Study on the differences of phyllosphere microorganisms between poplar hybrid offspring and their parents

Experimental site and experimental materials

The experimental field site was located in Baituliang Forest Farm, Dalat Banner, Erdos City, Inner Mongolia Autonomous Region (37°35′24″∼407°35′247°N, 106°42′40″∼111°35′247°E), which is classified as temperate continental monsoon climate. The annual average temperature is 6.8 °C with a minimum of −22 °C in winter and a maximum of 37 °C in summer. The annual precipitation and annual average frost-free period are 300 mm and 150 days, respectively.

In the spring of 2015, F1 progeny seeds of P. simonii × P. nigra ‘DH1’ (PSPNDH1), P. simonii × P. nigra ‘DH2’ (PSPNDH2), and P. simonii × P. nigra ‘DH3’ (PSPNDH3) were obtained from the hybridizations between female clone of P. simonii ‘DH4’ and male clone of P. nigra ‘DH5’ and planted in the greenhouse of CAF (Chinese Academy of Forestry), Beijing, China. In the spring of 2016, cutting seedlings of F1 progeny and their parents were planted with the density of 30 cm × 50 cm at Baituliang Forest Farm, Dalat Baner, Inner Mongolia Autonomous Region. In the spring of 2018, 16 plants for each genotype of F1 progenies and each clone of parents were grown in a plot with a spacing of 10 × 15 m. A total of 25 plots were designed and five replicates were randomly distributed (Fig. S1). Plants were planted in each plot with the density of 2 m × 3 m.

The determination of plant functional traits

The height was measured with an altimeter. The diameter at breast height was measured using a breast diameter ruler to measure the diameter of the tree trunk 1.3 m above the ground. The relative moisture content of leaf was weighed by the drying method. The length of petiole was measured with a ruler. Leaf area was calculated using Image J and leaves were scanned with a CanonScan LiDE 210 (Canon Inc., Tokyo, Japan). The contents of soluble sugar and starch were determined by anthrone colorimetry.

Sample collection

A total of 15–20 leaves from the tip of the shoots in the middle of the canopy from three directions, including 120° around the tree, were collected, and leaves from ten trees at each plot were mixed as one replicate. A total of 25 leaf samples (5 clones × 5 replicates) were collected. To analyze the phyllosphere microbial community on the leaves, 10 g of leaves from each replicate were cut into pieces and submerged in phosphate-buffered solution (20 mL, PBS, 0.01 M, pH 7.4) (leaf weight/volume TE buffer = 1:20). After vigorous shaking on a shaker at 200 r/min for 30 min at room temperature, leaves were removed, and the suspension containing phyllosphere microorganism was retained. The suspension was filtered through sterile vacuum filtration, and phyllosphere microbes from the oscillating liquid were collected on a 0.22 µm filter membrane and then placed into 2 ml sterile centrifuge tubes. The samples were stored at −80 °C prior to DNA extraction and high-throughput sequencing.

High-throughput sequencing

According to the manufacturer’s instructions, we used the FastDNA SPIN Kit for soil (MP Biomedical, Santa Ana, CA, USA) to extract Genomic DNA from the filter. The NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA) was used to measure the DNA concentration (Deng et al., 2021). The primer pairs 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) with barcode sequence were used to amplify the V3–V4 regions of bacterial 16S rDNA gene (Deng et al., 2021). The primer pairs ITS1F (5’-CTTGGTCATAGGAAGAAGTAA-3’) and ITS2 (5’-GCTGCGTTCTTCAGATGC-3’) with barcode sequence were used to amplify the ITS1 region of the fungal ITS rDNA gene. All the PCR reactions were performed with 25 μl mixture, including DNA Template (40–50 ng) 2 μl, 0.25 μl (5 U/μl) of Q5 High-Fidelity DNA Polymerase, 2 μl of dNTPs (2.5 mM), 1 μl (10 uM) of forward and reverse primer, severally; 5 μl of Q5 High-Fidelity GC buffer (5×), 8.75 μl of ddH₂O, 5 μl of Q5 reaction buffer (5×). The PCR thermal cycling condition was consistent with the study from Deng et al. (2020). Agencourt AMPure Beads (Beckman Coulter, Indianapolis, IN, USA) was used to purify the PCR amplicons, and PicoGreen dsDNA Assay Kit (Invitrogen, Carlsbad, CA, USA) was used to further quantify the PCR amplicons (Deng et al., 2020). PCR products for sequencing were carried out by an Illumina NovaSeq 6000 sequencing platform at Shanghai Personal Biotechnology Co., Ltd., Shanghai, China. The high-throughput sequencing raw data of phyllosphere bacteria and fungi were uploaded in the NCBI database with the SRA accession number PRJNA736812.

Statistical analysis

The high-quality sequences were finally obtained after removing primers, quality filter, denoise, joint and removal of chimeras (Callahan et al., 2016). And sequences with ≥97% similarity were assigned to the same OUT (Edgar, 2010). Then, the qiime feature-table rarefy function was used for OTU leveling, and the leveling depth was set as 95% of the minimum sample sequence quantity (Kemp & Aller, 2004). Multiple-sample comparisons using one-way analysis with Kruskal–Wallis tests were used to explore the differences of phyllosphere microbial community diversity. Venn diagrams were constructed to show the shared and unique OTUs using RStudio with vegan package (Chen & Boutros, 2011). Linear discriminant analysis effect size (LEfSe) with the Kruskall–Wallis test was employed to identify the bacterial and fungal taxonomic from the phylum to genus levels responsible for the community differentiation between treatments (Segata et al., 2011). The threshold on the logarithmic LDA score for discriminative features was set at 2. For β-diversity, non-metric multidimensional scaling (NMDS) analysis was performed to reveal the differences phyllosphere bacterial (based on weighted-unifrac) and fungal (based on bray distance) community compositions among different samples using RStudio with vegan package (Anderson, 2001). Spearman’s rank correlation was used to analyze the relationships between plant functional traits and phyllosphere microbial community diversity and composition using IBM SPSS (Clarke, 2010).

Plant functional traits analysis

There was considerable variations of plant height (F = 46.57, P < 0.01), diameter at breast height (F = 53.98, P < 0.01), leaf area (F = 35.83, P < 0.01), length of petioles (F = 287.89, P < 0.01), leaf moisture content (F = 8.24, P < 0.01), and starch (F = 3.09, P = 0.04) among different samples, and PSDH2 owned the highest plant height, diameter at breast height, and length of petioles with 6.38 m, 5.92 cm, 4.81 cm, respectively. PSDH1 owned the highest starch content with 129.54 mg/g, followed by PSDH2, PSDH3, PSDH4, and PSDH5 (Table 1), while no obvious differences were obtained among different samples (F = 1.77, P = 0.18) (Table 1).

Phyllosphere microbial community diversity

A total of 2,147,073 high quality bacterial sequences were obtained with average sequences of 85,882, which were clustered into 10,031 OTUs. The number of OTUs under PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 was 2,701, 2,197, 2,735, 2,981, and 2,695, respectively, and the number of unique OTUs of PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 was 1,730, 1,214, 1,606, 1,931, and 1,735, individually. The number of shared OTUs among PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 was172 (Fig. 1A). As for fungi, 3,519,792 high quality sequences were obtained with average sequences of 140,791, which were incorporated into 1,732 OTUs. PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 hold 605, 571, 502, 690, and 654 OTUs respectively, with unique OUTs of 233, 206, 171, 294, and 276, individually, and the shared OUTs of 159. In our research, the depth of sample sequencing increased, but the curve no longer increased significantly (Fig. S2). We believe that the amount of sequencing was sufficient, that is, the sample alpha diversity index has stabilized.

No distinct differences of phyllosphere bacterial Chao1 index (P = 0.67), Goods_coverage (P = 0.60), Observed_species (P = 0.79), Pielou_e index (P = 0.21), Shannon index (P = 0.46), and Simpson index (P = 0.23) were observed among PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 (Fig. 2A). While, phyllosphere fungal Chao1 index (P = 0.028), Goods_coverage (P = 0.046), Observed_species (P = 0.025), Pielou_e index (P = 0.036), Shannon index (P = 0.024), and Simpson index (P = 0.044) observably differed among PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5. PSDH4 hold the highest Chao 1 index of 275.15 and Observed_species of 259.22. PSPNDH2 owned the highest Pielou_e index, Shannon index, and Simpson index with 0.41, 3.21, and 0.74, respectively. Compared to PSPNDH2 and PSPNDH3, PSPNDH1 had the lowest Chao 1 index, Observed_species, Pielou_e index, Shannon index, and Simpson index with 200.26, 187.46, 0.29, 2.19, and 0.51, respectively (Fig. 2B).

Phyllosphere microbial community composition

In total, 35 bacterial phyla were detected across all 25 samples. The groups with average relative abundance more than 0.05% were Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Acidobacteria, Gemmatimonadetes, and Deinococcus-Thermus, accounting for 99.85%. The predominant groups were Firmicutes and Proteobacteria (Fig. 3A). At the class level, Bacilli and Gammaproteobacteria were two most dominant bacterial groups regardless of parent and the hybrid offspring (Fig. S3A). The relative abundance of Bacilli was relatively higher in PSDH4 (78.06%) compared to the other samples (37.04–63.55%). While, the relative abundance of Gammaproteobacteria showed the opposite trend, which was lower in PSDH4 (10.28%) than in the other samples (15.10–35.59%). At the genus level, 1,071 bacterial genera were obtained, and the bacterial groups with the average relative abundance more than 1% were Exiguobacterium, Planomicrobium, Pseudomonas, Bacillus, Massilia, Frigoribacterium, Lysinibacillus, Planococcus, Pantoea, Curtobacterium, and Arthrobacter, accounting for 71.26%.

In total, 9 fungal phyla, including Ascomycota, Basidiomycota, Mortierellomycota, Mucoromycota, Olpidiomycota, Aphelidiomycota, Blastocladiomycota, Chytridiomycota, and Rozellomycota were detected across all 25 samples (Fig. 3B). The predominant groups were Ascomycota, and Basidiomycota, accounting for 99.04%. At the class level, the phyllosphere fungal communities were dominated by Dothideomycetes (69.15–86.18%), Sordariomycetes (5.41–17.66%), Tremellomycetes (2.26–9.49%), and Agaricostilbomycetes (0.92–2.97%) (Fig. S3B). At the genus level, a total of 448 fungal genera were detected, and Alternaria, Phialemoniopsis, Didymella, Filobasidium, Mycosphaerella, and Kondoa were the dominant fungal communities, accounting for 90.10% (Fig. S3B).

The NMDS demonstrated that the phyllosphere microbial community composition obviously differed between PSDH4 and PNDH5, while, the phyllosphere microbial community composition presented some similarities under PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5 (Fig. 4). In addition, PSPNDH2 enriched Oceanobacillus, Lachnoclostridium, Escherichia_Shigella, Selenophoma, Selenophoma_mahoniae, Dothideales, Piloderma and Nigrospora. PSPNDH3 enriched Pseudomonadaceae, Pseudomonas. PSPNDH1 enriched Hymenobacteraceae, Hymenobacter, Massilia and Didymella. PNDH5 enriched Alteromonadales, Paracaedibacterales, Aliihoeflea, Cystobacter, Rahnella, Saccharomycetes, Massarinaceae, Stagonospora, Wilcoxina, and Simplicillium. PSDH4 enriched Planomicrobium, Allobaculum, Enterobacter, Erysiphales, Lentitheciaceae, Phaeosphaeria, Alternaria, and Phyllactinia (Fig. 5).

The relationships between leaf characteristics and phyllosphere microbial community

Phyllosphere bacterial Chao1 index (r = 0.63, p = 0.01; r = 0.64, p = 0.01) and Observed_species (r = 0.66, p = 0.01; r = 0.62, p = 0.02) had significantly positive correlation with soluble sugar and starch. Phyllosphere bacterial Pielou_e index (r = 0.55, p = 0.01), Shannon index (r = 0.62, p = 0.003), Simpson index (r = 0.49, p = 0.03) remarkably increased with the increase of soluble sugar content (Table 2). With regard to phyllosphere fungi, phyllosphere fungal Chao 1 index (r = 0.48, p = 0.01), Observed_species (r = 0.49, p = 0.01), and Shannon index (r = 0.39, p = 0.03) existed distinctly positive relation to soluble sugar (Table 2).

The relative abundance of Firmicutes decreased with the increase of starch (r = −0.41, p < 0.05). While, the relative abundance of Actinobacteria (r = 0.55, p < 0.05), Bacteroidetes (r = 0.51, p < 0.05), Chloroflexi (r = 0.40, p < 0.05), Deinococcus-Thermus (r = 0.42, p < 0.05) increased with the increase of starch content (Table 3). The relative abundance of Basidiomycota hold significant positive correlation with starch (r = 0.40, p < 0.05) (Table 3).

Variation of plant functional traits of the parental clones and different hybrid progeny

Heterosis refers to the phenomenon that the F1 generation plants produced by crossing two parents with different genetic compositions are superior to the parents in one or more traits. The utilization of heterosis in modern breeding has achieved remarkable results in crops and trees, and most of the previous research results showed that the photosynthetic capacity of hybrid was significantly higher than that of their parents (Khan et al., 1998). In our study, the height and diameter at breast height of PSPNDH1, PSPNDH2, and PSPNDH3 existed higher than those of PSDH4, and PNDH5 (Table 1), which demonstrated that PSPNDH1, PSPNDH2, and PSPNDH3 owned higher plant biomass than those of PSDH4, and PNDH5. What’s more, leaf is one of the important vegetative organs of plants, and the research on leaf characteristics has always been an important part of poplar breeding research. A large number of studies have shown that there is a close relationship between leaves and growth, especially leaf area and leaf area index, which are closely related to biomass (Gebauer et al., 2016). Leaf area is also an important parameter to characterize the photosynthetic and transpiration capacity of plants and can be used as an early selection index for tree growth traits (Du et al., 2014; Guet et al., 2015). Therefore, it is very necessary to carry out the analysis of leaf-related traits in hybrid breeding. In our study, the leaf area and leaf moisture in PSPNDH1, PSPNDH2, and PSPNDH3 were significantly higher than those of PSDH4, and PSDH5 (Table 1), which proved that PSPNDH1, PSPNDH2, and PSPNDH3 had higher plant biomass from another perspective. In addition, PSDH1, PSDH2, and PSDH3 could increase the contents of starch, compared to PSDH4, and PSDH5 (Table 1), and all these results collectively demonstrated that the hybrid progeny had obvious heterosis.

Variation of phyllosphere microganism of the parental clones and different hybrid progeny

As we all know, the leaf field of plants is a habitat characterized by a high degree of microbial diversity, but it is also a dynamic microenvironment due to direct exposure to a variety of abiotic and biological factors (Kinkel, 1997). In present study, we found that overall alpha diversity of the phyllosphere bacterial community existed no distinct differences among PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5. While, phyllosphere fungal Chao1 index, Goods_coverage, Observed_species, Pielou_e index, Shannon index, and Simpson index observably differed among PSPNDH2, PSPNDH3, PSPNDH1, PSDH4, and PNDH5. PSPNDH2 had the highest Pielou_e index, Shannon index, and Simpson index. Our findings were not completely similar to the previous study from Liu et al. (2021) demonstrated that phyllosphere microbial community diversity of P. cathayana existed no distinct difference between male and female, which might be related to the similar physical and chemical properties, as well as similar physiological metabolism and traits of male and female leaves of P. cathayana, while male (PSDH4) and female (PNDH5) were not the same species in our present study. In addition, plant species and host plant genotype may be the main factor determining phyllosphere fungal community composition at the same location (Leveau, 2019).

In addition, the phyllosphere microbial communities are characterized by a small number of highly abundant taxa and a large number of relatively low abundance rare taxa (Vacher et al., 2016). At the phylum level, the dominant position of Proteobacteria in phyllosphere bacterial community has been confirmed by a large number of studies (Kembel et al., 2014). In our study, high-throughput sequence analysis of the 16S rDNA showed that Firmicutes, and Proteobacteria belonged to the predominant bacterial groups (Fig. 3A). At the class level, Bacilli and Gammaproteobacteria were the two most dominant bacterial classes regardless of parent and the hybrid offspring (Fig. S3A). The bacterial groups Alphaproteobacteria and Gammaproteobacteria have higher abundance and are typical representatives of Gram-negative bacteria in this habitat (Truchado et al., 2017; Izhaki et al., 2013; Huang et al., 2010). At the genus level, Exiguobacterium, Planomicrobium, Pseudomonas, Bacillus, Massilia, Frigoribacterium, Lysinibacillus, Planococcus, Pantoea, Curtobacterium, Arthrobacter were the dominant microbial groups, accounting for 71.26%. Most of studies indicated that Pseudomonas and Pantoea are indigenous members of phyllosphere microbe (Ning et al., 2010), and they can produce a signal molecule called N-acyl-homoserine (Lv et al., 2013; Poonguzhali, Madhaiyan & Sa, 2007), that may help bacteria inhabit the harsh environment (Lv et al., 2013). Furthermore, Pseudomonas are considered to be very competitive plant leaf colonizers, and their extracellular polysaccharides and special pigments can protect them from ultraviolet radiation and osmotic stress (Qin et al., 2019), which was also frequently reported to benefit plant growth by means of its anti-phytopathogen ability (Alymanesh, Taheri & Tarighi, 2016; Mikiciński et al., 2016). The members of genus Arthrobacter can degrade a variety of organic pollutants and persist in the phyllosphere by up-regulating several genes known to contribute to epiphytic fitness (Scheublin et al., 2014). Collectively, these studies explained the existence of these bacteria in phyllosphere.

With regard to phyllosphere fungi, the predominant groups were Ascomycota, and Basidiomycota, accounting for 99.04%. At the class level, the dominant phyllosphere fungal communities were Dothideomycetes, Sordariomycetes, Tremellomycetes, and Agaricostilbomycetes (Fig. S3B). At the genus level, Alternaria, Phialemoniopsis, Didymella, Filobasidium, Mycosphaerella, and Kondoa were the dominant fungal communities. Interestingly, phyllosphere bacterial community and fungal community significantly differed between parental clones and hybrid progeny, while the phyllosphere microbial community presented some similarities under different hybrid progeny. This is in accordance with the view obtained from Maignien et al. (2014) indicated that a high variability of phyllosphere microbiomes across individual plants of the same species grown in the same location.

The relationship between leaf characteristics and phyllosphere microbial community

Our study first provided a detailed insight into the effects of parental clones and different hybrid progeny on the above-ground microbial colonizers of plants. The host has greater genetic control over the phyllosphere microganism than the rhizosphere microbiota (Wagner et al., 2016). However, the rapidly fluctuating environmental conditions aboveground also play an important role, and only a few microbial groups that can adapt to harsh environments will flourish. The living environment of phyllosphere microorganisms is unstable and greatly affected by environmental changes (Jia et al., 2018), such as light, temperature and humidity (Verma, Ladha & Tripathi, 2001). In addition, plant species, leaf structural, chemical composition and secretions are known to influence phyllosphere microbial colonization (Leveau, 2019; Schlechter, Miebach & Remus-Emsermann, 2019; Espenshade et al., 2019) and phyllosphere microbial community diversity and composition (Hunter et al., 2010; Redford & Fierer, 2009; Kim et al., 2012). Our findings showed similar results, namely, that phyllosphere bacterial and fungal community diversity and composition had a significantly positive correlation with soluble sugar and starch (Tables 2 and 3), which was consistent with previous findings demonstrated that the phyllosphere fungal community structure was significantly affected by plant carbon (Jia et al., 2018). Thus, all these findings collectively established that plant traits are key factors that affect phyllosphere microbial community structure (Whipps et al., 2008).