The soil microbiome of Lolium perenne L. depends on host genotype, is modified by nitrogen level and varies across season

Genotype by environment interactions (G × E) are frequently observed in herbage production. Understanding the underlying biological mechanisms is important for achieving stable and predictive outputs across production environments. The microbiome is gaining increasing attention as a significant contributing factor to G × E. Here, we focused on the soil microbiome of perennial ryegrass (Lolium perenne L.) grown under field conditions and investigated the soil microbiome variation across different ryegrass varieties to assess whether environmental factors, such as seasonality and nitrogen levels, affect the microbial community. We identified bacteria, archaea, and fungi operational taxonomic units (OTUs) and showed that seasonality and ryegrass variety were the two factors explaining the largest fraction of the soil microbiome diversity. The strong and significant variety-by-treatment-by-seasonal cut interaction for ryegrass dry matter was associated with the number of unique OTUs within each sample. We identified seven OTUs associated with ryegrass dry matter variation. An OTU belonging to the Solirubrobacterales (Thermoleophilales) order was associated with increased plant biomass, supporting the possibility of developing engineered microbiomes for increased plant yield. Our results indicate the importance of incorporating different layers of biological data, such as genomic and soil microbiome data to improve the prediction accuracy of plant phenotypes grown across heterogeneous environments.

Corrigendum: Methylome changes in Lolium perenne associated with long-term colonisation by the endophytic fungus Epichloë sp. LpTG-3 strain AR37

[This corrects the article DOI: 10.3389/fpls.2023.1258100.].

Methylome changes in Lolium perenne associated with long-term colonisation by the endophytic fungus Epichloë sp. LpTG-3 strain AR37

Epichloë spp. often form mutualistic interactions with cool-season grasses, such as Lolium perenne. However, the molecular mechanisms underlying this interaction remain poorly understood. In this study, we employed reduced representation bisulfite sequencing method (epiGBS) to investigate the impact of the Epichloë sp. LpTG-3 strain AR37 on the methylome of L. perenne across multiple grass generations and under drought stress conditions. Our results showed that the presence of the endophyte leads to a decrease in DNA methylation across genomic features, with differentially methylated regions primarily located in intergenic regions and CHH contexts. The presence of the endophyte was consistently associated with hypomethylation in plants across generations. This research sheds new light on the molecular mechanisms governing the mutualistic interaction between Epichloë sp. LpTG-3 strain AR37 and L. perenne. It underscores the role of methylation changes associated with endophyte infection and suggests that the observed global DNA hypomethylation in L. perenne may be influenced by factors such as the duration of the endophyte-plant association and the accumulation of genetic and epigenetic changes over time.

Genetic architecture of inter-specific and -generic grass hybrids by network analysis on multi-omics data

BACKGROUND

Understanding the mechanisms underlining forage production and its biomass nutritive quality at the omics level is crucial for boosting the output of high-quality dry matter per unit of land. Despite the advent of multiple omics integration for the study of biological systems in major crops, investigations on forage species are still scarce.

RESULTS

Our results identified substantial changes in gene co-expression and metabolite-metabolite network topologies as a result of genetic perturbation by hybridizing L. perenne with another species within the genus (L. multiflorum) relative to across genera (F. pratensis). However, conserved hub genes and hub metabolomic features were detected between pedigree classes, some of which were highly heritable and displayed one or more significant edges with agronomic traits in a weighted omics-phenotype network. In spite of tagging relevant biological molecules as, for example, the light-induced rice 1 (LIR1), hub features were not necessarily better explanatory variables for omics-assisted prediction than features stochastically sampled and all available regressors.

CONCLUSIONS

The utilization of computational techniques for the reconstruction of co-expression networks facilitates the identification of key omic features that serve as central nodes and demonstrate correlation with the manifestation of observed traits. Our results also indicate a robust association between early multi-omic traits measured in a greenhouse setting and phenotypic traits evaluated under field conditions.

Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses

Self-incompatibility (SI) is a genetic mechanism of hermaphroditic plants to prevent inbreeding after self-pollination. Allogamous Poaceae species exhibit a unique gametophytic SI system controlled by two multi-allelic and independent loci, S and Z. Despite intense research efforts in the last decades, the genes that determine the initial recognition mechanism are yet to be identified. Here, we report the fine-mapping of the Z-locus in perennial ryegrass (Lolium perenne L.) and provide evidence that the pollen and stigma components are determined by two genes encoding DUF247 domain proteins (ZDUF247-I and ZDUF247-II) and the gene sZ, respectively. The pollen and stigma determinants are located side-by-side and were genetically linked in 10,245 individuals of two independent mapping populations segregating for Z. Moreover, they exhibited high allelic diversity as well as tissue-specific gene expression, matching the expected characteristics of SI determinants known from other systems. Revisiting the S-locus using the latest high-quality whole-genome assemblies revealed a similar gene composition and structure as found for Z, supporting the hypothesis of a duplicated origin of the two-locus SI system of grasses. Ultimately, comparative genomic analyses across a wide range of self-compatible and self-incompatible Poaceae species revealed that the absence of a functional copy of at least one of the six putative SI determinants is accompanied by a self-compatible phenotype. Our study provides new insights into the origin and evolution of the unique gametophytic SI system in one of the largest and economically most important plant families.

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 (GE_Control and GE_Drought ) 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.

Leveraging spatiotemporal genomic breeding value estimates of dry matter yield and herbage quality in ryegrass via random regression models

Joint modeling of correlated multienvironment and multiharvest data of perennial crop species may offer advantages in prediction schemes and a better understanding of the underlying dynamics in space and time. The goal of the present study was to investigate the relevance of incorporating the longitudinal dimension of within-season multiple measurements of forage perennial ryegrass (Lolium perenne L.) traits in a reaction-norm model setup that additionally accounts for genotype × environment (G × E) interactions. Genetic parameters and accuracy of genomic estimated breeding value (gEBV) predictions were investigated by fitting three genomic random regression models (gRRMs) using Legendre polynomial functions to the data. Genomic DNA sequencing of family pools of diploid perennial ryegrass was performed using DNA nanoball-based technology and yielded 56,645 single-nucleotide polymorphisms, which were used to calculate the allele frequency-based genomic relationship matrix. Biomass yield's estimated additive genetic variance and heritability values were higher in later harvests. The additive genetic correlations were moderate to low in early measurements and peaked at intermediates with fairly stable values across the environmental gradient except for the initial harvest data collection. This led to the conclusion that complex (G × E) arises from spatial and temporal dimensions in the early season with lower reranking trends thereafter. In general, modeling the temporal dimension with a second-order orthogonal polynomial improved the accuracy of gEBV prediction for nutritive quality traits, but no gain in prediction accuracy was detected for dry matter yield (DMY). This study leverages the flexibility and usefulness of gRRM models for perennial ryegrass breeding and can be readily extended to other multiharvest crops.

Integration of DNA Methylation and Transcriptome Data Improves Complex Trait Prediction in Hordeum vulgare

Whole-genome multi-omics profiles contain valuable information for the characterization and prediction of complex traits in plants. In this study, we evaluate multi-omics models to predict four complex traits in barley (Hordeum vulgare); grain yield, thousand kernel weight, protein content, and nitrogen uptake. Genomic, transcriptomic, and DNA methylation data were obtained from 75 spring barley lines tested in the RadiMax semi-field phenomics facility under control and water-scarce treatment. By integrating multi-omics data at genomic, transcriptomic, and DNA methylation regulatory levels, a higher proportion of phenotypic variance was explained (0.72–0.91) than with genomic models alone (0.55–0.86). The correlation between predictions and phenotypes varied from 0.17–0.28 for control plants and 0.23–0.37 for water-scarce plants, and the increase in accuracy was significant for nitrogen uptake and protein content compared to models using genomic information alone. Adding transcriptomic and DNA methylation information to the prediction models explained more of the phenotypic variance attributed to the environment in grain yield and nitrogen uptake. It furthermore explained more of the non-additive genetic effects for thousand kernel weight and protein content. Our results show the feasibility of multi-omics prediction for complex traits in barley.

Chromosome-scale assembly and annotation of the perennial ryegrass genome

BACKGROUND

The availability of chromosome-scale genome assemblies is fundamentally important to advance genetics and breeding in crops, as well as for evolutionary and comparative genomics. The improvement of long-read sequencing technologies and the advent of optical mapping and chromosome conformation capture technologies in the last few years, significantly promoted the development of chromosome-scale genome assemblies of model plants and crop species. In grasses, chromosome-scale genome assemblies recently became available for cultivated and wild species of the Triticeae subfamily. Development of state-of-the-art genomic resources in species of the Poeae subfamily, which includes important crops like fescues and ryegrasses, is lagging behind the progress in the cereal species.

RESULTS

Here, we report a new chromosome-scale genome sequence assembly for perennial ryegrass, obtained by combining PacBio long-read sequencing, Illumina short-read polishing, BioNano optical mapping and Hi-C scaffolding. More than 90% of the total genome size of perennial ryegrass (approximately 2.55 Gb) is covered by seven pseudo-chromosomes that show high levels of collinearity to the orthologous chromosomes of Triticeae species. The transposon fraction of perennial ryegrass was found to be relatively low, approximately 35% of the total genome content, which is less than half of the genome repeat content of cultivated cereal species. We predicted 54,629 high-confidence gene models, 10,287 long non-coding RNAs and a total of 8,393 short non-coding RNAs in the perennial ryegrass genome.

CONCLUSIONS

The new reference genome sequence and annotation presented here are valuable resources for comparative genomic studies in grasses, as well as for breeding applications and will expedite the development of productive varieties in perennial ryegrass and related species.

Genomic Prediction of Complex Traits in Forage Plants Species: Perennial Grasses Case

The majority of forage grass species are obligate outbreeders. Their breeding classically consists of an initial selection on spaced plants for highly heritable traits such as disease resistances and heading date, followed by familial selection on swards for forage yield and quality traits. The high level of diversity and heterozygosity, and associated decay of linkage disequilibrium (LD) over very short genomic distances, has hampered the implementation of genomic selection (GS) in these species. However, next generation sequencing technologies in combination with the development of genomic resources have recently facilitated implementation of GS in forage grass species such as perennial ryegrass (Lolium perenne L.), switchgrass (Panicum virgatum L.), and timothy (Phleum pratense L.). Experimental work and simulations have shown that GS can increase significantly the genetic gain per unit of time for traits with different levels of heritability. The main reasons are (1) the possibility to select single plants based on their genomic estimated breeding values (GEBV) for traits measured at sward level, (2) a reduction in the duration of selection cycles, and less importantly (3) an increase in the selection intensity associated with an increase in the genetic variance used for selection. Nevertheless, several factors should be taken into account for the successful implementation of GS in forage grasses. For example, it has been shown that the level of relatedness between the training and the selection population is particularly critical when working with highly structured meta-populations consisting of several genetic groups. A sufficient number of markers should be used to estimate properly the kinship between individuals and to reflect the variability of major QTLs. It is also important that the prediction models are trained for relevant environments when dealing with traits with high genotype × environment interaction (G × E). Finally, in these outbreeding species, measures to reduce inbreeding should be used to counterbalance the high selection intensity that can be achieved in GS.

Insights into the evolution of symbiosis gene copy number and distribution from a chromosome-scale Lotus japonicus Gifu genome sequence

Lotus japonicus is a herbaceous perennial legume that has been used extensively as a genetically tractable model system for deciphering the molecular genetics of symbiotic nitrogen fixation. Our aim is to improve the L. japonicus reference genome sequence, which has so far been based on Sanger and Illumina sequencing reads from the L. japonicus accession MG-20 and contained a large fraction of unanchored contigs. Here, we use long PacBio reads from L. japonicus Gifu combined with Hi-C data and new high-density genetic maps to generate a high-quality chromosome-scale reference genome assembly for L. japonicus. The assembly comprises 554 megabases of which 549 were assigned to six pseudomolecules that appear complete with telomeric repeats at their extremes and large centromeric regions with low gene density. The new L. japonicus Gifu reference genome and associated expression data represent valuable resources for legume functional and comparative genomics. Here, we provide a first example by showing that the symbiotic islands recently described in Medicago truncatula do not appear to be conserved in L. japonicus.

Genomic selection in American mink (Neovison vison) using a single-step genomic best linear unbiased prediction model for size and quality traits graded on live mink

Genomic selection relies on single-nucleotide polymorphisms (SNPs), which are often collected using medium-density SNP arrays. In mink, no such array is available; instead, genotyping by sequencing (GBS) can be used to generate marker information. Here, we evaluated the effect of genomic selection for mink using GBS. We compared the estimated breeding values (EBVs) from single-step genomic best linear unbiased prediction (SSGBLUP) models to the EBV from ordinary pedigree-based BLUP models. We analyzed seven size and quality traits from the live grading of brown mink. The phenotype data consisted of ~20,600 records for the seven traits from the mink born between 2013 and 2016. Genotype data included 2,103 mink born between 2010 and 2014, mostly breeding animals. In total, 28,336 SNP markers from 391 scaffolds were available for genomic prediction. The pedigree file included 29,212 mink. The predictive ability was assessed by the correlation (r) between progeny trait deviation (PTD) and EBV, and the regression of PTD on EBV, using 5-fold cross-validation. For each fold, one-fifth of animals born in 2014 formed the validation set. For all traits, the SSGBLUP model resulted in higher accuracies than the BLUP model. The average increase in accuracy was 15% (between 3% for fur clarity and 28% for body weight). For three traits (body weight, silky appearance of the under wool, and guard hair thickness), the difference in r between the two models was significant (P < 0.05). For all traits, the regression slopes of PTD on EBV from SSGBLUP models were closer to 1 than regression slopes from BLUP models, indicating SSGBLUP models resulted in less bias of EBV for selection candidates than the BLUP models. However, the regression coefficients did not differ significantly. In conclusion, the SSGBLUP model is superior to conventional BLUP model in the accurate selection of superior animals, and, thus, it would increase genetic gain in a selective breeding program. In addition, this study shows that GBS data work well in genomic prediction in mink, demonstrating the potential of GBS for genomic selection in livestock species.

The cytosine methylation landscape of spring barley revealed by a new reduced representation bisulfite sequencing pipeline, WellMeth

Patterns and level of cytosine methylation vary widely among plant species and are associated with genome size as well as the proportion of transposons and other repetitive elements in the genome. We explored epigenetic patterns and diversity in a representative proportion of the spring barley (Hordeum vulgare L.) genome across several commercial and historical cultivars. This study adapted a genotyping-by-sequencing (GBS) approach for the detection of methylated cytosines in genomic DNA. To analyze the data, we developed WellMeth, a complete pipeline for analysis of reduced representation bisulfite sequencing. WellMeth enabled quantification of context-specific DNA methylation at the single-base resolution as well as identification of differentially methylated sites (DMCs) and regions (DMRs). On average, DNA methylation levels were significantly higher than what is commonly observed in many plants species, reaching over 10-fold higher levels than those in Arabidopsis thaliana (L.) Heynh. in the CHH methylation. Preferential methylation was observed within and at the edges of long-terminal repeats (LTR) retrotransposons Gypsy and Copia. From a pairwise comparison of cultivars, numerous DMRs could be identified of which more than 5,000 were conserved within the analyzed set of barley cultivars. The subset of regions overlapping with genes showed enrichment in gene ontology (GO) categories associated with chromatin and cellular structure and organization. A significant correlation between genetic and epigenetic distances suggests that a considerable portion of methylated regions is under strict genetic control in barley. The data presented herein represents the first step in efforts toward a better understanding of genome-level structural and functional aspects of methylation in barley.

The Mitogenome of Norway Spruce and a Reappraisal of Mitochondrial Recombination in Plants

Plant mitogenomes can be difficult to assemble because they are structurally dynamic and prone to intergenomic DNA transfers, leading to the unusual situation where an organelle genome is far outnumbered by its nuclear counterparts. As a result, comparative mitogenome studies are in their infancy and some key aspects of genome evolution are still known mainly from pregenomic, qualitative methods. To help address these limitations, we combined machine learning and in silico enrichment of mitochondrial-like long reads to assemble the bacterial-sized mitogenome of Norway spruce (Pinaceae: Picea abies). We conducted comparative analyses of repeat abundance, intergenomic transfers, substitution and rearrangement rates, and estimated repeat-by-repeat homologous recombination rates. Prompted by our discovery of highly recombinogenic small repeats in P. abies, we assessed the genomic support for the prevailing hypothesis that intramolecular recombination is predominantly driven by repeat length, with larger repeats facilitating DNA exchange more readily. Overall, we found mixed support for this view: Recombination dynamics were heterogeneous across vascular plants and highly active small repeats (ca. 200 bp) were present in about one-third of studied mitogenomes. As in previous studies, we did not observe any robust relationships among commonly studied genome attributes, but we identify variation in recombination rates as a underinvestigated source of plant mitogenome diversity.

Mycelial biomass and concentration of loline alkaloids driven by complex population structure in Epichloë uncinata and meadow fescue (Schedonorus pratensis)

Many efforts have been made to select and isolate naturally occurring animal-friendly Epichloë strains for later reinfection into elite cultivars. Often this process involves large-scale screening of Epichloë-infected wild grass populations where strains are characterized and alkaloids measured. Here, we describe for the first time the use of genotyping-by-sequencing (GBS) on a collection of 217 Epichloë-infected grasses (7 S. arundinaceum, 4 L. perenne, and 206 S. pratensis). This genotyping strategy is cheaper than complete genome sequencing, is suitable for a large number of individuals, and, when applied to endophyte-infected grasses, conveniently genotypes both organisms. In total, 6273 single nucleotide polymorphisms (SNPs) in the endophyte data set and 38 323 SNPs in the host data set were obtained. Our findings reveal a composite structure with three distinct endophyte clusters unrelated to the three main S. pratensis gene pools that have most likely spread from different glacial refugia in Eurasia. All three gene pools can establish symbiosis with E. uncinata. A comparison of the endophyte clusters with microsatellite-based fingerprinting of the same samples allows a quick test to discriminate between these clusters using two simple sequence repeats (SSRs). Concentrations of loline alkaloids and mycelial biomass are correlated and differ significantly among the plant and endophyte subpopulations; one endophyte strain has higher levels of lolines than others, and one specific host genotype is particularly suitable to host E. uncinata. These findings pave the way for targeted artificial inoculations of specific host-endophyte combinations to boost loline production in the symbiota and for genome association studies with the aim of isolating genes involved in the compatibility between meadow fescue and E. uncinata.

Fungal Endophyte Colonization Patterns Alter Over Time in the Novel Association Between Lolium perenne and Epichloë Endophyte AR37

Infection of the pasture grass Lolium perenne with the seed-transmitted fungal endophyte Epichloë festucae enhances its resilience to biotic and abiotic stress. Agricultural benefits of endophyte infection can be increased by generating novel symbiotic associations through inoculating L. perenne with selected Epichloë strains. Natural symbioses have coevolved over long periods. Thus, artificial symbioses will probably not have static properties, but symbionts will coadapt over time improving the fitness of the association. Here we report for the first time on temporal changes in a novel association of Epichloë strain AR37 and the L. perenne cultivar Grasslands Samson. Over nine generations, a seed maintenance program had increased the endophyte seed transmission rates to > 95% (from an initial 76%). We observed an approximately fivefold decline in endophyte biomass concentration in vegetative tissues over time (between generations 2 and 9). This indicates strong selection pressure toward reducing endophyte-related fitness costs by reducing endophyte biomass, without compromising the frequency of endophyte transmission to seed. We observed no obvious changes in tillering and only minor transcriptomic changes in infected plants over time. Functional analysis of 40 plant genes, showing continuously decreasing expression over time, suggests that adaptation of host metabolism and defense mechanisms are important for increasing the fitness of this association, and possibly fitness of such symbioses in general. Our results indicate that fitness of novel associations is likely to improve over time and that monitoring changes in novel associations can assist in identifying key features of endophyte-mediated enhancement of host fitness.

Transcriptome profiling and environmental linkage to salinity across Salicornia europaea vegetation

BACKGROUND

Salicornia europaea, a succulent obligatory halophyte is the most salt-tolerant plant species in the world. It survives salt concentrations of more than 1 M. Therefore, it is a suitable model plant to identify genes involved in salt tolerance mechanisms that can be used for the improvement of crops. The changes in a plant's gene expression in response to abiotic stresses may depend on factors like soil conditions at the site, seasonality, etc. To date, experiments were performed to study the gene expression of S. europaea only under controlled conditions. Conversely, the present study investigates the transcriptome and physicochemical parameters of S. europaea shoots and roots from two different types of saline ecosystems growing under natural conditions.

RESULTS

The level of soil salinity was higher at the naturally saline site than at the anthropogenic saline site. The parameters such as EC_e, Na⁺, Cl^-, Ca⁺, SO₄^2- and HCO₃^- of the soils and plant organs significantly varied according to sites and seasons. We found that Na⁺ mainly accumulated in shoots, whereas K⁺ and Ca²⁺ levels were higher in roots throughout the growing period. Moreover, changes in S. europaea gene expression were more prominent in seasons, than sites and plant organs. The 30 differentially expressed genes included enzymes for synthesis of S-adenosyl methionine, CP47 of light-harvesting complex II, photosystem I proteins, Hsp70 gene, ATP-dependent Clp proteases, ribulose bisphosphate carboxylase/oxygenase (Rubisco), phenylalanine ammonia-lyase (PAL), cytochrome c oxidase (COX) and ATP synthase.

CONCLUSION

The comparisons made based on two seasons, plant organs and two different sites suggest the importance of seasonal variations in gene expression of S. europaea. We identify the genes that may play an important role in acclimation to season-dependent changes of salinity. The genes were involved in processes such as osmotic adjustment, energy metabolism and photosynthesis.

Breaking Free: The Genomics of Allopolyploidy-Facilitated Niche Expansion in White Clover

The merging of distinct genomes, allopolyploidization, is a widespread phenomenon in plants. It generates adaptive potential through increased genetic diversity, but examples demonstrating its exploitation remain scarce. White clover (Trifolium repens) is a ubiquitous temperate allotetraploid forage crop derived from two European diploid progenitors confined to extreme coastal or alpine habitats. We sequenced and assembled the genomes and transcriptomes of this species complex to gain insight into the genesis of white clover and the consequences of allopolyploidization. Based on these data, we estimate that white clover originated ∼15,000 to 28,000 years ago during the last glaciation when alpine and coastal progenitors were likely colocated in glacial refugia. We found evidence of progenitor diversity carryover through multiple hybridization events and show that the progenitor subgenomes have retained integrity and gene expression activity as they traveled within white clover from their original confined habitats to a global presence. At the transcriptional level, we observed remarkably stable subgenome expression ratios across tissues. Among the few genes that show tissue-specific switching between homeologous gene copies, we found flavonoid biosynthesis genes strongly overrepresented, suggesting an adaptive role of some allopolyploidy-associated transcriptional changes. Our results highlight white clover as an example of allopolyploidy-facilitated niche expansion, where two progenitor genomes, adapted and confined to disparate and highly specialized habitats, expanded to a ubiquitous global presence after glaciation-associated allopolyploidization.

Integrating a newly developed BAC-based physical mapping resource for Lolium perenne with a genome-wide association study across a L. perenne European ecotype collection identifies genomic contexts associated with agriculturally important traits

BACKGROUND AND AIMS

Lolium perenne (perennial ryegrass) is the most widely cultivated forage and amenity grass species in temperate areas worldwide and there is a need to understand the genetic architectures of key agricultural traits and crop characteristics that deliver wider environmental services. Our aim was to identify genomic regions associated with agriculturally important traits by integrating a bacterial artificial chromosome (BAC)-based physical map with a genome-wide association study (GWAS).

METHODS

BAC-based physical maps for L. perenne were constructed from ~212 000 high-information-content fingerprints using Fingerprint Contig and Linear Topology Contig software. BAC clones were associated with both BAC-end sequences and a partial minimum tiling path sequence. A panel of 716 L. perenne diploid genotypes from 90 European accessions was assessed in the field over 2 years, and genotyped using a Lolium Infinium SNP array. The GWAS was carried out using a linear mixed model implemented in TASSEL, and extended genomic regions associated with significant markers were identified through integration with the physical map.

KEY RESULTS

Between ~3600 and 7500 physical map contigs were derived, depending on the software and probability thresholds used, and integrated with ~35 k sequenced BAC clones to develop a resource predicted to span the majority of the L. perenne genome. From the GWAS, eight different loci were significantly associated with heading date, plant width, plant biomass and water-soluble carbohydrate accumulation, seven of which could be associated with physical map contigs. This allowed the identification of a number of candidate genes.

CONCLUSIONS

Combining the physical mapping resource with the GWAS has allowed us to extend the search for candidate genes across larger regions of the L. perenne genome and identified a number of interesting gene model annotations. These physical maps will aid in validating future sequence-based assemblies of the L. perenne genome.

Large Scale Screening of Epichloë Endophytes Infecting Schedonorus pratensis and Other Forage Grasses Reveals a Relation Between Microsatellite-Based Haplotypes and Loline Alkaloid Levels

Species belonging to the Festuca-Lolium complex are often naturally infected with endophytic fungi of genus Epichloë. Recent studies on endophytes have shown the beneficial roles of host-endophyte associations as protection against insect herbivores in agriculturally important grasses. However, large-scale screenings are crucial to identify animal friendly strains suitable for agricultural use. In this study we analyzed collected populations of meadow fescue (Schedonorus pratensis) from 135 different locations across Europe, 255 accessions from the United States Department of Agriculture and 96 accessions from The Nordic Genetic Resource Centre. The analysis also included representatives of S. arundinaceus, S. giganteus, and Lolium perenne. All plants were screened for the presence of Epichloë endophytes, resulting in a nursery of about 2500 infected plants from 176 different locations. Genetic diversity was investigated on 250 isolates using a microsatellite-based PCR fingerprinting assay at 7 loci, 5 of which were uncharacterized for these species. Phylogenetic and principal components analysis showed a strong interspecific genetic differentiation among isolates, and, with E. uncinata isolates, a small but significant correlation between genetic diversity and geographical effect (r = 0.227) was detected. Concentrations of loline alkaloids were measured in 218 infected meadow fescue plants. Average amount of total loline and the proportions of the single loline alkaloids differed significantly among endophyte haplotypes (P < 0.005). This study provides insight into endophyte genetic diversity and geographic variation in Europe and a reference database of allele sizes for fast discrimination of isolates. We also discuss the possibility of multiple hybridization events as a source of genetic and alkaloid variation observed in E. uncinata.

Overcoming challenges in variant calling: exploring sequence diversity in candidate genes for plant development in perennial ryegrass (Lolium perenne)

Revealing DNA sequence variation within the Lolium perenne genepool is important for genetic analysis and development of breeding applications. We reviewed current literature on plant development to select candidate genes in pathways that control agronomic traits, and identified 503 orthologues in L. perenne. Using targeted resequencing, we constructed a comprehensive catalogue of genomic variation for a L. perenne germplasm collection of 736 genotypes derived from current cultivars, breeding material and wild accessions. To overcome challenges of variant calling in heterogeneous outbreeding species, we used two complementary strategies to explore sequence diversity. First, four variant calling pipelines were integrated with the VariantMetaCaller to reach maximal sensitivity. Additional multiplex amplicon sequencing was used to empirically estimate an appropriate precision threshold. Second, a de novo assembly strategy was used to reconstruct divergent alleles for each gene. The advantage of this approach was illustrated by discovery of 28 novel alleles of LpSDUF247, a polymorphic gene co-segregating with the S-locus of the grass self-incompatibility system. Our approach is applicable to other genetically diverse outbreeding species. The resulting collection of functionally annotated variants can be mined for variants causing phenotypic variation, either through genetic association studies, or by selecting carriers of rare defective alleles for physiological analyses.

Pooled DNA sequencing to identify SNPs associated with a major QTL for bacterial wilt resistance in Italian ryegrass (Lolium multiflorum Lam.)

SNPs and candidate genes associated with bacterial wilt resistance in Italian ryegrass were identified by sequencing the parental plants and pooled F₁ progeny of a segregating population. Italian ryegrass (Lolium multiflorum Lam.) is one of the most important forage grass species in temperate regions. Its yield, quality and persistency can significantly be reduced by bacterial wilt, a serious disease caused by Xanthomonas translucens pv. graminis. Although a major QTL for bacterial wilt resistance has previously been reported, detailed knowledge on underlying genes and DNA markers to allow for efficient resistance breeding strategies is currently not available. We used pooled DNA sequencing to characterize a major QTL for bacterial wilt resistance of Italian ryegrass and to develop inexpensive sequence-based markers to efficiently target resistance alleles for marker-assisted recurrent selection. From the mapping population segregating for the QTL, DNA of 44 of the most resistant and 44 of the most susceptible F₁ individuals was pooled and sequenced using the Illumina HiSeq 2000 platform. Allele frequencies of 18 × 10⁶ single nucleotide polymorphisms (SNP) were determined in the resistant and susceptible pool. A total of 271 SNPs on 140 scaffold sequences of the reference parental genome showed significantly different allele frequencies in both pools. We converted 44 selected SNPs to KASP™ markers, genetically mapped these proximal to the major QTL and thus validated their association with bacterial wilt resistance. This study highlights the power of pooled DNA sequencing to efficiently target binary traits in biparental mapping populations. It delivers genome sequence data, SNP markers and potential candidate genes which will allow to implement marker-assisted strategies to fix bacterial wilt resistance in outcrossing breeding populations of Italian ryegrass.

De novo assembly of Agave sisalana transcriptome in response to drought stress provides insight into the tolerance mechanisms

Agave, monocotyledonous succulent plants, is endemic to arid regions of North America, exhibiting exceptional tolerance to their xeric environments. They employ various strategies to overcome environmental constraints, such as crassulacean acid metabolism, wax depositions, and protective leaf morphology. Genomic resources of Agave species have received little attention irrespective of their cultural, economic and ecological importance, which so far prevented the understanding of the molecular bases underlying their adaptations to the arid environment. In this study, we aimed to elucidate molecular mechanism(s) using transcriptome sequencing of A. sisalana. A de novo approach was applied to assemble paired-end reads. The expression study unveiled 3,095 differentially expressed unigenes between well-irrigated and drought-stressed leaf samples. Gene ontology and KEGG analysis specified a significant number of abiotic stress responsive genes and pathways involved in processes like hormonal responses, antioxidant activity, response to stress stimuli, wax biosynthesis, and ROS metabolism. We also identified transcripts belonging to several families harboring important drought-responsive genes. Our study provides the first insight into the genomic structure of A. sisalana underlying adaptations to drought stress, thus providing diverse genetic resources for drought tolerance breeding research.

SNP markers associated with body size and pelt length in American mink (Neovison vison)

Background

Identification of genes underlying production traits is a key aim of the mink research community. Recent availability of genomic tools have opened the possibility for faster genetic progress in mink breeding. Availability of mink genome assembly allows genome-wide association studies in mink.

Results

In this study, we used genotyping-by-sequencing to obtain single nucleotide polymorphism (SNP) genotypes of 2496 mink. After multiple rounds of filtering, we retained 28,336 high quality SNPs and 2352 individuals for a genome-wide association study (GWAS). We performed the first GWAS for body weight, behavior, along with 10 traits related to fur quality in mink.

Conclusions

Combining association results with existing functional information of genes and mammalian phenotype databases, we proposed WWC3, MAP2K4, SLC7A1 and USP22 as candidate genes for body weight and pelt length in mink.

Electronic supplementary material

The online version of this article (10.1186/s12863-018-0688-6) contains supplementary material, which is available to authorized users.

The Value of Expanding the Training Population to Improve Genomic Selection Models in Tetraploid Potato

Genomic selection (GS) is becoming increasingly applicable to crops as the genotyping costs continue to decrease, which makes it an attractive alternative to traditional selective breeding based on observed phenotypes. With genome-wide molecular markers, selection based on predictions from genotypes can be made in the absence of direct phenotyping. The reliability of predictions depends strongly on the number of individuals used for training the predictive algorithms, particularly in a highly genetically diverse organism such as potatoes; however, the relationship between the individuals also has an enormous impact on prediction accuracy. Here we have studied genomic prediction in three different panels of potato cultivars, varying in size, design, and phenotypic profile. We have developed genomic prediction models for two important agronomic traits of potato, dry matter content and chipping quality. We used genotyping-by-sequencing to genotype 1,146 individuals and generated genomic prediction models from 167,637 markers to calculate genomic estimated breeding values with genomic best linear unbiased prediction. Cross-validated prediction correlations of 0.75-0.83 and 0.39-0.79 were obtained for dry matter content and chipping quality, respectively, when combining the three populations. These prediction accuracies were similar to those obtained when predicting performance within each panel. In contrast, but not unexpectedly, predictions across populations were generally lower, 0.37-0.71 and 0.28-0.48 for dry matter content and chipping quality, respectively. These predictions are not limited by the number of markers included, since similar prediction accuracies could be obtained when using merely 7,800 markers (<5%). Our results suggest that predictions across breeding populations in tetraploid potato are presently unreliable, but that individual prediction models within populations can be combined in an additive fashion to obtain high quality prediction models relevant for several breeding populations.

Optimized Use of Low-Depth Genotyping-by-Sequencing for Genomic Prediction Among Multi-Parental Family Pools and Single Plants in Perennial Ryegrass (Lolium perenne L.)

Ryegrass single plants, bi-parental family pools, and multi-parental family pools are often genotyped, based on allele-frequencies using genotyping-by-sequencing (GBS) assays. GBS assays can be performed at low-coverage depth to reduce costs. However, reducing the coverage depth leads to a higher proportion of missing data, and leads to a reduction in accuracy when identifying the allele-frequency at each locus. As a consequence of the latter, genomic relationship matrices (GRMs) will be biased. This bias in GRMs affects variance estimates and the accuracy of GBLUP for genomic prediction (GBLUP-GP). We derived equations that describe the bias from low-coverage sequencing as an effect of binomial sampling of sequence reads, and allowed for any ploidy level of the sample considered. This allowed us to combine individual and pool genotypes in one GRM, treating pool-genotypes as a polyploid genotype, equal to the total ploidy-level of the parents of the pool. Using simulated data, we verified the magnitude of the GRM bias at different coverage depths for three different kinds of ryegrass breeding material: individual genotypes from single plants, pool-genotypes from F₂ families, and pool-genotypes from synthetic varieties. To better handle missing data, we also tested imputation procedures, which are suited for analyzing allele-frequency genomic data. The relative advantages of the bias-correction and the imputation of missing data were evaluated using real data. We examined a large dataset, including single plants, F₂ families, and synthetic varieties genotyped in three GBS assays, each with a different coverage depth, and evaluated them for heading date, crown rust resistance, and seed yield. Cross validations were used to test the accuracy using GBLUP approaches, demonstrating the feasibility of predicting among different breeding material. Bias-corrected GRMs proved to increase predictive accuracies when compared with standard approaches to construct GRMs. Among the imputation methods we tested, the random forest method yielded the highest predictive accuracy. The combinations of these two methods resulted in a meaningful increase of predictive ability (up to 0.09). The possibility of predicting across individuals and pools provides new opportunities for improving ryegrass breeding schemes.

Transcript profiling of a bitter variety of narrow-leafed lupin to discover alkaloid biosynthetic genes

Lupins (Lupinus spp.) are nitrogen-fixing legumes that accumulate toxic alkaloids in their protein-rich beans. These anti-nutritional compounds belong to the family of quinolizidine alkaloids (QAs), which are of interest to the pharmaceutical and chemical industries. To unleash the potential of lupins as protein crops and as sources of QAs, a thorough understanding of the QA pathway is needed. However, only the first enzyme in the pathway, lysine decarboxylase (LDC), is known. Here, we report the transcriptome of a high-QA variety of narrow-leafed lupin (L. angustifolius), obtained using eight different tissues and two different sequencing technologies. In addition, we present a list of 33 genes that are closely co-expressed with LDC and that represent strong candidates for involvement in lupin alkaloid biosynthesis. One of these genes encodes a copper amine oxidase able to convert the product of LDC, cadaverine, into 1-piperideine, as shown by heterologous expression and enzyme assays. Kinetic analysis revealed a low KM value for cadaverine, supporting a role as the second enzyme in the QA pathway. Our transcriptomic data set represents a crucial step towards the discovery of enzymes, transporters, and regulators involved in lupin alkaloid biosynthesis.

Genomic prediction of starch content and chipping quality in tetraploid potato using genotyping-by-sequencing

KEY MESSAGE

Genomic prediction models for starch content and chipping quality show promising results, suggesting that genomic selection is a feasible breeding strategy in tetraploid potato. Genomic selection uses genome-wide molecular markers to predict performance of individuals and allows selections in the absence of direct phenotyping. It is regarded as a useful tool to accelerate genetic gain in breeding programs, and is becoming increasingly viable for crops as genotyping costs continue to fall. In this study, we have generated genomic prediction models for starch content and chipping quality in tetraploid potato to facilitate varietal development. Chipping quality was evaluated as the colour of a potato chip after frying following cold induced sweetening. We used genotyping-by-sequencing to genotype 762 offspring, derived from a population generated from biparental crosses of 18 tetraploid parents. Additionally, 74 breeding clones were genotyped, representing a test panel for model validation. We generated genomic prediction models from 171,859 single-nucleotide polymorphisms to calculate genomic estimated breeding values. Cross-validated prediction correlations of 0.56 and 0.73 were obtained within the training population for starch content and chipping quality, respectively, while correlations were lower when predicting performance in the test panel, at 0.30-0.31 and 0.42-0.43, respectively. Predictions in the test panel were slightly improved when including representatives from the test panel in the training population but worsened when preceded by marker selection. Our results suggest that genomic prediction is feasible, however, the extremely high allelic diversity of tetraploid potato necessitates large training populations to efficiently capture the genetic diversity of elite potato germplasm and enable accurate prediction across the entire spectrum of elite potatoes. Nonetheless, our results demonstrate that GS is a promising breeding strategy for tetraploid potato.

In Silico Identification of Candidate Genes for Fertility Restoration in Cytoplasmic Male Sterile Perennial Ryegrass (Lolium perenne L.)

Perennial ryegrass (Lolium perenne L.) is widely used for forage production in both permanent and temporary grassland systems. To increase yields in perennial ryegrass, recent breeding efforts have been focused on strategies to more efficiently exploit heterosis by hybrid breeding. Cytoplasmic male sterility (CMS) is a widely applied mechanism to control pollination for commercial hybrid seed production and although CMS systems have been identified in perennial ryegrass, they are yet to be fully characterized. Here, we present a bioinformatics pipeline for efficient identification of candidate restorer of fertility (Rf) genes for CMS. From a high-quality draft of the perennial ryegrass genome, 373 pentatricopeptide repeat (PPR) genes were identified and classified, further identifying 25 restorer of fertility-like PPR (RFL) genes through a combination of DNA sequence clustering and comparison to known Rf genes. This extensive gene family was targeted as the majority of Rf genes in higher plants are RFL genes. These RFL genes were further investigated by phylogenetic analyses, identifying three groups of perennial ryegrass RFLs. These three groups likely represent genomic regions of active RFL generation and identify the probable location of perennial ryegrass PPR-Rf genes. This pipeline allows for the identification of candidate PPR-Rf genes from genomic sequence data and can be used in any plant species. Functional markers for PPR-Rf genes will facilitate map-based cloning of Rf genes and enable the use of CMS as an efficient tool to control pollination for hybrid crop production.

Accuracy of Genomic Prediction in a Commercial Perennial Ryegrass Breeding Program

The implementation of genomic selection (GS) in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses) in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L.) using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN) families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E) interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.

On the Accuracy of Genomic Selection

Genomic selection is focused on prediction of breeding values of selection candidates by means of high density of markers. It relies on the assumption that all quantitative trait loci (QTLs) tend to be in strong linkage disequilibrium (LD) with at least one marker. In this context, we present theoretical results regarding the accuracy of genomic selection, i.e., the correlation between predicted and true breeding values. Typically, for individuals (so-called test individuals), breeding values are predicted by means of markers, using marker effects estimated by fitting a ridge regression model to a set of training individuals. We present a theoretical expression for the accuracy; this expression is suitable for any configurations of LD between QTLs and markers. We also introduce a new accuracy proxy that is free of the QTL parameters and easily computable; it outperforms the proxies suggested in the literature, in particular, those based on an estimated effective number of independent loci (M_e). The theoretical formula, the new proxy, and existing proxies were compared for simulated data, and the results point to the validity of our approach. The calculations were also illustrated on a new perennial ryegrass set (367 individuals) genotyped for 24,957 single nucleotide polymorphisms (SNPs). In this case, most of the proxies studied yielded similar results because of the lack of markers for coverage of the entire genome (2.7 Gb).

Transcriptome Analysis of an Insecticide Resistant Housefly Strain: Insights about SNPs and Regulatory Elements in Cytochrome P450 Genes

Background

Insecticide resistance in the housefly, Musca domestica, has been investigated for more than 60 years. It will enter a new era after the recent publication of the housefly genome and the development of multiple next generation sequencing technologies. The genetic background of the xenobiotic response can now be investigated in greater detail. Here, we investigate the 454-pyrosequencing transcriptome of the spinosad-resistant 791spin strain in relation to the housefly genome with focus on P450 genes.

Results

The de novo assembly of clean reads gave 35,834 contigs consisting of 21,780 sequences of the spinosad resistant strain. The 3,648 sequences were annotated with an enzyme code EC number and were mapped to 124 KEGG pathways with metabolic processes as most highly represented pathway. One hundred and twenty contigs were annotated as P450s covering 44 different P450 genes of housefly. Eight differentially expressed P450s genes were identified and investigated for SNPs, CpG islands and common regulatory motifs in promoter and coding regions. Functional annotation clustering of metabolic related genes and motif analysis of P450s revealed their association with epigenetic, transcription and gene expression related functions. The sequence variation analysis resulted in 12 SNPs and eight of them found in cyp6d1. There is variation in location, size and frequency of CpG islands and specific motifs were also identified in these P450s. Moreover, identified motifs were associated to GO terms and transcription factors using bioinformatic tools.

Conclusion

Transcriptome data of a spinosad resistant strain provide together with genome data fundamental support for future research to understand evolution of resistance in houseflies. Here, we report for the first time the SNPs, CpG islands and common regulatory motifs in differentially expressed P450s. Taken together our findings will serve as a stepping stone to advance understanding of the mechanism and role of P450s in xenobiotic detoxification.

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.

Estimating genomic heritabilities at the level of family-pool samples of perennial ryegrass using genotyping-by-sequencing

By using the genotyping-by-sequencing method, it is feasible to characterize genomic relationships directly at the level of family pools and to estimate genomic heritabilities from phenotypes scored on family-pools in outbreeding species. Genotyping-by-sequencing (GBS) has recently become a promising approach for characterizing plant genetic diversity on a genome-wide scale. We use GBS to extend the concept of heritability beyond individuals by genotyping family-pool samples by GBS and computing genomic relationship matrices (GRMs) and genomic heritabilities directly at the level of family-pools from pool-frequencies obtained by sequencing. The concept is of interest for species where breeding and phenotyping is not done at the individual level but operates uniquely at the level of (multi-parent) families. As an example we demonstrate the approach using a set of 990 two-parent F2 families of perennial ryegrass (Lolium Perenne). The families were phenotyped as a family-unit in field plots for heading date and crown rust resistance. A total of 728 K single nucleotide polymorphism (SNP) variants were available and were divided in groups of different sequencing depths. GRMs based on GBS data showed diagonal values biased upwards at low sequencing depth, while off-diagonals were little affected by the sequencing depth. Using variants with high sequencing depth, genomic heritability for crown rust resistance was 0.33, and for heading date 0.22, and these genomic heritabilities were biased downwards when using variants with lower sequencing depth. Broad sense heritabilities were 0.61 and 0.66, respectively. Underestimation of genomic heritability at lower sequencing depth was confirmed with simulated data. We conclude that it is feasible to use GBS to describe relationships between family-pools and to estimate genomic heritability directly at the level of F2 family-pool samples, but estimates are biased at low sequencing depth.

A Gene Encoding a DUF247 Domain Protein Cosegregates with the S Self-Incompatibility Locus in Perennial Ryegrass

The grass family (Poaceae), the fourth largest family of flowering plants, encompasses the most economically important cereal, forage, and energy crops, and exhibits a unique gametophytic self-incompatibility (SI) mechanism that is controlled by at least two multiallelic and independent loci, S and Z. Despite intense research efforts over the last six decades, the genes underlying S and Z remain uncharacterized. Here, we report a fine-mapping approach to identify the male component of the S-locus in perennial ryegrass (Lolium perenne L.) and provide multiple evidence that a domain of unknown function 247 (DUF247) gene is involved in its determination. Using a total of 10,177 individuals from seven different mapping populations segregating for S, we narrowed the S-locus to a genomic region containing eight genes, the closest recombinant marker mapping at a distance of 0.016 cM. Of the eight genes cosegregating with the S-locus, a highly polymorphic gene encoding for a protein containing a DUF247 was fully predictive of known S-locus genotypes at the amino acid level in the seven mapping populations. Strikingly, this gene showed a frameshift mutation in self-compatible darnel (Lolium temulentum L.), whereas all of the self-incompatible species of the Festuca-Lolium complex were predicted to encode functional proteins. Our results represent a major step forward toward understanding the gametophytic SI system in one of the most important plant families and will enable the identification of additional components interacting with the S-locus.

Population Structure, Genetic Variation, and Linkage Disequilibrium in Perennial Ryegrass Populations Divergently Selected for Freezing Tolerance

Low temperature is one of the abiotic stresses seriously affecting the growth of perennial ryegrass (Lolium perenne L.), and freezing tolerance is a complex trait of major agronomical importance in northern and central Europe. Understanding the genetic control of freezing tolerance would aid in the development of cultivars of perennial ryegrass with improved adaptation to frost. The plant material investigated in this study was an experimental synthetic population derived from pair-crosses among five European perennial ryegrass genotypes, representing adaptations to a range of climatic conditions across Europe. A total number of 80 individuals (24 of High frost [HF]; 29 of Low frost [LF], and 27 of Unselected [US]) from the second generation of the two divergently selected populations and an unselected (US) control population were genotyped using 278 genome-wide SNPs derived from perennial ryegrass transcriptome sequences. Our studies investigated the genetic diversity among the three experimental populations by analysis of molecular variance and population structure, and determined that the HF and LF populations are very divergent after selection for freezing tolerance, whereas the HF and US populations are more similar. Linkage disequilibrium (LD) decay varied across the seven chromosomes and the conspicuous pattern of LD between the HF and LF population confirmed their divergence in freezing tolerance. Furthermore, two F st outlier methods; finite island model (fdist) by LOSITAN and hierarchical structure model using ARLEQUIN, both detected six loci under directional selection. These outlier loci are most probably linked to genes involved in freezing tolerance, cold adaptation, and abiotic stress. These six candidate loci under directional selection for freezing tolerance might be potential marker resources for breeding perennial ryegrass cultivars with improved freezing tolerance.

Genomic dissection and prediction of heading date in perennial ryegrass

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).

A synteny-based draft genome sequence of the forage grass Lolium perenne

Here we report the draft genome sequence of perennial ryegrass (Lolium perenne), an economically important forage and turf grass species that is widely cultivated in temperate regions worldwide. It is classified along with wheat, barley, oats and Brachypodium distachyon in the Pooideae sub-family of the grass family (Poaceae). Transcriptome data was used to identify 28,455 gene models, and we utilized macro-co-linearity between perennial ryegrass and barley, and synteny within the grass family, to establish a synteny-based linear gene order. The gametophytic self-incompatibility mechanism enables the pistil of a plant to reject self-pollen and therefore promote out-crossing. We have used the sequence assembly to characterize transcriptional changes in the stigma during pollination with both compatible and incompatible pollen. Characterization of the pollen transcriptome identified homologs to pollen allergens from a range of species, many of which were expressed to very high levels in mature pollen grains, and are potentially involved in the self-incompatibility mechanism. The genome sequence provides a valuable resource for future breeding efforts based on genomic prediction, and will accelerate the development of new varieties for more productive grasslands.

Changes in Lolium perenne transcriptome during cold acclimation in two genotypes adapted to different climatic conditions

BACKGROUND

Activation of numerous protective mechanisms during cold acclimation is important for the acquisition of freezing tolerance in perennial ryegrass (Lolium perenne L.). To elucidate the molecular mechanisms of cold acclimation in two genotypes ('Veyo' and 'Falster') of perennial ryegrass from distinct geographical origins, we performed transcriptome profiling during cold acclimation using RNA-Seq.

METHODS

We cold-acclimated plants from both genotypes in controlled conditions for a period of 17 days and isolated Total RNA at various time points for high throughput sequencing using Illumina technology. RNA-seq reads were aligned to genotype specific references to identify transcripts with significant changes in expression during cold acclimation.

RESULTS

The genes induced were involved in protective mechanisms such as cell response to abiotic stimulus, signal transduction, redox homeostasis, plasma membrane and cell wall modifications, and carbohydrate metabolism in both genotypes. 'Falster' genotype, adapted to cold climates, showed a stronger transcriptional differentiation during cold acclimation, and more differentially expressed transcripts related to stress, signal transduction, response to abiotic stimulus, and metabolic processes compared to 'Veyo'. 'Falster' genotype also showed an induction of more transcripts with sequence homology to fructosyltransferase genes (FTs) and a higher fold induction of fructan in response to low-temperature stress. The circadian rhythm network was perturbed in the 'Veyo' genotype adapted to warmer climates.

CONCLUSION

In this study, the differentially expressed genes during cold acclimation, potentially involved in numerous protective mechanisms, were identified in two genotypes of perennial ryegrass from distinct geographical origins. The observation that the circadian rhythm network was perturbed in 'Veyo' during cold acclimation may point to a low adaptability of 'Veyo' to low temperature stresses. This study also revealed the transcriptional mechanisms underlying carbon allocation towards fructan biosynthesis in perennial ryegrass.

Clade classification of monolignol biosynthesis gene family members reveals target genes to decrease lignin in Lolium perenne

In monocots, lignin content has a strong impact on the digestibility of the cell wall fraction. Engineering lignin biosynthesis requires a profound knowledge of the role of paralogues in the multigene families that constitute the monolignol biosynthesis pathway. We applied a bioinformatics approach for genome-wide identification of candidate genes in Lolium perenne that are likely to be involved in the biosynthesis of monolignols. More specifically, we performed functional subtyping of phylogenetic clades in four multigene families: 4CL, COMT, CAD and CCR. Essential residues were considered for functional clade delineation within these families. This classification was complemented with previously published experimental evidence on gene expression, gene function and enzymatic activity in closely related crops and model species. This allowed us to assign functions to novel identified L. perenne genes, and to assess functional redundancy among paralogues. We found that two 4CL paralogues, two COMT paralogues, three CCR paralogues and one CAD gene are prime targets for genetic studies to engineer developmentally regulated lignin in this species. Based on the delineation of sequence conservation between paralogues and a first analysis of allelic diversity, we discuss possibilities to further study the roles of these paralogues in lignin biosynthesis, including expression analysis, reverse genetics and forward genetics, such as association mapping. We propose criteria to prioritise paralogues within multigene families and certain SNPs within these genes for developing genotyping assays or increasing power in association mapping studies. Although L. perenne was the target of the analyses presented here, this functional subtyping of phylogenetic clades represents a valuable tool for studies investigating monolignol biosynthesis genes in other monocot species.

Candidate gene association mapping for winter survival and spring regrowth in perennial ryegrass

Perennial ryegrass (Lolium perenne L.) is a widely cultivated cool-season grass species because of its high quality for forage and turf. Susceptibility to freezing damage limits its further use in temperate zones. The objective of this study was to identify candidate genes significantly associated with winter survival and spring regrowth in a global collection of 192 perennial ryegrass accessions. Significant differences in winter survival (WS), percentage of canopy green cover (CGC), chlorophyll index (Chl), and normalized difference vegetation index (NDVI) were found among accessions. After controlling population structure, LpLEA3 encoding a late embryogenesis abundant group 3 protein and LpCAT encoding a catalase were associated with CGC and Chl, while LpMnSOD encoding a magnesium superoxide dismutase and LpChl Cu-ZnSOD encoding a chlorophyll copper-zinc superoxide dismutase were associated with NDVI or Chl. Significant association was also discovered between C-repeat binding factor LpCBF1b and WS. Three sequence variations identified in LpCAT, LpMnSOD, and LpChl Cu-ZnSOD were synonymous substitutions, whereas one pair of adjacent single nucleotide polymorphisms (SNPs) in LpLEA3 and one SNP in LpCBF1b resulted in amino acid change. The results demonstrated that allelic variation in LpLEA3 and LpCBF1b was closely related to winter survival and spring regrowth in perennial ryegrass.

Fructan metabolism and changes in fructan composition during cold acclimation in perennial ryegrass

Perennial ryegrass (Lolium perenne L.) produces high levels of fructans as a mixture of oligosaccharides and polysaccharides with different degrees of polymerization (DP). The present study describes the analysis of the compositional changes in the full spectrum of fructans, fructan distribution between above ground biomass (top) and the roots, and the transcription of candidate genes involved in fructan metabolism during cold acclimation in perennial ryegrass variety "Veyo" and ecotype "Falster" from distinct geographical origins. We observed changes in fructan composition and induction of low-DP fructans, especially DP = 4, in both the top and the roots of "Veyo" and "Falster" in response to low-temperature stress. The accumulation of DP > 50 fructans was only apparent in the top tissues where the Lp1-FFT expression is higher compared to the roots in both "Veyo" and "Falster." Our results also show the accumulation and depolymerization of fructans with different DP, together with the induction of genes encoding fructosyltransferases and fructan exohydrolases in both "Veyo" and "Falster" during cold acclimation, supporting the hypothesis that fructan synthesis and depolymerization occurring simultaneously. The ecotype "Falster," adapted to cold climates, increased total fructan content and produced more DP > 7 fructans in the roots than the variety "Veyo," adapted to warmer climates. This indicates that high-DP fructan accumulation in roots may be an adaptive trait for plant recovery after abiotic stresses.

Comparative transcriptome analysis within the Lolium/Festuca species complex reveals high sequence conservation

Background

The Lolium-Festuca complex incorporates species from the Lolium genera and the broad leaf fescues, both belonging to the subfamily Pooideae. This subfamily also includes wheat, barley, oat and rye, making it extremely important to world agriculture. Species within the Lolium-Festuca complex show very diverse phenotypes, and many of them are related to agronomically important traits. Analysis of sequenced transcriptomes of these non-model species may shed light on the molecular mechanisms underlying this phenotypic diversity.

Results

We have generated de novo transcriptome assemblies for four species from the Lolium-Festuca complex, ranging from 52,166 to 72,133 transcripts per assembly. We have also predicted a set of proteins and validated it with a high-confidence protein database from three closely related species (H. vulgare, B. distachyon and O. sativa). We have obtained gene family clusters for the four species using OrthoMCL and analyzed their inferred phylogenetic relationships. Our results indicate that VRN2 is a candidate gene for differentiating vernalization and non-vernalization types in the Lolium-Festuca complex. Grouping of the gene families based on their BLAST identity enabled us to divide ortholog groups into those that are very conserved and those that are more evolutionarily relaxed. The ratio of the non-synonumous to synonymous substitutions enabled us to pinpoint protein sequences evolving in response to positive selection. These proteins may explain some of the differences between the more stress tolerant Festuca, and the less stress tolerant Lolium species.

Conclusions

Our data presents a comprehensive transcriptome sequence comparison between species from the Lolium-Festuca complex, with the identification of potential candidate genes underlying some important phenotypical differences within the complex (such as VRN2). The orthologous genes between the species have a very high %id (91,61%) and the majority of gene families were shared for all of them. It is likely that the knowledge of the genomes will be largely transferable between species within the complex.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1447-y) contains supplementary material, which is available to authorized users.

Vernalization mediated changes in the Lolium perenne transcriptome

Vernalization is a key requirement for the induction of flowering in perennial ryegrass (Lolium perenne L.). The transcriptome of two genotypes with contrasting vernalization requirement was studied during primary (vernalization and short day conditions) and secondary induction (higher temperature and long day conditions) using an RNA-Seq approach. This revealed transcripts with expression profiles indicative of a role in floral induction, both in the promotion and repression of flowering. We observed similarities and specific differences between the two genotypes related to cold response, carbohydrate metabolism, and photoperiod regulation. Components of the photoperiod pathway showed regulation during vernalization, pointing to possible interactions between elements of the photoperiod and vernalization pathways. The results provide a global picture of the processes ongoing during the transition from vegetative to reproductive phase of perennial ryegrass genotypes with and without a vernalization requirement.

De novo assembly of the perennial ryegrass transcriptome using an RNA-Seq strategy

BACKGROUND

Perennial ryegrass is a highly heterozygous outbreeding grass species used for turf and forage production. Heterozygosity can affect de-Bruijn graph assembly making de novo transcriptome assembly of species such as perennial ryegrass challenging. Creating a reference transcriptome from a homozygous perennial ryegrass genotype can circumvent the challenge of heterozygosity. The goals of this study were to perform RNA-sequencing on multiple tissues from a highly inbred genotype to develop a reference transcriptome. This was complemented with RNA-sequencing of a highly heterozygous genotype for SNP calling.

RESULT

De novo transcriptome assembly of the inbred genotype created 185,833 transcripts with an average length of 830 base pairs. Within the inbred reference transcriptome 78,560 predicted open reading frames were found of which 24,434 were predicted as complete. Functional annotation found 50,890 transcripts with a BLASTp hit from the Swiss-Prot non-redundant database, 58,941 transcripts with a Pfam protein domain and 1,151 transcripts encoding putative secreted peptides. To evaluate the reference transcriptome we targeted the high-affinity K+ transporter gene family and found multiple orthologs. Using the longest unique open reading frames as the reference sequence, 64,242 single nucleotide polymorphisms were found. One thousand sixty one open reading frames from the inbred genotype contained heterozygous sites, confirming the high degree of homozygosity.

CONCLUSION

Our study has developed an annotated, comprehensive transcriptome reference for perennial ryegrass that can aid in determining genetic variation, expression analysis, genome annotation, and gene mapping.

Association studies using family pools of outcrossing crops based on allele-frequency estimates from DNA sequencing

We propose a method in which GBS data can be conveniently analyzed without calling genotypes. F2 families are frequently used in breeding of outcrossing species, for instance to obtain trait measurements on plots. We propose to perform association studies by obtaining a matching "family genotype" from sequencing a pooled sample of the family, and to directly use allele frequencies computed from sequence read-counts for mapping. We show that, under additivity assumptions, there is a linear relationship between the family phenotype and family allele frequency, and that a regression of family phenotype on family allele frequency will estimate twice the allele substitution effect at a locus. However, medium-to-low sequencing depth causes underestimation of the true allele substitution effect. An expression for this underestimation is derived for the case that parents are diploid, such that F2 families have up to four dosages of every allele. Using simulation studies, estimation of the allele effect from F2-family pools was verified and it was shown that the underestimation of the allele effect is correctly described. The optimal design for an association study when sequencing budget would be fixed is obtained using large sample size and lower sequence depth, and using higher SNP density (resulting in higher LD with causative mutations) and lower sequencing depth. Therefore, association studies using genotyping by sequencing are optimal and use low sequencing depth per sample. The developed framework for association studies using allele frequencies from sequencing can be modified for other types of family pools and is also directly applicable for association studies in polyploids.

Flow sorting and sequencing meadow fescue chromosome 4F

The analysis of large genomes is hampered by a high proportion of repetitive DNA, which makes the assembly of short sequence reads difficult. This is also the case in meadow fescue (Festuca pratensis), which is known for good abiotic stress resistance and has been used in intergeneric hybridization with ryegrasses (Lolium spp.) to produce Festulolium cultivars. In this work, we describe a new approach to analyze the large genome of meadow fescue, which involves the reduction of sample complexity without compromising information content. This is achieved by dissecting the genome to smaller parts: individual chromosomes and groups of chromosomes. As the first step, we flow sorted chromosome 4F and sequenced it by Illumina with approximately 50× coverage. This provided, to our knowledge, the first insight into the composition of the fescue genome, enabled the construction of the virtual gene order of the chromosome, and facilitated detailed comparative analysis with the sequenced genomes of rice (Oryza sativa), Brachypodium distachyon, sorghum (Sorghum bicolor), and barley (Hordeum vulgare). Using GenomeZipper, we were able to confirm the collinearity of chromosome 4F with barley chromosome 4H and the long arm of chromosome 5H. Several new tandem repeats were identified and physically mapped using fluorescence in situ hybridization. They were found as robust cytogenetic markers for karyotyping of meadow fescue and ryegrass species and their hybrids. The ability to purify chromosome 4F opens the way for more efficient analysis of genomic loci on this chromosome underlying important traits, including freezing tolerance. Our results confirm that next-generation sequencing of flow-sorted chromosomes enables an overview of chromosome structure and evolution at a resolution never achieved before.

Evidence for adaptive evolution of low-temperature stress response genes in a Pooideae grass ancestor

Adaptation to temperate environments is common in the grass subfamily Pooideae, suggesting an ancestral origin of cold climate adaptation. Here, we investigated substitution rates of genes involved in low-temperature-induced (LTI) stress responses to test the hypothesis that adaptive molecular evolution of LTI pathway genes was important for Pooideae evolution. Substitution rates and signatures of positive selection were analyzed using 4330 gene trees including three warm climate-adapted species (maize (Zea mays), sorghum (Sorghum bicolor), and rice (Oryza sativa)) and five temperate Pooideae species (Brachypodium distachyon, wheat (Triticum aestivum), barley (Hordeum vulgare), Lolium perenne and Festuca pratensis). Nonsynonymous substitution rate differences between Pooideae and warm habitat-adapted species were elevated in LTI trees compared with all trees. Furthermore, signatures of positive selection were significantly stronger in LTI trees after the rice and Pooideae split but before the Brachypodium divergence (P < 0.05). Genome-wide heterogeneity in substitution rates was also observed, reflecting divergent genome evolution processes within these grasses. Our results provide evidence for a link between adaptation to cold habitats and adaptive evolution of LTI stress responses in early Pooideae evolution and shed light on a poorly understood chapter in the evolutionary history of some of the world's most important temperate crops.