The WRKY transcription factors in the diploid woodland strawberry Fragaria vesca: Identification and expression analysis under biotic and abiotic stresses

Plant Physiology and Biochemistry 105 (2016) 129e144

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Research article

The WRKY transcription factors in the diploid woodland strawberry Fragaria vesca: Identification and expression analysis under biotic and abiotic stresses Wei Wei a, b, Yang Hu a, Yong-Tao Han a, Kai Zhang a, b, Feng-Li Zhao a, Jia-Yue Feng a, b, * a b

State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F University, Yangling 712100, Shaanxi, China Key Laboratory of Protected Horticulture Engineering in Northwest China, Ministry of Agriculture, Yangling 712100, Shaanxi, China

a r t i c l e i n f o

a b s t r a c t

Article history: Received 14 January 2016 Received in revised form 2 April 2016 Accepted 8 April 2016 Available online 11 April 2016

WRKY proteins comprise a large family of transcription factors that play important roles in response to biotic and abiotic stresses and in plant growth and development. To date, little is known about the WRKY gene family in strawberry. In this study, we identified 62 WRKY genes (FvWRKYs) in the wild diploid woodland strawberry (Fragaria vesca, 2n ¼ 2x ¼ 14) accession Heilongjiang-3. According to the phylogenetic analysis and structural features, these identified strawberry FvWRKY genes were classified into three main groups. In addition, eight FvWRKY-GFP fusion proteins showed distinct subcellular localizations in Arabidopsis mesophyll protoplasts. Furthermore, we examined the expression of the 62 FvWRKY genes in ‘Heilongjiang-3’ under various conditions, including biotic stress (Podosphaera aphanis), abiotic stresses (drought, salt, cold, and heat), and hormone treatments (abscisic acid, ethephon, methyl jasmonate, and salicylic acid). The expression levels of 33 FvWRKY genes were upregulated, while 12 FvWRKY genes were downregulated during powdery mildew infection. FvWRKY genes responded to drought and salt treatment to a greater extent than to temperature stress. Expression profiles derived from quantitative real-time PCR suggested that 11 FvWRKY genes responded dramatically to various stimuli at the transcriptional level, indicating versatile roles in responses to biotic and abiotic stresses. Interaction networks revealed that the crucial pathways controlled by WRKY proteins may be involved in the differential response to biotic stress. Taken together, the present work may provide the basis for future studies of the genetic modification of WRKY genes for pathogen resistance and stress tolerance in strawberry. © 2016 Elsevier Masson SAS. All rights reserved.

Keywords: Strawberry (Fragaria vesca) WRKY transcription factors Expression profiles Powdery mildew Abiotic stresses Subcellular localization

1. Introduction The strawberry (Fragaria  ananassa Duch.), which has high economical and nutritional value, is one of the most important fruit crops worldwide. However, strawberry production is limited by a range of biotic and abiotic stresses that cause significant losses in

Abbreviations: ABA, Abscisic acid; CDD, Conserved Domain Database; ETH, Ethephon; GFP, Green fluorescent protein; HMM, Hidden Markov Model; hpi, hours post-inoculation; hpt, hours post-treatment; MeJA, Methyl jasmonate; NCBI, National Center for Biotechnology Information; PM, Powdery mildew; qRT-PCR, quantitative real-time polymerase chain reaction; RT-PCR, Reverse-transcription polymerase chain reaction; SA, Salicylic acid; TFs, Transcription factors. * Corresponding author. State Key Laboratory of Crop Stress Biology for Arid Areas, College of Horticulture, Northwest A&F University, Yangling 712100, Shaanxi, China. E-mail address: [email protected] (J.-Y. Feng). http://dx.doi.org/10.1016/j.plaphy.2016.04.014 0981-9428/© 2016 Elsevier Masson SAS. All rights reserved.

yield every year, as well as a reduction in berry quality (Nezhadahmadi et al., 2015; Kirnak et al., 2001). To adapt to the recurrent biotic and abiotic challenges, plants must regulate gene expression, and transcription factors (TFs) are commonly considered to play a crucial role in this process (Jang et al., 2010). Among the numerous transcription factors, WRKY transcription factors function as important regulatory molecules; they belong to a large gene family that is specific to the green lineage, including green algae and land plants (Zhang and Wang, 2005). The most prominent characteristic of the WRKY gene family is the presence of either one or two highly conserved domains consisting of approximately 60 amino acid residues with a highly conserved sequence, WRKYGQK, at the N-terminus (Eulgem et al., 2000). An additional feature is a metal chelating zinc-finger motif (C-X4e5-C-X22e23-HX-H or C-X5e8-C-X25e28-H-X1e2-C) at the C-terminus of the WRKY motif (Zhang and Wang, 2005; Eulgem et al., 2000). WRKY proteins

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bind to the W-box ((C/T) TGAC (T/C)) of their target genes (Ciolkowski et al., 2008) as well as SURE (sugar responsive), which plays a role in promoting transcription (Sun et al., 2003). The first WRKY gene was cloned from sweet potato (Ipomoea batatas) (SPF1) by Ishiguro in 1994 (Ishiguro and Nakamura, 1994). Subsequently, a large number of WRKY genes have been identified in Arabidopsis thaliana (Eulgem et al., 2000), rice (Oryza sativa) (Wu et al., 2005), barley (Hordeum vulgare) (Mangelsen et al., 2008), poplar (Populus trichocarpa) (He et al., 2012), and grape (Vitis vinifera L.) (Guo et al., 2014). Based on the number of WRKY domains and the pattern of the zinc-finger motifs, WRKY genes can be divided into three groups (I, II and III) (Eulgem et al., 2000). Group I members are characterized by two WRKY domains containing a C2H2 zinc-finger motif. Group II have only one WRKY domain and a C2H2 zinc-finger motif and can be further divided into five subgroups (IIa, IIb, IIc, IId and IIe, respectively). Group III members also have a single WRKY domain, but their zinc-finger motif is C2HC (Eulgem et al., 2000). WRKY TFs played an important role in plant defense responses to pathogens (Birkenbihl and Somssich, 2011). For example, Arabidopsis WRKY46 coordinates with WRKY70 and WRKY53 to positively regulate basal resistance to Pseudomonas syringae (Hu et al., 2012). AtWRKY33 expression is induced rapidly by pathogens and by endogenous signaling molecules that play a role in defense (Lippok et al., 2007). Overexpression of VvWRKY1 in grapevines can increase the resistance of grapevine against the downy mildew pathogen through transcriptional reprogramming that leads to activation of the jasmonic acid signaling pathway (Marchive et al., 2013). Additionally, overexpression of VvWRKY2 can lead to improved protection against a broad range of necrotrophic fungal pathogens in tobacco (Mzid et al., 2007). WRKY genes also play a vital role in the regulation of abiotic stresses. For example, over-expression of either AtWRKY25 or AtWRKY33 increases salt tolerance in Arabidopsis (Jiang and Deyholos, 2009). Additional studies of AtWRKY25 using both null mutants and over-expression lines showed that it is also involved in the response to heat stress (Li et al., 2009). In addition to biotic and abiotic stress responses, WRKY TFs are also involved in various plant developmental and physiological processes (Rabara et al., 2013; Besseau et al., 2012). Sequencing of the woodland strawberry (Fragaria vesca, 2n ¼ 2X ¼ 14) genome has been completed. The genome is small (~240 Mb) (Darwish et al., 2015; Shulaev et al., 2011), providing an opportunity for genome-wide mining of WRKY transcription factors. Although a previous investigation of WRKY genes in Fragaria ananassa demonstrated that FaWRKY1 plays a positive regulatory role in pathogen resistance (Encinas-Villarejo et al., 2009), little is known about the WRKY gene family in strawberry (Fragaria vesca). In the present study, we performed a genome-wide search for WRKYs in the diploid woodland strawberry (Fragaria vesca) accession Heilongjiang-3 and revealed that the strawberry WRKY gene family (FvWRKY) contained a total of 62 members. To explore the functions of FvWRKYs in response to biotic and abiotic stress responses, the expression profiles of FvWRKY genes were examined following powdery mildew infection, abiotic stresses (drought, salt, cold, and heat), and hormone treatments (abscisic acid, ethephon, methyl jasmonate, and salicylic acid). Additionally, a series of bioinformatics analyses provided insights regarding structure and function, and evolution and function. We also determined the subcellular localization of eight FvWRKYs members that were transiently expressed in Arabidopsis mesophyll protoplasts. Taken together, the present findings may provide the basis for further studies to dissect the functions of strawberry WRKY genes in response to biotic and abiotic stresses.

2. Materials and methods 2.1. Identification of WRKY genes in strawberry To identify WRKY genes in strawberry, we downloaded the Hidden Markov Model (HMM) profile of the WRKY DNA-binding domain (PF03106) from the Pfam protein family database (http:// pfam.xfam.org/). Next, we performed a BLAST-P search of the National Center for Biotechnology Information (NCBI) database (Fragaria vesca Annotation Release 101) using the HMM profiles as queries with default parameters. All putative WRKY genes were manually verified using the Conserved Domain Database at NCBI (CDD, http://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi/) and the Pfam database (http://pfam.xfam.org/search/) to confirm their completeness and the presence of WRKY domains. Among those alternative splice variants, we selected the longest variant for further analysis (Zhang et al., 2015). Sequences of Arabidopsis and grape WRKY genes were downloaded from the Arabidopsis Information Resource (TAIR, https://www.arabidopsis.org/) (Li et al., 2015) and Grape Genome Database (http://www.genoscope.cns. fr/externe/GenomeBrowser/Vitis/) (Guo et al., 2014), respectively. The theoretical isoelectric point (pI) and molecular weight (Mw) were predicted using the Compute pI/Mw tool available at the ExPASy server (http://web.expasy.org/compute_pi/). 2.2. Bioinformatics analysis of WRKY genes in strawberry Chromosomal localization data were retrieved from annotations downloaded from NCBI Map Viewer (http://www.ncbi.nlm.nih.gov/ mapview/). Genes were mapped to the chromosomes using MapDraw. The identified strawberry WRKY genes were annotated based on their respective chromosome distribution (Ling et al., 2011). Multiple sequence alignments of WRKY proteins and domains were performed separately using ClustalX 2.0.12 (Larkin et al., 2007), and the alignment results were manually modified using GeneDoc. The full-length amino acid sequences of WRKY proteins from strawberry (FvWRKY), A. thaliana (AtWRKY), and grape (Vitis vinifera L.) (VvWRKY) were used to construct a phylogenetic tree in MEGA 5.0 (Tamura et al., 2011) using the neighbor-joining method with the following parameters: p-distance model, pairwise deletion, and bootstrap test replicated 1000 times. Based on the multiple sequence alignment and the previously reported classification of AtWRKY genes, the FvWRKY genes were assigned to different groups and subgroups. The conserved motifs of the FvWRKY genes were obtained from the online Multiple Expectation Maximization for Motif Elicitation (MEME) (http://meme-suite.org/tools/meme). The parameters employed in the analysis were as follows: minimum motif width, 6; maximum motif width, 100; and maximum number of motifs, 22. A specific interaction network with experimental evidence for each WRKY family member was constructed using STRING 10 (http://string-db.org/) with an option value >0.800, which identified 14 high confidence interactive proteins in Arabidopsis. The homologs of these interactive proteins in strawberry were then identified by phylogenetic tree analysis. 2.3. Plant materials, growth conditions and stress treatments Strawberry organs/tissues (roots, stems, runners, leaves, floral buds, flowers, and fruits) were obtained from the greenhousegrown wild diploid strawberry F. vesca accession Heilongjiang-3, which was grown at 22  C with 70% relative humidity and no supplemental light in plastic pots (diameter: 14 cm, height: 10 cm) in the strawberry germplasm resource greenhouse of Northwest A&F University, Yangling, Shaanxi, China (34 200 N 108 240 E). Sixmonth-old strawberry seedlings with the tenth leaf fully expanded

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were selected for treatment. Plants of A. thaliana ecotype Col0 were grown at 22  C with 75% relative humidity under shortday (8 h light at 125 mmol m2 s1, 16 h dark) conditions for 4e5 weeks before transformation. The wild diploid strawberry F. vesca accession Heilongjiang-3 was exposed to powdery mildew (Podosphaera aphanis) stress by inoculation according to the method described by Hu et al. (Hu et al., 2015). Inoculated leaves were collected at 0, 24, 48, 72, 96, 120, 144, and 168 h post-inoculation (hpi), and uninfected leaves served as a negative control. The inoculations were repeated three times. Drought stress treatment was performed by withholding water followed by sampling at 0, 24, 48, 72, 96, 120, and 144 h posttreatment (hpt). The plants were watered again after 144 h of drought stress and sampled again 24 h later. Strawberry seedlings grown without drought stress were used as a control. Salt stress was simulated by irrigating potted strawberry plants with 300 mM NaCl. Another set of control ‘Heilongjiang-3’ seedlings was similarly treated with distilled water. The cold and heat stress treatments was performed by transferring the plants to a 4  C/42  C chamber for 48 h. Another set of potted ‘Heilongjiang-3’ seedlings was maintained in the control temperature range of 22  Ce27  C. Hormone treatments were performed by spraying the strawberry leaves with a solution containing 0.1 mM abscisic acid (ABA), 1 mM salicylic acid (SA), 0.1 mM methyl jasmonate (MeJA), or 0.5 g/L ethephon (ETH), while another set of control ‘Heilongjiang-3’ seedlings were similarly sprayed with distilled water. The leaves of all of the above plants treated with salt, cold, heat, and hormone stresses were then collected at 0, 0.5, 2, 4, 8, 12, 24, and 48 hpt. All experiments were performed independently in triplicate. After collection, the samples were immediately frozen in liquid nitrogen and stored at 80  C until further analysis.

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40 cycles at 95  C for 30 s and 58  C for 30 s. After amplification, the samples were maintained at 50  C for 1 min, and the temperature was gradually increased by 0.5  C every 10 s to perform the meltcurve analysis. The relative gene expression was determined using an interspacer 26S-18S strawberry RNA gene as an endogenous control gene (Hu et al., 2015; Feng et al., 2013; Raab et al., 2006). Each relative expression level was analyzed with IQ5 software using the Normalized Expression method. The primers used for quantitative real-time PCR are listed in Table S1. 2.6. Subcellular localization of WRKY genes in strawberry To gain more insight into the function of FvWRKYs, we designed gene-specific primers to isolate the putative WRKY genes from the diploid woodland strawberry accession Heilongjiang-3. The predicted full-length coding sequences of FvWRKY genes were amplified from ‘Heilongjiang-3’ cDNA using high-fidelity Taq HSmediated PCR. The amplified PCR products were digested with XbaI and KpnI and fused in-frame with GFP in the XbaI and KpnI site of the pBI221 vector containing the CaMV 35S promoter (Clontech, Beijing, China), resulting in pFvWRKY-GFP plasmids. The primers used to clone the genes and construct the vectors are listed in Table S1. For subcellular localization analysis, transient expression of Arabidopsis mesophyll protoplasts was performed as previously described (Yoo et al., 2007) with some modifications. After transformation, the Arabidopsis mesophyll protoplasts were maintained in the dark at room temperature for 16e18 h before examination by fluorescence microscopy. Fluorescence was observed using an Olympus BX-51 inverted fluorescence microscope (Olympus, Japan). The image data were processed using Adobe Photoshop (Mountain View, CA, USA). All transient expression assays were repeated at least three times.

2.4. Semi-quantitative reverse-transcription PCR analysis 2.7. Statistical analysis Total RNA was isolated from treated leaves or tissue samples using an EZNA Plant RNA Kit (R6827-01, Omega Bio-tek, USA). Firststrand cDNA was synthesized by reverse transcription of 1.5 mg total RNA using PrimeScript RTase (TaKaRa Biotechnology, Dalian, China). The cDNA concentration was adjusted using PCR and an interspacer 26S-18S strawberry RNA gene (housekeeping gene) with primers Fv18S-F (50 -ACCGTTGATTCGCACAATTGGTCATCG-30 ) and Fv18S-R (50 -TACTGCGGGTCGGCAATCGGACG-30 ) (Hu et al., 2015; Feng et al., 2013; Raab et al., 2006). Gene-specific primers for each FvWRKY gene were designed using VECTOR NTI (Table S1). The following semi-quantitative reverse-transcription (RT) PCR program was used: 95  C for 3 min, 30e34 cycles of 95  C for 30 s, 55  C for 30 s and 72  C for 30 s, and a final step at 72  C for 5 min. The PCR products were separated in a 1.0% (w/v) agarose gel, stained with ethidium bromide, and imaged under UV light for further gene expression analysis. Each reaction was performed in triplicate, with three independent analyses for each treatment showing the same trends for each gene. The expression profiles obtained by semi-quantitative RT-PCR were collated, analyzed, and visualized using the AlphaView SA and MeV 4.8.1 programs. 2.5. Quantitative real-time PCR (qRT-PCR) analysis Quantitative real-time PCR was conducted using SYBR green (TaKaRa Biotechnology) on an IQ5 real time-PCR machine (Bio-Rad, Hercules, CA, USA) with a final volume of 21 ml per reaction. Each reaction mixture consisted of 10.5 ml SYBR Premix Ex Taq II (TaKaRa Biotechnology), 1.0 ml cDNA template, 1.0 ml of each primer (1.0 mM), and 7.5 ml sterile distilled H2O. Each reaction was performed in triplicate. The cycling parameters were 95  C for 30 s, followed by

Statistical significance was assessed using a paired Student's ttest (http://www.physics.csbsju.edu/stats/). Mean values ± standard deviations of the mean (SD) of at least three replicates are presented, and significant differences relative to controls are indicated at p < 0.05 and p < 0.01. 3. Results 3.1. Identification of WRKY genes in the strawberry (F. vesca) genome We identified WRKY genes by searching the Pfam database and obtained the HMM profile of the WRKY DNA-binding domain (PF03106). Next, we used BLAST-P to search the public NCBI database (Fragaria vesca Annotation Release 101) using WRKY HMM profiles (Darwish et al., 2015). Subsequently, we identified a total of 81 candidate genes (data not shown). The sequences of the 81 candidates were submitted to the NCBI online program CDD and Pfam databases to confirm their WRKY domains. Based on the presence of apparently complete WRKY domains, four candidate genes (XM_011467748.1, XM_004302081.2, XM_011466257.1, and XM_004301258.2) were discarded due to the absence of a complete predicted WRKY domain. Among the alternative splice variants, we selected the longest variant for further analysis (Zhang et al., 2015). Finally, a total of 62 non-redundant strawberry WRKY genes were identified in the diploid woodland strawberry and annotated as FvWRKY1 to FvWRKY61 according to their position from the top to the bottom of strawberry chromosomes 1e7. In particular, XM_004310052.2 was located in an unknown region and thus was

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renamed FvWRKY62 (Table 1). The deduced FvWRKY proteins contain amino acid numbers from 155 to 1475. More detailed information about each FvWRKY gene, including the WRKY gene accession numbers, gene location, length of the coding sequences, and characteristics of the FvWRKY proteins are shown in Table 1. A total of 61 FvWRKY genes are distributed throughout all seven F. vesca chromosomes (Fig. 1). Of these, chromosome 6 has the most

FvWRKY genes (19) and chromosome 4 has the fewest (3). Further investigation revealed that the distribution of each group of WRKY genes was significantly irregular. According to a previous description, a chromosome region containing two or more genes within 200 kb can be defined as a gene cluster (Holub, 2001). In strawberry, 16 WRKY genes were grouped into five clusters (Fig. 1). Among the five clusters, two were found on chromosome 7, while

Table 1 Characteristics of strawberry WRKY genes. Name

Accession no.

Length (bp)

No. of aa

Mw (kDa)

pI

Chr.

Location

Group

FvWRKY1 FvWRKY2 FvWRKY3 FvWRKY4 FvWRKY5 FvWRKY6 FvWRKY7 FvWRKY8 FvWRKY9 FvWRKY10 FvWRKY11 FvWRKY12 FvWRKY13 FvWRKY14 FvWRKY15 FvWRKY16 FvWRKY17 FvWRKY18 FvWRKY19 FvWRKY20 FvWRKY21 FvWRKY22 FvWRKY23 FvWRKY24 FvWRKY25 FvWRKY26 FvWRKY27 FvWRKY28 FvWRKY29 FvWRKY30 FvWRKY31 FvWRKY32 FvWRKY33 FvWRKY34 FvWRKY35 FvWRKY36 FvWRKY37 FvWRKY38 FvWRKY39 FvWRKY40 FvWRKY41 FvWRKY42 FvWRKY43 FvWRKY44 FvWRKY45 FvWRKY46 FvWRKY47 FvWRKY48 FvWRKY49 FvWRKY50 FvWRKY51 FvWRKY52 FvWRKY53 FvWRKY54 FvWRKY55 FvWRKY56 FvWRKY57 FvWRKY58 FvWRKY59 FvWRKY60 FvWRKY61 FvWRKY62

XM_004287081.2 XM_011465135.1 XM_004287958.2 XM_004288081.2 XM_011468891.1 XM_004288494.2 XM_004288505.2 XM_011459675.1 XM_004291028.2 XM_004291213.2 XM_011461309.1 XM_004291907.2 XM_004293264.2 XM_004293406.2 XM_004293620.2 XM_004293637.2 XM_004295538.2 XM_004294360.2 XM_004294412.2 XM_004294710.2 XM_004294821.2 XM_004295013.2 XM_004297210.2 XM_004297221.2 XM_004298395.2 XM_011465623.1 XM_004298842.2 XM_004299344.2 XM_004299750.2 XM_004299918.2 XM_004300397.2 XM_004302014.2 XM_004304728.2 XM_004304767.2 XM_004302300.2 XM_004305022.1 XM_004305027.2 XM_004305029.1 XM_004305030.1 XM_004302544.2 XM_004305031.2 XM_004302509.2 XM_004302718.2 XM_004302784.2 XM_004305403.2 XM_004303194.2 XM_004303439.2 XM_004303826.2 XM_004304219.2 XM_004304482.2 XM_004306641.2 XM_004306682.2 XM_011472186.1 XM_011470907.1 XM_004308940.2 XM_004307690.2 XM_004308942.2 XM_004307693.2 XM_004307962.2 XM_004307993.2 XM_011472124.1 XM_004310052.2

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51.00 64.56 34.71 27.81 46.70 35.38 22.97 38.91 36.11 37.06 42.30 36.81 61.54 55.37 39.18 53.62 30.43 59.56 62.38 68.68 79.16 41.49 37.77 54.77 67.73 35.23 40.09 72.81 32.90 62.78 32.38 35.77 167.12 84.07 53.10 35.76 33.54 31.94 25.96 38.76 38.22 57.46 33.31 52.19 29.90 36.08 17.78 41.62 56.65 23.55 39.26 25.33 37.72 28.69 42.42 37.93 162.66 152.82 40.96 46.34 151.67 21.67

6.68 5.20 9.61 9.08 6.79 6.66 6.15 9.71 9.54 9.51 6.27 8.89 7.15 6.40 7.00 5.92 5.19 6.22 6.73 7.68 5.87 5.67 7.23 7.69 6.67 5.14 4.96 6.95 9.97 5.15 4.92 9.58 6.10 5.77 7.56 5.39 7.17 4.96 9.32 5.41 5.64 7.63 5.44 9.14 5.12 8.80 5.13 6.46 8.57 8.76 5.23 9.16 8.50 7.76 6.63 6.43 6.13 6.25 6.64 5.12 6.81 9.45

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870919..874229 10045673..10048222 10577850..10579374 11770138..11773994 16629836..16633210 20465509..20467726 20708900..20711644 5696899..5699900 20833008..20836027 22347375..22349507 33088502..33091155 33093532..33095374 635027..637933 1716020..1719529 4533799..4536252 4856445..4859544 7633622..7635218 15053416..15056443 15885293..15890393 20956047..20959174 22341618..22346373 25007887..25010163 17481528..17484817 17623403..17626444 18215850..18219380 1863533..1865479 2523342..2525716 8486170..8489600 14058553..14060307 16764396..16767244 24702940..24704404 642733..645019 1187349..1193974 1832751..1837559 4272821..4275209 6515030..6516185 6539328..6542693 6550918..6556156 6561995..6563274 6567849..6569763 6575081..6577760 7059890..7062489 8879460..8882223 10015991..10020299 16131681..16137526 16823225..16825479 21039097..21040162 26896885..26900342 31544425..31547916 36309105..36311468 3840757..3843405 4326075..4327864 4348088..4349716 7738940..7741851 19102161..19104605 19104994..19107275 19118281..19127913 19127913..19134566 21782499..21784846 22089165..22090972 23082749..23089750 1339517..1342239

I IIb IId IIc IIb IIc IIc IId IId IId IIa IIa IIb I IIc IIe IIe IIb I I I IIc IIc I IIb IIe III IIb IId IIb IIe IId III I IIb III III III III III III I IIc I IIe IIa IIc IIc I IIc III IIc IIe IIc III III III III III IIe III IIc

Abbreviations: Chr, chromosome numbers; Mw, molecular weight; pI, isoelectric point; Un, unknown chromosome.

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Fig. 1. Chromosomal distributions of FvWRKY genes. Chromosome numbers are provided at the top of each chromosome together with the approximate size. The names on the right side of each chromosome correspond to the approximate location of each WRKY gene. Group I members are indicated in blue font; group II members are indicated in black font; group III members are indicated in red font. The green lines on the left side of the names of the WRKY genes indicate the gene clusters on each chromosome. Unmapped WRKY genes (FvWRKY62) are not shown. The scale is in megabases (Mb). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

only one cluster was located on each of chromosomes 2, 4, and 6. No cluster was identified on chromosomes 1, 3, or 5. Notably, we observed two high-density genes distribution regions in the chromosomes, one of which comprised six WRKY genes (FvWRKY36, 37, 38, 39, 40, and 41) in a region of only 62.73 kb on chromosome 6 and another comprised four WRKY genes (FvWRKY55, 56, 57, and 58) in a region of only 32.41 kb on chromosome 7. 3.2. Bioinformatics analysis of FvWRKY genes The WRKY domain is approximately 60 amino acid residues in length and is considered to be a crucial element for the interaction with the W-box (C/T)TGAC(T/C) to activate many stress-related genes (Eulgem et al., 2000). A multiple sequence alignment of the core WRKY domain, spanning approximately 60 amino acids of all 62 FvWRKY proteins, is shown in Fig. S1. In our study, a total of 57 FvWRKY proteins contained the highly conserved sequence WRKYGQK, while WRKYGKK, the most common variant in the WRKY family, was only shared by two genes in the WRKY family in strawberry. Other atypical sequences, such as WIKYGDK, WTKYDQR, and RRGSYKR, were identified in FvWRKY57, 33, and 38, respectively (Fig. S1, Table S2). Another important characteristic of the WRKY protein is the metal-chelating zinc-finger motif (CX4e5-X22e23-H-X-H or C-X7-C-X23-H-X-C) (Eulgem et al., 2000), which was identified in all strawberry WRKY proteins (Fig. S1, Table S2). To further analyze the evolutionary relationships between the FvWRKY genes and the other plant WRKY gene family, a total of 193 WRKY genes, comprising 72 genes from Arabidopsis, 59 from grape, and 62 from strawberry, were used to construct a phylogenetic tree. As shown in Fig. 2 and Fig. S1, all 62 FvWRKY genes were classified mainly into three groups (I, II, and III), with five subgroups in group II (IIa, IIb, IIc, IId, and IIe). Ten strawberry WRKY genes were assigned to group I, in which the proteins contained two WRKY domains, an N-terminal WRKY domain (NTWD) and a C-terminal WRKY domain (CTWD). The NTWD zinc-finger motif is C-X4-CX22-HXH expect for FvWRKY34; the CTWD zinc-finger motif is C-

X4-CX23-HXH. Thirty-seven strawberry WRKY genes possessing a single WRKY domain were assigned to group II, in which the C2H2 pattern zinc-finger motif is C-X4-5-C-X23-HXH. Group II was further divided into five subgroups consisting of groups IIa, IIb, IIc, IId, and IIe with 3, 8, 13, 6, and 7 members, respectively. Rather than the C2H2 pattern, group III contained a single WRKY domain with a C2HC zinc-finger motif (C-X7-C-X23-HXC) for FvWRKY33 and fifteen FvWRKY genes assigned to group III. Additionally, the phylogenetic relationship and classification of strawberry WRKYs were further supported by a conserved motif analysis. As shown in Fig. 3, a total of 22 conserved motifs were identified in FvWRKYs. The conserved motifs 1 and 2 were characterized as WRKY domains and were present in all WRKY family members except FvWRKY38, which contained only motif 2. In group I members, motif 3 was characterized as NTWD and was only present in this group. In group III, most of the FvWRKY proteins contained four to five motifs. Notably, four proteins (FvWRKY33, 57, 58, and 61) contained 13 to 15 motifs, and a search of the Pfam database showed that these proteins contained an additional TIR domain and NB-ARC domain or LRR (leucine-rich repeat). These proteins belong to the TIReNBSeLRReWRKY proteins and have also been observed in Arabidopsis (Rushton et al., 2010). In group II, motifs 11 and 13 commonly exist in groups IIa and IIb, two close subgroups in the phylogenetic tree; motif 21 is only present in group IId; group IIc only contains motifs 1, 2 and 4, excluding FvWRKY15 and 43. Overall, most of the WRKY proteins in a group have similar motif compositions. 3.3. Subcellular localization of FvWRKYs To further confirm the subcellular localization of putative FvWRKY proteins, the coding-sequences of eight FvWRKY genes were fused in-frame with GFP under the control of the CaMV 35S promoter (Fig. 4A). The fusion constructs and positive control were transiently transformed into Arabidopsis mesophyll protoplasts. As shown in Fig. 4B, the GFP signals expressed from the control construct were dispersed throughout the whole Arabidopsis

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Fig. 2. Phylogenetic analysis of strawberry WRKY genes. The full-length amino acid sequences of WRKY genes from strawberry (Fv, red), Arabidopsis (At, blue) and grape (Vv, black) were aligned using ClustalX, and the phylogenetic tree was constructed using the neighbor-joining method with 1000 bootstrap replicates with MEGA 5.0. The branches of the subtrees are colored to indicate the different WRKY subgroups. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

mesophyll protoplasts, whereas the GFP signals from eight FvWRKY-GFP fusion proteins (FvWRKY9-GFP, FvWRKY22-GFP, FvWRKY27-GFP, FvWRKY41-GFP, FvWRKY42-GFP, FvWRKY51-GFP, FvWRKY59-GFP, and FvWRKY62-GFP) were clearly observed in the nucleus. To confirm the nuclear localization of the FvWRKYs, we also examined the subcellular localization of FvHsfA1b, a strawberry heat shock transcription factor that has been localized in the nucleus of Arabidopsis mesophyll protoplasts (Hu et al., 2015). FvWRKYs and FvHsfA1b exhibited similar subcellular distributions (Fig. 4B). Additionally, the FvWRKY59-GFP signal as observed as small fluorescent spots resembling mitochondria (Fig. 4B).

expressed at high levels in floral buds. Further analysis revealed that eight genes (FvWRKY1, 7, 23, 27, 32, 42, 46, and 58) were downregulated from green fruits to red fruits, while FvWRKY12 was upregulated from green fruits to red fruits, suggesting that these genes play a different role in strawberry fruit development. In addition, 22 FvWRKY gene transcripts could not be detected in the flowers of ‘Heilongjiang-3’, while 8 FvWRKY genes showed very low transcription levels in all ‘Heilongjiang-3’ tissues. The organspecific FvWRKY expression patterns suggested that FvWRKYs could play vital biological roles in strawberry growth and developmental processes.

3.4. Expression profiles of FvWRKY genes in different strawberry tissues

3.5. Expression profiles of FvWRKY genes in response to biotic stress

Many WRKY proteins have been shown to be involved in plant developmental processes (Brown and Hudson, 2015; Ross et al., 2007). To preliminarily understand the roles of WRKYs in F. vesca development processes, we analyzed the expression of FvWRKYs under normal growth conditions in different tissues, including roots, stems, runners, leaves, floral buds, flowers, and fruits, of the diploid woodland strawberry accession Heilongjiang-3. As shown in Fig. S2, the transcripts of eight FvWRKY genes (FvWRKY5, 12, 16, 21, 22, 29, 52, and 55) displayed a consistent distribution throughout all of the tested organs; three genes (FvWRKY28, 35, and 61) were expressed at high levels in roots; four genes (FvWRKY11, 38, 40, and 59) showed particularly high expression in young leaves; and two genes (FvWRKY15 and FvWRKY34) were

WRKY genes have been shown to play a crucial role in plant responses to biotic stresses. To gain insights into the potential roles of all 62 FvWRKY genes in biotic stress-associated gene expression, we inoculated ‘Heilongjiang-3’ strawberry with powdery mildew and performed semi-quantitative RT-PCR to evaluate the expression profiles of the 62 FvWRKY genes. The semi-quantitative RT-PCR data showed that thirty-three of the strawberry WRKY genes were upregulated in response to powdery mildew infection (Fig. 5A and Fig. S3). Of the 33 FvWRKYs, FvWRKY2, FvWRKY3, FvWRKY4, FvWRKY5 and FvWRKY20 were upregulated during early infection (24e72 hpi), while FvWRKY11, FvWRKY42 and FvWRKY56 were upregulated during a later stage (72e144 hpi), potentially implying a relationship between expression patterns and response times. By contrast, twelve WRKY genes were downregulated in response to

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Fig. 3. Phylogenetic tree of deduced FvWRKY domains associated with the motif compositions of the amino acid sequences. The unrooted phylogenetic tree was constructed using full-length protein sequences of 62 strawberry WRKY genes by the neighbor-joining method using 1000 bootstrap replicates. The numbers at the nodes indicate how often the group to the right appeared among the bootstrap replicates. Subtrees branch lines are colored to indicate the different WRKY subgroups. The motif composition related to each FvWRKY protein is displayed on the right-hand side. The motifs, numbered 1e22, are displayed in different colored boxes. The schematic diagram of FvWRKY motifs is shown on the right side. The sequence information for each motif is provided in Table S3.

powdery mildew inoculation. Based on the results of the semi-quantitative RT-PCR analysis of the pathogen inoculation and other stimuli (Fig. 5A; Fig. 6), six FvWRKY genes (FvWRKY27, FvWRKY41, FvWRKY42, FvWRKY50, FvWRKY56, and FvWRKY62) were selected using quantitative realtime PCR for further analysis and validation of their transcript abundance during powdery mildew inoculation (Fig. 5B). FvWRKY27, FvWRKY50 and FvWRKY62 were significantly upregulated (~5.0e6.0 fold) (P < 0.01) in the earlier stage (0e24 hpi). Of these, FvWRKY62 persisted at high levels at 24 hpi and reached the

highest transcription levels (26.2-fold) at 120 hpi. However, FvWRKY27 and FvWRKY50 returned to baseline or were downregulated at 24 hpi, and then peaked at 120 hpi (8.2-fold and 12.7fold, respectively). In contrast, FvWRKY41, FvWRKY42 and FvWRKY56 showed almost no response during the earlier stage (0e96 hpi); however, they were significantly up-regulated (P < 0.05) during the late stage (120 hpi or 144 hpi). For example, FvWRKY41 demonstrated a peak of ~3.0-fold at 144 hpi and then returned to a level below baseline. FvWRKY42 and FvWRKY56 were significantly upregulated at 120 hpi and peaked at 144 hpi (6.6-fold

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Fig. 4. Subcellular localization of eight strawberry WRKY genes. (A) The schematic illustration of vectors pBI221 and FvWRKYs. The selected WRKY genes were cloned from a diploid woodland strawberry (F. vesca) and used to construct CaMV35S::WRKYs-GFP vectors in which GFP was fused at the C terminus. 35S, a constitutive promoter from the cauliflower mosaic virus; GFP, green fluorescent protein. (B) The eight FvWRKY-GFP fusion proteins (FvWRKY9-GFP, FvWRKY22-GFP, FvWRKY27-GFP, FvWRKY41-GFP, FvWRKY42GFP, FvWRKY51-GFP, FvWRKY59-GFP and FvWRKY62-GFP), the FvHsfA1b-GFP marker protein, and GFP as the control were transiently expressed in col-0 Arabidopsis protoplasts and observed using a fluorescence microscope. The merged pictures were constructed using the green fluorescence channel (first panels) and the chloroplast autofluorescence channel (second panels). The corresponding bright field images are shown on the right. Bar ¼ 10 mm. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

and 4.4-fold, respectively) and then remained at high levels. These results demonstrated the potential involvement of FvWRKY genes in response to powdery mildew inoculation in the diploid woodland strawberry F. vesca accession Heilongjiang-3, supporting their vital roles in biotic stress regulatory networks.

3.6. Expression profiles of FvWRKY genes in response to abiotic stress WRKY genes also play critical roles in the adaptation of plants to various abiotic stresses. In this study, we used drought treatment, NaCl treatment, and incubation at low or high temperature (4  C or 42  C) to examine the responses of FvWRKYs to these abiotic stresses at the transcriptional level. As shown in Fig. 6A (see also Figs. S4eS7), most FvWRKY genes tended to be upregulated to a greater degree by drought and NaCl treatment. In contrast, FvWRKY genes tended to be downregulated to a greater degree by extreme temperatures than drought and NaCl treatment, potentially indicating a positive effect of osmotic stress and a negative effect of temperature stress on FvWRKY genes.

During drought treatment (Figs. 6A and 7), twenty-nine of the sixty-two WRKY genes were upregulated, and fifteen genes were downregulated. FvWRKY23 was highly upregulated, peaked at 3.9fold at 48 hpt, and then persisted at a high transcript abundance. Moreover, FvWRKY35 peaked at 4.0-fold at 96 hpt but then decreased to baseline during the remaining treatment time. FvWRKY56 was upregulated early, subsequently downregulated, and finally rapidly upregulated. The FvWRKY27, FvWRKY41, and FvWRKY42 transcripts were primarily upregulated during the middle or late stage of the drought treatments; of these, FvWRKY42, which strongly and rapidly responded to the drought treatment from 24 to 144 hpt and peaked at 29.3- fold at 120 hpt. The FvWRKY27, FvWRKY41, FvWRKY42, and FvWRKY56 transcripts rapidly decreased when the plants were rewatered, but FvWRKY23 and FvWRKY35 remained upregulated at this time point. After NaCl treatment (Figs. 6A and 7), thirty-one genes were upregulated, while ten genes showed the opposite pattern. FvWRKY27, the most rapidly responding gene, reached a peak of nearly 34.2-fold at 0.5 hpt and rapidly decreased to 2.3-fold at 2 hpt; subsequently, its transcript levels increased from 2.3-fold to

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Fig. 5. Expression of WRKY genes in the diploid woodland strawberry (F. vesca) during powdery mildew infection. Expression was measured by reverse transcription followed by real-time, quantitative PCR, and it is presented as the fold-change in response to the experimental treatments relative to the control samples and visualized as heat maps (A) and histograms (B). Fv18s served as an internal control. The experiments were repeated three times and provided consistent results. Mean values and SDs were obtained from three biological and three technical replicates. (A) The expression profile of the FvWRKY gene family in response to powdery mildew infection (original results shown in Fig. S3). The color scale represents relative expression levels, with red indicating increased transcript abundance and green indicating decreased transcript abundance. (B) Detailed expression levels of six FvWRKY genes that were significantly upregulated during powdery mildew infection. The data represent the mean value ± SD. * and ** represent statistically significant (p < 0.05) and highly significant (p < 0.01), respectively.

29.8-fold at 2 h to 48 hpt. FvWRKY50 and FvWRKY56 were also rapidly responding genes, and their transcript levels exhibited a continuous increase and peaked at ~24.0-fold at 48 hpt. FvWRKY41 was gradually downregulated to 0.3-fold from 0.5 to 8 hpt and then rapidly increased to ~1.8-fold, while FvWRKY34 was gradually upregulated only from 0.5 to 48 hpt. FvWRKY44 was only slightly upregulated at 24 hpt. These results might indicate the potential positive regulatory functions of FvWRKYs during plant responses to drought and NaCl treatments. We also measured the transcript levels of FvWRKY genes in response to extreme temperatures. For the 4  C treatments (Figs. 6A and 7), thirty-two of the sixty-two WRKY genes were downregulated, and only nine genes were upregulated. FvWRKY27 was rapidly upregulated, peaked at 9.8-fold at 2 hpt, and then declined to approximately baseline. In contrast, the FvWRKY41 and FvWRKY56 transcripts were primarily upregulated during the

middle or late stage. FvWRKY50 and FvWRKY62 were downregulated early but subsequent rapidly upregulated. In particular, FvWRKY62 displayed a rapid and sustained upregulation after 0.5 hpt, and it reached its highest transcription level (38.4-fold) at 48 hpt. FvWRKY24 was only slightly downregulated at 12 hpt and subsequently upregulated. For the 42  C treatments (Figs. 6A and 7), thirty-one genes were downregulated, and only eight genes were upregulated. Among the downregulated genes, FvWRKY27 was the most prominent and rapidly decreased to significantly low transcript levels at 0.5 hpt, maintaining very lower mRNA levels throughout the entire treatment period. These results supported a negative regulatory role of FvWRKY27. The transcript abundances of FvWRKY34 and FvWRKY50 were upregulated in response to the 42  C treatments. FvWRKY23 and FvWRKY42 were significantly downregulated (0.3- and 0.5-fold) at 0.5 and 4 hpt. FvWRKY24 showed no significant difference in response to the 42  C treatment.

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Fig. 6. Expression of WRKY genes in the diploid woodland strawberry (F. vesca) in response to different treatments. The expression profiles were generated by semiquantitative PCR and were visualized as heat maps. The color scale represents relative expression levels, with red denoting increased transcript abundance and green denoting decreased transcript abundance. (A) Expression profiles of FvWRKY genes in response to drought treatments, NaCl, 4  C, and 42  C treatments (original results shown in Figs. S4eS7). (B) Expression profiles of FvWRKY genes in response to four hormone treatments (abscisic acid (ABA), ethanol (ETH), methyl jasmonic acid (MeJA), and salicylic acid (SA)) (original results shown in Figs. S8eS11). The experiments were repeated three times with consistent results. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.7. Expression profiles of FvWRKY genes in response to hormone treatments Plant hormones such as salicylic acid (SA), methyl jasmonate (MeJA), ethylene (ETH) and abscisic acid (ABA) play important roles in the regulation of the developmental processes and signaling networks involved in plant responses to a wide range of biotic and abiotic stresses (Bari and Jones, 2009). In the present study, hormone treatments resulted in a wide variety of changes in the transcript levels of FvWRKY genes (Fig. 6B; Figs. S8, S9, S10 and S11). A total of 31 FvWRKY genes showed different degrees of upregulation in response to ABA treatment, while 12 were downregulated. Similarly, 38 FvWRKY genes were upregulated and 12 were downregulated following MeJA treatment. However, the expression profiles observed following ETH and SA treatments were distinct from those modulated by ABA and MeJA, and a substantially greater number of downregulated genes were observed: 34 genes were downregulated and 8 were upregulated by ETH, whereas 30 were downregulated and 15 were upregulated by SA. As shown in Fig. 8, quantitative real-time PCR analysis revealed that ABA treatment rapidly (0.5 hpt) upregulated FvWRKY27, which peaked at 5.6-fold, while the FvWRKY35, FvWRKY44, and FvWRKY50 transcript levels continuously increased. In addition, FvWRKY23

and FvWRKY56 showed two counter trends in response to ABA treatment. During ETH treatment, the FvWRKY27, FvWRKY34, FvWRKY35, FvWRKY42, FvWRKY50, and FvWRKY62 transcripts were rapidly upregulated during the middle stage (2e12 hpt). In particular, the highest transcript levels of FvWRKY42, FvWRKY50 and FvWRKY62 reached ~20.0- to 80.0-fold. Treatment with MeJA also caused a rapid and significant increase in the transcript levels of FvWRKY27, FvWRKY42, FvWRKY50, and FvWRKY62 (~5- to 143fold) during the middle stage (2e24 hpt). For the SA treatment, FvWRKY27, FvWRKY41, FvWRKY50, and FvWRKY56 displayed a strong response during the middle stage and, coincidentally, peaked at 4 hpt. The transcript levels of FvWRKY23 fluctuated around the control value, while FvWRKY24 gradually rose in response to SA treatment. It is worth noting that FvWRKY27, FvWRKY35, and FvWRKY50 were distinctly involved in the response to at least three of the hormone treatments. 3.8. Protein-protein interaction (PPI) network analysis To identify the protein interactions, we constructed the networks of WRKYs using STRING 10 software with an option value >0.8, which identifies 10 high confidence interactive proteins involved in the WRKY family networks in Arabidopsis. These WRKY

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Fig. 7. Expression of WRKY genes in the diploid woodland strawberry (F. vesca) in response to drought, NaCl, 4  C, and 42  C treatments. Detailed expression levels of six FvWRKY genes revealed unusual expression patterns in response to drought, NaCl, 4  C, and 42  C treatments. The results were normalized to Fv18s. The experiments were repeated three times and provided consistent results. The mean values and SDs were obtained from three biological and three technical replicates. The asterisks indicate that the corresponding gene was significantly up or downregulated in response to treatment, as determined by the Student's t-test (*P < 0.05, **P < 0.01).

partners mainly include VQ proteins (MKS1, SIB1, and SIB2) that are involved in the regulation of plant defense response, MPK3 and MPK4 involved in plant responses to pathogens and stress conditions, STZ involved in abiotic stress responses, and other proteins (Table S4). The FvWRKY42 protein, which exhibited a high

homology to Arabidopsis WRKY33, had stronger interactions (thicker lines) with most plant defense proteins (MPK3, MPK4, MKS1, SIB1, SIB2, and STZ). The FvWRKY46 protein, which displayed a high homology with Arabidopsis WRKY40, was involved in stronger interactions with WRKY gene family members (Fig. 9).

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Fig. 8. Expression of WRKY genes in the diploid woodland strawberry (F. vesca) in response to treatment with plant hormones. Detailed expression levels of six FvWRKY genes revealed unusual expression patterns in response to ABA, ETH, MeJA, and SA treatments. The results were normalized to Fv18s. The experiments were repeated three times and provided consistent results. The mean values and SDs were obtained from three biological and three technical replicates. The asterisks indicate that the corresponding gene was significantly up or downregulated in response to treatment, as determined by the Student's t-test (*P < 0.05, **P < 0.01).

4. Discussion As a family of transcription factors, the WRKY gene family appears to be involved in regulatory processes mediated by various biotic and abiotic stresses (Eulgem et al., 2000; Encinas-Villarejo

et al., 2009; Ding et al., 2015). The complex features and functions of this family have been studied extensively in the model herbaceous plants, Arabidopsis and rice, and in the woody poplar plant (Eulgem et al., 2000; He et al., 2012; Ryu et al., 2006). The identification of WRKY genes in the diploid woodland strawberry

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Fig. 9. Interaction network analysis of WRKY genes identified in strawberry and related genes in Arabidopsis. The line thickness is related to the combined score. The homologous genes in strawberry are shown in red font in parentheses. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

(F. vesca) would facilitate a broader understanding of this gene superfamily. In the present study, we identified a total of 62 WRKY genes in the diploid woodland strawberry, together with an analysis of their evolutionary relationships, conserved motif compositions, subcellular localization, protein interactions, and expression pattern diversity with respect to biotic or abiotic stresses and hormone treatments. Current information suggests that WRKY genes play a key role in regulating the pathogen-induced defense program, biotic or abiotic stresses and also seem to be involved in other physiological processes such as hormone signaling (Ding et al., 2015; Agarwal et al., 2011). A phylogenetic tree combining gene families from different species will not only facilitate our understanding of the phylogenetic relationships among the members, but also allow speculation regarding the putative functions of the proteins based on the functional clades identified (Jiang et al., 2014). The expression profiles generated in this study (Figs. 5A and 6) revealed different expression patterns for each FvWRKY gene in response to specific treatments, thus providing a useful resource for future gene expression and functional analyses. A previous expression analysis of AtWRKY genes demonstrated that nearly 70% are differentially expressed in response to pathogen infection or SA treatment (Dong et al., 2003). Consistently, our data revealed changes in gene expression in more than 80% of the 62 FvWRKY genes in response to various abiotic and biotic stress treatments (Figs. 5A and 6), suggesting that WRKY genes play important roles in the environmental adaptation of strawberry. WRKY genes that are components of plant biotic stress regulatory networks display a complex response pattern. For example, AtWRKY33 (At2g38470) can positively modulate defense-related

gene expression and improve disease resistance, whereas some negative regulatory elements may prevent the overexpression of AtWRKY33 and are detrimental to plant growth (Lippok et al., 2007). The orthologous genes, FvWRKY42 and FvWRKY20, displayed high expression levels after infection with strawberry powdery mildew (Figs. 2 and 5), suggesting that they may play a role similar to AtWRKY33 in pathogen resistance. Additionally, AtWRKY33 has been reported to localize to the nucleus during transient expression in Arabidopsis epidermal cells (Lippok et al., 2007), consistent with our data showing that FvWRKY42 also localized to the nucleus (Fig. 4). These expression and location similarities suggest a functional consistency. Arabidopsis WRKY46 (At2g46400) is specifically induced by salicylic acid (SA) and biotrophic pathogen Pseudomonas syringae infection, whereas WRKY46 coordinates with WRKY70 (At3g56400) and WRKY53 (At4g23810) in the basal resistance to the pathogen P. syringae and play overlapping and synergetic roles in plant basal defense (Hu et al., 2012). FvWRKY56 and FvWRKY27 are phylogenetically close to AtWRKY46, AtWRKY53 and AtWRKY70 (Fig. 2). The expression patterns suggest that FvWRKY56 and FvWRKY27 responded to powdery mildew inoculation as well as hormone treatment (Figs. 5B and 8). These findings indicate that FvWRKY56 and FvWRKY27 might have similar functions to AtWRKY46, AtWRKY70 and AtWRKY53 in Arabidopsis. Recent studies have shown that AtWRKY75 is a transcriptional regulator of salicylic acid (SA)- and jasmonic acid/ethylene (JA/ETH)-dependent defense signaling pathways and is mainly active in the JA/ETH pathway in Arabidopsis defense against Sclerotinia sclerotiorum and oxalic acid stress (Chen et al., 2013). In addition, AtWRKY75 should also be a positive regulator in JA- or SA-mediated defense signaling responses to

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Pectobacterium carotovorum ssp. carotovorum (Pcc) (Choi et al., 2014). VvWRKY1 (named in Fig. 2, VvWRKY53), the ortholog of AtWRKY75 (Fig. 2), is involved in grapevine defense against fungal pathogens, and VvWRKY1 overexpression in tobacco resulted in reduced susceptibility to various fungi (Marchive et al., 2007). Additionally, VvWRKY1 can also increase grapevine resistance against downy mildew via transcriptional reprogramming that leads to activation of the jasmonic acid signaling pathway (Marchive et al., 2013). FvWRKY50 and FvWRKY62 are orthologs of AtWRKY75 and VvWRKY1; they were both significantly upregulated at 24 h post-inoculation and peaked at 120 hpi (Figs. 2 and 5), thus appearing to share a similar inoculation response to VvWRKY1, suggesting that FvWRKY50 and FvWRKY62 might play a role in eliciting a resistance response during an early stage of infection. Our data also showed that FvWRKY50 and FvWRKY62 responded positively to hormone treatments and abiotic stress (Figs. 6e8). These results indicate that FvWRKY50 and FvWRKY62 can regulate several different processes and may also mediate the crosstalk between different signaling pathways. WRKY genes play crucial roles in response to abiotic stresses. In Arabidopsis, AtWRKY70 and AtWRKY54 play an important role in osmotic stress signaling, and the wrky54wrky70 double mutants clearly exhibit enhanced tolerance to osmotic stress (Li et al., 2013). FvWRKY56, which is an ortholog of AtWRKY70 and AtWRKY54, was significantly induced by NaCl and drought treatments (Figs. 2 and 7). These results are consistent with the expression profile of AtWRKY70 and AtWRKY54 following PEG treatment (Li et al., 2013) and indicate that FvWRKY56 might also play an important role in mediating the plant osmotic stress response in strawberry. WRKY25, WRKY26, and WRKY33 positively regulate the cooperation between the ethylene-activated and heat shock protein-related signaling pathways that mediate responses to heat stress; and these three proteins interact functionally and play overlapping and synergetic roles in plant thermotolerance (Li et al., 2011). Additionally, AtWRKY25 and AtWRKY33 also regulate the adaptation of plants to salinity stress through an interaction with their upstream or downstream target genes (Jiang and Deyholos, 2009). Similarly, their orthologs, FvWRKY34 and FvWRKY42, were highly expressed in response to 42  C, NaCl and ETH treatment (Figs. 2 and 6e8). In particular, AtWRKY25 and AtWRKY33 localized to the nucleus (Jiang and Deyholos, 2009), consistent with our results showing FvWRKY42 localization to the nucleus (Fig. 4). These results indicate their potential roles in heat and salinity stress and that they most likely participate in the analogous pathways to those mentioned above for Arabidopsis (Li et al., 2011). Recent studies have shown that activated expression of AtWRKY53 inhibits stomatal closure by reducing H2O2 content and facilitates stomatal opening by promoting starch degradation (Sun and Yu, 2015). FvWRKY27, the ortholog of AtWRKY53, was strongly upregulated by drought and NaCl treatment (Figs. 2 and 7). These results are consistent with the expression profile of AtWRKY53 in response to dehydration and other osmotic stressors, including high salinity, PEG6000 and mannitol (Sun and Yu, 2015), and they suggest that FvWRKY27 has the same function in response drought tolerance by mediating stomatal movement with AtWRKY53. Investigations of the potential interaction network associated with a gene family are useful for a better understanding their functions (Tohge and Fernie, 2010). In Arabidopsis, one of most studied WRKY TFs in terms of protein interactions has been AtWRKY33, which has been reported to be important for plant defense responses (Chi et al., 2013). For example, Arabidopsis WRKY33 and the closely related WRKY25 interact with MKS1, a VQ motifecontaining protein substrate of Arabidopsis MPK4. Upon infection by the bacterial pathogen P. syringae or flagellin treatment, activated MPK4 phosphorylates MKS1 and releases

AtWRKY33. The released AtWRKY33 then targets the promoter of PAD3, which encodes a biosynthetic enzyme that catalyzes the production of camalexin (Qiu et al., 2008). Additionally, dualtargeted SIB1 and SIB2 function as activators of WRKY33 in plant defense against necrotrophic pathogens (Lai et al., 2011). In strawberry, FvWRKY42 displays a high homology to Arabidopsis WRKY33 and is significantly induced by powdery mildew infection (Figs. 5 and 9). These results imply that FvWRKY42 mediates crosstalk between different signaling pathways and plays a vitally important role in plant defense response regulatory networks. 5. Conclusion In this study, a total of 62 putative strawberry WRKY genes (FvWRKY) were identified in the diploid woodland strawberry (F. vesca) and renamed based on their respective chromosome distribution. Bioinformatics analysis indicated that the FvWRKY genes were classified into three main groups with similar motif compositions within the same groups and subgroups. The gene expression profiles obtained during powdery mildew infection, drought, salt, 4  C, 42  C, and phytohormone treatments suggested that 11 strawberry WRKY genes (FvWRKY23, 24, 27, 34, 35, 41, 42, 44, 50, 56, and 62) could play versatile roles in response to environmental stresses. Additionally, eight FvWRKY-GFP fusion proteins exhibited a distinct subcellular localization in Arabidopsis mesophyll protoplasts, which provided additional insights into their functions. The interaction networks of these orthologous genes revealed that the crucial pathways controlled by WRKY proteins might be involved in the differential response to biotic stress. Taken together, the present findings may lay the foundation for further studies to unravel the functions of strawberry WRKY genes in response to biotic and abiotic stresses. Conflicts of interest The authors declare that they have no conflicts of interests to disclose. Availability of supporting data Sequence data for the isolated FvWRKY genes in this article can be found in GenBank (http://www.ncbi.nlm.nih.gov/) under the accessions of KU207049 (FvWRKY9), KU207050 (FvWRKY22), KU207051 (FvWRKY27), KU207052 (FvWRKY41), KU207053 (FvWRKY42), KU207055 (FvWRKY51), KU207057 (FvWRKY59), and KU207058 (FvWRKY62). Author contributions JYF conceived and designed the experiments. WW, YH, YTH, and FLZ performed the experiments. WW, KZ and JYF analyzed the data. WW and JYF contributed to the writing of the manuscript. All authors read and approved the final manuscript. The authors thank Dr. Ke Duan of the Shanghai Academy of Agricultural Sciences for generously providing wild type Fragaria vesca plants. Acknowledgements The authors would like to thank the anonymous reviewers for their comments on the manuscript. This research was supported by the National Natural Science Foundation of China (Grant No. 31201657), the Fundamental Research Funds for the Central Universities (QN2013019, 2452015287), and the Shaanxi province science and technology research and development program (2014K02-02-02).

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