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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. [ABSTRACT FROM AUTHOR]

Background: Recent advances in the mapping of biochemical traits have been reported in Lolium perenne. Although the mapped traits, including individual sugars and fatty acids, contribute greatly towards ruminant productivity, organic acids and amino acids have been largely understudied despite their influence on the ruminal microbiome. Results: In this study, we used a targeted gas-chromatography mass spectrometry (GC-MS) approach to profile the levels of 25 polar metabolites from different classes (sugars, amino acids, phenolic acids, organic acids and other nitrogen-containing compounds) present in a L. perenne F2 population consisting of 325 individuals. A quantitative trait (QTL) mapping approach was applied and successfully identified QTLs regulating seven of those polar metabolites (L-serine, L-leucine, glucose, fructose, myo-inositol, citric acid and 2, 3-hydroxypropanoic acid). Two QTL mapping approaches were carried out using SNP markers on about half of the population only and an imputation approach using SNP and DArT markers on the entire population. The imputation approach confirmed the four QTLs found in the SNP-only analysis and identified a further seven QTLs. Conclusions: These results highlight the potential of utilising molecular assisted breeding in perennial ryegrass to modulate a range of biochemical quality traits with downstream effects in livestock productivity and ruminal digestion. [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) 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]