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Background: Drought resistance is a complex characteristic closely related to the severity and duration of stress. Perennial ryegrass (Lolium perenne L.) has no distinct drought tolerance but often encounters drought stress seasonally. Although the response of perennial ryegrass to either extreme or moderate drought stress has been investigated, a comprehensive understanding of perennial ryegrass response to both conditions of drought stress is currently lacking. Results: In this study, we investigated the genetic variation in drought resistance in 18 perennial ryegrass varieties under both extreme and moderate drought conditions. The performance of these varieties exhibited obvious diversity, and the survival of perennial ryegrass under severe stress was not equal to good growth under moderate drought stress. 'Sopin', with superior performance under both stress conditions, was the best-performing variety. Transcriptome, physiological, and molecular analyses revealed that 'Sopin' adapted to drought stress through multiple sophisticated mechanisms. Under stress conditions, starch and sugar metabolic enzymes were highly expressed, while CslA was expressed at low levels in 'Sopin', promoting starch degradation and soluble sugar accumulation. The expression and activity of superoxide dismutase were significantly higher in 'Sopin', while the activity of peroxidase was lower, allowing for 'Sopin' to maintain a better balance between maintaining ROS signal transduction and alleviating oxidative damage. Furthermore, drought stress-related transcriptional and posttranscriptional regulatory mechanisms, including the upregulation of transcription factors, kinases, and E3 ubiquitin ligases, facilitate abscisic acid and stress signal transduction. Conclusion: Our study provides insights into the resistance of perennial ryegrass to both extreme and moderate droughts and the underlying mechanisms by which perennial ryegrass adapts to drought conditions. [ABSTRACT FROM AUTHOR]

Cadmium (Cd) and arsenic (As) exist simultaneously in soil environment, which poses a serious threat to the safety of agricultural products and forage production. Four Perennial Ryegrass (Lolium perenne L.) cultivars with different accumulation characteristics (ʻNicaraguaʼ, ʻVenusʼ, ʻExcellentʼ and ʻMonroʼ) were selected as the material for pot experiment. The coupled responses of key components and related enzyme activities under combined stresses of Cd and As were investigated. key components contents include Non protein sulfhydryl (NPT), glutathione (GSH) and phytochelatins (PCs). The related enzyme includes (superoxide dismutase (SOD), peroxidase (POD), catalase (CAT), γ-glutamylcysteine synthetase (γ-ECS), glutathione synthetase (GSS), phytochelatin synthetases (PCSase) and arsenate reductase (AR). The results showed that Cd contents of perennial ryegrass were higher than those of As contents with TFCd/As < 1. Cd and As contents in roots were in the higher proportion than those in shoots. Compared to control, POD activities increased by 2.72 folds under 120 mg kg−1 As treatment. The contents of PCs increased by 5.68 folds under 120 mg kg−1 As treatment. Under combined Cd and As stress, the MDA contents and antioxidant enzyme activities of ʻVenusʼ were higher than those of ʻNicaraguaʼ. ʻNicaraguaʼ, a high accumulation cultivar. Under the combined stresses of Cd and As, the enzyme activities and the key components were significantly correlated (P < 0.05) with the contents of Cd and As. The tolerance to Cd and As was improved with increase in GSH and PCs contents and γ-ECS, GSS, PCSase and AR activities. In conclusion, the antioxidant enzyme system and key resistant substances of perennial ryegrass have important and antagonistic effects on Cd and As stresses. [ABSTRACT FROM AUTHOR]

Background: The unambiguous identification of individual chromosomes is a key part of the genomic characterization of any species. In this respect, the development and application of chromosome banding techniques has revolutionised mammalian and especially, human genomics. However, partly because of the traditional use of chromosome squash preparations, consistent fluorescence banding has rarely been achieved in plants. Here, successful fluorescence chromosome banding has been achieved for the first time in perennial ryegrass (Lolium perenne), a forage and turf grass with a large genome and a symmetrical karyotype with chromosomes that are difficult to distinguish. Results: Based on flame-dried chromosome preparations instead of squashes, a simple fluorescence Q-banding technique using quinacrine mustard, unambiguously identified each chromosome and enabled the development of a banded karyotype and ideogram of the species. This Q-banding technique was also shown to be compatible with sequential FISH mapping enabling labelled genes and molecular markers to be precisely assigned to specific cytogenetic bands. A technique for DAPI-banding, which gave a similar pattern to Q-banding, was also introduced. This was compatible with FISH mapping and was used to anchor a single copy gene from an earlier mapped linkage group of L. perenne, thus providing a step towards integration of the genetic and cytogenetic maps. Conclusions: By enabling the allocation of genes mapped by other methods to physically identified chromosome positions, this work will contribute to a better understanding of genomic structures and functions in grasses. [ABSTRACT FROM AUTHOR]

Background: Heading and aftermath heading are important traits in perennial ryegrass because they impact forage quality. So far, genome-wide association analyses in this major forage species have only identified a small number of genetic variants associated with heading date that overall explained little of the variation. Some possible reasons include rare alleles with large phenotypic affects, allelic heterogeneity, or insufficient marker density. We established a genome-wide association panel with multiple genotypes from multiple full-sib families. This ensured alleles were present at the frequency needed to have sufficient statistical power to identify associations. We genotyped the panel via partial genome sequencing and performed genome-wide association analyses with multi-year phenotype data collected for heading date, and aftermath heading. Results: Genome wide association using a mixed linear model failed to identify any variants significantly associated with heading date or aftermath heading. Our failure to identify associations for these traits is likely due to the extremely low linkage disequilibrium we observed in this population. However, using single marker analysis within each full-sib family we could identify markers and genomic regions associated with heading and aftermath heading. Using the ryegrass genome we identified putative orthologs of key heading genes, some of which were located in regions of marker-trait associations. Conclusion: Given the very low levels of LD, genome wide association studies in perennial ryegrass populations are going to require very high SNP densities. Single marker analysis within full-sibs enabled us to identify significant marker-trait associations. One of these markers anchored proximal to a putative ortholog of TFL1, homologues of which have been shown to play a key role in continuous heading of some members of the rose family, Rosaceae. [ABSTRACT FROM AUTHOR]

Background: Genomic selection (GS) has become a commonly used technology in animal breeding. In crops, it is expected to significantly improve the genetic gains per unit of time. So far, its implementation in plant breeding has been mainly investigated in species farmed as homogeneous varieties. Concerning crops farmed in family pools, only a few theoretical studies are currently available. Here, we test the opportunity to implement GS in breeding of perennial ryegrass, using real data from a forage breeding program. Heading date was chosen as a model trait, due to its high heritability and ease of assessment. Genome Wide Association analysis was performed to uncover the genetic architecture of the trait. Then, Genomic Prediction (GP) models were tested and prediction accuracy was compared to the one obtained in traditional Marker Assisted Selection (MAS) methods. Results: Several markers were significantly associated with heading date, some locating within or proximal to genes with a well-established role in floral regulation. GP models gave very high accuracies, which were significantly better than those obtained through traditional MAS. Accuracies were higher when predictions were made from related families and from larger training populations, whereas predicting from unrelated families caused the variance of the estimated breeding values to be biased downwards. Conclusions: We have demonstrated that there are good perspectives for GS implementation in perennial ryegrass breeding, and that problems resulting from low linkage disequilibrium (LD) can be reduced by the presence of structure and related families in the breeding population. While comprehensive Genome Wide Association analysis is difficult in species with extremely low LD, we did identify variants proximal to genes with a known role in flowering time (e.g. CONSTANS and Phytochrome C). [ABSTRACT FROM AUTHOR]

Background: Identification of genetic diversity in heat tolerance and associated traits is of great importance for improving heat tolerance in cool-season grass species. The objectives of this study were to determine genetic variations in heat tolerance associated with phenotypic and physiological traits and to identify molecular markers associated with heat tolerance in a diverse collection of perennial ryegrass (Lolium perenne L.). Results: Plants of 98 accessions were subjected to heat stress (35/30 °C, day/night) or optimal growth temperature (25/20 °C) for 24 d in growth chambers. Overall heat tolerance of those accessions was ranked by principal component analysis (PCA) based on eight phenotypic and physiological traits. Among these traits, electrolyte leakage (EL), chlorophyll content (Chl), relative water content (RWC) had high correlation coefficients (− 0.858, 0.769, and 0.764, respectively) with the PCA ranking of heat tolerance. We also found expression levels of four Chl catabolic genes (CCGs), including LpNYC1, LpNOL, LpSGR, and LpPPH, were significant higher in heat sensitive ryegrass accessions then heat tolerant ones under heat stress. Furthermore, 66 pairs of simple sequence repeat (SSR) markers were used to perform association analysis based on the PCA result. The population structure of ryegrass can be grouped into three clusters, and accessions in cluster C were relatively more heat tolerant than those in cluster A and B. SSR markers significantly associated with above-mentioned traits were identified (R2 > 0.05, p < 0.01)., including two pairs of markers located on chromosome 4 in association with Chl content and another four pairs of markers in association with EL. Conclusion: The result not only identified useful physiological parameters, including EL, Chl content, and RWC, and their associated SSR markers for heat-tolerance breeding of perennial ryegrass, but also highlighted the involvement of Chl catabolism in ryegrass heat tolerance. Such knowledge is of significance for heat-tolerance breeding and heat tolerance mechanisms in perennial ryegrass as well as in other cool-season grass species. [ABSTRACT FROM AUTHOR]

Background: In-field measurement of yield and growth rate in pasture species is imprecise and costly, limiting scientific and commercial application. Our study proposed a LiDAR-based mobile platform for non-invasive vegetative biomass and growth rate estimation in perennial ryegrass (Lolium perenne L.). This included design and build of the platform, development of an algorithm for volumetric estimation, and field validation of the system. The LiDAR-based volumetric estimates were compared against fresh weight and dry weight data across different ages of plants, seasons, stages of regrowth, sites, and row configurations. Results: The project had three phases, the last one comprising four experiments. Phase 1: a LiDAR-based, field-ready prototype mobile platform for perennial ryegrassrecognition in single row plots was developed. Phase 2: real-time volumetric data capture, modelling and analysis software were developed and integrated and the resultant algorithm was validated in the field. Phase 3. LiDAR Volume data were collected via the LiDAR platform and field-validated in four experiments. Expt.1: single-row plots of cultivars and experimental diploid breeding populations were scanned in the southern hemisphere spring for biomass estimation. Significant (P < 0.001) correlations were observed between LiDAR Volume and both fresh and dry weight data from 360 individual plots (R2 = 0.89 and 0.86 respectively). Expt 2: recurrent scanning of single row plots over long time intervals of a few weeks was conducted, and growth was estimated over an 83 day period. Expt 3: recurrent scanning of single-row plots over nine short time intervals of 2 to 5 days was conducted, and growth rate was observed over a 26 day period. Expt 4: recurrent scanning of paired-row plots over an annual cycle of repeated growth and defoliation was conducted, showing an overall mean correlation of LiDAR Volume and fresh weight of R2 = 0.79 for 1008 observations made across seven different harvests between March and December 2018. Conclusions: Here we report development and validation of LiDAR-based volumetric estimation as an efficient and effective tool for measuring fresh weight, dry weight and growth rate in single and paired-row plots of perennial ryegrass for the first time, with a consistently high level of accuracy. This development offers precise, non-destructive and cost-effective estimation of these economic traits in the field for ryegrass and potentially other pasture grasses in the future, based on the platform and algorithm developed for ryegrass. [ABSTRACT FROM AUTHOR]

Background: Genomic selection (GS) can accelerate genetic gains in breeding programmes by reducing the time it takes to complete a cycle of selection. Puccinia coronata f. sp lolli (crown rust) is one of the most widespread diseases of perennial ryegrass and can lead to reductions in yield, persistency and nutritional value. Here, we used a large perennial ryegrass population to assess the accuracy of using genome wide markers to predict crown rust resistance and to investigate the factors affecting predictive ability. Results: Using these data, predictive ability for crown rust resistance in the complete population reached a maximum of 0.52. Much of the predictive ability resulted from the ability of markers to capture genetic relationships among families within the training set, and reducing the marker density had little impact on predictive ability. Using permutation based variable importance measure and genome wide association studies (GWAS) to identify and rank markers enabled the identification of a small subset of SNPs that could achieve predictive abilities close to those achieved using the complete marker set. Conclusion: Using a GWAS to identify and rank markers enabled a small panel of markers to be identified that could achieve higher predictive ability than the same number of randomly selected markers, and predictive abilities close to those achieved with the entire marker set. This was particularly evident in a sub-population characterised by having on-average higher genome-wide linkage disequilibirum (LD). Higher predictive abilities with selected markers over random markers suggests they are in LD with QTL. Accuracy due to genetic relationships will decay rapidly over generations whereas accuracy due to LD will persist, which is advantageous for practical breeding applications. [ABSTRACT FROM AUTHOR]