Phenotypic characterization of drought responses in red clover (Trifolium pratense L.)

Introduction

Red clover (Trifolium pratense) is a protein-rich, short-lived perennial forage crop that can achieve high yields, but suffers increasingly from drought in different cultivation areas. Breeding for increased adaptation to drought is becoming essential, but at this stage it is unclear which traits breeders should target to phenotype responses to drought that allow them to identify the most promising red clover genotypes. In this study, we assessed how prolonged periods of drought affected plant growth in field conditions, and which traits could be used to distinguish better adapted plant material.

Methods

A diverse panel of 395 red clover accessions was evaluated during two growing seasons. We simulated 6-to-8-week drought periods during two consecutive summers, using mobile rain-out shelters, while an irrigated control field was established in an adjacent parcel. Plant growth was monitored throughout both growing seasons using multiple flights with a drone equipped with RGB and thermal sensors. At various observation moments throughout both growing seasons, we measured canopy cover (CC) and canopy height (CH). The crop water stress index (CWSI) was determined at two moments, during or shortly after the drought event.

Results

Manual and UAV-derived measurements for CH were well correlated, indicating that UAV-derived measurements can be reliably used in red clover. In both years, CC, CH and CWSI were affected by drought, with measurable growth reductions by the end of the drought periods, and during the recovery phase. We found that the end of the drought treatment and the recovery phase of approximately 20 days after drought were suitable periods to phenotype drought responses and to distinguish among genotypes.

Discussion

Multifactorial analysis of accession responses revealed interactions of the maturity type with drought responses, which suggests the presence of two independent strategies in red clover: 'drought tolerance' and 'drought recovery'. We further found that a large proportion of the accessions able to perform well under well-watered conditions were also the ones that were less affected by drought. The results of this investigation are interpreted in view of the development of breeding for adaptation to drought in red clover.

Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression

In the plant sciences, results of laboratory studies often do not translate well to the field. To help close this lab-field gap, we developed a strategy for studying the wiring of plant traits directly in the field, based on molecular profiling and phenotyping of individual plants. Here, we use this single-plant omics strategy on winter-type Brassica napus (rapeseed). We investigate to what extent early and late phenotypes of field-grown rapeseed plants can be predicted from their autumnal leaf gene expression, and find that autumnal leaf gene expression not only has substantial predictive power for autumnal leaf phenotypes but also for final yield phenotypes in spring. Many of the top predictor genes are linked to developmental processes known to occur in autumn in winter-type B. napus accessions, such as the juvenile-to-adult and vegetative-to-reproductive phase transitions, indicating that the yield potential of winter-type B. napus is influenced by autumnal development. Our results show that single-plant omics can be used to identify genes and processes influencing crop yield in the field.

Variation in potential feeding value of triticale forage among plant fraction, maturity stage, growing season and genotype

Cereal forages, such as triticale forage, progressively gain interest as alternative crop for maize. The main study objective was to investigate the variation in potential feeding value of triticale forage among maturity stage, growing season and genotype, using total plant and stem fractions. Therefore, near infrared spectroscopy (NIRS) was evaluated as fast screening tool. The prediction ability was good (ratio of prediction to deviation, RPD ≥3.0) for total plant residual moisture, starch, sugars and for stem crude ash (CAsh) and neutral detergent fibre (aNDFom); suitable for screening (2.0 ≤ RPD <3.0) for total plant CAsh, acid detergent fibre (ADFom), in vitro digestibility of organic matter (IVOMD), in vitro digestibility of neutral detergent fibre (IVNDFD) and for stem total lignin (TL) and IVNDFD; poor (1.5 ≤ RPD <2.0) for total plant crude protein, crude fat, aNDFom, lignin (sa) and for stem Klason lignin (KL); unreliable (RPD <1.5) for stem residual moisture and acid soluble lignin (ASL). The evolution in potential feeding value of 36 genotypes harvested at the medium and late milk to the early, soft and hard dough stage was followed. The most important changes occurred between the late milk and early dough stage, with little variation in quality after the soft dough stage. During 2 growing seasons, variation in feeding value of 120 genotypes harvested at the soft dough stage was demonstrated. Interestingly, variation in stem IVNDFD is almost twice as high as for the total plant (CV 12.4% versus 6.6%). Furthermore, Spearman correlations show no link between dry matter yield and digestibility of genotypes harvested at the soft dough stage. Based on linear regression models ADFom appears as main predictor of both plant IVOMD and plant IVNDFD. Stem IVNDFD is particularly determined by KL.

Genetic control of tolerance to drought stress in soybean

BACKGROUND

Drought stress limits the production of soybean [Glycine max (L.) Merr.], which is the most grown high-value legume crop worldwide. Breeding for drought tolerance is a difficult endeavor and understanding the genetic basis of drought tolerance in soybean is therefore crucial for harnessing the genomic regions involved in the tolerance mechanisms. A genome-wide association study (GWAS) analysis was applied in a soybean germplasm collection (the EUCLEG collection) of 359 accessions relevant for breeding in Europe, to identify genomic regions and candidate genes involved in the response to short duration and long duration drought stress (SDS and LDS respectively) in soybean.

RESULTS

The phenotypic response to drought was stronger in the long duration drought (LDS) than in the short duration drought (SDS) experiment. Over the four traits considered (canopy wilting, leaf senescence, maximum absolute growth rate and maximum plant height) the variation was in the range of 8.4-25.2% in the SDS, and 14.7-29.7% in the LDS experiments. The GWAS analysis identified a total of 17 and 22 significant marker-trait associations for four traits in the SDS and LDS experiments, respectively. In the genomic regions delimited by these markers we identified a total of 12 and 16 genes with putative functions that are of particular relevance for drought stress responses including stomatal movement, root formation, photosynthesis, ABA signaling, cellular protection and cellular repair mechanisms. Some of these genomic regions co-localized with previously known QTLs for drought tolerance traits including water use efficiency, chlorophyll content and photosynthesis.

CONCLUSION

Our results indicate that the mechanism of slow wilting in the SDS might be associated with the characteristics of the root system, whereas in the LDS, slow wilting could be due to low stomatal conductance and transpiration rates enabling a high WUE. Drought-induced leaf senescence was found to be associated to ABA and ROS responses. The QTLs related to WUE contributed to growth rate and canopy height maintenance under drought stress. Co-localization of several previously known QTLs for multiple agronomic traits with the SNPs identified in this study, highlights the importance of the identified genomic regions for the improvement of agronomic performance in addition to drought tolerance in the EUCLEG collection.

Phenotypic variation and quantitative trait loci for resistance to southern anthracnose and clover rot in red clover

High variability for and candidate loci associated with resistance to southern anthracnose and clover rot in a worldwide collection of red clover provide a first basis for genomics-assisted breeding. Red clover (Trifolium pratense L.) is an important forage legume of temperate regions, particularly valued for its high yield potential and its high forage quality. Despite substantial breeding progress during the last decades, continuous improvement of cultivars is crucial to ensure yield stability in view of newly emerging diseases or changing climatic conditions. The high amount of genetic diversity present in red clover ecotypes, landraces, and cultivars provides an invaluable, but often unexploited resource for the improvement of key traits such as yield, quality, and resistance to biotic and abiotic stresses. A collection of 397 red clover accessions was genotyped using a pooled genotyping-by-sequencing approach with 200 plants per accession. Resistance to the two most pertinent diseases in red clover production, southern anthracnose caused by Colletotrichum trifolii, and clover rot caused by Sclerotinia trifoliorum, was assessed using spray inoculation. The mean survival rate for southern anthracnose was 22.9% and the mean resistance index for clover rot was 34.0%. Genome-wide association analysis revealed several loci significantly associated with resistance to southern anthracnose and clover rot. Most of these loci are in coding regions. One quantitative trait locus (QTL) on chromosome 1 explained 16.8% of the variation in resistance to southern anthracnose. For clover rot resistance we found eight QTL, explaining together 80.2% of the total phenotypic variation. The SNPs associated with these QTL provide a promising resource for marker-assisted selection in existing breeding programs, facilitating the development of novel cultivars with increased resistance against two devastating fungal diseases of red clover.

Genetic composition and diversity of Arabica coffee in the crop's center of origin and its impact on four major fungal diseases

Conventional wisdom states that genetic variation reduces disease levels in plant populations. Nevertheless, crop species have been subject to a gradual loss of genetic variation through selection for specific traits during breeding, thereby increasing their vulnerability to biotic stresses such as pathogens. We explored how genetic variation in Arabica coffee sites in southwestern Ethiopia was related to the incidence of four major fungal diseases. Sixty sites were selected along a gradient of management intensity, ranging from nearly wild to intensively managed coffee stands. We used genotyping-by-sequencing of pooled leaf samples (pool-GBS) derived from 16 individual coffee shrubs in each of the sixty sites to assess the variation in genetic composition (multivariate: reference allele frequency) and genetic diversity (univariate: mean expected heterozygosity) between sites. We found that genetic composition had a clear spatial pattern and that genetic diversity was higher in less managed sites. The incidence of the four fungal diseases was related to the genetic composition of the coffee stands, but in a specific way for each disease. In contrast, genetic diversity was only related to the within-site variation of coffee berry disease, but not to the mean incidence of any of the four diseases across sites. Given that fungal diseases are major challenges of Arabica coffee in its native range, our findings that genetic composition of coffee sites impacted the major fungal diseases may serve as baseline information to study the molecular basis of disease resistance in coffee. Overall, our study illustrates the need to consider both host genetic composition and genetic diversity when investigating the genetic basis for variation in disease levels.

Response of a Diverse European Soybean Collection to "Short Duration" and "Long Duration" Drought Stress

Drought causes significant damage to a high value crop of soybean. Europe has an increasing demand for soybean and its own production is insufficient. Selection and breeding of cultivars adapted to European growth conditions is therefore urgently needed. These new cultivars must have a shorter growing cycle (specifically for adaptation to North-West Europe), high yield potential under European growing conditions, and sufficient drought resistance. We have evaluated the performance of a diverse collection of 359 soybean accessions under drought stress using rain-out shelters for 2 years. The contrasting weather conditions between years and correspondingly the varying plant responses demonstrated that the consequences of drought for an individual accession can vary strongly depending on the characteristics (e.g., duration and intensity) of the drought period. Short duration drought stress, for a period of four to 7 weeks, caused an average reduction of 11% in maximum canopy height (CH), a reduction of 17% in seed number per plant (SN) and a reduction of 16% in seed weight per plant (SW). Long duration drought stress caused an average reduction of 29% in CH, a reduction of 38% in SN and a reduction of 43% in SW. Drought accelerated plant development and caused an earlier cessation of flowering and pod formation. This seemed to help some accessions to better protect the seed yield, under short duration drought stress. Drought resistance for yield-related traits was associated with the maintenance of growth under long duration drought stress. The collection displayed a broad range of variation for canopy wilting and leaf senescence but a very narrow range of variation for crop water stress index (CWSI; derived from canopy temperature data). To the best of our knowledge this is the first study reporting a detailed investigation of the response to drought within a diverse soybean collection relevant for breeding in Europe.

Seasonal Differences in Structural and Genetic Control of Digestibility in Perennial Ryegrass

Perennial ryegrass is an important forage crop in dairy farming, either for grazing or haying purposes. To further optimise the forage use, this study focused on understanding forage digestibility in the two most important cuts of perennial ryegrass, the spring cut at heading and the autumn cut. In a highly diverse collection of 592 Lolium perenne genotypes, the organic matter digestibility (OMD) and underlying traits such as cell wall digestibility (NDFD) and cell wall components (cellulose, hemicellulose, and lignin) were investigated for 2 years. A high genotype × season interaction was found for OMD and NDFD, indicating differences in genetic control of these forage quality traits in spring versus autumn. OMD could be explained by both the quantity of cell wall content (NDF) and the quality of the cell wall content (NDFD). The variability in NDFD in spring was mainly explained by differences in hemicellulose. A 1% increase of the hemicellulose content in the cell wall (HC.NDF) resulted in an increase of 0.81% of NDFD. In autumn, it was mainly explained by the lignin content in the cell wall (ADL.NDF). A 0.1% decrease of ADL.NDF resulted in an increase of 0.41% of NDFD. The seasonal traits were highly heritable and showed a higher variation in autumn versus spring, indicating the potential to select for forage quality in the autumn cut. In a candidate gene association mapping approach, in which 503 genes involved in cell wall biogenesis, plant architecture, and phytohormone biosynthesis and signalling, identified significant quantitative trait loci (QTLs) which could explain from 29 to 52% of the phenotypic variance in the forage quality traits OMD and NDFD, with small effects of each marker taken individually (ranging from 1 to 7%). No identical QTLs were identified between seasons, but within a season, some QTLs were in common between digestibility traits and cell wall composition traits confirming the importance of hemicellulose concentration for spring digestibility and lignin concentration in NDF for autumn digestibility.

Inter-annual and spatial climatic variability have led to a balance between local fluctuating selection and wide-range directional selection in a perennial grass species

BACKGROUND AND AIMS

The persistence of a plant population under a specific local climatic regime requires phenotypic adaptation with underlying particular combinations of alleles at adaptive loci. The level of allele diversity at adaptive loci within a natural plant population conditions its potential to evolve, notably towards adaptation to a change in climate. Investigating the environmental factors that contribute to the maintenance of adaptive diversity in populations is thus worthwhile. Within-population allele diversity at adaptive loci can be partly driven by the mean climate at the population site but also by its temporal variability.

METHODS

The effects of climate temporal mean and variability on within-population allele diversity at putatively adaptive quantitative trait loci (QTLs) were evaluated using 385 natural populations of Lolium perenne (perennial ryegrass) collected right across Europe. For seven adaptive traits related to reproductive phenology and vegetative potential growth seasonality, the average within-population allele diversity at major QTLs (HeA) was computed.

KEY RESULTS

Significant relationships were found between HeA of these traits and the temporal mean and variability of the local climate. These relationships were consistent with functional ecology theory.

CONCLUSIONS

Results indicated that temporal variability of local climate has likely led to fluctuating directional selection, which has contributed to the maintenance of allele diversity at adaptive loci and thus potential for further adaptation.

A Genome-Wide Genetic Diversity Scan Reveals Multiple Signatures of Selection in a European Soybean Collection Compared to Chinese Collections of Wild and Cultivated Soybean Accessions

Targeted and untargeted selections including domestication and breeding efforts can reduce genetic diversity in breeding germplasm and create selective sweeps in crop genomes. The genomic regions at which selective sweeps are detected can reveal important information about signatures of selection. We have analyzed the genetic diversity within a soybean germplasm collection relevant for breeding in Europe (the EUCLEG collection), and have identified selective sweeps through a genome-wide scan comparing that collection to Chinese soybean collections. This work involved genotyping of 480 EUCLEG soybean accessions, including 210 improved varieties, 216 breeding lines and 54 landraces using the 355K SoySNP microarray. SNP calling of 477 EUCLEG accessions together with 328 Chinese soybean accessions identified 224,993 high-quality SNP markers. Population structure analysis revealed a clear differentiation between the EUCLEG collection and the Chinese materials. Further, the EUCLEG collection was sub-structured into five subgroups that were differentiated by geographical origin. No clear association between subgroups and maturity group was detected. The genetic diversity was lower in the EUCLEG collection compared to the Chinese collections. Selective sweep analysis revealed 23 selective sweep regions distributed over 12 chromosomes. Co-localization of these selective sweep regions with previously reported QTLs and genes revealed that various signatures of selection in the EUCLEG collection may be related to domestication and improvement traits including seed protein and oil content, phenology, nitrogen fixation, yield components, diseases resistance and quality. No signatures of selection related to stem determinacy were detected. In addition, absence of signatures of selection for a substantial number of QTLs related to yield, protein content, oil content and phenological traits suggests the presence of substantial genetic diversity in the EUCLEG collection. Taken together, the results obtained demonstrate that the available genetic diversity in the EUCLEG collection can be further exploited for research and breeding purposes. However, incorporation of exotic material can be considered to broaden its genetic base.

Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass

Germplasm from perennial ryegrass (Lolium perenne L.) natural populations is useful for breeding because of its adaptation to a wide range of climates. Climate-adaptive genes can be detected from associations between genotype, phenotype and climate but an integrated framework for the analysis of these three sources of information is lacking. We used two approaches to identify adaptive loci in perennial ryegrass and their effect on phenotypic traits. First, we combined Genome-Environment Association (GEA) and GWAS analyses. Then, we implemented a new test based on a Canonical Correlation Analysis (CANCOR) to detect adaptive loci. Furthermore, we improved the previous perennial ryegrass gene set by de novo gene prediction and functional annotation of 39,967 genes. GEA-GWAS revealed eight outlier loci associated with both environmental variables and phenotypic traits. CANCOR retrieved 633 outlier loci associated with two climatic gradients, characterized by cold-dry winter versus mild-wet winter and long rainy season versus long summer, and pointed out traits putatively conferring adaptation at the extremes of these gradients. Our CANCOR test also revealed the presence of both polygenic and oligogenic climatic adaptations. Our gene annotation revealed that 374 of the CANCOR outlier loci were positioned within or close to a gene. Co-association networks of outlier loci revealed a potential utility of CANCOR for investigating the interaction of genes involved in polygenic adaptations. The CANCOR test provides an integrated framework to analyse adaptive genomic diversity and phenotypic responses to environmental selection pressures that could be used to facilitate the adaptation of plant species to climate change.

Automatic wheat ear counting using machine learning based on RGB UAV imagery

In wheat (Triticum aestivum L) and other cereals, the number of ears per unit area is one of the main yield-determining components. An automatic evaluation of this parameter may contribute to the advance of wheat phenotyping and monitoring. There is no standard protocol for wheat ear counting in the field, and moreover it is time consuming. An automatic ear-counting system is proposed using machine learning techniques based on RGB (red, green, blue) images acquired from an unmanned aerial vehicle (UAV). Evaluation was performed on a set of 12 winter wheat cultivars with three nitrogen treatments during the 2017-2018 crop season. The automatic system uses a frequency filter, segmentation and feature extraction, with different classification techniques, to discriminate wheat ears in micro-plot images. The relationship between the image-based manual counting and the algorithm counting exhibited high levels of accuracy and efficiency. In addition, manual ear counting was conducted in the field for secondary validation. The correlations between the automatic and the manual in-situ ear counting with grain yield were also compared. Correlations between the automatic ear counting and grain yield were stronger than those between manual in-situ counting and GY, particularly for the lower nitrogen treatment. Methodological requirements and limitations are discussed.

Gloxinia-An Open-Source Sensing Platform to Monitor the Dynamic Responses of Plants

The study of the dynamic responses of plants to short-term environmental changes is becoming increasingly important in basic plant science, phenotyping, breeding, crop management, and modelling. These short-term variations are crucial in plant adaptation to new environments and, consequently, in plant fitness and productivity. Scalable, versatile, accurate, and low-cost data-logging solutions are necessary to advance these fields and complement existing sensing platforms such as high-throughput phenotyping. However, current data logging and sensing platforms do not meet the requirements to monitor these responses. Therefore, a new modular data logging platform was designed, named Gloxinia. Different sensor boards are interconnected depending upon the needs, with the potential to scale to hundreds of sensors in a distributed sensor system. To demonstrate the architecture, two sensor boards were designed—one for single-ended measurements and one for lock-in amplifier based measurements, named Sylvatica and Planalta, respectively. To evaluate the performance of the system in small setups, a small-scale trial was conducted in a growth chamber. Expected plant dynamics were successfully captured, indicating proper operation of the system. Though a large scale trial was not performed, we expect the system to scale very well to larger setups. Additionally, the platform is open-source, enabling other users to easily build upon our work and perform application-specific optimisations.

Environmental sustainability of conventional and organic farming: Accounting for ecosystem services in life cycle assessment

Today, there is an ongoing debate about the environmental sustainability of the products of organic farming. To compare the performance of conventional and organic farming systems regarding environmental impact and productivity, the comprehensive environmental assessment tool 'life cycle assessment' can be used. The lower crop yields attained by organic systems compared to conventional farming systems might, however, outweigh the benefits of the use of more environmental-friendly practices when evaluating the environmental impact per product unit. Although these practices are beneficial for the environment, which is reflected in the delivery of a range of ecosystem services (ES), the focus is traditionally put only on the (harvested) product. Because the agricultural product involves actually a bundle of ES, the impact should be allocated among the whole output of an agricultural system. In this study, we propose an allocation procedure based on the capacity of agricultural systems to deliver ES to divide the environmental impact over all agricultural outputs (i.e. provisioning and other ES). Allocation factors are developed for conventional and organic arable farming systems. Applying these allocation factors, we demonstrate that for about half of the studied food products (including maize, potato), organic farming has clear environmental benefits in terms of resource consumption in comparison to conventional cultivation methods. This allocation approach allows a more complete comparison of the environmental sustainability of organically and conventionally produced food.

A Multifaceted Overview of Apple Tree Domestication

The apple is an iconic tree and a major fruit crop worldwide. It is also a model species for the study of the evolutionary processes and genomic basis underlying the domestication of clonally propagated perennial crops. Multidisciplinary approaches from across Eurasia have documented the pace and process of cultivation of this remarkable crop. While population genetics and genomics have revealed the overall domestication history of apple across Eurasia, untangling the evolutionary processes involved, archeobotany has helped to document the transition from gathering and using apples to the practice of cultivation. Further studies integrating archeogenetic and archeogenomic approaches will bring new insights about key traits involved in apple domestication. Such knowledge has potential to boost innovation in present-day apple breeding.

Use of identifiability analysis in designing phenotyping experiments for modelling forage production and quality

Agricultural systems models are complex and tend to be over-parameterized with respect to observational datasets. Practical identifiability analysis based on local sensitivity analysis has proved effective in investigating identifiable parameter sets in environmental models, but has not been applied to agricultural systems models. Here, we demonstrate that identifiability analysis improves experimental design to ensure independent parameter estimation for yield and quality outputs of a complex grassland model. The Pasture Simulation model (PaSim) was used to demonstrate the effectiveness of practical identifiability analysis in designing experiments and measurement protocols within phenotyping experiments with perennial ryegrass. Virtual experiments were designed combining three factors: frequency of measurements, duration of the experiment. and location of trials. Our results demonstrate that (i) PaSim provides sufficient detail in terms of simulating biomass yield and quality of perennial ryegrass for use in breeding, (ii) typical breeding trials are insufficient to parameterize all influential parameters, (iii) the frequency of measurements is more important than the number of growing seasons to improve the identifiability of PaSim parameters, and (iv) identifiability analysis provides a sound approach for optimizing the design of multi-location trials. Practical identifiability analysis can play an important role in ensuring proper exploitation of phenotypic data and cost-effective multi-location experimental designs. Considering the growing importance of simulation models, this study supports the design of experiments and measurement protocols in the phenotyping networks that have recently been organized.

Single Nucleotide Polymorphisms and Biochemical Markers As Complementary Tools To Characterize Hops ( Humulus lupulus L.) in Brewing Practice

In brewing practice, the use of the appropriate hop variety is essential to produce consistent and high-quality beers. Yet, hop batches of the same variety cultivated in different geographical regions can display significant biochemical differences, resulting in specific taste- and aroma-related characteristics in beer. In this study, we illustrate the complementarity of genetic and biochemical fingerprinting methods to fully characterize hop batches. Using genotyping-by-sequencing (GBS), a set of 1 830 polymorphic single nucleotide polymorphism (SNP) markers generated 48 unique genetic fingerprints for a collection of 56 commercial hop varieties. Three groups of varieties, consisting of somaclonal variants, could not be further differentiated using this set of markers. Biochemical marker information offered added value to characterize hop samples from a given variety grown at different geographical locations. We demonstrate the power of combining genetic and biochemical fingerprints for quality control of hop batches in the brewing industry.

Overcoming challenges in variant calling: exploring sequence diversity in candidate genes for plant development in perennial ryegrass (Lolium perenne)

Revealing DNA sequence variation within the Lolium perenne genepool is important for genetic analysis and development of breeding applications. We reviewed current literature on plant development to select candidate genes in pathways that control agronomic traits, and identified 503 orthologues in L. perenne. Using targeted resequencing, we constructed a comprehensive catalogue of genomic variation for a L. perenne germplasm collection of 736 genotypes derived from current cultivars, breeding material and wild accessions. To overcome challenges of variant calling in heterogeneous outbreeding species, we used two complementary strategies to explore sequence diversity. First, four variant calling pipelines were integrated with the VariantMetaCaller to reach maximal sensitivity. Additional multiplex amplicon sequencing was used to empirically estimate an appropriate precision threshold. Second, a de novo assembly strategy was used to reconstruct divergent alleles for each gene. The advantage of this approach was illustrated by discovery of 28 novel alleles of LpSDUF247, a polymorphic gene co-segregating with the S-locus of the grass self-incompatibility system. Our approach is applicable to other genetically diverse outbreeding species. The resulting collection of functionally annotated variants can be mined for variants causing phenotypic variation, either through genetic association studies, or by selecting carriers of rare defective alleles for physiological analyses.

Temporal changes in genetic diversity and forage yield of perennial ryegrass in monoculture and in combination with red clover in swards

Agricultural grasslands are often cultivated as mixtures of grasses and legumes, and an extensive body of literature is available regarding interspecific interactions, and how these relate to yield and agronomic performance. However, knowledge of the impact of intraspecific diversity on grassland functioning is scarce. We investigated these effects during a 4-year field trial established with perennial ryegrass (Lolium perenne) and red clover (Trifolium pratense). We simulated different levels of intraspecific functional diversity by sowing single cultivars or by combining cultivars with contrasting growth habits, in monospecific or bispecific settings (i.e. perennial ryegrass whether or not in combination with red clover). Replicate field plots were established for seven seed compositions. We determined yield parameters and monitored differences in genetic diversity in the ryegrass component among seed compositions, and temporal changes in the genetic composition and genetic diversity at the within plot level. The composition of cultivars of both species affected the yield and species abundance. In general, the presence of clover had a positive effect on the yield. The cultivar composition of the ryegrass component had a significant effect on the yield, both in monoculture, and in combination with clover. For the genetic analyses, we validated empirically that genotyping-by-sequencing of pooled samples (pool-GBS) is a suitable method for accurate measurement of population allele frequencies, and obtained a dataset of 22,324 SNPs with complete data. We present a method to investigate the temporal dynamics of cultivars in seed mixtures grown under field conditions, and show how cultivar abundances vary during subsequent years. We screened the SNP panel for outlier loci, putatively under selection during the cultivation period, but none were detected.

Introduction of a natural resource balance indicator to assess soil organic carbon management: Agricultural Biomass Productivity Benefit

The rising demand for feed and food has put an increasing pressure on agriculture, with agricultural intensification as a direct response. Notwithstanding the higher crop productivity, intensive agriculture management entails many adverse environmental impacts. Worldwide, soil organic carbon (SOC) decline is hereby considered as a main danger which affects soil fertility and productivity. The life cycle perspective helps to get a holistic overview when evaluating the environmental sustainability of agricultural systems, though the impact of farm management on soil quality aspects is often not integrated. In this paper, we introduce an indicator called Agricultural Biomass Productivity Benefit of SOC management (ABB_SOC), which, relying on natural resource consumption, enables to estimate the net effect of the efforts made to attain a better soil quality. Hereby the focus is put on SOC. First, we introduce a framework to describe the SOC trend due to farm management decisions. The extent to which remediation measures are required are used as a measure for the induced SOC losses. Next, ABB_SOC values are calculated as the balance between the natural resource consumption of the inputs (including remediation efforts) and the desired output of arable crop production systems. The models RothC and EU-Rotate_N are used to simulate the SOC evolution due to farm management and the response of the biomass productivity, respectively. The developed indicator is applied on several rotation systems in Flanders, comparing different remediation strategies. The indicator could be used as a base for a method to account for soil quality in life cycle analysis.

Modelling leaf spectral properties in a soybean functional-structural plant model by integrating the prospect radiative transfer model

Background and Aims

Currently, functional-structural plant models (FSPMs) mostly resort to static descriptions of leaf spectral characteristics, which disregard the influence of leaf physiological changes over time. In many crop species, including soybean, these time-dependent physiological changes are of particular importance as leaf chlorophyll content changes with leaf age and vegetative nitrogen is remobilized to the developing fruit during pod filling.

Methods

PROSPECT, a model developed to estimate leaf biochemical composition from remote sensing data, is well suited to allow a dynamic approximation of leaf spectral characteristics in terms of leaf composition. In this study, measurements of the chlorophyll content index (CCI) were linked to leaf spectral characteristics within the 400-800 nm range by integrating the PROSPECT model into a soybean FSPM alongside a wavelength-specific light model.

Key Results

Straightforward links between the CCI and the parameters of the PROSPECT model allowed us to estimate leaf spectral characteristics with high accuracy using only the CCI as an input. After integration with an FSPM, this allowed digital reconstruction of leaf spectral characteristics on the scale of both individual leaves and the whole canopy. As a result, accurate simulations of light conditions within the canopy were obtained.

Conclusions

The proposed approach resulted in a very accurate representation of leaf spectral properties, based on fast and simple measurements of the CCI. Integration of accurate leaf spectral characteristics into a soybean FSPM leads to a better, dynamic understanding of the actual perceived light within the canopy in terms of both light quantity and quality.

Introducing turgor-driven growth dynamics into functional-structural plant models

Background and Aims

In many scenarios the availability of assimilated carbon is not the constraining factor of plant growth. Rather, organ growth appears driven by sink activity in which water availability plays a determinant role. Current functional-structural plant models (FSPMs) mainly focus on plant-carbon relations and largely disregard the importance of plant water status in organogenesis. Consequently, incorporating a turgor-driven growth concept, coupling carbon and water dynamics in an FSPM, presents a significant improvement towards capturing plant development in a more mechanistic manner.

Methods

An existing process-based water flow and storage model served as a basis for implementing water control in FSPMs. Its concepts were adjusted to the scale of individual plant organs and interwoven with the basic principles of modelling carbon dynamics to allow evaluation of turgor pressure across the entire plant. This was then linked to plant organ growth by applying the principles of the widely used Lockhart equation.

Key results

This model successfully integrates a mechanistic understanding of plant water transport dynamics coupled with simple carbon dynamics within a dynamically developing plant architecture. It allows evaluation of turgor pressure on the scale of plant organs, resulting in clear diel and long-term patterns, directly linked to plant organ growth.

Conclusions

A conceptual sap flow and turgor-driven growth model was introduced for functional-structural plant modelling. It is applicable to any plant architecture and allows visual exploration of the diel patterns of organ water content and growth. Integrated in existing FSPMs, this new concept fosters an array of possibilities for FSPMs, as it presents a different formulation of growth in terms of local processes, influenced by local and external conditions.

Physiological basis of chilling tolerance and early-season growth in miscanthus

BACKGROUND AND AIMS

The high productivity of Miscanthus × giganteus has been at least partly ascribed to its high chilling tolerance compared with related C4 crops, allowing for a longer productive growing season in temperate climates. However, the chilling tolerance of M. × giganteus has been predominantly studied under controlled environmental conditions. The understanding of the underlying mechanisms contributing to chilling tolerance in the field and their variation in different miscanthus genotypes is largely unexplored.

METHODS

Five miscanthus genotypes with different sensitivities to chilling were grown in the field and scored for a comprehensive set of physiological traits throughout the spring season. Chlorophyll fluorescence was measured as an indication of photosynthesis, and leaf samples were analysed for biochemical traits related to photosynthetic activity (chlorophyll content and pyruvate, Pi dikinase activity), redox homeostasis (malondialdehyde, glutathione and ascorbate contents, and catalase activity) and water-soluble carbohydrate content.

KEY RESULTS

Chilling-tolerant genotypes were characterized by higher levels of malondialdehyde, raffinose and sucrose, and higher catalase activity, while the chilling-sensitive genotypes were characterized by higher concentrations of glucose and fructose, and higher pyruvate, Pi dikinase activity later in the growing season. On the early sampling dates, the biochemical responses of M. × giganteus were similar to those of the chilling-tolerant genotypes, but later in the season they became more similar to those of the chilling-sensitive genotypes.

CONCLUSIONS

The overall physiological response of chilling-tolerant genotypes was distinguishable from that of chilling-sensitive genotypes, while M. × giganteus was intermediate between the two. There appears to be a trade-off between high and efficient photosynthesis and chilling stress tolerance. Miscanthus × giganteus is able to overcome this trade-off and, while it is more similar to the chilling-sensitive genotypes in early spring, its photosynthetic capacity is similar to that of the chilling-tolerant genotypes later on.

Orthology Guided Transcriptome Assembly of Italian Ryegrass and Meadow Fescue for Single-Nucleotide Polymorphism Discovery

Single-nucleotide polymorphisms (SNPs) represent natural DNA sequence variation. They can be used for various applications including the construction of high-density genetic maps, analysis of genetic variability, genome-wide association studies, and map-based cloning. Here we report on transcriptome sequencing in the two forage grasses, meadow fescue ( Huds.) and Italian ryegrass ( Lam.), and identification of various classes of SNPs. Using the Orthology Guided Assembly (OGA) strategy, we assembled and annotated a total of 18,952 and 19,036 transcripts for Italian ryegrass and meadow fescue, respectively. In addition, we used transcriptome sequence data of perennial ryegrass ( L.) from a previous study to identify 16,613 transcripts shared across all three species. Large numbers of intraspecific SNPs were identified in all three species: 248,000 in meadow fescue, 715,000 in Italian ryegrass, and 529,000 in perennial ryegrass. Moreover, we identified almost 25,000 interspecific SNPs located in 5343 genes that can distinguish meadow fescue from Italian ryegrass and 15,000 SNPs located in 3976 genes that discriminate meadow fescue from both species. All identified SNPs were positioned in silico on the seven linkage groups (LGs) of using the GenomeZipper approach. With the identification and positioning of interspecific SNPs, our study provides a valuable resource for the grass research and breeding community and will enable detailed characterization of genomic composition and gene expression analysis in prospective × hybrids.

Environmental life cycle assessment of grain maize production: An analysis of factors causing variability

To meet the growing demand, high yielding, but environmentally sustainable agricultural plant production systems are desired. Today, life cycle assessment (LCA) is increasingly used to assess the environmental impact of these agricultural systems. However, the impact results are very diverse due to management decisions or local natural conditions. The impact of grain maize is often generalized and an average is taken. Therefore, we studied variation in production systems. Four types of drivers for variability are distinguished: policy, farm management, year-to-year weather variation and innovation. For each driver, scenarios are elaborated using ReCiPe and CEENE (Cumulative Exergy Extraction from the Natural Environment) to assess the environmental footprint. Policy limits fertilisation levels in a soil-specific way. The resource consumption is lower for non-sandy soils than for sandy soils, but entails however more eutrophication. Farm management seems to have less influence on the environmental impact when considering the CEENE only. But farm management choices such as fertiliser type have a large effect on emission-related problems (e.g. eutrophication and acidification). In contrast, year-to-year weather variation results in large differences in the environmental footprint. The difference in impact results between favourable and poor environmental conditions amounts to 19% and 17% in terms of resources and emissions respectively, and irrigation clearly is an unfavourable environmental process. The best environmental performance is obtained by innovation as plant breeding results in a steadily increasing yield over 25 years. Finally, a comparison is made between grain maize production in Flanders and a generically applied dataset, based on Swiss practices. These very different results endorse the importance of using local data to conduct LCA of plant production systems. The results of this study show decision makers and farmers how they can improve the environmental performance of agricultural systems, and LCA practitioners are alerted to challenges due to variation.

Overexpression of GA20-OXIDASE1 impacts plant height, biomass allocation and saccharification efficiency in maize

Increased biomass yield and quality are of great importance for the improvement of feedstock for the biorefinery. For the production of bioethanol, both stem biomass yield and the conversion efficiency of the polysaccharides in the cell wall to fermentable sugars are of relevance. Increasing the endogenous levels of gibberellic acid (GA) by ectopic expression of GA20-OXIDASE1 (GA20-OX1), the rate-limiting step in GA biosynthesis, is known to affect cell division and cell expansion, resulting in larger plants and organs in several plant species. In this study, we examined biomass yield and quality traits of maize plants overexpressing GA20-OX1 (GA20-OX1). GA20-OX1 plants accumulated more vegetative biomass than control plants in greenhouse experiments, but not consistently over two years of field trials. The stems of these plants were longer but also more slender. Investigation of GA20-OX1 biomass quality using biochemical analyses showed the presence of more cellulose, lignin and cell wall residue. Cell wall analysis as well as expression analysis of lignin biosynthetic genes in developing stems revealed that cellulose and lignin were deposited earlier in development. Pretreatment of GA20-OX1 biomass with NaOH resulted in a higher saccharification efficiency per unit of dry weight, in agreement with the higher cellulose content. On the other hand, the cellulose-to-glucose conversion was slower upon HCl or hot-water pretreatment, presumably due to the higher lignin content. This study showed that biomass yield and quality traits can be interconnected, which is important for the development of future breeding strategies to improve lignocellulosic feedstock for bioethanol production.

Progress on Optimizing Miscanthus Biomass Production for the European Bioeconomy: Results of the EU FP7 Project OPTIMISC

This paper describes the complete findings of the EU-funded research project OPTIMISC, which investigated methods to optimize the production and use of miscanthus biomass. Miscanthus bioenergy and bioproduct chains were investigated by trialing 15 diverse germplasm types in a range of climatic and soil environments across central Europe, Ukraine, Russia, and China. The abiotic stress tolerances of a wider panel of 100 germplasm types to drought, salinity, and low temperatures were measured in the laboratory and a field trial in Belgium. A small selection of germplasm types was evaluated for performance in grasslands on marginal sites in Germany and the UK. The growth traits underlying biomass yield and quality were measured to improve regional estimates of feedstock availability. Several potential high-value bioproducts were identified. The combined results provide recommendations to policymakers, growers and industry. The major technical advances in miscanthus production achieved by OPTIMISC include: (1) demonstration that novel hybrids can out-yield the standard commercially grown genotype Miscanthus x giganteus; (2) characterization of the interactions of physiological growth responses with environmental variation within and between sites; (3) quantification of biomass-quality-relevant traits; (4) abiotic stress tolerances of miscanthus genotypes; (5) selections suitable for production on marginal land; (6) field establishment methods for seeds using plugs; (7) evaluation of harvesting methods; and (8) quantification of energy used in densification (pellet) technologies with a range of hybrids with differences in stem wall properties. End-user needs were addressed by demonstrating the potential of optimizing miscanthus biomass composition for the production of ethanol and biogas as well as for combustion. The costs and life-cycle assessment of seven miscanthus-based value chains, including small- and large-scale heat and power, ethanol, biogas, and insulation material production, revealed GHG-emission- and fossil-energy-saving potentials of up to 30.6 t CO_2eq C ha^-1y^-1 and 429 GJ ha^-1y^-1, respectively. Transport distance was identified as an important cost factor. Negative carbon mitigation costs of -78€ t^-1 CO_2eq C were recorded for local biomass use. The OPTIMISC results demonstrate the potential of miscanthus as a crop for marginal sites and provide information and technologies for the commercial implementation of miscanthus-based value chains.

A direct assessment of realized seed and pollen flow within and between two isolated populations of the food-deceptive orchid Orchis mascula

Gene flow can counteract the loss of genetic diversity caused by genetic drift in small populations. For this reason, clearly understanding gene flow patterns is of the highest importance across fragmented landscapes. However, gene flow patterns are not only dependent upon the degree of spatial isolation of fragmented populations, but are also dependent upon the life-history traits of the species. Indeed, habitat fragmentation effects appear especially unpredictable for food-deceptive orchid species, because of their highly specialised seed and pollen dispersal mechanisms. In this study we used amplified fragment length polymorphism markers and subsequent parentage and spatial autocorrelation analysis to quantify the extent and the patterns of realized gene flow within and between two adjacent fragmented populations of the food-deceptive Orchis mascula. We observed considerable gene flow between both populations, occurring mainly through pollen dispersal. Seed dispersal, on the other hand, was mainly limited to the first few meters from the mother plant in both populations, although at least one among-population seed dispersal event was observed. This, in turn, resulted in a significant spatial genetic structure for both populations. Although genetic diversity was high in both populations and mainly outcrossing occurred, reproductive output was strongly skewed toward a limited number of successful adult plants. These observed patterns are likely due to the different pollinator behaviour associated with food-deceptive plants. We conclude that these populations can be considered viable under their current fragmented state.

High-throughput phenotyping of lateral expansion and regrowth of spaced Lolium perenne plants using on-field image analysis

BACKGROUND

Genetic studies and breeding of agricultural crops frequently involve phenotypic characterization of large collections of genotypes grown in field conditions. These evaluations are typically based on visual observations and manual (destructive) measurements. Robust image capture and analysis procedures that allow phenotyping large collections of genotypes in time series during developmental phases represent a clear advantage as they allow non-destructive monitoring of plant growth and performance. A L. perenne germplasm panel including wild accessions, breeding material and commercial varieties has been used to develop a low-cost, high-throughput phenotyping tool for determining plant growth based on images of individual plants during two consecutive growing seasons. Further we have determined the correlation between image analysis-based estimates of the plant's base area and the capacity to regrow after cutting, with manual counts of tiller number and measurements of leaf growth 2 weeks after cutting, respectively. When working with field-grown plants, image acquisition and image segmentation are particularly challenging as outdoor light conditions vary throughout the day and the season, and variable soil colours hamper the delineation of the object of interest in the image. Therefore we have used several segmentation methods including colour-, texture- and edge-based approaches, and factors derived after a fast Fourier transformation. The performance of the procedure developed has been analysed in terms of effectiveness across different environmental conditions and time points in the season.

RESULTS

The procedure developed was able to analyse correctly 77.2 % of the 24,048 top view images processed. High correlations were found between plant's base area (image analysis-based) and tiller number (manual measurement) and between regrowth after cutting (image analysis-based) and leaf growth 2 weeks after cutting (manual measurement), with r values up to 0.792 and 0.824, respectively. Nevertheless, these relations depend on the origin of the plant material (forage breeding lines, current forage varieties, current turf varieties, and wild accessions) and the period in the season.

CONCLUSIONS

The image-derived parameters presented here deliver reliable, objective data, complementary to the breeders' scores, and are useful for genetic studies. Furthermore, large variation was shown among genotypes for the parameters investigated.

Clade classification of monolignol biosynthesis gene family members reveals target genes to decrease lignin in Lolium perenne

In monocots, lignin content has a strong impact on the digestibility of the cell wall fraction. Engineering lignin biosynthesis requires a profound knowledge of the role of paralogues in the multigene families that constitute the monolignol biosynthesis pathway. We applied a bioinformatics approach for genome-wide identification of candidate genes in Lolium perenne that are likely to be involved in the biosynthesis of monolignols. More specifically, we performed functional subtyping of phylogenetic clades in four multigene families: 4CL, COMT, CAD and CCR. Essential residues were considered for functional clade delineation within these families. This classification was complemented with previously published experimental evidence on gene expression, gene function and enzymatic activity in closely related crops and model species. This allowed us to assign functions to novel identified L. perenne genes, and to assess functional redundancy among paralogues. We found that two 4CL paralogues, two COMT paralogues, three CCR paralogues and one CAD gene are prime targets for genetic studies to engineer developmentally regulated lignin in this species. Based on the delineation of sequence conservation between paralogues and a first analysis of allelic diversity, we discuss possibilities to further study the roles of these paralogues in lignin biosynthesis, including expression analysis, reverse genetics and forward genetics, such as association mapping. We propose criteria to prioritise paralogues within multigene families and certain SNPs within these genes for developing genotyping assays or increasing power in association mapping studies. Although L. perenne was the target of the analyses presented here, this functional subtyping of phylogenetic clades represents a valuable tool for studies investigating monolignol biosynthesis genes in other monocot species.

Cold storage to overcome dormancy affects the carbohydrate status and photosynthetic capacity of Rhododendron simsii

Global warming leads to increasing irregular and unexpected warm spells during autumn, and therefore natural chilling requirements to break dormancy are at risk. Controlled cold treatment can provide an answer to this problem. Nevertheless, artificial cold treatment will have consequences for carbon reserves and photosynthesis. In this paper, the effect of dark cold storage at 7 °C to break flower bud dormancy in the evergreen Rhododendron simsii was quantified. Carbohydrate and starch content in leaves and flower buds of an early ('Nordlicht'), semi-early ('M. Marie') and late ('Mw. G. Kint') flowering cultivar showed that carbon loss due to respiration was lowest in 'M. Marie', while 'Mw. G. Kint' was completely depleted of starch reserves at the end of cold treatment. Gene isolation resulted in a candidate gene for sucrose synthase (SUS) RsSus, which appears to be homologous to AtSus3 and had a clear increase in expression in leaves during cold treatment. Photosynthesis measurements on 'Nordlicht' and the late-flowering cultivar 'Thesla' showed that during cold treatment, dark respiration decreased 58% and 63%, respectively. Immediately after cold treatment, dark respiration increased and stabilised after 3 days. The light compensation point followed the same trend as dark respiration. Quantum efficiency showed no significant changes during the first days after cold treatment, but was significantly higher than in plants with dormant flower buds at the start of cold treatment. In conclusion, photosynthesis stabilised 3 days after cold treatment and was improved compared to the level before cold treatment.

LEAF-E: a tool to analyze grass leaf growth using function fitting

In grasses, leaf growth is often monitored to gain insights in growth processes, biomass accumulation, regrowth after cutting, etc. To study the growth dynamics of the grass leaf, its length is measured at regular time intervals to derive the leaf elongation rate (LER) profile over time. From the LER profile, parameters such as maximal LER and leaf elongation duration (LED), which are essential for detecting inter-genotype growth differences and/or quantifying plant growth responses to changing environmental conditions, can be determined. As growth is influenced by the circadian clock and, especially in grasses, changes in environmental conditions such as temperature and evaporative demand, the LER profiles show considerable experimental variation and thus often do not follow a smooth curve. Hence it is difficult to quantify the duration and timing of growth. For these reasons, the measured data points should be fitted using a suitable mathematical function, such as the beta sigmoid function for leaf elongation. In the context of high-throughput phenotyping, we implemented the fitting of leaf growth measurements into a user-friendly Microsoft Excel-based macro, a tool called LEAF-E. LEAF-E allows to perform non-linear regression modeling of leaf length measurements suitable for robust and automated extraction of leaf growth parameters such as LER and LED from large datasets. LEAF-E is particularly useful to quantify the timing of leaf growth, which forms an important added value for detecting differences in leaf growth development. We illustrate the broad application range of LEAF-E using published and unpublished data sets of maize, Miscanthus spp. and Brachypodium distachyon, generated in independent experiments and for different purposes. In addition, we show that LEAF-E could also be used to fit datasets of other growth-related processes that follow the sigmoidal profile, such as cell length measurements along the leaf axis. Given its user-friendliness, ability to quantify duration and timing of leaf growth and broad application range, LEAF-E is a tool that could be routinely used to study growth processes following the sigmoidal profile.

The impact of extensive clonal growth on fine-scale mating patterns: a full paternity analysis of a lily-of-the-valley population (Convallaria majalis)

BACKGROUND AND AIMS

The combination of clonality and a mating system promoting outcrossing is considered advantageous because outcrossing avoids the fitness costs of selfing within clones (geitonogamy) while clonality assures local persistence and increases floral display. The spatial spread of genetically identical plants (ramets) may, however, also decrease paternal diversity (the number of sires fertilizing a given dam) and fertility, particularly towards the centre of large clumped clones. This study aimed to quantify the impact of extensive clonal growth on fine-scale paternity patterns in a population of the allogamous Convallaria majalis.

METHODS

A full analysis of paternity was performed by genotyping all flowering individuals and all viable seeds produced during a single season using AFLP. Mating patterns were examined and the spatial position of ramets was related to the extent of multiple paternity, fruiting success and seed production.

KEY RESULTS

The overall outcrossing rate was high (91 %) and pollen flow into the population was considerable (27 %). Despite extensive clonal growth, multiple paternity was relatively common (the fraction of siblings sharing the same father was 0·53 within ramets). The diversity of offspring collected from reproductive ramets surrounded by genetically identical inflorescences was as high as among offspring collected from ramets surrounded by distinct genets. There was no significant relationship between the similarity of the pollen load received by two ramets and the distance between them. Neither the distance of ramets with respect to distinct genets nor the distance to the genet centre significantly affected fruiting success or seed production.

CONCLUSIONS

Random mating and considerable pollen inflow most probably implied that pollen dispersal distances were sufficiently high to mitigate local mate scarcity despite extensive clonal spread. The data provide no evidence for the intrusion of clonal growth on fine-scale plant mating patterns.

SNP discovery using Paired-End RAD-tag sequencing on pooled genomic DNA of Sisymbrium austriacum (Brassicaceae)

Single nucleotide polymorphisms SNPs are rapidly replacing anonymous markers in population genomic studies, but their use in non model organisms is hampered by the scarcity of cost-effective approaches to uncover genome-wide variation in a comprehensive subset of individuals. The screening of one or only a few individuals induces ascertainment bias. To discover SNPs for a population genomic study of the Pyrenean rocket (Sisymbrium austriacum subsp. chrysanthum), we undertook a pooled RAD-PE (Restriction site Associated DNA Paired-End sequencing) approach. RAD tags were generated from the PstI-digested pooled genomic DNA of 12 individuals sampled across the species distribution range and paired-end sequenced using Illumina technology to produce ~24.5 Mb of sequences, covering ~7% of the specie's genome. Sequences were assembled into ~76 000 contigs with a mean length of 323 bp (N(50)  = 357 bp, sequencing depth = 24x). In all, >15 000 SNPs were called, of which 47% were annotated in putative genic regions based on homology with the Arabidopsis thaliana genome. Gene ontology (GO) slim categorization demonstrated that the identified SNPs covered extant genic variation well. The validation of 300 SNPs on a larger set of individuals using a KASPar assay underpinned the utility of pooled RAD-PE as an inexpensive genome-wide SNP discovery technique (success rate: 87%). In addition to SNPs, we discovered >600 putative SSR markers.

Genetic variation and risks of introgression in the wild Coffea arabica gene pool in south-western Ethiopian montane rainforests

The montane rainforests of SW Ethiopia are the primary centre of diversity of Coffea arabica and the origin of all Arabica coffee cultivated worldwide. This wild gene pool is potentially threatened by forest fragmentation and degradation, and by introgressive hybridization with locally improved coffee varieties. We genotyped 703 coffee shrubs from unmanaged and managed coffee populations, using 24 microsatellite loci. Additionally, we genotyped 90 individuals representing 23 Ethiopian cultivars resistant to coffee berry disease (CBD). We determined population genetic diversity, genetic structure, and admixture of cultivar alleles in the in situ gene pool. We found strong genetic differentiation between managed and unmanaged coffee populations, but without significant differences in within-population genetic diversity. The widespread planting of coffee seedlings including CBD-resistant cultivars most likely offsets losses of genetic variation attributable to genetic drift and inbreeding. Mixing cultivars with original coffee genotypes, however, leaves ample opportunity for hybridization and replacement of the original coffee gene pool, which already shows signs of admixture. In situ conservation of the wild gene pool of C. arabica must therefore focus on limiting coffee production in the remaining wild populations, as intensification threatens the genetic integrity of the gene pool by exposing wild genotypes to cultivars.

New insight into the history of domesticated apple: secondary contribution of the European wild apple to the genome of cultivated varieties

The apple is the most common and culturally important fruit crop of temperate areas. The elucidation of its origin and domestication history is therefore of great interest. The wild Central Asian species Malus sieversii has previously been identified as the main contributor to the genome of the cultivated apple (Malus domestica), on the basis of morphological, molecular, and historical evidence. The possible contribution of other wild species present along the Silk Route running from Asia to Western Europe remains a matter of debate, particularly with respect to the contribution of the European wild apple. We used microsatellite markers and an unprecedented large sampling of five Malus species throughout Eurasia (839 accessions from China to Spain) to show that multiple species have contributed to the genetic makeup of domesticated apples. The wild European crabapple M. sylvestris, in particular, was a major secondary contributor. Bidirectional gene flow between the domesticated apple and the European crabapple resulted in the current M. domestica being genetically more closely related to this species than to its Central Asian progenitor, M. sieversii. We found no evidence of a domestication bottleneck or clonal population structure in apples, despite the use of vegetative propagation by grafting. We show that the evolution of domesticated apples occurred over a long time period and involved more than one wild species. Our results support the view that self-incompatibility, a long lifespan, and cultural practices such as selection from open-pollinated seeds have facilitated introgression from wild relatives and the maintenance of genetic variation during domestication. This combination of processes may account for the diversification of several long-lived perennial crops, yielding domestication patterns different from those observed for annual species.

A comparative study of seed yield parameters in Arabidopsis thaliana mutants and transgenics

Because seed yield is the major factor determining the commercial success of grain crop cultivars, there is a large interest to obtain more understanding of the genetic factors underlying this trait. Despite many studies, mainly in the model plant Arabidopsis thaliana, have reported transgenes and mutants with effects on seed number and/or seed size, knowledge about seed yield parameters remains fragmented. This study investigated the effect of 46 genes, either in gain- and/or loss-of-function situations, with a total of 64 Arabidopsis lines being examined for seed phenotypes such as seed size, seed number per silique, number of inflorescences, number of branches on the main inflorescence and number of siliques. Sixteen of the 46 genes, examined in 14 Arabidopsis lines, were reported earlier to directly affect in seed size and/or seed number or to indirectly affect seed yield by their involvement in biomass production. Other genes involved in vegetative growth, flower or inflorescence development or cell division were hypothesized to potentially affect the final seed size and seed number. Analysis of this comprehensive data set shows that of the 14 lines previously described to be affected in seed size or seed number, only nine showed a comparable effect. Overall, this study provides the community with a useful resource for identifying genes with effects on seed yield and candidate genes underlying seed QTL. In addition, this study highlights the need for more thorough analysis of genes affecting seed yield.

Reproductive isolation and hybridization in sympatric populations of three Dactylorhiza species (Orchidaceae) with different ploidy levels

BACKGROUND AND AIMS

The potential for gene exchange between species with different ploidy levels has long been recognized, but only a few studies have tested this hypothesis in situ and most of them focused on not more than two co-occurring species. In this study, we examined hybridization patterns in two sites containing three species of the genus Dactylorhiza (diploid D. incarnata and D. fuchsii and their allotetraploid derivative D. praetermissa).

METHODS

To compare the strength of reproductive barriers between diploid species, and between diploid and tetraploid species, crossing experiments were combined with morphometric and molecular analyses using amplified fragment length polymorphism markers, whereas flow cytometric analyses were used to verify the hybrid origin of putative hybrids.

KEY RESULTS

In both sites, extensive hybridization was observed, indicating that gene flow between species is possible within the investigated populations. Bayesian assignment analyses indicated that the majority of hybrids were F(1) hybrids, but in some cases triple hybrids (hybrids with three species as parents) were observed, suggesting secondary gene flow. Crossing experiments showed that only crosses between pure species yielded a high percentage of viable seeds. When hybrids were involved as either pollen-receptor or pollen-donor, almost no viable seeds were formed, indicating strong post-zygotic reproductive isolation and high sterility.

CONCLUSIONS

Strong post-mating reproductive barriers prevent local breakdown of species boundaries in Dactylorhiza despite frequent hybridization between parental species. However, the presence of triple hybrids indicates that in some cases hybridization may extend the F(1) generation.

Nonrandom spatial structuring of orchids in a hybrid zone of three Orchis species

• Nonrandom species-species associations may arise from a range of factors, including localized dispersal, intra- and interspecific interactions and heterogeneous environmental conditions. Because seed germination and establishment in orchids are critically dependent upon the availability of suitable mycorrhizal fungi, species-species associations in orchids may reflect associations with mycorrhizal fungi. • To test this hypothesis, we examined spatial association patterns, mycorrhizal associations and germination success in a hybrid zone containing three species of the genus Orchis (Orchis anthropophora, Orchis militaris and Orchis purpurea). • Hybridization occurred predominantly between O. purpurea and O. militaris. The spatial distribution patterns of most pure species and hybrids were independent from each other, except that of O. purpurea and its hybrids. The fungal community composition of established individuals differed significantly between pure species, but not between hybrids and O. purpurea. Seed germination experiments using pure seeds showed that the highest number of protocorms were found in regions where adult individuals were most abundant. In the case of hybrid seeds, germination was restricted to areas where the mother plant was most abundant. • Overall, these results suggest that the observed nonrandom spatial distribution of both pure and hybrid plants is dependent on the contingencies of the spatial distribution of suitable mycorrhizal fungi.

The consequences of mating over a range of parental genetic similarity in a selfing allopolyploid plant species

In diploids, F(1) offspring performance is expected to increase with increasing genetic dissimilarity between the parents until an optimum is reached because outbreeding mitigates inbreeding depression and maximizes heterosis. However, many flowering plant species are derived through allopolyploidization, i.e. interspecific hybridization with genome doubling. This mode of plant speciation can be expected to considerably alter the consequences of inbreeding and outbreeding. We investigated the F1 fitness consequences of mating over a range of (genetic) distances in the allohexaploid plant species Geum urbanum. Offspring was raised under controlled conditions (632 plants). The performance of outcrossed progeny was not significantly better than that of their selfed half-siblings and did not increase with parental genetic dissimilarity (0-0.83). Our findings support low, if any, inbreeding depression and heterosis. We attribute this to the peculiar state of quasi-permanent heterozygosity in allopolyploids and frequent selfing.

Patterns of hybridization between diploid and derived allotetraploid species of Dactylorhiza (Orchidaceae) co-occurring in Belgium

PREMISE OF THE STUDY

Although the potential for gene flow between species with large differences in chromosome numbers has long been recognized, only few studies have thoroughly investigated in situ hybridization across taxa with different ploidy levels. We combined morphological, cytological, and genetic marker data with pollination experiments to investigate the degree, direction, and spatial pattern of hybridization between the diploid Dactylorhiza incarnata and its tetraploid derivative, D. praetermissa.

METHODS

To identify hybrids, 169 individuals were genotyped using AFLPs and morphologically characterized. Individuals were clustered on the basis of their AFLP profile using the program Structure. To reduce the dimensionality of the plant-trait matrix, PCA was applied. The origin of suspected hybrid individuals was verified using flow cytometry. An AMOVA and spatial autocorrelation analysis were used to indirectly infer the extent of gene flow.

KEY RESULTS

Only five individuals were regarded as putative hybrids on the basis of the AFLP data; all had been assigned to the D. praetermissa morphotype. Only one had deviating DNA content and was presumably a triploid. High Φ(ST) values between different subpopulations and significant spatial genetic structure were observed, suggesting localized gene flow.

CONCLUSIONS

Using combined data to study hybridization between D. incarnata and D. praetermissa, very few unequivocal hybrids were observed. We propose several non-mutually exclusive explanations. Localized pollen flow, in combination with different microhabitat preferences, is probably one of the reasons for the low frequency of hybrids. Also, the triploid first-generation hybrids may experience difficulties in successful establishment, as a result of genic incompatibilities.

EST-derived SSR markers used as anchor loci for the construction of a consensus linkage map in ryegrass (Lolium spp.)

BACKGROUND

Genetic markers and linkage mapping are basic prerequisites for marker-assisted selection and map-based cloning. In the case of the key grassland species Lolium spp., numerous mapping populations have been developed and characterised for various traits. Although some genetic linkage maps of these populations have been aligned with each other using publicly available DNA markers, the number of common markers among genetic maps is still low, limiting the ability to compare candidate gene and QTL locations across germplasm.

RESULTS

A set of 204 expressed sequence tag (EST)-derived simple sequence repeat (SSR) markers has been assigned to map positions using eight different ryegrass mapping populations. Marker properties of a subset of 64 EST-SSRs were assessed in six to eight individuals of each mapping population and revealed 83% of the markers to be polymorphic in at least one population and an average number of alleles of 4.88. EST-SSR markers polymorphic in multiple populations served as anchor markers and allowed the construction of the first comprehensive consensus map for ryegrass. The integrated map was complemented with 97 SSRs from previously published linkage maps and finally contained 284 EST-derived and genomic SSR markers. The total map length was 742 centiMorgan (cM), ranging for individual chromosomes from 70 cM of linkage group (LG) 6 to 171 cM of LG 2.

CONCLUSIONS

The consensus linkage map for ryegrass based on eight mapping populations and constructed using a large set of publicly available Lolium EST-SSRs mapped for the first time together with previously mapped SSR markers will allow for consolidating existing mapping and QTL information in ryegrass. Map and markers presented here will prove to be an asset in the development for both molecular breeding of ryegrass as well as comparative genetics and genomics within grass species.

Extremely low genotypic diversity and sexual reproduction in isolated populations of the self-incompatible lily-of-the-valley (Convallaria majalis) and the role of the local forest environment

BACKGROUND AND AIMS

Clonal growth is a common phenomenon in plants and allows them to persist when sexual life-cycle completion is impeded. Very low levels of recruitment from seed will ultimately result in low levels of genotypic diversity. The situation can be expected to be exacerbated in spatially isolated populations of obligated allogamous species, as low genotypic diversities will result in low availability of compatible genotypes and low reproductive success. Populations of the self-incompatible forest herb lily-of-the-valley (Convallaria majalis) were studied with the aim of inferring the relative importance of sexual and asexual recruitment. Then the aim was to establish a relationship between genotypic diversity, sexual reproduction and the local forest environment.

METHODS

Highly polymorphic microsatellite markers were used to investigate clonal diversities and population genetic structure of 20 populations of C. majalis in central Belgium.

KEY RESULTS

Most of the populations studied consisted of a single genotype and linkage disequilibrium within populations was high, manifesting clonal growth as the main mode of reproduction. A population consisting of multiple genotypes mainly occurred in locations with a thin litter layer and high soil phosphorus levels, suggesting environment-mediated sporadic recruitment from seed. Highly significant genetic differentiation indicated that populations are reproductively isolated. In agreement with the self-incompatibility of C. majalis, monoclonal populations showed very low or even absent fruit set.

CONCLUSIONS

Lack of sexual recruitment in spatially isolated C. majalis populations has resulted in almost monoclonal populations with reduced or absent sexual reproduction, potentially constraining their long-term persistence. The local forest environment may play an important role in mediating sexual recruitment in clonal forest plant species.