Making effective use of existing data for case‐by‐case risk assessments of genetically engineered crops

Many crops in developing countries suffer devastating attacks from insect pests. Expression of insecticidal proteins in genetically engineered (GE) crops is a potentially powerful means of controlling such pests. Potentially harmful effects of these crops on non‐target organisms (NTOs) is of major concern as many of those provide important ecological functions such as pest regulation. Consequently, the likelihood of adverse effects of insect‐resistant GE crops on NTOs is assessed case‐by‐case as part of environmental risk assessments that inform regulatory decision‐making. While risk assessments should be rigorous, it is vital that regulatory barriers do not unnecessarily restrict or prevent the application of genetic engineering to important crops in those countries. Efficient regulatory decision‐making should make effective use of published information on the biology and ecology of the crop in the country where approval is sought, along with regulatory data produced for GE insect‐resistant crops that have received regulatory approvals elsewhere. Just as the risks are assessed for each GE crop individually, the amount of new regulatory data required for a GE crop should vary between crops depending on the amount of existing data and the severity of the perceived risks: new data should be collected only if existing data do not corroborate identified risk hypotheses with sufficient certainty. In this paper, we illustrate how such an approach could work using risks to NTOs from insect‐resistant GE pigeonpea in India as an example.     

Environmental fate and behaviour of antibiotic resistance genes and small interference RNAs released from genetically modified crops

Rising global populations have amplified food scarcity across the world and ushered in the development of genetically modified (GM) crops to overcome these challenges. Cultivation of major crops such as corn and soy has favoured GM crops over conventional varieties to meet crop production and resilience needs. Modern GM crops containing small interference RNA molecules and antibiotic resistance genes have become increasingly common in the United States. However, the use of these crops remains controversial due to the uncertainty regarding the unintended release of its genetic material into the environment and possible downstream effects on human and environmental health. DNA or RNA transgenes may be exuded from crop tissues during cultivation or released during plant decomposition and adsorbed by soil. This can contribute to the persistence and bioavailability in soil or water environment and possible uptake by soil microbial communities and further passing of this information to neighbouring bacteria, disrupting microbial ecosystem services such as nutrient cycling and soil fertility. In this review, transgene mechanisms of action, uses in crops, and knowledge regarding their environmental fate and impact to microbes are evaluated. This aims to encapsulate the current knowledge and promote further research regarding unintended effects transgenes may cause.     

Resources for image-based high-throughput phenotyping in crops and data sharing challenges

High-throughput phenotyping (HTP) platforms are capable of monitoring the phenotypic variation of plants through multiple types of sensors, such as red green and blue (RGB) cameras, hyperspectral sensors, and computed tomography, which can be associated with environmental and genotypic data. Because of the wide range of information provided, HTP datasets represent a valuable asset to characterize crop phenotypes. As HTP becomes widely employed with more tools and data being released, it is important that researchers are aware of these resources and how they can be applied to accelerate crop improvement. Researchers may exploit these datasets either for phenotype comparison or employ them as a benchmark to assess tool performance and to support the development of tools that are better at generalizing between different crops and environments. In this review, we describe the use of image-based HTP for yield prediction, root phenotyping, development of climate-resilient crops, detecting pathogen and pest infestation, and quantitative trait measurement. We emphasize the need for researchers to share phenotypic data, and offer a comprehensive list of available datasets to assist crop breeders and tool developers to leverage these resources in order to accelerate crop breeding.

Various approaches are used to analyze high-throughput phenotyping data and tools can be developed and assessed using available image-based datasets.     

Functional mapping of N deficiency‐induced response in wheat yield‐component traits by implementing high‐throughput phenotyping

As overfertilization leads to environmental concerns and the cost of N fertilizer increases, the issue of how to select crop cultivars that can produce high yields on N‐deficient soils has become crucially important. However, little information is known about the genetic mechanisms by which crops respond to environmental changes induced by N signaling. Here, we dissected the genetic architecture of N‐induced phenotypic plasticity in bread wheat (Triticum aestivum L.) by integrating functional mapping and semiautomatic high‐throughput phenotyping data of yield‐related canopy architecture. We identified a set of quantitative trait loci (QTLs) that determined the pattern and magnitude of how wheat cultivars responded to low N stress from normal N supply throughout the wheat life cycle. This analysis highlighted the phenological landscape of genetic effects exerted by individual QTLs, as well as their interactions with N‐induced signals and with canopy measurement angles. This information may shed light on our mechanistic understanding of plant adaptation and provide valuable information for the breeding of N‐deficiency tolerant wheat varieties.     

Translational research: from pot to plot

Plant molecular biology has been the key driver to elucidate molecular pathways underlying plant growth, development and stress responses during the past decades. Although this has led to a plethora of available data, the translation to crop improvement is lagging behind. Here, we argue that plant scientists should become more involved in converting basic knowledge into applications in crops to sustainably support food security and agriculture. As the translatability from model species to crops is rather poor, this kind of translational research requires diligence and a thorough knowledge of the investigated trait in the crop. In addition, the robustness of a trait depends on the genotype and environmental conditions, demanding a holistic approach, which cannot always be evaluated under growth chamber and greenhouse conditions. To date, the improved resolution of many genome‐wide technologies and the emerging expertise in canopy imaging, plant phenotyping and field monitoring make it very timely to move from the pathway specifics to important agronomical realizations, thus from pot to plot. Despite the availability of scientific know‐how and expertise, the translation of new traits to applications using a transgene approach is in some regions of the world, such as Europe, seriously hampered by heavy and nontranslucent legislation for biotech crops. Nevertheless, progress in crop improvement will remain highly dependent on our ability to evaluate improved varieties in field conditions. Here, we plead for a network of protected sites for field trials across the different European climates to test improved biotech traits directly in crops.     

Environmental change challenges decision-making during post-market environmental monitoring of transgenic crops

The ability to decide what kind of environmental changes observed during post-market environmental monitoring of genetically modified (GM) crops represent environmental harm is an essential part of most legal frameworks regulating the commercial release of GM crops into the environment. Among others, such decisions are necessary to initiate remedial measures or to sustain claims of redress linked to environmental liability. Given that consensus on criteria to evaluate ‘environmental harm’ has not yet been found, there are a number of challenges for risk managers when interpreting GM crop monitoring data for environmental decision-making. In the present paper, we argue that the challenges in decision-making have four main causes. The first three causes relate to scientific data collection and analysis, which have methodological limits. The forth cause concerns scientific data evaluation, which is controversial among the different stakeholders involved in the debate on potential impacts of GM crops on the environment. This results in controversy how the effects of GM crops should be valued and what constitutes environmental harm. This controversy may influence decision-making about triggering corrective actions by regulators. We analyse all four challenges and propose potential strategies for addressing them. We conclude that environmental monitoring has its limits in reducing uncertainties remaining from the environmental risk assessment prior to market approval. We argue that remaining uncertainties related to adverse environmental effects of GM crops would probably be assessed in a more efficient and rigorous way during pre-market risk assessment. Risk managers should acknowledge the limits of environmental monitoring programmes as a tool for decision-making.     

Intercropping drives plant phenotypic plasticity and changes in functional trait space

The relevance of intercropping, where two or more crop species are simultaneously grown on the same land space, is growing due to its potential for improving resource use and maintaining stable yields under variable weather conditions. However, the actual growth of intercropped species may differ resulting from the idiosyncratic effect of crop diversity, and with this, the realized benefits from intercrops are found to depend critically on the cultivar, species, management and environmental conditions. This study aimed to apply a trait-based approach, in which ecological niche spaces are defined through n-dimensional hypervolumes, to identify the contribution of species/cultivar, cultivation design (sole crop or intercrop) and management (low or high fertilization) to the trait diversity of four crop species, pea-barley and faba bean-wheat, when grown as sole crops and intercrops. Four traits were used as trait axes for the trait space analysis: canopy height, shoot biomass, tiller/node number, and grain yield. We found that trait spaces differed with crop species and cultivars, and whether they were grown as intercrops or sole crops. Trait spaces differed between high and low fertilization only for the cereals grown in the more productive site (i.e. Denmark). Species grown as intercrops had larger volumes than when grown as sole crops, as a result of trait plasticity. This response to intercropping was apparent in almost all the species grown in Sweden and Denmark, except for wheat in Denmark. The study demonstrated that individual species responded to intercropping compared to sole cropping through the plasticity of traits, which influenced the shape of the hypervolumes to divide up the trait space between the species. The findings are important in illustrating the plastic responses of arable crops, which are relevant for understanding the productivity of species grown in intercrops as compared to sole crops.     

Adaptation of crops to environment

Adaptability is defined as the ability of a crop (or variety) to respond positively to changes in agricultural conditions. The trait is genetically controlled and provides an ability to exploit environmental attributes, both natural and agronomic. Values of relative adaptability can be determined by the regression of the yield of the tested crop over the average yield of compared crops from several environments. We evaluated relative adaptability of 12 staple crops in 12 European countries and compared the yield data over a 43-year period from 1961 to 2003. An additional set of average yield data was also available for the 15 European Union (EU15) member countries. A wider range of 26 crop species was investigated that allowed comparisons between Europe and the USA between 1961 and 2003. Adaptability was closely related to the annual yield increases of the crops studied (r ²=0.999 both in the EU15 and the USA). However, the adaptability of certain crops differed between the two regions. Pulse, maize, millet, wheat and sorghum showed the highest adaptability in the EU15 region, whereas strawberry, pear, tomato, walnut and maize were highest in the USA. The lowest adaptability was found for walnut, pear, apple, cauliflower and hop in the EU15 and for mustard, hop, sugar beet, millet and oat in the USA. In European countries, crops with similar biology, environment and agronomical practices (like the amount of fertilizers and pesticides applied) tended to have similar adaptability values. The data indicate that high adaptability is an important prerequisite for continued yield gains in the best environments.     

Contributions of domesticated plant studies to our understanding of plant evolution

BACKGROUND: Plant evolutionary theory has been greatly enriched by studies on crop species. Over the last century, important information has been generated on many aspects of population biology, speciation and polyploid genetics. SCOPE: Searches for quantitative trait loci (QTL) in crop species have uncovered numerous blocks of genes that have dramatic effects on adaptation, particularly during the domestication process. Many of these QTL have epistatic and pleiotropic effects making rapid evolutionary change possible. Most of the pioneering work on the molecular basis of self-incompatibility has been conducted on crop species, along with the sequencing of the phytopathogenic resistance genes (R genes) responsible for the 'gene-to-gene' relations of coevolution observed in host-pathogen relationships. Some of the better examples of co-adaptation and early acting inbreeding depression have also been elucidated in crops. Crop-wild progenitor interactions have provided rich opportunities to study the evolution of novel adaptations subsequent to hybridization. Most crop/wild F1 hybrids have reduced fitness, but in some instances the crop relatives have acquired genes that make them more efficient weeds through crop mimicry. Studies on autopolyploid alfalfa and potato have uncovered the means by which polyploid gametes are formed and have led to hypotheses about how multiallelic interactions are associated with fitness and self-fertility. Research on the cole crops and wheat has discovered that newly formed polyploids can undergo dramatic genome rearrangements that could lead to rapid evolutionary change. CONCLUSIONS: Many more important evolutionary discoveries are on the horizon, now that the whole genome sequence is available of the two major subspecies of rice Oryza sativa ssp. japonica and O. sativa ssp. indica. The rice sequence data can be used to study the origin of genes and gene families, track rates of sequence divergence over time, and provide hints about how genes evolve and generate products with novel biological properties. The rice sequence data has already been mined to show that transposable elements often carry fragments of cellular genes. This type of genome shuffling could play a role in creating novel, reorganized genes with new adaptive properties.     

Restructuring plant types for developing tailor-made crops

Plants have adapted to different environmental niches by fine-tuning the developmental factors working together to regulate traits. Variations in the developmental factors result in a wide range of quantitative variations in these traits that helped plants survive better. The major developmental pathways affecting plant architecture are also under the control of such pathways. Most notable are the CLAVATA-WUSCHEL pathway regulating shoot apical meristem fate, GID1-DELLA module influencing plant height and tillering, LAZY1-TAC1 module controlling branch/tiller angle and the TFL1-FT determining the floral fate in plants. Allelic variants of these key regulators selected during domestication shaped the crops the way we know them today. There is immense yield potential in the ‘ideal plant architecture’ of a crop. With the available genome-editing techniques, possibilities are not restricted to naturally occurring variations. Using a transient reprogramming system, one can screen the effect of several developmental gene expressions in novel ecosystems to identify the best targets. We can use the plant's fine-tuning mechanism for customizing crops to specific environments. The process of crop domestication can be accelerated with a proper understanding of these developmental pathways. It is time to step forward towards the next-generation molecular breeding for restructuring plant types in crops ensuring yield stability.     

Expression of Arabidopsis Bax Inhibitor‐1 in transgenic sugarcane confers drought tolerance

The sustainability of global crop production is critically dependent on improving tolerance of crop plants to various types of environmental stress. Thus, identification of genes that confer stress tolerance in crops has become a top priority especially in view of expected changes in global climatic patterns. Drought stress is one of the abiotic stresses that can result in dramatic loss of crop productivity. In this work, we show that transgenic expression of a highly conserved cell death suppressor, Bax Inhibitor‐1 from Arabidopsis thaliana (AtBI‐1), can confer increased tolerance of sugarcane plants to long‐term (>20 days) water stress conditions. This robust trait is correlated with an increased tolerance of the transgenic sugarcane plants, especially in the roots, to induction of endoplasmic reticulum (ER) stress by the protein glycosylation inhibitor tunicamycin. Our findings suggest that suppression of ER stress in C₄ grasses, which include important crops such as sorghum and maize, can be an effective means of conferring improved tolerance to long‐term water deficit. This result could potentially lead to improved resilience and yield of major crops in the world.     

REVIEW ARTICLE: Transgenic plants and the environment

With a continued increase in the range of transgenes, and plantspecies for which genetic modification is possible, this reviewattempts to bring together some of the factors that will influencethe eventual fate of transgenes in the environment, and theeffects that such a dispersal may have. The review is developedfrom papers presented at the SEB Swansea meeting (April, 1994). Using experiments with GM (genetically modified) plants, andmarkers in non-GM plants, as well as observations on naturaland crop populations, it is possible to predict isolation distancesrequired for limiting the unintentional release from GM crops,and the probable fate of both GM pollen and seed if it is releasedbeyond the GM plot. Knowledge of wild relatives of crop plants,and ecological mechanisms can also give insights into the possibleeffects of different transgenes on native plants, and otheragricultural crops. A large number of limited scale releasesof GM plants have now taken place from which we can gain informationon the performance of GM crops in an agricultural environment,and the stability of the GM phenotype. All this information,can help to form a sound basis for regulations on the releaseof GM plants, an assessment of the need for, and scope of monitoring,and the best way in which to use GM crops. Key words: Transgenic releases, genetically-modified plants, molecular ecology, transgene stability     

Probability functions to build composite indicators: A methodology to measure environmental impacts of genetically modified crops

There is an on-going debate on the environmental effects of genetically modified crops to which this paper aims to contribute. First, data on environmental impacts of genetically modified (GM) and conventional crops are collected from peer-reviewed journals, and secondly an analysis is conducted in order to examine which crop type is less harmful for the environment. Published data on environmental impacts are measured using an array of indicators, and their analysis requires their normalisation and aggregation. Taking advantage of composite indicators literature, this paper builds composite indicators to measure the impact of GM and conventional crops in three dimensions: (1) non-target key species richness, (2) pesticide use, and (3) aggregated environmental impact. The comparison between the three composite indicators for both crop types allows us to establish not only a ranking to elucidate which crop is more convenient for the environment but the probability that one crop type outperforms the other from an environmental perspective. Results show that GM crops tend to cause lower environmental impacts than conventional crops for the analysed indicators.     

Advancing environmental risk assessment for transgenic biofeedstock crops

Transgenic modification of plants is a key enabling technology for developing sustainable biofeedstocks for biofuels production. Regulatory decisions and the wider acceptance and development of transgenic biofeedstock crops are considered from the context of science-based risk assessment. The risk assessment paradigm for transgenic biofeedstock crops is fundamentally no different from that of current generation transgenic crops, except that the focus of the assessment must consider the unique attributes of a given biofeedstock crop and its environmental release. For currently envisioned biofeedstock crops, particular emphasis in risk assessment will be given to characterization of altered metabolic profiles and their implications relative to non-target environmental effects and food safety; weediness and invasiveness when plants are modified for abiotic stress tolerance or are domesticated; and aggregate risk when plants are platforms for multi-product production. Robust risk assessments for transgenic biofeedstock crops are case-specific, initiated through problem formulation, and use tiered approaches for risk characterization.     

Assessing the application of a geographic presence-only model for land suitability mapping

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1300 sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the MaxEnt model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results.     

Assessment of risk of insect-resistant transgenic crops to nontarget arthropods

An international initiative is developing a scientifically rigorous approach to evaluate the potential risks to nontarget arthropods (NTAs) posed by insect-resistant, genetically modified (IRGM) crops. It adapts the tiered approach to risk assessment that is used internationally within regulatory toxicology and environmental sciences. The approach focuses on the formulation and testing of clearly stated risk hypotheses, making maximum use of available data and using formal decision guidelines to progress between testing stages (or tiers). It is intended to provide guidance to regulatory agencies that are currently developing their own NTA risk assessment guidelines for IRGM crops and to help harmonize regulatory requirements between different countries and different regions of the world.     

Development of a construct-based risk assessment framework for genetic engineered crops

Experience gained in the risk assessment (RA) of genetically engineered (GE) crops since their first experimental introductions in the early nineties, has increased the level of familiarity with these breeding methodologies and has motivated several agencies and expert groups worldwide to revisit the scientific criteria underlying the RA process. Along these lines, the need to engage in a scientific discussion for the case of GE crops transformed with similar constructs was recently identified in Argentina. In response to this need, the Argentine branch of the International Life Sciences Institute (ILSI Argentina) convened a tripartite working group to discuss a science-based evaluation approach for transformation events developed with genetic constructs which are identical or similar to those used in previously evaluated or approved GE crops. This discussion considered new transformation events within the same or different species and covered both environmental and food safety aspects. A construct similarity concept was defined, considering the biological function of the introduced genes. Factors like environmental and dietary exposure, familiarity with both the crop and the trait as well as the crop biology, were identified as key to inform a construct-based RA process.     

Limitations of trait‐based approaches for stressor assessment: The case of freshwater invertebrates and climate drivers

The appeal of trait‐based approaches for assessing environmental vulnerabilities arises from the potential insight they provide into the mechanisms underlying the changes in populations and community structure. Traits can provide ecologically based explanations for observed responses to environmental changes, along with predictive power gained by developing relationships between traits and environmental variables. Despite these potential benefits, questions remain regarding the utility and limitations of these approaches, which we explore focusing on the following questions: (a) How reliable are predictions of biotic responses to changing conditions based on single trait–environment relationships? (b) What factors constrain detection of single trait–environment relationships, and how can they be addressed? (c) Can we use information on meta‐community processes to reveal conditions when assumptions underlying trait‐based studies are not met? We address these questions by reviewing published literature on aquatic invertebrate communities from stream ecosystems. Our findings help to define factors that influence the successful application of trait‐based approaches in addressing the complex, multifaceted effects of changing climate conditions on hydrologic and thermal regimes in stream ecosystems. Key conclusions are that observed relationships between traits and environmental stressors are often inconsistent with predefined hypotheses derived from current trait‐based thinking, particularly related to single trait–environment relationships. Factors that can influence findings of trait‐based assessments include intercorrelations of among traits and among environmental variables, spatial scale, strength of biotic interactions, intensity of habitat disturbance, degree of abiotic stress, and methods of trait characterization. Several recommendations are made for practice and further study to address these concerns, including using phylogenetic relatedness to address intercorrelation. With proper consideration of these issues, trait‐based assessment of organismal vulnerability to environmental changes can become a useful tool to conserve threatened populations into the future.     

转基因作物与其野生亲缘种间的基因流

随着基因工程技术的突飞猛进,许多主要的农作物经过遗传修饰获得了优良的性状,并被批准进入市场。在美国,到１９９６年５月为止,经政府批准商业化的转基因作物已有７种;而在欧共体,仅在１９９１～１９９４年被释放作大田试验的转基因植物就达２９１个［１］。对于转...