Genomic distances reveal relationships of wild and cultivated beets.

Cultivated beets (Beta vulgaris ssp. vulgaris), including sugar beet, rank among the most important crops. The wild ancestor of beet crops is the sea beet Beta vulgaris ssp. maritima. Species and subspecies of wild beets are readily crossable with cultivated beets and are thus available for crop improvement. To study genomic relationships in the genus Beta, we sequence and analyse 606 beet genomes, encompassing sugar beet, sea beet, B. v. adanensis, B. macrocarpa, and B. patula. We observe two genetically distinct groups of sea beets, one from the Atlantic coast and the other from the Mediterranean area. Genomic comparisons based on k-mers identify sea beets from Greece as the closest wild relatives of sugar beet, suggesting that domestication of the ancestors of sugar beet may be traced to this area. Our work provides comprehensive insight into the phylogeny of wild and cultivated beets and establishes a framework for classification of further accessions of unknown (sub-)species assignment.

Early-stage sugar beet taproot development is characterized by three distinct physiological phases.

Despite the agronomic importance of sugar beet (Beta vulgaris L.), the early-stage development of its taproot has only been poorly investigated. Thus, the mechanisms that determine growth and sugar accumulation in sugar beet are largely unknown. In the presented study, a physiological characterization of early-stage sugar beet taproot development was conducted. Activities were analyzed for fourteen key enzymes of carbohydrate metabolism in developing taproots over the first 80 days after sowing. In addition, we performed in situ localizations of selected carbohydrate-metabolic enzyme activities, anatomical investigations, and quantifications of soluble carbohydrates, hexose phosphates, and phytohormones. Based on the accumulation dynamics of biomass and sucrose, as well as on anatomical parameters, the early phase of taproot development could be subdivided into three stages-prestorage, transition, secondary growth and sucrose accumulation stage-each of which was characterized by distinct metabolic and phytohormonal signatures. The enzyme activity signatures corresponding to these stages were also shown to be robustly reproducible in experiments conducted in two additional locations. The results from this physiological phenotyping approach contribute to the identification of the key regulators of sugar beet taproot development and open up new perspectives for sugar beet crop improvement concerning both physiological marker-based breeding and biotechnological approaches.

Hybridity has a greater effect than paternal genome dosage on heterosis in sugar beet (Beta vulgaris).

BACKGROUND: The phenomenon of heterosis is critical to plant breeding and agricultural productivity. Heterosis occurs when F1 hybrid offspring display quantitative improvements in traits to levels that do not occur in the parents. Increasing the genome dosage (i.e. ploidy level) of F1 offspring can contribute to heterosis effects. Sugar beet (Beta vulgaris) provides a model for investigating the relative effects of genetic hybridity and genome dosage on heterosis. Sugar beet lines of different ploidy levels were crossed to generate diploid and triploid F1 offspring to investigate the effect of; (1) paternal genome dosage increase on F1 heterosis, and; (2) homozygous versus heterozygous tetraploid male parents on F1 triploid heterosis. A range of traits of agronomic and commercial importance were analyzed for the extent of heterosis effects observed in the F1 offspring. RESULTS: Comparisons of parental lines to diploid (EA, EB) and triploid (EAA, EBB) F1 hybrids for total yield, root yield, and sugar yield indicated that there was no effect of paternal genome dosage increases on heterosis levels, indicating that hybridity is the main contributor to the heterosis levels observed. For all traits measured (apart from seed viability), F1 triploid hybrids derived from heterozygous tetraploid male parents displayed equivalent levels of heterosis as F1 triploid hybrids generated with homozygous tetraploid male parents, suggesting that heterosis gains in F1 triploids do not arise by simply increasing the extent of multi-locus heterozygosity in sugar beet F1 offspring. CONCLUSIONS: Overall, our study indicates that; (1) increasing the paternal genome dosage does not enhance heterosis in F1 hybrids, and; (2) increasing multi-locus heterozygosity using highly heterozygous paternal genomes to generate F1 triploid hybrids does not enhance heterosis. Our findings have implications for the design of future F1 hybrid improvement programs for sugar beet.

Reliable in silico identification of sequence polymorphisms and their application for extending the genetic map of sugar beet (Beta vulgaris).

Molecular markers are a highly valuable tool for creating genetic maps. Like in many other crops, sugar beet (Beta vulgaris L.) breeding is increasingly supported by the application of such genetic markers. Single nucleotide polymorphism (SNP) based markers have a high potential for automated analysis and high-throughput genotyping. We developed a bioinformatics workflow that uses Sanger and 2nd-generation sequence data for detection, evaluation and verification of new transcript-associated SNPs from sugar beet. RNAseq data from one parent of an established mapping population were produced by 454-FLX sequencing and compared to Sanger ESTs derived from the other parent. The workflow established for SNP detection considers the quality values of both types of reads, provides polymorphic alignments as well as selection criteria for reliable SNP detection and allows painless generation of new genetic markers within genes. We obtained a total of 14,323 genic SNPs and InDels. According to empirically optimised settings for the quality parameters, we classified these SNPs into four usability categories. Validation of a subset of the in silico detected SNPs by genotyping the mapping population indicated a high success rate of the SNP detection. Finally, a total of 307 new markers were integrated with existing data into a new genetic map of sugar beet which offers improved resolution and the integration of terminal markers.

The genome of the recently domesticated crop plant sugar beet (Beta vulgaris).

Sugar beet (Beta vulgaris ssp. vulgaris) is an important crop of temperate climates which provides nearly 30% of the world's annual sugar production and is a source for bioethanol and animal feed. The species belongs to the order of Caryophylalles, is diploid with 2n = 18 chromosomes, has an estimated genome size of 714-758 megabases and shares an ancient genome triplication with other eudicot plants. Leafy beets have been cultivated since Roman times, but sugar beet is one of the most recently domesticated crops. It arose in the late eighteenth century when lines accumulating sugar in the storage root were selected from crosses made with chard and fodder beet. Here we present a reference genome sequence for sugar beet as the first non-rosid, non-asterid eudicot genome, advancing comparative genomics and phylogenetic reconstructions. The genome sequence comprises 567 megabases, of which 85% could be assigned to chromosomes. The assembly covers a large proportion of the repetitive sequence content that was estimated to be 63%. We predicted 27,421 protein-coding genes supported by transcript data and annotated them on the basis of sequence homology. Phylogenetic analyses provided evidence for the separation of Caryophyllales before the split of asterids and rosids, and revealed lineage-specific gene family expansions and losses. We sequenced spinach (Spinacia oleracea), another Caryophyllales species, and validated features that separate this clade from rosids and asterids. Intraspecific genomic variation was analysed based on the genome sequences of sea beet (Beta vulgaris ssp. maritima; progenitor of all beet crops) and four additional sugar beet accessions. We identified seven million variant positions in the reference genome, and also large regions of low variability, indicating artificial selection. The sugar beet genome sequence enables the identification of genes affecting agronomically relevant traits, supports molecular breeding and maximizes the plant's potential in energy biotechnology.

Palaeohexaploid ancestry for Caryophyllales inferred from extensive gene-based physical and genetic mapping of the sugar beet genome (Beta vulgaris).

Sugar beet (Beta vulgaris) is an important crop plant that accounts for 30% of the world's sugar production annually. The genus Beta is a distant relative of currently sequenced taxa within the core eudicotyledons; the genomic characterization of sugar beet is essential to make its genome accessible to molecular dissection. Here, we present comprehensive genomic information in genetic and physical maps that cover all nine chromosomes. Based on this information we identified the proposed ancestral linkage groups of rosids and asterids within the sugar beet genome. We generated an extended genetic map that comprises 1127 single nucleotide polymorphism markers prepared from expressed sequence tags and bacterial artificial chromosome (BAC) end sequences. To construct a genome-wide physical map, we hybridized gene-derived oligomer probes against two BAC libraries with 9.5-fold cumulative coverage of the 758 Mbp genome. More than 2500 probes and clones were integrated both in genetic maps and the physical data. The final physical map encompasses 535 chromosomally anchored contigs that contains 8361 probes and 22 815 BAC clones. By using the gene order established with the physical map, we detected regions of synteny between sugar beet (order Caryophyllales) and rosid species that involves 1400-2700 genes in the sequenced genomes of Arabidopsis, poplar, grapevine, and cacao. The data suggest that Caryophyllales share the palaeohexaploid ancestor proposed for rosids and asterids. Taken together, we here provide extensive molecular resources for sugar beet and enable future high-resolution trait mapping, gene identification, and cross-referencing to regions sequenced in other plant species.

Transcript profiles in sugar beet genotypes uncover timing and strength of defense reactions to Cercospora beticola infection.

Cercospora leaf spot disease, caused by the fungus Cercospora beticola, is the most destructive foliar disease of sugar beet (Beta vulgaris) worldwide. Despite the great agronomical importance of this disease, little is known about its underlying molecular processes. Technical resources are scarce for analyzing this important crop species. We developed a sugar beet microarray with 44,000 oligonucleotides that represent 17,277 cDNAs. During the four stages of C. beticola-B. vulgaris interactions, we profiled the transcriptional responses of three genotypes: susceptible, polygenic partial resistance, and monogenic resistant. Similar genes were induced in all three genotypes during infection but with striking differences in timing. The monogenic resistant genotype displayed strong defense responses at 1 day postinoculation (dpi). The other genotypes displayed defense responses in a later phase (15 dpi) of the infection cycle. The partially resistant genotype displayed a strong defense response in the late phase of the infection cycle. Furthermore, the partially resistant genotype expressed pathogen-related transcripts that the susceptible genotype lacked. These results indicate that resistance was achieved by the ability to mount an early defense response, and partial resistance was determined by additional defense and signaling transcripts that allowed effective defense in the late phase of the infection cycle.

Genome-wide association mapping reveals epistasis and genetic interaction networks in sugar beet.

Epistasis is defined as interactions between alleles of two or more genetic loci. Detection of epistatic interactions is the key to understand the genetic architecture and gene networks underlying complex traits. Here, we examined the extent of epistasis for seven quantitative traits with an association mapping approach in a large population of elite sugar beet lines. We found that correction for population stratification is required and that in terms of reducing the false-positive rate the mixed model approach including the kinship matrix performed best. In genome-wide scans, we detected both main effects and epistatic QTL. For physiological traits, the detected digenic and higher-order epistasis explained a considerable proportion of the genotypic variance. We illustrate that the identified epistatic interactions define comprehensive genetic networks, which may serve as starting points towards a systems-oriented approach to understand the regulation of complex traits.

Construction and characterization of a sugar beet (Beta vulgaris) fosmid library.

A sugar beet (Beta vulgaris) fosmid library from the doubled haploid accession KWS2320 encompassing 115 200 independent clones was constructed and characterized. The average insert size of the fosmid library was determined by pulsed field gel electrophoresis to be 39 kbp on average, thus representing 5.9-fold coverage of the sugar beet genome (758 Mbp). PCR screening of plate pools with primer pairs against nine sugar beet genes supported the insert size estimation. BLAST searches with 2951 fosmid end-sequences originating from 1510 clones (1536 clones attempted) revealed little contamination with organellar DNA (2.1% chloroplast DNA, 0.3% mitochondrial DNA). The sugar beet fosmid library will be integrated in the presently ongoing efforts to determine the sequence of the sugar beet genome. Fosmids will be publicly available in the format of plate pools and individual clones.

Multi-trait association mapping in sugar beet (Beta vulgaris L.).

Association mapping promises to overcome the limitations of linkage mapping methods. The main objective of this study was to examine the applicability of multivariate association mapping with an empirical data set of sugar beet. A total of 111 diploid sugar beet inbreds was selected from the seed parent heterotic pool to represent a broad diversity with respect to sugar content (SC). The inbreds were genotyped with 26 simple sequence repeat markers chosen according to their map positions in proximity to previously identified quantitative trait loci for SC. For SC and beet yield (BY), the genotypic variances were highly significant (P < 0.01). Based on the global test of the bivariate mixed-model approach, four markers were significantly associated with SC, BY, or both at a false discovery rate of 0.025. All four markers were significantly (P < 0.05) associated with BY but only two with SC. The identification of markers associated with SC, BY, or both indicated that association mapping can be successfully applied in a sugar beet breeding context for detection of marker-phenotype associations. Furthermore, based on our results multivariate association mapping can be recommended as a promising tool to discriminate with a high mapping resolution between pleiotropy and linkage as reasons for co-localization of marker-phenotype associations for different traits.

Analysis of DNA polymorphisms in sugar beet (Beta vulgaris L.) and development of an SNP-based map of expressed genes.

A panel of 13 sugar beet lines and one genotype each of the Beta vulgaris cultivars red beet and Swiss chard, and B. vulgaris ssp. maritima were used to identify polymorphisms in alignments of genomic DNA sequences derived from 315 EST- and 43 non-coding RFLP-derived loci. In sugar beet lines, loci of expressed genes showed an average SNP frequency of 1/72 bp, 1 in 58 bp in non-coding sequences, increasing to 1/47 bp upon the addition of the remaining genotypes. Within analysed DNA fragments, alleles at different SNP positions displayed linkage disequilibrium indicative of haplotype structures. On average 2.7 haplotypes were found in sugar beet lines, and haplotype conservation in expressed genes appeared to exceed 500 bp in length. Seven different genotyping techniques including SNP detection by MALDI-TOF mass spectrometry, pyrosequencing and fluorescence scanning of labelled nucleotides were employed to perform 712 segregation analyses for 538 markers in three F(2) populations. Functions were predicted for 492 mapped sequences. Genetic maps comprised 305 loci covering 599.8 cM in population K1, 241 loci distributed over 636.6 cM in population D2, and 166 loci over 507.1 cM in population K2, respectively. Based on 156 markers common to more than one population an integrated map was constructed with 524 loci covering 664.3 cM. For 377 loci the genome positions of the most similar sequences from A. thaliana were identified, but little evidence for previously presented ancestral genome structures was found.

Transcript profiles at different growth stages and tap-root zones identify correlated developmental and metabolic pathways of sugar beet.

Field-grown sugar beets were analysed for morphological characters, sucrose content, and reproducible transcript profiles by macroarray analyses with 11,520 unique sugar-beet cDNA targets in two different years. Seasonal differences were partly compensated by expressing sampling dates as thermal time. During early beet development the number of cambial rings, root length, and sucrose concentration had already achieved >40% of their final values. Sucrose levels rose from 10% to 17% over the thermal time of 1300-1400 degrees Cd with only small changes later when lower concentrations were restricted to the exterior zone at the minimum of the spatial sucrose gradient through the beet. The number of leaves and root diameter followed the same temporal growth pattern, but mass increased until beet maturity at around 2000 degrees Cd. Cluster analysis identified 543 transcripts with reproducible preferential expression between 1300-1400 degrees Cd, and 170 showing the highest transcript levels later. In maturing beets, 373 transcripts were over-represented in the inner zone and 148 in the outer zone. During early development, genes involved in cytoskeletal reorganization and transport processes showed the highest transcript levels. Cell wall biogenesis-, defence-, stress-, and degradation-related transcripts were identified in all samples, and associated with pathogen attack during late development and in the outer zone. Candidates with potential roles in carbohydrate metabolism appeared to serve anaplerotic functions by converting excess intermediates to sucrose production. Transcripts preferentially occurring in sucrose-accumulating young beet cells and newly generated peripheral cells of mature beets are discussed as potential breeding targets to improve sink strength and growth.

Construction of a 'unigene' cDNA clone set by oligonucleotide fingerprinting allows access to 25 000 potential sugar beet genes.

Access to the complete gene inventory of an organism is crucial to understanding physiological processes like development, differentiation, pathogenesis, or adaptation to the environment. Transcripts from many active genes are present at low copy numbers. Therefore, procedures that rely on random EST sequencing or on normalisation and subtraction methods have to produce massively redundant data to get access to low-abundance genes. Here, we present an improved oligonucleotide fingerprinting (ofp) approach to the genome of sugar beet (Beta vulgaris), a plant for which practically no molecular information has been available. To identify distinct genes and to provide a representative 'unigene' cDNA set for sugar beet, 159 936 cDNA clones were processed utilizing large-scale, high-throughput data generation and analysis methods. Data analysis yielded 30 444 ofp clusters reflecting the number of different genes in the original cDNA sample. A sample of 10 961 cDNA clones, each representing a different cluster, were selected for sequencing. Standard sequence analysis confirmed that 89% of these EST sequences did represent different genes. These results indicate that the full set of 30 444 ofp clusters represent up to 25 000 genes. We conclude that the ofp analysis pipeline is an accurate and effective way to construct large representative 'unigene' sets for any plant of interest with no requirement for prior molecular sequence data.