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International audience; GBS markers at the population level were used to study the genetic structure of lucerne in a set of 395 accessions from Europe, North and South America and China. More than 100K SNP without missing data were obtained. The structure revealed a certain genetic distance between European and American accessions, with a continuous variation between these groups. Contrastingly, Chinese accessions were genetically separated from the other accessions. This analysis is an invitation to go more deeply into a phenotypic analysis of these genetic resources to exploit them in breeding.

International audience; GBS is an efficient genotyping tool for heterozygous and polyploid species, yet the fraction of missing data, inherent to the method, may be detrimental to genetic analyses. We tested several restriction enzymes to choose the ones that were likely to provide the maximum number of loci with little missing data considering a certain sequencing effort. For lucerne and cocksfoot, the enzymes that met the target of about 10 000 loci were the combination of PstI-MseI for lucerne and PstI for cocksfoot. 1 066 lucerne accessions were genotyped with PstI-MseI, and more than 200 000 SNP with less than 5% missing data were obtained. Based on these results, we recommend performing such a test to optimize GBS genotyping efforts in forage species.

International audience; Genomic prediction has proven its efficiency in numerous animal and plant species. In this study, we used diverse lucerne varieties and populations to test the predicting ability of genomic prediction. Several parameters, such as the number of markers, the population size and the addition of QTL effects, were tested for their effect on the quality of prediction. Based on a large number of SNPs (227 K) obtained by GBS and phenotypes observed in different locations, our results showed a good quality of predicting ability for dry matter yield, ADF (acid detergent fiber) and protein content, especially with a large training population size (around 0.6). The predicting ability is improved by the integration of QTL information directly in the model (above 0.8). A reduction of number of markers (less than 100K) did not alter much the predictive ability. Our results show an accurate prediction of the phenotype of populations via genomic prediction models that could speed up the creation of new lucerne varieties.

In breeding programs, balancing short-term genetic gain and loss of diversity per generation is essential to sustain a long-term genetic response. Depending on the dynamic of the species, the acceptable trade-off will be different. One of the most common and successful tools to achieve this management is the Optimal Contribution Selection (OCS), which readily mathematically formulate the trade-off between genetic gain and coancestry. However, OCS only accounts for the next generation gain and diversity, which can lead to suboptimality given the uncertainties of random mating and segregation. In this paper, we have extended the OCS by conveniently integrating a way to promote certain parental pairs, so that this method can account for the next t+2 generation. In the study case of Populus nigra , fully phenotyped and SNP array genotyped, we have shown that (i) a non negligible part of the long-term success of a breeding strategy depends on the implemented mating strategy, and (ii) favoring a compensatory mating can accelerate the selection without compromising the future diversity.

Relationship between the sequencing depth and imputation quality variables at individual level. On the top of the diagonal: Pearson’s correlations. The distribution of each variable is shown on the diagonal. On the bottom of the diagonal: the bivariate scatter plots. (PDF 58.3 kb)

Relationship between the proportion of alleles correctly imputed by each leave-one-out individual (Propi) and the lower bound individual proportion of SNP correctly imputed lbPropi).The different colors correspond to the different individual classes in the mating regimes, and each point represents the values for one chromosome and one individual. (PDF 11.1 kb)

Variation of the three different estimates of imputation quality at the SNP level (Props (Green), lbProps (Purple), cProps (Orange)), as a function of different classes of minor allele frequency (FreqOri). (PDF 42.3 kb)

National audience; Genome-wide evaluation (GWE) is expected to bring substantial benefits to the genetic improvement of perennials like poplar. Firstly, because current phenotypic evaluation is lengthy, costly and complex for the species. Secondly, because identifying poplar clonal varieties rely on a costly built-up of large segregation families from which to draw the best candidates combining favourable alleles with additive and non-additive effects.The present study provide preliminary assessments of the feasibility of GWE in a highly monitored subset of the French black poplar breeding pedigree. The training subset comprised a factorial mating design involving 6 parents and 1 known grand-parents and 261 individual records. Recorded traits were growth in the form of tree circumference and height, and architecture assessments taken as branch angle. Patterns of environmental heterogeneity in the trials were carefully taken into account at the individual tree level, by implementing autoregressive and splinebased two-dimensional smoothing surfaces into the evaluation model. All individuals have been genotyped thanks to a recently developed 12K SNP chip, which produced in our pedigree 7812 usable SNPs. Missing genotyping values, which amounted to 1.7% of data, were imputed by the FImpute software. Several genomic best linear unbiased predictors (G-BLUP) models were applied using GS3 software.Results provided prediction abilities for each trait obtained from a cross-validation approach. Accuracies of these predictions differ according to architecture and heritability of these traits. The benefits of imputation and environmental heterogeneity adjustments are discussed at the light of these results, together with the impacts that a GWE based selection would have on the relatedness among candidates compared to a pedigree-based approach.

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