Various antimicrobial compounds are correlated with AFR resistance, including 1-acetoxy-2-hydroxy- 4-oxoheneicosa-12,15-diene and avocadynone acetate in avocado, and dopamine and dopamine-derivatives in banana. In blueberry, resistance was previously hypothesized to come from the interaction of several compounds, including phenolics and organic acids . Supportive of this hypothesis, two non-anthocyanin f lavonoids from blueberry fruit, quercetin 3-Orhamnoside and putative syringetin-rhamnoside, were found to have antifungal activity against the causative agent of AFR. Alternatively, resistant fruits may prompt active resistance mechanisms such as inducible defense-related proteins, including chitinases and β-1-3-glucanases that degrade the cell wall. Expression of defense-related proteins in response to anthracnose fungi has been previously reported in pepper , apple, raspberry, tomato, and blueberry . Putative defense genes in blueberry include those that encode cell wall degrading protein, pathogenesis-related protein 10 , metallothionein-like protein, and monodehydroascorbate reductase. Moreover,hydroponic nft channel resistant fruits may actively combat anthracnose infection through the formation of reactive oxygen species .
Production of ROS in response to anthracnose has been documented in tomato, strawberry, and blueberry. In all three crops, ROS occurs at or near the time of attempted penetration of the pathogen. Concurrently, infected fruits upregulate expression of oxidative stress response genes to minimize potential harmful effects of the ROS on the host’s own tissues. In this study, we sought to identify genomic loci associated with resistance to AFR by examining a genetic mapping population with tremendous variation in susceptibility. In order to capture allele and sub-genome-specific variation that might be associated with resistance, we mapped to a fully haplotype resolved genome assembly with no explicit association made between the locations of the equivalent bases in the different subgenomes/haplotypes. Cultivated high bush blueberry has a rich history of introgression from multiple other wild blueberry species from breeding efforts, plus natural gene f low that has previously shown to occur among sympatric blueberry species. We have an unpublished analysis, as part of another study, that suggests that the genome of cultivar ‘Draper’, one of the parents analyzed here, has minimally 23% introgressed from at least three other Vaccinium species. This may, in part, be the reason why we identified significant candidate genomic regions in only one of the homoeologous chromosomes. Homoeologous chromosomesets are shown in Supplemental Figure S5.
The different homoeologous chromosomes of ‘Draper’ exhibit high sequence divergence. In effect, the tetraploid was treated in alignment terms as a single fully expanded haploid. QTL mapping tools are available that function for polyploids, but they frequently depend on other tools such as polymap that require dosage information that we are not exploring in the current work or require rather specific types of population that were not generated as a part of this study. Meanwhile, the GWAS approaches are necessarily somewhat robust to variable levels of population relatedness, explicitly incorporating this in approach-specific ways, while more recent GWAS approaches adopt elements of QTL mapping to improve their sensitivity. Both the FARMCPU approach and BLINK approach for example exploit the generation of pseudo-markers and marker aggregation, FARMCPU using block-interval marker aggregation with block-size determined by MLE and BLINK marker aggregation in discovered bayesian linkage groups to recover essentially much of the power lost in approaches such as GWAS GLM/MLM where markers are considered essentially individually. Nonetheless, the different GWAS approaches selected very similar sites with only the association strength being notably different. BLINK and FARMCPU in this respect achieved higher levels of significance at these consistent sites likely due to their mapping-like marker aggregation. We have added to the supplementals a QTL mapping study results that includes standard interval mapping, composite interval mapping, and multiple QTL mapping to test whether the QTL and GWAS approaches are essentially in agreement.
The QTL approaches largely support the GWAS sites albeit with the limitations on marker selection discussed above not always leading to greatly enhanced levels of significance relative to FARMCPU/BLINK . In addition, we reran GWAS and QTL analysis to examine results with a binary categorization of susceptibility . There was no evident increase in association power when classifying the genotypes in a binary form . We identified three loci located on pseudomolecules 17, 23, and 28 in the V. corymbosum ‘Draper’ genome that are significantly associated with the resistance phenotype . Having several candidate causal SNPs is consistent with a polygenic resistance trait that may partly contribute to the observed continuous fruitrot susceptibility distribution. Variants in several linked biosynthesis pathways, including cytokines, anthocyanins, and other f lavonoids such as quercetin, may have become established in the population due to a protective role gained over time against multiple fungal pathogens. The identification of these loci will be useful for developing a molecular marker-assisted selection protocol for blueberry, which will greatly facilitate future screening for AFR resistance early in the breeding and selection process. Several candidate genes within these QTLs were previously associated with resistance against pathogens and/or f lavonoid biosynthesis, including anthocyanins. In comparing gene expression of blueberry fruits infected with C. fioriniae to uninfected fruits, numerous biological processes showed differential expression across the infection time course. Within 1 hour of infection, infected samples began upregulating genes related to metabolic pathways, including starch and sucrose metabolism and biosynthesis of secondary metabolites. In the following days, genes involved in metabolic pathways and biosynthesis of secondary metabolites continued to be upregulated. Additionally, the biosynthesis and metabolism of other primary and specialized metabolites and plant hormones were upregulated. Notably, many of the differential KEGG pathways show associations with the metabolite marker quercetin 3-Orhamnoside. Most clearly, phenylpropanoid and f lavonoid biosynthesis can be tied directly to quercetin 3-O-rhamnoside content as this metabolite falls within the phenylpropanoid and f lavonoid families of specialized metabolites. Furthermore, the biosynthesis of amino acids may also be connected to quercetin 3-Orhamnoside, as L-phenylalanine, an amino acid, is a precursor of quercetin 3-O-rhamnoside.
Our transcriptome analyses identified an enrichment of significantly differentially expressed genes associated with certain specialized metabolic pathways and pathogen resistance. Plus, several candidate genes within these QTLs were previously associated with resistance againstpathogens and/or f lavonoid biosynthesis, including anthocyanins. However, it’s important to note that none of these genes were identified as significantly differentially expressed. Low expressed genes, including certain regulators ,may not be identified as significantly differently expressed but can cause a cascade of transcriptional changes,nft growing system including inducing certain genetic pathways, and impact certain phenotypic traits. Thus, it’s possible that our transcriptome analyses were unable to identify them based on the current data and significance thresholds.We hope that the community will engage in combining these results with their own to further explore the data and identify additional potential candidate genes. Lastly, we identified a f lavonol glycoside with accurate mass, fragmentation, and absorbance characteristics consistent with a quercetin rhamnoside, whose abundance is significantly greater in berries from resistant individuals. These findings confirm data previously reported by Miles et al. , which identified quercetin 3-O-rhamnoside as an antifungal component of blueberry fruit. Several efforts were taken to normalize any variation in metabolite content due to fruit location on the bush, collection time, and fruit ripeness. Fruits within each subset were ground together and homogenized, resulting in three separate homogeneous mixtures of powdered fruit from each individual. Variability of the quercetin rhamnoside abundances was observed within resistant and susceptible individuals . Furthermore, levels of quercetin were previously shown to vary greatly between different harvests – indicating that the biosynthesis of these compounds may be inf luenced by the environment. In general, f lavonol glycosides are known to have antioxidant activity , and blueberry fruit f lavonol extracts demonstrate antioxidative activity against peroxyl and superoxide anion radicals. Taken with the hypotheses of Cipollini and Stiles , these findings suggest that quercetin 3-O-rhamnoside, a phenolic compound, is likely a major component of resistance to AFR in blueberry, but not the only component. Perhaps this molecule acts with other resistance mechanisms to protect the fruits from AFR. Traditional breeding efforts in blueberry have contributed to major improvements of various target traits, but it is a lengthy and expensive process for perennial crops. The use of molecular markers to guide breeding efforts has long been shown to greatly accelerate the development of superior cultivars, including selecting disease-resistant individuals.
There has been a strong community effort to develop and implement cost-effective methods for blueberry breeding programs. Collectively, we hope that these findings reported in this study will allow breeders to develop new resistant cultivars to AFR more efficiently and rapidly by leveraging these new genetic regions to identify and select resistant individuals in their breeding programs. The phenotype predictive power from the combination of the three markers on chromosomes 17, 23 and 28 was assessed using a multiple regression approach. Individually the Pearson product moment between phenotype on the 0–5 scale and genotype ranged from a low of 0.25 to a high of 0.30 , jointly a predictive model generated from all 3 sites had an r of 0.49 . In summary, to the best of our knowledge, this is the first study to identify potential markers associated with resistance to AFR in blueberry. We anticipate that additional markers and candidate genes will likely be identified as part of future studies of this important target trait in blueberry. We see the research presented in this manuscript as a stepping stone toward uncovering the underlying mechanism that contributes to anthracnose resistance in fruit of northern high bush blueberry.Farmland covers more than 35% of Earth’s ice-free terrestrial area, and agriculture is expanding and intensifying in many regions to meet the growing demands of human populations . This trend threatens biodiversity and the ecosystem services on which agriculture depends, including crop pollination . Indeed, recent reviews have highlighted how multiple anthropogenic pressures lead to a decline in wild pollinators such as bees, flies, beetles, and butterflies . However, practices to enhance wild pollinators in agroecosystems are still in development , and considerable uncertainty remains regarding their effects on crop yield and farmers’ profits. Here we review recent research on the topic, including the impacts of certain practices on wild pollinators, crop pollination, yield, and profits . We focus on practices that enhance the carrying capacity of habitats for wild insect assemblages that may then provide crop pollination services; practices to conserve or manage a particular pollinator species are outside our scope although they have received attention elsewhere . We offer general science-based advice to land managers and policy makers and highlight knowledge gaps. Throughout, we emphasize the need to consider population-level processes, rather than just short-term behavioral responses of pollinators to floral resources.Plant–pollinator interactions are typically very general, with many pollinators being rewarded with pollen, nectar, or other resources from several plant species , and with most angiosperms being pollinated by multiple insect species . Humans benefit from this generalized nature of pollination systems, as exotic crops brought far from their ancestral ranges can find effective pollinators within native insect assemblages . Accordingly, a synthesis of 600 fields from 41 crop systems showed that only two of the 68 most frequent pollinators globally were specialist species: the weevil Elaeidobius kamerunicus pollinating oil palm and the squash-bee Peponapis pruinosa pollinating pumpkin .Because of differences in species functional traits, greater pollinator richness can lead to foraging complementarity or synergy, improving the quantity and quality of pollination and therefore increasing both the proportion of flowers setting fruits and product quality . Across crop species, insects with contrasting mouth part lengths may be needed for the pollination of flowers not only with easily accessible rewards but also with rewards hidden at the bottom of a tubular corolla . Within a crop species, social and solitary bees visited flowering radish plants at different times of day, suggesting temporal complementarity among these pollinator groups . Flower visiting behavior also differs among pollinators of different body sizes, and visits by a range of differently sized pollinator species increase pumpkin pollination . In addition to functional traits, inter specific differences in response traits to climate and land-use change can increase resilience of pollination services . The role of diverse assemblages of wild insects in crop pollination is also evident from recent global analyses. Worldwide, incomplete and variable animal pollen delivery decreases the growth and stability of yields for pollinator-dependent crops . This lower yield growth has been compensated for by greater land cultivation to sustain production growth .