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.

Breeding patterns and cultivated beets origins by genetic diversity and linkage disequilibrium analyses.

KEY MESSAGE: Genetic diversity in worldwide population of beets is strongly affected by the domestication history, and the comparison of linkage disequilibrium in worldwide and elite populations highlights strong selection pressure. Genetic relationships and linkage disequilibrium (LD) were evaluated in a set of 2035 worldwide beet accessions and in another of 1338 elite sugar beet lines, using 320 and 769 single nucleotide polymorphisms, respectively. The structures of the populations were analyzed using four different approaches. Within the worldwide population, three of the methods gave a very coherent picture of the population structure. Fodder beet and sugar beet accessions were grouped together, separated from garden beets and sea beets, reflecting well the origins of beet domestication. The structure of the elite panel, however, was less stable between clustering methods, which was probably because of the high level of genetic mixing in breeding programs. For the linkage disequilibrium analysis, the usual measure (r (2)) was used, and compared with others that correct for population structure and relatedness (r S (2) , r V (2) , r VS (2)). The LD as measured by r (2) persisted beyond 10 cM within the elite panel and fell below 0.1 after less than 2 cM in the worldwide population, for almost all chromosomes. With correction for relatedness, LD decreased under 0.1 by 1 cM for almost all chromosomes in both populations, except for chromosomes 3 and 9 within the elite panel. In these regions, the larger extent of LD could be explained by strong selection pressure.

High throughput phenotyping dataset related to seed and seedling traits of sugar beet genotypes.

Several seed and seedling traits are measured to evaluate germination and emergence potential in relation with environmental conditions. More generally, these traits are also measured in the field of ecology as simple traits that can be correlated to other adaptative traits more difficult to measure on adult plants, as for example traits of the rooting system. Methods were developed for deep high throughput phenotyping of hundreds of genotypes from dry seed to the end of heterotrophic growth. The present dataset comes from a project on genotyping and phenotyping of populations of genotypes, with different geographic and genetic origins so as to increase genotypic diversity of sugar beet in terms of germination and early growth traits, evaluated at low temperatures. Data were collected in relation to the creation of the first sugar beet crop ontology. This dataset corresponds to the first automated phenotyping of a population of 198 genotypes and 4 commercial control varieties and is hosted on INRAE public depository under the reference number doi.org/10.15,454/AKNF4Q. The equipment and methods presented here are available on a phenotyping platform opened to collaborative research and adaptable for specific services for characterizing thousands of genotypes on different crops or other species. The phenotyping values can also be linked to genomic information to study the genetic determinism of the trait values.