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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. [ABSTRACT FROM AUTHOR]

Despite the progress made in DNA sequencing over the last decade, reconstructing telomere-to-telomere genome assemblies of large and repeat-rich eukaryotic genomes is still difficult. More accurate basecalls or longer reads could address this issue, but no current sequencing platform can provide both simultaneously. Perennial ryegrass (Lolium perenne L.) is an example of an important species for which the lack of a reference genome assembly hindered a swift adoption of genomics-based methods into breeding programs. To fill this gap, we optimized the Oxford Nanopore Technologies' sequencing protocol, obtaining sequencing reads with an N50 of 62 kb—a very high value for a plant sample. The assembly of such reads produced a highly complete (2.3 of 2.7 Gb), correct (QV 45), and contiguous (contig N50 and N90 11.74 and 3.34 Mb, respectively) genome assembly. We show how read length was key in determining the assembly contiguity. Sequence annotation revealed the dominance of transposable elements and repeated sequences (81.6% of the assembly) and identified 38,868 protein coding genes. Almost 90% of the bases could be anchored to seven pseudomolecules, providing the first high-quality haploid reference assembly for perennial ryegrass. This protocol will enable producing longer Oxford Nanopore Technology reads for more plant samples and ushering forage grasses into modern genomics-assisted breeding programs. [ABSTRACT FROM AUTHOR]

Genomic prediction of nitrogen-use efficiency (NUE) has not previously been studied in perennial grass species exposed to low-N stress. Here, we conducted a genomic prediction of physiological traits and NUE in 184 global accessions of perennial ryegrass (Lolium perenne) in response to a normal (7.5 mM) and low (0.75 mM) supply of N. After 21 d of treatment under greenhouse conditions, significant variations in plant height increment (ΔHT), leaf fresh weight (LFW), leaf dry weight (LDW), chlorophyll index (Chl), chlorophyll fluorescence, leaf N and carbon (C) contents, C/N ratio, and NUE were observed in accessions , but to a greater extent under low-N stress. Six genomic prediction models were applied to the data, namely the Bayesian method Bayes C, Bayesian LASSO, Bayesian Ridge Regression, Ridge Regression-Best Linear Unbiased Prediction, Reproducing Kernel Hilbert Spaces, and randomForest. These models produced similar prediction accuracy of traits within the normal or low-N treatments, but the accuracy differed between the two treatments. ΔHT, LFW, LDW, and C were predicted slightly better under normal N with a mean Pearson r -value of 0.26, compared with r =0.22 under low N, while the prediction accuracies for Chl, N, C/N, and NUE were significantly improved under low-N stress with a mean r =0.45, compared with r =0.26 under normal N. The population panel contained three population structures, which generally had no effect on prediction accuracy. The moderate prediction accuracies obtained for N, C, and NUE under low-N stress are promising, and suggest a feasible means by which germplasm might be initially assessed for further detailed studies in breeding programs. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) is a potential pathway to accelerate genetic gain for perennial ryegrass (Lolium perenne L.). The main objectives of the present study were to investigate the level of genetic gain and accuracy by applying GS in commercial perennial ryegrass breeding programs. Different scenarios were compared to a conventional breeding program. Simulated scenarios differed in the method of selection and structure of the breeding program. Two scenarios (Phen-Y12 and Phen) for phenotypic selection and three scenarios (GS-Y12, GS and GS-SP) were considered for genomic breeding schemes. All breeding schemes were simulated for 25 cycles. The amount of genetic gain achieved was different across scenarios. Compared to phenotypic scenarios, GS scenarios resulted in substantially larger genetic gain for the simulated traits. This was mainly due to more efficient selection of plots and single plants based on genomic estimated breeding values. Also, GS allows for reduction in waiting time for the availability of the superior genetic materials from previous cycles, which led to at least a doubling or a trebling of genetic gain compared to the traditional program. Reduction in additive genetic variance levels were higher with GS scenarios than with phenotypic selection. The results demonstrated that implementation of GS in ryegrass breeding is possible and presents an opportunity to make very significant improvements in genetic gains. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Chl breakdown is a hallmark of leaf senescence. Protein degradation is tightly associated with accelerated Chl catabolism during leaf senescence. Therefore, blocking or reducing Chl breakdown and thereby improving Chl and leaf protein contents is desirable for agronomic improvement in perennial forage grasses. Perennial ryegrass (Lolium perenne L.) is one principle cool-season forage grass in temperate areas throughout the world. In this study, the perennial ryegrass STAY-GREEN gene (LpSGR) was cloned and characterized. LpSGR was highly expressed in developmentally or dark-induced senescent leaves. LpSGR was subcellularly localized in chloroplast and interacted with the other Chl catabolic enzymes. RNA interference (RNAi) of LpSGR in perennial ryegrass blocked the degradation of Chl, resulting in increased Chl content and photochemical efficiency in senescent leaves. The RNAi transgenic plants had significantly improved forage quality, with up to 46.1% increased protein content in the harvested biomass. Transcriptome comparison revealed that suppression of LpSGR led to multiple alterations in metabolic pathways in locations inside the chloroplast. Most transcription factors of senescence-associated hormonal signaling pathways (e.g. ABA, ethylene and jasmonic acid) had decreased expression levels in the RNAi plants. These results provided a foundation for the further study on the regulatory mechanism of LpSGR in perennial ryegrass for the purpose of forage improvement with delayed leaf senescence and higher forage quality. [ABSTRACT FROM AUTHOR]

Nitrogen excretion from sheep production systems is an important source of nitrate, ammonia, and nitrous oxide responsible for groundwater pollution and global warming. The present study aimed to identify key parameters influencing N utilization efficiency and develop prediction equations for manure N, feces N, and urine N outputs in sheep. Data used were collected from 82 sheep offered fresh perennial ryegrass (Lolium perenne) as the sole diet in 6 metabolism experiments (data from non-grassonly diets were not used). Sheep were from breeds of Highlander, Texel, Scottish Blackface, and Swaledale at the age of 5 to 18 mo and weighing from 24.5 to 62.7 kg. Herbage was harvested daily from 6 swards of contrasting harvest dates (May to December), offering wide variation in feed value to cover the range that would be offered in most practical farm situations. Before the commencement of each study, the experimental sward was harvested at a residual height of 4 cm and allowed to grow for 2 to 4 wk to target an average pregrazing sward height in a range of 8 to 15 cm depending on the time of year. Sheep were housed in individual pens for 14 d and then transferred to individual metabolism crates for 4 d with feed intake and feces and urine outputs measured. Data were analyzed using the linear mixed model procedure to develop prediction equations for feces N, urine N, and manure N outputs using N intake, herbage chemical composition, and digestibility with effects of sex, breed, and experimental periods removed. Nitrogen intake was the best single predictor for N output in feces, urine, and manure, and the r² value for prediction of manure N output was greater than those for feces N and urine N (0.86 vs. 0.70 and 0.77, respectively; P < 0.001). Animal BW and herbage DM, ether extract, NDF, ADF, water soluble carbohydrate, and DE concentrations and N digestibility were also used to predict N outputs because N intake may not be available in commercial practice. The prediction equations for N utilization efficiency indicated that increasing feeding level and ME concentration and reducing N concentration could improve N utilization efficiency and shift N excretion into feces rather than urine (P < 0.001). The equations developed in the current study provide an approach for sheep producers to quantify N excretion against production and, consequently, to develop their own mitigation strategies to reduce the environmental impact of sheep production systems. [ABSTRACT FROM AUTHOR]

• Background and Aims High density genetic linkage maps that are extensively anchored to assembled genome sequences of the organism in question are extremely useful in gene discovery. To facilitate this process in perennial ryegrass (Lolium perenne L.), a high density single nucleotide polymorphism (SNP)- and presence/absence variant (PAV)-based genetic linkage map has been developed in an F2 mapping population that has been used as a reference population in numerous studies. To provide a reference sequence to which to align genotyping by sequencing (GBS) reads, a shotgun assembly of one of the grandparents of the population, a tenth-generation inbred line, was created using Illumina-based sequencing. • Methods The assembly was based on paired-end Illumina reads, scaffolded by mate pair and long jumping distance reads in the range of 3-40 kb, with >200-fold initial genome coverage. A total of 169 individuals from an F2 mapping population were used to construct PstI-based GBS libraries tagged with unique 4-9 nucleotide barcodes, resulting in 284 million reads, with approx. 1.6 million reads per individual. A bioinformatics pipeline was employed to identify both SNPs and PAVs. A core genetic map was generated using high confidence SNPs, to which lower confidence SNPs and PAVs were subsequently fitted in a straightforward binning approach. • Key Results The assembly comprises 424 750 scaffolds, covering 1.11 Gbp of the 2.5 Gbp perennial ryegrass genome, with a scaffold N50 of 25 212 bp and a contig N50 of 3790 bp. It is available for download, and access to a genome browser has been provided. Comparison of the assembly with available transcript and gene model data sets for perennial ryegrass indicates that approx. 570 Mbp of the gene-rich portion of the genome has been captured. An ultra-high density genetic linkage map with 3092 SNPs and 7260 PAVs was developed, anchoring just over 200Mb of the reference assembly. • Conclusions The combined genetic map and assembly, combined with another recently released genome assembly, represent a significant resource for the perennial ryegrass genetics community. [ABSTRACT FROM AUTHOR]

This study investigated successional colonization of fresh perennial ryegrass (PRG) by the rumen microbiota over time. Fresh PRG was incubated in sacco in the rumens of three Holstein × Friesian cows over a period of 8 h, with samples recovered at various times. The diversity of attached bacteria was assessed using 454 pyrosequencing of 16S rRNA (cDNA). Results showed that plant epiphytic communities either decreased to low relative abundances or disappeared following rumen incubation, and that temporal colonization of the PRG by the rumen bacteria was biphasic with primary (1 and 2 h) and secondary (4-8 h) events evident with the transition period being with 2-4 h. A decrease in sequence reads pertaining to Succinivibrio spp. and increases in Pseudobutyrivibrio, Roseburia and Ruminococcus spp. (the latter all order Clostridiales) were evident during secondary colonization. Irrespective of temporal changes, the continually high abundances of Butyrivibrio, Fibrobacter, Olsenella and Prevotella suggest that they play a major role in the degradation of the plant. It is clear that a temporal understanding of the functional roles of these microbiota within the rumen is now required to unravel the role of these bacteria in the ruminal degradation of fresh PRG. [ABSTRACT FROM AUTHOR]

We have developed a new methodology to assess individual perennial ryegrass plant performance under moisture stress and identified QTLs associated with improved performance during drought in this important forage species.Periodic drought events present a significant and, with climate change, increasing constraint on temperate forage plants’ production. Consequently, improving plants’ adaptive response to abiotic stress is a key goal to ensure agricultural productivity in these regions. In this study we developed a new methodology, using both area-based comparison and soil water content measurements of individual non-irrigated and irrigated clones, to assess performance of perennial ryegrass (Lolium perenne L.) genotypes subjected to moisture stress in a simulated competitive environment. We applied this method to the evaluation of a full-sibling population from a pair cross between genotypes from a New Zealand cultivar and a Moroccan ecotype. Our hypothesis was that: (i) both leaf lamina regrowth after defoliation (LR) and plant vigour affect plant performance during drought and rehydration; and (ii) quantitative trait loci (QTLs) associated with plant performance under moisture stress could be identified. Differences amongst genotypes in dry matter (DM) production, early vigour at establishment, leaf elongation rate and LR were measured. LR explained most of the variation in DM production during exposure to moisture deficit and rehydration followed by plant vigour, indicated by initial DM production in both treatments and subsequent measures of DM production of irrigated clones. We identified two main QTL regions associated with DM production and LR, both during drought exposure and rehydration. Further research focused on these regions should improve our understanding of the genetic control of drought response in this forage crop and potentially other grass species with significant synteny, and support improvement in performance through molecular breeding approaches. [ABSTRACT FROM AUTHOR]

Background and Aims There are many unresolved issues concerning the biochemistry of fructan biosynthesis. The aim of this paper is to address some of these by means of modelling mathematically the biochemical processes. Methods A model has been constructed for the step-by-step synthesis of fructan polymers. This is run until a steady state is achieved for which a polymer distribution is predicted. It is shown how qualitatively different distributions can be obtained. Key Results It is demonstrated how a set of experimental results on polymer distribution can by simulated by a simple parameter adjustments. Conclusions Mathematical modelling of fructan biosynthesis can provide a useful tool for helping elucidate the details of the biosynthetic processes. [ABSTRACT FROM PUBLISHER]

Tall fescue [Lolium arundinaceum (Schreb.) Darbysh. syn. Festuca arundinacea Schreb.] and perennial ryegrass (Lolium perenne L.) are impor-tant perennial forage grasses utilized throughout the moderate- to high-rainfall temperate zones of the world. These grasses have coevolved with symbiotic fungal endophytes (Epichloe/Neotyphodium spp.) that can impart bioactive properties and environmental stress tolerance to the grass compared with endophyte-free individuals. These endophytes have proven to be very important in pastoral agriculture in the United States, New Zealand, and Australia, where forage grasses are the principal feed for grazing ruminants. In this review, we describe the biology of these grass-endophyte associations and implications for the livestock indus-tries that are dependent on these forages. Endophyte alkaloid production is put in context with endophyte diversity, and we illustrate how this has facilitated uti-lization of grasses infected with different endophyte strains that reduce livestock toxicity issues. Utilization of tall fescue and use of perennial ryegrass in the United States, New Zealand, and Australia are compared, and management strategies focused predominantly on the success of endophyte-infected perennial ryegrass in New Zealand and Australia are discussed. In addition, we consider the impact of grass-endophyte associations on the sustainability of pasture ecosystems and their likely response to future changes in climate. [ABSTRACT FROM AUTHOR]

This study tested the hypotheses that: (i) genetic variation in Rubisco turnover may exist in perennial ryegrass (Lolium perenne L.); (ii) such variation might affect nitrogen use efficiency and plant yield; and (iii) genetic control of Rubisco turnover might be amenable to identification by quantitative trait loci (QTL) mapping. A set of 135 full-sib F1 perennial ryegrass plants derived from a pair cross between genotypes from the cultivars ‘Grasslands Impact’ and ‘Grasslands Samson’ was studied to test these hypotheses. Leaf Rubisco concentration at different leaf ages was measured and modelled as a log-normal curve described by three mathematical parameters: D (peak Rubisco concentration), G (time of D), and F (curve standard deviation). Herbage dry matter (DM) yield and morphological traits (tiller weight (TW), tiller number (TN), leaf lamina length (LL), and an index of competitive ability (PI)) were also measured. The progeny exhibited continuous variation for all traits. Simple correlation and principal component analyses indicated that plant productivity was associated with peak Rubisco concentration and not Rubisco turnover. Lower DM was associated with higher leaf Rubisco concentration indicating that Rubisco turnover effects on plant productivity may relate to energy cost of Rubisco synthesis rather than photosynthetic capacity. QTL detection by a multiple QTL model identified seven significant QTL for Rubisco turnover and nine QTL for DM and morphological traits. An indication of the genetic interdependence of DM and the measures of Rubisco turnover was the support interval overlap involving QTL for D and QTL for TN on linkage group 5 in a cluster involving QTL for DM and PI. In this region, alleles associated with increased TN, DM, and PI were associated with decreased D, indicating that this region may regulate Rubisco concentration and plant productivity via increased tillering. A second cluster involving QTL for LL, TN, PI and DM was found on linkage group 2. The two clusters represent marker-trait associations that might be useful for marker-assisted plant breeding applications. In silico comparative analysis indicated conservation of the genetic loci controlling Rubisco concentration in perennial ryegrass and rice. [ABSTRACT FROM AUTHOR]

Background and Scope Self-incompatibility (SI) in flowering plants ensures the maintenance of genetic diversity by ensuring outbreeding. Different genetic and mechanistic systems of SI among flowering plants suggest either multiple origins of SI or considerable evolutionary diversification. In the grasses, SI is based on two loci, S and Z, which are both polyallelic: an incompatible reaction occurs only if both S and Z alleles are matched in individual pollen with alleles of the pistil on which they alight. Such incompatibility is referred to as gametophytic SI (GSI). The mechanics of grass GSI is poorly understood relative to the well-characterized S-RNase-based single-locus GSI systems (Solanaceae, Rosaceae, Plantaginaceae), or the Papaver recognition system that triggers a calcium-dependent signalling network culminating in programmed cell death. There is every reason to suggest that the grass SI system represents yet another mechanism of SI. S and Z loci have been mapped using isozymes to linkage groups C1 and C2 of the Triticeae consensus maps in Secale, Phalaris and Lolium. Recently, in Lolium perenne, in order to finely map and identify S and Z, more closely spaced markers have been developed based on cDNA and repeat DNA sequences, in part from genomic regions syntenic between the grasses. Several genes tightly linked to the S and Z loci were identified, but so far no convincing candidate has emerged. Research and Progress From subtracted Lolium immature stigma cDNA libraries derived from S and Z genotyped individuals enriched for SI potential component genes, kinase enzyme domains, a calmodulin-dependent kinase and a peptide with several calcium (Ca2+) binding domains were identified. Preliminary findings suggest that Ca2+ signalling and phosphorylation may be involved in Lolium GSI. This is supported by the inhibition of Lolium SI by Ca2+ channel blockers lanthanum (La3+) and verapamil, and by findings of increased phosphorylation activity during an SI response. [ABSTRACT FROM PUBLISHER]