Luke W. Pembleton

Transcriptome sequencing of lentil based on second-generation technology permits large-scale unigene assembly and SSR marker discovery

BackgroundLentil (Lens culinaris Medik.) is a cool-season grain legume which provides a rich source of protein for human consumption. In terms of genomic resources, lentil is relatively underdeveloped, in comparison to other Fabaceae species, with limited available data. There is hence a significant need to enhance such resources in order to identify novel genes and alleles for molecular breeding to increase crop productivity and quality.ResultsTissue-specific cDNA samples from six distinct lentil genotypes were sequenced using Roche 454 GS-FLX Titanium technology, generating c. 1.38 × 106 expressed sequence tags (ESTs). De novo assembly generated a total of 15,354 contigs and 68,715 singletons. The complete unigene set was sequence-analysed against genome drafts of the model legume species Medicago truncatula and Arabidopsis thaliana to identify 12,639, and 7,476 unique matches, respectively. When compared to the genome of Glycine max, a total of 20,419 unique hits were observed corresponding to c. 31% of the known gene space. A total of 25,592 lentil unigenes were subsequently annoated from GenBank. Simple sequence repeat (SSR)-containing ESTs were identified from consensus sequences and a total of 2,393 primer pairs were designed. A subset of 192 EST-SSR markers was screened for validation across a panel 12 cultivated lentil genotypes and one wild relative species. A total of 166 primer pairs obtained successful amplification, of which 47.5% detected genetic polymorphism.ConclusionsA substantial collection of ESTs has been developed from sequence analysis of lentil genotypes using second-generation technology, permitting unigene definition across a broad range of functional categories. As well as providing resources for functional genomics studies, the unigene set has permitted significant enhancement of the number of publicly-available molecular genetic markers as tools for improvement of this species.

StAMPP: an R package for calculation of genetic differentiation and structure of mixed-ploidy level populations.

Statistical Analysis of Mixed‐Ploidy Populations (StAMPP) is a freely available R package for calculation of population structure and differentiation based on single nucleotide polymorphism (SNP) genotype data from populations of any ploidy level, and/or mixed‐ploidy levels. StAMPP provides an advance on previous similar software packages, due to an ability to calculate pairwise FST values along with confidence intervals, Neis genetic distance and genomic relationship matrixes from data sets of mixed‐ploidy level. The software code is designed to efficiently handle analysis of large genotypic data sets that are typically generated by high‐throughput genotyping platforms. Population differentiation studies using StAMPP are broadly applicable to studies of molecular ecology and conservation genetics, as well as animal and plant breeding.

Development and implementation of a multiplexed single nucleotide polymorphism genotyping tool for differentiation of ryegrass species and cultivars

Perennial ryegrass (Lolium perenne L.) and Italian ryegrass (Lolium multiflorum Lam.) are important temperate forage grasses which are closely related, generating fertile interspecific hybrids. All groups are represented by multiple cultivars in the commercial pasture seeds market. Due to the close taxonomic relationship between the two species, differentiation based on morphophysiological criteria is not always readily achievable. In addition, an obligate outbreeding reproductive habit produces high levels of individual heterozygosity and intrapopulation diversity, which presents problems for discrimination between cultivars. Molecular genetic marker polymorphism provides an effective means of addressing these challenges. An iterative process of resequencing from loci distributed across the perennial ryegrass genome was used to identify single nucleotide polymorphism (SNP) markers, which were then validated and formatted in a highly multiplexed (384-plex) assay system. SNP genotyping was then performed across samples of 48–192 individuals from a total of 27 ryegrass cultivars (19 of perennial ryegrass, seven of Italian ryegrass and one hybrid cultivar). SNP markers from perennial ryegrass exhibited a high level of transfer to Italian ryegrass. Data analysis permitted quantification of intra- and inter-species diversity, as well as discrimination between cultivars within each species, including diploid and autotetraploid cultivars of perennial ryegrass. Lower levels of SNP-based diversity were detected in Italian ryegrass than in perennial ryegrass. A neighbour-joining tree based on genetic distance analysis located a hybrid cultivar to an intermediate position between the two species-specific cultivar groups. The resulting catalogue of ryegrass cultivars will provide support for the processes of cultivar accreditation and quality assurance.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass (Lolium perenne L.) improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4‐yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Design of an F1 hybrid breeding strategy for ryegrasses based on selection of self-incompatibility locus-specific alleles

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.

Candidate gene-based association genetics analysis of herbage quality traits in perennial ryegrass (Lolium perenne L.)

Abstract. Due to the complex genetic architecture of perennial ryegrass, based on an obligate outbreeding reproductive habit, association-mapping approaches to genetic dissection offer the potential for effective identification of genetic marker–trait linkages. Associations with genes for agronomic characters, such as components of herbage nutritive quality, may then be utilised for accelerated cultivar improvement using advanced molecular breeding practices. The objective of the present study was to evaluate the presence of such associations for a broad range of candidate genes involved in pathways of cell wall biosynthesis and carbohydrate metabolism. An association-mapping panel composed from a broad range of non-domesticated and varietal sources was assembled and assessed for genome-wide sequence polymorphism. Removal of significant population structure obtained a diverse meta-population (220 genotypes) suitable for association studies. The meta-population was established with replication as a spaced-plant field trial. All plants were genotyped with a cohort of candidate gene-derived single nucleotide polymorphism (SNP) markers. Herbage samples were harvested at both vegetative and reproductive stages and were measured for a range of herbage quality traits using near infrared reflectance spectroscopy. Significant associations were identified for ∼50% of the genes, accounting for small but significant components of phenotypic variance. The identities of genes with associated SNPs were largely consistent with detailed knowledge of ryegrass biology, and they are interpreted in terms of known biochemical and physiological processes. Magnitudes of effect of observed marker–trait gene association were small, indicating that future activities should focus on genome-wide association studies in order to identify the majority of causal mutations for complex traits such as forage quality.

Targeted genotyping-by-sequencing permits cost-effective identification and discrimination of pasture grass species and cultivars

Key messageA targeted amplicon-based genotyping-by-sequencing approach has permitted cost-effective and accurate discrimination betweenryegrass species (perennial, Italian and inter-species hybrid), and identification of cultivars based on bulked samples.AbstractPerennial ryegrass and Italian ryegrass are the most important temperate forage species for global agriculture, and are represented in the commercial pasture seed market by numerous cultivars each composed of multiple highly heterozygous individuals. Previous studies have identified difficulties in the use of morphophysiological criteria to discriminate between these two closely related taxa. Recently, a highly multiplexed single nucleotide polymorphism (SNP)-based genotyping assay has been developed that permits accurate differentiation between both species and cultivars of ryegrasses at the genetic level. This assay has since been further developed into an amplicon-based genotyping-by-sequencing (GBS) approach implemented on a second-generation sequencing platform, allowing accelerated throughput and ca. sixfold reduction in cost. Using the GBS approach, 63 cultivars of perennial, Italian and interspecific hybrid ryegrasses, as well as intergeneric Festulolium hybrids, were genotyped. The genetic relationships between cultivars were interpreted in terms of known breeding histories and indistinct species boundaries within the Lolium genus, as well as suitability of current cultivar registration methodologies. An example of applicability to quality assurance and control (QA/QC) of seed purity is also described. Rapid, low-cost genotypic assays provide new opportunities for breeders to more fully explore genetic diversity within breeding programs, allowing the combination of novel unique genetic backgrounds. Such tools also offer the potential to more accurately define cultivar identities, allowing protection of varieties in the commercial market and supporting processes of cultivar accreditation and quality assurance.

Genotyping-by-sequencing through transcriptomics: implementation in a range of crop species with varying reproductive habits and ploidy levels

Summary The application of genomics in crops has the ability to significantly improve genetic gain for agriculture. Many marker‐dense tools have been developed, but few have seen broad adoption in plant genomics due to issues of significant variations of genome size, levels of ploidy, single nucleotide polymorphism (SNP) frequency and reproductive habit. When combined with limited breeding activities, small research communities and scant sequence resources, the suitability of popular systems is often suboptimal and routinely fails to effectively balance cost‐effectiveness and sample throughput. Genotyping‐by‐sequencing (GBS) encompasses a range of protocols including resequencing of the transcriptome. This study describes a skim GBS‐transcriptomics (GBS‐t) approach developed to be broadly applicable, cost‐effective and high‐throughput while still assaying a significant number of SNP loci. A range of crop species with differing levels of ploidy and degree of inbreeding/outbreeding were chosen, including perennial ryegrass, a diploid outbreeding forage grass; phalaris, a putative segmental allotetraploid outbreeding forage grass; lentil, a diploid inbreeding grain legume; and canola, an allotetraploid partially outbreeding oilseed. GBS‐t was validated as a simple and largely automated, cost‐effective method which generates sufficient SNPs (from 89 738 to 231 977) with acceptable levels of missing data and even genome coverage from c. 3 million sequence reads per sample. GBS‐t is therefore a broadly applicable system suitable for many crops, offering advantages over other systems. The correct choice of subsequent sequence analysis software is important, and the bioinformatics process should be iterative and tailored to the specific challenges posed by ploidy variation and extent of heterozygosity.

Variance, inter-trait correlation, heritability and trait-marker association of herbage yield, nutritive values, and morphological characteristics in Italian ryegrass (Lolium multiflorum Lam.)

Abstract. Italian ryegrass (Lolium multiflorum Lam.) is one of the most important temperate forage grasses on a global basis. The present study estimated trait variance, inter-trait correlation and broad-sense heritability (H2) for herbage yield, nutritive values and morphological characteristics of Italian ryegrass, and analysed associations between these traits and single nucleotide polymorphism (SNP) markers. A field-based, spaced-plant nursery experiment was conducted to assess 960 genotypes from seven cultivars and breeding lines, in a randomised complete block design with four replicates. Significant correlations, broad ranges of variation and significant genotypic variance components were identified for 18 measured phenotypic traits. Moderate H2 estimates (0.36–0.52) were obtained for nutritive values, compared with low to high H2 estimates (0.20–0.69) for yield over five cuttings, and moderate to high H2 estimates (0.40–0.78) for morphological traits. Within- and among-cultivar variation ranged from 40.0% to 95.1% and 4.9% to 60.0%, respectively, depending on different traits. Association analysis identified 65 significant SNP–trait gene associations involving multiple genomic regions, which warrant further validation. The implications of trait correlation and heritability for selection and improvement are discussed.

Low-cost automated biochemical phenotyping for optimised nutrient quality components in ryegrass breeding

Abstract. Quantification of forage quality is essential for the identification of elite genotypes in forage grass breeding. Perennial ryegrass is the most important temperate species for global pastoral agriculture. However, the protein content of ryegrass generally exceeds the requirements of a grazing animal, and the ratio of water soluble carbohydrate (WSC) to protein is too low for efficient protein utilisation. This results in poor nitrogen use efficiency (NUE) in the farming system by livestock, and hence limits optimal animal production. New ryegrass cultivars with optimised WSC and protein content are desirable for farming efficiencies. Several methods are available for quantification of WSC and plant protein (such as near-infrared spectroscopy [NIRS] and high performance liquid chromatography [HPLC]). However, such methods are labour-intensive, low-throughput and cost-prohibitive for commercial breeding programs, which typically need to assess thousands of samples annually. An accurate high-throughput micro-plate-based protocol has been developed and validated, with the ability to simultaneously process and quantify WSC and plant protein with a high level of automation, and an increase in sample processing of ∼10-fold compared with commonly-used methods, along with a 3-fold cost reduction. As WSC and protein are extracted simultaneously and quantified within micro-plates, consumable costs are minimised with optimal reagent use efficiency, resulting in a low per sample cost that is suitable for commercial pasture breeding companies. This is the first demonstration of a forage quality phenotyping protocol suitable for broad-scale application, and will allow breeders to select elite genotypes based not only on visual assessment but also on WSC : protein ratios for improved ruminant nutrition.