Rethinking temperature effects on leaf growth, gene expression and metabolism: Diel variation matters

Plants have evolved to grow under prominently fluctuating environmental conditions. In experiments under controlled conditions, temperature is often set to artificial, binary regimes with constant values at day and at night. This study investigated how such a diel (24 hr) temperature regime affects leaf growth, carbohydrate metabolism and gene expression, compared to a temperature regime with a field-like gradual increase and decline throughout 24 hr. Soybean (Glycine max) was grown under two contrasting diel temperature treatments. Leaf growth was measured in high temporal resolution. Periodical measurements were performed of carbohydrate concentrations, carbon isotopes as well as the transcriptome by RNA sequencing. Leaf growth activity peaked at different times under the two treatments, which cannot be explained intuitively. Under field-like temperature conditions, leaf growth followed temperature and peaked in the afternoon, whereas in the binary temperature regime, growth increased at night and decreased during daytime. Differential gene expression data suggest that a synchronization of cell division activity seems to be evoked in the binary temperature regime. Overall, the results show that the coordination of a wide range of metabolic processes is markedly affected by the diel variation of temperature, which emphasizes the importance of realistic environmental settings in controlled condition experiments.

Characterization and practical use of self-compatibility in outcrossing grass species

BACKGROUND

Self-incompatibility (SI) systems prevent self-fertilization in several species of Poaceae, many of which are economically important forage, bioenergy and turf grasses. Self-incompatibility ensures cross-pollination and genetic diversity but restricts the ability to fix useful genetic variation. In most inbred crops it is possible to develop high-performing homozygous parental lines by self-pollination, which then enables the creation of F1 hybrid varieties with higher performance, a phenomenon known as heterosis. The inability to fully exploit heterosis in outcrossing grasses is partially responsible for lower levels of improvement in breeding programmes compared with inbred crops. However, SI can be overcome in forage grasses to create self-compatible populations. This is generating interest in understanding the genetical basis of self-compatibility (SC), its significance for reproductive strategies and its exploitation for crop improvement, especially in the context of F1 hybrid breeding.

SCOPE

We review the literature on SI and SC in outcrossing grass species. We review the currently available genomic tools and approaches used to discover and characterize novel SC sources. We discuss opportunities barely explored for outcrossing grasses that SC facilitates. Specifically, we discuss strategies for wide SC introgression in the context of the Lolium-Festuca complex and the use of SC to develop immortalized mapping populations for the dissection of a wide range of agronomically important traits. The germplasm available is a valuable practical resource and will aid understanding the basis of inbreeding depression and hybrid vigour in key temperate forage grass species.

CONCLUSIONS

A better understanding of the genetic control of additional SC loci offers new insight into SI systems, their evolutionary origins and their reproductive significance. Heterozygous outcrossing grass species that can be readily selfed facilitate studies of heterosis. Moreover, SC introduction into a range of grass species will enable heterosis to be exploited in innovative ways in genetic improvement programmes.

Heritable Variation in Pea for Resistance Against a Root Rot Complex and Its Characterization by Amplicon Sequencing

Soil-borne pathogens cause severe root rot of pea (Pisum sativum L.) and are a major constraint to pea cultivation worldwide. Resistance against individual pathogen species is often ineffective in the field where multiple pathogens form a pea root rot complex (PRRC) and conjointly infect pea plants. On the other hand, various beneficial plant-microbe interactions are known that offer opportunities to strengthen plant health. To account for the whole rhizosphere microbiome in the assessment of root rot resistance in pea, an infested soil-based resistance screening assay was established. The infested soil originated from a field that showed severe pea root rot in the past. Initially, amplicon sequencing was employed to characterize the fungal microbiome of diseased pea roots grown in the infested soil. The amplicon sequencing evidenced a diverse fungal community in the roots including pea pathogens Fusarium oxysporum, F. solani, Didymella sp., and Rhizoctonia solani and antagonists such as Clonostachys rosea and several mycorrhizal species. The screening system allowed for a reproducible assessment of disease parameters among 261 pea cultivars, breeding lines, and landraces grown for 21 days under controlled conditions. A sterile soil control treatment was used to calculate relative shoot and root biomass in order to compare growth performance of pea lines with highly different growth morphologies. Broad sense heritability was calculated from linear mixed model estimated variance components for all traits. Emergence on the infested soil showed high (H 2 = 0.89), root rot index (H 2 = 0.43), and relative shoot dry weight (H 2 = 0.51) medium heritability. The resistance screening allowed for a reproducible distinction between PRRC susceptible and resistant pea lines. The combined assessment of root rot index and relative shoot dry weight allowed to identify resistant (low root rot index) and tolerant pea lines (low relative shoot dry weight at moderate to high root rot index). We conclude that relative shoot dry weight is a valuable trait to select disease tolerant pea lines. Subsequently, the resistance ranking was verified in an on-farm experiment with a subset of pea lines. We found a significant correlation (r s = 0.73, p = 0.03) between the controlled conditions and the resistance ranking in a field with high PRRC infestation. The screening system allows to predict PRRC resistance for a given field site and offers a tool for selection at the seedling stage in breeding nurseries. Using the complexity of the infested field soil, the screening system provides opportunities to study plant resistance in the light of diverse plant-microbe interactions occurring in the rhizosphere.

The apple REFPOP-a reference population for genomics-assisted breeding in apple

Breeding of apple is a long-term and costly process due to the time and space requirements for screening selection candidates. Genomics-assisted breeding utilizes genomic and phenotypic information to increase the selection efficiency in breeding programs, and measurements of phenotypes in different environments can facilitate the application of the approach under various climatic conditions. Here we present an apple reference population: the apple REFPOP, a large collection formed of 534 genotypes planted in six European countries, as a unique tool to accelerate apple breeding. The population consisted of 269 accessions and 265 progeny from 27 parental combinations, representing the diversity in cultivated apple and current European breeding material, respectively. A high-density genome-wide dataset of 303,239 SNPs was produced as a combined output of two SNP arrays of different densities using marker imputation with an imputation accuracy of 0.95. Based on the genotypic data, linkage disequilibrium was low and population structure was weak. Two well-studied phenological traits of horticultural importance were measured. We found marker-trait associations in several previously identified genomic regions and maximum predictive abilities of 0.57 and 0.75 for floral emergence and harvest date, respectively. With decreasing SNP density, the detection of significant marker-trait associations varied depending on trait architecture. Regardless of the trait, 10,000 SNPs sufficed to maximize genomic prediction ability. We confirm the suitability of the apple REFPOP design for genomics-assisted breeding, especially for breeding programs using related germplasm, and emphasize the advantages of a coordinated and multinational effort for customizing apple breeding methods in the genomics era.

A Non-destructive Method to Quantify Leaf Starch Content in Red Clover

Grassland-based ruminant livestock production provides a sustainable alternative to intensive production systems relying on concentrated feeds. However, grassland-based roughage often lacks the energy content required to meet the productivity potential of modern livestock breeds. Forage legumes, such as red clover, with increased starch content could partly replace maize and cereal supplements. However, breeding for increased starch content requires efficient phenotyping methods. This study is unique in evaluating a non-destructive hyperspectral imaging approach to estimate leaf starch content in red clover for enabling efficient development of high starch red clover genotypes. We assessed prediction performance of partial least square regression models (PLSR) using cross-validation, and validated model performance with an independent test set under controlled conditions. Starch content of the training set ranged from 0.1 to 120.3 mg g-1 DW. The best cross-validated PLSR model explained 56% of the measured variation and yielded a root mean square error (RMSE) of 17 mg g-1 DW. Model performance decreased when applying the trained model on the independent test set (RMSE = 29 mg g-1 DW, R 2 = 0.36). Different variable selection methods did not increase model performance. Once validated in the field, the non-destructive spectral method presented here has the potential to detect large differences in leaf starch content of red clover genotypes. Breeding material could be sampled and selected according to their starch content without destroying the plant.

Genomic Prediction of Agronomic Traits in Common Bean (Phaseolus vulgaris L.) Under Environmental Stress

In plant and animal breeding, genomic prediction models are established to select new lines based on genomic data, without the need for laborious phenotyping. Prediction models can be trained on recent or historic phenotypic data and increasingly available genotypic data. This enables the adoption of genomic selection also in under-used legume crops such as common bean. Beans are an important staple food in the tropics and mainly grown by smallholders under limiting environmental conditions such as drought or low soil fertility. Therefore, genotype-by-environment interactions (G × E) are an important consideration when developing new bean varieties. However, G × E are often not considered in genomic prediction models nor are these models implemented in current bean breeding programs. Here we show the prediction abilities of four agronomic traits in common bean under various environmental stresses based on twelve field trials. The dataset includes 481 elite breeding lines characterized by 5,820 SNP markers. Prediction abilities over all twelve trials ranged between 0.6 and 0.8 for yield and days to maturity, respectively, predicting new lines into new seasons. In all four evaluated traits, the prediction abilities reached about 50-80% of the maximum accuracies given by phenotypic correlations and heritability. Predictions under drought and low phosphorus stress were up to 10 and 20% improved when G × E were included in the model, respectively. Our results demonstrate the potential of genomic selection to increase the genetic gain in common bean breeding. Prediction abilities improved when more phenotypic data was available and G × E could be accounted for. Furthermore, the developed models allowed us to predict genotypic performance under different environmental stresses. This will be a key factor in the development of common bean varieties adapted to future challenging conditions.

DNA barcode trnH-psbA is a promising candidate for efficient identification of forage legumes and grasses

OBJECTIVE

Grasslands are widespread ecosystems that fulfil many functions. Plant species richness (PSR) is known to have beneficial effects on such functions and monitoring PSR is crucial for tracking the effects of land use and agricultural management on these ecosystems. Unfortunately, traditional morphology-based methods are labor-intensive and cannot be adapted for high-throughput assessments. DNA barcoding could aid increasing the throughput of PSR assessments in grasslands. In this proof-of-concept work, we aimed at determining which of three plant DNA barcodes (rbcLa, matK and trnH-psbA) best discriminates 16 key grass and legume species common in temperate sub-alpine grasslands.

RESULTS

Barcode trnH-psbA had a 100% correct assignment rate (CAR) in the five analyzed legumes, followed by rbcLa (93.3%) and matK (55.6%). Barcode trnH-psbA had a 100% CAR in the grasses Cynosurus cristatus, Dactylis glomerata and Trisetum flavescens. However, the closely related Festuca, Lolium and Poa species were not always correctly identified, which led to an overall CAR in grasses of 66.7%, 50.0% and 46.4% for trnH-psbA, matK and rbcLa, respectively. Barcode trnH-psbA is thus the most promising candidate for PSR assessments in permanent grasslands and could greatly support plant biodiversity monitoring on a larger scale.

Genome-Wide Association Study to Identify Candidate Loci for Biomass Formation Under Water Deficit in Perennial Ryegrass

Global warming is predicted to impact many agricultural areas, which will suffer from reduced water availability. Due to precipitation changes, mild summer droughts are expected to become more frequent, even in temperate regions. For perennial ryegrass (Lolium perenne L.), an important forage grass of the Poaceae family, leaf growth is a crucial factor determining biomass accumulation and hence forage yield. Although leaf elongation has been shown to be temperature-dependent under normal conditions, the genetic regulation of leaf growth under water deficit in perennial ryegrass is poorly understood. Herein, we evaluated the response to water deprivation in a diverse panel of perennial ryegrass genotypes, employing a high-precision phenotyping platform. The study revealed phenotypic variation for growth-related traits and significant (P < 0.05) differences in leaf growth under normal conditions within the subgroups of turf and forage type cultivars. The phenotypic data was combined with genotypic variants identified using genotyping-by-sequencing to conduct a genome-wide association study (GWAS). Using GWAS, we identified DNA polymorphisms significantly associated with leaf growth reduction under water deprivation. These polymorphisms were adjacent to genes predicted to encode for phytochrome B and a MYB41 transcription factor. The result obtained in the present study will increase our understanding on the complex molecular mechanisms involved in plant growth under water deficit. Moreover, the single nucleotide polymorphism (SNP) markers identified will serve as a valuable resource in future breeding programs to select for enhanced biomass formation under mild summer drought conditions.

Haplotypes at the Phg-2 Locus Are Determining Pathotype-Specificity of Angular Leaf Spot Resistance in Common Bean

Angular leaf spot (ALS) is one of the most devastating diseases of common bean (Phaseolus vulgaris L.) and causes serious yield losses worldwide. ALS resistance is reportedly pathotype-specific, but little is known about the efficacy of resistance loci against different pathotypes. Here, we report on ALS resistance evaluations of 316 bean lines under greenhouse and field conditions at multiple sites in Colombia and Uganda. Surprisingly, genome-wide association studies revealed only two of the five previously described resistance loci to be significantly associated with ALS resistance. Phg-2 on chromosome eight was crucial for ALS resistance in all trials, while the resistance locus Phg-4 on chromosome 4 was effective against one particular pathotype. Further dissection of Phg-2 uncovered an unprecedented diversity of functional haplotypes for a resistance locus in common bean. DNA sequence-based clustering identified eleven haplotype groups at Phg-2. One haplotype group conferred broad-spectrum ALS resistance, six showed pathotype-specific effects, and the remaining seven did not exhibit clear resistance patterns. Our research highlights the importance of ALS pathotype-specificity for durable resistance management strategies in common bean. Molecular markers co-segregating with resistance loci and haplotypes will increase breeding efficiency for ALS resistance and allow to react faster to future changes in pathogen pressure and composition.

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.

Pooled DNA sequencing to identify SNPs associated with a major QTL for bacterial wilt resistance in Italian ryegrass (Lolium multiflorum Lam.)

SNPs and candidate genes associated with bacterial wilt resistance in Italian ryegrass were identified by sequencing the parental plants and pooled F₁ progeny of a segregating population. Italian ryegrass (Lolium multiflorum Lam.) is one of the most important forage grass species in temperate regions. Its yield, quality and persistency can significantly be reduced by bacterial wilt, a serious disease caused by Xanthomonas translucens pv. graminis. Although a major QTL for bacterial wilt resistance has previously been reported, detailed knowledge on underlying genes and DNA markers to allow for efficient resistance breeding strategies is currently not available. We used pooled DNA sequencing to characterize a major QTL for bacterial wilt resistance of Italian ryegrass and to develop inexpensive sequence-based markers to efficiently target resistance alleles for marker-assisted recurrent selection. From the mapping population segregating for the QTL, DNA of 44 of the most resistant and 44 of the most susceptible F₁ individuals was pooled and sequenced using the Illumina HiSeq 2000 platform. Allele frequencies of 18 × 10⁶ single nucleotide polymorphisms (SNP) were determined in the resistant and susceptible pool. A total of 271 SNPs on 140 scaffold sequences of the reference parental genome showed significantly different allele frequencies in both pools. We converted 44 selected SNPs to KASP™ markers, genetically mapped these proximal to the major QTL and thus validated their association with bacterial wilt resistance. This study highlights the power of pooled DNA sequencing to efficiently target binary traits in biparental mapping populations. It delivers genome sequence data, SNP markers and potential candidate genes which will allow to implement marker-assisted strategies to fix bacterial wilt resistance in outcrossing breeding populations of Italian ryegrass.

Phenotyping a Dynamic Trait: Leaf Growth of Perennial Ryegrass Under Water Limiting Conditions

Water limitation is one of the major factors reducing crop productivity worldwide. In order to develop efficient breeding strategies to improve drought tolerance, accurate methods to identify when a plant reduces growth as a consequence of water deficit have yet to be established. In perennial ryegrass (Lolium perenne L.), an important forage grass of the Poaceae family, leaf elongation is a key factor determining plant growth and hence forage yield. Although leaf elongation has been shown to be temperature-dependent under non-stress conditions, the impact of water limitation on leaf elongation in perennial ryegrass is poorly understood. We describe a method for quantifying tolerance to water deficit based on leaf elongation in relation to temperature and soil moisture in perennial ryegrass. With decreasing soil moisture, three growth response phases were identified: first, a "normal" phase where growth is mainly determined by temperature, second a "slow" phase where leaf elongation decreases proportionally to soil water potential and third an "arrest" phase where leaf growth terminates. A custom R function was able to quantify the points which demarcate these phases and can be used to describe the response of plants to water deficit. Applied to different perennial ryegrass genotypes, this function revealed significant genotypic variation in the response of leaf growth to temperature and soil moisture. Dynamic phenotyping of leaf elongation can be used as a tool to accurately quantify tolerance to water deficit in perennial ryegrass and to improve this trait by breeding. Moreover, the tools presented here are applicable to study the plant response to other stresses in species with linear, graminoid leaf morphology.

Insights to plant-microbe interactions provide opportunities to improve resistance breeding against root diseases in grain legumes

Root and foot diseases severely impede grain legume cultivation worldwide. Breeding lines with resistance against individual pathogens exist, but these resistances are often overcome by the interaction of multiple pathogens in field situations. Novel tools allow to decipher plant-microbiome interactions in unprecedented detail and provide insights into resistance mechanisms that consider both simultaneous attacks of various pathogens and the interplay with beneficial microbes. Although it has become clear that plant-associated microbes play a key role in plant health, a systematic picture of how and to what extent plants can shape their own detrimental or beneficial microbiome remains to be drawn. There is increasing evidence for the existence of genetic variation in the regulation of plant-microbe interactions that can be exploited by plant breeders. We propose to consider the entire plant holobiont in resistance breeding strategies in order to unravel hidden parts of complex defence mechanisms. This review summarizes (a) the current knowledge of resistance against soil-borne pathogens in grain legumes, (b) evidence for genetic variation for rhizosphere-related traits, (c) the role of root exudation in microbe-mediated disease resistance and elaborates (d) how these traits can be incorporated in resistance breeding programmes.

Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch

Accurate, high-throughput phenotyping for quantitative traits is a limiting factor for progress in plant breeding. We developed an automated image analysis to measure quantitative resistance to septoria tritici blotch (STB), a globally important wheat disease, enabling identification of small chromosome intervals containing plausible candidate genes for STB resistance. 335 winter wheat cultivars were included in a replicated field experiment that experienced natural epidemic development by a highly diverse but fungicide-resistant pathogen population. More than 5.4 million automatically generated phenotypes were associated with 13,648 SNP markers to perform the GWAS. We identified 26 chromosome intervals explaining 1.9-10.6% of the variance associated with four independent resistance traits. Sixteen of the intervals overlapped with known STB resistance intervals, suggesting that our phenotyping approach can identify simultaneously (i.e., in a single experiment) many previously defined STB resistance intervals. Seventeen of the intervals were less than 5 Mbp in size and encoded only 173 genes, including many genes associated with disease resistance. Five intervals contained four or fewer genes, providing high priority targets for functional validation. Ten chromosome intervals were not previously associated with STB resistance, perhaps representing resistance to pathogen strains that had not been tested in earlier experiments. The SNP markers associated with these chromosome intervals can be used to recombine different forms of quantitative STB resistance that are likely to be more durable than pyramids of major resistance genes. Our experiment illustrates how high-throughput automated phenotyping can accelerate breeding for quantitative disease resistance.

Genetic Loci Governing Androgenic Capacity in Perennial Ryegrass (Lolium perenne L.)

Immature pollen can be induced to switch developmental pathways from gametogenesis to embryogenesis and subsequently regenerate into homozygous, diploid plants. Such androgenic production of doubled haploids is particularly useful for species where inbreeding is hampered by effective self-incompatibility systems. Therefore, increasing the generally low androgenic capacity of perennial ryegrass (Lolium perenne L.) germplasm would enable the efficient production of homozygous plant material, so that a more effective exploitation of heterosis through hybrid breeding schemes can be realized. Here, we present the results of a genome-wide association study in a heterozygous, multiparental population of perennial ryegrass (n = 391) segregating for androgenic capacity. Genotyping-by-sequencing was used to interrogate gene- dense genomic regions and revealed over 1,100 polymorphic sites. Between one and 10 quantitative trait loci (QTL) were identified for anther response, embryo and total plant production, green and albino plant production and regeneration. Most traits were under polygenic control, although a major QTL on linkage group 5 was associated with green plant regeneration. Distinct genetic factors seem to affect green and albino plant recovery. Two intriguing candidate genes, encoding chromatin binding domains of the developmental phase transition regulator, Polycomb Repressive Complex 2, were identified. Our results shed the first light on the molecular mechanisms behind perennial ryegrass microspore embryogenesis and enable marker-assisted introgression of androgenic capacity into recalcitrant germplasm of this forage crop of global significance.

Fine mapping a self-fertility locus in perennial ryegrass

A self-fertility locus was fine mapped to a 1.6 cM region on linkage group 5 in a perennial ryegrass population. This locus was the main determinant of pollen self-compatibility. In grasses, self-incompatibility (SI) is characterized by a two-loci gametophytic (S and Z) mechanism acting together in the recognition and inhibition of self-pollen. Mutations affecting the expression of SI have been reported in a few grass species. In perennial ryegrass (Lolium perenne L.), a mutation independent from S and Z, and mapping on linkage group 5 (LG 5), was previously reported to produce self-fertile plants. Here, we describe fine mapping of the self-fertility (SF) gene in a perennial ryegrass population and determine whether there is any effect of other genomic regions on the pollen compatibility. The phenotypic segregation of SF showed a bimodal distribution with one mean at 49% pollen compatibility and the other at 91%. Marker-trait association analysis showed that only markers on LG 5 were significantly associated with the trait. A single gene model explained 82% of the observed variability and no effects of the other regions were detected. Using segregation and linkage analysis, the SF locus was located to a 1.6 cM region on LG 5. The flanking marker sequences were aligned to rice and Brachypodium distachyon reference genomes to estimate the physical distance. We provide markers tightly linked to SF that can be used for introgression of this trait into advanced breeding germplasm. Moreover, our results represent a further step towards the identification of the SF gene in LG 5.

In Silico Identification of Candidate Genes for Fertility Restoration in Cytoplasmic Male Sterile Perennial Ryegrass (Lolium perenne L.)

Perennial ryegrass (Lolium perenne L.) is widely used for forage production in both permanent and temporary grassland systems. To increase yields in perennial ryegrass, recent breeding efforts have been focused on strategies to more efficiently exploit heterosis by hybrid breeding. Cytoplasmic male sterility (CMS) is a widely applied mechanism to control pollination for commercial hybrid seed production and although CMS systems have been identified in perennial ryegrass, they are yet to be fully characterized. Here, we present a bioinformatics pipeline for efficient identification of candidate restorer of fertility (Rf) genes for CMS. From a high-quality draft of the perennial ryegrass genome, 373 pentatricopeptide repeat (PPR) genes were identified and classified, further identifying 25 restorer of fertility-like PPR (RFL) genes through a combination of DNA sequence clustering and comparison to known Rf genes. This extensive gene family was targeted as the majority of Rf genes in higher plants are RFL genes. These RFL genes were further investigated by phylogenetic analyses, identifying three groups of perennial ryegrass RFLs. These three groups likely represent genomic regions of active RFL generation and identify the probable location of perennial ryegrass PPR-Rf genes. This pipeline allows for the identification of candidate PPR-Rf genes from genomic sequence data and can be used in any plant species. Functional markers for PPR-Rf genes will facilitate map-based cloning of Rf genes and enable the use of CMS as an efficient tool to control pollination for hybrid crop production.

A Novel Multivariate Approach to Phenotyping and Association Mapping of Multi-Locus Gametophytic Self-Incompatibility Reveals S, Z, and Other Loci in a Perennial Ryegrass (Poaceae) Population

Self-incompatibility (SI) is a mechanism that many flowering plants employ to prevent fertilisation by self- and self-like pollen ensuring heterozygosity and hybrid vigour. Although a number of single locus mechanisms have been characterised in detail, no multi-locus systems have been fully elucidated. Historically, examples of the genetic analysis of multi-locus SI, to make analysis tractable, are either made on the progeny of bi-parental crosses, where the number of alleles at each locus is restricted, or on crosses prepared in such a way that only one of the SI loci segregates. Perennial ryegrass (Lolium perenne L.) possesses a well-documented two locus (S and Z) gametophytic incompatibility system. A more universal, realistic proof of principle study was conducted in a perennial ryegrass population in which allelic and non-allelic diversity was not artificially restricted. A complex pattern of pollinations from a diallel cross was revealed which could not possibly be interpreted easily per se, even with an already established genetic model. Instead, pollination scores were distilled into principal component scores described as Compatibility Components (CC1-CC3). These were then subjected to a conventional genome-wide association analysis. CC1 associated with markers on linkage groups (LGs) 1, 2, 3, and 6, CC2 exclusively with markers in a genomic region on LG 2, and CC3 with markers on LG 1. BLAST alignment with the Brachypodium physical map revealed highly significantly associated markers with peak associations with genes adjacent and four genes away from the chromosomal locations of candidate SI genes, S- and Z-DUF247, respectively. Further significant associations were found in a Brachypodium distachyon chromosome 3 region, having shared synteny with Lolium LG 1, suggesting further SI loci linked to S or extensive micro-re-arrangement of the genome between B. distachyon and L. perenne. Significant associations with gene sequences aligning with marker sequences on Lolium LGs 3 and 6 were also identified. We therefore demonstrate the power of a novel association genetics approach to identify the genes controlling multi-locus gametophytic SI systems and to identify novel loci potentially involved in already established SI systems.

Drought Effects on Proanthocyanidins in Sainfoin (Onobrychis viciifolia Scop.) Are Dependent on the Plant's Ontogenetic Stage

Sainfoin (Onobrychis viciifolia Scop.) is a forage legume, which improves animal health and the environmental impact of livestock farming due to its proanthocyanidin content. To identify the impact of drought on acetone/water-extractable proanthocyanidin (PA) concentration and composition in the generative and vegetative stages, a rain exclosure experiment was established. Leaves of 120 plants from 5 different sainfoin accessions were sampled repeatedly and analyzed by UPLC-ESI-MS/MS. The results showed distinct differences in response to drought between vegetative and generative plants. Whereas vegetative plants showed a strong response to drought in growth (-56%) and leaf PA concentration (+46%), generative plants showed no response in growth (-2%) or PA concentration (-9%). The PA composition was stable across environments. The five accessions varied in PA concentrations and composition but showed the same pattern of response to the experimental treatments. These results show that the ontogenetic stage at which drought occurs significantly affects the plant's response.

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.

Overcoming self-incompatibility in grasses: a pathway to hybrid breeding

Allogamous grasses exhibit an effective two-locus gametophytic self-incompatibility (SI) system, limiting the range of breeding techniques applicable for cultivar development. Current breeding methods based on populations are characterized by comparably low genetic gains for important traits such as biomass yield. To implement more efficient breeding schemes, the overall understanding of the SI system is crucial as are the mechanisms involved in the breakdown of SI. Self-fertile variants in outcrossing grasses have been studied, and the current level of knowledge includes approximate gene locations, linked molecular markers and first hypotheses on their mode of action. Environmental conditions increasing seed set upon self-pollination have also been described. Even though some strategies were proposed to take advantage of self-fertility, there have, so far, not been changes in the methods applied in cultivar development for allogamous grasses. In this review, we describe the current knowledge about self-fertility in allogamous grasses and outline strategies to incorporate this trait for implementation in synthetic and hybrid breeding schemes.

Motivation: What have we learned and what is still missing?

This final chapter deliberates three overarching topics and conclusions of the research presented in this volume: the endurance of the concept of extrinsic vs intrinsic motivation, the importance of considering subjective costs of activities when aiming to understand and enhance motivation, and current knowledge of the neurobiological underpinnings of motivation. Furthermore, three topics for future motivation research are outlined, namely the assessment and determinants of intrinsic benefits, the reconciliation of activity-specific motivation models with generalized motivation impairments in clinical populations, and the motivational dynamics of groups.

A benefit-cost framework of motivation for a specific activity

How can an individual be motivated to perform a target exercise or activity? This question arises in training, therapeutic, and education settings alike, yet despite-or even because of-the large range of extant motivation theories, finding a clear answer to this question can be challenging. Here we propose an application-friendly framework of motivation for a specific activity or exercise that incorporates core concepts from several well-regarded psychological and economic theories of motivation. The key assumption of this framework is that motivation for performing a given activity is determined by the expected benefits and the expected costs of (performance of) the activity. Benefits comprise positive feelings, gains, and rewards experienced during performance of the activity (intrinsic benefits) or achieved through the activity (extrinsic benefits). Costs entail effort requirements, time demands, and other expenditure (intrinsic costs) as well as unwanted associated outcomes and missing out on alternative activities (extrinsic costs). The expected benefits and costs of a given exercise are subjective and state dependent. We discuss convergence of the proposed framework with a selection of extant motivation theories and briefly outline neurobiological correlates of its main components and assumptions. One particular strength of our framework is that it allows to specify five pathways to increasing motivation for a target exercise, which we illustrate and discuss with reference to previous empirical data.

Increasing self-directed training in neurorehabilitation patients through competition

This proof-of-concept study aimed to test whether competition could be a useful tool to increase intensity and amount of self-directed training in neurorehabilitation. Stroke patients undergoing inpatient neurorehabilitation (n=93) conducted self-directed endurance training on a (wheelchair-compatible) bicycle trainer under three experimental conditions: a "Competition" condition and two noncompetition control conditions (repeated randomized within-subject design). Training performance and perceived exertion were recorded and statistically analyzed. Three motivational effects of competition were found. First, competition led to an increase in self-directed training. Patients exercised significantly more intensively under competition than in the two noncompetition control conditions. Second, (winning a) competition had a positive influence on performance in the subsequent training session. Third, training performance was particularly high during rematch competitions; that is to say, during second encounter competitions against an opponent that the patient had just beaten. No systematic effect of competition upon perceived exertion (controlled for training performance) was found. Together, our results demonstrate that competition is a potent motivational tool to increase self-directed training in neurorehabilitation.