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Molecular characterization of genetically modified plants can provide crucial information for the development of detection and identification methods, to comply with traceability, and labeling requirements prior to commercialization. Detailed description of the genetic modification was previously a challenging step in the safety assessment, since it required the use of laborious and time-consuming techniques. In this study an accurate, simple, and fast method was developed for molecular characterization of genetically modified (GM) plants, following a user-friendly workflow for researchers with limited bioinformatic capabilities. Three GM events from a diverse array of crop species—perennial ryegrass, white clover, and canola—were used to test the approach that exploits long-read sequencing by the MinION device, from Oxford Nanopore Technologies. The method delivered a higher degree of resolution of the transgenic events within the host genome than has previously been possible with the standard Illumina short-range sequencing strategies. The flanking sequences, copy number, and presence of backbone sequences, and overall transgene insertion structure were determined for each of the plant genomes, with the additional identification of moderate-sized secondary insertions that would have previously been missed. The proposed workflow takes only about 1 week from DNA extraction to analyzed result, and the method will complement the existing approaches for molecular characterization of GM plants, since it makes the process faster, simpler, and more cost-effective. [ABSTRACT FROM AUTHOR]

Key message: Exploitation 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.Abstract: 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. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) has been recognized as offering numerous potential benefits for ryegrass (Lolium perenne L.) breeding. While the theoretical benefits of GS in ryegrass breeding are clear, the best way to apply GS in practical breeding programs remains to be determined. The present study aimed to investigate genomic breeding options that best balance genetic gain, breeding costs, and the level of inbreeding using stochastic simulation. Nine GS scenarios were tested, including different numbers of selection candidates (10,000, 5000, and 2000 F1 seedlings) and three reference population sizes for GS composed of plots representing a sward-based trial (500, 200, and 100 plots). Low to moderate prediction accuracy was achieved for productivity traits across cycles (i.e., 0.1–0.45 for yield [h2 = 0.3]). Scenarios with larger reference populations (i.e., 500 plots) achieved higher prediction accuracy but, when considering field trial costs, were more expensive per unit of genetic gain. All nine GS scenarios delivered significantly higher genetic gain (up to fourfold) than the conventional breeding scenario over a 20-yr period. Scenarios with moderate selection intensity on F1 seedlings with fewer plots tested in field gave the most genetic gain per dollar invested (i.e., 2000 or 5000 F1 seedlings and 100 plots). However, all GS scenarios reduced genetic diversity in the breeding population more than phenotypic selection, highlighting the need to mitigate inbreeding when applying GS in perennial ryegrass. [ABSTRACT FROM AUTHOR]

Relatively modest levels of genetic gain have been achieved in conventional ryegrass breeding when compared to cereal crops such as maize, current estimates indicating an annual improvement of 0.25-0.6% in dry matter production. This property is partially due to an inability to effectively exploit heterosis through the formation of F1 hybrids. Controlled crossing of ryegrass lines from geographically distant origins has demonstrated the occurrence of heterosis, which can result in increases of dry matter production in the order of 25%. Although capture of hybrid vigor offers obvious advantages for ryegrass cultivar production, to date there have been no effective and commercially suitable methods for obtaining high proportions of F1 hybrid seed. Continued advances in fine-scale genetic and physical mapping of the gametophytic self-incompatibility (SI) loci (S and Z) of ryegrasses are likely in the near future to permit the identification of closely linked genetic markers that define locus-specific haplotypes, allowing prediction of allelic variants and hence compatibility between different plant genotypes. Given the availability of such information, a strategy for efficient generation of ryegrass cultivars with a high proportion of F1 hybrid individuals has been simulated, which is suitable for commercial implementation. Through development of two parental pools with restricted diversity at the SI loci, relative crossing compatibility between pools is increased. Based on simulation of various levels of SI allele diversity restriction, the most effective scheme will generate 83.33% F1 hybrids. Results from the study, including the impact of varying flowering time, are discussed along with a proposed breeding design for commercial application. [ABSTRACT FROM AUTHOR]

Genomic selection ( GS) is a powerful method for exploitation of DNA sequence polymorphisms in breeding improvement, through the prediction of breeding values based on all markers distributed genome-wide. Forage grasses and legumes provide important targets for GS implementation, as many key traits are difficult or expensive to assess, and are measured late in the breeding cycle. Generic attributes of forage breeding programmes are described, along with status of genomic resources for a representative species group (ryegrasses). Two schemes for implementing GS in ryegrass breeding are described. The first requires relatively little modification of current schemes, but could lead to significant reductions in operating cost. The second scheme would allow two rounds of selection for key agronomic traits within a time period previously required for a single round, potentially leading to doubling of genetic gain rate, but requires a purpose-designed reference population. In both schemes, the limited extent of linkage disequilibrium ( LD), which is the major challenge for GS implementation in ryegrass breeding, is addressed. The strategies also incorporate recent advances in DNA sequencing technology to minimize costs. [ABSTRACT FROM AUTHOR]

Background: In 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. Results: A 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. Conclusions: Functional 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. [ABSTRACT FROM AUTHOR]

Background: Qualitative pathogen resistance in both dicotyledenous and monocotyledonous plants has been attributed to the action of resistance (R) genes, including those encoding nucleotide binding site -- leucine rich repeat (NBS-LRR) proteins and receptor-like kinase enzymes. This study describes the large-scale isolation and characterisation of candidate R genes from perennial ryegrass. The analysis was based on the availability of an expressed sequence tag (EST) resource and a functionally-integrated bioinformatics database. Results: Amplification of R gene sequences was performed using template EST data and information from orthologous candidate using a degenerate consensus PCR approach. A total of 102 unique partial R genes were cloned, sequenced and functionally annotated. Analysis of motif structure and R gene phylogeny demonstrated that Lolium R genes cluster with putative ortholoci, and evolved from common ancestral origins. Single nucleotide polymorphisms (SNPs) predicted through resequencing of amplicons from the parental genotypes of a genetic mapping family were validated, and 26 distinct R gene loci were assigned to multiple genetic maps. Clusters of largely non-related NBS-LRR genes were located at multiple distinct genomic locations and were commonly found in close proximity to previously mapped defence response (DR) genes. A comparative genomics analysis revealed the co-location of several candidate R genes with disease resistance quantitative trait loci (QTLs). Conclusion: This study is the most comprehensive analysis to date of qualitative disease resistance candidate genes in perennial ryegrass. SNPs identified within candidate genes provide a valuable resource for mapping in various ryegrass pair cross-derived populations and further germplasm analysis using association genetics. In parallel with the use of specific pathogen virulence races, such resources provide the means to identify gene-forgene mechanisms for multiple host pathogen-interactions and ultimately to obtain durable field-based resistance. [ABSTRACT FROM AUTHOR]

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Corrections are presented on the development and characterisation of EST-SSR markers from the crown rust pathogen of ryegrass.