Traits In Perennial Ryegrass Research Articles

Developing an integrated genomic selection approach beyond biomass for varietal protection and nutritive traits in perennial ryegrass (Lolium perenne L.)

Key messageBreeding target traits can be broadened to include nutritive value and plant breeder’s rights traits in perennial ryegrass by using in-field regression-based spectroscopy phenotyping and genomic selection.Perennial ryegrass breeding has focused on biomass yield, but expansion into a broader set of traits is needed to benefit livestock industries whilst also providing support for intellectual property protection of cultivars. Numerous breeding objectives can be targeted simultaneously with the development of sensor-based phenomics and genomic selection (GS). Of particular interest are nutritive value (NV), which has been difficult and expensive to measure using traditional phenotyping methods, resulting in limited genetic improvement to date, and traits required to obtain varietal protection, known as plant breeder’s rights (PBR) traits. In order to assess phenotyping requirements for NV improvement and potential for genetic improvement, in-field reflectance-based spectroscopy was assessed and GS evaluated in a single population for three key NV traits, captured across four timepoints. Using three prediction approaches, the possibility of targeting PBR traits using GS was evaluated for five traits recorded across three years of a breeding program. Prediction accuracy was generally low to moderate for NV traits and moderate to high for PBR traits, with heritability highly correlated with GS accuracy. NV did not show significant or consistent correlation between timepoints highlighting the need to incorporate seasonal NV into selection indexes and the value of being able to regularly monitor NV across seasons. This study has demonstrated the ability to implement GS for both NV and PBR traits in perennial ryegrass, facilitating the expansion of ryegrass breeding targets to agronomically relevant traits while ensuring necessary varietal protection is achieved.

Relative importance of genotype, gene expression, and DNA methylation on complex traits in perennial ryegrass.

The growing demand for food and feed crops in the world because of growing population and more extreme weather events requires high-yielding and resilient crops. Many agriculturally important traits are polygenic, controlled by multiple regulatory layers, and with a strong interaction with the environment. In this study, 120 F2 families of perennial ryegrass (Lolium perenne L.) were grown across a water gradient in a semifield facility with subsoil irrigation. Genomic (single-nucleotide polymorphism [SNP]), transcriptomic (gene expression [GE]), and DNA methylomic (MET) data were integrated with feed quality trait data collected from control and drought sections in the semifield facility, providing a treatment effect. Deep root length (DRL) below 110 cm was assessed with convolutional neural network image analysis. Bayesian prediction models were used to partition phenotypic variance into its components and evaluated the proportion of phenotypic variance in all traits captured by different regulatory layers (SNP, GE, and MET). The spatial effects and effects of SNP, GE, MET, the interaction between GE and MET (GE × MET) and GE× treatment (GEControl and GEDrought ) interaction were investigated. Gene expression explained a substantial part of the genetic and spatial variance for all the investigated phenotypes, whereas MET explained residual variance not accounted for by SNPs or GE. For DRL, MET also contributed to explaining spatial variance. The study provides a statistically elegant analytical paradigm that integrates genomic, transcriptomic, and MET information to understand the regulatory mechanisms of polygenic effects for complex traits.

NOL-mediated functional stay-green traits in perennial ryegrass (Lolium perenne L.) involving multifaceted molecular factors and metabolic pathways regulating leaf senescence.

Loss of chlorophyll (Chl) is a hallmark of leaf senescence, which may be regulated by Chl catabolic genes, including NON-YELLOW COLORING 1 (NYC1)-like (NOL). The objective of this study was to determine molecular factors and metabolic pathways underlying NOL regulation of leaf senescence in perennial grass species. LpNOL was cloned from perennial ryegrass (Lolium perenne L.) and found to be highly expressed in senescent leaves. Transient overexpression of LpNOL accelerated leaf senescence and Chl b degradation in Nicotiana benthamiana. LpNOL RNA interference (NOLi) in perennial ryegrass not only significantly blocked Chl degradation in senescent leaves, but also delayed initiation and progression of leaf senescence. This study found that NOL, in addition to functioning as a Chl b reductase, could enact the functional stay-green phenotype in perennial grass species, as manifested by increased photosynthetic activities in NOLi plants. Comparative transcriptomic analysis revealed that NOL-mediated functional stay-green in perennial ryegrass was mainly achieved through the modulation of Chl catabolism, light harvesting for photosynthesis, photorespiration, cytochrome respiration, carbohydrate catabolism, oxidative detoxification, and abscisic acid biosynthesis and signaling pathways.

Genomic Predictive Ability for Foliar Nutritive Traits in Perennial Ryegrass.

Forage nutritive value impacts animal nutrition, which underpins livestock productivity, reproduction and health. Genetic improvement for nutritive traits in perennial ryegrass has been limited, as they are typically expensive and time-consuming to measure through conventional methods. Genomic selection is appropriate for such complex and expensive traits, enabling cost-effective prediction of breeding values using genome-wide markers. The aims of the present study were to assess the potential of genomic selection for a range of nutritive traits in a multi-population training set, and to quantify contributions of family, location and family-by-location variance components to trait variation and heritability for nutritive traits. The training set consisted of a total of 517 half-sibling (half-sib) families, from five advanced breeding populations, evaluated in two distinct New Zealand grazing environments. Autumn-harvested samples were analyzed for 18 nutritive traits and maternal parents of the half-sib families were genotyped using genotyping-by-sequencing. Significant (P < 0.05) family variance was detected for all nutritive traits and genomic heritability (h2g) was moderate to high (0.20 to 0.74). Family-by-location interactions were significant and particularly large for water soluble carbohydrate (WSC), crude fat, phosphorus (P) and crude protein. GBLUP, KGD-GBLUP and BayesCπ genomic prediction models displayed similar predictive ability, estimated by 10-fold cross validation, for all nutritive traits with values ranging from r = 0.16 to 0.45 using phenotypes from across two locations. High predictive ability was observed for the mineral traits sulfur (0.44), sodium (0.45) and magnesium (0.45) and the lowest values were observed for P (0.16), digestibility (0.22) and high molecular weight WSC (0.23). Predictive ability estimates for most nutritive traits were retained when marker number was reduced from one million to as few as 50,000. The moderate to high predictive abilities observed suggests implementation of genomic selection is feasible for most of the nutritive traits examined.

Exploitation of data from breeding programs supports rapid implementation of genomic selection for key agronomic traits in perennial ryegrass

Key messageExploitation of data from a ryegrass breeding program has enabled rapid development and implementation of genomic selection for sward-based biomass yield with a twofold-to-threefold increase in genetic gain.Genomic selection, which uses genome-wide sequence polymorphism data and quantitative genetics techniques to predict plant performance, has large potential for the improvement in pasture plants. Major factors influencing the accuracy of genomic selection include the size of reference populations, trait heritability values and the genetic diversity of breeding populations. Global diversity of the important forage species perennial ryegrass is high and so would require a large reference population in order to achieve moderate accuracies of genomic selection. However, diversity of germplasm within a breeding program is likely to be lower. In addition, de novo construction and characterisation of reference populations are a logistically complex process. Consequently, historical phenotypic records for seasonal biomass yield and heading date over a 18-year period within a commercial perennial ryegrass breeding program have been accessed, and target populations have been characterised with a high-density transcriptome-based genotyping-by-sequencing assay. Ability to predict observed phenotypic performance in each successive year was assessed by using all synthetic populations from previous years as a reference population. Moderate and high accuracies were achieved for the two traits, respectively, consistent with broad-sense heritability values. The present study represents the first demonstration and validation of genomic selection for seasonal biomass yield within a diverse commercial breeding program across multiple years. These results, supported by previous simulation studies, demonstrate the ability to predict sward-based phenotypic performance early in the process of individual plant selection, so shortening the breeding cycle, increasing the rate of genetic gain and allowing rapid adoption in ryegrass improvement programs.

An Immortalized Genetic Mapping Population for Perennial Ryegrass: A Resource for Phenotyping and Complex Trait Mapping.

To address the lack of a truly portable, universal reference mapping population for perennial ryegrass, we have been developing a recombinant inbred line (RIL) mapping population of perennial ryegrass derived via single seed descent from a well-characterized F2 mapping population based on genetically distinct inbred parents in which the natural self-incompatibility (SI) system of perennial ryegrass has been overcome. We examined whether it is possible to create a genotyping by sequencing (GBS) based genetic linkage map in a small population of the F6 generation of this population. We used 41 F6 genotypes for GBS with PstI/MspI-based libraries. We successfully developed a genetic linkage map comprising 6074 SNP markers, placing a further 22080 presence and absence variation (PAV) markers on the map. We examined the resulting genetic map for general and RIL specific features. Overall segregation distortion levels were similar to those experienced in the F2 generation, but segregation distortion was reduced on linkage group 6 and increased on linkage group 7. Residual heterozygosity in the F6 generation was observed at a level of 5.4%. There was a high proportion of chromosomes (30%) exhibiting the intact haplotype of the original inbred parents of the F1 genotype from which the population is derived, pointing to a tendency for chromosomes to assort without recombining. This could affect the applicability of these lines and might make them more suitable for situations where repressed recombination is an advantage. Inter- and intra-chromosomal linkage disequilibrium (LD) analysis suggested that the map order was robust. We conclude that this RIL population, and subsequent F7 and F8 generations will be useful for genetic analysis and phenotyping of agronomic and biological important traits in perennial ryegrass.

Markers associated with heading and aftermath heading in perennial ryegrass full-sib families

BackgroundHeading 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.ResultsGenome 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.ConclusionGiven 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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12870-016-0844-y) contains supplementary material, which is available to authorized users.

Using a Candidate Gene-Based Genetic Linkage Map to Identify QTL for Winter Survival in Perennial Ryegrass.

Important agronomical traits in perennial ryegrass (Lolium perenne) breeding programs such as winter survival and heading date, are quantitative traits that are generally controlled by multiple loci. Individually, these loci have relatively small effects. The aim of this study was to develop a candidate gene based Illumina GoldenGate 1,536-plex assay, containing single nucleotide polymorphism markers designed from transcripts involved in response to cold acclimation, vernalization, and induction of flowering. The assay was used to genotype a mapping population that we have also phenotyped for winter survival to complement the heading date trait previously mapped in this population. A positive correlation was observed between strong vernalization requirement and winter survival, and some QTL for winter survival and heading date overlapped on the genetic map. Candidate genes were located in clusters along the genetic map, some of which co-localized with QTL for winter survival and heading date. These clusters of candidate genes may be used in candidate gene based association studies to identify alleles associated with winter survival and heading date.

Cultivar by environment effects of perennial ryegrass cultivars selected for high water soluble carbohydrates managed under differing precipitation levels

Historic results of perennial ryegrass (Lolium perenne L.) breeding include improved disease resistance, biomass, and nutritional quality. Yet, lack of tolerance to water stress limits its wide use. Recent efforts to increase water soluble carbohydrate (WSC) content in perennial ryegrass may increase drought tolerance. Herein, we report results of a multi-year and location evaluation of differing precipitation/irrigations levels on genetic and genotype × environment interaction effects of various agronomic traits in perennial ryegrass. The study included two UK environments (Aberystwyth, Wales and Edinburgh, Scotland) and four USA environments located in Logan, UT and consisting in four supplemental irrigation levels in a line-source irrigation design. Data included herbage dry matter, dry matter digestibility, crude protein, and WSC, collected from 2011 to 2013. There were differences (P < 0.05) among the included cultivars for each phenotype when evaluated across environments. There was observed cultivar × environment interaction for each phenotype, which precluded the identification of the best cultivar over all environments. Additive main effect and multiplicative interaction modeling allowed for grouping of the individual environments to mega-environments. The analysis identified three mega-environments for each phenotype: (1) the UK environments, (2) the two highest Logan irrigation levels, and (3) the two lowest Logan irrigation levels. Mega-environments designations corresponded to water stress, temperature, and inherent geographic/climate differences between the environments. The evidence for the potential of increased WSC to improve drought tolerance under water stress was inconclusive, but high WSC cultivars also exhibited high herbage production under the imposed water stress.

Higher energy concentration traits in perennial ryegrass (Lolium perenne L.) may increase profitability and improve energy conversion on dairy farms

The effect of improving energy concentration of pasture dry matter (DM) in perennial ryegrass (Lolium perenne L.) on two dairy farms in temperate regions (south west Victoria and Tasmania) of Australia was modeled in this study. A deterministic, dynamic model of a pasture based dairy system was used to assess how annual farm operating profit (OP), and energy conversion efficiency (as greenhouse gas emissions per unit of product) may be affected by an increase in metabolizable energy (ME) concentration of pasture compared to a ‘Base Scenario’ (with no changes in ME). Changes in OP were calculated over 20 1-year periods using three methods of utilizing additional ME from perennial ryegrass. These included the effect of an arbitrary 1 MJ/kg of dry matter (kg DM) increase in ME concentration of pasture on, milk production per cow with no change in the number of cows (‘Base1M Scenario’), no change in milk production per cow but an increase in stocking rate (‘Base1 + SR Scenario’), or a proportionate reduction in purchased concentrates (‘Base1-Conc Scenario’). The mean increase in OP relative to the Base Scenario was AUD482/ha.year for Terang and AUD783/ha.year for Elliott in the Base1M Scenario. This assumed additional ME in pasture was converted into greater milk production per cow using factors of 5.19 MJ/L milk for Terang and 5.23 MJ/L milk for Elliott. Changes in OP for the two other scenarios (Base1 + SR Scenario and Base-Conc Scenario) still provided between 40% and 54% increases in OP compared to the respective Base1M Scenarios. If the energy requirements of additional milk production was increased by 3 MJ/L milk, the OP in the Base1M Scenarios for Terang and Elliott were still 24% and 27% greater than the respective Base Scenarios. In terms of energy conversion, reductions of 10–13% of greenhouse gas emissions per unit of energy corrected milk were estimated for a 1 MJ/kg DM increase in pasture ME in the Base1M Scenarios compared to the respective Base Scenarios. The magnitude of changes in OP using alternative methods of calculation supports the hypothesis that increasing ME concentration of pasture could provide benefit to grazing-based dairy farms, regardless of how a farmer utilizes the additional ME. This study provides a valuable method to aid investment decisions about the value of the ME concentration trait and where best to allocate resources towards achieving these traits in perennial ryegrass.

Association of single nucleotide polymorphisms in LpIRI1 gene with freezing tolerance traits in perennial ryegrass

Perennial ryegrass is an important agricultural crop, however, it is susceptible to winterkill. Freezing injury is caused primarily by ice formation. The LpIRI1 protein has the potential to inhibit ice recrystallization, thus minimize the damage. An association study was conducted using single nucleotide polymorphisms obtained through allele sequencing of the LpIRI1 gene and phenotypic data were collected using two phenotyping platforms in a perennial ryegrass association mapping population of 76 diverse genotypes. Winter survival (FWS) was evaluated under field conditions, while tiller survival (PTS) and electrolyte leakage (EL) at −8 and −12 °C were determined under controlled-environment conditions. Proline content (PC) in cold-acclimated plants was measured prior to the freezing test. Significant variation in FWS, PTS, EL and PC was observed among genotypes in our panel. EL and PTS revealed significant negative correlations at −8 °C (rs = −0.40) and −12 °C (rs = −0.49). PC, however, did not show significant correlations with any of the measured traits, while FWS was correlated (rs = −0.48) with EL at −12 °C. The LpIRI1 gene was found to be highly polymorphic with an average SNP frequency of 1 SNP per 16 bp. Association analysis revealed two non-synonymous SNPs being associated with increased EL, both located in the LpIRI1 leucine-rich repeat. The results indicate that allelic variation in the LpIRI1 gene plays an important role in the cell membrane integrity of perennial ryegrass during freezing, and can be exploited for developing more freezing tolerant cultivars.

Use of modelling to identify perennial ryegrass plant traits for future warmer and drier climates

Potential exists to select pasture species better adapted to anticipated warmer temperatures and lower rainfall, associated with increasing atmospheric carbon dioxide (CO2) and other greenhouse gas concentrations, to maximise pasture yields and persistence. This study assessed the effect of increasing three plant traits in perennial ryegrass (Lolium perenne L.) to adapt to future climates: root depth; heat tolerance, defined as the ability of plant to grow at high temperatures; and responsiveness to elevated CO2 concentrations. Pasture production was simulated using the Sustainable Grazing Systems Pasture model at three sites with temperate climates in south-eastern Australia: Hamilton, Victoria (medium rainfall); Ellinbank, Victoria (high rainfall); and Elliott, Tasmania (high rainfall). Two future climate scenarios were created at each site by scaling the historical climate (1971–2010) by +1°C with –10% rain (435 ppm CO2) and +2°C with –20% rain (535 ppm CO2). A genotype × environment interaction suggested that the plants traits most effective at increasing pasture yield differed depending on the local climate. Increased root depth was the most effective change in a single trait that increased pasture harvested at Elliott, increased heat tolerance was most effective at Ellinbank, whereas increasing all three individual traits was similarly effective at Hamilton. At each site, the most effective traits increased pasture growth during the period between late spring and mid-summer compared with the current cultivar. When all three traits were increased at the same time, the pasture production advantage was greater than the additive effects of changing single traits at Hamilton and Ellinbank. Further consideration of the feasibility of selecting multiple traits and the effects of a broader range of climate projections is required. Nonetheless, results of this study provide guidance to plant breeders for selection of traits adapted to future climates.

Seasonal and genetic variations in water-soluble carbohydrates and other quality traits in ecotypes and cultivars of perennial ryegrass (Lolium perenneL.)

Phenotyping of genetic resources remains the bottleneck in the characterization of genetic resources, since the advent of modern next-generation sequencing technologies has made genotyping much more cost- and time-effective. This article reports on the phenotyping of agriculturally important traits in perennial ryegrass (Lolium perenne). In the present study, water-soluble carbohydrate (WSC), crude protein and dry matter contents were recorded for 1320 individuals, pooled into 132 samples from 33 perennial ryegrass ecotypes and cultivars at five different harvest time points across the 2004 growing season. While, in general, the cultivars had higher WSC contents than the ecotypes, individual ecotypes did show potential to be used in breeding programmes, as they had higher values than all other accessions at particular cutting time points. In correlation analyses, positive relationships were observed between dry matter and glucose contents both early and late in the growing season. Principal components analysis allowed the split either between cultivars and ecotypes or between tetraploid cultivars and the rest of the accessions at four of the five cutting time points. In the analysis of variance, cutting time was the most significant factor influencing the variation in traits.

Genotyping by RAD sequencing enables mapping of fatty acid composition traits in perennial ryegrass (Lolium perenne (L.)).

Perennial ryegrass (Lolium perenne L.) is the most important forage crop in temperate livestock agriculture. Its nutritional quality has significant impact on the quality of meat and milk for human consumption. Evidence suggests that higher energy content in forage can assist in reducing greenhouse gas emissions from ruminants. Increasing the fatty acid content (especially α-linolenic acid, an omega-3 fatty acid) may thus contribute to better forage, but little is known about the genetic basis of variation for this trait. To this end, quantitative trait loci (QTLs) were identified associated with major fatty acid content in perennial ryegrass using a population derived from a cross between the heterozygous and outbreeding high-sugar grass variety AberMagic and an older variety, Aurora. A genetic map with 434 restriction-associated DNA (RAD) and SSR markers was generated. Significant QTLs for the content of palmitic (C16:0) on linkage groups (LGs) 2 and 7; stearic (C18:0) on LGs 3, 4 and 7; linoleic (C18:2n-6) on LGs 2 and 5; and α-linolenic acids (C18:3n-3) on LG 1 were identified. Two candidate genes (a lipase and a beta-ketoacyl CoA synthase), both associated with C16:0, and separately with C18:2n-6 and C18:0 contents, were identified. The physical positions of these genes in rice and their genetic positions in perennial ryegrass were consistent with established syntenic relationships between these two species. Validation of these associations is required, but the utility of RAD markers for rapid generation of genetic maps and QTL analysis has been demonstrated for fatty acid composition in a global forage crop.

Quantitative Trait Locus (QTL) meta-analysis and comparative genomics for candidate gene prediction in perennial ryegrass (Lolium perenne L.)

BackgroundIn crop species, QTL analysis is commonly used for identification of factors contributing to variation of agronomically important traits. As an important pasture species, a large number of QTLs have been reported for perennial ryegrass based on analysis of biparental mapping populations. Further characterisation of those QTLs is, however, essential for utilisation in varietal improvement programs.ResultsA bibliographic survey of perennial ryegrass trait-dissection studies identified a total of 560 QTLs from previously published papers, of which 189, 270 and 101 were classified as morphology-, physiology- and resistance/tolerance-related loci, respectively. The collected dataset permitted a subsequent meta-QTL study and implementation of a cross-species candidate gene identification approach. A meta-QTL analysis based on use of the BioMercator software was performed to identify two consensus regions for pathogen resistance traits. Genes that are candidates for causal polymorphism underpinning perennial ryegrass QTLs were identified through in silico comparative mapping using rice databases, and 7 genes were assigned to the p150/112 reference map. Markers linked to the LpDGL1, LpPh1 and LpPIPK1 genes were located close to plant size, leaf extension time and heading date-related QTLs, respectively, suggesting that these genes may be functionally associated with important agronomic traits in perennial ryegrass.ConclusionsFunctional markers are valuable for QTL meta-analysis and comparative genomics. Enrichment of such genetic markers may permit further detailed characterisation of QTLs. The outcomes of QTL meta-analysis and comparative genomics studies may be useful for accelerated development of novel perennial ryegrass cultivars with desirable traits.

Phenotypic and QTL analyses of herbage production-related traits in perennial ryegrass (Lolium perenne L.)

Phenotypic and genetic evaluation of morphological traits associated with herbage biomass production was undertaken in a perennial ryegrass (Lolium perenne L.) biparental F1 mapping population (n = 200) with parent plants from cultivars ‘Grasslands Impact’ and ‘Grasslands Samson’. Morphological traits measured on three clonal replicates of the parental genotypes and 200 F1 progeny in a glasshouse in two separate trials (autumn and spring) included: dry weight (DW), leaf elongation rate (LER), initial tiller number (TNs), final tiller number (TNe), site filling (Fs), tiller weight (TW), leaf lamina length, leaf tip and ligule appearance rates (ALf, ALg) and leaf elongation duration (LED). Principal component analysis of patterns of trait association identified negative correlation between TNs or TNe, and TW as the primary basis for morphological difference and indicated that either high LER or long LED could reduce TN. Plants with higher LER tended to have increased DW. Quantitative trait loci (QTL) were detected on all seven linkage groups (LG) of a perennial ryegrass linkage map for all but three traits. A total of 61 QTL were identified, many of which clustered at 15 shared genome locations. Significant genotype by environment effects were encountered, evidenced both by variation between experiments in genotype rankings and by a general lack of commonality for QTL for the same traits in the different experiments. Only five QTL, for ALf, ALg and TN, were conserved between autumn and spring trials. A QTL for TN and DW on LG6 is a strong candidate for application of MAS in future plant improvement work and was found to be co-linear with QTL for equivalent traits reported on chromosome 2 in rice.

Testing water-soluble carbohydrate QTL effects in perennial ryegrass (Lolium perenne L.) by marker selection

Water-soluble carbohydrates (WSC) are an important factor determining the nutritional value of grass forage and development of genetic markers for selection of WSC traits in perennial ryegrass would benefit future breeding programmes. Quantitative trait loci (QTLs) for WSC have been published for an F(2) ryegrass mapping family. Markers showing significant associations with these QTLs were used to design narrow-based populations with homozygosity for target QTLs. Founders were selected from within the mapping family. The divergent populations produced were analysed for WSC content in the glasshouse and the field. There was evidence of complex interactions between WSC content and other factors and traits, including the scale of assessment, time/degree of sward establishment and other forage quality parameters. Differences between the divergent pairs of the various populations were small. However, differences observed between the founder selection groups were maintained and the roles of the QTL regions in regulating forage WSC content were confirmed. In general, the individual divergent populations exploited only a limited extent of the large phenotypic variation available within the mapping family. However, this study sets the scene for exploring the opportunities for marker-assisted breeding strategies for complex traits in obligate out-breeding species, and the challenges of doing this are discussed.

Genetic improvement of fibre traits in perennial ryegrass

Genetic changes in fibre characteristics of perennial ryegrass (Lolium perenne) may enhance degradability and thereby improve voluntary feed intake and energy availability from ingested grass.

Quantitative trait loci mapping for biomass yield traits in a Lolium inbred line derived F2 population

Lolium perenne L. (perennial ryegrass) is the principle forage grass species in temperate agriculture. Improving biomass yield still remains one of the most important aims of current forage breeding programmes. A quantitative trait locus (QTL) study investigating biomass yield traits in perennial ryegrass was carried out in greenhouse and field environments. The study is based on an F2 population consisting of 360 individuals derived from two inbred grandparents where the F1 has a large biomass yield phenotype. For both experimental environments co-localized QTL for biomass yield traits including fresh and dry weight and dry matter were identified on linkage groups 2, 3 and 7. A major QTL for fresh and dry weight was identified on LG 3 which explained around 30% of the phenotypic variance in the field experiment. The findings of this study are discussed with regard for their potential in research and breeding.

Rubisco turnover and its relationship with herbage yield traits in perennial ryegrass (Lolium perenne L.)

Leaf Rubisco content was monitored over the life span of the sixth leaf blades of hydroponically grown perennial ryegrass tillers of 18 genotypes, to determine protein turnover patterns and investigate possible links between protein turnover pattern and plant performance. Keywords: Rubisco, perennial ryegrass, remobilisation, dynamic model, mapping population