Advanced Genomic Tools Research Articles

Sesame, an Underutilized Oil Seed Crop: Breeding Achievements and Future Challenges.

Sesame seeds and their edible oil are highly nutritious and rich in mono- and polyunsaturated fatty acids. Bioactive compounds such as sterols, tocopherols, and sesamol provide significant medicinal benefits. The high oil content (50%) and favorable mono- and polyunsaturated fatty acid balance, as well as resilience to water stress, make sesame a promising candidate crop for global agricultural expansion. However, sesame production faces challenges such as low yields, poor response to agricultural inputs, and losses due to capsule dehiscence. To enhance yield, traits like determinate growth, dwarfism, a high harvest index, non-shattering capsules, disease resistance, and photoperiod sensitivity are needed. These traits can be achieved through variation or induced mutation breeding. Crossbreeding methods often result in unwanted genetic changes. The gene editing CRISPR/Cas9 technology has the potential to suppress detrimental alleles and improve the fatty acid profile by inhibiting polyunsaturated fatty acid biosynthesis. Even though sesame is an orphan crop, it has entered the genomic era, with available sequences assisting molecular breeding efforts. This progress aids in associating single-nucleotide polymorphisms (SNPs) and simple sequence repeats (SSR) with key economic traits, as well as identifying genes related to adaptability, oil production, fatty acid synthesis, and photosynthesis. Additionally, transcriptomic research can reveal genes involved in abiotic stress responses and adaptation to diverse climates. The mapping of quantitative trait loci (QTL) can identify loci linked to key traits such as capsule size, seed count per capsule, and capsule number per plant. This article reviews recent advances in sesame breeding, discusses ongoing challenges, and explores potential strategies for future improvement. Hence, integrating advanced genomic tools and breeding strategies provides promising ways to enhance sesame production to meet global demands.

Wheat genetic resources have avoided disease pandemics, improved food security, and reduced environmental footprints: A review of historical impacts and future opportunities.

The use of plant genetic resources (PGR)-wild relatives, landraces, and isolated breeding gene pools-has had substantial impacts on wheat breeding for resistance to biotic and abiotic stresses, while increasing nutritional value, end-use quality, and grain yield. In the Global South, post-Green Revolution genetic yield gains are generally achieved with minimal additional inputs. As a result, production has increased, and millions of hectares of natural ecosystems have been spared. Without PGR-derived disease resistance, fungicide use would have easily doubled, massively increasing selection pressure for fungicide resistance. It is estimated that in wheat, a billion liters of fungicide application have been avoided just since 2000. This review presents examples of successful use of PGR including the relentless battle against wheat rust epidemics/pandemics, defending against diseases that jump species barriers like blast, biofortification giving nutrient-dense varieties and the use of novel genetic variation for improving polygenic traits like climate resilience. Crop breeding genepools urgently need to be diversified to increase yields across a range of environments (>200 Mha globally), under less predictable weather and biotic stress pressure, while increasing input use efficiency. Given that the ~0.8 m PGR in wheat collections worldwide are relatively untapped and massive impacts of the tiny fraction studied, larger scale screenings and introgression promise solutions to emerging challenges, facilitated by advanced phenomic and genomic tools. The first translocations in wheat to modify rhizosphere microbiome interaction (reducing biological nitrification, reducing greenhouse gases, and increasing nitrogen use efficiency) is a landmark proof of concept. Phenomics and next-generation sequencing have already elucidated exotic haplotypes associated with biotic and complex abiotic traits now mainstreamed in breeding. Big data from decades of global yield trials can elucidate the benefits of PGR across environments. This kind of impact cannot be achieved without widescale sharing of germplasm and other breeding technologies through networks and public-private partnerships in a pre-competitive space.

Enhancing Crop Resilience: Advances and Challenges in Marker-Assisted Selection for Disease Resistance

Marker-assisted selection (MAS) has emerged as a pivotal technique in crop improvement programs, enabling the identification and incorporation of disease-resistant traits in crops. This review highlights the significance of MAS in enhancing disease resistance, the current state of research, and the challenges faced in its implementation. Various case studies, including successful applications in crops such as rice, wheat, and maize, demonstrate the potential of MAS in sustainable agriculture. The review also discusses the integration of MAS with other modern breeding techniques and emphasizes the need for advanced genomic tools for future advancements in this field. The development of advanced molecular markers, high-throughput screening techniques, and the incorporation of genomic selection approaches have all contributed to recent developments in MAS. Even in intricate polygenic situations, these developments have significantly improved t+he precision and speed of discovering disease-resistant characteristics. Case studies involving important crops such as maize, wheat, and rice show how MAS can be successfully applied to create varieties with improved resistance to certain diseases, significantly lowering crop losses and reduced use of pesticides. These developments have consequences that go beyond the purely technical; they could have a big influence on environmentally friendly agriculture methods, cost effectiveness, and sustainable development. This study addresses the possible future path of MAS in crop breeding and summarizes the major discoveries from current research, highlighting both the successes and difficulties in the field. The body of data highlights MAS as a critical instrument in the toolbox of the contemporary breeder, essential for satisfying the ever-increasing demands of a world that is changing quickly.

Identification of Candidate Genes for Salt Tolerance at Seedling Stage in Rice Using QTL-Seq and Chromosome Segment Substitution Line-Derived Population

Rice is a staple food for more than half of the world’s population. However, the pervasive problem of salinity is severely undermining rice production, especially in coastal and low-lying areas where soil salinization is widespread. This stress, exacerbated by climate change, necessitates the development of salt-tolerant rice varieties to ensure food security. In this study, an F2:3 population (n = 454) from a cross of KDML105 and its chromosome segment substitution line (CSSL) was used to identify genomic regions associated with salt tolerance at the seedling stage. Using the QTL-seq approach, a QTL significantly associated with salt tolerance was identified on chromosome 1. Annotation of candidate genes in this region revealed the potential regulators of salt tolerance, including MIKC-type MADS domain proteins, calmodulin-binding transcription factors, and NB-ARC domain-containing proteins. These and other identified genes provide insights into the genetic basis of salt tolerance. This study underscores the importance of using advanced genomics tools and CSSL populations in the study of complex traits such as salt tolerance in rice. Several candidate genes identified in this study could be used in further studies on molecular or physiological mechanisms related to the salt response and tolerance mechanism in rice. Additionally, these genes could also be utilized in plant breeding programs for salt tolerance.

Enhancing Sustainable Crop Production through Innovations in Precision Agriculture Technologies

Precision agriculture technologies provide innovative tools to optimize crop production while minimizing environmental impacts. This review examines recent advances in precision ag systems to enhance sustainable agriculture. Key innovations include: remote and proximal crop sensing techniques leveraging hyperspectral imaging, thermal imaging, and Lidar to assess crop health and stress status; variable rate technologies like targeted sprayers and precision planters to reduce input waste; data analytics and decision support systems that integrate multi-source data streams to guide site-specific intervention; robotics and automation for precision field operations; and advanced breeding techniques and genomic tools enabling development of stress resilient, high yielding varieties. Adoption barriers, future technology trajectories, and priority research needs are discussed to further advance precision solutions that support productivity, efficiency, and sustainability goals.

Applying 12 machine learning algorithms and Non-negative Matrix Factorization for robust prediction of lupus nephritis.

Lupus nephritis (LN) is a challenging condition with limited diagnostic and treatment options. In this study, we applied 12 distinct machine learning algorithms along with Non-negative Matrix Factorization (NMF) to analyze single-cell datasets from kidney biopsies, aiming to provide a comprehensive profile of LN. Through this analysis, we identified various immune cell populations and their roles in LN progression and constructed 102 machine learning-based immune-related gene (IRG) predictive models. The most effective models demonstrated high predictive accuracy, evidenced by Area Under the Curve (AUC) values, and were further validated in external cohorts. These models highlight six hub IRGs (CD14, CYBB, IFNGR1, IL1B, MSR1, and PLAUR) as key diagnostic markers for LN, showing remarkable diagnostic performance in both renal and peripheral blood cohorts, thus offering a novel approach for noninvasive LN diagnosis. Further clinical correlation analysis revealed that expressions of IFNGR1, PLAUR, and CYBB were negatively correlated with the glomerular filtration rate (GFR), while CYBB also positively correlated with proteinuria and serum creatinine levels, highlighting their roles in LN pathophysiology. Additionally, protein-protein interaction (PPI) analysis revealed significant networks involving hub IRGs, emphasizing the importance of the interleukin family and chemokines in LN pathogenesis. This study highlights the potential of integrating advanced genomic tools and machine learning algorithms to improve diagnosis and personalize management of complex autoimmune diseases like LN.

Establishment of a stable transfection and gene targeting system in Babesia divergens.

Babesia divergens is an emerging tick-borne pathogen considered as the principal causative agent of bovine babesiosis in Europe with a notable zoonotic risk to human health. Despite its increasing impact, considerable gaps persist in our understanding of the molecular interactions between this parasite and its hosts. In this study, we address the current limitation of functional genomic tools in B. divergens and introduce a stable transfection system specific to this parasite. We define the parameters for a drug selection system hdhfr-WR99210 and evaluate different transfection protocols for highly efficient generation of transgenic parasites expressing GFP. We proved that plasmid delivery into bovine erythrocytes prior to their infection is the most optimal transfection approach for B. divergens, providing novel evidence of Babesia parasites' ability to spontaneously uptake external DNA from erythrocytes cytoplasm. Furthermore, we validated the bidirectional and symmetrical activity of ef-tgtp promoter, enabling simultaneous expression of external genes. Lastly, we generated a B. divergens knockout line by targeting a 6-cys-e gene locus. The observed dispensability of this gene in intraerythrocytic parasite development makes it a suitable recipient locus for further transgenic application. The platform for genetic manipulations presented herein serves as the initial step towards developing advanced functional genomic tools enabling the discovery of B. divergens molecules involved in host-vector-pathogen interactions.

Predator-prey systems as models for integrative research in biology: the value of a non-consumptive effects framework.

Predator-prey interactions are a cornerstone of many ecological and evolutionary processes that influence various levels of biological organization, from individuals to ecosystems. Predators play a crucial role in shaping ecosystems through the consumption of prey species and non-consumptive effects. Non-consumptive effects (NCEs) can induce changes in prey behavior, including altered foraging strategies, habitat selection, life history and anti-predator responses. These defensive strategies have physiological consequences for prey, affecting their growth, reproduction and immune function to name a few. Numerous experimental studies have incorporated NCEs in investigating predator-prey dynamics in the past decade. Interestingly, predator-prey systems can also be used as experimental models to answer physiology, cognition and adaptability questions. In this Commentary, I highlight research that uses NCEs in predator-prey systems to provide novel insights into cognition, adaptation, epigenetic inheritance and aging. I discuss the evolution of instinct, anxiety and other cognitive disorders, the shaping of brain connectomes, stress-induced aging and the development of behavioral coping styles. I outline how studies can integrate the investigation of NCEs with advanced behavioral, genomic and neurological tools to provide novel insights into physiological and cognitive health.

Breeding for Biotic Stress Resistance in Pea

Pea (Pisum sativum) stands out as one of the most significant and productive cool-season pulse crops cultivated worldwide. Dealing with biotic stresses remains a critical challenge in fully harnessing pea’s potential productivity. As such, dedicated research and developmental efforts are necessary to make use of omic resources and advanced breeding techniques. These approaches are crucial in facilitating the rapid and timely development of high-yielding varieties that can tolerate and resist multiple stresses. The availability of advanced genomic tools, such as comprehensive genetic maps and reliable DNA markers, holds immense promise for integrating resistance genes from diverse sources. This integration helps accelerate genetic gains in pea crops. This review provides an overview of recent accomplishments in the genetic and genomic resource development of peas. It also covers the inheritance of genes controlling various biotic stress responses, genes that control pathogenesis in disease-causing organisms, the mapping of genes/QTLs, as well as transcriptomic and proteomic advancements. By combining conventional and modern omics-enabled breeding strategies, genetic gains can be significantly enhanced.

Genomic approaches to enhance adaptive plasticity to cope with soil constraints amidst climate change in wheat.

Climate change is varying the availability of resources, soil physicochemical properties, and rainfall events, which collectively determines soil physical and chemical properties. Soil constraints-acidity (pH<6), salinity (pH≤8.5), sodicity, and dispersion (pH>8.5)-are major causes of wheat yield loss in arid and semiarid cropping systems. To cope with changing environments, plants employ adaptive strategies such as phenotypic plasticity, a key multifaceted trait, to promote shifts in phenotypes. Adaptive strategies for constrained soils are complex, determined by key functional traits and genotype×environment×management interactions. The understanding of the molecular basis of stress tolerance is particularly challenging for plasticity traits. Advances in sequencing and high-throughput genomics technologies have identified functional alleles in gene-rich regions, haplotypes, candidate genes, mechanisms, and in silico gene expression profiles at various growth developmental stages. Our review focuses on favorable alleles for enhanced gene expression, quantitative trait loci, and epigenetic regulation of plant responses to soil constraints, including heavy metal stress and nutrient limitations. A strategy is then described for quantitative traits in wheat by investigating significant alleles and functional characterization of variants, followed by gene validation using advanced genomic tools, and marker development for molecular breeding and genome editing. Moreover, the review highlights the progress of gene editing in wheat, multiplex gene editing, and novel alleles for smart control of gene expression. Application of these advanced genomic technologies to enhance plasticity traits along with soil management practices will be an effective tool to build yield, stability, and sustainability on constrained soils in the face of climate change.

Wheat quality: A review on chemical composition, nutritional attributes, grain anatomy, types, classification, and function of seed storage proteins in bread making quality.

Wheat (Triticum aestivum L.) belonging to one of the most diverse and substantial families, Poaceae, is the principal cereal crop for the majority of the world's population. This cereal is polyploidy in nature and domestically grown worldwide. Wheat is the source of approximately half of the food calories consumed worldwide and is rich in proteins (gluten), minerals (Cu, Mg, Zn, P, and Fe), vitamins (B-group and E), riboflavin, niacin, thiamine, and dietary fiber. Wheat seed-storage proteins represent an important source of food and energy and play a major role in the determination of bread-making quality. The two groups of wheat grain proteins, i.e., gliadins and glutenins, have been widely studied using SDS-PAGE and other techniques. Sustainable production with little input of chemicals along with high nutritional quality for its precise ultimate uses in the human diet are major focus areas for wheat improvement. An expansion in the hereditary base of wheat varieties must be considered in the wheat breeding program. It may be accomplished in several ways, such as the use of plant genetic resources, comprising wild relatives and landraces, germplasm-assisted breeding through advanced genomic tools, and the application of modern methods, such as genome editing. In this review, we critically focus on phytochemical composition, reproduction growth, types, quality, seed storage protein, and recent challenges in wheat breeding and discuss possible ways forward to combat those issues.

Genetic diversity pattern reveals the primary determinant of burcucumber (Sicyos angulatus L.) invasion in Korea.

Biological invasion is a complex process associated with propagule pressure, dispersal ability, environmental constraints, and human interventions, which leave genetic signatures. The population genetics of an invasive species thus provides invaluable insights into the patterns of invasion. Burcucumber, one of the most detrimental weeds for soybean production in US, has recently colonized Korea and rapidly spread posing a great threat to the natural ecosystem. We aim to infer the determinants of the rapid burcucumber invasion by examining the genetic diversity, demography, and spread pattern with advanced genomic tools. We employed 2,696 genome-wide single-nucleotide polymorphisms to assess the level of diversity and the spatial pattern associated with the landscape factors and to infer the demographic changes of 24 populations (364 genotypes) across four major river basins with the east coastal streams in South Korea. Through the approximate Bayesian computation, we inferred the likely invasion scenario of burcucumber in Korea. The landscape genetics approach adopting the circuit theory and MaxEnt model was applied to determine the landscape contributors. Our data suggested that most populations have experienced population bottlenecks, which led to lowered within-population genetic diversity and inflated population divergences. Burcucumber colonization in Korea has strongly been affected by demographic bottlenecks and multiple introductions, whereas environmental factors were not the primary determinant of the invasion. Our work highlighted the significance of preventing secondary introductions, particularly for aggressive weedy plants such as the burcucumber.

A CRISPR Path to Finding Vulnerabilities and Solving Drug Resistance: Targeting the Diverse Cancer Landscape and Its Ecosystem.

Cancer is the second leading cause of death globally, with therapeutic resistance being a major cause of treatment failure in the clinic. The dynamic signaling that occurs between tumor cells and the diverse cells of the surrounding tumor microenvironment actively promotes disease progression and therapeutic resistance. Improving the understanding of how tumors evolve following therapy and the molecular mechanisms underpinning de novo or acquired resistance is thus critical for the identification of new targets and for the subsequent development of more effective combination regimens. Simultaneously targeting multiple hallmark capabilities of cancer to circumvent adaptive or evasive resistance may lead to significantly improved treatment response in the clinic. Here, the latest applications of functional genomics tools, such as clustered regularly interspaced short palindromic repeats (CRISPR) editing, to characterize the dynamic cancer resistance mechanisms, from improving the understanding of resistance to classical chemotherapeutics, to deciphering unique mechanisms that regulate tumor responses to new targeted agents and immunotherapies, are discussed. Potential avenues of future research in combating therapeutic resistance, the contribution of tumor-stroma signaling in this setting, and how advanced functional genomics tools can help streamline the identification of key molecular determinants of drug response are explored.

Genomics Enabled Breeding Strategies for Major Biotic Stresses in Pea (Pisum sativum L.).

Pea (Pisum sativum L.) is one of the most important and productive cool season pulse crops grown throughout the world. Biotic stresses are the crucial constraints in harnessing the potential productivity of pea and warrant dedicated research and developmental efforts to utilize omics resources and advanced breeding techniques to assist rapid and timely development of high-yielding multiple stress-tolerant–resistant varieties. Recently, the pea researcher’s community has made notable achievements in conventional and molecular breeding to accelerate its genetic gain. Several quantitative trait loci (QTLs) or markers associated with genes controlling resistance for fusarium wilt, fusarium root rot, powdery mildew, ascochyta blight, rust, common root rot, broomrape, pea enation, and pea seed borne mosaic virus are available for the marker-assisted breeding. The advanced genomic tools such as the availability of comprehensive genetic maps and linked reliable DNA markers hold great promise toward the introgression of resistance genes from different sources to speed up the genetic gain in pea. This review provides a brief account of the achievements made in the recent past regarding genetic and genomic resources’ development, inheritance of genes controlling various biotic stress responses and genes controlling pathogenesis in disease causing organisms, genes/QTLs mapping, and transcriptomic and proteomic advances. Moreover, the emerging new breeding approaches such as transgenics, genome editing, genomic selection, epigenetic breeding, and speed breeding hold great promise to transform pea breeding. Overall, the judicious amalgamation of conventional and modern omics-enabled breeding strategies will augment the genetic gain and could hasten the development of biotic stress-resistant cultivars to sustain pea production under changing climate. The present review encompasses at one platform the research accomplishment made so far in pea improvement with respect to major biotic stresses and the way forward to enhance pea productivity through advanced genomic tools and technologies.

Advanced analytical, chemometric, and genomic tools to identify polymer degradation products and potential microbial consumers in wastewater environments

The worldwide growth in the production of plastics and lack of appropriate waste management has led to unsustainable environmental pollution of global concern. Hence, determining the key drivers characterizing the degradation of polymers in water is a rising topic. Here we propose a workflow based on advanced high throughput data analysis and processing tools aiming at the characterization of (a) the degradation products of polymers exposed to an aquatic environment, and (b) the taxonomical composition of the potential microbial consumers' consortia. To test this approach, polycaprolactonediol (PCLD) polymer probes were exposed to different wastewater environments (influent, aerobic, and anaerobic denitrifying reactors) in four different wastewater treatment plants (WWTPs). Probes were extracted and analyzed by non-target liquid chromatography-high resolution mass spectrometry (LC-HRMS) and the acquired data were processed using advanced chemometric tools (Regions of Interest-Multivariate Curve Resolution-Alternate Least Squares, ROIMCR-ALS). Up to 26 components explaining ca. 69% of the variance were resolved, and 20 of these were further identified. Degradation was dominated by two processes: (a) hydrolysis of the ester groups present in PCLD and (b) formation of cyclic polycaprolactone oligomers. These transformation pathways occurred regardless of what were the WWTPs and the treatment stages, varying only the respective concentrations of the formed by-products. The composition of the microbial communities attached to the polymer and free-living in the surrounding water was characterized by 16S rDNA amplicon sequencing analysis. The two communities showed taxonomic differences and were unique in each WWTP treatment stage. Polymer-attached communities were tentatively proposed as potential consumers.

QTL mapping and genomic analyses of earliness and fruit ripening traits in a melon Recombinant Inbred Lines population supported by de novo assembly of their parental genomes.

Earliness and ripening behavior are important attributes of fruits on and off the vine, and affect quality and preference of both growers and consumers. Fruit ripening is a complex physiological process that involves metabolic shifts affecting fruit color, firmness, and aroma production. Melon is a promising model crop for the study of fruit ripening, as the full spectrum of climacteric behavior is represented across the natural variation. Using Recombinant Inbred Lines (RILs) population derived from the parental lines “Dulce” (reticulatus, climacteric) and “Tam Dew” (inodorus, non-climacteric) that vary in earliness and ripening traits, we mapped QTLs for ethylene emission, fruit firmness and days to flowering and maturity. To further annotate the main QTL intervals and identify candidate genes, we used Oxford Nanopore long-read sequencing in combination with Illumina short-read resequencing, to assemble the parental genomes de-novo. In addition to 2.5 million genome-wide SNPs and short InDels detected between the parents, we also highlight here the structural variation between these lines and the reference melon genome. Through systematic multi-layered prioritization process, we identified 18 potential polymorphisms in candidate genes within multi-trait QTLs. The associations of selected SNPs with earliness and ripening traits were further validated across a panel of 177 diverse melon accessions and across a diallel population of 190 F1 hybrids derived from a core subset of 20 diverse parents. The combination of advanced genomic tools with diverse germplasm and targeted mapping populations is demonstrated as a way to leverage forward genetics strategies to dissect complex horticulturally important traits.

Advanced Analytical, Chemometric, and Genomic Tools to Identify Polymer's Degradation Products and Potential Microbial Consumers in Wastewater Environments

Advanced Analytical, Chemometric, and Genomic Tools to Identify Polymer's Degradation Products and Potential Microbial Consumers in Wastewater Environments

Progressive Genomic Approaches to Explore Drought- and Salt-Induced Oxidative Stress Responses in Plants under Changing Climate.

Drought and salinity are the major environmental abiotic stresses that negatively impact crop development and yield. To improve yields under abiotic stress conditions, drought- and salinity-tolerant crops are key to support world crop production and mitigate the demand of the growing world population. Nevertheless, plant responses to abiotic stresses are highly complex and controlled by networks of genetic and ecological factors that are the main targets of crop breeding programs. Several genomics strategies are employed to improve crop productivity under abiotic stress conditions, but traditional techniques are not sufficient to prevent stress-related losses in productivity. Within the last decade, modern genomics studies have advanced our capabilities of improving crop genetics, especially those traits relevant to abiotic stress management. This review provided updated and comprehensive knowledge concerning all possible combinations of advanced genomics tools and the gene regulatory network of reactive oxygen species homeostasis for the appropriate planning of future breeding programs, which will assist sustainable crop production under salinity and drought conditions.

Current Status of the Disease-Resistant Gene(s)/QTLs, and Strategies for Improvement in Brassica juncea.

Brassica juncea is a major oilseed crop in tropical and subtropical countries, especially in south-east Asia like India, China, Bangladesh, and Pakistan. The widespread cultivation of genetically similar varieties tends to attract fungal pathogens which cause heavy yield losses in the absence of resistant sources. The conventional disease management techniques are often expensive, have limited efficacy, and cause additional harm to the environment. A substantial approach is to identify and use of resistance sources within the Brassica hosts and other non-hosts to ensure sustainable oilseed crop production. In the present review, we discuss six major fungal pathogens of B. juncea: Sclerotinia stem rot (Sclerotinia sclerotiorum), Alternaria blight (Alternaria brassicae), White rust (Albugo candida), Downy mildew (Hyaloperonospora parasitica), Powdery mildew (Erysiphe cruciferarum), and Blackleg (Leptoshaeria maculans). From discussing studies on pathogen prevalence in B. juncea, the review then focuses on highlighting the resistance sources and quantitative trait loci/gene identified so far from Brassicaceae and non-filial sources against these fungal pathogens. The problems in the identification of resistance sources for B. juncea concerning genome complexity in host subpopulation and pathotypes were addressed. Emphasis has been laid on more elaborate and coordinated research to identify and deploy R genes, robust techniques, and research materials. Examples of fully characterized genes conferring resistance have been discussed that can be transformed into B. juncea using advanced genomics tools. Lastly, effective strategies for B. juncea improvement through introgression of novel R genes, development of pre-breeding resistant lines, characterization of pathotypes, and defense-related secondary metabolites have been provided suggesting the plan for the development of resistant B. juncea.

A Model for the Production of Regulatory Grade Viral Hemorrhagic Fever Exposure Stocks: From Field Surveillance to Advanced Characterization of SFTSV.

Severe fever with thrombocytopenia syndrome virus (SFTSV) is an emerging human pathogen, endemic in areas of China, Japan, and the Korea (KOR). It is primarily transmitted through infected ticks and can cause a severe hemorrhagic fever disease with case fatality rates as high as 30%. Despite its high virulence and increasing prevalence, molecular and functional studies in situ are scarce due to the limited availability of high-titer SFTSV exposure stocks. During the course of field virologic surveillance in 2017, we detected SFTSV in ticks and in a symptomatic soldier in a KOR Army training area. SFTSV was isolated from the ticks producing a high-titer viral exposure stock. Through the use of advanced genomic tools, we present here a complete, in-depth characterization of this viral stock, including a comparison with both the virus in its arthropod source and in the human case, and an in vivo study of its pathogenicity. Thanks to this detailed characterization, this SFTSV viral exposure stock constitutes a quality biological tool for the study of this viral agent and for the development of medical countermeasures, fulfilling the requirements of the main regulatory agencies.