Fresh weight was used due to the large number of plants and measurements being done in situ in the field setting. All measurements were made in kg. To measure the BRIX value of the fruit, the collected tomatoes was taken to the lab where the juice was squeezed out and measured on a refractometer . The yield and BRIX for each plant were multiplied together to get the BRIX x Yield Index , which gives an overall fruit quality measure, accounting for variations and extreme values in either measurement. It should be noted that while BRIX is used as a standard quality measure, BY is a composite value that folds in yield to assess kilograms of soluble solids per plant and is used to measure commercial quality and not consumer quality .Leaf shape and complexity measures were performed for the 2014, 2015, and 2016 field season. Subsequently, primary leaflets were used for imaging and analysis of shape and size as described , and the images then processed in ImageJ . The images were cropped to individual leaflets maintaining the exact pixel ratio of the original image, and then cropped again to only include the single leaflet using a custom Java script written for FIJI . Single leaflet images converted to a binary image as black on a white background and smoothed to allow for the exclusion of any particulates in the image and were then processed in SHAPE , plastic plant pot a shape analysis software.
Leaflet images were imported and then aligned along their axes so that all images faced the same direction and then were processed using elliptical Fourier analysis based on the calculated number of harmonics. PCA was performed on the resulting eFourier analysis and the Principal Components used for subsequent analysis . The PC values were used for all subsequent leaflet shape analyses. Total leaf area for each plant was measured by imaging the whole plant and a 4 cm2 red square and then processed in the Easy Leaf Area software .Plants were grown in the field to flowering stage for the lines M82, BIL 260, and sub IL 4-3-4. Three leaf punches from three separate leaves were collected from each plant every two hours for twenty-four hours. For sugar analysis leaf punches were then heated in 500 mL of 100% Ethanol for 20 minutes at 80 C and the liquid collected and stored at -80 C. The discs were then heated in 100% ethanol at 80 C for 20 minutes a second time. The discs were then placed in 500 L of 5% Sodium Hydroxide and heated for 20 minutes at 80 C. After cooling to root temperature 125 L of 5M HCl was added to neutralize the solution and then the supernatant discarded. The discs were then resuspended in 500 uL of 50 mM Sodium Acetate Buffer and ground by hand 2 mL Eppendorf tubes , after which they were spun down at 13,000 rpm for 1 minute. 25 L of starch degradation mix, consisting of Amyloglucosidase and a-Amylase in 50 mM Sodium Acetate Buffer, was added to the solution. The solution was incubated at 65 C for 24 hours and then the enzymes inactivated by heating at 80 C for five minutes. To measure sugar and starch content of the leaves, the solution was processed by the sugar assay as described by Rowland et al., 2019.Three to five leaf punches per plant were collected from individual leaves for each genotype.
The leaf punches were cleared by heating in 100% EtOH for 20 minutes three consecutive times and then heated at 80 C for 20 minutes in 5% NaOH and then the liquid discarded. After this 50% Bleach was added to the discs and they were incubated at root temperature for 20 minutesand then rinsed several times with water. The leaf discs were stained with 1% safranin and then imaged on an Eclipse C1 plus microscope at a fixed magnification .Count data of the DEGs was normalized across all samples prior to UMAP dimensionality reduction. UMAP dimensionality reduction was performed using the Julia package, UMAP. In order to identify smaller sets of genes with similar expression patterns, Mean Shift clustering was performed . GO enrichment analysis using the R package, GOseq , was performed on the 39 generated clusters. Cluster 19 was found to have GO terms “extracellular region” and “carbohydrate metabolic process”, among others. WGCNA was used to construct gene coexpression networks using normalized expression data of genes from cluster 19. Pearson correlation cutoff value of 0.95 was used. Separate networks for BIL260 and M82 were constructed. Networks were visualized using Cytoscape .BIL260 x M82 back crosses were made by removing the stamens from the female plant, and then these flowers were painted with pollen from the “male” plant with a paint brush. Flowers were bagged to tag and isolate from other nearby flowers and collected when mature. F1 seed were grown up in the greenhouse to generate F2 seed. The F2 plants were then grown in a random order in the field to perform analysis and collect seed. These plants were labeled 1 through 400. The F3 plants were grown in the greenhouse to characterize the plants for leaf shape, vasculature, and BY.The fleshy fruits produced by strawberry , tomato , and many other horticulturally important plants are susceptible to post harvest decay by gray mold, a devastating disease caused by the necrotrophic fungal pathogen Botrytis cinerea . Botrytis cinerea can infect most organs of the plant but is especially destructive on ripe fruit and senescent tissues of dicotyledonous hosts .
Gray mold renders strawberries unmarketable and often causes significant postharvest losses under conditions favorable for pathogen growth . The mechanisms of defense against B. cinerea are physiologically and genetically complex and markedly differ from the gene-for-gene resistance and programmed cell death mechanisms commonly triggered by biotrophic pathogens . As with other necrotrophic pathogens, B. cinerea pathogenesis is promoted by fruit ripening and host cell death . Consequently, genetic variation for resistance to gray mold tends to be subtle, limited, and quantitative, which undoubtedly underlies the paucity of studies on breeding for resistance to this pathogen . Because natural genetic resistance has been insufficient to prevent post harvest gray mold disease development, preharvest fungicides are often applied to suppress pathogen growth and minimize post harvest losses . Controlling B. cinerea with fungicides is difficult because the airborne inoculum is present year round, the host–pathogen interactions are complicated, and the pathogen rapidly evolves resistance to fungicides, particularly after repeated applications of specific chemicals . Moreover, preharvest foliar applications of fungicides have not been shown to be effective for reducing post harvest gray mold incidence in strawberry fruit possibly because many fruit infections arise from contaminated flower tissues . The development of gray mold resistant cultivars has been challenging in strawberry and other hosts because most genotypes are highly susceptible, strong sources of natural genetic resistance have not been identified, plastic planter pot and resistance mechanisms are quantitative . The feasibility of selecting for increased resistance to gray mold has not been deeply explored in strawberry, a species where limited studies have been undertaken to shed light on the genetics of resistance and assess genetic variation for resistance . The problem of breeding for resistance to gray mold has been most extensively studied in tomato, albeit without achieving robust or foolproof solutions . Genetic studies in tomato and Arabidopsis leaves have identified multiple small-effect quantitative trait loci that only account for a small fraction of the genetic variation for resistance, seldom translate across genetic backgrounds, and have not solved the problem of breeding for resistance to gray mold . Although genetic studies of similar depth and breadth have not been undertaken in strawberry, previous studies have not uncovered strong sources of resistance to gray mold . We suspected that selection for increased fruit firmness and other fruit quality traits that extend shelf life pleiotropically increased resistance to gray mold in strawberry. While hypotheses can be formulated from insights gained from genetic studies in tomato and other hosts , natural genetic resistance appears to be negligible and quantitative and additive genetic correlations between gray mold resistance and fruit quality phenotypes are unknown in strawberry . The susceptibility of strawberry fruit to B. cinerea increases during ripening , which suggests that susceptibility factors accumulate independent of defense mechanisms during fruit maturation and senescence, as is typical for this necrotroph . Changes in fruit firmness and other fruit quality traits associated with fruit maturation and ripening in tomato have been shown to increase susceptibility to B. cinerea . Although previous studies have been somewhat inconclusive in strawberry, firm-fruited cultivars are predicted to be more resistant to B. cinerea than soft fruited cultivars . Moreover, ripening induced differences in proanthocyanidin and anthocyanin accumulation have been predicted to affect B. cinerea resistance in tomato and strawberry .
To more deeply explore the genetics of resistance to gray mold and assess the feasibility of applying genomic selection for increased resistance to gray mold in strawberry, we developed and studied training populations segregating for fruit quality traits predicted to affect shelf life. Genomic prediction approaches are particularly attractive for post harvest traits that are difficult and costly to phenotype in strawberry but still require sufficient accuracy to complement phenotypic selection and achieve genetic gains . The training populations for our studies were developed from crosses between firm-fruited long shelf life cultivars and soft-fruited short shelf life cultivars. Although the gray mold resistance phenotypes of the parents of these populations were unknown, our hypothesis was that selection for extended shelf life has pleiotropically increased resistance to gray mold in strawberry, primarily because fruit of LSL cultivars deteriorate more slowly in post harvest storage than those of SSL cultivars. We describe a highly repeatable artificial inoculation protocol for gray mold resistance phenotyping developed for the GS studies described herein. Finally, we discuss the prospects for increasing genetic gains for resistance to gray mold through the application of genomic prediction approaches.We developed a high-throughput protocol for post harvest phenotyping of B. cinerea disease progression and symptom development on ripe fruit. Spore suspensions of the B. cinerea strain B05.10 were produced from spores grown on potato dextrose agar as described by Petrasch et al. . Uniformly ripe fruit were harvested at sunrise, avoiding fruit that were under- or over-ripe. The fruit were immediately transferred to cold storage and inoculated the day of harvest. Several incubation temperatures were tested to identify the optimum temperature for B. cinerea growth and development with a minimum of contamination from other post harvest decay pathogens. Fruit were placed on 30-cell plastic egg hatching trays with dimensions of 29 cm 29 cm and 4.5 cm 4.5 cm cells. The fruit were punctured once near the center with a 3 mm sterile pipette tip to an approximate depth of 1–2 mm. Ten ll of the B. cinerea conidia suspension was placed on the surface of the puncture. The inoculated fruit were incubated in a growth chamber at 10 C and 95% humidity for 14 days. Disease symptoms were assessed daily after inoculation by manually measuring lesion diameter and determining the number of days until external mycelium was evident on the surface of the fruit near the wound site. Fruit were phenotyped until mycelia covered the entire surface of the fruit. Spoiled fruit with infections outside of the inoculation site or caused by decay organisms other than B. cinerea were removed from the experiment. Genome-wide association study , QTL mapping, and GS analyses were applied to LD at 8 days post inoculation and EM.Fruit quality phenotypes were measured on one to four fruit harvested from individuals in the multifamily population at harvest. The fruit were photographed with a Sony a 6000 camera equipped with an E PZ 16–50 mm F3.5–5.6 OSS lens . Photographs were processed with a custom macro in Fiji to obtain RGB color metrics . RGB colors were subsequently converted into Lab colors using the convert Color function in R . Fruit firmness and fruit diameter were assessed on whole fruit using a TA.XT plus Texture Analyzer with a TA-53 3 mm puncture probe . Fruit samples were frozen at 20 C in WhirlPakVR Homogenizer Blender Filter Bags for quantifying titrable acidity , SSC , and total anthocyanin concentration .