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Article

Role of PsnWRKY70 in Regulatory Network Response to Infection with Alternaria alternata (Fr.) Keissl in Populus

by
Wei Wang
1,
Xiang-Dong Bai
1,
Kun Chen
1,
Chen-Rui Gu
1,
Qi-Bin Yu
2,
Jing Jiang
1 and
Gui-Feng Liu
1,*
1
State Key Laboratory of Tree Genetics and Breeding, Northeast Forestry University, 26 Hexing Road, Harbin 150040, China
2
Citrus Research and Education Center, University of Florida, Lake Alfred, FL 33850, USA
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2022, 23(14), 7537; https://doi.org/10.3390/ijms23147537
Submission received: 13 June 2022 / Revised: 4 July 2022 / Accepted: 5 July 2022 / Published: 7 July 2022
(This article belongs to the Section Molecular Plant Sciences)
Browse Figures
Versions Notes

Abstract

:
WRKY is an important complex family of transcription factors involved in plant immune responses. Among them, WRKY70 plays an important role in the process of the plant defense response to the invasion of pathogens. However, the defense mechanism of PsnWRKY70 is not clear in Populus nigra. In this study, we showed that PsnWRKY70-overexpression lines (OE) had fewer leaf blight symptoms than PsnWRKY70-repressing lines (RE). PsnWRKY70 activated MAP kinase cascade genes (PsnM2K4, PsnMPK3, PsnM3K18), calcium channel proteins-related genes (PsnCNG3, PsnCNGC1, PsnCNG4), and calcium-dependent protein kinases genes (PsnCDPKL, PsnCDPKW, PsnCDPKS, PsnCDPKQ). Furthermore, 129 genes of PsnWRKY70 putative genome-wide direct targets (DTGs) were identified by using transcriptome (RNA-seq) and DNA affinity purification sequencing (DAP-seq). PsnWRKY70 directly binds to the promoters of homologous genes and LRR domain proteins to promote the expression of WRKY6, WRKY18, WRKY22, and WRKY22–1, LRR domain proteins LRR8, LRR-RLK, ADR1-like 2, NB-ARC, etc. Our study suggests that PsnWRKY70 enhances the resistance of A. alternata in poplar by activating genes in both pathogen-associated molecular pattern-triggered immunity (PTI) and effector-triggered immunity (ETI).

1. Introduction

In the natural environment, plants are constantly confronted with diverse biotic and abiotic stresses that adversely affect their growth and development [1]. Pathogen attack is one of the most limiting factors affecting plant growth and thus poses a serious threat to the agroforestry industry worldwide [1,2,3]. Alternaria alternata is a necrotrophic fungal pathogen. Its multiple pathological races can infect many plants, such as chrysanthemum (Chrysanthemum morifolium), tobacco (Nicotiana attenuata), and poplar (Populus. tomentosa), causing huge national economic losses [3,4,5].
Plants have developed multitiered defense mechanisms for protection against pathogens. Plants have evolved pathogen-associated molecular patterns (PAMP)-triggered immunity (PTI) and effector-triggered immunity (ETI) systems [6,7]. Usually, a reactive oxygen species (ROS) burst occurs by binding to cell membrane surface co-receptors and by phosphorylating RLCKs, MAPKs, and calcineurin kinases [8,9,10,11]. At the same time, intracellular nucleotide-binding LRR (NLR) receptors cooperate with lipase-like proteins such as EDS1, SAG101, and PAD4 to induce ETI through NLRs of the ADR1 family and the NRG1 family [12]. In N. benthamiana, the MAPK cascade activates WRKY7, WRKY8, WRKY9, and WRKY11. These WRKYs can bind to the W-box element in the RBOHB promoter to upregulate the RBOHB gene and cause a ROS burst [13]. Recent studies have shown that, in Arabidopsis, activation of the RPS2 gene leads to the accumulation of BIK1 and RBOHD proteins and increased transcription of WRKY29 and AZI [14]. Pathogen defense response is achieved through large-scale transcriptional activation of defense-related genes [15,16]. WRKY transcription factors play a crucial role in the regulatory network for defense against pathogenic infection [17]. WRKYs are mainly characterized by a highly conserved WRKYGQK motif and a zinc finger motif [18]. WRKYs exert their regulatory functions by binding to the DNA sequence of the W-box (TTGACT/C) [19,20]. PtrWRKY89 accelerates pathogenesis-related protein (PR) gene expressions and enhances pathogen resistance in transgenic poplar (Populus trichocarpa) and is a regulator of salicylic acid (SA)-dependent defense signaling in poplar [21]. Liu et al. identified BnWRKY33 as a S. sclerotiorum responsive gene by enhancing the expression of genes involved in camalexin synthesis and regulating SA and jasmonic acid (JA) to defend against the pathogen [22].
We previously showed that PsnWRKY70 overexpression improved leaf blight resistance in Populus. Fifteen days after A. alternata infection, the leaf disease index and MDA content of OE lines were significantly lower than those of WT lines, and the plant height was significantly higher than that of WT lines [23]. However, little is known about the defense mechanism of how poplar trees respond to the infection of A. alternata. The objective of the study was to investigate the defense mechanism of PsnWRKY70 and understand its role in the regulatory network response to infection with A. alternata. We performed RNA-seq analysis to investigate differentially expressed genes regulated by PsnWRKY70 during disease resistance in poplar. We also identified direct genome-wide target genes of PsnWRKY70 using DAP-seq. The key direct target genes regulated by PsnWRKY70 were verified in vivo by CHIP-PCR and qRT-PCR. Our results provide new insight into the molecular mechanism of the PsnWRKY70 transcription factor in forest disease resistance and could be used as one technical guidance for molecular breeding of forest disease prevention.

2. Results

2.1. PsnWRKY70 Reduces Infection with A. alternata

To ensure the accuracy of gene transformation, PCR molecular detection was performed on the PsnWRKY70-transformed poplars (Figure 1A). At the same time, qRT-PCR results show that compared with the WT line, the gene expression of PsnWRKY70 was significantly upregulated, 2.94 times in OE compared to that of WT (Figure 1B); on the contrary, the relative expression of PsnWRKY70 in the RE was significantly lower than that in the WT (Figure 1B). All the tested lines were susceptible to A. alternata in different degrees after 15 days of inoculation (Figure 1C,D). The leaves of the OE line had fewer disease spots and more green leaf color. OE had a 16% disease index in comparison with 46.3% of the WT line. The RE line had a 62.8% disease index and leaves showed chlorosis and yellowing with serious disease.

2.2. Transcriptime Analysis

A total of about 86 Gb of clean data was obtained with an average of about 9.5 Gb per sample. The mapping rate was between 81.72% and 84.68% (Table S2). The thresholds of DEGs between OE vs. WT and RE vs. WT were used with fold change ≥ 2 and p-value < 0.05. There were 691 and 309 exclusively upregulated DEGs in OE and RE lines. There were 70 overlap DEGs between OE and RE (Figure 2A). There were 804 and 322 exclusively downregulated DEGs in OE and RE lines. There were 55 overlap DEGs between OE and RE (Figure 2B). GO analysis showed that the 691 upregulated DEGs in OE were enriched in protein phosphorylation, cellular protein modification process, and response to stimulus (Figure 2C). The 309 upregulated DEGs for RE were enriched in protein phosphorylation, defense response to other organism, and immune response (Figure 2E). The 804 downregulated DEG for OE were enriched in cellular process, metabolic process, and organic substance metabolic process (Figure 2D). The 322 downregulated DEGs for RE were enriched in response to chemical, biological regulation, and cellular process (Figure 2F). KEGG enrichment analysis showed that 691 DEGs upregulated for OE were enriched in plant–pathogen interaction, MAPK signaling pathway–plant, and ABC transporters (Figure 3A). The 309 upregulated DEGs for RE were enriched in propanoate metabolism, alpha-Linolenic acid metabolism, and phosphonate and phosphinate metabolism (Figure 3C). The 804 downregulated DEGs for OE were enriched in alpha-Linolenic acid metabolism, starch and sucrose metabolism, phenylalanine, tyrosine, and tryptophan biosynthesis (Figure 3B). The 322 downregulated DEGs for RE lines were enriched in ABC transporters, ubiquitin-mediated proteolysis, and plant hormone signal transduction (Figure 3D).

2.3. PsnWRKY70 Activates the Expression of MAPK and Ca2+ Signaling-Related Genes

Genes that play important roles in disease resistance were regulated by PsnWRKY70 (Figure 4A,B). After OE lines were infected with A. alternata, genes in the MAPK cascades, such as M2K4, MPK3, and M3K18, were significantly upregulated. Similarly, Ca2+ channel proteins CNG3, CNGC1, and CNG4, and calcium-dependent protein kinases CDPKL, CDPKW, CDPKS, and CDPKQ were significantly upregulated as well. In addition, transmembrane receptor protein-related genes NIK2, CRK35, CRPK1, LRK10L-1.2, CRCK2, CES101, and CRK23 were significantly upregulated. As a result, PsnWRKY70 enhances disease resistance by upregulating the expression of a MAP kinase cascade, calcium signal-related genes, membrane receptors, and other related genes. SA-related biological processes were enriched with upregulated DEGs in OE (Figure 5). They were PAD4, CBP60C, and CBP60D, but they were not significantly changed in RE.

2.4. Genome-Wide Binding Targets of PsnWRKY70

The target protein of PsnWRKY70 was expressed by the wheat germ protein expression system and the protein expression was detected by Western blot. The detection results are shown in Figure 6A: the fusion protein is about 70 kD. After filtering the original DAP-seq data, a total of about 2.95 Gb of data was obtained, including 5.6~6.5 million clean reads per sample (Q30 ≥ 89.82%) (Table S3). The mapping rate of the unique locus of the gene was 40.38–42.24%. The total mapping rate (including the multi-locus alignment of the genome) was 71.05–73.92% (Table S4). The 1 kb flanking sequences around the peaks of all genes were applied to the motif discovery tool MEME-CHIP to explore the PsnWRKY70 transcription factor binding motif (Figure 6D). The results showed that the main motifs bound by PsnWRKY70 were “NMAAGTCAACNNNDN“ (E-value = 1.7 × 10−270) and “RGTCAAY” (E-value = 4.9 × 10−268). PsnWRKY70 peaks in DAP-seq were distributed over gene regions. The transcription starting site is 2 kb downstream of the transcription termination. PsnWRKY70 binding sites were identified in 2103 gene regions. Among them, 65.56% were in the promoter region (−2 kb to +500 bp of TSS), 0.41% in the intergenic region, 14.09% in the intron region, 14.73% in the exon region, and 5.18% in the terminator region (Figure 6C). The identification promoter site for PsnWRKY70 was based on the distance between each peak and its closest gene TSS. It was determined that the PsnWRKY70 binding site was significantly concentrated at 300 bp upstream of TSS in the core promoter region (Figure 6B). These distribution patterns of PsnWRKY70 binding sites in DAP-seq experiments are consistent with the fact that PsnWRKY70 acts as a transcription factor.

2.5. Target Genes Were Regulated by PsnWRKY70

To find the downstream target genes directly regulated by PsnWRKY70, the Venn map showed that PsnWRKY70 directly regulated 43 target genes among 691 upregulated genes in OE lines (Figure 7A). These include the WRKY family homologous genes WRKY6, WRKY18, WRKY22, and WRKY22-1. These WRKY family homologous genes play an important role in the process of resistance to pathogenic bacteria. It also includes some R genes that play an important role in disease resistance, such as leucine-rich repeat (LRR8), leucine-rich repeat receptor-like protein kinase family protein (LRR-RLK), ADR1-like 2, similar to putative disease resistance protein, LRR protein, NB-ARC domain, and LRR-containing proteins (Table 1). Among the 322 downregulated genes in RE lines, PsnWRKY70 directly regulated 12 target genes (Figure 7B). These include LOB domain-containing protein 41, LRR-1, photosystem II subunit R, glycosyl transferase family 2 protein, and some others. These genes positively regulated by PsnWRKY70 play an important role in disease resistance. Similarly, among the 804 downregulated genes in the OE lines, PsnWRKY70 directly targeted 47 of them (Figure 7A). Among the 309 upregulated genes in RE lines, PsnWRKY70 directly regulated 27 of them as target genes (Figure 7B). These PsnWRKY70 negatively regulated genes may also play a role in disease resistance. qPCR validation showed that WRKY6, WRKY18, WRKY22, ADR1-like2, CBP60C, and LEA2 genes were significantly upregulated in OE lines (p < 0.05) (Figure 7D). In addition, CHIP-PCR showed that WRKY6, WRKY18, WRKY22, WRKY22-1, ADR1-like2, NB-ARC, and LRR8 amplify clear bands. This suggests that PsnWRKY70 directly regulates WRKY6, PsnWRKY18, WRKY22, WRKY22-1, ADR1-like2, NB-ARC, and LRR8, thereby enhancing the resistance to A. alternata (Figure 7C).

3. Discussion

3.1. PsnWRKY70 Induces Other WRKYs to Enhance Disease Resistance

WRKYs typically contain functional W-boxes in their promoters and can be regulated by their own gene products or other WRKYs [24,25,26,27]. In Parsley (Petroselinum crispum), PcWRKY1 binds to the W-box element on its own promoter for self-regulation, and can also bind to the W-box element on the promoter of PcWRKY3 [25]. In Arabidopsis, WRKY46 interacts with NPR1 to bind to the W-box of the WRKY6 promoter to induce its expression in response to SA signaling. Overexpression of WRKY6 is sufficient to accelerate leaf senescence [26]. In Rice (Oryza sativa), WRKY45-2, WRKY13, and WRKY42 form a transcriptional regulatory cascade in response to Magnaporthe oryzae [27]. WRKY transcription factor plays an important role in disease resistance. Previous studies have shown that OsWRKY6 directly binds to WLE1 and W-box in defense-related gene promoters and regulates pathogen defense responses. OsWRKY6 enhances SA accumulation by activating rice OsICS1 gene expression involved in SA biosynthesis [15]. AtWRKY18 enhances PR gene expression and resistance to Pseudomonas syringae. However, excessive expression of AtWRKY18 also leads to severe abnormalities in plant growth [28]. Our data suggest that the PsnWRKY70 directly binds to the promoters of the homologous genes WRKY6, WRKY18, WRKY22, and WRKY22-1 to induce their expression after infection with A. alternata, thereby enhancing the resistance of poplar to necrotrophic fungi invasion.

3.2. PsnWRKY70 Plays a Key Role in PTI and ETI Pathways

Plant immunity has evolved into a complex, multilayered, and sophisticated system to fight against the threat of pathogenic microorganisms [29]. It is well-known that the plant’s innate immune system mainly relies on two major pathogen recognition mechanisms: PTI and ETI [30]. In Arabidopsis, the EDS1–PAD4–ADR1 node is a convergence point for defense signaling cascades activated by both surface-resident and intracellular LRR receptors in conferring pathogen immunity through PTI and ETI [31]. Additionally, (Ca2+) signaling plays an important role in plant PTI and ETI processes [32]. OsCNGC9 enhances rice resistance to Magnaporthe oryzae by regulating extracellular Ca2+ influx to promote ROS burst and activate the expression of PTI-related genes [33]. The formation of calcium channels by CNGC2 and CNGC4 is phosphorylated and activated by BIK1. BIK1 triggers an increase in cytosolic calcium concentration, which in turn activates immune signaling [34]. SA is a phytohormone essential for signaling in the pattern PTI and ETI [35]. SARD1 is a plant immune activator that promotes the production of the hormone SA and the activation of defense gene expression [36,37]. In the uninfected stage, AtWRKY70 represses the expression by binding to the GACTTTT motif on the SARD gene promoter and indirectly repressing CBP60g and SID2. In the infected stage, CBP60g and SARD1 are significantly induced. ES4326, CBP60g, and SARD1 are significantly induced by Pseudomonas syringae pv. Maculicola [38]. In Figure 8, we show that the PsnWRKY70 gene acts as a regulator to mediate the activation of PTI and ETI pathways of innate immunity. Our study found that M2K4, MPK3, and M3K18 in the MAPK cascade pathway were significantly upregulated in OE lines, along with calcium channel protein genes CNG3, CNGC1, and CNG4, and calcium-dependent protein kinase (CPKs) genes CDPKL, CDPKW, CDPKS, and CDPKQ. In addition, it was also found that SA biosynthesis-related genes PAD4, CBP60C, and CBP60D were also significantly upregulated in OE lines. The overexpression of the PsnWRKY70 gene in the OE line upregulated the expression of the MAP kinase cascade, calcium signal-related genes, SA synthesis genes, membrane receptors, and some other genes, thereby enhancing the resistance to A. alternata.

4. Materials and Methods

4.1. Plant Material

Transgenic plants (Populus simonii × Populus nigra) of PsnWRKY70 used in this study were described previously [23]. They are the overexpression line (OE), the repressed expression line (RE), and the wildtype (WT). Plants were grown in the Breeding Base of Northeast Forestry University in Harbin, Heilongjiang Province (126°64′ E, 45°72′ N). In the greenhouse, 15 cm-long stem cuttings were propagated in a substrate of peat soil:river sand:black soil (v/v) = 2:2:1 (16:8 h, light:dark, 22:25 °C) for 30 days. For each transgenic line, 9 plants with the same growth status were selected for treatment. To ensure the accuracy of transgenic plants, PCR molecular detection was performed on the PsnWRKY70 gene-transformed poplar. The PsnW70-F/PsnW70-R and A/B primer pairs were used for PCR validation of OE and RE. Primers are listed in Table S1.

4.2. Evaluation of Disease Severity

Plants for OE, RE, and WT lines were inoculated by spraying with A. alternata spore suspension (5.0 × 107 spores mL−1). Plants sprayed with water were used as controls for OE, RE, and WT lines. Each treatment had three biological replications. Disease severity scores were recorded and photographed after inoculation for 15 days. The disease index was calculated using the method [23]. The leaves were scored on a scale from 0 to 4: 0 (healthy leaves), 1 (<20% of leaves with spots), 2 (about 50% of leaves with spots), 3 (>80% of leaves with spots), and 4 (leaf is dead). Leaf disease index = ∑ (i × Ni) (Nt × Gmax)/ (Nt ×Gmax) × 100%, where i is the grade level (i.e., 0–4), Ni is the number of grades of i leaves, Nt is the total number of leaves, and Gmax is the highest grade level (i.e., 4) [23].

4.3. Transcriptome Analysis

Total RNA was extracted from the whole leaves of WT, OE, and RE transgenic plants using a universal plant total RNA extraction kit (BioTeke Corporation, Beijing, China) after A. alternata infection for 15 days. RNA samples were submitted for 150 bp paired−end reads on Illumina × 10 platform. To ensure the quality of the analysis data, the original sequences were filtered to obtain high-quality clean reads. Clean reads were mapped to the Populus trichocarpa genome using hisat2 [39]. The mapped reads were counted using Stringtie software [40]. Significance analysis of differentially expressed genes (DEGs) was performed using DEseq2 (p < 0.05, fold change ≥ 2) [41]. Each treatment sample had three sequencing biological replicates. DEGs were used for gene ontology (GO) enrichment analysis using the GO enrichment tool (http://geneontology.org (accessed on 1 February 2022)), with a p-value less than 0.01 as the threshold for significant enrichment [42,43,44]. DEGs were used for KEGG enrichment analysis using the KEGG enrichment tool (http://kobas.cbi.pku.edu.cn/genelist/ (accessed on 1 February 2022)), with a p-value less than 0.05 as the threshold for significant enrichment [45].

4.4. Quantitative Real-Time Polymerase Chain Reaction (qPCR)

Total RNA was extracted using a universal plant total RNA extraction kit (BioTeke Corporation, Beijing, China), and cDNA was separately synthesized using the Toyobo Reverse Transcription Kit (ReverTra Ace® qPCR RT Master Mix with gDNA Remover (Toyobo, Osaka, Japan)). qRT-PCR was performed on an ABI-7500 quantitative PCR instrument using Toyobo SYBR® Green Real-time PCR Master Mix Plus (Toyobo, Osaka, Japan). The qPCR data were analyzed by the 2−ΔΔCT method, and 18S was used as the internal reference gene [46]. Primers of target genes are listed in Table S1.

4.5. DAP-Seq Analysis

The DAP experiments were performed following the published protocol [47]. Briefly, the genomic DNA of WT leaves was extracted by the CTAB method [48], and the genomic DNA was fragmented about 100–400 bp by Covaris M220, and then the genomic DNA library was prepared. In parallel, the coding sequence of PsnWRKY70 was cloned into the pFN19K HaloTag T7 SP6 Flexi expression vector. The Halo-PsnWRKY70 fusion protein was expressed using a TNT SP6-coupled wheat germ extraction system (Promega, USA) in 50 µL reactions and incubated at 37 °C for 2 h. The proteins were captured directly using Magne Halo Tag Beads (Promega, Madison, WI, USA). Finally, the purified protein was incubated with the genomic DNA library. The non-specifically bound DNA was eluted. The DNA fragments that could bind to the PsnWRKY70 protein were eluted. The library was amplified with primers containing sample-specific barcodes. A sample with two biological replicates for PsnWRKY70 DAP was used for 150 bp paired-end sequencing on the Hiseq X Ten platform (Illumina, San Diego, CA, USA). Reads were mapped to the Populus trichocarpa genome sequence using bowtie2 [49]. Peak calling was performed using Macs2 [50]. Motif discovery was performed using MEME [51]. Associations of DAP-seq peaks located upstream or downstream of the transcription start site (TSS) within 3.5 kb were analyzed using Homer [52].

4.6. CHIP-PCR

The CHIP procedure followed the method in [53]. The leaves of OE were cross-linked in a vacuum with a cross-linking buffer containing 1% formaldehyde on ice for 15 min. Chromatin was sonicated into fragments between 300 and 500 bp. The supernatant was incubated with an anti-GFP antibody (Abcam, ab290). Immunoprecipitated DNA fragments were purified using the Qiaquick PCR purification kit (Qiagen, Hilden, Germany). CHIP-PCR was conducted using the immunoprecipitated DNA fragments that were obtained above, and the sheared genome DNA was used as a positive control (primers are listed in Table S1) [54].

4.7. Statistical Analysis

Statistical significance was assessed by Student’s t-test and one-way ANOVA (**** p < 0.0001, *** p < 0.001, ** p < 0.01, * p < 0.05). Each sample had three biological replicates. The data mean was shown as the mean ± standard deviation (SD).

5. Conclusions

Here, we reported previously unknown regulatory pathways that mediate the response of Populus nigra to resistance to A. alternata necrotrophic fungi. RNA-seq analysis showed that the PsnWRKY70 gene enhanced the disease resistance by upregulating the expression of the MAP kinase cascade, calcium ion signal-related genes, membrane receptors, and other related genes. In addition, 129 downstream target genes of PsnWRKY70 were identified by RNA-seq and DAP-seq analysis, and CHIP-PCR found that the PsnWRKY70 gene can activate homologous WRKY6, WRKY18, WRKY22, WRKY22-1, and R genes to confer higher disease resistance in Populus. Other members of WRKYs may also play a role in disease resistance. This study further demonstrated the role of PsnWRKY70 in the regulatory network response to infection with Alternaria alternata (Fr.) Keissl in Populus.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijms23147537/s1.

Author Contributions

J.J., G.-F.L. and W.W. designed the experiment; W.W. and X.-D.B. performed the experiment; C.-R.G. and K.C. performed RNA-seq data analysis; W.W. wrote the manuscript; Q.-B.Y. and J.J. performed review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Safety Monitoring of Pilot-scale Experiment of Transgenic Populus simonii × P. nigra (KJZXSA202002) and The Heilongjiang Touyan Innovation Team Program (Tree Genetics and Breeding Innovation Team).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable

Data Availability Statement

All RNA-seq and DAP-seq data have been archived in the NCBI Sequence Read Archive (SRA), accession number PRJNA833248.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Peng, X.; Wang, H.; Jang, J.-C.; Xiao, T.; He, H.; Jiang, D.; Tang, X. OsWRKY80-OsWRKY4 Module as a Positive Regulatory Circuit in Rice Resistance against Rhizoctonia solani. Rice 2016, 9, 63. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Qi, M.; Wu, R.; Song, Z.; Dong, B.; Chen, T.; Wang, M.; Cao, H.; Du, T.; Wang, S.; Li, N.; et al. Sorbitol Reduces Sensitivity to Alternaria by Promoting Ceramide Kinases (CERK) Expression through Transcription Factor Pswrky25 in Populus (Populus simonii Carr.). Genes 2022, 13, 405. [Google Scholar] [CrossRef] [PubMed]
  3. Huang, Y.; Liu, H.; Jia, Z.; Fang, Q.; Luo, K. Combined expression of antimicrobial genes (Bbchit1 and LJAMP2) in transgenic poplar enhances resistance to fungal pathogens. Tree Physiol. 2012, 32, 1313–1320. [Google Scholar] [CrossRef] [Green Version]
  4. Sun, H.; Hu, X.; Ma, J.; Hettenhausen, C.; Wang, L.; Sun, G.; Wu, J. Requirement of ABA signalling-mediated stomatal closure for resistance of wild tobacco to Alternaria alternata. Plant Pathol. 2013, 63, 1070–1077. [Google Scholar] [CrossRef]
  5. Xin, J.; Liu, Y.; Li, H.; Chen, S.; Jiang, J.; Song, A.; Fang, W.; Chen, F. CmMLO17 and its partner CmKIC potentially support Alternaria alternata growth in Chrysanthemum morifolium. Hortic. Res. 2021, 8, 101. [Google Scholar] [CrossRef] [PubMed]
  6. Monaghan, J.; Zipfel, C. Plant pattern recognition receptor complexes at the plasma membrane. Curr. Opin. Plant Biol. 2012, 15, 349–357. [Google Scholar] [CrossRef]
  7. Nicaise, V.; Roux, M.; Zipfel, C. Recent Advances in PAMP-Triggered Immunity against Bacteria: Pattern Recognition Receptors Watch over and Raise the Alarm. Plant Physiol. 2009, 150, 1638–1647. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Ngou, B.P.M.; Ahn, H.-K.; Ding, P.; Jones, J.D.G. Mutual potentiation of plant immunity by cell-surface and intracellular receptors. Nature 2021, 592, 110–115. [Google Scholar] [CrossRef]
  9. Kadota, Y.; Sklenar, J.; Derbyshire, P.; Stransfeld, L.; Asai, S.; Ntoukakis, V.; Jones, J.D.; Shirasu, K.; Menke, F.; Jones, A.; et al. Direct Regulation of the NADPH Oxidase RBOHD by the PRR-Associated Kinase BIK1 during Plant Immunity. Mol. Cell 2014, 54, 43–55. [Google Scholar] [CrossRef] [Green Version]
  10. Peng, Y.; van Wersch, R.; Zhang, Y. Convergent and Divergent Signaling in PAMP-Triggered Immunity and Effector-Triggered Immunity. Mol. Plant-Microbe Interact. 2018, 31, 403–409. [Google Scholar] [CrossRef] [Green Version]
  11. Couto, D.; Zipfel, C. Regulation of pattern recognition receptor signalling in plants. Nat. Rev. Immunol. 2016, 16, 537–552. [Google Scholar] [CrossRef] [PubMed]
  12. Lapin, D.; Bhandari, D.D.; Parker, J.E. Origins and Immunity Networking Functions of EDS1 Family Proteins. Annu. Rev. Phytopathol. 2020, 58, 253–276. [Google Scholar] [CrossRef] [PubMed]
  13. Adachi, H.; Nakano, T.; Miyagawa, N.; Ishihama, N.; Yoshioka, M.; Katou, Y.; Yaeno, T.; Shirasu, K.; Yoshioka, H. WRKY Transcription Factors Phosphorylated by MAPK Regulate a Plant Immune NADPH Oxidase in Nicotiana benthamiana. Plant Cell 2015, 27, 2645–2663. [Google Scholar] [CrossRef] [Green Version]
  14. Yuan, M.; Jiang, Z.; Bi, G.; Nomura, K.; Liu, M.; Wang, Y.; Cai, B.; Zhou, J.; He, S.; Xin, X. Pattern-recognition receptors are required for NLR-mediated plant immunity. Nature 2021, 592, 105–109. [Google Scholar] [CrossRef] [PubMed]
  15. Choi, C.; Hwang, S.H.; Fang, I.R.; Kwon, S.I.; Park, S.R.; Ahn, I.; Kim, J.B.; Hwang, D.J. Molecular characterization of Oryza sativa WRKY6, which binds to W-box-like element 1 of the Oryza sativa pathogenesis-related (PR) 10a promoter and confers reduced susceptibility to pathogens. New Phytol. 2015, 208, 846–859. [Google Scholar] [CrossRef] [PubMed]
  16. Thieffry, A.; López-Márquez, D.; Bornholdt, J.; Malekroudi, M.G.; Bressendorff, S.; Barghetti, A.; Sandelin, A.; Brodersen, P. PAMP-triggered genetic reprogramming involves widespread alternative transcription initiation and an immediate transcription factor wave. Plant Cell 2022, 34, 2615–2637. [Google Scholar] [CrossRef]
  17. Winkelmüller, T.M.; Entila, F.; Anver, S.; Piasecka, A.; Song, B.; Dahms, E.; Sakakibara, H.; Gan, X.; Kułak, K.; Sawikowska, A.; et al. Gene expression evolution in pattern-triggered immunity within Arabidopsis thaliana and across Brassicaceae species. Plant Cell 2021, 33, 1863–1887. [Google Scholar] [CrossRef] [PubMed]
  18. Zhou, Q.; Tian, A.; Zou, H.; Xie, Z.; Lei, G.; Huang, J.; Wang, C.; Wang, H.; Zhang, J.; Chen, S. Soybean WRKY-type transcription factor genes, GmWRKY13, GmWRKY21, and GmWRKY54, confer differ-ential tolerance to abiotic stresses in transgenic Arabidopsis plants. Plant Biotechnol. J. 2008, 6, 486–503. [Google Scholar] [CrossRef] [PubMed]
  19. Rushton, P.J.; Macdonald, H.; Huttly, A.K.; Lazarus, C.M.; Hooley, R. Members of a new family of DNA-binding proteins bind to a conserved cis-element in the promoters of al-pha-Amy2 genes. Plant Mol. Biol. 1995, 29, 691–702. [Google Scholar] [CrossRef]
  20. Rushton, P.J.; Torres, J.T.; Parniske, M.; Wernert, P.; Hahlbrock, K.; Somssich, I. Interaction of elicitor-induced DNA-binding proteins with elicitor response elements in the promoters of parsley PR1 genes. EMBO J. 1996, 15, 5690–5700. [Google Scholar] [CrossRef]
  21. Jiang, Y.; Duan, Y.; Yin, J.; Ye, S.; Zhu, J.; Zhang, F.; Lu, W.; Fan, D.; Luo, K. Genome-wide identification and characterization of the Populus WRKY transcription factor family and analysis of their expression in response to biotic and abiotic stresses. J. Exp. Bot. 2014, 65, 6629–6644. [Google Scholar] [CrossRef]
  22. Liu, F.; Li, X.; Wang, M.; Wen, J.; Yi, B.; Shen, J.; Ma, C.; Fu, T.; Tu, J. Interactions of WRKY15 and WRKY33 transcription factors and their roles in the resistance of oilseed rape to Scle-rotinia infection. Plant Biotechnol. J. 2018, 16, 911–925. [Google Scholar] [CrossRef] [Green Version]
  23. Zhao, H.; Jiang, J.; Li, K.; Liu, G. Populus simonii x Populus nigra WRKY70 is involved in salt stress and leaf blight disease responses. Tree Physiol. 2017, 37, 827–844. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Liu, Z.; Shi, L.; Yang, S.; Qiu, S.; Ma, X.; Cai, J.; Guan, D.; Wang, Z.; He, S. A conserved double-W box in the promoter of CaWRKY40 mediates autoregulation during response to pathogen attack and heat stress in pepper. Mol. Plant Pathol. 2020, 22, 3–18. [Google Scholar] [CrossRef] [PubMed]
  25. Turck, F.; Zhou, A.; Somssich, I.E. Stimulus-dependent, promoter-specific binding of transcription factor WRKY1 to Its native promoter and the defense-related gene PcPR1-1 in Parsley. Plant Cell 2004, 16, 2573–2585. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Zhang, D.; Zhu, Z.; Gao, J.; Zhou, X.; Zhu, S.; Wang, X.; Wang, X.; Ren, G.; Kuai, B. The NPR1-WRKY46-WRKY6 signaling cascade mediates probenazole/salicylic acid-elicited leaf senescence in Arabidopsis thaliana. J. Integr. Plant Biol. 2021, 63, 924–936. [Google Scholar] [CrossRef] [PubMed]
  27. Cheng, H.; Liu, H.; Deng, Y.; Xiao, J.; Li, X.; Wang, S. The WRKY45-2 WRKY13 WRKY42 Transcriptional Regulatory Cascade Is Required for Rice Resistance to Fungal Pathogen. Plant Physiol. 2015, 167, 1087–1099. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Chen, C.; Chen, Z. Potentiation of Developmentally Regulated Plant Defense Response by AtWRKY18, a Pathogen-Induced Arabidopsis Transcription Factor. Plant Physiol. 2002, 129, 706–716. [Google Scholar] [CrossRef] [Green Version]
  29. Jones, J.D.G.; Dangl, J.L. The plant immune system. Nature 2006, 444, 323–329. [Google Scholar] [CrossRef] [Green Version]
  30. Dodds, P.N.; Rathjen, J.P. Plant immunity: Towards an integrated view of plant–pathogen interactions. Nat. Rev. Genet. 2010, 11, 539–548. [Google Scholar] [CrossRef]
  31. Pruitt, R.N.; Locci, F.; Wanke, F.; Zhang, L.; Saile, S.C.; Joe, A.; Karelina, D.; Hua, C.; Fröhlich, K.; Wan, W.L.; et al. The EDS1-PAD4-ADR1 node mediates Arabidopsis pattern-triggered immunity. Nature 2021, 598, 495–499. [Google Scholar] [CrossRef] [PubMed]
  32. Gao, X.; Cox, K.L., Jr.; He, P. Functions of Calcium-Dependent Protein Kinases in Plant Innate Immunity. Plants 2014, 3, 160–176. [Google Scholar] [CrossRef] [Green Version]
  33. Wang, J.; Liu, X.; Zhang, A.; Ren, Y.; Wu, F.; Wang, G.; Xu, Y.; Lei, C.; Zhu, S.; Pan, T.; et al. A cyclic nucleotide-gated channel mediates cytoplasmic calcium elevation and disease resistance in rice. Cell Res. 2019, 29, 820–831. [Google Scholar] [CrossRef] [PubMed]
  34. Tian, W.; Hou, C.; Ren, Z.; Wang, C.; Zhao, F.; Dahlbeck, D.; Hu, S.; Zhang, L.; Niu, Q.; Li, L.; et al. A calmodulin-gated calcium channel links pathogen patterns to plant immunity. Nature 2019, 572, 131–135. [Google Scholar] [CrossRef] [PubMed]
  35. Li, N.; Han, X.; Feng, D.; Yuan, D.; Huang, L. Signaling Crosstalk between Salicylic Acid and Ethylene/Jasmonate in Plant Defense: Do We Understand What They Are Whispering? Int. J. Mol. Sci. 2019, 20, 671. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Zhang, Y.; Xu, S.; Ding, P.; Wang, D.; Cheng, Y.; He, J.; Gao, M.; Xu, F.; Li, Y.; Zhu, Z.; et al. Control of salicylic acid synthesis and systemic acquired resistance by two members of a plant-specific family of transcription factors. Proc. Natl. Acad. Sci. USA 2010, 107, 18220–18225. [Google Scholar] [CrossRef] [Green Version]
  37. Wang, L.; Tsuda, K.; Truman, W.; Sato, M.; Nguyen, L.V.; Katagiri, F.; Glazebrook, J. CBP60g and SARD1 play partially redundant critical roles in salicylic acid signaling. Plant J. 2011, 67, 1029–1041. [Google Scholar] [CrossRef] [PubMed]
  38. Zhou, M.; Lu, Y.; Bethke, G.; Harrison, B.T.; Hatsugai, N.; Katagiri, F.; Glazebrook, J. WRKY70 prevents axenic activation of plant immunity by direct repression of SARD1. New Phytol. 2017, 217, 700–712. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  39. Pertea, M.; Kim, D.; Pertea, G.M.; Leek, J.T.; Salzberg, S.L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 2016, 11, 1650–1667. [Google Scholar] [CrossRef]
  40. Pertea, M.; Pertea, G.M.; Antonescu, C.M.; Chang, T.-C.; Mendell, J.T.; Salzberg, S.L. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat. Biotechnol. 2015, 33, 290–295. [Google Scholar] [CrossRef] [Green Version]
  41. Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Ashburner, M.; Ball, C.A.; Blake, J.A.; Botstein, D.; Butler, H.; Cherry, J.M.; Davis, A.P.; Dolinski, K.; Dwight, S.S.; Eppig, J.T.; et al. Gene ontology: Tool for the unification of biology. Nat. Genet. 2000, 25, 25–29. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Gene Ontology, C. The Gene Ontology resource: Enriching a GOld mine. Nucleic Acids Res. 2021, 49, D325–D334. [Google Scholar] [CrossRef] [PubMed]
  44. Mi, H.; Muruganujan, A.; Ebert, D.; Huang, X.; Thomas, P.D. PANTHER version 14: More genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res. 2018, 47, D419–D426. [Google Scholar] [CrossRef]
  45. Bu, D.; Luo, H.; Huo, P.; Wang, Z.; Zhang, S.; He, Z.; Wu, Y.; Zhao, L.; Liu, J.; Guo, J.; et al. KOBAS-i: Intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res. 2021, 49, W317–W325. [Google Scholar] [CrossRef]
  46. Wang, Y.; Yang, Y.; Wang, F.; Wang, G.; Wang, C.; Wang, W.; Chen, K.; Gu, C.; Yu, Q.; Jiang, J. Growth adaptability and foreign gene stability of TaLEA transgenic Populus simonii × nigra. Ann. For. Sci. 2021, 78, 42. [Google Scholar] [CrossRef]
  47. O’Malley, R.C.; Huang, S.-S.C.; Song, L.; Lewsey, M.G.; Bartlett, A.; Nery, J.R.; Galli, M.; Gallavotti, A.; Ecker, J.R. Cistrome and Epicistrome Features Shape the Regulatory DNA Landscape. Cell 2016, 165, 1280–1292. [Google Scholar] [CrossRef] [Green Version]
  48. Yao, J.; Shen, Z.; Zhang, Y.; Wu, X.; Wang, J.; Sa, G.; Zhang, Y.; Zhang, H.; Deng, C.; Liu, J.; et al. Populus euphratica WRKY1 binds the promoter of H+-ATPase gene to enhance gene expression and salt tolerance. J. Exp. Bot. 2019, 71, 1527–1539. [Google Scholar] [CrossRef]
  49. Langmead, B.; Salzberg, S.L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 2012, 9, 357–359. [Google Scholar] [CrossRef] [Green Version]
  50. Zhang, Y.; Liu, T.; Meyer, C.A.; Eeckhoute, J.; Johnson, D.S.; Bernstein, B.E.; Nusbaum, C.; Myers, R.M.; Brown, M.; Li, W.; et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 2008, 9, R137. [Google Scholar] [CrossRef] [Green Version]
  51. Machanick, P.; Bailey, T.L. MEME-ChIP: Motif analysis of large DNA, datasets. Bioinformatics 2011, 27, 1696–1697. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Heinz, S.; Benner, C.; Spann, N.; Bertolino, E.; Lin, Y.C.; Laslo, P.; Cheng, J.X.; Murre, C.; Singh, H. Glass CKSimple combinations of lineage-determining transcription factors prime cis-regulatory elements required for mac-rophage and B cell identities. Mol. Cell 2010, 38, 576–589. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Li, W.; Lin, Y.; Li, Q.; Shi, R.; Lin, C.-Y.; Chen, H.; Chuang, L.; Qu, G.-Z.; Sederoff, R.R.; Chiang, V.L. A robust chromatin immunoprecipitation protocol for studying transcription factor–DNA interactions and histone modifications in wood-forming tissue. Nat. Protoc. 2014, 9, 2180–2193. [Google Scholar] [CrossRef] [PubMed]
  54. Wang, S.; Huang, H.; Han, R.; Liu, C.; Qiu, Z.; Liu, G.; Chen, S.; Jiang, J. Negative feedback loop between BpAP1 and BpPI/BpDEF heterodimer in Betula platyphylla x B. pendula. Plant Sci. 2019, 289, 110280. [Google Scholar] [CrossRef]
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Figure 1. Molecular detection and disease severity of PsnWRKY70 transgenic lines infected with A. alternata. (A) PCR amplification of PsnWRKY70 transgenic lines, DNA ladder DL2000 (lane M), positive control (pGWB5-PsnWRKY70-GFP plasmid) (lane 1), water control (lane 2), WT (lane 3), PsnWRKY70 OE lines (lane 4), positive control (pGWB5-amiRNAiPsnWRKY70-GFP plasmid) (lane 5), water control (lane 6), WT (lane 7), and PsnWRKY70 RE lines (lane 8). (B) qRT-PCR detection of PsnWRKY70 transgenic lines (n = 3, ** p < 0.01, *** p < 0.001, **** p < 0.0001). (C) Phenotype characterization of each transgenic line with inoculation of A. alternaria for 15 days. (D) Disease index of each transgenic line with inoculation of A. alternata after 15 days (n = 9, **** p < 0.0001).
Figure 1. Molecular detection and disease severity of PsnWRKY70 transgenic lines infected with A. alternata. (A) PCR amplification of PsnWRKY70 transgenic lines, DNA ladder DL2000 (lane M), positive control (pGWB5-PsnWRKY70-GFP plasmid) (lane 1), water control (lane 2), WT (lane 3), PsnWRKY70 OE lines (lane 4), positive control (pGWB5-amiRNAiPsnWRKY70-GFP plasmid) (lane 5), water control (lane 6), WT (lane 7), and PsnWRKY70 RE lines (lane 8). (B) qRT-PCR detection of PsnWRKY70 transgenic lines (n = 3, ** p < 0.01, *** p < 0.001, **** p < 0.0001). (C) Phenotype characterization of each transgenic line with inoculation of A. alternaria for 15 days. (D) Disease index of each transgenic line with inoculation of A. alternata after 15 days (n = 9, **** p < 0.0001).
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Figure 2. Transcriptome analysis of PsnWRKY70 transgenic lines infected with A. alternata. (A) Venn diagram of upregulated DEGs between OE and RE. (B) Venn diagram of downregulated DEGs between OE and RE. (C) GO enrichment analysis of uniquely upregulated genes in OE lines. (D) GO enrichment analysis of uniquely downregulated genes in OE lines. (E) GO enrichment analysis of uniquely upregulated genes in RE lines. (F) GO enrichment analysis of uniquely downregulated genes in RE lines.
Figure 2. Transcriptome analysis of PsnWRKY70 transgenic lines infected with A. alternata. (A) Venn diagram of upregulated DEGs between OE and RE. (B) Venn diagram of downregulated DEGs between OE and RE. (C) GO enrichment analysis of uniquely upregulated genes in OE lines. (D) GO enrichment analysis of uniquely downregulated genes in OE lines. (E) GO enrichment analysis of uniquely upregulated genes in RE lines. (F) GO enrichment analysis of uniquely downregulated genes in RE lines.
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Figure 3. KEGG enrichment analysis of differential genes in PsnWRKY70 transgenic poplar. (A) KEGG enrichment analysis of uniquely upregulated genes in OE lines. (B) KEGG enrichment analysis of uniquely downregulated genes in OE lines. (C) KEGG enrichment analysis of uniquely upregulated genes in RE lines. (D) KEGG enrichment analysis of uniquely downregulated genes in OE lines.
Figure 3. KEGG enrichment analysis of differential genes in PsnWRKY70 transgenic poplar. (A) KEGG enrichment analysis of uniquely upregulated genes in OE lines. (B) KEGG enrichment analysis of uniquely downregulated genes in OE lines. (C) KEGG enrichment analysis of uniquely upregulated genes in RE lines. (D) KEGG enrichment analysis of uniquely downregulated genes in OE lines.
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Figure 4. Expression of immune-related genes in PsnWRKY70 transgenic line. (A) KEGG enriched genes in the plant–pathogen interaction pathway. (B) GO enriched genes in the protein phosphorylation pathway.
Figure 4. Expression of immune-related genes in PsnWRKY70 transgenic line. (A) KEGG enriched genes in the plant–pathogen interaction pathway. (B) GO enriched genes in the protein phosphorylation pathway.
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Figure 5. Expression of SA-related genes in PsnWRKY70 transgenic poplar (n = 3, ** p < 0.01).
Figure 5. Expression of SA-related genes in PsnWRKY70 transgenic poplar (n = 3, ** p < 0.01).
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Figure 6. Expression of genome-wide identification of PsnWRKY70-binding sites. (A) Western blot detection of the expression of PsnWRKY70 fusion protein. (B) Genomic distribution of PsnWRKY70-binding peaks. (C) Distribution of PsnWRKY70-binding peaks relative to gene structure. (D) Motif analysis of the PsnWRKY70 peak revealed the W-box as the highest enriched motif.
Figure 6. Expression of genome-wide identification of PsnWRKY70-binding sites. (A) Western blot detection of the expression of PsnWRKY70 fusion protein. (B) Genomic distribution of PsnWRKY70-binding peaks. (C) Distribution of PsnWRKY70-binding peaks relative to gene structure. (D) Motif analysis of the PsnWRKY70 peak revealed the W-box as the highest enriched motif.
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Figure 7. Validation of downstream target genes of PsnWRKY70 gene. (A) Venn diagram of upregulated genes between RNA-seq and DAP-seq. (B) Venn diagram of downregulated genes between RNA-seq and DAP-seq. (C) CHIP-PCR for downstream genes of PsnWRKY70. (D) qRT-PCR of downstream genes of PsnWRKY70 (n = 3, * p < 0.05).
Figure 7. Validation of downstream target genes of PsnWRKY70 gene. (A) Venn diagram of upregulated genes between RNA-seq and DAP-seq. (B) Venn diagram of downregulated genes between RNA-seq and DAP-seq. (C) CHIP-PCR for downstream genes of PsnWRKY70. (D) qRT-PCR of downstream genes of PsnWRKY70 (n = 3, * p < 0.05).
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Figure 8. A proposed model of the PsnWRKY70-mediated regulatory network response to Alternaria infection in Populus. PsnWRKY70 indirectly activated PTI pathway genes, including MAP kinase cascades, calcium channel proteins, calcium-dependent protein kinases, and SA pathway-related genes. It directly binds to the promoters of homologous genes and induces the expression of PsnWRKY6, PsnWRKY18, PsnWRKY22, PsnWRKY22-1, and R genes in the ETI pathway. The gray represents that PsnWRKY70 indirectly regulates genes. The purple represents that PsnWRKY70 directly regulates genes.
Figure 8. A proposed model of the PsnWRKY70-mediated regulatory network response to Alternaria infection in Populus. PsnWRKY70 indirectly activated PTI pathway genes, including MAP kinase cascades, calcium channel proteins, calcium-dependent protein kinases, and SA pathway-related genes. It directly binds to the promoters of homologous genes and induces the expression of PsnWRKY6, PsnWRKY18, PsnWRKY22, PsnWRKY22-1, and R genes in the ETI pathway. The gray represents that PsnWRKY70 indirectly regulates genes. The purple represents that PsnWRKY70 directly regulates genes.
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Table
Table 1. Representative PsnWRKY70 DTGs were identified by RNA-seq and DAP-seq analysis.
Table 1. Representative PsnWRKY70 DTGs were identified by RNA-seq and DAP-seq analysis.
GeneDescriptionFold Changep-ValuePeak
Potri.004G007500.1WRKY 61.10510.0192Chr04-461048-1
Potri.014G195100.7LRR_81.38310.0453Chr14-17455217-2
Potri.019G122500.2LRR_RLK1.59680.0015Chr19-14761541-1
Potri.014G035700.1ADR1-like 21.31150.0008Chr14-2249744-1
Potri.011G043300.1CBP60-C1.75180.0050Chr11-3380308-1
Potri.006G263600.1WRKY181.45730.0089Chr06-25984884-1
Potri.002G164400.4WRKY221.12190.0045 Chr02-12589328-2
Potri.T001933.3NB-ARC 1.44440.0281scaffold_45-136830-2
Potri.014G090300.1.WRKY22-11.07720.0047Chr14-5869875-1
Potri.003G133400.1LEA_21.25160.0002Chr03-15146326-1
Potri.019G097300.1LRR3.15360.0385Chr19-13468226-1
Potri.013G010700.2SARD11.46777.7484 × 10−6Chr13-680718-1
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Wang, W.; Bai, X.-D.; Chen, K.; Gu, C.-R.; Yu, Q.-B.; Jiang, J.; Liu, G.-F. Role of PsnWRKY70 in Regulatory Network Response to Infection with Alternaria alternata (Fr.) Keissl in Populus. Int. J. Mol. Sci. 2022, 23, 7537. https://doi.org/10.3390/ijms23147537

AMA Style

Wang W, Bai X-D, Chen K, Gu C-R, Yu Q-B, Jiang J, Liu G-F. Role of PsnWRKY70 in Regulatory Network Response to Infection with Alternaria alternata (Fr.) Keissl in Populus. International Journal of Molecular Sciences. 2022; 23(14):7537. https://doi.org/10.3390/ijms23147537

Chicago/Turabian Style

Wang, Wei, Xiang-Dong Bai, Kun Chen, Chen-Rui Gu, Qi-Bin Yu, Jing Jiang, and Gui-Feng Liu. 2022. "Role of PsnWRKY70 in Regulatory Network Response to Infection with Alternaria alternata (Fr.) Keissl in Populus" International Journal of Molecular Sciences 23, no. 14: 7537. https://doi.org/10.3390/ijms23147537

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