.g. equal‐area study plots). For each topic, we summarize the current state of knowledge and key future directions.     

Water‐level fluctuations regulate the structure and functioning of natural lakes

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Population genomics of eusocial insects: the costs of a vertebrate‐like effective population size

The evolution of reproductive division of labour and social life in social insects has lead to the emergence of several life‐history traits and adaptations typical of larger organisms: social insect colonies can reach masses of several kilograms, they start reproducing only when they are several years old, and can live for decades. These features and the monopolization of reproduction by only one or few individuals in a colony should affect molecular evolution by reducing the effective population size. We tested this prediction by analysing genome‐wide patterns of coding sequence polymorphism and divergence in eusocial vs. noneusocial insects based on newly generated RNA‐seq data. We report very low amounts of genetic polymorphism and an elevated ratio of nonsynonymous to synonymous changes – a marker of the effective population size – in four distinct species of eusocial insects, which were more similar to vertebrates than to solitary insects regarding molecular evolutionary processes. Moreover, the ratio of nonsynonymous to synonymous substitutions was positively correlated with the level of social complexity across ant species. These results are fully consistent with the hypothesis of a reduced effective population size and an increased genetic load in eusocial insects, indicating that the evolution of social life has important consequences at both the genomic and population levels.     

In Silico Analysis of Crop Science： Report on the First China-UK Workshop on Chips, Computers and Crops

A workshop on ＂Chips, Computers and Crops＂ was held in Hangzhou, China during September 26-27, 2008. The main objective of the workshop was to bring together China and UK scientists from mathematics, bioinformatics and plant molecular biology communities to exchange ideas, enhance awareness of each others＇ fields, explore synergisms and make recommendations on fruitful future directions in crop science. Here we describe the contributions to the workshop, and examine some conceptual issues that lie at the foundations and future of crop systems biology.     

Communities of ground‐dwelling arthropods in conventional and transgenic maize: background data for the post‐market environmental monitoring

To verify the validity of concerns about environmental safety of maize expressing insecticidal Cry toxins (referred to as Bt maize), we compared communities of ground beetles (Carabidae), rove beetles (Staphylinidae) and spiders (Araneae) in plots planted either with Bt maize cultivar YieldGard^® or with the non‐transgenic parental cultivar Monumental. Each cultivar was grown on 5 plots of 0.5 ha for three consecutive years. To increase the field load of Cry toxin, the fully grown maize of the first study year was shredded to small pieces that were ploughed into the soil. Arthropods were collected in pitfall traps and determined to the species level. The abundance and species richness of all studied groups greatly varied over the season and between the seasons but without statistically significant differences between the Bt and non‐Bt plots. A single spider species and three ground beetle species dominated in the catches every year, whereas a set of 1–4 most abundant rove beetle species changed every year. Frequently occurring species were typical for most of Europe. The total counts of ground beetles, rove beetles and spiders collected once or twice per season are proposed to serve as bioindicators in the post‐market environmental monitoring (PMEM).