Genetic-geographic correlation revealed across a broad European ecotypic sample of perennial ryegrass (Lolium perenne) using array-based SNP genotyping

Lower grass stomatal conductance under elevated CO2 can decrease transpiration and evapotranspiration rates despite carbon fertilization

Anthropogenic increase in carbon dioxide (CO2) affects plant physiology. Plant responses to elevated CO2 typically include: (1) enhanced photosynthesis and increased primary productivity due to carbon fertilization and (2) suppression of leaf transpiration due to CO2-driven decrease in stomatal conductance. The combined effect of these responses on the total plant transpiration and on evapotranspiration (ET) has a wide range of implications on local, regional, and global hydrological cycles, and thus needs to be better understood. Here, we investigated the net effect of CO2-driven perennial ryegrass (Lolium perenne) physiological responses on transpiration and evapotranspiration by integrating physiological and hydrological (water budget) methods, under a controlled environment. Measurements of the net photosynthetic rate, stomatal conductance, transpiration rate, leaf mass per area, aboveground biomass, and water balance components were recorded. Measured variables under elevated CO2 were compared with those of ambient CO2. As expected, our results show that elevated CO2 significantly decreases whole-plant transpiration rates (38% lower in the final week) which is a result of lower stomatal conductance (57% lower in the final week) despite a slight increase in aboveground biomass. Additionally, there was an overall decline in evapotranspiration (ET) under elevated CO2, indicating the impact of CO2-mediated suppression of transpiration on the overall water balance. Although studies with larger sample sizes are needed for more robust conclusions, our findings have significant implications for global environmental change. Reductions in ET from ryegrass-dominated grasslands and pastures could increase soil moisture and groundwater recharge, potentially leading to increased surface runoff and flooding.

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.

Characterization and practical use of self-compatibility in outcrossing grass species

BACKGROUND

Self-incompatibility (SI) systems prevent self-fertilization in several species of Poaceae, many of which are economically important forage, bioenergy and turf grasses. Self-incompatibility ensures cross-pollination and genetic diversity but restricts the ability to fix useful genetic variation. In most inbred crops it is possible to develop high-performing homozygous parental lines by self-pollination, which then enables the creation of F1 hybrid varieties with higher performance, a phenomenon known as heterosis. The inability to fully exploit heterosis in outcrossing grasses is partially responsible for lower levels of improvement in breeding programmes compared with inbred crops. However, SI can be overcome in forage grasses to create self-compatible populations. This is generating interest in understanding the genetical basis of self-compatibility (SC), its significance for reproductive strategies and its exploitation for crop improvement, especially in the context of F1 hybrid breeding.

SCOPE

We review the literature on SI and SC in outcrossing grass species. We review the currently available genomic tools and approaches used to discover and characterize novel SC sources. We discuss opportunities barely explored for outcrossing grasses that SC facilitates. Specifically, we discuss strategies for wide SC introgression in the context of the Lolium-Festuca complex and the use of SC to develop immortalized mapping populations for the dissection of a wide range of agronomically important traits. The germplasm available is a valuable practical resource and will aid understanding the basis of inbreeding depression and hybrid vigour in key temperate forage grass species.

CONCLUSIONS

A better understanding of the genetic control of additional SC loci offers new insight into SI systems, their evolutionary origins and their reproductive significance. Heterozygous outcrossing grass species that can be readily selfed facilitate studies of heterosis. Moreover, SC introduction into a range of grass species will enable heterosis to be exploited in innovative ways in genetic improvement programmes.

A comparison of shared patterns of differential gene expression and gene ontologies in response to water-stress in roots and leaves of four diverse genotypes of Lolium and Festuca spp. temperate pasture grasses

Ryegrasses (Lolium spp.) and fescues (Festuca spp.) are closely related and widely cultivated perennial forage grasses. As such, resilience in the face of abiotic stresses is an important component of their traits. We have compared patterns of differentially expressed genes (DEGs) in roots and leaves of two perennial ryegrass genotypes and a single genotype of each of a festulolium (predominantly Italian ryegrass) and meadow fescue with the onset of water stress, focussing on overall patterns of DEGs and gene ontology terms (GOs) shared by all four genotypes. Plants were established in a growing medium of vermiculite watered with nutrient solution. Leaf and root material were sampled at 35% (saturation) and, as the medium dried, at 15%, 5% and 1% estimated water contents (EWCs) and RNA extracted. Differential gene expression was evaluated comparing the EWC sampling points from RNAseq data using a combination of analysis methods. For all genotypes, the greatest numbers of DEGs were identified in the 35/1 and 5/1 comparisons in both leaves and roots. In total, 566 leaf and 643 root DEGs were common to all 4 genotypes, though a third of these leaf DEGs were not regulated in the same up/down direction in all 4 genotypes. For roots, the equivalent figure was 1% of the DEGs. GO terms shared by all four genotypes were often enriched by both up- and down-regulated DEGs in the leaf, whereas generally, only by either up- or down-regulated DEGs in the root. Overall, up-regulated leaf DEGs tended to be more genotype-specific than down-regulated leaf DEGs or root DEGs and were also associated with fewer GOs. On average, only 5–15% of the DEGs enriching common GO terms were shared by all 4 genotypes, suggesting considerable variation in DEGs between related genotypes in enacting similar biological processes.

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.

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.

An investigation of genotype-phenotype association in a festulolium forage grass population containing genome-spanning Festuca pratensis chromosome segments in a Lolium perenne background

Alien chromosome introgression is used for the transfer of beneficial traits in plant breeding. For temperate forage grasses, much of the work in this context has focused on species within the ryegrasses (Lolium spp.) and the closely related fescues (Festuca spp.) particularly with a view to combining high forage quality with reliability and enhanced environmental services. We have analysed a L. perenne (perennial ryegrass) population containing the majority of a F. pratensis (meadow fescue) genome as introgressed chromosome segments to identify a) marker-trait associations for nutrient use and abiotic stress response across the family, and b) to assess the effects of introgression of F. pratensis genomic regions on phenotype. Using container-based assays and a system of flowing solution culture, we looked at phenotype responses, including root growth, to nitrogen and phosphorus status in the growing medium and abiotic stresses within this festulolium family. A number of significant marker/trait associations were identified across the family for root biomass on chromosomes 2, 3 and 5 and for heading date on chromosome 2. Of particular interest was a region on chromosome 2 associated with increased root biomass in phosphorus-limited conditions derived from one of the L. perenne parents. A genotype containing F. pratensis chromosome 4 as a monosomic introgression showed increased tiller number, shoot and root growth and genotypes with F. pratensis chromosome segment introgressions at different ends of chromosome 4 exhibited differential phenotypes across a variety of test conditions. There was also a general negative correlation between the extent of the F. pratensis genome that had been introgressed and root-related trait performances. We conclude that 1) the identification of alleles affecting root growth has potential application in forage grass breeding and, 2) F. pratensis introgressions can enhance quantitative traits, however, introgression can also have more general negative effects.

Aluminium toxicity and phosphate deficiency activates antioxidant systems and up-regulates expression of phosphate transporters gene in ryegrass (Lolium perenne L.) plants

Soil acidity, associated with aluminium (Al) toxicity and low phosphorus (P) availability, is considered the most important problem for agricultural production. Even though the Al-P interaction has been widely investigated, the impact of P-nutrition on Al-toxicity still remains controversial and poorly understood. To elucidate further insights into the underlying mechanisms of this interaction in ryegrass (Lolium perenne L.), P uptake, antioxidant responses and the gene expression of phosphate transporters were determined. Two ryegrass cultivars with different Al resistances, the Al-tolerant Nui cultivar and the Al-sensitive Expo cultivar were hydroponically grown under low (16 μM) and optimal (100 μM) P doses for 16 days. After P treatments, plants were exposed to Al doses (0 and 200 μM) under acidic conditions (pH 4.8) for 24 h. Al and P accumulation were higher in the roots of Nui than that of Expo. Moreover, lower Al accumulation was found in shoots of Nui independent of P supplies. Oxidative stress induced by Al-toxicity and P-deficiency was more severe in the Al-sensitive Expo. Expression levels of L. perenne phosphate transporters were higher in Nui than they were in Expo. While LpPHT1 expression was up-regulated by P deficiency and Al toxicity in both cultivars, LpPHT4 expression only increased in the Al-tolerant cultivar. This report shows that the higher Al-tolerance of Nui can be attributed to a greater antioxidant system under both P conditions. The observation of higher P and Al accumulation in roots of Nui might indicate that the Al-tolerance of Nui is a consequence of Al immobilization by P mediated by the high expression of phosphate transporters.

Revolution in Genotyping Platforms for Crop Improvement

In the past decade, the application of high-throughput sequencing to crop genotyping has given rise to novel platforms capable of genotyping tens of thousands of genome-wide DNA markers. Coupled with the decreasing costs of sequencing, this rapid increase in markers allows accelerated and highly accurate genotyping of entire crop populations and diversity sets using single nucleotide polymorphisms (SNPs). These revolutionary advances accelerate crop improvement by facilitating a more precise connection of phenotype to genotype through association studies, linkage mapping and diversity analysis. The platforms driving the advances in genotyping are array technologies and genotyping by sequencing (GBS) methods, which include both low-coverage whole genome resequencing (skim sequencing) and reduced representation sequencing (RRS) approaches. Here, we outline and compare these genotyping platforms and provide a perspective on the promising future of crop genotyping. While SNP arrays provide high quality, simple handling, and unchallenging analysis, the lower cost of RRS and the greater data volume produced by skim sequencing suggest that use of GBS will become more prevalent in crop genomics as sequencing costs decrease and data analysis becomes more streamlined. Graphical Abstract.

Crop Breeding Chips and Genotyping Platforms: Progress, Challenges, and Perspectives

There is a rapidly rising trend in the development and application of molecular marker assays for gene mapping and discovery in field crops and trees. Thus far, more than 50 SNP arrays and 15 different types of genotyping-by-sequencing (GBS) platforms have been developed in over 25 crop species and perennial trees. However, much less effort has been made on developing ultra-high-throughput and cost-effective genotyping platforms for applied breeding programs. In this review, we discuss the scientific bottlenecks in existing SNP arrays and GBS technologies and the strategies to develop targeted platforms for crop molecular breeding. We propose that future practical breeding platforms should adopt automated genotyping technologies, either array or sequencing based, target functional polymorphisms underpinning economic traits, and provide desirable prediction accuracy for quantitative traits, with universal applications under wide genetic backgrounds in crops. The development of such platforms faces serious challenges at both the technological level due to cost ineffectiveness, and the knowledge level due to large genotype-phenotype gaps in crop plants. It is expected that such genotyping platforms will be achieved in the next ten years in major crops in consideration of (a) rapid development in gene discovery of important traits, (b) deepened understanding of quantitative traits through new analytical models and population designs, (c) integration of multi-layer -omics data leading to identification of genes and pathways responsible for important breeding traits, and (d) improvement in cost effectiveness of large-scale genotyping. Crop breeding chips and genotyping platforms will provide unprecedented opportunities to accelerate the development of cultivars with desired yield potential, quality, and enhanced adaptation to mitigate the effects of climate change.

A Novel Multivariate Approach to Phenotyping and Association Mapping of Multi-Locus Gametophytic Self-Incompatibility Reveals S, Z, and Other Loci in a Perennial Ryegrass (Poaceae) Population

Self-incompatibility (SI) is a mechanism that many flowering plants employ to prevent fertilisation by self- and self-like pollen ensuring heterozygosity and hybrid vigour. Although a number of single locus mechanisms have been characterised in detail, no multi-locus systems have been fully elucidated. Historically, examples of the genetic analysis of multi-locus SI, to make analysis tractable, are either made on the progeny of bi-parental crosses, where the number of alleles at each locus is restricted, or on crosses prepared in such a way that only one of the SI loci segregates. Perennial ryegrass (Lolium perenne L.) possesses a well-documented two locus (S and Z) gametophytic incompatibility system. A more universal, realistic proof of principle study was conducted in a perennial ryegrass population in which allelic and non-allelic diversity was not artificially restricted. A complex pattern of pollinations from a diallel cross was revealed which could not possibly be interpreted easily per se, even with an already established genetic model. Instead, pollination scores were distilled into principal component scores described as Compatibility Components (CC1-CC3). These were then subjected to a conventional genome-wide association analysis. CC1 associated with markers on linkage groups (LGs) 1, 2, 3, and 6, CC2 exclusively with markers in a genomic region on LG 2, and CC3 with markers on LG 1. BLAST alignment with the Brachypodium physical map revealed highly significantly associated markers with peak associations with genes adjacent and four genes away from the chromosomal locations of candidate SI genes, S- and Z-DUF247, respectively. Further significant associations were found in a Brachypodium distachyon chromosome 3 region, having shared synteny with Lolium LG 1, suggesting further SI loci linked to S or extensive micro-re-arrangement of the genome between B. distachyon and L. perenne. Significant associations with gene sequences aligning with marker sequences on Lolium LGs 3 and 6 were also identified. We therefore demonstrate the power of a novel association genetics approach to identify the genes controlling multi-locus gametophytic SI systems and to identify novel loci potentially involved in already established SI systems.

Germplasm dynamics: the role of ecotypic diversity in shaping the patterns of genetic variation in Lolium perenne

Perennial ryegrass (Lolium perenne) is the most widely grown temperate grass species globally. Intensive plant breeding in ryegrass compared to many other crops species is a relatively recent exercise (last 100 years) and provides an interesting experimental system to trace the extent, impact and trajectory of undomesticated ecotypic variation represented in modern ryegrass cultivars. To explore germplasm dynamics in Lolium perenne, 2199 SNPs were genotyped in 716 ecotypes sampled from 90 European locations together with 249 cultivars representing 33 forage/amenity accessions. In addition three pseudo-cross mapping populations (450 individual recombinants) were genotyped to create a consensus genetic linkage map. Multivariate analyses revealed strong differentiation between cultivars with a small proportion of the ecotypic variation captured in improved cultivars. Ryegrass cultivars generated as part of a recurrent selection programme (RSP) are strongly associated with a small number of geographically localised Italian ecotypes which were among the founders of the RSP. Changes in haplotype frequency revealed signatures of selection in genes putatively involved in water-soluble carbohydrate (WSC) accumulation (a trait selected in the RSP). Retrospective analysis of germplasm in breeding programmes (germplasm dynamics) provides an experimental framework for the identification of candidate genes for novel traits such as WSC accumulation in ryegrass.

Implementation of Genomic Prediction in Lolium perenne (L.) Breeding Populations

Perennial ryegrass (Lolium perenne L.) is one of the most widely grown forage grasses in temperate agriculture. In order to maintain and increase its usage as forage in livestock agriculture, there is a continued need for improvement in biomass yield, quality, disease resistance, and seed yield. Genetic gain for traits such as biomass yield has been relatively modest. This has been attributed to its long breeding cycle, and the necessity to use population based breeding methods. Thanks to recent advances in genotyping techniques there is increasing interest in genomic selection from which genomically estimated breeding values are derived. In this paper we compare the classical RRBLUP model with state-of-the-art machine learning techniques that should yield themselves easily to use in GS and demonstrate their application to predicting quantitative traits in a breeding population of L. perenne. Prediction accuracies varied from 0 to 0.59 depending on trait, prediction model and composition of the training population. The BLUP model produced the highest prediction accuracies for most traits and training populations. Forage quality traits had the highest accuracies compared to yield related traits. There appeared to be no clear pattern to the effect of the training population composition on the prediction accuracies. The heritability of the forage quality traits was generally higher than for the yield related traits, and could partly explain the difference in accuracy. Some population structure was evident in the breeding populations, and probably contributed to the varying effects of training population on the predictions. The average linkage disequilibrium between adjacent markers ranged from 0.121 to 0.215. Higher marker density and larger training population closely related with the test population are likely to improve the prediction accuracy.