Genomic prediction has mostly been used in single environment contexts, largely ignoring genotype x environment interaction, which greatly affects the performance of plants. However, in the last decade, prediction models including marker x environment (MxE) interaction have been developed. We evaluated the potential of genomic prediction in red clover (Trifolium pratense L.) using field trial data from five European locations, obtained in the Horizon 2020 EUCLEG project. Three models were compared: (1) single environment (SingleEnv), (2) across environment (AcrossEnv), (3) marker x environment interaction (MxE). Annual dry matter yield (DMY) gave the highest predictive ability (PA). Joint analyses of DMY from years 1 and 2 from each location varied from 0.87 in Britain and Switzerland in year 1, to 0.40 in Serbia in year 2. Overall, crude protein (CP) was predicted poorly. PAs for date of flowering (DOF), however ranged from 0.87 to 0.67 for Britain and Switzerland, respectively. Across the three traits, the MxE model performed best and the AcrossEnv worst, demonstrating that including marker x environment effects can improve genomic prediction in red clover. Leaving out accessions from specific regions or from specific breeders’ material in the cross validation tended to reduce PA, but the magnitude of reduction depended on trait, region and breeders’ material, indicating that population structure contributed to the high PAs observed for DMY and DOF. Testing the genomic estimated breeding values on new phenotypic data from Sweden showed that DMY training data from Britain gave high PAs in both years (0.43–0.76), while DMY training data from Switzerland gave high PAs only for year 1 (0.70–0.87). The genomic predictions we report here underline the potential benefits of incorporating MxE interaction in multi-environment trials and could have perspectives for identifying markers with effects that are stable across environments, and markers with environment-specific effects.

Yield is the most complex trait to improve crop production, and identifying the genetic determinants for high yield is a major issue in breeding new varieties. In faba bean (Vicia faba L.), quantitative trait loci (QTLs) have previously been detected in studies of biparental mapping populations, but the genes controlling the main trait components remain largely unknown. In this study, we investigated for the first time the genetic control of six faba bean yield-related traits: shattering (SH), pods per plant (PP), seeds per pod (SP), seeds per plant (SPL), 100-seed weight (HSW), and plot yield (PY), using a genome-wide association study (GWAS) on a worldwide collection of 352 homozygous faba bean accessions with the aim of identifying markers associated with them. Phenotyping was carried out in field trials at three locations (Spain, United Kingdom, and Serbia) over 2 years. The faba bean panel was genotyped with the Affymetrix faba bean SNP-chip yielding 22,867 SNP markers. The GWAS analysis identified 112 marker–trait associations (MTAs) in 97 candidate genes, distributed over the six faba bean chromosomes. Eight MTAs were detected in at least two environments, and five were associated with multiple traits. The next step will be to validate these candidates in different genetic backgrounds to provide resources for marker-assisted breeding of faba bean yield.

IntroductionChocolate spot, caused by the ascomycete fungus Botrytis fabae, is a devastating foliar disease and a major constraint on the quality and yield of faba beans (Vicia faba). The use of fungicides is the primary strategy for controlling the disease. However, high levels of partial genetic resistance have been identified and can be exploited to mitigate the disease.MethodsThe partially resistant V. faba cultivar Maris Bead and susceptible Egyptian accession ig70726 were crossed, and a genetic mapping population of 184 individuals was genotyped in the F2 generation and screened for resistance to B. fabae infection in the F3, F5, and F6 generations in a series of field experiments. A high-density linkage map of V. faba containing 3897 DArT markers spanning 1713.7 cM was constructed.ResultsMultiple candidate quantitative trait loci (QTLs) in 11 separate regions of the V. faba genome were identified; some on chromosomes 2, 3, and 6 overlapped with loci previously linked to resistance to Ascochyta leaf and pod blight caused by the necrotrophic fungus Ascochyta fabae. A transcriptomics experiment was conducted at 18 h post-inoculation in seedlings of both parents of the mapping population, identifying several differentially expressed transcripts potentially involved in early stage defence against B. fabae, including cell-wall associated protein kinases, NLR genes, and genes involved in metabolism and response to reactive oxygen species.DiscussionThis study identified several novel candidate QTLs in the V. faba genome that contribute to partial resistance to chocolate spot, but differences between growing seasons highlighted the importance of multi-year phenotyping experiments when searching for candidate QTLs for partial resistance.

Phenotypic and genotypic characterization were performed to assess heritability, variability, and seed yield stability of pea genotypes used in breeding to increase the pea production area. A European pea diversity panel, including genotypes from North America, Asia, and Australia consisting of varieties, breeding lines, pea, and landraces was examined in 2019 and 2020 in Serbia and Belgium using augmented block design. The highest heritability was for thousand seed weight; the highest coefficient of variation was for seed yield. The highest positive correlation was between number of seeds per plant and number of pods per plant; the highest negative correlation was between seed yield and protein content. Hierarchical clustering separated pea germplasm based on use and type. Different Principal component analysis grouping of landraces, breeding lines, and varieties, as well as forage types and garden and dry peas, confirms that there was an apparent decrease in similarity between the genotypes, which can be explained by their different purposes. Pea breeding should be focused on traits with consistent heritability and a positive effect on seed yield when selecting high-yielding genotypes, and on allowing for more widespread use of pea in various agricultural production systems.

Biparental recombinant inbred line (RIL) populations are sets of genetically stable lines and have a simple population structure that facilitates the dissection of the genetics of interesting traits. On the other hand, populations derived from multiparent intercrosses combine both greater diversity and higher numbers of recombination events than RILs. Here, we describe a simple population structure: a three-way recombinant inbred population combination. This structure was easy to produce and was a compromise between biparental and multiparent populations. We show that this structure had advantages when analyzing cultivar crosses, and could achieve a mapping resolution of a few genes.

Red clover (Trifolium pratense L.) is a highly adaptable forage crop for temperate livestock agriculture. Genetic variation can be identified, via molecular techniques, and used to assess diversity among populations that may otherwise be indistinguishable. Here we have used genotyping by sequencing (GBS) to determine the genetic variation and population structure in red clover natural populations from Europe and Asia, and varieties or synthetic populations. Cluster analysis differentiated the collection into four large regional groups: Asia, Iberia, UK, and Central Europe. The five varieties clustered with the geographical area from which they were derived. Two methods (BayeScan and Samβada) were used to search for outlier loci indicating signatures of selection. A total of 60 loci were identified by both methods, but no specific genomic region was highlighted. The rate of decay in linkage disequilibrium was fast, and no significant evidence of any bottlenecks was found. Phenotypic analysis showed that a more prostrate and spreading growth habit was predominantly found among populations from Iberia and the UK. A genome wide association study identified a single nucleotide polymorphism (SNP) located in a homologue of the VEG2 gene from pea, associated with flowering time. The identification of genetic variation within the natural populations is likely to be useful for enhancing the breeding of red clover in the future.