Identification and Precise Mapping of Resistant QTLs of Cercospora Leaf Spot Resistance in Sugar Beet (Beta vulgaris L.)

GWAS reveals a rapidly evolving candidate avirulence effector in the Cercospora leaf spot pathogen

The major resistance gene BvCR4 recently bred into sugar beet hybrids provides a high level of resistance to Cercospora leaf spot caused by the fungal pathogen Cercospora beticola. The occurrence of pathogen strains that overcome BvCR4 was studied using field trials in Switzerland conducted under natural disease pressure. Virulence of a subset of these strains was evaluated in a field trial conducted under elevated artificial disease pressure. We created a new C. beticola reference genome and mapped whole genome sequences of 256 isolates collected in Switzerland and Germany. These were combined with virulence phenotypes to conduct three separate genome-wide association studies (GWAS) to identify candidate avirulence genes. We identified a locus associated with avirulence containing a putative avirulence effector gene named AvrCR4. All virulent isolates either lacked AvrCR4 or had nonsynonymous mutations within the gene. AvrCR4 was present in all 74 isolates from non-BvCR4 hybrids, whereas 33 of 89 isolates from BvCR4 hybrids carried a deletion. We also mapped genomic data from 190 publicly available US isolates to our new reference genome. The AvrCR4 deletion was found in only one of 95 unique isolates from non-BvCR4 hybrids in the United States. AvrCR4 presents a unique example of an avirulence effector in which virulent alleles have only recently emerged. Most likely these were selected out of standing genetic variation after deployment of BvCR4. Identification of AvrCR4 will enable real-time screening of C. beticola populations for the emergence and spread of virulent isolates.

Advancements and prospects of CRISPR/Cas9 technologies for abiotic and biotic stresses in sugar beet

Sugar beet is a crop with high sucrose content, known for sugar production and recently being considered as an emerging raw material for bioethanol production. This crop is also utilized as cattle feed, mainly when animal green fodder is scarce. Bioethanol and hydrogen gas production from this crop is an essential source of clean energy. Environmental stresses (abiotic/biotic) severely affect the productivity of this crop. Over the past few decades, the molecular mechanisms of biotic and abiotic stress responses in sugar beet have been investigated using next-generation sequencing, gene editing/silencing, and over-expression approaches. This information can be efficiently utilized through CRISPR/Cas 9 technology to mitigate the effects of abiotic and biotic stresses in sugar beet cultivation. This review highlights the potential use of CRISPR/Cas 9 technology for abiotic and biotic stress management in sugar beet. Beet genes known to be involved in response to alkaline, cold, and heavy metal stresses can be precisely modified via CRISPR/Cas 9 technology for enhancing sugar beet's resilience to abiotic stresses with minimal off-target effects. Similarly, CRISPR/Cas 9 technology can help generate insect-resistant sugar beet varieties by targeting susceptibility-related genes, whereas incorporating Cry1Ab and Cry1C genes may provide defense against lepidopteron insects. Overall, CRISPR/Cas 9 technology may help enhance sugar beet's adaptability to challenging environments, ensuring sustainable, high-yield production.

Cercospora beticola: The intoxicating lifestyle of the leaf spot pathogen of sugar beet

Cercospora leaf spot, caused by the fungal pathogen Cercospora beticola, is the most destructive foliar disease of sugar beet worldwide. This review discusses C. beticola genetics, genomics, and biology and summarizes our current understanding of the molecular interactions that occur between C. beticola and its sugar beet host. We highlight the known virulence arsenal of C. beticola as well as its ability to overcome currently used disease management strategies. Finally, we discuss future prospects for the study and management of C. beticola infections in the context of newly employed molecular tools to uncover additional information regarding the biology of this pathogen.

TAXONOMY

Cercospora beticola Sacc.; Kingdom Fungi, Phylum Ascomycota, Class Dothideomycetes, Order Capnodiales, Family Mycosphaerellaceae, Genus Cercospora.

HOST RANGE

Well-known pathogen of sugar beet (Beta vulgaris subsp. vulgaris) and most species of the Beta genus. Reported as pathogenic on other members of the Chenopodiaceae (e.g., lamb's quarters, spinach) as well as members of the Acanthaceae (e.g., bear's breeches), Apiaceae (e.g., Apium), Asteraceae (e.g., chrysanthemum, lettuce, safflower), Brassicaceae (e.g., wild mustard), Malvaceae (e.g., Malva), Plumbaginaceae (e.g., Limonium), and Polygonaceae (e.g., broad-leaved dock) families.

DISEASE SYMPTOMS

Leaves infected with C. beticola exhibit circular lesions that are coloured tan to grey in the centre and are often delimited by tan-brown to reddish-purple rings. As disease progresses, spots can coalesce to form larger necrotic areas, causing severely infected leaves to wither and die. At the centre of these spots are black spore-bearing structures (pseudostromata). Older leaves often show symptoms first and younger leaves become infected as the disease progresses.

MANAGEMENT

Application of a mixture of fungicides with different modes of action is currently performed although elevated resistance has been documented in most employed fungicide classes. Breeding for high-yielding cultivars with improved host resistance is an ongoing effort and prudent cultural practices, such as crop rotation, weed host management, and cultivation to reduce infested residue levels, are widely used to manage disease. USEFUL WEBSITE: https://www.ncbi.nlm.nih.gov/genome/11237?genome_assembly_id=352037.

Genetic and phenotypic assessment of sugar beet (Beta vulgaris L. subsp. vulgaris) elite inbred lines selected in Japan during the past 50 years

Genetic diversity of Japanese sugar beet elite inbred line diversity (JSBDIV) set consisting of 63 lines was investigated using 33 cleaved amplified polymorphic sequence and 38 simple sequence repeat analyses. JSBDIV set was significantly subdivided into six (pedigree information), seven (Neighbor-Joining method) or 12 (population structure analysis) groups. The highest value of a pairwise population differentiation estimate, Φ PT value, among groups was yielded from population structure analysis with explained variation 32%. Some of the groups defined in this study exhibited close association with ancestral open-pollinated varieties (OPVs), suggesting that inter-OPV cross was rare during the establishment of JSBDIV set. On the other hand, low Φ PT values between some groups suggest that genetic backgrounds of ancestral OPVs had historically overlapped to some extent. Phenotypic traits showed significant differences both among and within groups. A nearly identical group was identified as the highest sugar content group irrespective of the grouping methods. Groups with Aphanomyces root rot resistance are associated with an OPV 'Tmm-1', suggesting it as a source of this trait. 'Tmm-1' is also associated with Cercospora leaf spot resistance, but an exceptional resistant line with no association of 'Tmm-1' supports a notion that different genetic resources exist for this trait.

New Generation of Resistant Sugar Beet Varieties for Advanced Integrated Management of Cercospora Leaf Spot in Central Europe

Cercospora leaf spot (CLS) epidemics in sugar beet have been increasing in recent years causing higher use of fungicides. Concomitantly, the availability of effective fungicides is at risk because of resistance development in the fungus, the lack of new active ingredients as well as restrictive approval practices. A key option for an integrated management of CLS is cultivation of resistant varieties. Because of the yield penalty in resistant varieties, acceptance in commercial practice so far has been low. The aim of our study was to characterize recent sugar beet varieties registered in Germany in terms of resistance and tolerance to CLS and their value for integrated pest management. The genetic basis of CLS resistance in varieties is protected by intellectual property rights even after variety registration and not open to the public due to economic competition. To gain reliable data for cultivation, varieties have to be tested for their resistance traits under field conditions at varying levels of infection with Cercospora beticola. In collaboration with variety related stakeholders, 15 sugar beet varieties were tested in 49 field trials in Germany from 2014 to 2016 for their yield response to CLS. The trials were set up in a split-plot design with and without infection (i.e., with and without fungicide). The classification of varietal reaction to CLS is based on symptomatic leaf area (susceptibility) and the resulting relative yield loss (tolerance). Since the relation between both parameters varied among varieties, it was used as an additional parameter to describe tolerance. On this basis, three groups of varieties were identified. They can be characterized as a susceptible, a resistant and a presumably tolerant cluster. A comparison of the data with an older dataset originating from 2009 to 2011 revealed that yield performance of recent varieties with resistance to C. beticola caught up with susceptible varieties due to breeding progress. They showed no yield penalty in the absence of the disease and better economic performance than susceptible varieties. It is assumed that these varieties will allow a substantial reduction of fungicide use for an advanced integrated pest management under central European conditions.

NMR-Based Metabolic Profiling of Field-Grown Leaves from Sugar Beet Plants Harbouring Different Levels of Resistance to Cercospora Leaf Spot Disease

Cercospora leaf spot (CLS) is one of the most serious leaf diseases for sugar beet (Beta vulgaris L.) worldwide. The breeding of sugar beet cultivars with both high CLS resistance and high yield is a major challenge for breeders. In this study, we report the nuclear magnetic resonance (NMR)-based metabolic profiling of field-grown leaves for a subset of sugar beet genotypes harbouring different levels of CLS resistance. Leaves were collected from 12 sugar beet genotypes at four time points: seedling, early growth, root enlargement, and disease development stages. ¹H-NMR spectra of foliar metabolites soluble in a deuterium-oxide (D₂O)-based buffer were acquired and subjected to multivariate analyses. A principal component analysis (PCA) of the NMR data from the sugar beet leaves shows clear differences among the growth stages. At the later time points, the sugar and glycine betaine contents were increased, whereas the choline content was decreased. The relationship between the foliar metabolite profiles and resistance level to CLS was examined by combining partial least squares projection to latent structure (PLS) or orthogonal PLS (OPLS) analysis and univariate analyses. It was difficult to build a robust model for predicting precisely the disease severity indices (DSIs) of each genotype; however, GABA and Gln differentiated susceptible genotypes (genotypes with weak resistance) from resistant genotypes (genotypes with resistance greater than a moderate level) before inoculation tests. The results suggested that breeders might exclude susceptible genotypes from breeding programs based on foliar metabolites profiled without inoculation tests, which require an enormous amount of time and effort.

OMICS Technologies and Applications in Sugar Beet

Sugar beet is a species of the Chenopodiaceae family. It is an important sugar crop that supplies approximately 35% of the sugar in the world. Sugar beet M14 line is a unique germplasm that contains genetic materials from Beta vulgaris L. and Beta corolliflora Zoss. And exhibits tolerance to salt stress. In this review, we have summarized OMICS technologies and applications in sugar beet including M14 for identification of novel genes, proteins related to biotic and abiotic stresses, apomixes and metabolites related to energy and food. An OMICS overview for the discovery of novel genes, proteins and metabolites in sugar beet has helped us understand the complex mechanisms underlying many processes such as apomixes, tolerance to biotic and abiotic stresses. The knowledge gained is valuable for improving the tolerance of sugar beet and other crops to biotic and abiotic stresses as well as for enhancing the yield of sugar beet for energy and food production.

SBMDb: first whole genome putative microsatellite DNA marker database of sugarbeet for bioenergy and industrial applications

DNA marker plays important role as valuable tools to increase crop productivity by finding plausible answers to genetic variations and linking the Quantitative Trait Loci (QTL) of beneficial trait. Prior approaches in development of Short Tandem Repeats (STR) markers were time consuming and inefficient. Recent methods invoking the development of STR markers using whole genomic or transcriptomics data has gained wide importance with immense potential in developing breeding and cultivator improvement approaches. Availability of whole genome sequences and in silico approaches has revolutionized bulk marker discovery. We report world's first sugarbeet whole genome marker discovery having 145 K markers along with 5 K functional domain markers unified in common platform using MySQL, Apache and PHP in SBMDb. Embedded markers and corresponding location information can be selected for desired chromosome, location/interval and primers can be generated using Primer3 core, integrated at backend. Our analyses revealed abundance of 'mono' repeat (76.82%) over 'di' repeats (13.68%). Highest density (671.05 markers/Mb) was found in chromosome 1 and lowest density (341.27 markers/Mb) in chromosome 6. Current investigation of sugarbeet genome marker density has direct implications in increasing mapping marker density. This will enable present linkage map having marker distance of ∼2 cM, i.e. from 200 to 2.6 Kb, thus facilitating QTL/gene mapping. We also report e-PCR-based detection of 2027 polymorphic markers in panel of five genotypes. These markers can be used for DUS test of variety identification and MAS/GAS in variety improvement program. The present database presents wide source of potential markers for developing and implementing new approaches for molecular breeding required to accelerate industrious use of this crop, especially for sugar, health care products, medicines and color dye. Identified markers will also help in improvement of bioenergy trait of bioethanol and biogas production along with reaping advantage of crop efficiency in terms of low water and carbon footprint especially in era of climate change. Database URL: http://webapp.cabgrid.res.in/sbmdb/.