Single‐nucleotide polymorphism discovery in Leptographium longiclavatum,a mountain pine beetle‐associated symbiotic fungus,using whole‐genome resequencing

Single‐nucleotide polymorphisms (SNPs) are rapidly becoming the standard markers in population genomics studies; however, their use in nonmodel organisms is limited due to the lack of cost‐effective approaches to uncover genome‐wide variation, and the large number of individuals needed in the screening process to reduce ascertainment bias. To discover SNPs for population genomics studies in the fungal symbionts of the mountain pine beetle (MPB), we developed a road map to discover SNPs and to produce a genotyping platform. We undertook a whole‐genome sequencing approach of Leptographium longiclavatum in combination with available genomics resources of another MPB symbiont, Grosmannia clavigera. We sequenced 71 individuals pooled into four groups using the Illumina sequencing technology. We generated between 27 and 30 million reads of 75 bp that resulted in a total of 1, 181 contigs longer than 2 kb and an assembled genome size of 28.9 Mb (N₅₀ = 48 kb, average depth = 125x). A total of 9052 proteins were annotated, and between 9531 and 17 266 SNPs were identified in the four pools. A subset of 206 genes (containing 574 SNPs, 11% false positives) was used to develop a genotyping platform for this species. Using this roadmap, we developed a genotyping assay with a total of 147 SNPs located in 121 genes using the Illumina^® Sequenom iPLEX Gold. Our preliminary genotyping (success rate = 85%) of 304 individuals from 36 populations supports the utility of this approach for population genomics studies in other MPB fungal symbionts and other fungal nonmodel species.     

Which species,how many,and from where: Integrating habitat suitability,population genomics,and abundance estimates into species reintroduction planning

Extirpated organisms are reintroduced into their former ranges worldwide to combat species declines and biodiversity losses. The growing field of reintroduction biology provides guiding principles for reestablishing populations, though criticisms remain regarding limited integration of initial planning, modeling frameworks, interdisciplinary collaborations, and multispecies approaches. We used an interdisciplinary, multispecies, quantitative framework to plan reintroductions of three fish species into Abrams Creek, Great Smoky Mountains National Park, USA. We first assessed the appropriateness of habitat at reintroduction sites for banded sculpin (Cottus carolinae), greenside darter (Etheostoma blennioides), and mottled sculpin (Cottus bairdii) using species distribution modeling. Next, we evaluated the relative suitability of nine potential source stock sites using population genomics, abundance estimates, and multiple‐criteria decision analysis (MCDA) based on known correlates of reintroduction success. Species distribution modeling identified mottled sculpin as a poor candidate, but banded sculpin and greenside darter as suitable candidates for reintroduction based on species‐habitat relationships and habitats available in Abrams Creek. Genotyping by sequencing revealed acceptable levels of genetic diversity at all candidate source stock sites, identified population clusters, and allowed for estimating the number of fish that should be included in translocations. Finally, MCDA highlighted priorities among candidate source stock sites that were most likely to yield successful reintroductions based on differential weightings of habitat assessment, population genomics, and the number of fish available for translocation. Our integrative approach represents a unification of multiple recent advancements in the field of reintroduction biology and highlights the benefit of shifting away from simply choosing nearby populations for translocation to an information‐based science with strong a priori planning coupled with several suggested posteriori monitoring objectives. Our framework can be applied to optimize reintroduction successes for a multitude of organisms and advances in the science of reintroduction biology by simultaneously addressing a variety of past criticisms of the field.     

Beyond the genome: Reconstituting the new genetics

The mapping and sequencing of the human genome has been the 'Holy Grail' of the new genetics, and its publication marks a turning point in the development of modern biotechnology. However, the question remains: what has been the impact of this discovery on how biotechnology develops in science, and in society at large? Using concepts developed in the social studies of science and technology, the paper begins by rehearsing the historical development of the Human Genome Project (HGP), and suggests that its translation into genomics has been achieved through a process of 'black-boxing' to ensure stabilization. It continues by exploring the extent to which the move to genomics is part of a paradigm shift in biotechnology resulting from the conceptual and organizational changes that have occurred following the completion of HGP. The discussion then focuses on whether genomics can be seen as part of the development of socially robust knowledge in late modernity. The paper suggests that there is strong evidence that a transformation is indeed taking place. It concludes by sketching a social scientific agenda for investigating the reconstitution of the new genetics in a post-genomic era using a 'situated' analytic approach based on an understanding of techno-scientific change as both emergent and contingent.     

主要禾谷类作物比较基因组学研究策略与进展

随着拟南芥、水稻等模式植物基因组测序计划的完成, 比较基因组学作为一门新兴学科, 近年来发展迅速, 为植物基因组的进化、结构和功能研究开辟了新的途径。文章综述了比较基因组学在作物比较遗传作图、基因结构区域的微共线性、ESTs和蛋白质水平的比较以及基于比较基因组学的基因和QTL的克隆等方面内容与研究进展, 分析了不同水平上比较基因组学研究策略的原理、特点、可行性, 以期为利用模式生物的基因和基因组数据、采用比较基因组学策略克隆作物重要性状功能基因、阐明基因组结构与进化提供帮助。     

Time‐resolved quantitative proteome profiling of host–pathogen interactions: The response of Staphylococcus aureus RN1HG to internalisation by human airway epithelial cells

Staphylococcus aureus is a versatile Gram‐positive pathogen that gains increasing importance due to the rapid spreading of resistances. Functional genomics technologies can provide new insights into the adaptational network of this bacterium and its response to environmental challenges. While functional genomics technologies, including proteomics, have been extensively used to study these phenomena in shake flask cultures, studies of bacteria from in vivo settings lack behind. Particularly for proteomics studies, the major bottleneck is the lack of sufficient proteomic coverage for low numbers of cells. In this study, we introduce a workflow that combines a pulse‐chase stable isotope labelling by amino acids in cell culture approach with high capacity cell sorting, on‐membrane digestion, and high‐sensitivity MS to detect and quantitatively monitor several hundred S. aureus proteins from a few million internalised bacteria. This workflow has been used in a proof‐of‐principle experiment to reveal changes in levels of proteins with a function in protection against oxidative damage and adaptation of cell wall synthesis in strain RN1HG upon internalisation by S9 human bronchial epithelial cells.     

Human behavioral ecology and niche construction

We examine the relationship between niche construction theory (NCT) and human behavioral ecology (HBE), two branches of evolutionary science that are important sources of theory in archeology. We distinguish between formal models of niche construction as an evolutionary process, and uses of niche construction to refer to a kind of human behavior. Formal models from NCT examine how environmental modification can change the selection pressures that organisms face. In contrast, formal models from HBE predict behavior assuming people behave adaptively in their local setting, and can be used to predict when and why people engage in niche construction. We emphasize that HBE as a field is much broader than foraging theory and can incorporate social and cultural influences on decision‐making. We demonstrate how these approaches can be formally incorporated in a multi‐inheritance framework for evolutionary research, and argue that archeologists can best contribute to evolutionary theory by building and testing models that flexibly incorporate HBE and NCT elements.     

Population genomics: a new generation of genome scans to bridge the gap with functional genomics

Population genomics is an increasingly popular approach to investigate the genetic basis of adaptation and speciation at the genome scale. However, it has so far largely failed to go beyond the mere identification of anonymous markers displaying selection signatures. Will population genomics ever be up to our expectations and able to really pinpoint genes underlying adaptation and speciation processes? In this issue of Molecular Ecology, Namroud et al. use population genomics to investigate local adaptation in natural populations of a conifer tree, the white spruce (Picea glauca). They show how population and functional genomics can finally converge with the deployment of the next generation of genome scans, which target gene‐rich regions rather than the whole genome.     

Advances in sex determination in bats and its utility in wind‐wildlife studies

We developed a simple and reliable genetic method to determine sex in bats from the Vespertilionidae and Molossidae families. Polymerase chain reaction was used to amplify a portion of the introns within the zinc‐finger‐X (Zfx) and zinc‐finger‐Y (Zfy) genes. We designed primers to produce size variation between the Zfx and Zfy products that could be visualized using gel electrophoresis. Using an example from our wind‐wildlife research, we show how sex data generated using this method are superior to sex data based on external morphology. Our method allows for the generation of sex data across a wide range of bats that can be used to address key questions in wildlife forensics, behavioural ecology, conservation and evolutionary biology.     

Applicability of RAD‐tag genotyping for interfamilial comparisons: empirical data from two cetaceans

Restriction‐site‐associated DNA tag (RAD‐tag) sequencing has become a popular approach to generate thousands of SNPs used to address diverse questions in population genomics. Comparatively, the suitability of RAD‐tag genotyping to address evolutionary questions across divergent species has been the subject of only a few recent studies. Here, we evaluate the applicability of this approach to conduct genome‐wide scans for polymorphisms across two cetacean species belonging to distinct families: the short‐beaked common dolphin (Delphinus delphis; n = 5 individuals) and the harbour porpoise (Phocoena phocoena; n = 1 individual). Additionally, we explore the effects of varying two parameters in the Stacks analysis pipeline on the number of loci and level of divergence obtained. We observed a 34% drop in the total number of loci that were present in all individuals when analysing individuals from the distinct families compared with analyses restricted to intraspecific comparisons (i.e. within D. delphis). Despite relatively stringent quality filters, 3595 polymorphic loci were retrieved from our interfamilial comparison. Cetaceans have undergone rapid diversification, and the estimated divergence time between the two families is relatively recent (14–19 Ma). Thus, our results showed that, for this level of divergence, a large number of orthologous loci can still be genotyped using this approach, which is on par with two recent in silico studies. Our findings constitute one of the first empirical investigations using RAD‐tag sequencing at this level of divergence and highlights the great potential of this approach in comparative studies and to address evolutionary questions.     

Correcting for bias in distribution modelling for rare species using citizen science data

Aim

To improve the accuracy of inferences on habitat associations and distribution patterns of rare species by combining machine‐learning, spatial filtering and resampling to address class imbalance and spatial bias of large volumes of citizen science data.

Innovation

Modelling rare species’ distributions is a pressing challenge for conservation and applied research. Often, a large number of surveys are required before enough detections occur to model distributions of rare species accurately, resulting in a data set with a high proportion of non‐detections (i.e. class imbalance). Citizen science data can provide a cost‐effective source of surveys but likely suffer from class imbalance. Citizen science data also suffer from spatial bias, likely from preferential sampling. To correct for class imbalance and spatial bias, we used spatial filtering to under‐sample the majority class (non‐detection) while maintaining all of the limited information from the minority class (detection). We investigated the use of spatial under‐sampling with randomForest models and compared it to common approaches used for imbalanced data, the synthetic minority oversampling technique (SMOTE), weighted random forest and balanced random forest models. Model accuracy was assessed using kappa, Brier score and AUC. We demonstrate the method by evaluating habitat associations and seasonal distribution patterns using citizen science data for a rare species, the tricoloured blackbird (Agelaius tricolor).

Main Conclusions

Spatial under‐sampling increased the accuracy of each model and outperformed the approach typically used to direct under‐sampling in the SMOTE algorithm. Our approach is the first to characterize winter distribution and movement of tricoloured blackbirds. Our results show that tricoloured blackbirds are positively associated with grassland, pasture and wetland habitats, and negatively associated with high elevations or evergreen forests during both winter and breeding seasons. The seasonal differences in distribution indicate that individuals move to the coast during the winter, as suggested by historical accounts.

     

Using the Value of Information to improve conservation decision making

Conservation decisions are challenging, not only because they often involve difficult conflicts among outcomes that people value, but because our understanding of the natural world and our effects on it is fraught with uncertainty. Value of Information (VoI) methods provide an approach for understanding and managing uncertainty from the standpoint of the decision maker. These methods are commonly used in other fields (e.g. economics, public health) and are increasingly used in biodiversity conservation. This decision‐analytical approach can identify the best management alternative to select where the effectiveness of interventions is uncertain, and can help to decide when to act and when to delay action until after further research. We review the use of VoI in the environmental domain, reflect on the need for greater uptake of VoI, particularly for strategic conservation planning, and suggest promising areas for new research. We also suggest common reporting standards as a means of increasing the leverage of this powerful tool. The environmental science, ecology and biodiversity categories of the Web of Knowledge were searched using the terms ‘Value of Information,’ ‘Expected Value of Perfect Information,’ and the abbreviation ‘EVPI.’ Google Scholar was searched with the same terms, and additionally the terms decision and biology, biodiversity conservation, fish, or ecology. We identified 1225 papers from these searches. Included studies were limited to those that showed an application of VoI in biodiversity conservation rather than simply describing the method. All examples of use of VOI were summarised regarding the application of VoI, the management objectives, the uncertainties, the models used, how the objectives were measured, and the type of VoI. While the use of VoI appears to be on the increase in biodiversity conservation, the reporting of results is highly variable, which can make it difficult to understand the decision context and which uncertainties were considered. Moreover, it was unclear if, and how, the papers informed management and policy interventions, which is why we suggest a range of reporting standards that would aid the use of VoI. The use of VoI in conservation settings is at an early stage. There are opportunities for broader applications, not only for species‐focussed management problems, but also for setting local or global research priorities for biodiversity conservation, making funding decisions, or designing or improving protected area networks and management. The long‐term benefits of applying VoI methods to biodiversity conservation include a more structured and decision‐focused allocation of resources to research.     

Mediated speculations in the genomics futures markets

This article examines the interactions between the media and genomics, with particular reference to the case of deCODE Genetics in Iceland. It focuses on the role of "forward-looking statements" and other forms of speculation as they operate in the science of genomics, in the social relations that happen around genomics, and in the commercial genomics economy. The article discusses how these fundamentally anticipatory speech acts uttered or written by genomic corporate executives, journalists, or social scientists are simultaneously volatile, exceeding any formal practices of accounting or analysis, and demanding to be accounted for, analysed, or valued. The article discusses four speculative events or cases in the genomics economy: the March 2000 bursting out of the genomics bubble, prompted in part by remarks by President Clinton and Prime Minister Blair to the media concerning gene patenting; the new disclosure requirements of the US Securities and Exchange Commission (SEC) regarding "forward-looking statements" as they appear in genomics press releases; deCODE Genetics' registration statement with the SEC that discloses a settlement of a dispute over the ownership of a fragment of DNA; and the entanglement between the author's ethnographic fieldwork and the breaking news story of reported payoffs from deCODE to the Icelandic political parties.     

Molecular diversity and landscape genomics of the crop wild relative Triticum urartu across the Fertile Crescent

Modern plant breeding can benefit from the allelic variation that exists in natural populations of crop wild relatives that evolved under natural selection in varying pedoclimatic conditions. In this study, next‐generation sequencing was used to generate 1.3 million genome‐wide single nucleotide polymorphisms (SNPs) on ex situ collections of Triticum urartu L., the wild donor of the A^u subgenome of modern wheat. A set of 75 511 high‐quality SNPs were retained to describe 298 T. urartu accessions collected throughout the Fertile Crescent. Triticum urartu showed a complex pattern of genetic diversity, with two main genetic groups distributed sequentially from west to east. The incorporation of geographical information on sampling points showed that genetic diversity was correlated to the geographical distance (R² = 0.19) separating samples from Jordan and Lebanon, from Syria and southern Turkey, and from eastern Turkey, Iran and Iraq. The wild emmer genome was used to derive the physical positions of SNPs on the seven chromosomes of the A^u subgenome, allowing us to describe a relatively slow decay of linkage disequilibrium in the collection. Outlier loci were described on the basis of the geographic distribution of the T. urartu accessions, identifying a hotspot of directional selection on chromosome 4A. Bioclimatic variation was derived from grid data and related to allelic variation using a genome‐wide association approach, identifying several marker–environment associations (MEAs). Fifty‐seven MEAs were associated with altitude and temperature measures while 358 were associated with rainfall measures. The most significant MEAs and outlier loci were used to identify genomic loci with adaptive potential (some already reported in wheat), including dormancy and frost resistance loci. We advocate the application of genomics and landscape genomics on ex situ collections of crop wild relatives to efficiently identify promising alleles and genetic materials for incorporation into modern crop breeding.     

CropSNPdb: a database of SNP array data for Brassica crops and hexaploid bread wheat

Advances in sequencing technology have led to a rapid rise in the genomic data available for plants, driving new insights into the evolution, domestication and improvement of crops. Single nucleotide polymorphisms (SNPs) are a major component of crop genomic diversity, and are invaluable as genetic markers in research and breeding programs. High‐throughput SNP arrays, or ‘SNP chips’, can generate reproducible sets of informative SNP markers and have been broadly adopted. Although there are many public repositories for sequencing data, which are routinely uploaded, there are no formal repositories for crop SNP array data. To make SNP array data more easily accessible, we have developed CropSNPdb ( http://snpdb.appliedbioinformatics.com.au ), a database for SNP array data produced by the Illumina Infinium? hexaploid bread wheat (Triticum aestivum) 90K and Brassica 60K arrays. We currently host SNPs from datasets covering 526 Brassica lines and 309 bread wheat lines, and provide search, download and upload utilities for users. CropSNPdb provides a useful repository for these data, which can be applied for a range of genomics and molecular crop‐breeding activities.     

batemanater: a computer program to estimate and bootstrap mating system variables based on Bateman's principles

Bateman's principles continue to play a major role in the characterization of genetic mating systems in natural populations. The modern manifestations of Bateman's ideas include the opportunity for sexual selection (i.e. I_s – the variance in relative mating success), the opportunity for selection (i.e. I – the variance in relative reproductive success) and the Bateman gradient (i.e. β_ss – the slope of the least‐squares regression of reproductive success on mating success). These variables serve as the foundation for one convenient approach for the quantification of mating systems. However, their estimation presents at least two challenges, which I address here with a new Windows‐based computer software package called batemanater . The first challenge is that confidence intervals for these variables are not easy to calculate. batemanater solves this problem using a bootstrapping approach. The second, more serious, problem is that direct estimates of mating system variables from open populations will typically be biased if some potential progeny or adults are missing from the analysed sample. batemanater addresses this problem using a maximum‐likelihood approach to estimate mating system variables from incompletely sampled breeding populations. The current version of batemanater addresses the problem for systems in which progeny can be collected in groups of half‐ or full‐siblings, as would occur when eggs are laid in discrete masses or offspring occur in pregnant females. batemanater has a user‐friendly graphical interface and thus represents a new, convenient tool for the characterization and comparison of genetic mating systems.     

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.