Genetic mapping of a pollinator preference trait: Nectar volume in sunflower (Helianthus annuus L.)

Variant filters using segregation information improve mapping of nectar-production genes in sunflower (Helianthus annuus L.)

Accurate variant calling is critical for identifying the genetic basis of complex traits, yet filters used in variant detection may inadvertently exclude valuable genetic information. In this study, we compare common sequencing depth filters, used to eliminate error-prone variants associated with repetitive regions and technical issues, with a biologically relevant filtering approach that targets expected Mendelian segregation. The resulting variant sets were evaluated in the context of nectar volume quantitative trait loci (QTL) mapping in sunflower (Helianthus annuus L.). Our previous research failed to detect an interval containing a strong candidate gene for nectar production (HaCWINV2). We removed hard filters and implemented a chi-square goodness-of-fit test to retain variants that segregate according to expected genetic ratios. We demonstrate that biologically relevant filtering retains more significant QTL and candidate genes, including HaCWINV2, while removing variants due to technical errors more effectively, and accounted for 48.55% of nectar production phenotypic variation. In finding nine putative homologs of Arabidopsis genes with nectary function within QTL regions, we demonstrate that this filtering strategy has a higher power of true variant detection in QTL mapping than the commonly used variant depth filtering strategy. Future research will adapt the technique to multiple population contexts, such as genomic selection.

A guide to sunflowers: floral resource nutrition for bee health and key pollination syndromes

Sunflower, Helianthus annuus L., is a prominent global oilseed crop with rising cultivation and appeal as a bee-friendly plant by providing abundant floral resources for pollinators. Mass-flowering crops can increase the availability of resources, and sunflower is a good opportunity to relieve pollen scarcity during the late summer in agricultural landscapes. Yet this should be taken with caution as they also provide a homogeneous source of nutrition. This study aimed to review and summarize the nutritional profile of sunflower pollen, nectar, bee bread, and honey, while assessing their effects on bee survival, development, and health. Furthermore, we present here the general state of knowledge on additional pollinator syndromes that extend beyond floral resources, including those influencing pollinator visual and olfactory attraction. We found that while sunflower pollen's nutritional quality is questioned due to lower protein and amino acid deficiencies, its nutrient content, like nectar sugars, had large variability. Sunflower pollen consumption showed mixed effects on Apis mellifera and Bombus species, sometimes negatively impacting development and survival. However, studies have conveyed a positive impact on bee health as sunflower pollen consistently reduced the infection intensity of the gut parasite, Crithidia bombi, in Bombus species. This probes the question on defining the quality of floral resources, emphasizing the need for caution when categorizing sunflower as a low quality nutritional resource. This review also outlines the importance of sunflower nectar characteristics (sugar content and volume) and floral morphology (flower pigmentation and corolla length) on pollinator foraging preferences. A prominent knowledge gap persists regarding nectar chemistry and sunflowers' extensive volatile profile to better understand the pollination syndromes that drive its pollinator interactions.

Genotypic variation in blueberry flower morphology and nectar reward content affects pollinator attraction in a diverse breeding population

BACKGROUND

Pollination is crucial to obtaining optimal blueberry yield and fruit quality. Despite substantial investments in seasonal beekeeping services, blueberry producers consistently report suboptimal pollinator visitation and fruit set in some cultivars. Flower morphology and floral rewards are among the key factors that have shown to contribute to pollinator attraction, however little is known about their relative importance for improving yield in the context of plant breeding. Clarifying the relationships between flower morphology, nectar reward content, pollinator recruitment, and pollination outcomes, as well as their genetic components, can inform breeding priorities for enhancing blueberry production. In the present study, we measured ten flower and nectar traits and indices of successful pollination, including fruit set, seed count, and fruit weight in 38 southern highbush blueberry genotypes. Additionally, we assessed pollinator visitation frequency and foraging behavior over two growing seasons. Several statistical models were tested to optimize the prediction of pollinator visitation and pollination success, including partial least squares, BayesB, ridge-regression, and random forest.

RESULTS

Random forest models obtained high predictive abilities for pollinator visitation frequency, with values of 0.54, 0.52, and 0.66 for honey bee, bumble bee, and total pollinator visits, respectively. The BayesB model provided the most consistent prediction of fruit set, fruit weight, and seed set, with predictive abilities of 0.07, -0.08, and 0.42, respectively. Variable importance analysis revealed that genotypic differences in nectar volume had the greatest impact on honey bee and bumble bee visitation, although preferences for flower morphological traits varied depending on the foraging task. Flower density was a major driving factor attracting nectar-foraging honey bees and bumble bees, while pollen-foraging bumble bees were most influenced by flower accessibility, specifically corolla length and the length-to-width ratio.

CONCLUSIONS

Honey bees comprised the majority of pollinator visits, and were primarily influenced by nectar volume and flower density. Corolla length and the length-to-width ratio were also identified as the main predictors of fruit set, fruit weight, seed count, as well as pollen-foraging bumble bee visits, suggesting that these bees and their foraging preferences may play a pivotal role in fruit production. Moderate to high narrow-sense heritability values (ranging from 0.30 to 0.77) were obtained for all floral traits, indicating that selective breeding efforts may enhance cultivar attractiveness to pollinators.

A phosphatase gene is linked to nectar dihydroxyacetone accumulation in mānuka (Leptospermum scoparium)

Floral nectar composition beyond common sugars shows great diversity but contributing genetic factors are generally unknown. Mānuka (Leptospermum scoparium) is renowned for the antimicrobial compound methylglyoxal in its derived honey, which originates from the precursor, dihydroxyacetone (DHA), accumulating in the nectar. Although this nectar trait is highly variable, genetic contribution to the trait is unclear. Therefore, we investigated key gene(s) and genomic regions underpinning this trait. We used RNAseq analysis to identify nectary-associated genes differentially expressed between high and low nectar DHA genotypes. We also used a mānuka high-density linkage map and quantitative trait loci (QTL) mapping population, supported by an improved genome assembly, to reveal genetic regions associated with nectar DHA content. Expression and QTL analyses both pointed to the involvement of a phosphatase gene, LsSgpp2. The expression pattern of LsSgpp2 correlated with nectar DHA accumulation, and it co-located with a QTL on chromosome 4. The identification of three QTLs, some of the first reported for a plant nectar trait, indicates polygenic control of DHA content. We have established plant genetics as a key influence on DHA accumulation. The data suggest the hypothesis of LsSGPP2 releasing DHA from DHA-phosphate and variability in LsSgpp2 gene expression contributing to the trait variability.