DOI: 10.5061/dryad.crjdfn3f8
title: Data for: Walnut PR10/Bet v1-like proteins interact with chitinase in response to anthracnose stress

description: Walnut is a significant woody oil tree species that has been increasingly
 affected by anthracnose in recent years. Effective anthracnose control is
 crucial for walnut yield and quality, which requires a comprehensive
 understanding of the response mechanisms to Colletotrichum
 gloeosporioides. The PR10/Bet v1-like proteins are involved in defense
 against various diseases, therefore, in this study, 7 JrBet v1s
 were identified from the walnut transcriptome (named JrBet v1-1~1-7),
 whose open reading frame (ORF) was 414~483 bp in length with isoelectric
 point ranging from 4.96 to 6.11. These JrBet v1s were classified into
 three groups, with the MLP/RRP and Dicot PR-10 subfamilies each comprising
 three members (the largest ones), indicating that the proteins within
 these two subfamilies may have evolved from a shared ancestral gene within
 the broader PR10/Bet v1 protein family. The cis-elements in the promoters
 of JrBet v1s were involved in response to hormones, coercive, and plant
 growth metabolism. Most JrBet v1s could be significantly upregulated by
 walnut anthracnose, JrBet v1-1, JrBet v1-2, JrBet v1-4, and JrBet v1-6
 peaked at 12 days of anthracnose stress, showing a 2.85- to 63.12-fold
 increase compared to the control, while JrBet v1-3, JrBet v1-5 and JrBet
 v1-7 peaked at 9 days, with a 3.23- to 27.67-fold increase. Furthermore,
 the significant correlation of the upregulation under anthracnose stress
 of JrBet v1s and JrChit02-1 as well as JrChit02-2, the genes encoding
 chitinase, suggesting that during the long process of microevolution in
 walnut-C. gloeosporioides interactions, walnut has developed a Bet
 v1-chitinase defense mechanism to counteract pathogen invasion.
description: <strong>1 plant materials and
 treatments</strong> Two-year-old ‘Xiangling’
 walnut grafted seedlings were potted and used as materials (the growth
 temperature was 22±2℃, relative humidity was 70±5%, light cycle 14 h
 light/10 h dark). The <em>C. gloeosporioides</em> was isolated
 by the Laboratory of Walnut Research Center in Northwest A&F
 University, and cultivated to the conidia concentration of
 10<sup>5</sup>~10<sup>6</sup> cells/mL. Then spray
 the <em>C. gloeosporioides</em> spore re-suspension on the
 leaves for treatment after slight friction. The leaves were harvested
 after being treated with 1, 3, 6, 9, 12, and 15 days, and saved in a -80℃
 refrigerator for further RNA isolation. Each treatment contained 6
 plants. <strong>2 Identification, collinearity,
 and structure analysis of <em>JrBet
 v1s</em></strong> “Pathogenesis-related
 protein Bet v1” was used to search for walnut <em>Bet v1</em>
 family genes (<em>JrBet v1s</em>) in walnut transcriptome. The
 ORF Finder (https://www.ncbi.nlm.nih.gov/orffinder/) was used to find the open reading frame (ORF) of <em>JrBet v1s</em>. Basic biological information, including amino acid number, theoretical isoelectric point (pI), and molecular weight were predicted by ExPASy (https://web.expasy.org/protparam/). The sub-cellular location of <em>JrBet v1s</em> was predicted using the WoLF PSORT tool (http:∥wolfpsort.seq.cbrc.jp/). The BLASTP was applied to the double-direction alignment of the walnut genome and obtained all the collinear sequences. The TBtools (program: MCScan X) was used to visualize <em>Bet v1 </em>collinear genes in the walnut genome (Chen et al., 2020), and TBtools was utilized to calculate the synonymous (Ks) and non-synonymous (Ka) nucleotide substitution rates between all <em>JrBet v1s</em> gene pairs. The online software Gene Structure Display Server2.0 (GSDS 2.0: http://gsds.gao-lab.org/) (Hu et al., 2015) was applied to construct the gene structure map. <strong>3 The <em>cis</em>-elements analysis of the <em>JrBet v1s</em> promoter</strong> The 2,000 bp upstream promoter sequences for each JrBet v1 gene were extracted from the walnut genome. Potential <em>cis</em>-elements within these promoters were identified using the PlantCARE database (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/). The identified elements were then screened and organized using Excel, and subsequently visualized using TBtools (Chen et al., 2020) for further analysis. <strong>4 Conserved domain, multiple sequence alignment, and evolutionary analysis</strong> CD-Search (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi) was used to analyze the conserved domains of the JrBet v1 protein. Multi-sequence alignment was applied using ESPript3.0（https://espript.ibcp.fr/ESPript /cgi-bin/ESPript.cgi）. MEME online tools (http://alternate.meme-suite.org/) were adopted to uncover the conservative motifs. The setting parameters were as follows: the number of motifs was 10 and the motif width was 6 to 50. The PRANK software (http://wasabiapp.org/software/prank/#About_PRANK_alignments) was used for sequence alignment and phylogenetic tree construction. The WAG model (Whelan and Goldman, 2001) was applied for protein alignments. MAFFT (Katoh et al., 2005) was employed to generate a preliminary alignment and infer the relationships tree based on evolutionary distances, with optimization scores derived from maximum likelihood inference. And iTOL v6 (https://itol.embl.de/) was used for visualization. <strong>5 Interaction protein prediction and protein structure analysis</strong> The interaction network of the JrBet v1 protein was analyzed using the STRING protein interaction database (http://string-db.org/). The three-dimensional structure and interaction sites of the JrBet v1 protein, particularly those associated with potential disease responses, were predicted using the AlphaFold Server (https://golgi.sandbox.google.com/), and the predicted results were visualized using PyMOL. <strong>6 RNA extraction, reverse transcription, and expression analysis</strong> The total RNA of each sample was isolated using the CTAB (cetyltriethyl ammonium bromide) method (Yang et al., 2018). Then the RNA was digested with RNase-free DNase I (Fermentas, Germany) for quality evaluation by agarose gel electrophoresis and ultra-micro UV spectrophotometer (Thermo, USA). The RNA was reversely transcribed into cDNA using PrimeScript™ RT reagent Kit (CWBIO, Beijing, China). The cDNA was diluted 10-fold by sterile water and used as the template of qRT-PCR. The 20 μL reaction system for qRT-PCR includes 10 μL SYBR Green Real-time PCR Master Mix (CWBIO), 2 μL cDNA, 1.0 μL forward primer and 1.0 μL reverse primer. The reaction program was 94°C for 30 s; 94°C for 12 s, 60°C for 45 s, 72°C for 45 s, 44 cycles; 81°C for 1 s. 18S rRNA was used as an internal reference gene (Xu et al., 2012). The primers are shown in Table S1, the quantitative results were calculated based on the threshold cycle using the 2<sup>−ΔΔCT</sup> method (Livak et al., 2001). The expression was related to the internal reference gene and 0 d. Data analysis was performed using SPSS (SPSS, Chicago, USA). <strong>7 Yeast two-hybrid assay</strong> To determine whether JrBet v1 proteins interact with chitinase 2-like proteins JrChit02-1 and JrChit02-2, the yeast two-hybrid (Y2H) assay was employed. <em>JrChit02-1</em> and <em>JrChit02-2</em> were cloned into the pGBKT7 vector (denoted as BD) to create bait recombinants BD-JrChit02-1 and BD-JrChit02-2. Independently, <em>JrBet v1s</em> (<em>JrBet v1-1</em>, <em>JrBet v1-2</em>, <em>JrBet v1-3</em>, <em>JrBet v1-4</em>) were inserted into the pGADT7_Rec vector (denoted as AD) to generate prey recombinants AD-JrBet v1s. Additionally, JrChit02-1 and JrChit02-2 were cloned into pGADT7_Rec to form AD-JrChit02-1 and AD-JrChit02-2, while each JrBet v1 gene was independently cloned into pGBKT7 to create BD-JrBet v1s. The interactions between BD-JrChit02-1, BD-JrChit02-2, and AD-JrBet v1s, as well as between AD-JrChit02-1, AD-JrChit02-2, and each BD-JrBet v1, were then tested using Y2H assays on SD/-Ade/-His/-Leu/-Trp/X-α-Gal/Aureobasidin A (QDO/X/A) medium plates. Empty AD and BD vectors served as negative controls. The specific primers used in this study are listed in Table S2. <strong>8 Statistical analysis</strong> All the data were organized and analyzed using Excel 2023 and SPSS (Chicago, Illinois, USA). The sample variability was described by standard deviation (S.D.) from three repeated assays. <strong>References</strong> Chen C, Chen H, Zhang Y, Thomas HR, Frank MH, He Y, Xia R. TBtools: an integrative toolkit developed for interactive analyses of big biological data. Molecular plant. 2020, 13(8): 1194-1202. doi: 10.1016/j.molp.2020.06.009. Hu B, Jin J, Guo AY, Zhang H, Luo J, Gao G. GSDS 2.0: an upgraded gene feature visualization server. Bioinformatics. 2015, 31(8): 1296-1297. doi: 10.1093/bioinformatics/btu817. Katoh K, Kuma KI, Toh H, Miyata T. MAFFT version 5: improvement in accuracy of multiple sequence alignment. Nucleic acids research. 2005, 33(2): 511-518. doi: 10.1093/nar/gki198. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001, 25(4): 402-408. doi: 10.1006/meth.2001.1262. Whelan S, Goldman N. A general empirical model of protein evolution derived from multiple protein families using a maximum-likelihood approach. Molecular biology and evolution. 2001, 18(5): 691-699. doi: 10.1093/oxfordjournals.molbev.a003851. Xu F, Deng G, Cheng S, Zhang W, Huang X, Li l, Cheng H, Rong X, Li J. Molecular cloning, characterization and expression of the phenylalanine ammonia-lyase gene from <em>Juglans regia</em>. Molecules. 2012, 17(7): 7810-7823. doi: 10.3390/molecules17077810. Yang G, Gao X, Ma K, Gao X, Su L, Peng S, Zhai M. The walnut transcription factor JrGRAS2 contributes to high temperature stress tolerance involving in Dof transcriptional regulation and HSP protein expression. BMC Plant Biol. 2018, 18(1): 367. doi:10.1186/s12870-018-1568-y.
description: # Data for: Walnut PR10/Bet v1-like proteins interact with chitinase in
 response to anthracnose stress \[Access this dataset on Dryad](DOI:
 10.5061/dryad.crjdfn3f8) We have submitted the original datasets
 corresponding to all figures and tables presented in the manuscript.
 Specifically, the folders for Figures 1, 2, 3, 4, 5, S1, S2, S3, S4, and
 S5 contain the raw data used in the creation of these figures. Similarly,
 the folder for Table 1 includes the raw data utilized in the generation of
 Table 1. ## Description of the data and file structure ### **Figure 1**
 #### The folder Figure 1 contains the following raw data: * 7 walnut
 PR10-Bet v1 genes full length sequences.txt * 7 walnut PR10-Bet v1 genes
 ORF sequences.txt * 7 walnut PR10-Bet v1 genes full length sequence.txt
 #### The methods of Figure 1 The Gene Structure Display Server 2.0 (GSDS
 2.0; [http://gsds.gao-lab.org/](http://gsds.gao-lab.org/)) was utilized to
 construct the gene structure map (Hu et al., 2015). The open reading
 frames (ORFs) and full-length sequences of the Walnut PR10/Bet v1-like
 genes, as analyzed by this software, are provided in the Figure 1 folder
 (**7 walnut PR10-Bet v1 genes full-length sequences.txt**, **7 walnut
 PR10-Bet v1 genes ORF sequences.txt**). The MEME online tools
 ([http://alternate.meme-suite.org/](http://alternate.meme-suite.org/))
 were adopted to uncover the conservative motifs. The setting parameters
 were as follows: the number of motifs was 10 and the motif width was 6 to
 50. The protein sequences of the Walnut PR10/Bet v1-like proteins are
 provided in the Figure 1 folder (**7 walnut PR10-Bet v1 proteins
 sequences.txt**). ### **Figure 2** #### The folder Figure 2 contains the
 following raw data: * Phylogenetic tree of plant Bet v1 homologs (Figure
 2) containing protein sequences.txt #### The methods of Figure 2 The PRANK
 software
 ([http://wasabiapp.org/software/prank/#About_PRANK_alignments](http://wasabiapp.org/software/prank/#About_PRANK_alignments)) was used for sequence alignment and phylogenetic tree construction. The WAG model (Whelan and Goldman, 2001) was applied for protein alignments. MAFFT (Katoh et al., 2005) was employed to generate a preliminary alignment and infer the relationships tree based on evolutionary distances, with optimization scores derived from maximum likelihood inference. And iTOL v6 ([https://itol.embl.de/](https://itol.embl.de/)) was used for visualization. All protein sequences used to construct the phylogenetic tree are provided in the Figure 2 folder (**Phylogenetic tree of plant Bet v1 homologs (Figure 2) containing protein sequences.txt**). ### **Figure 3** #### The folder Figure 3 contains the following raw data: * JrBet v1s’ Promoters sequences.txt #### The methods of Figure 3 Potential cis-elements within these promoters were identified using the PlantCARE database ([http://bioinformatics.psb.ugent.be/webtools/plantcare/html/](http://bioinformatics.psb.ugent.be/webtools/plantcare/html/)). The identified elements were then screened and organized using Excel, and subsequently visualized using TBtools (Chen et al., 2020) for further analysis. The 2,000 bp upstream promoter sequences (**JrBet v1s’ Promoters sequences.txt**) for each JrBet v1 gene were provided in the Figure 3 folder. ### **Figure 4** #### The folder Figure 4 contains the following raw data: * 7 PR10-Bet v1 proteins sequences.txt #### The methods of Figure 4 The interaction network of the JrBet v1 protein was analyzed using the STRING protein interaction database ([http://string-db.org/](http://string-db.org/)). The three-dimensional structure and interaction sites of the JrBet v1 protein, particularly those associated with potential disease responses, were predicted using the AlphaFold Server ([https://golgi.sandbox.google.com/](https://golgi.sandbox.google.com/)), and the predicted results were visualized using PyMOL. To determine whether JrBet v1 proteins interact with chitinase 2-like proteins JrChit02-1 and JrChit02-2, the yeast two-hybrid (Y2H) assay was employed. JrChit02-1 and JrChit02-2 were cloned into the pGBKT7 vector (denoted as BD) to create bait recombinants BD-JrChit02-1 and BD-JrChit02-2. Independently, JrBet v1s (JrBet v1-1, JrBet v1-2, JrBet v1-3, JrBet v1-4) were inserted into the pGADT7_Rec vector (denoted as AD) to generate prey recombinants AD-JrBet v1s. Additionally, JrChit02-1 and JrChit02-2 were cloned into pGADT7_Rec to form AD-JrChit02-1 and AD-JrChit02-2, while each JrBet v1 gene was independently cloned into pGBKT7 to create BD-JrBet v1s. The interactions between BD-JrChit02-1, BD-JrChit02-2, and AD-JrBet v1s, as well as between AD-JrChit02-1, AD-JrChit02-2, and each BD-JrBet v1, were then tested using Y2H assays on SD/-Ade/-His/-Leu/-Trp/X-α-Gal/Aureobasidin A (QDO/X/A) medium plates. Empty AD and BD vectors served as negative controls. The specific primers used in this study are listed in Table S2. ### **Figure 5** #### The folder Figure 5 contains the following raw data: * Raw data of relative expression levels of JrChit02-1, JrChit02-2, and JrBet v1s.csv #### The methods of Figure 5 The total RNA of each sample was isolated using the CTAB (cetyltriethyl ammonium bromide) method (Yang et al., 2018). Then the RNA was digested with RNase-free DNase I (Fermentas, Germany) for quality evaluation by agarose gel electrophoresis and ultra-micro UV spectrophotometer (Thermo, USA). The RNA was reversely transcribed into cDNA using PrimeScript™ RT reagent Kit (CWBIO, Beijing, China). The cDNA was diluted 10-fold by sterile water and used as the template of qRT-PCR. The 20 μL reaction system for qRT-PCR includes 10 μL SYBR Green Real-time PCR Master Mix (CWBIO), 2 μL cDNA, 1.0 μL forward primer and 1.0 μL reverse primer. The reaction program was 94°C for 30 s; 94°C for 12 s, 60°C for 45 s, 72°C for 45 s, 44 cycles; 81°C for 1 s. 18S rRNA was used as an internal reference gene (Xu et al., 2012). The primers are shown in Table S1, the quantitative results were calculated based on the threshold cycle using the 2−ΔΔCT method (Livak et al., 2001). The expression was related to the internal reference gene and 0 d. Data analysis was performed using SPSS (SPSS, Chicago, USA). The Correlation analysis of the relative expression levels of JrChit02-1, JrChit02-2, and JrBet v1s was conducted by TBtools. ### **Figure S1** #### The folder Figure S1 contains the following raw data: * Walnut chromosome length.txt * GCF_001411555.2_Walnut_2.0_genomic.fastaGCF_001411555.2_Walnut_2.0_genomic.fasta.gff #### The methods of Figure S1 The BLASTP was applied to the double-direction alignment of the walnut genome and obtained all the collinear sequences. The TBtools (program: MCScan X) was used to visualize Bet v1 collinear genes in the walnut genome (Chen et al., 2020), and TBtools was utilized to calculate the synonymous (Ks) and non-synonymous (Ka) nucleotide substitution rates between all JrBet v1s gene pairs. ### **Figure S2** #### The folder Figure S2 contains the following raw data: * 7 Walnut PR10-Bet v1 proteins sequences.txt #### The methods of Figure S2 The Multi-sequence alignment was applied using ESPript3.0（[https://espript.ibcp.fr/ESPript](https://espript.ibcp.fr/ESPript) /cgi-bin/ESPript.cgi). ### **Figure S3** #### The folder Figure S3 contains the following raw data: * 7 Walnut PR10-Bet v1 proteins sequences.txt #### The methods of Figure S3 The three-dimensional structure and interaction sites of the JrBet v1 protein, particularly those associated with potential disease responses, were predicted using the AlphaFold Server ([https://golgi.sandbox.google.com/](https://golgi.sandbox.google.com/)), and the predicted results were visualized using PyMOL. ### **Figure S4** #### The folder Figure S4 contains the following raw data: * 436 Bet v 1 allergen domain-containing protein sequences #### The methods of Figure S4 The PRANK software ([http://wasabiapp.org/software/prank/#About_PRANK_alignments](http://wasabiapp.org/software/prank/#About_PRANK_alignments)) was used for sequence alignment and phylogenetic tree construction. The WAG model (Whelan and Goldman, 2001) was applied for protein alignments. MAFFT (Katoh et al., 2005) was employed to generate a preliminary alignment and infer the relationships tree based on evolutionary distances, with optimization scores derived from maximum likelihood inference. And iTOL v6 ([https://itol.embl.de/](https://itol.embl.de/)) was used for visualization. ### **Figure S5** #### The folder Figure S5 contains the following raw data: * 7 Walnut PR10-Bet v1 proteins sequences.txt #### The methods of Figure S5 The interaction network of the JrBet v1 protein was analyzed using the STRING protein interaction database ([http://string-db.org/](http://string-db.org/)). The three-dimensional structure and interaction sites of the JrBet v1 protein, particularly those associated with potential disease responses, were predicted using the AlphaFold Server ([https://golgi.sandbox.google.com/](https://golgi.sandbox.google.com/)), and the predicted results were visualized using PyMOL. ### **Table 1** #### The folder Table 1 contains the following raw data: * 7 walnut PR10-Bet v1 genes ORF sequences.txt * 7 walnut PR10-Bet v1 proteins sequences.txt * GCF_001411555.2_Walnut_2.0_genomic.fastaGCF_001411555.2_Walnut_2.0_genomic.fasta.gff * walnut transcriptome unigene.blast.cds.txt #### The methods of Table 1 “Pathogenesis-related protein Bet v1” was used to search for walnut Bet v1 family genes (JrBet v1s) in walnut transcriptome. The ORF Finder ([https://www.ncbi.nlm.nih.gov/orffinder/](https://www.ncbi.nlm.nih.gov/orffinder/)) was used to find the open reading frame (ORF) of JrBet v1s. Basic biological information, including amino acid number, theoretical isoelectric point (pI), and molecular weight were predicted by ExPASy ([https://web.expasy.org/protparam/](https://web.expasy.org/protparam/)). The sub-cellular location of JrBet v1s was predicted using the WoLF PSORT tool (http:∥wolfpsort.seq.cbrc.jp/). ## Key Information Sources Walnut 2.0 genome data were derived from [[https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001411555.2/](https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001411555.2/)] ## Code/Software No custom scripts, code, or notebooks were used in this study. All analyses were conducted using available software and online tools.