ASHS 2024 Conference

In this interactive workshop, participants will be provided training on how to use Rosaceae (GDR, www.rosaceae.org), Vaccinium (GDV, www.vaccinoum.org) and Citrus (www.citrusgenomedb.org) specialty crop databases resources, as well as the Breeding Data Management tools, BIMS (www.breedwithbims.org), and the Field Book App for phenotype data collection. Using a case-study approach we will focus on how to use these integrated resources most efficiently for research and crop improvement efforts, how to apply FAIR data principles to sharing and submitting research data to these databases at the time of publication and facilitate a robust dialogue between researcher, breeders and the development team on needed improvements and long-term sustainability options for these resources.

This interactive workshop will bring together researchers and breeders to accelerate research and crop improvement in specialty crops. It will provide training and feedback on how to most effectively use the NIFA SCRI and National Research Support project 10 (NRSP10) funded Rosaceae, Citrus, and Vaccinium specialty crop databases and breeding data management resources (BIMS and Field Book), learn how to follow FAIR data principles, foster better two-way communication for increased feedback from researchers on further development of these resources, and continue to build a robust community around these research and crop improvement tools. The trainers include users and developers of these resources, ranging from early career to well-known and respected research enabling resource generators.

The Genome Database for Rosaceae (GDR), Genome Database for Vaccinium, and Citrus Genome Database (CGD) offer critical resources and tools to enable genomic, genetic, and breeding research for fruit, nut, and ornamental crops of great economic importance to the U.S. In addition, BIMS (BreedwithBIMS.org) and the Field Book APP provide widely used tools for managing plant breeding program data. While these resources are heavily used worldwide, many researchers are unaware of the full potential of using them and how they can contribute their own data for wider recognition and reuse. This interactive workshop aims to bridge this knowledge gap by providing hands-on training for specialty crop researchers on how to best use these resources and contribute their data. The workshop will also solicit ideas from participants on how to improve these databases and discuss the various options to make them sustainable in the long term. The workshop will bolster the utilization of integrated big data, promote future data sharing, and ensure that data is FAIR (Findable, Accessible, Interoperable, and Reusable).

The workshop aims to bring together researchers to accelerate research by more effective use of specialty crop databases and breeding data management resources, encouraging data submission at the time of publication, and gaining feedback from researchers. Through hands-on training, participants will become more familiar with the database resources and breeding data management tools, learn how to submit their data, and provide essential input for improving these databases and their long-term sustainability.

Coordinator(s)

• Dorrie Main, Washington State University, Pullman, WA, United States

Moderator(s)

• Cameron Peace, Washington State University, Horticulture, Pullman, WA, United States

Speaker/Participant(s)

• Dorrie Main, Washington State University, Pullman, WA, United States

Introduction to the Workshop and Specialty Crop Research Databases (15 mins)

• Jodi Humann, Washington State University, Horticulture, Pullman, WA, United States

How to efficiently use integrated genomics data and tools for research (20 mins)

• Sook Jung, Washington State University, Horticulture, Pullman, WA, United States
  How to efficiently use integrated genetics data and tools for research (20 mins)
  
  
• Nahla Bassil, USDA ARS, National Clonal Germplasm Repository, Corvallis, OR, United States
  How to efficiently use integrated germplasm and genotype data for research (15 mins)
  Summary:
  
  
• Trevor Rife, Clemson University, Plant and Environmental Sciences Department, Florence, SC, United States
  How to use the Field Book App for phenotypic data collection (15 mins)
• Sushan Ru, Auburn University, Auburn, United States
  How to use the Breeding Information Management System, BIMS, for Crop Improvement (20 mins)
• Cameron Peace, Washington State University, Horticulture, Pullman, WA, United States

After a brief introduction about BioChambers, Patrick Friesen (PhD) will talk about using growth chambers to effectively vernalize and cross perennial and biennial kales. The talk will focus on how to leverage the full environmental control growth chambers provide for successful synchronous flowering, sharing key details about growth temperatures, photoperiod, and light (quantity and quality) conditions used. This presentation is based on a successful crossing experiment, which is aimed toward breeding perennial kales that can successfully overwinter in southern Manitoba, Canada.

Genome-wide Association Study and Genome Prediction of Verticillium Wilt Resistance in Spinach - Kenani Chiwina
Spinach Seed for Grain Consumption: Feasibility and Potential for Genetic Improvement - Carlos Avila
Progress and Insights Into Downy Mildew Resistance Mapping Efforts in Spinach - Gehendra Bhattarai
Screening Baby Leaf Salad Greens for Downy Mildew Resistance - Shunping Ding
Detection of Novel Lettuce Fusarium Wilt Pathogenic Variants in California - Santosh Nayak
Unraveling Gene Regulation on the Interaction of Lettuce (Lactuca sativa L.) and Xanthomonas hortorum pv. vitians Causal Agent of Bacterial Leaf Spot. - Byron Manzanero
Exploring Physiological Traits as Predictors of Heat Content in Chile Peppers (Capsicum annuum L.) - Muhammad Ibrar Khan

Verticillium wilt, caused by Verticillium dahliae Kleb., poses a significant threat to spinach (Spinacia oleracea L.) production, necessitating genetic resistance as the primary defense against this disease. This study conducted a comprehensive genome-wide association study (GWAS) to identify single nucleotide polymorphism (SNP) markers linked to Verticillium wilt resistance in spinach and to evaluate genomic prediction for disease resistance. GWAS utilized a panel of 98 spinach germplasm accessions and 20,742 SNPs obtained from whole-genome resequencing. Various statistical models, including GLM, MLM, FarmCPU, and BLINK, were employed using the GAPIT 3 tool for analysis. Two quantitative trait loci (QTL) regions on chromosome 6 were found to be significantly associated with Verticillium wilt resistance. Specifically, SNP SOVchr6_29382746 at 29,382,746 bp and three SNPs (SOVchr6_86904401, SOVchr6_86906249, and SOVchr6_86906255) at 86,904,401 bp and 86,906,249 bp, respectively, demonstrated notable associations with disease resistance. Genomic prediction exhibited high accuracy, with a prediction ability (GA) represented by an r value of 0.95 for the panel. The identified SNP markers, along with the high prediction ability, offer valuable tools for breeders to select Verticillium wilt-resistant spinach plants and lines through molecular breeding, incorporating marker-assisted selection (MAS) and genomic selection (GS) strategies.

Spinach production is constantly challenged by endemic diseases that significantly reduce producers’ income. Even when resistant cultivars and cultural practices are used, mild disease damage can happen, negatively affecting quality and therefore reducing its commercial value. In contrast, under those conditions, spinach could still produce seed for grain with valuable nutritional content that can fetch premium prices for the gluten-free niche markets. This project evaluated grain production as an additional source of income by assessing yield potential, nutritional quality, and economic feasibility and potential for improvement. A total of ~200 USDA-NPGS accessions were evaluated for GWAS. For all nineteen amino acids evaluated, a wide range in content was observed. E.g. aspartic acid population mean was 106.5 nmol/g with a minimum of 36.2 nmol/g and a maximum of 353.9 nmol/g. Similar results were observed for all eight minerals evaluated. E.g. K population mean was 9,998.1 mg/kg with a minimum of 3,227 mg/kg and a maximum of 24,770 mg/Kg. High diversity can be used to improve nutritional content in spinach seed. Several SNP markers associated with amino acid and mineral content were identified in more than one nutrient, indicating pleiotropic genetic control. Furthermore, protein digestibility tests indicate that spinach provides ~50% of all amino acids required in the diet as compared with Amaranth and Quinoa protein in grain that provided ~20% of all amino acid required. Therefore, indicating spinach grain has a higher nutritional content as compared with highly demanded Amaranth and Quinoa grains. Finally, a partial budgeting approach was used to assess the economic feasibility of producing spinach seeds for grain. The added costs totaled US$ 218.71/ac, including custom harvesting (US$ 24/ac), an additional application of fertilizers (US$ 17.36/ac) and fungicide (US$ 62.54/ac), extra irrigation costs (US$ 60.63), and US$ 54.18/ac in associated interest on production expenses. The break-even price of seeds was estimated to be equal to US$ 0.20/lb when the average experimental yield was considered (i.e., 1,089lbs/ac). Producing seed for grain could expand the farmer portfolio, increase farmed acreage, and fringe products.

Spinach (Spinacia oleracea) is a popular leafy vegetable crop in the US, particularly for the fresh market baby leaf spinach. However, downy mildew (DM), caused by the obligate oomycete Peronospora effusa, poses a significant challenge to spinach cultivation in California and Arizona as it reduces the quality and yield of spinach. This is particularly concerning given that the two production areas contribute over 85% of the total fresh market spinach in the US. The emergence of new races of P. effusa, with nineteen races reported and fourteen identified in the last two decades, presents a persistent threat as new races and variant isolates can overcome the existing resistance in commercially deployed cultivars. Furthermore, over 50% of the spinach market is organic production, so utilizing host genetic resistance is a crucial disease management strategy. To combat this challenge, we conducted screenings of germplasm, cultivars, and multi-parent progeny populations in greenhouse conditions to identify resistant sources and genomic regions associated with resistance to multiple races of P. effusa (specifically race 5, 13, and 16). The spinach population panel was sequenced utilizing genotyping by sequencing (GBS), low coverage resequencing, and 10x coverage whole genome resequencing (WGR) to generate single nucleotide polymorphisms (SNP) markers. Subsequently, genetic analysis was performed using disease phenotype response data obtained and SNP markers for the identification of resistance-associated SNP markers and candidate resistance genes. The molecular analysis and mapping efforts have yielded valuable insights into the basis of downy mildew resistance in spinach, providing essential molecular tools to facilitate breeding for disease resistance. This work will summarize the updated findings from these efforts. This work will enhance our understanding of resistance mechanisms, which will contribute to developing more effective breeding strategies, increasing selection gains and breeding efficiency in spinach.

Downy mildew presents major challenges to baby leaf salad greens production in California. Baby kale (Brassica oleracea) particularly holds substantial economic value in the region with a crop value of over $12 million in 2022. Downy mildew, caused by the oomycete pathogen Hyaloperonospora brassicae, infects baby kale resulting in leaf chlorosis, necrosis, and sporulation, rendering affected leaves unmarketable. Resistant varieties offer an effective solution, reducing the need for pesticides and promoting sustainable disease management in baby kale production. This research aims to screen baby kale plant materials (accessions) for resistance to downy mildew isolates from across California. Initially, 212 baby kale accessions were evaluated for resistance using a downy mildew isolate from Gilroy, CA. Plants were inoculated with downy mildew spores and incubated in high-humidity conditions before being evaluated for disease symptoms. The initial screening indicated an average disease severity of 31%. From this screening, 50 accessions showing the lowest disease severity were further screened against seven additional downy mildew isolates. Among the subset of 50 accessions, disease severities ranged from 0.1% to 7.6%. Notably, nine accessions consistently exhibited a disease severity of 0%, and 17 accessions maintained disease severities of 0.1% or 0.2% across all seven isolates, making an elite secondary subset of accessions. Ongoing research includes replication trials with a secondary subset of accessions and the two most virulent and weak downy mildew isolates. This research will identify resistant baby kale varieties, providing valuable insights for breeders and improving downy mildew management practices in kale production systems.

Fusarium wilt (FW), caused by the soilborne fungus Fusarium oxysporum f.sp. lactucae (FOL), is an economically important disease of lettuce (Lactuca sativa L.). Four pathogenic races of FOL have been reported, though only race 1 is known to exist in the United States. Recently, California coastal lettuce growers have experienced changes in the severity and incidence of FW. Some race 1-resistant cultivars have exhibited susceptibility, whereas some susceptible cultivars have displayed a reduction in disease severity. In order to determine whether such changes in disease patterns are responses to potentially novel variants, we collected FW symptomatic plant samples from commercial fields in Salinas Valley and Santa Maria, recovered the fungus, and conducted a series of pathogenicity tests in controlled conditions over two years (2022 and 2023) using a standard set of FOL race differentials. Pathogenicity tests revealed two new FOL variants, Fol621s and 916, that elicited novel disease reaction patterns on the standard differentials which have never been reported in the United States or other parts of the world. Isolate 916 incited severe FW on race 1-resistant ‘Costa Rica No. 4’, whereas Fol621s was less virulent on race 1-suceptible ‘Banchu Red Fire’. This study provides valuable information critical for the development of FW management strategies, including broad-spectrum resistance breeding efforts against multiple FOL races and novel variants.

Bacterial leaf spot (BLS) of lettuce is a sporadic and destructive foliar disease that poses an economic threat to farmers, particularly those within Florida due to the subtropical environmental conditions. The disease is caused by the bacteria Xanthomonas hortorum pv. vitians (Xhv), which has three races. There are no chemical interventions that can effectively control this pathogen, creating a significant challenge for farmers to manage BLS. Additionally, most commercial lettuce cultivars are susceptible to BLS, emphasizing the need to improve host resistance. Resistance to Xhv race-1 has been identified in heirloom lettuce PI 358001-1 and ‘La Brillante’, and PI 667690. To facilitate and accelerate modern plant breeding techniques and the introgression of resistance into new cultivars, the identification of resistance genes is crucial. However, a detailed description on how these genes is regulated in the lettuce genome remains unknown. To aid in the understanding of the interaction between lettuce and Xhv, a gene expression study was conducted. A total of 180 plants each of La Brillante (R), PI 358001-1 (R), PI 667690 (R), and Okeechobee (S) were grown in laboratory conditions for 21 days. Half of the plants were mock inoculated with buffer, and the remaining plants were inoculated with Xhv race-1 isolate L7. Leaf samples were collected at 24-, 72-, and 144-hours post-inoculation, and RNA was extracted for sequencing using the Illumina NovaSeq 6000 platform. The analysis of differentially expressed genes and their associated pathways revealed distinct reactions upon interaction with Xhv. Additionally, similar reactions were observed in other crops and their respective Xanthomonas pathovars, such as the upregulation of peroxidases, chitinases, and proteases, were observed between inoculated and mock-inoculated plants, such response was time point dependent. Primers will be designed and validated for these candidate genes using qPCR with additional time points to confirm their expression across key plant development stages. These findings provide valuable insights into the molecular resistance of lettuce to BLS, unlocking new opportunities for molecular breeding techniques, identification of chemical compounds within the plant that control BLS, and the development of new resistant cultivars. This knowledge will benefit not only the UF/IFAS lettuce breeding program, but also be disseminated to other research groups working to breed BLS-resistant lettuce cultivars.

Chile peppers (C. annuum L.) are valued for their capsaicinoid content, which contributes to their pungency (heat) and has various health benefits, including anti-inflammatory and anti-cancer properties. Assessing photosynthetic efficiency through the LICOR-600 porometer/fluorometer (https://www.licor.com/env/products/LI-600/) provides insights into the physiological vigor of the plants. This study employs a comprehensive suite of machine learning models to investigate the correlation between photosynthetic efficiency (stomatal conductance and chlorophyll a fluorescence) and Scoville Heat Units (SHU) to predict the capsaicinoid content within 20 chile pepper varieties. Photosynthetic data were collected at two sites, Fabian Garcia Science Center and Leyendecker Plant Science Research Center, Las Cruces, NM, with readings taken from three different leaves of each of five plants per genotype. Capsaicinoid levels were quantified using High-Performance Liquid Chromatography (HPLC) for each variety. Correlation and principal component analyses (PCA) were implemented to discern the primary influencers on capsaicinoid production. Five predictive models were explored: Decision trees, Random forests, Ridge regression, LASSO Regression, and Support Vector Regression. Each model was applied to predict both total SHU values and categorical SHU labels (mild, hot, very hot). Among these, the decision tree model was the most superior, achieving an R² of 0.77. Initial findings indicate notable variability in photosynthetic activity and capsaicinoid concentrations across the varieties, suggesting a significant but complex relationship that may guide future genetic improvements. The challenges in modeling can be attributed to data collection constraints. Additionally, uniform growing conditions across all test plants might have limited the variability necessary for more definitive model differentiation. This analysis not only advances our understanding of the physiological and genetic factors affecting capsaicinoid content but also underscores the complexities of modeling agricultural traits under consistent environmental conditions. Future research should consider more frequent data collection and the introduction of environmental stressors to better capture the dynamics influencing capsaicinoid production in chile peppers. Key word: High-Performance Liquid Chromatography, Scoville heat unit, photosynthetic efficiency