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Objective: Cucumber mosaic virus (CMV) is a significant pathogen causing quality loss in spinach. Although host genetic resistance is the primary method of managing CMV infection in this crop, CMV resistance genes are not widely utilized in spinach breeding programs as the genetic and molecular mechanisms underlying resistance are not yet fully understood. CMV infections were therefore studied in different lines of spinach plants, and their progeny, to develop a model of the genetic basis of CMV resistance. Results: Visual observations and RT-PCR assays revealed that three monoecious lines (03-258, 03-263, and 03-336) were susceptible to CMV, while three traditional resistant cultivars and a near-isogenic line (NIL-M) exhibited resistance. A dioecious line (03–009) consisted of susceptible and resistant plants. Notably, resistant plants did not exhibit the lesions typical of the hypersensitive response. Genetic analysis of progeny from the cross NIL-M × 03-336 indicated that a single dominant allele (designated SRCm1, standing for Spinach Resistance to CMV 1) controlled CMV resistance; analysis of sib-cross progeny populations derived from line 03–009 supported this conclusion. These results offer a valuable model for CMV resistance in spinach and will enhance future breeding programs. [ABSTRACT FROM AUTHOR]

Background: Genomewide prediction estimates the genomic breeding values of selection candidates which can be utilized for population improvement and cultivar development. Ridge regression and deep learning-based selection models were implemented for yield and agronomic traits of 204 chile pepper genotypes evaluated in multi-environment trials in New Mexico, USA. Results: Accuracy of prediction differed across different models under ten-fold cross-validations, where high prediction accuracy was observed for highly heritable traits such as plant height and plant width. No model was superior across traits using 14,922 SNP markers for genomewide selection. Bayesian ridge regression had the highest average accuracy for first pod date (0.77) and total yield per plant (0.33). Multilayer perceptron (MLP) was the most superior for flowering time (0.76) and plant height (0.73), whereas the genomic BLUP model had the highest accuracy for plant width (0.62). Using a subset of 7,690 SNP loci resulting from grouping markers based on linkage disequilibrium coefficients resulted in improved accuracy for first pod date, ten pod weight, and total yield per plant, even under a relatively small training population size for MLP and random forest models. Genomic and ridge regression BLUP models were sufficient for optimal prediction accuracies for small training population size. Combining phenotypic selection and genomewide selection resulted in improved selection response for yield-related traits, indicating that integrated approaches can result in improved gains achieved through selection. Conclusions: Accuracy values for ridge regression and deep learning prediction models demonstrate the potential of implementing genomewide selection for genetic improvement in chile pepper breeding programs. Ultimately, a large training data is relevant for improved genomic selection accuracy for the deep learning models. [ABSTRACT FROM AUTHOR]

Background: Genomic libraries of introgression lines (ILs) consist of collections of homozygous lines with a single chromosomal introgression from a donor genotype in a common, usually elite, genetic background, representing the whole donor genome in the full collection. Currently, the only available melon IL collection was generated using Piel de sapo (var. inodorus) as the recurrent background. ILs are not available in genetic backgrounds representing other important market class cultivars, such as the cantalupensis. The recent availability of genomic tools in melon, such as SNP collections and genetic maps, facilitates the development of such mapping populations. Results: We have developed a new genomic library of introgression lines from the Japanese cv. Ginsen Makuwa (var. makuwa) into the French Charentais-type cv. Vedrantais (var. cantalupensis) genetic background. In order to speed up the breeding program, we applied medium-throughput SNP genotyping with Sequenom MassARRAY technology in early backcross generations and High Resolution Melting in the final steps. The phenotyping of the backcross generations and of the final set of 27 ILs (averaging 1.3 introgressions/plant and covering nearly 100 % of the donor genome), in three environments, allowed the detection of stable QTLs for flowering and fruit quality traits, including some that affect fruit size in chromosomes 6 and 11, others that change fruit shape in chromosomes 7 and 11, others that change flesh color in chromosomes 2, 8 and 9, and still others that increase sucrose content and delay climacteric behavior in chromosomes 5 and 10. Conclusions: A new melon IL collection in the Charentais genetic background has been developed. Genomic regions that consistently affect flowering and fruit quality traits have been identified, which demonstrates the suitability of this collection for dissecting complex traits in melon. Additionally, pre-breeding lines with new, commercially interesting phenotypes have been observed, including delayed climacteric ripening associated to higher sucrose levels, which is of great interest for Charentais cultivar breeding. [ABSTRACT FROM AUTHOR]

Background: Stevia rebaudiana (Asteraceae), native from Paraguay, accumulates steviol glycosides (SGs) into its leaves. These compounds exhibit acaloric intense sweet taste which answers to consumer demands for reducing daily sugar intake. Despite the developpement of S. rebaudiana cultivation all over the world, the development of new cultivars is very recent, in particular due to a colossal lack of (1) germplasm collection and breeding, (2) studies on genetic diversity and its structuring, (3) genomic tools. Results: In this study, we developped 18 EST-SSR from 150,258 EST from The Compositae Genome Project of UC Davis (http://compgenomics.ucdavis.edu/data/). We genotyped 145 S. rebaudiana individuals, issued from thirty-one cultivars and thirty-one landraces of various origins worldwide. Markers polymorphic information content (PIC) ranged between 0.60 and 0.84. An average of 12 alleles per locus and a high observed heterozygoty of 0.69 could be observed. The landraces revealed twice as many private alleles as cultivars. The genotypes could be clustered into 3 genetic populations. The landraces were grouped in the same cluster in which the oldest cultivars "Eirete" and "MoritaIII" type are also found. The other two clusters only include cultivated genotypes. One of them revealed an original genetic variability. SG phenotypes could not discriminate the three genetic clusters but phenotyping showed a wide range of composition in terms of bitter to sweet SGs. Conclusion: This is the first study of genetic diversity in Stevia rebaudiana involving 145 genotypes, including known cultivars as well as landrace populations of different origin. This study pointed out the structuration of S. rebaudiana germplasm and the resource of the landrace populations for genetic improvement, even on the trait of SG's composition. [ABSTRACT FROM AUTHOR]