2022 Volume 91 Issue 2 Pages 140-151
Pollination is an important factor affecting fruit development in highbush blueberry (Vaccinium corymbosum L.). In general, planting several different blueberry cultivars increases the chances of cross-pollination and ensures high-quality fruit production. However, little is known about the effects of the pollen source on fruit development in blueberry. The aims of this study were: 1) to understand the effects of the pollen source on fruit size and quality; and 2) to explore the mechanisms underlying fruit development affected by the pollen source. We first characterized the pollination effect on fruit development using 14 different pollination combinations for several years and found that the number of mature seeds and fruit size differed significantly among the fruit pollinated by different pollen sources. Significant correlations between the number of mature seeds and fruit size were found in most combinations, whereas the number of mature seeds was not correlated with other fruit quality parameters such as sugar concentration. Our results and those of previous reports showed that the number of mature seeds, which was influenced by the pollen source, was a primary determinant of fruit size. Time-course observation during fruit development revealed that fruit weight and cell size significantly differed between self-pollinated and cross-pollinated fruit from 30 days after pollination onwards. To explore the molecular mechanisms underlying berry growth affected by developing seeds, we compared gene expression changes between self-pollinated and cross-pollinated fruit. Transcriptome analysis of fruit at 10 days after pollination suggested that auxin signaling pathways were enhanced in cross-pollinated fruit compared with self-pollinated fruit. We thus hypothesize that activated auxin signal transduction underlying early stage seed and fruit development may promote fruit cell enlargement during the early stage of fruit growth in highbush blueberry.
For highbush blueberry (Vaccinium corymbosum L.) production, cultivation practices for promoting cross-pollination, such as mixed planting of multiple cultivars and the release of pollinators, result in high-quality production. Because fruit set and fruit size affect yield, cross-pollination is one important way to increase productivity. Additionally, the maturation time affects growers’ income because early season fruit can be sold at a higher price. As reported a century ago by Coville (1921), self-pollination results in a lower fruit set, smaller fruit, and delayed maturation. Thus, cross-pollination is also useful for increasing profits in blueberry production.
The larger fruit size of cross-pollinated fruit compared with self-pollinated ones has been well documented in various blueberries, including highbush, rabbiteye (V. virgatum Ait.), lowbush (V. angustifolium Ait.), half-high (V. corymbosum L./V. angustifolium Ait.), and southern highbush cultivars (Ehlenfeldt, 2001; Meader and Darrow, 1944; Taber and Olmstead, 2016; Wood, 1968). Studies on those species and varieties showed that the larger fruit size of cross-pollinated fruit is often associated with a larger number of mature seeds. Krebs and Hancock (1988, 1990) suggested that the poor fruit set performance achieved by self-pollination may be due to early acting inbreeding depression and seed abortion. Additionally, there may be cross-incompatibility in blueberry because the effect of cross-pollination on the fruit size varies depending on the genetic background of the pollen- and seed-parent (Ehlenfeldt, 2001). Although the reduced fruit size of self-pollinated fruit appears to be associated with fewer mature seeds due to seed abortion, the detailed mechanisms of the relationship are still unclear. Moreover, there is little knowledge on the molecular mechanisms underlying the effects of seed development/abortion on blueberry fruit development.
Previous reports suggested a phenomenon in which the effect of pollen sources extends to maternal tissues, known as metaxenia, may occur in blueberries. Gupton (1997) reported that pollination with pollen from late-ripening cultivars tended to delay maturation, whereas pollination with pollen from early ripening cultivars tended to accelerate maturation, suggesting the existence of metaxenia (mentioned as “xenia” in the paper). The metaxenia effects were also reported for fruit size and quality. For example, Miller et al. (2011) found that cross-pollination with pollen from large-fruiting cultivars produced larger fruit in ‘Hortblue Petite (Blue Muffin)’. Kobashi et al. (2002) reported that the artificial cross-pollination of highbush blueberries increased the number of seeds and promoted sugar accumulation in fruit. They hypothesized that the increased number of mature seeds in the fruit produced by cross-pollination may increase abscisic acid contents, thereby enhancing invertase activity to induce sugar accumulation. In both cases, the differences in fruit size or quality produced by pollen sources were accompanied with changes in the viable seed number in mature berries. Ehlenfeldt (2003) reported that although some positive or negative pollen-based effects, i.e., larger/smaller and earlier/later-maturing fruit were observed, these effects largely depend on cross-compatibility, represented by mature seed number. Ehlenfeldt (2003) proposed that a metaxenia effect that is not explained by mature seed number may be rare, if any, because negative pollen-based effects occurred more frequently than positive effects. Consistent with this suggestion, recent studies by Doi et al. (2018) reported that although significant differences were found in seed numbers among fruit pollinated by different pollen sources, analysis of covariance indicated no statistically significant differences in fruit size and maturation time among fruit pollinated by different pollen sources. These reports collectively suggested that metaxenia effects on blueberry could be largely affected by the pollen source-dependent mature seed number. However, further pollination studies using various cross-combinations may be important and necessary to understand the metaxenia effects in blueberries.
The aims of this study were as follows: 1) to revisit the pollen source effect on seed number, fruit size, and fruit quality; and 2) to explore the possible molecular mechanisms underlying the effects of the pollen source on blueberry seed and fruit development. For this purpose, we conducted 14 different controlled artificial pollination combination tests and investigated the relationship between blueberry fruit size and the number of mature seeds. On the basis of the results of our microscopic observations and transcriptome analyses, we discuss the possible mechanisms underlying seed and fruit development. These findings have implications for the use of cross-pollination to improve blueberry fruit production.
For the artificial pollination tests in 2018 and 2019, field-grown ‘O’Neal’ and ‘Chandler’ grown at Miyagi Prefectural Agriculture and Horticulture Research Center were used as seed parents. As pollen parents, ‘O’Neal’, ‘Darrow’, ‘Misty’, and ‘Sunshine Blue’ were used in both years, whereas ‘Chandler’ was only used for self-pollination in the 2019 season. Three and two plants were used for each cross pollination combination of ‘O’Neal’ and ‘Chandler’, respectively (total of 15 and 10 plants of ‘O’Neal’ and ‘Chandler’, respectively). Flowers of pollen parents grown at the Experimental farm, Kyoto University, and the Shizuoka Research Institute of Agriculture and Forestry were collected just before anthesis. Their anthers were excised and air-dried for at least one day at room temperature with silica gel. Pollen was collected from the anthers and stored in a refrigerator with silica gel until artificial pollination. A preliminary experiment indicated that emasculation caused extensive flower drop. Thus, although emasculation was not conducted in this study, flowers were covered with bags before anthesis until one week after pollination to avoid pollination from other sources. Artificial pollination was conducted by gently rubbing stigmas with pollen on glass rods twice per flower with a one-day interval. In both experimental years, mature fruit were harvested when the tip of the peduncle at the fruit side and fruit stem end turned purple. The numbers of pollinated flowers and harvested fruits are shown in Table S1.
Evaluation of seed number, fruit size, and fruit qualityFruits were weighed, and then the number of seeds was counted for each fruit. Seeds were classified into mature (large and brown-colored) or aborted seeds. Fruit juice squeezed from flesh and peel samples was frozen in liquid N2 and stored at −80°C until analyses of sugar content/composition and acidity.
The soluble solids content in juice was measured using a refractometer (APAL-1; Atago Co., Ltd., Tokyo, Japan) in 2018 and a Pocket Brix‐Acidity Meter (PAL-BX | ACID F5 Master Kit; Atago) in 2019. Juice acidity was also measured using a portable acidity meter (PAL-BX | ACID F5 Master Kit; Atago) in 2018 and a Pocket Brix-Acidity Meter (Atago) in 2019. The composition of sugars (fructose, glucose, and sucrose) in the juices was determined by HPLC. For the 2018 samples, an HPLC system (detector: ED723, pump: PU7710; GL Science Inc., Tokyo, Japan) equipped with an InertSphere Sugar-1 column (4.6 mm × 150 mm, GL Science) was used. Samples were prepared by adding 1910 μL distilled water and 80 μL 2 g·L−1 D-sorbitol (internal standard) to 10 μL juice. Standard samples containing D-(−)-fructose, D-(+)-glucose, D-sorbitol, and sucrose were prepared and used to calculate the standard curve. Isocratic elusion was achieved at room temperature using 100 mM NaOH with a flow rate at 1.0 mL·min−1. The concentration of each sugar was determined by the internal standard method. In 2019, an HPLC system (column oven: CTO-20A, detector: RID-10A, LC driver: LC-20AT, system controller: CMA-20A, LC work-station: LC Solution; Shimadzu Corporation, Kyoto, Japan) equipped with a Shim-pack CLC-NH2 column (6 mm × 150 mm, Shimadzu) was used. Diluted juice samples were filtered through a 0.45-μm filter (Nylon Syringe Filter; Membrane Solutions LLC., Kent, WA, USA). Standard samples containing equal concentrations of D-(+)-glucose, D-(−)-fructose, and sucrose were prepared. Isocratic elusion was achieved with the column oven temperature set to 40°C and a solvent system consisting of 87% acetonitrile. The concentration of each sugar was determined by the external standard method. In both experimental years, we detected only trace amounts of sucrose, so these results are not shown. This is consistent with a previous report that fructose and glucose account for more than 90% of total sugars in blueberry (Ito, 1991).
Pollen viability testA germination test was conducted in 2019 using pollen collected from plants of ‘O’Neal’, ‘Misty’, and ‘Sunshine blue’ growing at the Shizuoka Research Institute of Agriculture and Forestry or Kyoto University. Pollen was spread on a 90 mm-petri dish containing a solid medium (w/v: 15% sucrose, 1.5% agar powder, 0.01% boric acid), and then the dishes were covered with their lids and incubated for one day at 10°C, 15°C, or 20°C. After incubation, pollen was observed under a microscope (VHX-500F; Keyence Corporation, Osaka, Japan). Three hundred pollen grains were randomly chosen per petri dish and the percentage of germinating pollen grains was determined. The measurement was done for each tetrad pollen, and a tetrad pollen germinating at least one pollen tube was judged to be germinating. Pollen was collected at least three times per cultivar and this experiment consisted of three replicates per sampling date (total of nine replicates per cultivar).
Statistical analysisData were analyzed by factorial ANOVA. The Tukey-Kramer test was used to test the significance of differences (P < 0.05) among the mean values of measured parameters. The normality of distribution was tested using the Kolmogorov-Smirnov test and the homogeneity of variance was tested using Bartlett’s test. When the data were not normally distributed or showed non-homogeneous variance, the non-parametric Steel-Dwass test was applied. The significance of the relationship (P < 0.05) between mature seed number and fruit quality parameters was tested by Pearson’s correlation analysis using results from all samples.
Experiment 2: Molecular mechanisms underlying effects of pollen source on fruit development Plant materials, artificial pollination, and sample preparationArtificial pollination tests were conducted using 5-, 6-, and 7-year-old field-grown ‘Blue muffin’ plants grown at the Experimental farm, Kyoto University, as the seed parent in the 2016, 2017, and 2018 seasons. Pot-grown ‘O’Neal’, ‘Sharpblue’, and ‘Sunshine Blue’ were used as the pollen parent. Flowers were collected just before anthesis and their anthers were excised and dried by incubating them at room temperature for one day with silica gel. Then, pollen was collected from anthers and stored at 4°C with silica gel until artificial pollination.
In the 2016 experiment, flowers were emasculated by removing corollas and stamens one day before artificial pollination, and was conducted for each flower once by gently rubbing the stigmas with pollen on glass rods. In the 2017 experiment, emasculation was not conducted because these treatments caused excess flower drop, and artificial pollination was conducted twice per flower with a one-day interval. Flowers were covered with bags after pollination for seven days to avoid pollination from other sources. In both years, mature fruit were harvested when the peduncle turned purple. The numbers of harvested fruits in each treatment are shown in Table S2. Fruits were weighed and the number of mature seeds per berry was counted as described in Experiment 1.
In 2018, fruit development was observed over time and fruit samples were used for subsequent microscopic observation. Artificial pollination was conducted using the same procedure as that in 2017, except that only ‘O’Neal’ or ‘Blue Muffin’ pollen were used for artificial pollination and pollinated flowers were covered until 14 days after pollination (DAP). A total of 13 to 26 fruit were collected every 10 DAP for each treatment (Table S2) and weighed: four of them were soaked in FAA fixation solution (formaldehyde: acetic acid: 70% ethanol = 1:1:18) and stored at 4°C until tissue microscopic observations, while the other four fruit were frozen immediately in liquid N2 and stored at −80°C until RNA extraction. At the mature stage, the mature seed number was also counted in 10 randomly chosen self-pollinated and 8 cross-pollinated fruit.
Microscopic observation of fruit cell growth and seed developmentThe FAA fixation solution was replaced with a gradient of sucrose solutions (10%, 20%, and 30%) and then samples were embedded in SCEM embedding medium (Leica Microsystems GmbH, Wetzlar, Germany). Frozen samples were cut into 10–15-μm sections using a CM1520 cryostat (Leica) following Kawamoto (2003). The cross-section intersecting the fruit that had the largest transverse diameter was stained with 0.5% toluidine blue for 30–60 s, embedded in SCEM solution (Leica), and observed and photographed under a BX60 light microscope (Olympus Corporation, Tokyo, Japan) equipped with a digital camera (DP72 LPT; Olympus). The cell size of the 10 largest cells and number of cell layers per transverse diameter in randomly chosen areas were calculated using Image J (Abràmoff et al., 2004). Morphological differences between developing normal and abnormal seeds were also observed. Because the Kolmogorov-Smirnov test showed that all the measured parameters had normal distribution (P < 0.05), the t-test was used to test the significance of differences (P < 0.05) in the mean values of measured parameters between self-pollination and cross-pollination.
RNA extraction, and mRNA-seq library construction and sequencingTotal RNA was extracted from frozen samples of whole fruit collected at 10 DAP using PureLink plant RNA Reagent (Thermo Fisher Scientific Inc., Waltham, MA, USA). Then, mRNA was isolated using a Dynabeads mRNA purification kit (Thermo Fisher Scientific). First-strand cDNA was synthesized using Superscript III (Thermo Fisher Scientific) and second-strand cDNA was synthesized using DNA polymerase and nick translation. The mRNA-seq library was prepared with the KAPA HyperPrep Kit (Kapa Biosystems Inc., MA, USA) according to the manufacturer’s instructions. After no more than 15 cycles of PCR, the resulting mRNA-Seq library was sequenced on the Illumina HiSeq4000 platform (Illumina Inc., San Diego, CA, USA) (50-bp single-end). Three biological replicates were conducted for each treatment.
Reference sequence preparation and alignmentThe ‘Draper’ reference genome (Colle et al., 2019) (downloaded from the Genome Database for Vaccinium; <https://www.vaccinium.org/>) consists of several unphased contigs and 48 pseudomolecules representing four chromosome sets of the tetraploid blueberry genome. To reduce redundancy while retaining diversity within the group, we selected representative genes for each homologous gene group. Homologous gene groups were detected by OrthoFinder software (version 2.5.2) (Emms and Kelly, 2019). The number of genes belonging to the homologous gene group was counted for each chromosome. Then, only genes located on the chromosome with the largest number of homologous genes among the four homologous chromosomes were retained in the reference transcriptome. When the number of homologous genes located on each chromosome set was the same, the genes located on the longer chromosome were retained as representative genes. Homologous genes that were not located in the pseudomolecules, but located in the unphased contigs, were also included in the representative reference genes. Using this strategy, 55,648 representative genes were selected from a total of 128,559 genes in the blueberry reference genome (Table S3). Gene ID and uniprot ID were derived from the Genome Database for Vaccinium.
The RNA-seq reads were processed using fastp (version 0.20.0) (Chen et al., 2018) with a minimum length threshold of 35 bp. Clean reads were mapped to the above reference transcriptome by Bowtie2 (version 2.3.5.1) (Langmead and Salzberg, 2012) and the transcriptome expression level (expressed as TPM) was estimated using the rsem-calculate-expression program implemented by RSEM software (version 1.3.1) (Li and Dewey, 2011).
Differentially expressed gene detection and GO and KEGG enrichment analysesThe transcript-level estimates from RSEM software were imported using the tximport package (Soneson et al., 2015). Differentially expressed genes (DEGs) between self-pollinated and cross-pollinated fruit were identified using the DESeq2 package (Love et al., 2014) with a threshold adjusted P-value of ≤ 0.05. Gene Ontology (GO; <http://geneontology.org/>) and Kyoto Encyclopedia of Genes and Genome (KEGG; <https://www.genome.jp/kegg/>) terms were assigned to each gene based on functional annotation using the UniprotKB database <https://www.uniprot.org/>. The GO enrichment analysis for DEGs was performed using the clusterProfiler package (Yu et al., 2012) function enricher. The GO terms with an adjusted P-value of < 0.05 were considered significantly enriched. The KEGG enrichment analysis was conducted using the enrichKEGG function of the clusterProfiler package. Arabidopsis thaliana was selected as the organism for pathway information.
Phylogenetic analysisProtein sequences were aligned using MAFFT version 7 (Katoh and Standley, 2013). The phylogenetic tree was constructed using the neighbor-joining method with the pairwise deletion option and with 1000 bootstrap replicates by MEGA X (Kumar et al., 2018).
In both the 2018 and 2019 seasons, the number of mature seeds and the fruit weight of cross-pollinated fruit significantly differed among the pollen sources (Table 1). Smaller fruit size and a decreased number of mature seeds by self-pollination were observed in both ‘O’Neal’ and ‘Chandler’, except for 2018 season’s ‘O’Neal’. For ‘O’Neal’, self-pollinated fruit were as large as other cross-pollinated fruit and contained as many mature seeds as cross-pollinated fruit in 2018, while they were much smaller and contained fewer mature seeds compared with cross-pollinated fruit in 2019. For ‘Chandler’ fruit, self-pollinated fruit were consistently smaller than artificially cross-pollinated fruit in both years. Among the cross-pollinated fruit of ‘Chandler’, fruit pollinated by ‘Darrow’ pollen were the smallest in both years, contained the lowest number of mature seeds, and had the lowest mature seed ratio. Fruit weight, transverse diameter, longitudinal diameter, total seed number, mature seed number, and mature seed ratio were the largest for fruit pollinated with ‘O’Neal’ pollen in both years.
Effect of pollen source on number of seeds and fruit size of ‘O’Neal’ and ‘Chandler’ fruit. Values represent mean ± standard error. ON: ‘O’Neal’, CH: ‘Chandler’, DR: ‘Darrow’, MS: ‘Misty’, ‘SSB: ‘Sunshine Blue’.
Significant differences in fruit quality between self- and cross-pollinated fruit were detected for both cultivars in some quality parameters, whereas the effects of different pollen sources were inconsistent between seasons. For ‘O’Neal’ fruit, the soluble solids content, fructose concentration, and glucose concentration were the highest when pollinated with ‘O’Neal’ and the lowest when pollinated with ‘Sunshine Blue’ in 2018. In contrast, the sugar content did not significantly differ among fruit with different pollen sources in 2019. The acidity of ‘O’Neal’ fruit did not differ among different pollen sources in the two years. For ‘Chandler’ fruit, the soluble solids content, fructose concentration, and glucose concentration were highest in fruit pollinated with ‘Chandler’ and ‘Misty’ in 2018. ‘Chandler’ fruit showed lower soluble solids content, fructose concentration, and glucose concentration when pollinated by ‘Darrow’ pollen than when pollinated with pollen from other cultivars. The acidity of ‘Chandler’ fruit differed significantly among different pollen sources only in 2019.
Effect of pollen source on fruit quality of ‘O’Neal’ and ‘Chandler’ fruit. Values represent mean ± standard error. ON: ‘O’Neal’, CH: ‘Chandler’, DR: ‘Darrow’, MS: ‘Misty’, ‘SSB: ‘Sunshine Blue’.
Since the mature seed number appeared to be directly affected by pollen sources, we thought that fruit size and quality parameters may be correlated with mature seed number. Correlation coefficients calculated between the number of mature seeds and fruit size/quality parameters are shown in Table 3. The mature seed number was not significantly correlated with other fruit quality parameters in most cross combinations, although fruit weight was positively correlated with mature seed number in all cross combinations.
Correlation between number of mature seeds and fruit size/quality parameters. ON: ‘O’Neal’, CH: ‘Chandler’, DR: ‘Darrow’, MS: ‘Misty’, SSB: ‘Sunshine Blue’.
We assumed that the varying number of mature seeds in fruit based on different pollen sources could be affected by the pollen viability. To clarify this possibility, we investigated the pollen germination rate under different temperatures. Among three cultivars, ‘O’Neal’ showed the highest pollen germination rate at all tested temperatures (Fig. S1). The pollen germination rate of ‘Misty’ and ‘Sunshine Blue’ was dramatically lower at 10°C compared with 15°C and 20°C. On the other hand, ‘O’Neal’ had a relatively high germination rate, close to 50%, even at 10°C.
Experiment 2: Molecular mechanisms underlying pollen source effects on fruit development Comparison of fruit development between self-pollinated and cross-pollinated ‘Blue muffin’ fruitTo clarify the mechanism by which more mature seeds result in larger fruit size, we conducted in-depth analyses using ‘Blue Muffin’, which shows severe expression of self-sterility (Fig. 1). First, pollination effects for ‘Blue Muffin’ fruit were characterized as conducted in Experiment 1 using three different pollen sources. Fruit weight, total seed number, and mature seed number were significantly different among fruit pollinated by three different pollen sources, except for the total seed number in the 2017 season. ‘Blue Muffin’ fruit pollinated by ‘O’Neal’ pollen had the heaviest fruit weight with the highest numbers of total seeds and mature seeds in the 2016 season, while ‘Blue Muffin’ pollinated with ‘Sharpblue’ pollen had the heaviest fruit weight in the 2017 season (Fig. S2). In both years, fruit pollinated with ‘O’Neal’ pollen produced more mature seeds than fruit pollinated with other pollen sources. In all cross combinations, fruit weight was significantly positively correlated with the number of mature seeds (Fig. S3).
Seed and fruit development of self- and cross-pollinated ‘Blue Muffin’ (BM). ‘O’Neal’ (ON) pollen was used for the cross pollination. (a) Fruit development of ‘Blue Muffin’. (b) Normal and abnormal seed development. Seeds at 10 DAP (A), the normal seeds at 20 (B), 30 (C), 40 (D) DAP, and mature stage (E), and the abnormal (aborted) seeds at 20 (F), 30 (G), 40 (H) DAP, and mature stage (I), are shown. Scale bar = 200 μm. (c) Comparison of fruit weight between self-pollinated and cross-pollinated fruit. (d) Comparison of cell area between self-pollinated and cross-pollinated fruit. (e) Comparison of mature seed number between self-pollinated and cross-pollinated fruit. Error bars represented standard error, and *, ** and *** represented significant difference at the 5%, 1%, and 0.1% level, respectively.
Among the pollen sources tested, ‘O’Neal’ pollen was selected for subsequent cross-pollination analysis because it showed a stable effect on producing a large number of mature seeds in ‘Blue Muffin’ fruit across years (Fig. S2). The appearance of fruit samples at each stage is shown in Figure 1a. Based on microscopic observations, there was no difference in the seed structure or fruit cell size at 10 DAP between self-pollinated and cross-pollinated fruit (Fig. 1b). However, abnormal seeds containing disrupted endosperm were present in self-pollinated fruit from 20 DAP onwards. Fruit weight and fruit cell size differed significantly between self-pollinated and cross-pollinated fruit from 30 DAP onwards (Fig. 1c, d). Fruit weight and the number of mature seeds were significantly different between self- and cross-pollinated fruit at harvest time (Fig. 1c, e).
GO and KEGG enrichment analysis of DEGs between self-pollinated and cross-pollinated ‘Blue muffin’ fruitMapping results are shown in Table S4. All the obtained sequences from Illumina sequencing reads are available from the NCBI/DDBJ Sequence Read Archive under the following accession number, DRA012844. We found 661 DEGs between self- and cross-pollinated fruit samples at 10 DAP. Many DEGs were classified as GO terms related to phytohormone metabolism and signaling, such as “ethylene-activated signaling pathway”, “response to brassinosteroid”, “regulation of salicylic acid biosynthetic process”, and “auxin homeostasis” (Table 4). Also, in the KEGG pathway database, the pathways “MAPK signaling pathway—plant” (ath04016), “Phenylpropanoid biosynthesis” (ath00940), and “Plant hormone signal transduction” (ath04075) were enriched in the DEGs (Table S5).
Enriched GO terms in the DEGs between self- and cross-pollinated fruit at 10 DAP. Only GO terms classified into biological process are shown.
Among the phytohormone metabolism and signal transduction pathways, the auxin pathway in particular showed distinctive and coordinated gene expression changes between self- and cross-pollinated fruit. A homolog of IAA–LEUCINE RESISTANT1 (ILR1)-like 4 encoding an amidohydrolase that releases active IAA from conjugates (Bartel and Fink, 1995) was up-regulated in cross-pollinated fruit as compared with self-pollinated fruit (Fig. 2a). Also, among the seven DEGs assigned to the “Plant hormone signal transduction” KEGG pathway, two were related to auxin signal transduction (AUXIN/INDOLE-3-ACETIC ACID14 (IAA14) and Arabidopsis SMALL AUXIN UP RNA 72 (SAUR72) (Fig. 2b, c). Aux/IAA proteins are known to function as transcriptional repressors of AUXIN RESPONSE FACTOR (ARF) genes (Chapman and Estelle, 2009). Phylogenetic analysis revealed that this SAUR72 belongs to the SAUR41 family (Fig. S4). A member of this family was shown to induce cell elongation when overexpressed in Arabidopsis and to be associated with ovule abortion (Kong et al., 2013; Liao et al., 2020). We also found that VaccDscaff2-augustus-gene-404.28-mRNA-1, a probable Arabidopsis D-CLADE TYPE 2C PROTEIN PHOSPHATASE PP2C.D5 homolog, was down-regulated in cross-pollinated fruit (Fig. 2d). This expression pattern is consistent with the reported gene function in Arabidopsis, in which members of the PP2C.D family hinder plasma membrane H+-ATPase activity, whereas the function is inhibited by SAUR family proteins (Spartz et al., 2014).
Gene expression levels of differentially expressed genes in self-pollinated fruit [‘Blue Muffin’ (BM) fruit crossed by BM pollen] and cross-pollinated fruit [BM fruit crossed by ‘O’Neal’ (ON) pollen]. Gene expression levels of (a) AtILR1-like4 homolog (b) AtIAA14 homolog (c) AtSAUR72 homolog (d) AtPP2C.D5 homolog are represented as TPM. All of the genes in Figure 2 are DEGs at the 0.1% level (P < 0.001). Values are mean ± standard error.
We conducted 14 different cross-combinations using ‘O’Neal’, ‘Chandler’ (Experiment 1), and ‘Blue Muffin’ (Experiment 2) as seed parents and ‘O’Neal’, ‘Chandler’, ‘Misty’, ‘Sunshine Blue’, ‘Darrow’, ‘Sharpblue’, and ‘Blue Muffin’ as pollen parents. Compared with cross-pollinated fruit, self-pollinated fruit of all three cultivars were smaller and had fewer mature seeds, except for ‘O’Neal’ in the 2018 season. The smaller fruit with fewer mature seeds of self-pollinated ‘Chandler’ fruit and those pollinated by ‘Darrow’ pollen in both years suggest that ‘Chandler’ has stronger genetically determined self-sterility, considering that ‘Darrow’ is a breeding parent of ‘Chandler’. Although self-pollination of ‘Chandler’ resulted in smaller fruit on average, some large fruit (> 6 g) were also harvested (data not shown). ‘Chandler’ is a blueberry cultivar that bears large fruit, and in normal horticultural practice the fruit are thinned to obtain large fruit at harvest (Watanabe, 2006). Self-pollination may have reduced fruit set (i.e., had a thinning effect), which in turn may have increased fruit size. In contrast, the fluctuation of self-sterility of ‘O’Neal’ suggests that although blueberry generally exhibits self-sterility, the expression of self-sterility in ‘O’Neal’ could be affected by other factors. Even in the self-fertile cultivars ‘Rubel’ and ‘Duke’, fruit set was found to be lower after self-pollination than after cross-pollination (Ehlenfeldt, 2001), suggesting that they show a self-sterile-related phenotype. Parrie and Lang (1992) reported that the expression of self-sterility could be affected by stigmatic saturation (a condition in which the stigma is incapable of perceiving an additional 10 to 15 pollen tetrads interspersed across the stigmatic surface due to limited secretory fluid on the stigma) and the number of pollen grains that pollinate the stigma. Therefore, the pollination method could affect fruit development of self-pollinated ‘O’Neal’.
In most cross-combinations using ‘O’Neal’ and ‘Chandler’ as seed parents, fruit weight, fruit size, total seed number, and mature seed number of fruit significantly differed among fruit pollinated by different pollen sources. Additionally, fruit size was significantly positively correlated with the number of mature seeds in all combinations in both years. Our results provide further evidence that the pollen source affects fruit size in blueberry, as reported in other studies (Ehlenfeldt, 2003; Gupton, 1997). Miller et al. (2011) proposed that pollen of large-fruit blueberry cultivars may increase the fruit size of ‘Blue Muffin’, which supports the existence of metaxenia. In our study, we obtained some controversial results on this point. For example, pollen of the large-fruit cultivar ‘Chandler’ did not produce larger ‘O’Neal’ fruit than those produced by the other pollen source tested (Table 1). Conversely, compared with the other pollen sources, ‘O’Neal’ pollen tended to produce larger fruit with a larger number of mature seeds when used to pollinate ‘Chandler’ and ‘Blue Muffin’, while ‘Sunshine Blue’ pollen produced relatively smaller fruit with a lower number of mature seeds when used to pollinate ‘Blue Muffin’. We hypothesize that this difference could be attributed, at least partially, to cultivar-dependent pollen viability. According to our pollen viability test, ‘O’Neal’ pollen showed a higher pollen tube growth rate at all of the tested temperatures, while ‘Sunshine Blue’ pollen showed a lower pollen tube growth rate (Fig. S1). We assume that pollen viability, especially at low temperatures, affected pollination and fertilization because the average maximum temperature during an artificial pollination test (around 20°C) was expected to be favorable for pollen tube growth, while the average minimum temperature (around 10°C) was expected to have some limiting effect on pollen tube germination (Figs. S1 and S5). Among the three cultivars tested in our study, only ‘O’Neal’ pollen retained a higher pollen tube growth rate at 10°C. However, further studies will be required to test this possibility.
Although the soluble solids content, acidity, and fructose and glucose concentrations in fruit varied significantly depending on the pollen source, no positive correlations were found between the number of mature seeds and the soluble solids content in all cross-combinations. Rather, negative correlations were detected between mature seed number and soluble solid contents in some cross combinations (Table 3). Kobashi et al. (2002) found that controlled cross-pollination of highbush blueberry increased the number of seeds and promoted sugar accumulation. They hypothesized that the increased number of mature seeds in the fruit produced by cross-pollination may increase abscisic acid contents, thereby enhancing invertase activity and inducing sugar accumulation. Because we only measured sugar concentrations and considering that sugar concentrations could be affected by the water contents, it is still unclear regarding the positive effects of mature seeds on sugar accumulation.
In summary, the results show that there were metaxenia-like changes in fruit size affected by pollen source through developing seeds, but not in fruit quality. Additionally, the number of mature seeds, which was dependent on the pollen source, largely contributed to metaxenia expression in our 14 controlled artificial cross-pollination combinations.
Possible molecular pathways involved in fruit growth promoted by developing seedsTo explore the regulation of seed development and the promotional effects of seeds on fruit growth, we observed fruit development of self-pollinated and cross-pollinated ‘Blue Muffin’ fruit in relation to seed development. ‘Blue Muffin’ is synonymous with ‘Hortblue Petite’ and is known to be highly self-sterile (Miller et al., 2011). In the controlled pollination tests conducted in this study, ‘O’Neal’ pollen produced a larger number of mature seeds in fruit than self-pollination with ‘Blue Muffin’ pollen. Thus, we compared fruit growth between self-pollinated fruit and fruit pollinated with ‘O’Neal’ pollen. As expected, compared with self-pollinated fruit, the ‘Blue Muffin’ fruit pollinated with ‘O’Neal’ pollen were larger and had more mature seeds at harvest. Additionally, seed abortion caused by self-sterility of ‘Blue Muffin’ was evident from 20 DAP onwards. Miller et al. (2011) reported that self-pollen of ‘Blue Muffin’ could reach the ovule and achieve successful fertilization. Krebs and Hancock (1990) hypothesized that aborted seed development may be related to endosperm breakdown. Consistent with these reports, our observations of seeds at 10 DAP revealed that there were no discernable differences between seeds in self-pollinated fruit and cross-pollinated ones. The fertilized embryo developed for a certain period, but it eventually caused abnormal endosperm breakdown, leading to seed abortion from 20 DAP onwards. Regarding fruit development, the larger size of cross-pollinated fruit than self-pollinated fruit was largely due to increased cell size, not increased cell number (Fig. 1). This implies that developing seeds may stimulate cell enlargement, rather than cell division, to promote fruit development. This is consistent with earlier studies reporting that cell division occurs before anthesis in blueberry (Cano-Medrano and Darnell, 1997).
Although there were no clear morphological differences in seeds in self-pollinated and cross-pollinated fruit until 20 DAP, the seeds may be physiologically different from just after fertilization onwards due to the effects of self-sterility factors. We considered 10 DAP as the best time point to explore the genetic regulation of seed development and also fruit development by seeds, since it was the stage just before clear morphological differences were observed (Fig. 1). We assumed mRNA expression differences between samples at 10 DAP are not primarily caused by the secondary effects from morphological differences. The GO enrichment analysis suggested that the metabolism and signal transduction of phytohormones, which are known to regulate both seed development and fruit growth (Bhat et al., 2011; Iqbal et al., 2017; Pérez-Llorca et al., 2019), may differ between self-pollinated and cross-pollinated fruit. We found that an AtILR1 homolog was up-regulated in cross-pollinated fruit as compared with self-pollinated fruit (Fig. 2). Most of the IAA in plants exists not as free acid but as conjugates, and ILR1 converts conjugated IAA to free IAA (Rampey et al., 2004). In our study, we did not detect any significant differences in the transcript levels of genes related to auxin biosynthesis between self-pollinated and cross-pollinated fruit (data not shown), while the results of the KEGG pathway enrichment analysis suggested that the auxin signal transduction was different between self-pollinated and cross-pollinated fruit. We detected two DEGs, Aux/IAA and SAUR, in self-pollinated and cross-pollinated fruit (Fig. 2). Aux/IAA protein degradation is crucial for the auxin response (Chapman and Estelle, 2009). At high auxin levels, Aux/IAA proteins can be ubiquitinated by interacting with F-box protein auxin receptors, initiating their degradation by the 26S proteasome system. Liu et al. (2015) reported that transgenic Arabidopsis plants expressing a poplar (Populus trichoccarpa) IAA7 homolog were found to be less sensitive to auxin, suggesting not only degradation of Aux/IAA, but also its expression level, are important in regulating auxin signal transduction. Thus, it is possible that down-regulation of an AtIAA14 homolog in cross-pollinated fruit induced up-regulation of auxin-responsive genes, such as SAUR genes. Spartz et al. (2014) found that plants overexpressing stabilized SAUR19 fusion proteins exhibited increased plasma membrane H+-ATPase activity, resulting in increased growth. In addition, Liao et al. (2020) proposed that cell wall invertase (CWIN)-mediated sugar signaling regulates ovule formation by modulating downstream auxin signaling. In their study, auxin comprised of more than 50% DEGs between transgenic and wild-type plants during ovule initiation, and ovule abortion was observed along with decreased SAUR expression level and H+-ATPase activity. Therefore, we can hypothesize that a higher expression level of SAUR may increase H+-ATPase activity, which is key for normal seed development and fruit cell enlargement. We also found that the transcript level of an AtPP2C.D5 homolog was lower in cross-pollinated fruit than in self-pollinated fruit (Fig. 2). SAURs are known to interact with PP2C.D proteins (Spartz et al., 2014). A total of 76 Arabidopsis genes were identified as PP2C-type phosphatase candidates and nine of them were classified as PP2C.D (Schweighofer et al., 2004). Therefore, the lower transcript level of the AtPP2C.D5 homolog in cross-pollinated fruit (Fig. 2) could relate to the promotion of seed development and also fruit development through the activation of plasma membrane H+-ATPases.
In conclusion, controlled artificial pollination studies using many different pollen sources in the present study suggested that metaxenia effects in blueberry, that is, the effects of pollen source on female organs in fruit, were observable in terms of the fruit size. Our transcriptome analyses suggested that altered auxin metabolism and signaling may underlie seed development and early fruit cell enlargement. We thus propose the hypothesis that an appropriate pollen source that can activate auxin signaling may contribute to induce normal seed development and fruit cell enlargement. Further research is required to reveal tissue specificity of the altered auxin metabolism and signaling; this will contribute to a deeper understanding of seed-fruit interaction in blueberry.
We thank Ms. Kanako Ishii and Mr. Kohei Iida, Shizuoka Prefectural Research Institute of Agriculture and Forestry, Shizuoka, Japan, for kindly collecting pollen samples.
