Integrated transcriptomic and transgenic analyses reveal potential mechanisms of poplar resistance to Alternaria alternata infection

doi:10.21203/rs.3.rs-1594023/v1

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Integrated transcriptomic and transgenic analyses reveal potential mechanisms of poplar resistance to Alternaria alternata infection

https://doi.org/10.21203/rs.3.rs-1594023/v1

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Background

Populus davidiana × P. bollena is a species of poplar from northeastern China that is characterized by cold resistance and fast growth but now suffers from pathogen infections. Leaf blight caused by Alternaria alternata has become a common poplar disease that causes serious economic impacts, but the molecular mechanisms of resistance to A. alternata in P. davidiana × P. bollena are still unclear.

Results

In this study, the transcriptomic response of P. davidiana × P. bollena to A. alternata infection was determined via RNA-Seq. Twelve cDNA libraries were generated from RNA isolated from three biological replicates at four time points (0, 2, 3, and 4 d post inoculation), and a total of 5,930 differentially expressed genes (DEGs) were detected (| log₂ fold change | ≥ 1 and FDR values < 0.05). Functional analysis revealed that the DEGs were mainly enriched for the “plant hormone signal transduction” pathway, followed by the “phenylpropanoid biosynthesis” pathway. In addition, DEGs that encode defense-related proteins and are related to ROS metabolism were also identified. Numerous transcription factors, such as the bHLH, WRKY and MYB families, were also induced by A. alternata infection. Among these DEGs, those related to JA biosynthesis and JA signal transduction were consistently activated. Therefore, the lipoxygenase gene PdbLOX, which is involved in JA biosynthesis, was selected for functional characterization. Overexpression of PdbLOX enhanced the resistance of P. davidiana × P. bollena to A. alternata, whereas silencing this gene enhanced susceptibility to A. alternata infection.

Conclusions

These results provide new insight into the molecular mechanisms of poplar resistance to A. alternata infection and provide candidate genes for breeding resistant cultivars using genetic engineering.

RNA-Seq

poplar

Alternaria alternata

defense response

lipoxygenase gene

To ward off pathogens, plants have developed a complex defense system, which generally divided into a recognition layer, a signal integration layer, and a defense action layer [1]. The recognition layer recognizes the effectors by the cell surface pattern-recognition receptors (PRRs) and intracellular receptors. Among them, the PRRs recognize the microbe-associated molecular patterns (MAMPs) and damage-associated molecular patterns (DAMPs) as well as the apoplectic effectors [2]. While for the intracellular receptors, they can directly recognize the intracellular effectors, or recognize the complexes of host proteins and effectors as well as the host proteins which were already modified by effectors [3]. After recognize the effectors, the recognition layer transports the signals to the signal integration layer as well as the signals from neighboring cells and distant tissues. And then signal integration layer outputs a tuned set of signals to the defense action layer which helps plant resist interference from pathogen effectors [4, 5]. The defense action layer provides protection to plants for pathogens defence or modulates the interaction between itself with the microbiome, by diverse actions [6, 7]. Among these defense mechanisms, R genes, such as the CC-NBS-LRR genes (CNL genes) and TIR-NBS-LRR genes (TNL genes), help recognize pathogenic effectors and mimic pathogen targets [8–10]. Phytohormones, including salicylic acid (SA), jasmonates (JAs), and ethylene (ET), act as signals to trigger and mediate a diverse array of defense responses, while other hormones, such as auxin, gibberellic acids, brassinosteroids, and abscisic acid, are also actively involved in plant immunity by feeding into the SA–JA–ET backbone of the immune signaling circuitry [11–13]. Secondary metabolites, such as phenolics, alkaloids, sesquiterpenes, oxylipins, saponins, polyamines, and isoflavonoids, contribute to resistance against pathogens via preformed or induced physical barriers or chemical barriers [14–16]. Additionally, transcription factors (TFs), such as WRKYs, bHLHs, TGAs, and MYBs, play roles in plant resistance at several levels, including the basal expression of resistance components, the direct TF activity of receptor proteins, and activation downstream of receptor initiation [17–19]. In general, plant defense mechanisms are complex, and there are various ways to deal with different pathogens. Therefore, it is necessary to study the mechanisms that each type of plant uses against infection by different pathogens to provide a theoretical basis for improving the resistance of plants to disease and selecting disease resistance genes. Using RNA-seq, people can characterize the dynamic patterns of genome-wide gene expression during plant–pathogen interactions and help define gene and protein functions. Recently, pathogen-responsive transcriptomes have been studied in many crops and other economically important plants, such as Citrus jambhiri [20] apple [21, 22], tomato [23, 24], Zea mays [25] and Nicotiana benthamiana [26]. However, research on poplar-pathogen interactions has mainly focused on poplar rust [27, 28], and little is known about the defense mechanisms that poplars use against other pathogens.

Alternaria is a cosmopolitan fungal genus whose members commonly act as plant pathogens and infest a wide range of plants, including cereal crops, vegetables and fruits, leading to necrosis and defoliation on leaves, necrosis on fruits and new shoots, a shortened growth cycle, and postharvest decay [29]. To date, methods of controlling Alternaria rely mainly on chemical pesticides such as mancozeb, daconil and captafol, but the long-term use of fungicides results in resistance to chemical fungicides and environmental pollution [30]. Thus, an improved understanding of plant defense mechanisms in response to Alternaria may help to design safer control strategies and aid in the development of resistant cultivars. To date, several transcriptome studies in different plant species have been performed to understand the mechanisms of the plant defense response to Alternaria sp. infection. In chrysanthemum, the reactive oxygen species (ROS), Ca²⁺ and SA/JA or ET signaling pathways are induced to defend against Alternaria sp. [31, 32]. ET-/H₂O₂-mediated programmed cell death (PCD) and detoxifying processes have been shown to play vital roles in the interaction between pear and A. alternata [33]. Moreover, the apple “Starking Delicious” may be susceptible to A. alternata due to vulnerability in cell wall defense and the downregulation of PR proteins [21]. These investigations showed complex, varied interactions between the host and Alternaria sp. Poplar (Populus spp.), a fast-growing, high-yield tree genus, is vital to the world’s ecological and socioeconomic well-being. Poplar leaf blight caused by A. alternata has become a common disease that has serious economic impacts in China [34, 35]. Nevertheless, no detailed analysis has been performed to elucidate the molecular regulatory mechanisms underlying the response of poplar to A. alternata infection. In this study, we performed a global transcription analysis of P. davidiana × P. bollena in response to A. alternata infection using RNA-Seq technology, and the differentially expressed genes (DEGs) and significantly enriched pathways associated with pathogen resistance were explored. Multiple potential candidate genes involved in resistance to A. alternata infection were also identified, and the function of the lipoxygenase gene PdbLOX was characterized in transgenic poplar. These results provide new insight into the molecular mechanisms of poplar resistance to A. alternata infection and will facilitate the breeding of durable, broad-spectrum disease-resistant poplar cultivars in the future.

Symptoms and Physiological Changes in Leaves After Alternaria alternata Infection

The progression of disease on inoculated leaves was observed and the percentage disease index were assigned and calculated (Fig. 1A, C). The inoculation areas appeared to be water soaked by 2 DPI, which were hardly obvious. And the blotches comprising damaged tissue appeared to be weakly brown and the blotch size were increased by 3 DPI (Fig. 1B). Then, over the subsequent 24 h, observations confirmed that the blotch size was no further increased, but the color deepened further. To determine whether the hormones and ROS in the leaves of P. davidiana × P. bollena responded to A. alternata, the contents of SA, JA and hydrogen peroxide (H₂O₂) were determined. The results showed that the contents of SA, JA and H₂O₂in inoculated leaves were increased, among which the JA contents were significantly increased compared to the controls during infection (Fig. 1D-F). Additionally, assays of enzymes involved in plant resistance to pathogen infection, such as POD, SOD, PPO, PAL and CAT, were also performed, and the activities of all these enzymes were significantly higher than in the control (Fig. 1G-K). These data indicate that the defense system in P. davidiana × P. bollena is responsive to A. alternata infection.

RNA-Seq and identification of differentially expressed genes (DEGs) during disease progression

Based on macroscopic observations, four time points, 0 d, 2 d, 3 d and 4 d, were chosen, and 3 biological replicates from those points were then analyzed on an Illumina HiSeq 2500 platform. All together, 12 cDNA libraries were constructed and a total of 58.1 GB of clean reads were generated. The average Q20 and Q30 values of the raw reads were 97.17% and 92.23%, respectively. Approximately 72.13% of the reads were mapped to the reference genome sequences (Table S1).

To investigate the DEGs during pathogenic infection in poplar, the clustering method was used to analyze and identify genes with expression changes of more than 1-fold and significance levels of P ≤ 1e−4. Gene expression was compared between the pathogen-infected and control samples, a comparison of the 2 and 0 DPI libraries identified 1930 DEGs, of which 1341 were upregulated and 589 were downregulated, a comparison of 3 and 0 DPI generated 2200 DEGs with 1407 upregulated and 793 downregulated. Of all the comparisons, the most DEGs, 4381, were found when the 4 and 0 DPI libraries were compared, in that analysis, 2039 were upregulated and 2342 were downregulated, suggesting that this time is particularly important for the poplar in the response to A. alternata infection (Fig. 2A). Then, the results above were illustrated as a Venn diagram, both unique and shared DEGs occur between and among pairs (Fig. 2B). For example, 421 DEGs (21.81% of the total) in 2 DPI vs. 0 DPI, 709 DEGs (32.22% of the total) in 3 vs. 0 DPI and 2,803 DEGs (63.98% of the total) in 4 vs. 0 DPI were shared with the other compared libraries. In addition, 584 DEGs were shared across all comparisons. These results suggest that, more genes become involved in the defense response during the pathogen infection progresses, and genes that respond early to pathogen infection may also subsequently function.

Validation of RNA-Seq Data using RT–qPCR

To verify the accuracy and reproducibility of the RNA-Seq data, the transcript of 15 randomly selected DEGs, including 10 up-regulated genes and 5 down-regulated genes, were analyzed by RT-qPCR. All 10 upregulated genes were significantly induced after pathogen infection, while the five downregulated genes were correspondingly repressed, which were in accordance with the RNA-Seq results (Fig. S1). Therefore, the consistency between the RT–qPCR results and the RNA-Seq analyses confirmed the reliability of our RNA-Seq data.

GO enrichment and KEGG pathway analysis of DEGs

The functional categories of the DEGs induced by pathogenic infection were obtained by GO enrichment and KEGG analysis. The GO enrichment analysis was performed via eggNOG-mapper (Fisher’s exact test, P value ≤0.05). The most significant enriched biological processes (BPs) were “secondary metabolic process” and “defense response to fungus”. In contrast, the most significant cellular component (CC) terms were related to “plant-type cell wall” and “integral component of plasma membrane”, while molecular function (MF) enrichments were related to “beta-glucosidase activity” and “glucosidase activity” (Fig. 2C). The pathways that displayed significant changes (P value ≤0.05) were identified via the KEGG database. A total of 17 KEGG pathways were significantly enriched, among which “plant hormone signal transduction” (ko04075), “phenylpropanoid biosynthesis” (ko00940), “MAPK signaling pathway-plant” (ko04016) and “flavonoid biosynthesis” (ko00941) were the most highly represented. Both “plant hormone signal transduction” (ko04075) and “phenylpropanoid biosynthesis” (ko00940) exhibited many DEGs, suggesting that in poplar, plant hormones and phenylpropanoid compounds play significant roles in resistance to pathogen infection. The “MAPK signaling pathway” (ko04016) exhibited the third largest number of DEGs, indicating that during pathogen infection, the expression of internal genes in plants is regulated by various signaling substances for pathogen defense (Fig. 2D). Moreover, the disease resistance genes involved in the “plant–pathogen interaction pathway” (ko04626) or “Ras signaling pathway” (ko04014), such as RPM, RGA and DRL, were mainly upregulated after pathogen infection (Fig. S2). Taken together, these results suggest that poplar has evolved a range of different molecular defense strategies depending on the infection stage of the pathogen. Additionally, among these DEGs, 380 TFs that could be divided into 34 TF families were identified, such as the bHLH, MYB, NAC, bZIP (basic leucine zipper), WRKY and HSF families (Table S2). Some of these TFs have previously been reported to be closely related to the plant resistance response to biotic stress. For example, the largest group of pathogen-induced TFs belongs to the WRKY family, which is well known for plant defense, and several MYB, NAC, and bHLH family members were also induced during infection (Fig. 2E). This result suggests that TFs also play roles in the resistance of P. davidiana × P. bollena to A. alternata infection.

DEGs Involved in the Phenylpropanoid Pathway

Secondary metabolites are known to be involved in plant defense against pathogens by forming physical or chemical barriers. In this study, DEGs related to secondary metabolism showed significant changes during pathogen infection, especially changes in “phenylpropanoid biosynthesis” (ko00940) and “flavonoid biosynthesis” (ko00941). In total, over one hundred DEGs with significant expression involved in 32 different biosynthetic pathways were enriched in these pathways. A gene for phenylalanine ammonia-lyase (PAL), which is involved in the first step of phenylpropanoid biosynthesis and catalyzes lignin accumulation, was upregulated at 3 DPI. Other genes involved in lignin biosynthesis, such as the 4-coumarate-CoA ligase (4CL) and shikimate O-hydroxycinnamoyltransferase (HCT) genes, were upregulated, while the trans-cinnamate 4-monooxygenase (C4H) gene was downregulated. Key genes leading to lignin formation, including p-coumarate 3-hydroxylase (C3H), cinnamyl alcohol dehydrogenase (CAD) and cinnamoyl-CoA reductase (CCR), were up- or downregulated at different time points in this study (Fig. 3A). Moreover, genes for chalcone synthases (CHS), a branch point enzyme in flavonoid biosynthesis, were upregulated during pathogen infection, while flavanone 3-hydroxylase (F3H), which leads to the formation of quercetin derivatives, was downregulated or upregulated. Additionally, genes encoding leucoanthocyanidin dioxygenase (LDOX) and leucoanthocyanidin reductase (LAR), which are involved in the synthesis and extension of proanthocyanidins, respectively, were both upregulated at 2 DPI and 3 DPI (Fig. 3B).

DEGs related to ROS accumulation and scavenging

As the H₂O₂ content in leaves, as well as the enzyme activities involved in ROS scavenging, changed after infection, the DEGs related to ROS accumulation and scavenging were identified. Three genes encoding respiratory burst oxidase homolog (RBOH) proteins, which respond to pathogens by producing ROS, were upregulated during infection. Moreover, genes encoding enzymes involved in ROS scavenging also showed significant changes. The expression levels of genes such as SOD, PPO, CAT, POD and glutathione peroxidase (GPX) were mainly upregulated, especially for PPO and POD, which showed high expression during infection (Fig. 4D). In addition, the expression of glutathione S-transferases (GSTs) was mainly upregulated at 2 DPI, while only GSTFB (Pda_00008118-RA) was continuously activated during infection.

Defense-related Proteins

Pathogenesis-related (PR) proteins, which are indispensable components of plant innate immunity, play important roles in plant defense against pathogens. In this study, many poplar PR genes were induced in response to A. alternata infection, the expression of PR-1 was upregulated at both 2 DPI and 3 DPI, but most of the thaumatin-like protein (PR-5) genes were downregulated, except one that had high transcript levels during pathogen infection (Fig. 4C). Our results also demonstrate that the PR-9s (peroxidases), PR-10s (ribonucleases), PR-14s (lipid-transfer proteins) and PR-16s (germin-like proteins) were up or down regulated throughout the infection period (Fig. 4C,D). Furthermore, most of the chitinases showed high transcript levels at both 2 DPI and 3 DPI but were downregulated at 4 DPI (Fig. 4A), while some of the glucusidas were up regulated at 2 DPI but then down regulated (Fig. 4 B) .

DEGs Related to Plant hormone and signal transduction

Phytohormones, especially salicylic acid (SA), jasmonic acid (JA), and ethylene (ET), are critical regulators of plant–pathogen interactions, among them, the JA/ET signaling pathway is involved in the response to necrotrophic pathogen infection. In this study, DEGs related to JA/ET synthesis and signal transduction were identified, and most were upregulated during infection. Genes involved in JA synthesis, including linoleate lipoxygenase (LOX), allene oxide synthase (AOS), allene oxide cyclase (AOC), 12-oxophytodienoate reductase (OPR) and acyl-coenzyme oxidase (ACX), were induced during infection. The expression levels of LOX, AOC, AOS3 and ACX were upregulated continuously, while the expression of OPR3 was upregulated at 2 DPI but downregulated at 4 DPI. Moreover, the expression levels of MYCs involved in JA signal transduction were upregulated at both 2 DPI and 3 DPI. However, the expressions of JAZ, which contains a conserved TIFY domain and is a negative regulator of JA signal transduction, were mainly downregulated during pathogen infection (Fig. 5A). Similarly, genes for enzymes related to ET synthesis, including S-adenosylmethionine synthase (SAMS), 1-aminocyclopropane-1-carboxylate synthase (ACS) and 1-aminocyclopropane-1-carboxylate oxidase (ACO), were all upregulated during infection. Genes involved in the ET signal transduction pathway were also significantly induced. Five ethylene-responsive transcription factors (ERFs) were upregulated, while one ERF was downregulated. Among these ERFs, two ERFC3s (Pda_00014570-RA and Pda_00008900-RA) were highly induced at all time points (Fig. 5B). The SA response pathway has frequently been shown to be associated with plant resistance to biotrophic and hemibiotrophic pathogens. DEGs related to SA accumulation and signal transduction were also identified. The genes for enhanced disease susceptibility 1 (EDS1) and its coregulator phytoalexin deficient 4 (PAD4), which are related to SA accumulation, were both downregulated during infection. However, a few genes involved in the SA signal transduction pathway were induced. The TGA1 gene was transcribed 1.03-fold at 2 DPI, and two NPR genes were upregulated at 4 DPI (Fig. S3).

The linoleate 13 -lipoxygenase gene (PdbLOX) of P. davidiana × P. bollena is involved in resistance to A. alternata

Lipoxygenase (LOX), a key enzyme in the JA biosynthetic pathway, was shown to be involved in plant defense responses against diverse pathogens. Based on the KEGG analyses and gene expression data, we found that several lipoxygenase genes were strongly induced during the infection of poplar leaves by A. alternata, especially PdbLOX (Pda_00004421-RA), therefore, we speculated that this specific LOX gene plays an underlying role in regulating P. davidiana × P. bollena defense against A. alternata infection. The transgenic poplars with overexpressing PdbLOX (PdbLOX-OE) and RNAi-silenced PdbLOX (PdbLOX-IE) were obtained via Agrobacterium infection, and then the expressions of PdbLOX were analyzed via RT–qPCR. PdbLOX was expressed at significantly higher levels in PdbLOX-OE lines than in the wild type (WT), but lower in PdbLOX-IE lines (Fig. 6B). Next, leaves from transgenic poplars, as well as those from WT, were inoculated with A. alternata. After inoculation, the disease spots on WT leaves were dark, extensive, and irregular, while the disease spots on leaves of PdbLOX-OE plants were light-colored circles, were particularly smaller than WT. In contrast, the disease spots on leaves of PdbLOX-IE plants were darker and larger than that on WT (Fig. 6A,C). All this results above were further confirmed by the percentage disease index (Fig. 6D).

Recently, poplar leaf blight caused by A. alternata has become a common disease that has had a serious economic impact in China, but little is known about the molecular mechanisms underlying the resistance to A. alternata infection in poplar. In the present study, we investigated the mechanism of transcriptional response in P. davidiana × P. bollena caused by A. alternata infection. Through the result of transcriptomic analysis in both pathogen-infected (2 DPI, 3 DPI, 4 DPI) and mock-inoculated (0 DPI) leaves, 5,930 DEGs were identified, while 20.15% of them have no homologous genes after examined public databases, perhaps an indicator that those genes have yet to be identified in other plants. To determine the functional categories of the DEGs induced by pathogenic infection, GO and pathway enrichment analyses were performed. The results showed that most of the DEGs were involved in “plant hormone signal transduction” (ko04075) and “phenylpropanoid biosynthesis” (ko00940) or enriched for “defense response to fungus” and “plant-type cell wall”, which are all involved in plant defense against pathogens. These results are in line with plants potentially having evolved a series of molecular defense mechanisms during different infection stages of a pathogen.

Phenylpropanoid compounds are involved in defense against A. alternata infection

Secondary metabolites formed through the phenylpropanoid biosynthetic pathway act in plant defenses ranging from preformed or inducible physical and chemical barriers to signaling molecules involved in local and systemic signaling to induce other defense genes [14, 36, 37]. Among these secondary metabolites, lignin has been shown to form a mechanical barrier when plants resist pathogen infection, and genes involved in catalyzing lignin, such as PAL, HCT, CCR and CAD, affect plant disease resistance [15, 38]. For example, in wheat, silencing genes encoding the monolignol biosynthesis enzymes, such as PAL and CAD, leads to susceptibility of leaf tissues to the fungal pathogen Blumeria graminis f. sp. tritici [39]. And in Arabidopsis, the CAD genes which have been demonstrated to be involved in lignin biosynthesis, act as essential components of defence to virulent and avirulent strains of the bacterial pathogen P. syringae pv. tomato [40].The PtHCT2 gene was shown to respond to infection by the pathogen Sphaerulina musiva in resistant P. trichocarpa cultivars compared to susceptible cultivars [41]. For our study, genes related to lignin biosynthesis in poplar, such as PAL, 4CL, HCT, CCR and CAD, were induced during the interaction with A. alternata (Fig. 3A), which suggests that the lignin biosynthetic pathway responds to pathogen infection.

Moreover, flavonoids, including anthocyanins, flavonols, flavones, and proanthocyanidins, were also shown to play roles in protecting plants against pathogens. Genes related to the biosynthesis of these metabolites, especially CHS and F3H, were induced during pathogen infection. For example, the expression of CHS in soybean is upregulated during both fungal and bacterial pathogen infection [42]. The overexpression of OxF3H in rice increased tolerance to bacterial leaf blight [43]. In this study, DEGs related to flavonoid biosynthesis, including CHS, F3H, DFR and LDOX, were induced by A. alternata infection, especially at the early stage of infection (Fig. 3B), which indicated that poplar defends against A. alternata by inducing the production of flavonoids.

ROS signaling is involved in defense against A. alternata infection

Pathogen infections induce the rapid accumulation of ROS, which limit the ingress of or cause oxidative damage to pathogens [16, 44]. Simultaneously, excessive ROS can cause an increase in the levels of enzymatic and nonenzymatic antioxidants. The enzymes involved in oxidative bursts and scavenging, such as POD, GST, APX, SOD, and RBOH, are activated and induced by pathogen infection in plants. For example, genes encoding antioxidant and detoxifying enzymes, including GSTs and POD, were significantly induced in the resistant cucumber genotype No. 26 but not obviously induced in the susceptible genotype 26M during B. cinerea infection [45]. Similarly, tomato bushy stunt virus infection significantly affects enzymes that are responsible for the balance of ROS accumulation, such as CAT and SOD, in N. benthamiana [46]. Pyricularia oryzae infection induces the expression of OsRBOHB and alters its localization in rice, which results in the focal accumulation of ROS around invasive hyphae and effectively inhibits pathogen infection [47]. In this study, the activity of enzymes involved in ROS scavenging, including SOD, POD, PPO and CAT, was notably induced during infection, which is in line with the expression patterns of the related genes. Other genes related to ROS production, such as RBOH and LOX, were also induced, while the H₂O₂ content significantly increased during infection (Fig. 1G-K, Fig. 4D). These results suggest that poplar may defend against infection by accumulating ROS.

JA/ET signaling pathway activation after A. alternata infection

Plant responses to biotic stress are also coordinated by a network of signal transduction pathways that control a wide range of physiological processes. For example, JA/ET-dependent signaling is commonly known to be involved in basal or induced plant defense mechanisms against necrotrophic pathogens [11, 12]. The MYC protein, a positive regulator in the JA signaling pathway, was shown to play roles in plant defense by integrating signals from the JA and ET pathways. For example, MYC2 and its downstream MYC2-targeted TFs (MTFs) form a transcription module that may directly regulate the JA-induced transcription of late defense genes during tomato resistance to B. cinerea [48]. The overexpression of OsMYC2 in rice resulted in the upregulation of early JA-responsive genes, as well as resistance to bacterial blight [49]. Moreover, numerous ERF genes have been shown to be involved in JA-mediated defense responses; these genes include AtERFs in Arabidopsis [50–54], TaERF3 and TaPIEP1 in wheat [55, 56], and OsERFs and OsEREBP1 in rice [57–59]. In this study, genes involved in the JA/ET signaling pathway and JA/ET biosynthesis, such as LOX, AOS, MYC, and ERF, were notably induced, but genes related to SA signaling were downregulated during infection (Fig. 5). In addition, the JA content significantly increased during infection, while the changes in SA content were not very clear (Fig. 1D,E). These results suggested that P. davidiana × P. bollena may resist A. alternata infection mainly via the JA/ET signaling pathway.

PdbLOX participates in poplar resistance and defense by mediating JA signaling pathways and ROS production

Lipoxygenase plays roles in plant resistance, including initiating the synthesis of signaling molecules, such as JA or MeJA, or changing the metabolism in the cell, which leads to a high ROS content and ultimately causes cell death [60–64]. For example, the early activation of LOX genes and other JA biosynthetic genes was shown to be involved in resistance in maize, and ZmLOX3 in maize may be involved in fungal pathogenesis by mediating oxylipin metabolism; the loss of ZmLOX3 function leads to susceptibility to Aspergillus flavus and A. nidulans infection in maize [65, 66]. In cotton, GhLOX2 positively regulates tolerance to Verticillium dahliae infection via JA signaling, while silencing GhLOX2 inhibited H₂O₂ accumulation, which impaired cotton resistance [67]. In this study, we obtained transgenic poplar plants that overexpressed PdbLOX as well as the RNAi plants. The PdbLOX-OE plants exhibited significantly higher resistance to A. alternata infection than did WT plants, while the PdbLOX-IE lines shown more susceptible to A. alternata than WT (Fig. 6). Moreover, the overexpression of PdbLOX increased the transcription of JA-signaling-related genes and promoted JA accumulation. In addition, the H₂O₂ content increased significantly, and ROS-scavenging enzymes were activated in PdbLOX-OE lines. While the opposite physiological changes were observed in PdbLOX-IE plants (Fig. 7). Overall, these results suggest that the PdbLOX involved in the resistance of poplar to A. alternate infection by regulate the JA synthesis and signaling pathway as well as the ROS accumulation.

In summary, we used RNA-Seq technology to perform a global transcription analysis of P. davidiana × P. bollena in response to A. alternata infection, and the lipoxygenase gene PdbLOX was selected for further study; that analysis helped us better understand the transcriptional response of poplar to A. alternata infection and in the future breed durable, broad-spectrum disease-resistant crops. A total of 5,930 DEGs were obtained via RNA-Seq, and functional annotation showed that a variety of defense responses mediated by ROS accumulation, phenylpropanoid compound production and JA/ET signaling were activated. Then, the PdbLOX was shown to be involved in the resistance of poplar to A. alternate infection by regulate the JA synthesis and signaling pathway as well as the ROS accumulation by genetic engineering. Our results suggest that JA/ET signaling, the ROS metabolic pathway and phenylpropanoid compounds, which constitute a coordinated defense network, are involved in the response of poplar to A. alternata infection (Fig. 8).

Plant Materials, Pathogen Culture, and Inoculation Method

The phytopathogenic fungus Alternaria alternata was cultured for 10 days on potato dextrose agar (PDA) medium in the dark and then diluted with sterile water to 1 × 10⁶ spores/mL. Seedlings of Populus davidiana × P. bollena were grown in a greenhouse under 16-h light/8-h dark conditions at 25 °C for three months. Then, healthy leaves were inoculated with 10 μl of spore suspension and leaves inoculated with sterile water only served as the mock control. The leaves were observed and sampled 2, 3 and 4 d after inoculation. Leaf lesion areas were measured by ImageJ software [68, 69]. The infection ratings were assigned and calculated according to the method of Pandey [70]. Three biological replicates, each containing ten parallel leaves from ten different plants, were used for each treatment time point or control. The samples were then placed in liquid nitrogen rapidly and stored at −70 °C.

Biochemical assays

The samples were used to determine the contents of phytohormones, H₂O₂and the activity of enzymes, including peroxidase (POD), polyphenol oxidase (PPO), superoxide dismutase (SOD), catalase (CAT) and phenylalanine ammonia-lyase (PAL),. The phytohormones contents, including SA and JA were determined via enzyme-linked immunosorbent assay (ELISA) kits (Shanghai, China BYE97056 and RJ-21830, respectively), and the H₂O₂ content was determined via a hydrogen peroxide assay (Nanjing, China A064). The activities of PAL, SOD, POD as well as CAT were measured based on the methods of Liu [71].The PPO activity was measured according to the method of Hammerschmidt [72]. For each assay, three biological replicates were used.

RNA Extraction, Library Construction and Sequencing

Total RNA was isolated using an RNeasy Plant Mini Kit and treated with RNase-free DNase I (Qiagen, Hilden, Germany). The quality of the RNA was checked via agarose gel electrophoresis to ensure that clear bands were visible. The integrity and quantity of the RNA samples were determined using a NanoDrop2000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA) and an Agilent Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA, USA). RNA-Seq cDNA libraries were constructed from mRNA using an NEB Next UltraTM RNA Library Prep Kit for Illumina (NEB, USA) according to the manufacturer’s instructions. Finally, twelve cDNA libraries (three prior to inoculation (0 d), three at 2 DPI, three at 3 DPI and three at 4 DPI) were constructed for sequencing. RNA-Seq was performed on the Illumina HiSeq 2500 platform to obtain paired-end reads. The RNA-Seq data were deposited in the NCBI Sequence Read Archive database (http://www.ncbi.nlm.nih.gov/sra/) under project accession number PRJNA649854.

Analysis of differentially expressed genes and functional annotation

To obtained clean reads, the adaptor reads, low-quality reads(Q-value < 20) and reads those containing more than 10% ambiguous “N” bases were discarded. Clean reads were mapped to the Populus davidiana genome (GenBank: GCA_014885075.1) using Tophat2 software with default parameter settings [73]. To identify DEGs in poplar in response to A. alternata infection at different time points after inoculation, the expression level of each transcript was calculated based on the FPKM (fragments per kilobase of exons per million mapped reads) with the software package Cufflinks [74]. Differential expression analysis of the two samples was performed using the DESeq2 R package. | log₂fold change| ≥ 1 and false discovery rate (FDR) values <0.05 were used as cutoff criteria for DEGs. Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the DEGs were performed using eggNOG-mapper software [75].

Real-time quantitative PCR validation of expression profiles

Total RNA was extracted from the leaves of 3-month-old plants and transgenic plants treated with A. alternata for 0 (control), 2, 3 and 4 d using an RNeasy Plant Mini Kit (Qiagen, Hilden, Germany), and cDNA was synthesized for quantitative real-time PCR (RT–qPCR ) using the TransScript One-Step gDNA Removal and cDNA Synthesis SuperMix Kit (AT311, TransGen Biotech, Beijing, China) according to the manufacturer’s method. RT–qPCR was conducted using SYBR^®Green Real-time PCR Master Mix (QPK-201, Toyobo, Osaka, Japan) in a CFX96 TouchTM Real-Time PCR detection system (Bio–Rad, Hercules, CA, USA). Three biological replicates, each with three technical replicates, were used per sample. The housekeeping genes PdbEF and Pdbactin were selected as the internal controls, and the primers used for RT–qPCR analysis are listed in Table S3. Relative gene expression levels were measured using the 2⁻^ΔΔCtmethod [76].

Generation of transgenic plants

The complete ORF of PdbLOX was cloned into the KpnI and XbaI restriction enzyme sites of pROKII under the control of the CaMV 35S promoter and NOS terminator to generate the overexpression construct pROKII-PdbLOX. And a 203 bp truncated inverted repeat CDS of PdbLOX was inserted into RNAi vector pFGC5941 (pFGC::PdbLOX) to silence the expression of PdbLOX. Then, the constructs were introduced into Agrobacterium strain EHA105, which were then transformed into P. davidiana × P. bollena via Agrobacterium-mediated leaf-disk transformation, respectively. The transgenic poplar were selected using kanamycin (50 mg/L) for over expression plants (PdbLOX-OE), or glyphosate (1 mg/L) for RNA silenced plants (PdbLOX-IE), and all transgenic poplars were verified via genomic PCR and RT–qPCR. For the primers used for transformation are list in Table S3.

Alternaria alternata resistance assay in transgenic plants

Leaves collected from three-month-old transgenic plants and wild-type plants were inoculated with A. alternata plugs (5 mm) and then placed in a transparent square Petri dish under the conditions described above. The leaves were observed and sampled 4 d after inoculation. Three biological replicates, each including three parallel leaves from three different plants, were used for each treatment time point. The sampled leaves were used to determine the JA and H₂O₂contents, the activity of enzymes, including lipoxygenase (LOX), POD, CAT, SOD, ascorbate peroxidase (APX) and glycopeptide reductase (GR), and RT–qPCR. The contents of JA and H₂O₂were determined as described above. The activities of CAT, SOD, POD and APX were measured as described above. The determination and calculation of enzyme activity were performed using a lipoxygenase (LOX) activity assay kit (BC0320, Beijing Solarbio Science & Technology, Beijing, China). GR activity was measured as described by Ge [77]. GST activity was measured as described by Horváth [78]. RT–qPCR followed the method described above, and the primers used for analysis are listed in Table S3. For each assay, three biological replicates were analyzed.

Statistical analyses

Statistical analyses were carried out using SPSS v.20 software. The data were compared using Student’s t-test. Differences between two groups of data were considered statistically significant at p < 0.05. * means significant difference.

Ethics approval and consent to participate

All methods were performed in accordance with the relevant guidelines and regulations.

Consent for publication

Not applicable.

Availability of data and materials

The data used to support the findings of this study are available from the corresponding author upon request and are included in manuscript and its additional files. All the transcriptome data from 12 samples have been deposited in NCBI’s Sequence Read Archive (SRA) under accession number PRJNA649854.

Conflicts of interest

The authors declare no competing interests.

Funding

This work was supported by the National Natural Science Foundation of China (No. 31870665) and The Innovation Project of the State Key Laboratory of Tree Genetics and Breeding (Northeast Forestry University) (No. 2014B03).

Author Contributions

Chao Wang designed the experiments. Ying Huang, Huijun Ma, and Zhenyu Zhu performed the experiments. Yuanzhi Yue, and Tianchang Zhou analyzed the data. Ying Huang and Chao Wang drafted and revised the manuscript.

Acknowledgements

We thank the State Key Laboratory of Tree Genetics and Breeding(Northeast Forestry University).

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Integrated transcriptomic and transgenic analyses reveal potential mechanisms of poplar resistance to Alternaria alternata infection

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