Summary: Here we report the draft genome sequence of perennial ryegrass (Lolium perenne), an economically important forage and turf grass species that is widely cultivated in temperate regions worldwide. It is classified along with wheat, barley, oats and Brachypodium distachyon in the Pooideae sub‐family of the grass family (Poaceae). Transcriptome data was used to identify 28 455 gene models, and we utilized macro‐co‐linearity between perennial ryegrass and barley, and synteny within the grass family, to establish a synteny‐based linear gene order. The gametophytic self‐incompatibility mechanism enables the pistil of a plant to reject self‐pollen and therefore promote out‐crossing. We have used the sequence assembly to characterize transcriptional changes in the stigma during pollination with both compatible and incompatible pollen. Characterization of the pollen transcriptome identified homologs to pollen allergens from a range of species, many of which were expressed to very high levels in mature pollen grains, and are potentially involved in the self‐incompatibility mechanism. The genome sequence provides a valuable resource for future breeding efforts based on genomic prediction, and will accelerate the development of new varieties for more productive grasslands.

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.

Genotyping-by-Sequencing (GBS) is an excellent tool for characterising genetic variation between plant genomes. To date, its use has been reported only for genotyping of single individuals. However, there are many applications where resolving allele frequencies within populations on a genome-wide scale would be very powerful, examples include the breeding of outbreeding species, varietal protection in outbreeding species, monitoring changes in population allele frequencies. This motivated us to test the potential to use GBS to evaluate allele frequencies within populations. Perennial ryegrass is an outbreeding species, and breeding programs are based upon selection on populations. We tested two restriction enzymes for their efficiency in complexity reduction of the perennial ryegrass genome. The resulting profiles have been termed Genome Wide Allele Frequency Fingerprints (GWAFFs), and we have shown how these fingerprints can be used to distinguish between plant populations. Even at current costs and throughput, using sequencing to directly evaluate populations on a genome-wide scale is viable. GWAFFs should find many applications, from varietal development in outbreeding species right through to playing a role in protecting plant breeders’ rights.

Advanced phenotyping, i.e. the application of automated, high-throughput methods to characterize plant architecture and performance, has the potential to accelerate breeding progress but is far from being routinely used in current breeding approaches. In forage and turf improvement programmes, in particular, where breeding populations and cultivars are characterized by high genetic diversity and substantial genotype × environment interactions, precise and efficient phenotyping is essential to meet future challenges imposed by climate change, growing demand and declining resources. This review highlights recent achievements in the establishment of phenotyping tools and platforms. Some of these tools have originally been established in remote sensing, some in precision agriculture, while others are laboratory-based imaging procedures. They quantify plant colour, spectral reflection, chlorophyll-fluorescence, temperature and other properties, from which traits such as biomass, architecture, photosynthetic efficiency, stomatal aperture or stress resistance can be derived. Applications of these methods in the context of forage and turf breeding are discussed. Progress in cutting-edge molecular breeding tools is beginning to be matched by progress in automated non-destructive imaging methods. Joint application of precise phenotyping machinery and molecular tools in optimized breeding schemes will improve forage and turf breeding in the near future and will thereby contribute to amended performance of managed grassland agroecosystems.

Proanthocyanidins (PAs) in sainfoin (Onobrychis viciifolia Scop.) are of interest to ameliorate the sustainability of livestock production. However, sainfoin forage yield and PA concentrations, as well as their composition, require optimization. Individual plants of 27 sainfoin accessions from four continents were analyzed with LC-ESI-QqQ-MS/MS for PA concentrations and simple phenolic compounds. Large variability existed in PA concentrations (23.0–47.5 mg g^–1 leaf dry matter (DM)), share of prodelphinidins (79–96%), and mean degree of polymerization (11–14) among, but also within, accessions. PAs were mainly located in leaves (26.8 mg g^–1 DM), whereas stems had less PAs (7.8 mg g^–1 DM). Overall, high-yielding plants had lower PA leaf concentrations (R² = 0.16, P < 0.001) and fewer leaves (R² = 0.66, P < 0.001). However, the results show that these two trade-offs between yield and bioactive PAs can be overcome.

The grass family (Poaceae), the fourth largest family of flowering plants, encompasses the most economically important cereal, forage and energy crops, and exhibits a unique gametophytic self-incompatibility (SI) mechanism that is controlled by at least two multi-allelic and independent loci, S and Z. Despite intense research efforts over the last six decades, the genes underlying S and Z remain uncharacterised.