Genetic and Genomic Tools to Asssist Sugar Beet Improvement: The Value of the Crop Wild Relatives

Unraveling genotypic interactions in sugar beet for enhanced yield stability and trait associations

The interaction between genotype and environment (GEI) significantly influences plant performance, crucial for breeding programs and ultimately boosting crop productivity. Alongside GEI, breeders encounter another hurdle in their quest for yield improvement, notably adverse and negative correlations among pivotal traits. This study delved into the stability of white sugar yield (WSY), root yield (RY), sugar content (SC), extraction coefficient of sugar (ECS), and the interplay among essential traits including RY, SC, alpha amino nitrogen (N), sodium (Na+), and potassium (K+) across 15 sugar beet hybrids and three control varieties. The investigation spanned two locations over two consecutive years (2022-2023), employing a randomized complete block design with four replications to comprehensively analyze these factors. The analysis of variance highlighted the significant effects of environment, genotype, and GEI at the 1% probability level. Notably, the AMMI analysis of GEI revealed the significance of the first component for WSY, RY, and SC, with the first two components proving significant for ECS. Within the linear mixed model (LMM), WSY, RY, SC, and ECS demonstrated significant effects from both genotype and GEI. In the WAASB biplot, genotypes 10, 8, 17, 6, 13, 14, 15, 7, 12, and 16 exhibited stability in WSY, while genotypes 9, 10, 6, 14, 7, 8, 13, 12, 18, and 15 displayed stability in RY. Additionally, genotypes 10, 15, 12, 13, 16, 17, 6, and 14 were stable for SC, and genotypes 8, 10, 7, 6, 13, 12, 16, 17, 15, 14, and 18 showcased stability in ECS, boasting above-average yield values. In the genotype by yield × trait (GYT) biplot, genotypes 15, 18, and 16 emerged as top performers when combining RY with SC, Na+, N, and K+, suggesting their potential for inclusion in breeding programs.

Deciphering salt stress responses in Solanum pimpinellifolium through high-throughput phenotyping

Soil salinity is a major environmental stressor affecting agricultural productivity worldwide. Understanding plant responses to salt stress is crucial for developing resilient crop varieties. Wild relatives of cultivated crops, such as wild tomato, Solanum pimpinellifolium, can serve as a useful resource to further expand the resilience potential of the cultivated germplasm, S. lycopersicum. In this study, we employed high-throughput phenotyping in the greenhouse and field conditions to explore salt stress responses of a S. pimpinellifolium diversity panel. Our study revealed extensive phenotypic variations in response to salt stress, with traits such as transpiration rate, shoot mass, and ion accumulation showing significant correlations with plant performance. We found that while transpiration was a key determinant of plant performance in the greenhouse, shoot mass strongly correlated with yield under field conditions. Conversely, ion accumulation was the least influential factor under greenhouse conditions. Through a Genome Wide Association Study, we identified candidate genes not previously associated with salt stress, highlighting the power of high-throughput phenotyping in uncovering novel aspects of plant stress responses. This study contributes to our understanding of salt stress tolerance in S. pimpinellifolium and lays the groundwork for further investigations into the genetic basis of these traits, ultimately informing breeding efforts for salinity tolerance in tomato and other crops.

Genotype by environment interaction and stability analysis for harvest date in sugar beet cultivars

This research assessed the quantitative and qualitative reactions of commercially grown sugar beets to four different harvest dates and their yield stability. The study followed a split-plot design within a randomized complete block design over 3 years. The main plot involved 10 sugar beet cultivars, while the subplot involved four harvest dates: August 13 (HD1), September 7 (HD2), October 3 (HD3), and November 12 (HD4). The study found that environmental conditions, genotypes, and harvest dates significantly affected various traits of sugar beet. Yearly environmental variations and their interactions with genotypes and harvest dates had substantial impacts on all measured traits at the 1% probability level. Additive main effect and multiplicative interaction analysis based on white sugar yield indicated that genotype and environment's additive effects, as well as the genotype-environment interaction, were significant at 1% probability level. Shokoufa and Arya, which exhibit high white sugar yield (WSY) and low first interaction principal component (IPC1) values, are identified as desirable due to their stability across different environments. Among the harvest dates in different years, the fourth and third dates showed a higher yield than the total average. Perfekta and Ekbatan exhibited high specific adaptability. According to the multi-trait stability index, Arta, Arya and Sina were recognized as stable and superior across all measured traits.

Genotype by environment and genotype by yield*trait interactions in sugar beet: analyzing yield stability and determining key traits association

The genotype by environment interaction significantly influences plant yield, making it imperative to understand its nature for the creation of breeding programs to enhance crop production. However, this is not the only obstacle in the yield improvement process. Breeders also face the significant challenge of unfavorable and negative correlations among key traits. In this study, the stability of root yield and white sugar yield, and the association between the key traits of root yield, sugar content, nitrogen, sodium, and potassium were examined in 20 sugar beet genotypes. The study was conducted using a randomized complete block design with four replications over two consecutive years across five locations. The combined analysis of variance results revealed significant main effects of year, location, and genotype on both root yield and white sugar yield. Notably, two-way and three-way interactions between these main effects on root yield and white sugar yield resulted in a significant difference. The additive main effect and multiplicative interaction analysis revealed that the first five interaction principal components significantly impacted both the root yield and white sugar yield. The linear mixed model results for root yield and white sugar yield indicated that the genotype effect and the genotype by environment interaction were significant. The weighted average absolute scores of the best linear unbiased predictions biplot demonstrated that genotypes 20, 4, 7, 2, 16, 3, 6, 1, 14, and 15 were superior in terms of root yield. For white sugar yield, genotypes 4, 16, 3, 7, 5, 1, 10, 20, 2, and 6 stood out. These genotypes were not only stable but also had a yield value higher than the total average. All key traits, which include sugar content, sodium, potassium, and alpha amino nitrogen, demonstrated a negative correlation with root yield. Based on the genotype by yield*trait analysis results, genotypes 20, 19, and 16 demonstrated optimal performance when considering the combination of root yield with sugar content, sodium, alpha amino nitrogen, and potassium. The multi-trait stability study, genotype 13 ranked first, and genotypes 10, 8, and 9 were identified as the most ideal stable genotypes across all traits. According to the multi-trait stability index, genotype 13 emerged as the top-ranking genotype. Additionally, genotypes 10, 8, and 9 were recognized as the most stable genotypes.

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.

Salt and drought stress-mitigating approaches in sugar beet (Beta vulgaris L.) to improve its performance and yield

MAIN CONCLUSION

Although sugar beet is a salt- and drought-tolerant crop, high salinity, and water deprivation significantly reduce its yield and growth. Several reports have demonstrated stress tolerance enhancement through stress-mitigating strategies including the exogenous application of osmolytes or metabolites, nanoparticles, seed treatments, breeding salt/drought-tolerant varieties. These approaches would assist in achieving sustainable yields despite global climatic changes. Sugar beet (Beta vulgaris L.) is an economically vital crop for ~ 30% of world sugar production. They also provide essential raw materials for bioethanol, animal fodder, pulp, pectin, and functional food-related industries. Due to fewer irrigation water requirements and shorter regeneration time than sugarcane, beet cultivation is spreading to subtropical climates from temperate climates. However, beet varieties from different geographical locations display different stress tolerance levels. Although sugar beet can endure moderate exposure to various abiotic stresses, including high salinity and drought, prolonged exposure to salt and drought stress causes a significant decrease in crop yield and production. Hence, plant biologists and agronomists have devised several strategies to mitigate the stress-induced damage to sugar beet cultivation. Recently, several studies substantiated that the exogenous application of osmolytes or metabolite substances can help plants overcome injuries induced by salt or drought stress. Furthermore, these compounds likely elicit different physio-biochemical impacts, including improving nutrient/ionic homeostasis, photosynthetic efficiency, strengthening defense response, and water status improvement under various abiotic stress conditions. In the current review, we compiled different stress-mitigating agricultural strategies, prospects, and future experiments that can secure sustainable yields for sugar beets despite high saline or drought conditions.

Stability analysis and selection of sugar beet (Beta vulgaris L.) genotypes using AMMI, BLUP, GGE biplot and MTSI

The methods utilized to analyze genotype by environment interaction (GEI) and assess the stability and adaptability of genotypes are constantly changing and developing. In this regard, often instead of depending on a single analysis, it is better to use a combination of several methods to measure the nature of the GEI from various dimensions. In this study, the GEI was investigated using different methods. For this purpose, 18 sugar beet genotypes were evaluated in randomized complete block design in five research stations over 2 years. The additive effects analysis of the additive main effects and multiplicative interaction (AMMI) model showed that the effects of genotype, environment and GEI were significant for root yield (RY), white sugar yield (WSY), sugar content (SC), and extraction coefficient of sugar (ECS). The multiplicative effect's analysis of AMMI into interaction principal components (IPCs) showed that the number of significant components varies from one to four in the studied traits. According to the biplot of the mean yield against the weighted average of absolute scores (WAAS) of the IPCs, G2 and G16 for RY, G16 and G2 for WSY, G6, G4, and G1 for SC and G8, G10 and G15 for ECS were identified as stable genotypes with optimum performance. The likelihood ratio test showed that the effects of genotype and GEI was significant for all studied traits. In terms of RY and WSY, G3 and G4 had high mean values of the best linear unbiased predictions (BLUP), so they were identified as suitable genotypes. However, in terms of SC and ECS, G15 obtained high mean values of the BLUP. The GGE biplot method classified environments into four (RY and ECS) and three (WSY and SC) mega-environments (MEs). Based on the multi-trait stability index (MTSI), G15, G10, G6, and G1 were the most ideal genotypes.

QTL mapping of shoot and seed traits impacted by Drought in Barley using a recombinant inbred line Population

BACKGROUND

With ongoing climate change, drought events are severely limiting barley production worldwide and pose a significant risk to the malting, brewing and food industry. The genetic diversity inherent in the barley germplasm offers an important resource to develop stress resiliency. The purpose of this study was to identify novel, stable, and adaptive Quantitative Trait Loci (QTL), and candidate genes associated with drought tolerance. A recombinant inbred line (RIL) population (n = 192) developed from a cross between the drought tolerant 'Otis' barley variety, and susceptible 'Golden Promise'(GP) was subjected to short-term progressive drought during heading in the biotron. This population was also evaluated under irrigated and rainfed conditions in the field for yields and seed protein content.

RESULTS

Barley 50k iSelect SNP Array was used to genotype the RIL population to elucidate drought-adaptive QTL. Twenty-three QTL (eleven for seed weight, eight for shoot dry weight and four for protein content) were identified across several barley chromosomes. QTL analysis identified genomic regions on chromosome 2 and 5 H that appear to be stable across both environments and accounted for nearly 60% variation in shoot weight and 17.6% variation in seed protein content. QTL at approximately 29 Mbp on chromosome 2 H and 488 Mbp on chromosome 5 H are in very close proximity to ascorbate peroxidase (APX) and in the coding sequence of the Dirigent (DIR) gene, respectively. Both APX and DIR are well-known key players in abiotic stress tolerance in several plants. In the quest to identify key recombinants with improved tolerance to drought (like Otis) and good malting profiles (like GP), five drought tolerant RILs were selected for malt quality analysis. The selected drought tolerant RILs exhibited one or more traits that were outside the realms of the suggested limits for acceptable commercial malting quality.

CONCLUSIONS

The candidate genes can be used for marker assisted selection and/or genetic manipulation to develop barley cultivars with improved tolerance to drought. RILs with genetic network reshuffling necessary to generate drought tolerance of Otis and favorable malting quality attributes of GP may be realized by screening a larger population.

Cation diffusion facilitator proteins of Beta vulgaris reveal diversity of metal handling in dicotyledons

Manganese (Mn), iron (Fe), and zinc (Zn) are essential for diverse processes in plants, but their availability is often limiting or excessive. Cation diffusion facilitator (CDF) proteins have been implicated in the allocation of those metals in plants, whereby most of our mechanistic understanding has been obtained in Arabidopsis. It is unclear to what extent this can be generalized to other dicots. We characterized all CDFs/metal tolerance proteins of sugar beet (Beta vulgaris spp. vulgaris), which is phylogenetically distant from Arabidopsis. Analysis of subcellular localization, substrate selectivities, and transcriptional regulation upon exposure to metal deficiencies and toxicities revealed unexpected deviations from their Arabidopsis counterparts. Localization and selectivity of some members were modulated by alternative splicing. Notably, unlike in Arabidopsis, Mn- and Zn-sequestrating members were not induced in Fe-deficient roots, pointing to differences in the Fe acquisition machinery. This was supported by low Zn and Mn accumulation under Fe deficiency and a strikingly increased Fe accumulation under Mn and Zn excess, coinciding with an induction of BvIRT1. High Zn load caused a massive upregulation of Zn-BvMTPs. The results suggest that the employment of the CDF toolbox is highly diverse amongst dicots, which questions the general applicability of metal homeostasis models derived from Arabidopsis.

Evaluation of resistance and determination of stability of different sugar beet (Beta vulgaris L.) genotypes in rhizomania-infected conditions

Plant diseases are considered one of the main factors reducing yield and quality of crops, which are constantly developing and creating more virulent races and cause the resistance of more genes to break. Identifying resistance sources and including them in breeding programs will improve resistant genotypes. Rhizomania is the most common, widespread, and devastating disease of sugar beet in Iran and worldwide. Breeding genotypes with disease resistance genes is one of the most important ways to deal with this destructive disease. Twenty sugar beet genotypes along with five controls were evaluated in a randomized complete block design with four replications in rhizomania-infected conditions in four regions of Mashhad, Shiraz, Miandoab, and Hamedan for 2 years. The results of genotypic reaction to rhizomania showed that the genotypes with resistance reaction were much more frequent than those with susceptibility reaction. The analysis of multiplicative effects of the AMMI model showed that the first six components were significant and explained 98.80% of the interaction variations. The biplot obtained from the mean white sugar yield and the first interaction principal component confirmed the superiority of the RM5 genotype due to its high white sugar yield and stability in infected conditions. The results obtained from the first three principal components biplot showed that the RM9 genotype with a mean white sugar yield of 11.91 t. ha-1 was a genotype with vast general stability in all disease-infected environments. Based on the results of the MTSI index, RM3, RM17, RM9, RM13, and RM15 are introduced as stable genotypes under rhizomania-infected conditions. In conclusion, it seems that the studied genotypes have valuable and useful genes inherited from their parents to deal with rhizomania disease. Applying these genotypes in sugar beet breeding programs can effectively prevent the threat of rhizomania.

Exploitation of epigenetic variation of crop wild relatives for crop improvement and agrobiodiversity preservation

Crop wild relatives (CWRs) are recognized as the best potential source of traits for crop improvement. However, successful crop improvement using CWR relies on identifying variation in genes controlling desired traits in plant germplasms and subsequently incorporating them into cultivars. Epigenetic diversity may provide an additional layer of variation within CWR and can contribute novel epialleles for key traits for crop improvement. There is emerging evidence that epigenetic variants of functional and/or agronomic importance exist in CWR gene pools. This provides a rationale for the conservation of epigenotypes of interest, thus contributing to agrobiodiversity preservation through conservation and (epi)genetic monitoring. Concepts and techniques of classical and modern breeding should consider integrating recent progress in epigenetics, initially by identifying their association with phenotypic variations and then by assessing their heritability and stability in subsequent generations. New tools available for epigenomic analysis offer the opportunity to capture epigenetic variation and integrate it into advanced (epi)breeding programmes. Advances in -omics have provided new insights into the sources and inheritance of epigenetic variation and enabled the efficient introduction of epi-traits from CWR into crops using epigenetic molecular markers, such as epiQTLs.

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.

Efficiency and Management of Nitrogen Fertilization in Sugar Beet as Spring Crop: A Review

Sugar beet fertilization is a very complex agrotechnical measure for farmers. The main reason is that technological quality is equally important as sugar beet yield, but the increment of the root yield does not follow the root quality. Technological quality implies the concentration of sucrose in the root and the possibility of its extraction in the production of white table sugar. The great variability of agroecological factors that directly affect root yield and quality are possible good agrotechnics, primarily by minimizing fertilization. It should be considered that for sugar beet, the status of a single plant available nutrient in the soil is more important than the total amounts of nutrients in the soil. Soil analysis will show us the amount of free nutrients, the degree of soil acidity and the status of individual elements in the soil so that farmers can make a compensation plan. An estimate of the mineralizing ability of the soil, the N min, is very important in determining the amount of mineral nitrogen that the plant can absorb for high root yield and good technological quality. The amount of N needed by the sugar beet crop to be grown is an important factor, and it will always will be in the focus for the producers, especially from the aspect of trying to reduce the N input in agricultural production to preserve soils and their biodiversity but also to establish high yields and quality.

Transcriptome analysis reveals the molecular mechanism of boron deficiency tolerance in leaves of boron-efficient Beta vulgaris seedlings

Sugar beet (Beta vulgaris L.) has a high demand for B, and B deficiency inhibits normal growth and productivity. However, there is a lack of information on how B deficiency affects the growth of beet at the transcriptome level, and the factors that govern B utilisation efficiency. This study aimed to identify the genes differentially expressed under B deficiency and those that underlie the mechanisms of efficient B use in two sugar beet cultivars. Accordingly, B-efficient (H, KWS1197) and B-inefficient (L, KWS0143) sugar beet cultivars were used, and two levels of boron were employed in the hydroponic experiments: B0.1 (0.1 μM B, deficiency) and B50 (50 μM B, CK). The results showed that B deficiency inhibited leaf growth, significantly reduced B concentration and B transfer coefficient, and increased peroxidase (POD) activity and malondialdehyde and proline content. The transcriptome data showed that the B-efficient variety exhibited more differentially expressed genes than the B-inefficient variety. Metabolic pathways were the most critical pathways involved in the B deficiency response. The expression of POD, bHLH, WRKY transcription factors, and nodulin26-like intrinsic protein (NIP5;1) were upregulated in the KWS1197 variety. In conclusion, the KWS1197 variety had physiological advantages and a highly efficient B utilisation molecular mechanism, contributing to a high B deficiency tolerance. This study provides a theoretical basis for the adaptation mechanism to B deficiency in sugar beets.

Diversity and Cytogenomic Characterization of Wild Carrots in the Macaronesian Islands

The Macaronesian islands constitute an enormous reservoir of genetic variation of wild carrots (subtribe Daucinae; Apiaceae), including 10 endemic species, but an accurate understanding of the diversification processes within these islands is still lacking. We conducted a review of the morphology, ecology, and conservation status of the Daucinae species and, on the basis of a comprehensive dataset, we estimated the genome size variation for 16 taxa (around 320 samples) occurring in different habitats across the Macaronesian islands in comparison to mainland specimens. Results showed that taxa with larger genomes (e.g., Daucus crinitus: 2.544 pg) were generally found in mainland regions, while the insular endemic taxa from Azores and Cabo Verde have smaller genomes. Melanoselinum decipiens and Monizia edulis, both endemic to Madeira Island, showed intermediate values. Positive correlations were found between mean genome size and some morphological traits (e.g., spiny or winged fruits) and also with habit (herbaceous or woody). Despite the great morphological variation found within the Cabo Verde endemic species, the 2C-values obtained were quite homogeneous between these taxa and the subspecies of Daucus carota, supporting the close relationship among these taxa. Overall, this study improved the global knowledge of DNA content for Macaronesian endemics and shed light into the mechanisms underpinning diversity patterns of wild carrots in the western Mediterranean region.

Genotype by environment interaction for physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids using additive main effects and multiplicative interaction model

The objective of this study was to assess genotype by environment interaction for 21 physiological traits in sugar beet (Beta vulgaris L.) parents and hybrids grown in Rodasht Agricultural Research Station in Iran by the additive main effects and multiplicative interaction model. The study comprised of 51 sugar beet genotypes [10 multigerm pollen parents, four monogerm seed parents and 36 F1 hybrids], evaluated at four environments in a randomized complete block design, with three replicates. The additive main effects and multiplicative interaction analyses revealed significant environment main effects with respect to all observed traits, except extraction coefficient of sugar. The additive main effects and multiplicative interaction stability values ranged from 0.009 (G17 for leaf Ca2+) to 9.698 (G09 for extraction coefficient of sugar). The parental forms 2 7233-P.29 (G38) and C CMS (G49) as well as hybrids 2(6)*C (G27) and 5*C (G33) are recommended for further inclusion in the breeding programs because of their stability and good average values of observed traits.

Agricultural wilding: rewilding for agricultural landscapes through an increase in wild productive systems

Introducing wild crops and plants complements intentions for improved biodiversity outcomes in agricultural landscapes; and provides opportunity for in-situ conservation of a diverse range of wild plants and crops, and improved connectivity between conserved areas. This opinion article considers definitions and common value of conserving wild crops and plants, and crop wild relatives, in-situ and ex-situ. Rewilding definitions and common uses for policy and practice are described. The Ecological Sensitivity within Human Realities (ESHR) concept was developed to guide human natural-environment interactions in agricultural systems and landscapes for improved functional biodiversity outcomes. It is used to assess possible appropriateness of rewilding for agricultural systems and landscapes. The assessment demonstrates how agricultural systems and landscapes are often excluded, despite appearing a useful term to encourage such conservation efforts. The importance of a more specific term rather than a more specific definition and use of rewilding is suggested. Agricultural wilding is introduced as a more specific term for introducing and conserving wild crops and plants for agricultural purposes, as wild productive systems, useful for policy or other approaches the guide human natural-environment interactions. The conceptual approach to the article provides theoretical suggestions for minimum proportions of wild crops and plants for wild productive systems according to native and non native landscapes. From a conceptual to applied discussion, relevance of agricultural wilding for coffee farming landscapes is explained in some depth, and for an existing biodiversity campaign and an EU agricultural policy, briefly.

Structure and floristic composition associated with an endangered species Beta patula Aiton (Amaranthaceae) in the Islands of Madeira Archipelago

Background

Twenty-two native Crop Wild Relatives (CWR) occur in specific dry environments of Madeira Archipelago, like Desembarcadouro islet in Ponta de São Lourenço and Chão islet in Desertas Islands. Nine of them share the same gene pool with crop species included in Annex I of the International Treaty on Plant Genetic Resources for Food and Agriculture. Amongst them, Beta patula Aiton, an IUCN Critically Endangered species, has been studied in detail for in situ and ex situ conservation. The present paper summarises the information recorded during the Beta patula population assessment. Valuable information on plant communities associated with this species was obtained.

New information

The data provides information of a vegetation census spanning 7 years, from 2014 to 2020, in two uninhabited islets where Beta patula occurs, Desembarcadouro and Chão islets. The collected dataset consists of 1,786 vegetation descriptions, where 31 species were recorded. All generated data have been published and will be used towards the implementation of conservation actions and to establish a middle term management protocol for Beta patula and other CWR in situ conservation in the framework of a genetic reserve. This work is part of a EU LIFE Project, LIFE RECOVER NATURA and was conducted by members of the ISOPlexis Center, University of Madeira.

Diversification of Aeonium Species Across Macaronesian Archipelagos: Correlations Between Genome-Size Variation and Their Conservation Status

The rich endemic flora of the Macaronesian Islands places these oceanic archipelagos among the top biodiversity hotspots worldwide. The radiations that have determined the evolution of many of these insular lineages resulted in a wealth of endemic species, many of which occur in a wide range of ecological niches, but show small distribution areas in each of them. Aeonium (Crassulaceae) is the most speciose lineage in the Canary Islands (ca. 40 taxa), and as such can be considered a good model system to understand the diversification dynamics of oceanic endemic floras. The present study aims to assess the genome size variation within Aeonium distribution, i.e., the Macaronesian archipelagos of Madeira, Canaries and Cabo Verde, and analyse it together with information on distribution (i.e., geography and conservation status), taxonomy (i.e., sections), morphological traits (i.e., growth-form), geological data (i.e., island's geological age), and environmental variables (i.e., altitude, annual mean temperature, and precipitation). Based on extensive fieldwork, a cytogeographic screening of 24 Aeonium species was performed. The conservation status of these species was assessed based on IUCN criteria. 61% of the taxa were found to be threatened (4% Endangered and 57% Vulnerable). For the first time, the genome size of a comprehensive sample of Aeonium across the Macaronesian archipelagos was estimated, and considerable differences in Cx-values were found, ranging from 0.984 pg (A. dodrantale) to 2.768 pg (A. gorgoneum). An overall positive correlation between genome size and conservation status was found, with the more endangered species having the larger genomes on average. However, only slight relationships were found between genome size, morphological traits, and environmental variables. These results underscore the importance of characterizing the cytogenomic diversity and conservation status of endemic plants found in Macaronesian Islands, providing, therefore, new data to establish conservation priorities.

Tapping Diversity From the Wild: From Sampling to Implementation

The diversity observed among crop wild relatives (CWRs) and their ability to flourish in unfavorable and harsh environments have drawn the attention of plant scientists and breeders for many decades. However, it is also recognized that the benefit gained from using CWRs in breeding is a potential rose between thorns of detrimental genetic variation that is linked to the trait of interest. Despite the increased interest in CWRs, little attention was given so far to the statistical, analytical, and technical considerations that should guide the sampling design, the germplasm characterization, and later its implementation in breeding. Here, we review the entire process of sampling and identifying beneficial genetic variation in CWRs and the challenge of using it in breeding. The ability to detect beneficial genetic variation in CWRs is strongly affected by the sampling design which should be adjusted to the spatial and temporal variation of the target species, the trait of interest, and the analytical approach used. Moreover, linkage disequilibrium is a key factor that constrains the resolution of searching for beneficial alleles along the genome, and later, the ability to deplete linked deleterious genetic variation as a consequence of genetic drag. We also discuss how technological advances in genomics, phenomics, biotechnology, and data science can improve the ability to identify beneficial genetic variation in CWRs and to exploit it in strive for higher-yielding and sustainable crops.

The effect of heat stress on sugar beet recombination

Meiotic recombination plays a crucial role in plant breeding through the creation of new allelic combinations. Therefore, lack of recombination in some genomic regions constitutes a constraint for breeding programmes. In sugar beet, one of the major crops in Europe, recombination occurs mainly in the distal portions of the chromosomes, and so the development of simple approaches to change this pattern is of considerable interest for future breeding and genetics. In the present study, the effect of heat stress on recombination in sugar beet was studied by treating F₁ plants at 28 °C/25 °C (day/night) and genotyping the progeny. F₁ plants were reciprocally backcrossed allowing the study of male and female meiosis separately. Genotypic data indicated an overall increase in crossover frequency of approximately one extra crossover per meiosis, with an associated increase in pericentromeric recombination under heat treatment. Our data indicate that the changes were mainly induced by alterations in female meiosis only, showing that heterochiasmy in sugar beet is reduced under heat stress. Overall, despite the associated decrease in fertility, these data support the potential use of heat stress to foster recombination in sugar beet breeding programmes.

Image-Based Dynamic Quantification of Aboveground Structure of Sugar Beet in Field

Sugar beet is one of the main crops for sugar production in the world. With the increasing demand for sugar, more desirable sugar beet genotypes need to be cultivated through plant breeding programs. Precise plant phenotyping in the field still remains challenge. In this study, structure from motion (SFM) approach was used to reconstruct a three-dimensional (3D) model for sugar beets from 20 genotypes at three growth stages in the field. An automatic data processing pipeline was developed to process point clouds of sugar beet including preprocessing, coordinates correction, filtering and segmentation of point cloud of individual plant. Phenotypic traits were also automatically extracted regarding plant height, maximum canopy area, convex hull volume, total leaf area and individual leaf length. Total leaf area and convex hull volume were adopted to explore the relationship with biomass. The results showed that high correlations between measured and estimated values with R2 > 0.8. Statistical analyses between biomass and extracted traits proved that both convex hull volume and total leaf area can predict biomass well. The proposed pipeline can estimate sugar beet traits precisely in the field and provide a basis for sugar beet breeding.

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.

Genomes of the wild beets Beta patula and Beta vulgaris ssp. maritima

We present draft genome assemblies of Beta patula, a critically endangered wild beet endemic to the Madeira archipelago, and of the closely related Beta vulgaris ssp. maritima (sea beet). Evidence-based reference gene sets for B. patula and sea beet were generated, consisting of 25 127 and 27 662 genes, respectively. The genomes and gene sets of the two wild beets were compared with their cultivated sister taxon B. vulgaris ssp. vulgaris (sugar beet). Large syntenic regions were identified, and a display tool for automatic genome-wide synteny image generation was developed. Phylogenetic analysis based on 9861 genes showing 1:1:1 orthology supported the close relationship of B. patula to sea beet and sugar beet. A comparative analysis of the Rz2 locus, responsible for rhizomania resistance, suggested that the sequenced B. patula accession was rhizomania susceptible. Reference karyotypes for the two wild beets were established, and genomic rearrangements were detected. We consider our data as highly valuable and comprehensive resources for wild beet studies, B. patula conservation management, and sugar beet breeding research.