Analysis of TIR- and non-TIR-NBS-LRR disease resistance gene analogous in pepper: characterization, genetic variation, functional divergence and expression patterns
© Wan et al.; licensee BioMed Central Ltd. 2012
Received: 12 April 2012
Accepted: 12 September 2012
Published: 21 September 2012
Pepper (Capsicum annuum L.) is one of the most important vegetable crops worldwide. However, its yield and fruit quality can be severely threatened by several pathogens. The plant nucleotide-binding site (NBS)-leucine-rich repeat (LRR) gene family is the largest class of known disease resistance genes (R genes) effective against such pathogens. Therefore, the isolation and identification of such R gene homologues from pepper will provide a critical foundation for improving disease resistance breeding programs.
A total of 78 R gene analogues (CaRGAs) were identified in pepper by degenerate PCR amplification and database mining. Phylogenetic tree analysis of the deduced amino acid sequences for 51 of these CaRGAs with typically conserved motifs ( P-loop, kinase-2 and GLPL) along with some known R genes from Arabidopsis and tomato grouped these CaRGAs into the non-Toll interleukin-1 receptor (TIR)-NBS-LRR (CaRGAs I to IV) and TIR-NBS-LRR (CaRGAs V to VII) subfamilies. The presence of consensus motifs (i.e. P-loop, kinase-2 and hydrophobic domain) is typical of the non-TIR- and TIR-NBS-LRR gene subfamilies. This finding further supports the view that both subfamilies are widely distributed in dicot species. Functional divergence analysis provided strong statistical evidence of altered selective constraints during protein evolution between the two subfamilies. Thirteen critical amino acid sites involved in this divergence were also identified using DIVERGE version 2 software. Analyses of non-synonymous and synonymous substitutions per site showed that purifying selection can play a critical role in the evolutionary processes of non-TIR- and TIR-NBS-LRR RGAs in pepper. In addition, four specificity-determining positions were predicted to be responsible for functional specificity. qRT-PCR analysis showed that both salicylic and abscisic acids induce the expression of CaRGA genes, suggesting that they may primarily be involved in defence responses by activating signaling pathways.
The identified CaRGAs are a valuable resource for discovering R genes and developing RGA molecular markers for genetic map construction. They will also be useful for improving disease resistance in pepper. The findings of this study provide a better understanding of the evolutionary mechanisms that drive the functional diversification of non-TIR- and TIR-NBS-LRR R genes in pepper.
Plant disease resistance genes (R genes) are important components of the genetic resistance mechanism in plants [1, 2]. Over the past decade, several R genes conferring resistance to a wide spectrum of plant pathogens, including bacteria, fungi, oomycetes, viruses and nematodes, have been cloned from different plant species [2–5]. Sequence analyses revealed that these proteins share a high degree of homology and have a number of conserved motifs. These include a nucleotide-binding site (NBS), a leucine-rich repeat (LRR) region, a motif homologous to the cytoplasmic domains of the Drosophila Toll protein and the mammalian interleukin-1 receptor (TIR), a coiled-coil (CC) or leucine zipper structure, a transmembrane domain (TM) and a protein kinase domain . Although a wide range of pathogens are involved, these R genes encode a limited set of proteins that can be classified into several superfamilies, including NBS-LRR, a receptor-like kinase, LRR-TM and TM-CC [2, 7].
The NBS-LRR class of R genes can be divided into two subfamilies (TIR-NBS-LRR and non-TIR-NBS-LRR) based on the features of their N-terminal structure [2, 8]. These two subfamilies can also be distinguished (95% accuracy) by the last residue, D (Aspartate) or W (Tryptophan), of the conserved kinase-2 motif within the NBS domain . The former corresponds to the TIR-NBS-LRR subfamily, whereas the latter corresponds to the non-TIR-NBS-LRR subfamily of R genes. The ‘NBS’ and ‘LRR’ domains in the NBS-LRR R genes have different roles during host–pathogen recognition. The highly conserved NBS domains can bind and hydrolyze ATP or GTP , whereas the LRR motif is typically involved in protein–protein interactions and is responsible for recognition specificity [2, 11, 12].
To date, eight conserved motifs have been identified in the NBS domain of plant non-TIR- and TIR-NBS-LRR R genes, including P-loop, kinase-2, kinase-3a, GLPL, RNBS-A-TIR, RNBS-D-TIR, RNBS-A-non-TIR and RNBS-D-non-TIR . The first four conserved motifs are common in the TIR and non-TIR-NBS-LRR subfamilies. The RNBS-A-TIR and RNBS-D-TIR motifs are specific to the TIR-NBS-LRR subfamily. The remaining two motifs, RNBS-A-non-TIR and RNBS-D-non-TIR, belong to the non-TIR-NBS-LRR subfamily. These highly conserved motifs within the NBS domain occur across different plant species, making it possible to isolate R gene analogues (RGAs) from other crops using degenerate polymerase chain reaction (PCR) [13–19]. At present, more than 1600 NBS-LRR-type RGAs have been amplified via PCR from a wide range of plant species, and they have been arranged in clusters similar to R genes in plant genomes [5, 20]. Some of these are closely linked to known R gene loci or form a part of the R genes [21–23].
In recent years, the evolutionary patterns of NBS-LRR R genes have been investigated extensively in different plant species. For example, in annual species, such as Arabidopsis and rice, studies have shown that tandem and segmental gene duplication, gene conversion, unequal crossing-over, ectopic recombination and diversifying selection seem to be the primary evolutionary modes of NBS-LRR R genes [3, 24–27]. In woody perennial species (e.g. grapevine and poplar), tandem gene duplication and recombination play major roles in NBS-LRR R gene expansion . Point mutations, small insertions or deletions and gene loss have been proposed as the primary mechanisms by which NBS-LRR R genes evolve [29, 30]. Therefore, the evolution of plant NBS-LRR R genes appears to be a complex process.
Pepper (Capsicum annuum L.), a member of the botanical family Solanaceae, is an important vegetable crop worldwide. However, its production is affected because it is prone to many diseases. At present, three R genes conferring resistance to strains of Xanthomonas campestris pv. vesicatoria and root-knot nematodes have been identified from pepper [31–33]. Of them, two genes (Bs2 and CaMi) encode motifs characteristic of the NBS-LRR class of resistance genes. Moreover, some RGAs in pepper have been identified by modified amplified fragment length polymorphisms, NBS profiling and specific PCR amplification with primers designed from conserved regions of the NBS domain [34–37]. However, no detailed analysis of RGA characteristics is currently available. In this paper, we followed a PCR-based protocol using R gene-specific degenerate primers and data mining to identify and characterize the NBS-LRR CaRGAs and identify putative R genes in pepper. We also analyzed the genetic variations and phylogeny in pepper. Functional divergence analysis provided statistical evidence for altered selective constraints during protein evolution between the two subfamilies and identified some critical amino acid sites involved in this functional divergence. Analyses of non-synonymous (Ka) and synonymous (Ks) substitutions per site revealed a purifying selection in the evolutionary processes of non-TIR- and TIR-NBS-LRR CaRGAs in pepper. Several specificity-determining positions (SDPs) responsible for functional specificity were also predicted. Finally, the expression of representative CaRGAs was analysed in response to hormones and in different organs.
Results and discussion
Identification of non-TIR- and TIR-NBS-LRR CaRGAs in pepper
Candidate non-TIR- and TIR-NBS-LRR CaRGAs were identified in pepper using two approaches, PCR amplification with degenerate primers and database mining. Two pairs of degenerate primers, previously designed based on conserved domains (P-loop and GLPL regions) among known NBS-LRR R genes from other plant species [37–39], were used. Two bands of the predicted size (~500 bp) were amplified using the genomic DNA of pepper (Additional file 1). The bands were then excised from agarose gels and cloned. A total of fifty clones were randomly selected for sequencing, twenty-four of which were highly homologous to NBS-LRR sequences or known R genes from other plant species. These sequences were designated as NBS-LRR CaRGAs. The remaining clones were homologous to either a putative polyprotein or a hypothetical LRR protein. This finding suggests that degenerate PCR amplification is a very effective method for isolating potential CaRGAs from pepper.
A total of fifty-four CaRGAs were identified using the key word ‘Capsicum resistance gene’ in a search of the National Center for Biotechnology Information (NCBI) non-redundant protein database (http://www.ncbi.nlm.nih.gov/). A total of seventy-eight CaRGAs were obtained using these two methods. Among the seventy-eight CaRGAs, fifty-five had uninterrupted open reading frames (seventeen from amplified products, thirty-eight from data mining) and twenty-three CaRGAs had stop codons in the reading frames. These CaRGAs may be non-functional genes. Hence, they were excluded from further analysis. Moreover, two R genes reported previously were selected for further analysis [32, 33]. In addition, more than one hundred and seventy and four hundred NBS-LRR R genes from Arabidopsis and rice [3, 26], respectively, were used to retrieve potential R genes or CaRGAs from pepper. However, no novel CaRGAs or R genes were found. The nucleotide and amino acid sequences of all these pepper CaRGAs are listed in Additional file 2.
Sequence analysis and phylogenetic relationship between non-TIR- and TIR-NBS-LRR RGAs
BLASTX searches revealed that the fifty-seven CaRGAs had a certain degree of identity with known R genes as well as some RGAs from other plant species. They contained the conserved NB-ARC (nucleotide-binding adaptor shared by Apaf-1, R proteins and Ced-4) domain of known R genes [40–42]. Further analysis indicated that these CaRGAs, except for CaRGA54 (AF513549), CaRGA55 (FJ605104), CaRGA56 (FJ605105) and CaRGA57 (FJ605107), also included typically conserved motifs such as P-loop, kinase-2 and GLPL.
Characteristics of non-TIR and TIR-NBS CaRGAs from pepper ( Capsicum anuum L.)
Length of encoding nucleotide
residues (bp) and amino acids (aa)
GenBank accession number
CaRGA23;CaRGA28;CaRGA34;CaRGA43; CaRGA25;CaRGA39;CaRGA32;CaRGA20; CaRGA21;CaRGA26;CaRGA31;CaRGA24; CaRGA19;CaRGA37;CaRGA48;CaRGA41; CaRGA45; CaRGA46; CaRGA38
723/240;722/240;722/240;706/234728/242;701/233;722/240;697/232 684/227;728/242;712/237;731/243 730/243;731/243;613/204;703/234 510/170; 608/202; 707/235
DQ205986;DQ205995; DQ206007; DQ206021; DQ205988;DQ206016; DQ206000; DQ205982; DQ205984;DQ205989; DQ205999; DQ205987; DQ205981;DQ206010; FJ605106; DQ206019; FJ605101; FJ605102; DQ206015
CaRGA18;CaRGA30;CaRGA47;CaRGA22; CaRGA27;CaRGA33;CaRGA35;CaRGA29; CaRGA36; CaRGA40; CaRGA42
704/234;706/234;628/209;725/241 709/236;692/230;714/238;655/218 725/241; 725/241;725/241
DQ205980; DQ205998; FJ605103; DQ205985; DQ205992; DQ206001;DQ206008; DQ205997; DQ206009; DQ206018; DQ206020
CaRGA51;CaRGA16;CaRGA13; CaRGA17 Bs2; CaMi
525/175;513/171;501/167; 501/167 2715/905; 3774/1257
AF513548; JN112315; JN112312; JN112316 AF202179; DQ465824
CaRGA49; CaRGA50; CaRGA44
FJ605108; FJ605109; FJ605100
JN112302; JN112308; JN112304; JN112305
CaRGA04;CaRGA02;CaRGA10;CaRGA01; CaRGA07;CaRGA11;CaRGA08; CaRGA12
JN112303;JN112301;JN112309;JN112300; JN112306; JN112310; JN112307; JN112311
Amino acid sequence similarity (%) among representatives of the seven CaRGA subgroups identified from pepper and six known NBS-LRR plant R genes
CaRGA I (CaRGA23)
CaRGA II (CaRGA33)
CaRGA III (CaRGA13)
CaRGA IV (CaRGA14)
CaRGA V (CaRGA44)
CaRGA VI (CaRGA05)
CaRGA VII (CaRGA01)
Sequence homology comparisons between representatives of the identified pepper CaRGAs subgroups and its closest homolog in the GenBank
Length of BLASTX alignment
CaRGA I (CaRGA23)
R3a-like disease resistance protein gene
R3a-like disease resistance protein gene
CaRGA III (CaRGA13)
Solanum sp. VFNT
Mi-1.4 disease resistance protein gene
CaRGA IV (CaRGA14)
NBS-encoding resistance protein gene (RGA8)
CaRGA V (CaRGA44)
NBS-encoding resistance protein gene (clone crc Rgen8)
CaRGA VI (CaRGA05)
Nucleotide binding region of resistance-like gene (Q8)
CaRGA VII (CaRGA01)
Bacterial spot disease resistance protein gene (Bs4)
Multiple sequence alignments of non-TIR- and TIR-NBS-LRR RGAs in pepper
Analysis of functional divergence between the non-TIR- and TIR-NBS-LRR CaRGA subfamilies
Type I and II functional divergence between the non-TIR- and TIR-NBS-LRR subfamilies of pepper was assessed by posterior analysis using DIVERGE 2.0 software, which evaluates the (site-specific) shifted evolutionary rate after gene duplication or speciation [44, 45]. Posterior analysis results in a site-specific profile for predicting important amino acid residues responsible for functional divergence. The estimation was based on multiple sequence alignments and a neighbor-joining (NJ) tree of the NBS domain of the pepper RGAs, with clear separation of the two different subfamilies, non-TIR- and TIR-NBS-LRR (Figure 1). The coefficient of type-I functional divergence (θI) between the non-TIR- and TIR-NBS-LRR subfamilies was significantly greater than 0 (θI = 0.533 ± 0.156, P < 0.05). This result suggests that the altered functional constraint between the subfamilies is statistically significant and that some amino acid sites are subjected to different site-specific shifts in evolutionary rate that can lead to a subfamily-specific functional evolution after diversification. Compared with the findings for type-I functional divergence, the coefficient of type-II functional divergence (θII) between the non-TIR- and TIR-NBS-LRR subfamilies was less than 0. Therefore, type-I functional divergence was the primary pattern for the evolution of the non-TIR- and TIR-NBS-LRR subfamilies in pepper.
We further estimated the critical amino acid residues responsible for the functional divergence by calculating the site-specific profile based on a posterior probability (Q k ) analysis of the non-TIR- and TIR-NBS-LRR subfamilies. Among all of the aligned sites, the Q k values of most sites were <0.5 (Additional file 3). To reduce false positives, Q k > 0.70 was used as a cut-off to identify critical amino acid residues associated with type-I functional divergence between the non-TIR- and TIR-NBS-LRR subfamilies. A total of thirteen sites (positions 21, 22, 23, 69, 84, 104, 113, 116, 118, 125, 146, 155 and 165) were predicted (Additional file 3). Among these sites, the Q k value of site 22 was 0.878, which was predicted to be highly related to functional divergence, whereas the degree of relation to functional divergence was lowest at site 155 (Q k = 0.729).
Comparing evolutionary rates among NBS-LRR RGAs in pepper
Ka/Ks ratios for pairwise comparisons among members of the non-TIR and TIR-NBS CaRGA subfamilies in pepper
CaRGA I/CaRGA II
CaRGA I/CaRGA III
CaRGA I/CaRGA IV
CaRGA II/CaRGA III
CaRGA II/CaRGA IV
CaRGA III/CaRGA IV
CaRGA V/CaRGA VI
CaRGA V/CaRGA VII
CaRGA VI/CaRGA VII
Sliding window analysis
Determination of functional specificity positions among pepper NBS-LRR RGAs
Predicted specificity-determining residues of the non-TIR and TIR-NBS-LRR RGAs subfamilies in pepper
R gene group
2.41 × 10−4
2.83 × 10−8
3.49 × 10−12
3.01 × 10−16
Expression analysis of CaRGAs in different organs and in response to defence signaling molecules
After treatment with abscisic acid (ABA) and salicylic acid (SA), the expression levels of most of these CaRGA genes changed. We found that the addition of ABA increased the transcription levels of several of the analysed CaRGA genes, namely CaRGA18, CaRGA51, CaRGA23, CaRGA14 and CaRGA49. By contrast, ABA addition decreased the expression levels of CaRGA13, CaRGA01 and CaRGA05. However, the expression of CaRGA03, CaRGA36 and CaRGA38 were unchanged. SA is known to play a vital role in plant defence against pathogens . SA also induces the expression of a range of pathogen defence genes in plants [51, 52]. Among the CaRGAs tested, CaRGA01, CaRGA05, CaRGA03, CaRGA49, CaRGA14, CaRGA51, CaRGA36 and CaRGA38 displayed the most marked responses to SA treatment (Figure 6A). The expression levels of CaRGA18 and CaRGA23 decreased. The remaining genes showed no response to the SA treatment conditions. Real time-PCR experiments confirmed the expression levels of the selected CaRGAs (Figure 6B).
We found that two members from a subgroup may have different expression patterns, such as CaRGA01 and CaRGA04. However, similar expression patterns were also observed (CaRGA44 and CaRGA49). We also found that the CaRGAIV and VI subgroups had similar expression patterns. However, whether these genes with similar expression patterns have similar functions remains unclear. In addition, some earlier studies have reported that signaling molecules not only function as a critical signal for downstream resistance events but also upregulate the expression of R genes [51–56]. Some CaRGA genes were activated by SA and ABA (Figures 6A and 6B). This suggests that these stimuli induce the expression of the CaRGA genes and that they may play a potential role in mediating cross-talk between signaling pathways.
In summary, this paper provided detailed characterization and data on the functional divergence of non-TIR- and TIR-NBS-LRR CaRGAs in pepper. The mode of selection (positive selection, purifying selection and neutral selection) among the non-TIR- and TIR-NBS-LRR CaRGA subfamilies was identified by Ka/Ks analysis. However, the kind of evolutionary mechanisms responsible for the evolution of R genes in pepper cannot be inferred with certainty without the complete set of NBS-LRR genes from the pepper genome. Future studies must focus on verifying and elucidating the biological function of these CaRGA genes using supplementary experimental approaches, particularly with virus- or Agrobacterium-mediated transient assays  or by performing loss-of-function experiments, such as virus-induced gene silencing .
The present study identified numerous CaRGA sequences through degenerate PCR amplification and database mining. We divided these CaRGA sequences into two subfamilies (non-TIR- and TIR-NBS-LRR) based on phylogenetic tree and sequence analyses. The identified CaRGAs are a valuable resource for discovering R genes and developing RGA molecular markers that can be used for genetic mapping in pepper. We also predicted thirteen sites (positions 21, 22, 23, 69, 84, 104, 113, 116, 118, 125, 146, 155 and 165) as critical amino acid residues associated with the type-I functional divergence between non-TIR- and TIR-NBS-LRR subfamilies. Ka and Ks analyses showed that a purifying selection could play a critical role in the evolutionary processes of non-TIR- and TIR-NBS-LRR CaRGAs in pepper.
In addition, four SDPs (positions 91, 98, 146 and 124) were predicted to be involved in functional specificity in the non-TIR- and TIR-NBS-LRR CaRGA subfamilies. Expression analysis showed that some CaRGA genes were induced by SA or ABA, suggesting that they may be mainly involved in defence responses activated by signaling pathways associated with these two molecules. These findings provide a better understanding of the evolutionary mechanisms driving the functional diversification of non-TIR- and TIR-NBS-LRR R genes in pepper.
The sweet pepper breeding line PBC631B was selected to isolate potential NBS-type disease R genes. PBC631B seeds were germinated, and the seedlings were grown in growth chambers at 25°C for 12 h (day) and 18°C for 12 h (night). Relative humidity was maintained at 65–75%. Young leaves were harvested from 4 week-old plants, immediately frozen in liquid nitrogen and then stored at −80°C for nucleic acid extraction. For hormone treatments, the seedlings were cultured in Hoagland’s solution containing 100 μM SA and 100 μM ABA for 6 h. The treated samples were then harvested for testing. Genomic DNA was isolated using a commercial plant DNA extraction kit (Bioteke, Beijing, China) according to the manufacturer’s instructions.
Degenerate primers and PCR amplification
Cloning and sequencing of PCR products
Full volumes of the PCR products were run on a 1.0% agarose gel. Bands of the expected size (~500 bp) were excised from the agarose gel and purified using a DNA gel purification kit (Sangon, Shanghai, China). The obtained DNA was cloned into a pGEM T-Easy vector (Promega, Madison, WI, USA) and transformed into competent Escherichia coli JM 109 cells according to the manufacturer’s instructions. The cloned DNA fragment was sequenced by Bio-Asia Company (China).
Collection of other NBS-LRR RGAs through database mining
Other NBS-LRR RGAs from pepper were identified in the NCBI non-redundant protein database (http://www.ncbi.nlm.nih.gov/) using the key word ‘Capsicum resistance genes’. A total of 54 NBS-LRR-type sequences were identified. Six known disease R genes, including RPM1 (X87851), Gpa2 (AF195939), L6 (U27081), M (U73916), N (U15605) and Prf (U65391) were downloaded from the GenBank database, and their phylogenetic relationship with pepper NBS-LRR disease R genes was determined.
Sequence analysis and phylogenetic tree construction
Each of the acquired DNA sequences was trimmed of vector sequence contamination using VecScreen at NCBI. Identity and similarity searches of nucleotide and amino acid sequences were performed using BLAST at the NCBI GenBank database (http://www.ncbi.nlm.nih.gov/BLAST/). Sequence alignments were carried out using Clustal W (BioEdit software) . The phylogenetic tree was constructed by the NJ method using MEGA 5.0 software . The reliability of the interior nodes was assessed using 1000 bootstrap replicates. Human apoptosis activating factor-1 (Apaf-1), which contains homologous motifs with the NBS region in plant disease resistance genes, was included in the phylogenetic analysis as an outgroup sequence .
Analysis of functional divergence
The phylogenetic tree of the pepper NBS-LRR RGAs was broadly grouped into two clusters, namely the TIR- and non-TIR-NBS-LRR subfamilies. DIVERGE 2 software  was used to evaluate the potential functional divergence and to predict the important amino acid residues in these two subfamilies. The coefficients of type I and II functional divergence (θI and θII) between these two groups of pepper NBS-LRR RGAs were estimated through posterior analysis. A θI or θII value significantly >1 indicates altered selective constraints or a radical shift in amino acid physiochemical properties after gene duplication and/or speciation [44, 45]. A site-specific posterior analysis (Q k ) was also used to predict amino acid residues important for functional divergence.
Calculation of Ka/Ks ratios
We detected the mode of selection (positive selection, purifying selection or neutral selection) among the non-TIR- and TIR-NBS-LRR RGA subfamilies. The Ka/Ks ratios were calculated according to Nei and Gojobori  using K-Estimator 6.0 software [63, 64]. We identified the NBS-LRR RGAs subject to different selection pressures. DnaSP 5.0 software , which can calculate pairwise distance as part of a sliding window analysis, was applied. Ka/Ks values were plotted using Microsoft Excel to produce a graph of Ka and Ks values. The resultant Ka and Ks values were the sum of every possible pairwise comparison between every subgroup of R gene candidates selected for that particular window.
Analysis of SDPs
SDPfox was used to predict the SDPs that may determine the functional specificity of homologous proteins . SDP presents the statistical significance of the predictions in the form of Z-scores (the number of standard deviations away from the expected value) and displays the most significant positions in a multiple sequence alignment. Positions with high Z-scores are predicted to determine functional specificity.
RNA isolation, DNase l treatment, cDNA synthesis and semi-quantitative RT-PCR analysis
Total RNA from all samples was isolated using TRIZOL reagent according to the manufacturer’s protocol (Invitrogen). RNA integrity, RNA concentration, RNA quality, DNase l treatment and cDNA synthesis were performed as previously described . Two representatives of each class of NBS-LRR R genes were selected for expression analysis. Gene-specific primer pairs were designed using Primer5.0 software. A total of 13 pairs of CaRGA-specific primers were obtained (Additional file 5). Nine CaRGAs (i.e. CaRGA23, CaRGA38, CaRGA18, CaRGA36, CaRGA51, CaRGA13, CaRGA14, CaRGA49 and CaRGA44) were selected from NCBI. The remaining four CaRGAs (i.e. CaRGA03, CaRGA05, CaRGA04 and CaRGA01) were selected from PCR amplification. Subsequently, we analyzed the visualization of amplicon fragments to verify whether these primers were specific. Primers that exhibited the electrophoresis pattern of a single amplicon with the correct predicted size were considered CaRGA-specific primers. RT-PCR reactions were carried out using an Eppendorf PCR system 5331 cycler. The cycling program was as follows: 10 min at 94°C, 30 cycles of 45 s at 94°C, 45 s at 55°C and 1 min at 72°C and a 7 min extension at 72°C. The glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene was used as a reference .
Quantitative RT-PCR and data analyses
Primer specificity for quantitative RT-PCR was further confirmed by analyzing melting curves. Primers corresponding to the melting curves that yielded single sharp peaks were used for quantitative RT-PCR analysis. Real-time PCR reactions were carried out in a total volume of 25 μL containing 12.5 μL of 2× SYBRGreen PCR MasterMix (Applied Biosystems), 1 μL of each primer, 1 μL of template (10× diluted cDNA from samples) and 9.5 μL of sterile distilled water. The thermal conditions were as follows: 95°C for 10 min, followed by 40 cycles at 95°C for 15 s and a final step at 60°C for 1 min. Quantification analysis was performed through the comparative CT method. All reactions were performed in triplicate in 96-well reaction plates using an iQ5 machine (Bio-Rad). Two independent replicates were performed. GAPDH was used as a reference gene for the expression analysis of the pepper CaRGA genes .
We thank Prof. Zhiping Deng for reading this paper from Institute of Virology and Biotechnology, Zhejiang Academy of Agricultural Sciences, Hangzhou, China. This research was partially supported by the General Program from the National Natural Science Foundation of China (31071800); Zhejiang Provincial Natural Science Foundation of China (LQ12C15004) and Public Agricultural Technology Research (2011C22007); Breeding of Vegetable Varieties in Zhejiang Province (2009C02006-1) and Technological System of Ordinary Vegetable Industry.
- Flor HH: The current status of gene for gene concept. Ann Rev Phytopathol. 1971, 9: 275-296. 10.1146/annurev.py.09.090171.001423.View ArticleGoogle Scholar
- Dangl JL, Jones JDG: Plant pathogens and integrated responses to infection. Nature. 2001, 411: 826-833. 10.1038/35081161.View ArticlePubMedGoogle Scholar
- Meyers BC, Kozik A, Griego A, Kuang H, Michelmore RW: Genome wide analysis of NBS-LRR-encoding genes in Arabidopsis. Plant Cell. 2003, 15: 809-834. 10.1105/tpc.009308.PubMed CentralView ArticlePubMedGoogle Scholar
- DeYoung BJ, Innes RW: Plant NBS-LRR proteins in pathogen sensing and host. Nat Immunol. 2006, 7: 1243-1249. 10.1038/ni1410.PubMed CentralView ArticlePubMedGoogle Scholar
- McHale L, Tan X, Koehl P, Michelmore RW: Plant NBS-LRR proteins: adaptable guards. Genome Biol. 2006, 7: 212-PubMed CentralView ArticlePubMedGoogle Scholar
- Liu JL, Liu XL, Dai LY, Wang GL: Recent progress in elucidating the structure, function and evolution of disease resistance genes in plants. J Genet Genomics. 2007, 34: 765-776. 10.1016/S1673-8527(07)60087-3.View ArticlePubMedGoogle Scholar
- Holub EB: The arms race is ancient history in Arabidopsis, the wildflower. Nat Rev Genet. 2001, 2: 516-527. 10.1038/35080508.View ArticlePubMedGoogle Scholar
- Yue JX, Meyers BC, Chen JQ, Tian DC, Yang SH: Tracing the origin and evolutionary history of plant nucleotide-binding site-leucine-rich repeat (NBS-LRR) genes. New Phytol. 2012, 193: 1049-1063. 10.1111/j.1469-8137.2011.04006.x.View ArticlePubMedGoogle Scholar
- Meyers BC, Dickerman AW, Michelmore RW, Sivaramakrishnan S, Sobral BW, Young ND: Plant disease resistance genes encode members of an ancient and diverse protein family within the nucleotide-binding super family. Plant J. 1999, 20: 317-332. 10.1046/j.1365-313X.1999.t01-1-00606.x.View ArticlePubMedGoogle Scholar
- Tameling WI, Elzinga SD, Darmin PS, Vossen JH, Takken FL, Haring MA, Cornelissen BJ: The tomato R gene products I-2 and Mi-1 are functional ATP binding proteins with ATPase activity. Plant Cell. 2002, 14: 2929-2939. 10.1105/tpc.005793.PubMed CentralView ArticlePubMedGoogle Scholar
- Kobe B, Deisenhofer J: A structural basis of the interactions between leucine-rich repeats and protein ligands. Nature. 1995, 374: 183-186. 10.1038/374183a0.View ArticlePubMedGoogle Scholar
- Leister RT, Katagiri F: A resistance gene product of the nucleotide binding site-leucine rich repeats class can form a complex with bacterial avirulence proteins in vivo. Plant J. 2000, 22: 345-354. 10.1046/j.1365-313x.2000.00744.x.View ArticlePubMedGoogle Scholar
- Yu YG, Buss GR, Saghai Maroof MA: Isolation of a superfamily of candidate disease-resistance genes in soybean based on a conserved nucleotide-binding site. Proc Natl Acad Sci USA. 1996, 93: 11751-11756. 10.1073/pnas.93.21.11751.PubMed CentralView ArticlePubMedGoogle Scholar
- Gentzbittel L, Mouzeyar S, Badaoui S, Mestries E, Vear F, Tourvieille de Labrouhe D, Nicolas P: Cloning of molecular markers for disease resistance in sunflower, Helianthus annuus L. Theor Appl Genet. 1998, 96: 519-525. 10.1007/s001220050769.View ArticlePubMedGoogle Scholar
- Pan QL, Wendel J, Fluhr R: Divergent evolution of plant NBS LRR resistance gene homologues in dicot and cereal genomes. J Mol Evol. 2000, 50: 203-213.PubMedGoogle Scholar
- Tian YY, Fan LJ, Thurau T, Jung C, Cai DG: The absence of TIR-type resistance gene analogues in the sugar beet (Beta vulgaris L.) genome. J Mol Evol. 2004, 58: 40-53. 10.1007/s00239-003-2524-4.View ArticlePubMedGoogle Scholar
- Wan HJ, Zhao ZG, Malik AA, Qian CT, Chen JF: Identification vand characterization of potential NBS-encoding resistance genes and induction kinetics of a putative candidate gene associated with downy mildew resistance in Cucumis. BMC Plant Biol. 2010, 10: 186-10.1186/1471-2229-10-186.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhang HL, Wang YJ, Zhang CH, Wang XP, Li HE, Xu WR: Isolation, characterization and expression analysis of resistance gene candidates in pear (Pyrus spp.). Sci Horticul. 2011, 127: 282-289. 10.1016/j.scienta.2010.10.016.View ArticleGoogle Scholar
- Mutlu N, Miklas PN, Coyne DP: Resistance gene analog polymorphism (RGAP) markers co-localize with disease resistance genes and QTL in common bean. Mol breeding. 2006, 17: 127-135. 10.1007/s11032-005-4474-6.View ArticleGoogle Scholar
- Cannon SB, Zhu H, Baumgarten AM, Spangler R, May G, Cook DR, Young ND: Diversity, distribution and ancient taxonomic relationships within the TIR and non-TIR NBS-LRR resistance gene subfamilies. J Mol Evol. 2002, 54: 548-562. 10.1007/s00239-001-0057-2.View ArticlePubMedGoogle Scholar
- Speulman E, Bouchez D, Holub EB, Beynon JL: Disease resistance gene homologs correlate with disease resistance loci of Arabidopsis thaliana. Plant J. 1998, 14: 467-474. 10.1046/j.1365-313X.1998.00138.x.View ArticlePubMedGoogle Scholar
- Ashfield T, Bocian A, Held D, Henk AD, Marek LF, Danesh D, Penūela S, Meksem K, Lightfoot DA, Young ND, Shoemaker RC, Innes RW: Genetic and physical localization of the soybean Rpg1-b disease resistance gene reveals a complex locus containing several tightly linked families of NBS-LRR genes. Mol Plant Microbe Interact. 2003, 16: 817-826. 10.1094/MPMI.2003.16.9.817.View ArticlePubMedGoogle Scholar
- Radwan O, Bouzidi MF, Nicolas P, Mouzeyar S: Development of PCR markers of the PI5/PI8 locus for resistance to Plasmopara halstedii in sunflower, Helianthus annuus L. from complete CC-NBS–LRR sequences. Theor Appl Genet. 2004, 109: 176-185. 10.1007/s00122-004-1613-0.View ArticlePubMedGoogle Scholar
- Hulbert SH, Webb CA, Smith SM, Sun Q: Resistance gene complexes: Evolution and utilization. Annu Rev Phytopathol. 2001, 39: 285-312. 10.1146/annurev.phyto.39.1.285.View ArticlePubMedGoogle Scholar
- Richly E, Kurth J, Leister D: Mode of amplification and reorganization of resistance genes during recent Arabidopsis thaliana evolution. Mol Biol Evol. 2002, 19: 76-84. 10.1093/oxfordjournals.molbev.a003984.View ArticlePubMedGoogle Scholar
- Zhou T, Wang Y, Chen JQ, Araki H, Jing Z, Jiang K, Shen J, Tian D: Genome-wide identification of NBS genes in rice reveals significant expansion of divergent non-TIR NBS Genes. Mol Genet Genomics. 2004, 271: 402-415. 10.1007/s00438-004-0990-z.View ArticlePubMedGoogle Scholar
- Mondragón-Palomino M, Meyers BC, Michelmore RW, Gaut BS: Patterns of positive selection in the complete NBS-LRR gene family of Arabidopsis thaliana. Genome Res. 2002, 12: 1305-1315. 10.1101/gr.159402.PubMed CentralView ArticlePubMedGoogle Scholar
- Yang SH, Zhang XH, Yue JX, Tian DC, Chen JQ: Recent duplications domainate NBS-encoding gene expansion in two woody species. Mol Genet Genomics. 2008, 280: 187-198. 10.1007/s00438-008-0355-0.View ArticlePubMedGoogle Scholar
- Xu Q, Wen XP, Deng XX: Isolation and TIR and nonTIR NBS-LRR resistance gene analogues and identification of molecular markers linked to a powdery mildew resistance locus in chestnut rose (Rosa roxburghii Tratt). Theor Appl Genet. 2005, 111: 819-830. 10.1007/s00122-005-0002-7.View ArticlePubMedGoogle Scholar
- Xu Q, Wen XP, Deng XX: Phylogenetic and evolutionary analysis of NBS-encoding genes in Rosaceae fruit crops. Mol Phylogenet Evol. 2007, 44: 315-324. 10.1016/j.ympev.2006.12.029.View ArticlePubMedGoogle Scholar
- Römer P, Hahn S, Jordan T, Strauß T, Bonas U, Lahaye T: Plant pathogen recognition mediated by promoter activation of the pepper Bs3 resistance gene. Science. 2007, 318: 645-648. 10.1126/science.1144958.View ArticlePubMedGoogle Scholar
- Tai TH, Dahlbeck D, Clark ET, Gajiwala P, Pasion R, Whalen MC, Stall RE, Staskawicz BJ: Expression of the Bs2 pepper gene confers resistance to bacterial spot disease in tomato. Proc Natl Acad Sci. 1999, 96: 14153-14158. 10.1073/pnas.96.24.14153.PubMed CentralView ArticlePubMedGoogle Scholar
- Chen R, Li H, Zhang L, Zhang J, Xiao J, Ye Z: CaMi, a root-knot nematode resistance gene from hot pepper (Capsium annuum L.) confers nematode resistance in tomato. Plant Cell Rep. 2007, 26: 895-905. 10.1007/s00299-007-0304-0.View ArticlePubMedGoogle Scholar
- Egea-gilabert C, Dickinson MJ, Bilotti G, Candela ME: Isolation of resistance gene analogs in pepper using modified AFLPs. Biol Plantarum. 2003, 47: 27-32.View ArticleGoogle Scholar
- Pflieger S, Lefebvre V, Caranta C, Blattes A, Goffinet B, Palloix A: Disease resistance gene analogs as candidates for QTLs involved in pepper-pathogen interactions. Genome. 1999, 42: 1100-1110. 10.1139/g99-067.View ArticlePubMedGoogle Scholar
- Kochieva EZ, Ryzhova NN: Analysis of resistance gene family diversity in pepper (Capsicum annuum). Biochem Biophy Mol Biol. 2009, 425: 256-258.Google Scholar
- Zhang LY, Chen RG, Zhang JH: Cloning and analysis of resistance gene analogs from pepper (Capsicum annuum L.). Agr Sci China (in Chinese). 2008, 41: 169-175.Google Scholar
- Noir S, Combes M-C, Anthony F, Lashermes P: Origin, diversity and evolution of NBS-type disease-resistance gene homologues in coffee trees (Coffea L.). Mol Gen Genomics. 2001, 265: 654-662. 10.1007/s004380100459.View ArticleGoogle Scholar
- Deng Z, Huang S, Ling P, Chen C, Yu C, Weber CA, Moore GA, Gmitter FG: Cloning and characterization of NBS–LRR class resistance-gene candidate sequences in citrus. Theor Appl Genet. 2000, 101: 814-822. 10.1007/s001220051548.View ArticleGoogle Scholar
- van der Biezen EA, Jones JDG: The NB-ARC domain: a novel signalling motif shared by plant resistance gene products and regulators of cell death in animals. Curr Biol. 1998, 8: R226-R227. 10.1016/S0960-9822(98)70145-9.View ArticlePubMedGoogle Scholar
- Aravind L, Iyer LM, Leipe DD, Koonin EV: A novel family of P-loop NTPases with an unusual phyletic distribution and transmembrane segments inserted within the NTPase domain. Genome Biol. 2004, 5: R30-10.1186/gb-2004-5-5-r30.PubMed CentralView ArticlePubMedGoogle Scholar
- Leipe DD, Koonin EV, Aravind L: STAND, a class of P-loop NTPases including animal and plant regulators of programmed cell death: multiple, complex domain architectures, unusual phyletic patterns, and evolution by horizontal gene transfer. J Mol Biol. 2004, 343: 1-28. 10.1016/j.jmb.2004.08.023.View ArticlePubMedGoogle Scholar
- Tamura K, Peterson D, Peterson N, Stecher G, Nei M, Kumar S: MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol Biol Evol. 2011, 28: 2731-2739. 10.1093/molbev/msr121.PubMed CentralView ArticlePubMedGoogle Scholar
- Gu X: Statistical methods for testing functional divergence after gene duplication. Mol Biol Evol. 1999, 16: 1664-1674. 10.1093/oxfordjournals.molbev.a026080.View ArticlePubMedGoogle Scholar
- Gu X: A simple statistical method for estimating type-II (cluster-specific) functional divergence of protein sequences. Mol Biol Evol. 2006, 23: 1937-1945. 10.1093/molbev/msl056.View ArticlePubMedGoogle Scholar
- Michelmore R, Meyers B: Clusters of resistance genes in plants evolve by divergent selection and birth-and-death process. Genome Res. 1998, 8: 1113-1130.PubMedGoogle Scholar
- Martin GB, Brommonschenkel S, Chunwongse J, Frary A, Ganal MW, Spivey R, Wu T, Earle ED, Tanksley SD: Map-based cloning of a protein kinase gene conferring disease resistance in tomato. Science. 1993, 262: 1432-1436. 10.1126/science.7902614.View ArticlePubMedGoogle Scholar
- Creevey CJ, McInerney JO: CRANN: Detecting adaptive evolution in protein-coding DNA sequences. Bioinformatics. 2003, 19: 1726-10.1093/bioinformatics/btg225.View ArticlePubMedGoogle Scholar
- Mazin PV, Gelfand MS, Mironov AA, Rakhmaninova AB, Rubinov AR, Russell RB, Kalinina OV: An automated stochastic approach to the identification of the protein specificity determinants and functional subfamilies. Algorithm Mol Biol. 2010, 5: 29-10.1186/1748-7188-5-29.View ArticleGoogle Scholar
- Thomma BP, Penninckx IA, Broekaer WF, Cammue BP: The complexity of disese signaling in Arabidopsis. Curr Opin Immunol. 2011, 13: 63-68.View ArticleGoogle Scholar
- Shirano Y, Kachroo P, Shah J, Klessig DF: A gain-of-function mutation in an arabidopsis Toll interleukin1 receptor-nucleotide binding site-leucine-rich repeat type R gene triggers defense responses and results in enhanced disease resistance. Plant Cell. 2002, 14: 3149-3162. 10.1105/tpc.005348.PubMed CentralView ArticlePubMedGoogle Scholar
- Xiao SX, Brown EP, Brearley C, Turner JG: Enhanced transcription of the Arabidopsis disease resistance genes RPW8.1and RPW8.2 via a salicylic acid-dependent amplification circuit is required for hypersensitive cell death. Plant Cell. 2003, 15: 33-45. 10.1105/tpc.006940.PubMed CentralView ArticlePubMedGoogle Scholar
- Xiong QY, Wei LJ, Sen ZJ, Hong RM, Ping XL, Qing ZM: Molecular cloning and characterisation of a non-TIR-NBS-LRR type disease resistance gene analogue from sugarcane. Sugar Tech. 2008, 10: 71-73. 10.1007/s12355-008-0012-2.View ArticleGoogle Scholar
- Wang BJ, Zhang ZG, Li XG, Wang YJ, He CY, Zhang JS, Chen SY: Cloning and analysis of a disease resistance gene homolog from soybean. Acta Botan Sin. 2003, 45: 864-870.Google Scholar
- Wang BJ, Wang YJ, Wang Q, Luo GZ, Zhang ZG, He CY, He SJ, Zhang JS, Gai JY, Chen SY: Characterization of an NBS-LRR resistance gene homologue from soybean. J Plant Physiol. 2004, 161: 815-822. 10.1016/j.jplph.2004.01.007.View ArticlePubMedGoogle Scholar
- Tian AG, Luo GZ, Wang YJ, Zhang JS, Gai JY, Chen SY: Isolation and characterization of a Pti1 homologue from soybean. J Exp Bot. 2004, 396: 535-537.View ArticleGoogle Scholar
- Bendahmane A, Querci M, Kanyuka K, Baulcombe DC: Agrobacterium transient expression system as a tool for isolation of disease resistance genes: application to the Rx2 locus in potato. Plant J. 2000, 21: 73-81. 10.1046/j.1365-313x.2000.00654.x.View ArticlePubMedGoogle Scholar
- Baulcombe DC: Fast forward genetics based on virus-induced gene silencing. Curr Opin Plant Biol. 1999, 2: 109-113. 10.1016/S1369-5266(99)80022-3.View ArticlePubMedGoogle Scholar
- Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG: The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997, 25: 4876-4882. 10.1093/nar/25.24.4876.PubMed CentralView ArticlePubMedGoogle Scholar
- van der Biezen EA, Jones JD: The NB-ARC domain: a novel signaling motif shared by plant resistance gene products and regulators of cell death in animals. Curr Biol. 1998, 8: R226-R227. 10.1016/S0960-9822(98)70145-9.View ArticlePubMedGoogle Scholar
- Gu X, Vander Velden K: DIVERGE: phylogeny-based analysis for functional-structural divergence of a protein family. Bioinformatics. 2002, 18: 500-501. 10.1093/bioinformatics/18.3.500.View ArticlePubMedGoogle Scholar
- Nei M, Gojobori T: Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol. 1986, 3: 418-426.PubMedGoogle Scholar
- Comeron JM: A method for estimating the numbers of synonymous and non-synonymous substitutions per site. J Mol Evol. 1995, 41: 1152-1159.View ArticlePubMedGoogle Scholar
- Comeron JM: K-Estimator: Calculation of the number of nucleotide substitutions per site and the confidence intervals. Bioinformatics. 1999, 15: 763-764. 10.1093/bioinformatics/15.9.763.View ArticlePubMedGoogle Scholar
- Librado P, Rozas J: DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009, 25: 1451-1452. 10.1093/bioinformatics/btp187.View ArticlePubMedGoogle Scholar
- Wan HJ, Yuan W, Ruan MY, Ye QJ, Wang RQ, Li ZM, Zhou GZ, Yao ZP, Zhao J, Liu SJ, Yang YJ: Identification of reference genes for reverse transcription quantitative real-time PCR normalization in pepper (Capsicum annuum L.). Biochem Biophys Res Commun. 2011, 416: 24-30. 10.1016/j.bbrc.2011.10.105.View ArticlePubMedGoogle Scholar
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