Discovery of interesting new polymorphisms in a sugar beet (elite [Formula: see text] exotic) progeny by comparison with an elite panel.

KEY MESSAGE: The comparison of QTL detection performed on an elite panel and an (elite [Formula: see text] exotic) progeny shows that introducing exotic germplasm into breeding programs can bring new interesting allelic diversity. Selection of stable varieties producing the highest amount of extractable sugar per hectare (ha), resistant to diseases, and respecting environmental criteria is undoubtedly the main target for sugar beet breeding. As sodium, potassium, and [Formula: see text]-amino nitrogen in sugar beets are the impurities that have the biggest negative impact on white sugar extraction, it is interesting to reduce their concentration in further varieties. However, domestication history and strong selection pressures have affected the genetic diversity needed to achieve this goal. In this study, quantitative trait locus (QTL) detection was performed on two populations, an (elite [Formula: see text] exotic) sugar beet progeny and an elite panel, to find potentially new interesting regions brought by the exotic accession. The three traits linked with impurities content were studied. Some QTLs were detected in both populations, the majority in the elite panel because of most statistical power. Some of the QTLs were colocated and had favorable effect in the progeny since the exotic allele was linked with a decrease in the impurity content. A few number of favorable QTLs were detected in the progeny, only. Consequently, introgressing exotic genetic material into sugar beet breeding programs can allow the incorporation of new interesting alleles.

Predicting genotype environmental range from genome-environment associations.

Genome-environment association methods aim to detect genetic markers associated with environmental variables. The detected associations are usually analysed separately to identify the genomic regions involved in local adaptation. However, a recent study suggests that single-locus associations can be combined and used in a predictive way to estimate environmental variables for new individuals on the basis of their genotypes. Here, we introduce an original approach to predict the environmental range (values and upper and lower limits) of species genotypes from the genetic markers significantly associated with those environmental variables in an independent set of individuals. We illustrate this approach to predict aridity in a database constituted of 950 individuals of wild beets and 299 individuals of cultivated beets genotyped at 14,409 random single nucleotide polymorphisms (SNPs). We detected 66 alleles associated with aridity and used them to calculate the fraction (I) of aridity-associated alleles in each individual. The fraction I correctly predicted the values of aridity in an independent validation set of wild individuals and was then used to predict aridity in the 299 cultivated individuals. Wild individuals had higher median values and a wider range of values of aridity than the cultivated individuals, suggesting that wild individuals have higher ability to resist to stress-aridity conditions and could be used to improve the resistance of cultivated varieties to aridity.

Insights into the genetic relationships among plants of Beta section Beta using SNP markers.

KEY MESSAGE: Using a much higher number of SNP markers and larger sample sizes than all the previous studies, we characterized the genetic relationships among wild and cultivated plants of section Beta. We analyzed the genetic variation of Beta section Beta, which includes wild taxa (Beta macrocarpa, B. patula, B. vulgaris subsp. adanensis and B. vulgaris subsp. maritima) and cultivars (fodder beet, sugar beet, garden beet, leaf beet, and swiss chards), using 9724 single nucleotide polymorphism markers. The analyses conducted at the individual level without a priori groups confirmed the strong differentiation of B. macrocarpa and B. vulgaris subsp. adanensis from the other taxa. B. vulgaris subsp. maritima showed a complex genetic structure partly following a geographical pattern, which confounded the differences between this taxon and the cultivated varieties. Cultivated varieties were structured into three main groups: garden beets, fodder and sugar beets, and leaf beets and swiss chards. The genetic structure described here will be helpful to correctly estimate linkage disequilibrium and to test for statistical associations between genetic markers and environmental variables.

Taxonomic, spatial and adaptive genetic variation of Beta section Beta.

KEY MESSAGE: The genetic variation of Beta section Beta is structured into four taxonomic and spatial clusters. There are significant associations between molecular markers and environmental variables. ABSTRACT: We investigated the genetic diversity of Beta section Beta, which includes the wild and cultivated relatives of the sugar beet. The taxa included in the study were: Beta vulgaris subsp. maritima, B. vulgaris subsp. adanensis, B. macrocarpa, B. patula and B. vulgaris subsp. vulgaris (garden beet, leaf beet and swiss chards). We collected 1264 accessions originating from the entire distribution area of these taxa and genotyped them for 4436 DArT markers (DArTs). We showed that the genetic variation of these accessions is structured into four taxonomic and spatial clusters: (1) samples of Beta macrocarpa, (2) samples of Beta vulgaris subsp. adanensis, (3) Mediterranean and Asian samples and (4) Atlantic and Northern European samples. These last two clusters were mainly composed of samples of Beta vulgaris subsp. maritima. We investigated in deeper detail the genetic structure of B. vulgaris subsp. maritima, which constituted the majority (80%) of the wild samples. This subspecies exhibited a clinal genetic variation from South-East to North-West. We detected some markers significantly associated to environmental variables in B. vulgaris subsp. maritima. These associations are interpreted as results of natural selection. The variable most often involved in the associations was annual mean temperature. Therefore, these markers can be useful for the development of frost-tolerant winter beets and drought-tolerant rain-fed beets.

Impact of Variety and Agronomic Factors on Crude Protein and Total Lysine in Chicory; N(ε)-Carboxymethyl-lysine-Forming Potential during Drying and Roasting.

During the heat treatment of coffee and its substitutes some compounds potentially deleterious to health are synthesized by the Maillard reaction. Among these, N(ε)-carboxymethyl-lysine (CML) was detected at high levels in coffee substitutes. The objective of this study was to evaluate the impact of changes in agricultural practice on the lysine content present in chicory roots and try to limit CML formation during roasting. Of the 24 varieties analyzed, small variations in lysine content were observed, 213 ± 8 mg/100 g dry matter (DM). The formation of lysine tested in five commercial varieties was affected by the nitrogen treatment with mean levels of 176 ± 2 mg/100 g DM when no fertilizer was added and 217 ± 7 mg/100 g DM with a nitrogen supply of 120 kg/ha. The lysine content of fresh roots was significantly correlated to the concentration of CML formed in roasted roots (r = 0.51; p < 0.0001; n = 76).

Developmental genes have pleiotropic effects on plant morphology and source capacity, eventually impacting on seed protein content and productivity in pea.

Increasing pea (Pisum sativum) seed nutritional value and particularly seed protein content, while maintaining yield, is an important challenge for further development of this crop. Seed protein content and yield are complex and unstable traits, integrating all the processes occurring during the plant life cycle. During filling, seeds are the main sink to which assimilates are preferentially allocated at the expense of vegetative organs. Nitrogen seed demand is satisfied partly by nitrogen acquired by the roots, but also by nitrogen remobilized from vegetative organs. In this study, we evaluated the respective roles of nitrogen source capacity and sink strength in the genetic variability of seed protein content and yield. We showed in eight genotypes of diverse origins that both the maximal rate of nitrogen accumulation in the seeds and nitrogen source capacity varied among genotypes. Then, to identify the genetic factors responsible for seed protein content and yield variation, we searched for quantitative trait loci (QTL) for seed traits and for indicators of sink strength and source nitrogen capacity. We detected 261 QTL across five environments for all traits measured. Most QTL for seed and plant traits mapped in clusters, raising the possibility of common underlying processes and candidate genes. In most environments, the genes Le and Afila, which control internode length and the switch between leaflets and tendrils, respectively, determined plant nitrogen status. Depending on the environment, these genes were linked to QTL of seed protein content and yield, suggesting that source-sink adjustments depend on growing conditions.