Transgene × Environment Interactions in Genetically Modified Wheat

BACKGROUND: The introduction of transgenes into plants may cause unintended phenotypic effects which could have an impact on the plant itself and the environment. Little is published in the scientific literature about the interrelation of environmental factors and possible unintended effects in genetically modified (GM) plants. METHODS AND FINDINGS: We studied transgenic bread wheat Triticum aestivum lines expressing the wheat Pm3b gene against the fungus powdery mildew Blumeria graminis f.sp. tritici. Four independent offspring pairs, each consisting of a GM line and its corresponding non-GM control line, were grown under different soil nutrient conditions and with and without fungicide treatment in the glasshouse. Furthermore, we performed a field experiment with a similar design to validate our glasshouse results. The transgene increased the resistance to powdery mildew in all environments. However, GM plants reacted sensitive to fungicide spraying in the glasshouse. Without fungicide treatment, in the glasshouse GM lines had increased vegetative biomass and seed number and a twofold yield compared with control lines. In the field these results were reversed. Fertilization generally increased GM/control differences in the glasshouse but not in the field. Two of four GM lines showed up to 56% yield reduction and a 40-fold increase of infection with ergot disease Claviceps purpurea compared with their control lines in the field experiment; one GM line was very similar to its control. CONCLUSIONS: Our results demonstrate that, depending on the insertion event, a particular transgene can have large effects on the entire phenotype of a plant and that these effects can sometimes be reversed when plants are moved from the glasshouse to the field. However, it remains unclear which mechanisms underlie these effects and how they may affect concepts in molecular plant breeding and plant evolutionary ecology

Disaster, infrastructure and participatory knowledge: the Planetary Response Network

There are many challenges involved in online participatory humanitarian response. We evaluate the Planetary Response Network (PRN), a collaboration between researchers, humanitarian organizations, and the online citizen science platform Zooniverse. The PRN uses satellite and aerial image analysis to provide stakeholders with high-level situational awareness during and after humanitarian crises. During past deployments, thousands of online volunteers have compared pre- and post-event satellite images to identify damage to infrastructure and buildings, access blockages, and signs of people in distress. In addition to collectively producing aggregated “heat maps” of features that are shared with responders and decision makers, individual volunteers may also flag novel features directly using integrated community discussion software. The online infrastructure facilitates worldwide participation even for geographically focused disasters; this widespread public participation means that high-value information can be delivered rapidly and uniformly even for large-scale crises. We discuss lessons learned from deployments, place the PRN’s distributed online approach in the context of more localized efforts, and identify future needs for the PRN and similar online crisis-mapping projects. The successes of the PRN demonstrate that effective online crisis mapping is possible on a generalized citizen science platform such as the Zooniverse

Planet Hunters TESS II: findings from the first two years of TESS

Contains fulltext : 230761.pdf (publisher's version ) (Open Access

A transient search using combined human and machine classifications

Large modern surveys require efficient review of data in order to find transient sources such as supernovae, and to distinguish such sources from artefacts and noise. Much effort has been put into the development of automatic algorithms, but surveys still rely on human review of targets. This paper presents an integrated system for the identification of supernovae in data from Pan-STARRS1, combining classifications from volunteers participating in a citizen science project with those from a convolutional neural network. The unique aspect of this work is the deployment, in combination, of both human and machine classifications for near real-time discovery in an astronomical project. We show that the combination of the two methods outperforms either one used individually. This result has important implications for the future development of transient searches, especially in the era of LSST and other large-throughput surveys

Planet Hunters TESS II: Findings from the first two years of TESS

We present the results from the first two years of the Planet Hunters TESS (PHT) citizen science project, which identifies planet candidates in the TESS (Transiting Exoplanet Survey Satellite) data by engaging members of the general public. Over 22 000 citizen scientists from around the world visually inspected the first 26 sectors of TESS data in order to help identify transit-like signals. We use a clustering algorithm to combine these classifications into a ranked list of events for each sector, the top 500 of which are then visually vetted by the science team. We assess the detection efficiency of this methodology by comparing our results to the list of TESS Objects of Interest (TOIs) and show that we recover 85 per cent of the TOIs with radii greater than 4 R⊕ and 51 per cent of those with radii between 3 and 4 R⊕. Additionally, we present our 90 most promising planet candidates that had not previously been identified by other teams, 73 of which exhibit only a single-transit event in the TESS light curve, and outline our efforts to follow these candidates up using ground-based observatories. Finally, we present noteworthy stellar systems that were identified through the Planet Hunters TESS project

Effect of Genetically Modified Poplars on Soil Microbial Communities during the Phytoremediation of Waste Mine Tailings▿†

The application of transgenic plants to clean up environmental pollution caused by the wastes of heavy metal mining is a promising method for removing metal pollutants from soils. However, the effect of using genetically modified organisms for phytoremediation is a poorly researched topic in terms of microbial community structures, despite the important role of microorganisms in the health of soil. In this study, a comparative analysis of the bacterial and archaeal communities found in the rhizosphere of genetically modified (GM) versus wild-type (WT) poplar was conducted on trees at different growth stages (i.e., the rhizospheres of 1.5-, 2.5-, and 3-year-old poplars) that were cultivated on contaminated soils together with nonplanted control soil. Based on the results of DNA pyrosequencing, poplar type and growth stages were associated with directional changes in the structure of the microbial community. The rate of change was faster in GM poplars than in WT poplars, but the microbial communities were identical in the 3-year-old poplars. This phenomenon may arise because of a higher rate and greater extent of metal accumulation in GM poplars than in naturally occurring plants, which resulted in greater changes in soil environments and hence the microbial habitat