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Article

Genome-Wide Identification of Nucleotide-Binding Site–Leucine-Rich Repeat Gene Family in Cymbidium ensifolium and Expression Profiles in Response to Fusarium Wilt Infection

1
Key Laboratory of National Forestry and Grassland Administration for Orchid Conservation and Utilization, College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
Institute of Forest Protection, College of Forestry, Fujian Agriculture and Forestry University, Fuzhou 350002, China
*
Authors to whom correspondence should be addressed.
Horticulturae 2024, 10(6), 634; https://doi.org/10.3390/horticulturae10060634
Submission received: 28 April 2024 / Revised: 6 June 2024 / Accepted: 9 June 2024 / Published: 13 June 2024
(This article belongs to the Special Issue Germplasm Resources and Genetic Breeding of Ornamental Plants)

Abstract

:
Fusarium wilt in Cymbidium ensifolium, caused by Fusarium oxysporum, is highly contagious and poses a severe hazard. It significantly reduces the ornamental value of C. ensifolium and causes substantial economic losses in agricultural production. Nucleotide-binding site–leucine-rich repeat (NBS-LRR) genes are key regulatory factors in plant disease resistance responses, playing vital roles in defending against pathogen invasions. In our study, we conducted a comprehensive analysis of the NBS-LRR gene family in the genome of Cymbidium ensifolium. Phylogenetic analysis identified a total of 31 NBS-LRR genes encoding NB-ARC proteins, which were categorized into five classes (CNL, CN, NL, N, RNL) based on their protein structural domains. These genes were found to be unevenly distributed across eight chromosomes. Physicochemical analysis revealed significant variances in molecular weight and sequence length among the family members. Subcellular localization results indicated that most genes primarily reside in the cytoplasm and cell membrane, suggesting that the primary sites of disease resistance responses may be the cell membrane and cyto-plasm. Furthermore, noticeable disparities were observed in gene structures and conserved motifs among different categories of family genes. Promoter analysis indicated that cis-regulatory elements are mainly associated with plant stress, jasmonic acid, gibberellin, and other development-related factors, suggesting that CeNBS-LRR genes mainly resist external stress through hormones such as abscisic acid and jasmonic acid. We characterized twenty-seven CeNBS-LRR gene expression patterns of healthy C. ensifolium at different periods after Fusarium wilt infection, and found that those genes exhibit a temporospatial expression pattern, and that their expression is also responsive to Fusarium wilt infection. By analyzing the expression pattern via transcriptome and qRT-PCR, we speculated that JL006442 and JL014305 may play key roles in resisting Fusarium wilt. This study lays the groundwork and holds considerable significance as a reference for identifying disease-resistant genes and facilitating genetic breeding in C. ensifolium.

1. Introduction

Cymbidium ensifolium spp., a member of the Orchidaceae and genus Cymbidium, is an ornamental plant known for its vibrant colors, upright stature, and delightful fragrance, which holds high ornamental and economic value [1,2]. In recent years, the expansion of cultivation areas and various external factors, including biotic and abiotic stresses, have greatly impacted its cultivation. Among these factors, Fusarium wilt disease, caused by Fusarium oxysporum, is particularly prevalent. This disease has broad infectivity and severe consequences, greatly diminishing the ornamental value of C. ensifolium and resulting in substantial economic losses to the industry [3,4]. Currently, disease prevention and control primarily rely on chemical agents and cultivation management measures, but their long-term effectiveness is questionable [5]. Therefore, the breeding of disease-resistant varieties is crucial for addressing wilt disease, with elucidating its resistance mechanisms being a primary focus.
Plants encounter various pathogens during different growth periods, including fungi, bacteria, nematodes, and viruses, among others, which significantly hinder their growth, development, metabolism, and absorption of water and nutrients, often resulting in severe diseases such as Fusarium wilt, Anthracnose, and powdery mildew [3,6,7,8]. To combat pathogen invasion, plants have evolved two distinct levels of defense responses over time: primary immune response and secondary immune response [9]. The primary immune response (PTI) constitutes the first level, where pattern recognition receptors (PRRs) on the surface of host cells recognize pathogen-associated molecular patterns (PAMPs) from pathogens and microorganisms, activating the PTI triggered by PAMPs (PAMP-triggered immunity). The second level is the secondary immune response (ETI). In general, PTI responses can block the invasion of most pathogens and microorganisms, but some pathogens or microorganisms may secrete effectors to inhibit PTI responses. To prevent further invasion by pathogens, plants produce effectors that trigger immunity (ETI). In the ETI response, R genes act as receptors, specifically recognizing pathogen effectors, thereby activating hypersensitive responses, cell death, and the accumulation of reactive oxygen species [10,11,12].
The NBS-LRR gene family represents the largest class of disease resistance genes, also known as the R gene family, named after the abbreviations of its two important domains: NBS (nucleotide-binding site) and LRR (leucine-rich repeat) [13]. The NBS-LRR genes play a vital role in plants by perceiving and responding to invasion by pathogens such as fungi, viruses, and activating defense responses, including the accumulation of antimicrobial substances and the synthesis of antimicrobial enzymes. [12]. The NBS domain can bind and hydrolyze ATP or GTP nucleotides, thereby facilitating signal transduction and response [14]. The LRR domain is composed of multiple repeats rich in leucine residues, which interact with exogenous signaling molecules, proteins, and other molecules, thereby exerting disease resistance effects [15]. Typically, the N-terminal domain of NBS-encoding proteins consists of TIR (Toll/interleukin-1 receptor-like), CC (coiled coil), or RPW8. Based on their domain composition, they are often classified into three major subfamilies: TNL (TIR-NBS-LRR), CNL (CC-NBS-LRR), and RNL (RWP8-NBS-LRR) [16,17]. Previous studies have shown that the TNL subfamily is predominantly present in dicotyledons, whereas in monocotyledons, the TN class may lack the LRR structural domain or even be completely absent, suggesting that the NBS-LRR family of genes underwent significant divergence during the evolution of monocotyledons and dicotyledons. [18]. Given its significance, the NBS-LRR gene family has been consistently at the forefront of research in plant disease resistance. Currently, identification analyses of the NBS-LRR gene family have been completed in various plant genomes such as Arabidopsis thaliana, Oryza sativa, Triticum aestivum, Medicago sativa, and Actinidia chinensis [19,20,21,22,23]. This study employs bioinformatics techniques to identify members of the NBS-LRR gene family in C. ensifolium, uncovering their chromosome localization, conserved domains, and evolutionary relationships. In addition, we analyzed the expression patterns of the CeNBS-LRR genes at different stages of infection and screened for potential genes responsive to Fusarium wilt. The genome-wide identification and expression profiling of the NBS-LRR gene family in C. ensifolium aims to lay a foundation for screening disease resistance genes in C. ensifolium and for genetic breeding research.

2. Materials and Methods

2.1. Identification of the CeNBS-LRR Genes

The complete genome data of C. ensifolium was obtained from the NGDC database (https://ngdc.cncb.ac.cn/, accessed on 27 December 2023), and the genomic data of A. thaliana and the NBS-LRR protein sequences were obtained from the TAIR database (http://www.arabidopsis.org/, accessed on 27 December 2023) [24]. The NB-ARC domain Hidden Markov Model PF00931 was downloaded from the Pfam database (http://pfam.xfam.org/, accessed on 27 December 2023). The protein sequence files of C. ensifolium were searched and compared based on the PF00931 HMM model using the BLAST program of TBtools with a threshold E-value of ≤10−4 to initially screen candidate protein sequences. Subsequently, all potential candidate protein sequences were submitted to the CDD-SEARCH website (https://www.ncbi.nlm.nih.gov/Structure/cdd/wrpsb.cgi, accessed on 27 December 2023), the SMART website (http://smart.embl.de, accessed on 27 December 2023), and the PFAM website (https://pfam.xfam.org/, accessed on 29 December 2023) for further structural domain prediction, eliminating invalid genes lacking NB-ARC conserved structural domains and misannotated genes [25,26]. Finally, all candidate genes were validated using the INTERPRO website (https://www.ebi.ac.uk/interpro/, accessed on 29 December 2023). The final validated NBS-LRR genes were classified according to their domain arrangement.

2.2. Phylogenetic Analysis, Physicochemical Properties, and Chromosome Localization Analysis

The protein sequences of the NBS-LRR family were extracted from the protein sequence files of C. ensifolium and A. thaliana based on gene IDs. Multiple sequence alignment was performed using the CLustalW method in MEGA11.0.13 software with default parameters [27]. The ML (maximum likelihood) method was used to construct a phylogenetic tree of the CeNBS-LRR family protein sequences, using the p-distance model with bootstrap validation repeated 1000 times, partial deletion method, and a threshold of 50%. Ultimately, the web program Chiplot (https://www.chiplot.online/tvbot.html, accessed on 30 December 2023) was used to beautify the phylogenetic tree [28]. The subcellular localization of the NBS protein was predicted using the Plant-mPLoc website (http://www.csbio.sjtu.edu.cn/bioinf/Cell-PLoc-2/, accessed on 30 December 2023) and physicochemical properties like isoelectric point and molecular weight were calculated using the EXPASY online tool (https://web.expasy.org/protparam/, accessed on 30 December 2023) [29,30]. Applying the chromosome information from the C. ensifolium annotation file, the TBtools 1.119 software was used to visualize the chromosomal positions of CeNBS-LRR genes [31].

2.3. Cis-Acting Elements and Genome Collinearity Analysis of CeNBS-LRR Genes

According to their gene position, the upstream 2000bp sequences were extracted by TBtools from the coding sequences (CDS) file of C. ensifolium. These sequence files were submitted to the PlantCARE website (http://bioinformatics.psb.ugent.be/webtools/plantcare/html/, accessed on 3 January 2024) for investigating the putative cis-acting elements [32]. The resulting files were organized in Excel, irrelevant functional elements were removed, and the elements were categorized by function and visualized using a heatmap generated by Excel 2020 and TBtools. Genomic and annotation files for A. thaliana and O. sativa were downloaded from the Phytozome database (https://phytozome-next.jgi.doe.gov/, accessed on 5 January 2024). Genomic data analysis and visualization of the genomic collinearity between C. ensifolium, A. thaliana, and O. sativa were conducted using the quick-run MCScanX wrapper and multiple synteny plot programs in TBtools [31].

2.4. Analysis of Gene Structure and Conserved Domains

The CeNBS-LRR protein sequences were uploaded to the MEME website for motif analysis, with the number of motifs set to 10. The default parameters were used for other settings, resulting in an XML output file. Additionally, genetic structure and domain visualization were conducted via TBtools using the annotation file of C. ensifolium and the PFAM domain prediction result file. Conserved domain prediction was performed using the Jalview 2.11.3.2 software, and the logo of the conservative sequence was created using the Weblogo online tool (https://weblogo.berkeley.edu/, accessed on 12 January 2024). The final images were combined using Adobe Photoshop 2020 and Adobe Illustrator 2020 software.

2.5. Plant Material and Gene Expression Analysis to Fusarium Wilt Infection

The experimental plants were obtained from Fujian Agriculture and Forestry University (Forest Orchid Garden), and were cultivated in greenhouses. Healthy adult C. ensifoliumDa feng su’ plants were chosen as inoculation materials for the study. The pathogenic fungus F. oxysporum was isolated from diseased C. ensifolium roots, purified, and cultured on PDA medium. When the medium was colonized with mycelium, the mycelium was scraped and filtered to obtain a spore suspension with a concentration of 1 × 106 CFU/mL. The root-dipping method was used to treat the roots of plant materials. The roots were soaked in the spore suspension for 30 min before being transferred to an artificial culture chamber for incubation. Incubation conditions were kept at 25 °C with a 16 h light cycle and an 8 h dark cycle. Root samples were collected at 0 h (control), 6 h, 12 h, and 24 h post inoculation. All samples were subjected to three biological replicates. RNA extraction was conducted by an RNA extraction kit (OMEGA, Norcross, GA, USA) according to the instructions. cDNA was synthesized using a Hifair®III 1st Strand cDNA Synthesis Kit (gDNA digester plus), Yeasen Bio, Shanghai, China. Novozymes (Beijing, China) constructed the transcriptome data library using the Illumina Hiseq 6000 platform, quantifying gene expression levels in FPKM (fragments per kilobase of transcript per million mapped reads) (Table S1). The heatmap of gene expression was generated using TBtools.

2.6. Real-Time Fluorescence Quantitative Experiment

Based on the CeNBS-LRR genes expression values (FPKM > 10) and trends (|log2FoldChange| ≥ 1.0), eight candidate genes were selected for expression validation. The primers for these genes were designed using Primer Premier 5 software and synthesized by Shanghai Sangon Biotech Company (Shanghai, China). The details of the primers are listed in Table S2. The GAPDH was used as the internal reference gene for qPCR experiments. Experiments were carried out on an ABI 7500 real-time system (Applied Biosystems, Foster City, CA, USA) using the Hieff® qPCR SYBR Green Master Mix (Low Rox Plus) kit according to the instructions given by the Shanghai Yisheng Biological Company (Shanghai, China). Three biological replicates were performed, and the 2−CT formula was used to calculate the relative gene expression.

3. Results

3.1. Identification and Classification of NBS-LRR Genes in C. ensifolium

A total of 43 genes were obtained through retrieval and alignment using the HMM model (PF00931) in the C. ensifolium genome database. Gene structure prediction was further validated online using the Pfam, BatchCD search, Interprosearch, and SMART websites. Ultimately, 31 NBS-LRR family genes were identified, constituting approximately 0.1% of the entire genome. These genes were categorized into five classes based on different protein structural domains: CNL, CN, NL, N, and RNL. Specifically, there was 1 RNL gene, 9 CN genes, 11 CNL genes, 4 NL genes, and 6 N genes. All identified genes contained the NB-ARC domain, but the NBS-LRR gene carrying the TIR domain was not found (Table 1).

3.2. Phylogenetic Analysis, Physicochemical Properties, and Chromosomal Localization Analysis

A phylogenetic tree was constructed using the maximum likelihood (ML) method, based on 31 CeNBS-LRR and 166 AtNBS-LRR protein sequences (Figure 1). All NBS-LRR protein sequences were divided into three subfamilies: TNL, CNL, and RNL. Except for JL005200, which belonged to the RNL family, the remaining sequences were classified under the CNL subfamily. No clustering between CeNBS-LRR proteins and AtTNL subfamily members was observed. An analysis of the physicochemical properties of the 31 NBS-LRR protein sequences revealed that the average length of the CeNBS-LRR protein sequence was 2225.1 bp, with the longest being 3705 bp (JL006442) and the shortest being 384 bp (JL021707). A comparative analysis of the physicochemical properties of the 31 NBS-LRR family members revealed that most subfamily members had amino acid counts ranging from 127 to 1234. Specifically, JL021707 had the lowest amino acid count at 127, while JL006442 had the highest at 1234. The average theoretical isoelectric point was 6.68, and the molecular weight varied from 14,328.63 to 138,792.65 kDa. The average protein instability index was 48.38, indicating that the majority of the proteins were unstable. A high proportion of acidic amino acids were observed in the members, with an average aliphatic index ranging from 85.77 to 106.77. The average hydrophilicity ranged from -0.504 to 0.063; except for JL024806, the other proteins were hydrophilic (Table 2). Subcellular localization prediction using the Cell-PLoc 2.0 online website indicated that the majority were located in the cytoplasm and cell membrane, with a few found in the nucleus, suggesting that the primary sites of disease-resistance responses may be the cell membrane and cytoplasm. Chromosome localization analysis was performed based on the alignment of the C. ensifolium genome and annotation files. According to the analysis, CeNBS-LRR genes are distributed among eight chromosomes (Chr 2, Chr 4, Chr 5, Chr 6, Chr 8, Chr 12, Chr 13, Chr 17) out of the twenty chromosomes present in C. ensifolium. They form two gene clusters on chromosomes 8 and 17, containing up to 14 and 8 NBS-LRR genes, respectively (Figure 2). However, no genes from this family were found on the remaining 12 chromosomes, while the remaining chromosomes sporadically harbored one to two genes each.

3.3. Gene Structure Analysis, Conserved Motif Analysis, and Conserved Domain Analysis in C. ensifolium

In the CeNBS-LRR family, it has been observed that the NB-ARC domain typically contains eight conserved motifs: P-loop, Kinase2, GLPL, MHDV, RNBS-A, RNBS-B, RNBS-C, and RNBS-D [33,34]. A total of 10 conserved motifs were identified through MEME analysis of the CeNBS-LRR proteins (Figure S1). Within the NB-ARC domain, six conserved motifs were identified (P-loop, Kinase2, GLPL, MHDV, RNBS-B, RNBS-D). Motif1 contains the sequence VFAIVGMGGIGKTTLAKLVFD, with the underlined part representing a highly conserved amino acid sequence characteristic of the P-loop motif. Motif8 contains the sequence SVVSGKNLFLVLDDVWRADVW, characteristic of the Kinase2 motif [35]. The amino acid sequence NRLKGIGLQIAGNCGGLPLAIKAIAGVLAG of Motif6 can be inferred to represent the GLPL motif. Similarly, the sequence GSRVLVTTRNKE in Motif5 is indicative of a conserved feature of the RNBS-B motif. Notably, most CeNBS-LRR genes contain Motif1, Motif 5, Motif 6, and Motif 8, which collectively constitute highly conserved regions of the NB-ARC domain. The sequence LYLSFEDLPSHLKQCFLYFAL in Motif2 corresponds to a highly conserved motif of RNBS-D. The amino acid sequence FFTMHDLVYSLSR in Motif10 is a conserved region of the MHDV motif, and its presence or absence suggests the presence of the CC domain. Additionally, considering the different arrangements of the conserved motifs and the characteristics of the LRR domain, it can be inferred that the leucine-rich repeat sequence SFIPKGIGNLQQLNH in Motif9 represents the LRR domain [36]. Gene structure analysis revealed that most CeNBS-LRR genes lack introns, constituting approximately 47% of the total. These genes are primarily found in the subfamilies of CNL and CN, with the number of exons ranging from one to six. NL-category genes typically consist of three exons and two introns. Variations in the numbers of introns and exons were observed among genes of different subfamilies (Figure 3).

3.4. Collinearity Analysis of CeNBS-LRR Genes

Furthermore, collinearity analysis between the C. ensifolium genome and the model plants A. thaliana and O. sativa revealed that C. ensifolium exhibits four collinear relationships with O. sativa, but only one with A. thaliana (Figure 4, Table S3). In the self-collinearity analysis of C. ensifolium, only one pair of segmentally duplicated genes (JL014305 and JL022987) was identified (Figure 5).

3.5. Analysis of Cis-Acting Elements

To investigate the functions of NBS-LRR genes in C. ensifolium, the upstream 2000 bp gene sequences of the 31 CeNBS-LRR genes were analyzed to identify the related cis-regulatory elements. In the promoter region of the CeNBS-LRR genes, 19 cis-regulatory elements were identified after manual filtration to exclude those with low relevance (Table S4). These elements are involved in various plant life processes, including growth, development, stress response, hormone regulation, and signal transduction (Figure 6a). Each NBS-LRR gene was found to harbor cis-regulatory elements, with the gene JL021705 containing the highest number (12) and the gene JL000937 having the lowest (3). These cis-regulatory elements were classified into four categories: light-response-related, hormone-response-related, environmental-stress-related, and growth- and development-related. Among them, the most prevalent cis-regulatory elements were hormone-response-related, followed by environmental-stress-related elements (Figure 6b). Furthermore, cis-regulatory elements associated with abscisic acid and jasmonic acid were distributed among most genes, suggesting that CeNBS-LRR genes are mainly involved in the hormone induction process to resist external stress such as abscisic acid and jasmonic acid. The distribution of these cis-regulatory elements varies, with many clustering at the same locus or spanning limited lengths of the sequence.

3.6. Expression Patterns of CeNBS-LRR Genes in Response to Fusarium Wilt Infection

Plant materials of C. ensifolium were sampled at 0 h, 6 h, 12 h, and 24 h after inoculation with F. oxysporum, and the root samples were used for transcriptome analysis. We used transcriptome data to validate the expression patterns of CeNBS-LRR genes at 0 h, 6 h, 12 h, and 24 h post inoculation. After inoculation, different CeNBS-LRR genes showed diverse expression patterns (Figure 7). Among the CeNBS-LRR gene family members, a total of 27 genes showed differential expression patterns, with 13 CeNBS-LRR genes displaying their lowest expression levels at 0 hpi and 9 genes reaching their peak expression levels at 6 hpi. While 17 genes showed a decline in expression levels after 6 hpi, their expression trends varied at 12 hpi and 24 hpi. Five genes reached their peak expression levels at 24 hpi (Figure 7). Overall, the expression levels of most NBS-LRR gene family members exhibited an initial increase followed by a decrease after pathogen infection.
Based on the transcriptome data and expression profiles, eight NBS-LRR genes were selected for real-time fluorescence quantitative experiments to validate the reliability of the transcriptome data. The fluorescence quantification expression trends of most CeNBS-LRR genes were consistent with the transcriptome data (Figure 8). The expression levels of JL00642 and JL014305 showed a significant increasing trend from 0 hpi to 6 hpi, followed by a slight decline at 12 hpi. The expression of JL005200 and JL003306 exhibited a gradual decrease at 6 hpi with mild changes at 12 hpi; JL021699 was upregulated at 6 hpi, followed by a decline at 12 hpi, and a peak at 24 hpi. Additionally, it was noteworthy that the expression of JL006442 and JL014305 increased by more than 3-fold compared to 0 hpi, suggesting their primary involvement in the early disease response.

4. Discussion

C. ensifolium boasts a rich history and legacy in China, is renowned for its unique flower shape and diverse colors, and holds a significant position in the market [37]. However, despite its prominence, the continuous advancement and intensification of the C. ensifolium industry have led to an escalating incidence of diseases. Various pathogens are increasingly developing resistance to traditional chemical agents [38]. This phenomenon profoundly impacts the growth and prosperity of the C. ensifolium industry. Notably, Fusarium wilt, caused by F. oxysporum and often referred to as the ‘cancer of orchids’, stands out as a formidable threat to the health and vitality of C. ensifolium. Given these challenges, breeding C. ensifolium varieties resistant to diseases emerges as a pivotal solution. The completion of the whole-genome sequencing of C. ensifolium has provided a robust foundation for the exploration and identification of resistance genes.
NBS-LRR genes represent one of the most important classes of plant disease resistance genes, with the majority of the currently identified disease resistance genes falling within this class. Examples include the AvrRPS4 and RLM3 genes in A. thaliana, which confer resistance to Pseudomonas syringae, the Pto gene in Lycopersicon esculentum, providing resistance to spotted wilt, the Xa21 gene in O. sativa, imparting resistant to bacterial blight, and the Pm41 gene in T. aestivum, offering resistant against powdery mildew [39,40,41,42,43]. Researchers have found that overexpression of the NLR gene Rps11 in Glycine max can effectively enhance resistance to Phytophthora root rot. In T. aestivum, the CNL class TaRCR1 has been found to regulate downstream disease resistance gene expression by maintaining the balance of reactive oxygen species in plants, thereby reducing the damage caused by the wheat stripe rust pathogen to wheat. Despite these notable findings, there is a paucity of reports on disease resistance-related research in C. ensifolium, and the molecular mechanisms underlying its response to pathogens remain unclear. Therefore, by leveraging the identification of CeNBS-LRR genes through C. ensifolium genome data, the exploration of disease resistance-related genes can provide valuable insights for breeding disease-resistant C. ensifolium varieties. Based on the bioinformatic analysis of the C. ensifolium genome, this study identified a total of 31 CeNBS-LRR genes, including zero members of the TNL family and one member of the RNL family, while the remaining genes belonged to the CNL family. Similar situations have been found in various monocots such as rice, wheat, grapes, sugarcane, and sorghum, indicating a gradual loss of the TNL family members in the evolutionary history of monocot plants [44,45,46]. Although it has been suggested that the number of NBS-LRR genes is positively correlated with genome size, the number of CeNBS-LRR genes is extremely low compared to common agricultural and horticultural crops, and it is speculated that this may be related to the growing environment and the small number of ancestors [13]. In the phylogenetic tree, the CeNBS-LRR genes were clustered into CNL and RNL, similar to A. thaliana, O. sativa, and Phalaenopsis equestris. TNL genes form a distinct cluster separate from CNL genes, indicating a distant relationship between the TNL and CNL classes. None of the genes clustered with TNL; presumably, the TNL category was lost in early evolution, which is consistent with the fact that monocots contain very few or no TNL genes. In addition, noticeable clustering phenomena between the RNL subfamily and the CNL subfamily are observed, suggesting a high degree of homology between RNL and CNL proteins. Some researchers have reported that RNL genes and CNL genes share a common ancestor [17]. Only one RNL gene was identified in C. ensifolium, a pattern consistent with observations in other monocots, where only a very limited number of RNL genes are present [47,48]. It is speculated that RNL genes evolved from CNL genes and may play a specific role in disease resistance, akin to the RPW8 gene in Arabidopsis, which exhibits significant resistance to powdery mildew [49]. Additionally, CNL genes are considered to be an older category with a higher abundance in plants [50]. Furthermore, the number of NBS-LRR genes in C. ensifolium is extremely low, a phenomenon observed in other orchids such as Apostasia shenzhenica, Gastrodia elata, and P. equestris, where only a small number of NBS-LRR genes have been identified [51]. These orchids also lack TNL genes in their genomes. In contrast to common crops like Arabidopsis, rice, wheat, and tomato, orchids generally possess a significantly lower number of NBS-LRR genes. This discrepancy could be attributed to gene loss events in the ancestral genome of orchids, which experienced fewer expansions of gene families due to their relatively uniform habitat environments.
In the conserved domain and motif analysis of the CeNBS-LRR genes, representative motifs of the NBS-LRR gene family such as P-loop, Kinse2, GLPL, RNBS-B, and RNBS-D are all found in CeNBS-LRR genes. Motif positions are arranged in the physical structure order of motif10-motif1-motif4-motif3-motif2-motif5-motif9-motif8, which is typically consistent with the typical structure of NBS-LRR genes in other plants [52]. Within the same subfamily, different genes maintained a similar motif arrangement sequence, with genes exhibiting closer phylogenetic relationships showing higher sequence similarity and functional similarity. Except for motif7 and motif10, the other motifs are highly conserved. P-loop, GLPL, and RNBS-B constitute the most conserved part of the NB-ARC domain in C. ensifolium, suggesting their important role in disease resistance response. Gene structure analysis revealed significant differences in the number of introns and exons among the CeNBS-LRR genes, with exon counts ranging from 1 to 6. The number of domains is proportional to the number of exons, and overall, the number is relatively small. Approximately half of the genes have zero introns, suggesting that exon loss events may have occurred during early evolution.
Cis-acting element analysis enables the visual depiction of gene expression levels across different elements, facilitating the prediction of potential gene functions and the biological processes they participate in [53]. In our analysis, jasmonic acid, hypoxia-specific induction, and abscisic acid were the top three elements in terms of proportion. Jasmonic acid can induce the production of stress-resistant genes when plants are subjected to biotic stress, enabling them to defend themselves from damage. Exogenous treatment with jasmonic acid has been shown to significantly enhance plant disease resistance [54]. Abscisic acid is another important regulatory factor in plants. When subjected to external environmental, biotic, and abiotic stresses, it helps alleviate sustained damage to plants by initiating stress responses through signal transduction pathways [55]. Therefore, it is plausible to suggest that most CeNBS-LRR genes may be involved in various stress responses through hormonal regulation, a phenomenon similar to that in Dendrobium officinale [56].
Homologous analysis can reveal the correlation between homologous genes across different species or the occurrence of gene fragment duplication within the same species. The collinearity results show that the only RNL gene (JL005200) in C. ensifolium is homologous to those in A. thaliana and O. sativa, suggesting that the CeNBS-LRR gene family is highly conservative in evolution. There are more collinear regions between C. ensifolium and O. sativa compared to those between C. ensifolium and A. thaliana, indicating that the closer the relationship between species, the more unified the evolutionary trend in gene families. This homologous gene can be used to predict functions based on reports in other species. It is well established that plants trigger their own immune response upon pathogen infection, which leads to the upregulation of specific disease-resistant genes. Therefore, we conducted further analysis on the expression changes of 27 CeNBS-LRR genes at different time points after pathogen inoculation, and subsequently validated the findings using qRT-PCR. Remarkably, the results were consistent with the transcriptome data. Interestingly, different genes exhibited distinct expression patterns, with each reaching its maximum peaks at different time points post-inoculation. Specifically, the expression of JL006442 and JL014305 displayed a substantial increase at 6 hpi, and reaching their maximum expression levels. Conversely, JL003306 and JL005200 showed linear downregulation at 6 hpi. JL021699 showed an initial increase followed by a decrease in expression levels at different time points post-inoculation, ultimately reaching a peak at 24 hpi. These findings suggested that JL006442 and JL014305 may play key roles in resisting pathogen-induced stress. Further functional validation and protein interaction analysis are warranted for these candidate genes to provide a theoretical basis for disease resistance breeding in C. ensifolium.

5. Conclusions

In conclusion, this study identified a total of 31 CeNBS-LRR family genes in the whole genome of C. ensifolium and analyzed their physicochemical properties. Based on their diverse structures, 31 CeNBS-LRR family members were classified into two major categories. Different categories of CeNBS-LRR genes show distinct differences in their domains, with RNL genes featuring a unique RPW8 domain. The conserved motifs exhibited variations among genes of different subfamilies, while the motifs of NB-ARC domains were similar among different subfamilies. Only one pair of duplicated genes was identified in the CeNBS-LRR gene family, suggesting that the CeNBS-LRR gene family exhibits conservative evolution. Promoter analysis revealed that the most cis-acting elements are associated with plant stress response, growth, and development. Furthermore, the gene expression profiling and qRT-PCR results demonstrate that CeNBS-LRR has different trends in response to Fusarium wilt infection with varying degrees of expression. In summary, this study provides a solid theoretical foundation for the exploration of disease-resistant genes in C. ensifolium and for genetic breeding aimed at enhancing disease resistance in C. ensifolium varieties.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae10060634/s1, Figure S1: The conserved motif analysis of the CeNBS-LRR gene; Table S1: Average FPKM value of CeNBS-LRR genes transcriptome data before and after Fusarium wilt infection; Table S2: Primer information used in this study; Table S3: Synteny analysis of CeNBS-LRR gene IDs among C. ensifolium, A. thaliana, and O. sativa genomes; Table S4: Details of cis-acting elements in the promoter region of 31 CeNBS-LRR genes (2000 bp upstream of the initiation codon).

Author Contributions

Q.-H.Z. and Y.A. conceived and designed the experiments. L.Y. performed the experiments and wrote the manuscript. B.-X.S., J.-J.L., Y.-Y.L. and S.-Y.C. conducted the bioinformatics analysis. C.-Y.F. and Y.T. contributed materials. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by The Fujian Agriculture and Forestry University Science and Technology Innovation Program (KFB23052), The Provincial Ministry Joint Construction of State Key Laboratory of Ecological Prevention and Control of Crop Pests in Fujian and Taiwan Project (KFXZ23001), and National Key Research and Development Program of China (2023YFD16005004).

Data Availability Statement

The sequences of C. ensifolium used in this study are available at the National Genomics Data Center (NGDC). The RNA-Seq data have been deposited in NCBI under SRA accession codes: PRJNA1096825.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ai, Y.; Li, Z.; Sun, W.-H.; Chen, J.; Zhang, D.; Ma, L.; Zhang, Q.-H.; Chen, M.-K.; Zheng, Q.-D.; Liu, J.-F.; et al. The Cymbidium genome reveals the evolution of unique morphological traits. Hortic. Res. 2021, 8, 255–264. [Google Scholar] [CrossRef] [PubMed]
  2. Li, X.; Liu, L.; Sun, S.; Li, Y.; Jia, L.; Ye, S.; Yu, Y.; Dossa, K.; Luan, Y. Transcriptome analysis reveals the key pathways and candidate genes involved in salt stress responses in Cymbidium ensifolium leaves. BMC Plant Biol. 2023, 23, 64. [Google Scholar] [CrossRef] [PubMed]
  3. Paul, S.K.; Mahmud, N.U.; Gupta, D.R.; Alam, M.N.; Chakraborty, M.; Islam, M.T. First Report of Fusarium sacchari Causing Sugarcane Wilt in Bangladesh. Plant Dis. 2022, 106, 319. [Google Scholar] [CrossRef] [PubMed]
  4. Jin-Ai, Y.; Peng, H.; Cheng-Zhong, L.; De-Yi, Y. Stem rot on Cymbidium ensifolium (Orchidaceae) caused by Fusarium oxysporum in China. Can. J. Plant. Pathol. 2017, 40, 105–108. [Google Scholar] [CrossRef]
  5. Chung, W.C.; Chen, L.W.; Huang, J.H.; Huang, H.C.; Chung, W.H. A new ‘forma specialis’ of Fusarium solani causing leaf yellowing of Phalaenopsis. Plant Pathol. 2010, 60, 244–252. [Google Scholar] [CrossRef]
  6. Staskawicz, B.J.; Ausubel, F.M.; Baker, B.J.; Ellis, J.G.; Jones, J.D.G. Molecular Genetics of Plant Disease Resistance. Science 1995, 268, 661–667. [Google Scholar] [CrossRef]
  7. Wei, W.R.; Yue, H.L.; Nie, Y.X.; Chen, T.X. First Report of Colletotrichum siamense Causing Daylily (Hemerocallis citrina) Anthracnose in China. Plant Dis. 2022, 106, 1061. [Google Scholar] [CrossRef] [PubMed]
  8. Ajithkumar, K.; Savitha, A.S.; Mahadevakumar, S.; Sujatha, M.; Maharachchikumbura, S.S.N.; Sreenivasa, M.Y.; Renuka, M.; Yenjerappa, S.T. First Report of Powdery Mildew Caused by Erysiphe diffusa on Cluster Bean in India. Plant. Dis. 2022, 106, 3203. [Google Scholar] [CrossRef]
  9. Ji, H.M.; Mao, H.Y.; Li, S.J.; Feng, T.; Zhang, Z.Y.; Cheng, L.; Luo, S.J.; Borkovich, K.A.; Ouyang, S.Q. Fol-milR1, a pathogenicity factor of Fusarium oxysporum, confers tomato wilt disease resistance by impairing host immune responses. New Phytol. 2021, 232, 705–718. [Google Scholar] [CrossRef]
  10. Kourelis, J.; van der Hoorn, R.A.L. Defended to the Nines: 25 Years of Resistance Gene Cloning Identifies Nine Mechanisms for R Protein Function. Plant Cell 2018, 30, 285–299. [Google Scholar] [CrossRef]
  11. Ellis, J.G.; Lawrence, G.J.; Dodds, P.N. Further analysis of gene-for-gene disease resistance specificity in flax. Mol. Plant Pathol. 2007, 8, 103–109. [Google Scholar] [CrossRef] [PubMed]
  12. DeYoung, B.J.; Innes, R.W. Plant NBS-LRR proteins in pathogen sensing and host defense. Nat. Immunol. 2006, 7, 1243–1249. [Google Scholar] [CrossRef] [PubMed]
  13. Shao, Z.Q.; Xue, J.Y.; Wang, Q.; Wang, B.; Chen, J.Q. Revisiting the Origin of Plant NBS-LRR Genes. Trends Plant Sci. 2019, 24, 9–12. [Google Scholar] [CrossRef] [PubMed]
  14. McDowell, J.M.; Woffenden, B.J. Plant disease resistance genes: Recent insights and potential applications. Trends Biotechnol. 2003, 21, 178–183. [Google Scholar] [CrossRef] [PubMed]
  15. Kobe, B.; Kajava, A.V. The leucine-rich repeat as a protein recognition motif. Curr. Opin. Struct. Biol. 2001, 11, 725–732. [Google Scholar] [CrossRef] [PubMed]
  16. Yu, X.; Zhong, S.; Yang, H.; Chen, C.; Chen, W.; Yang, H.; Guan, J.; Fu, P.; Tan, F.; Ren, T.; et al. Identification and Characterization of NBS Resistance Genes in Akebia trifoliata. Front. Plant Sci. 2021, 12, 758559. [Google Scholar] [CrossRef] [PubMed]
  17. Meyers, B.C.; Kaushik, S.; Nandety, R.S. Evolving disease resistance genes. Curr. Opin. Plant Biol. 2005, 8, 129–134. [Google Scholar] [CrossRef] [PubMed]
  18. Bai, J.; Pennill, L.A.; Ning, J.; Lee, S.W.; Ramalingam, J.; Webb, C.A.; Zhao, B.; Sun, Q.; Nelson, J.C.; Leach, J.E.; et al. Diversity in Nucleotide Binding Site–Leucine-Rich Repeat Genes in Cereals. Genome Res. 2002, 12, 1871–1884. [Google Scholar] [CrossRef] [PubMed]
  19. Meyers, B.C.; Kozik, A.; Griego, A.; Kuang, H.; Michelmore, R.W. Genome-wide analysis of NBS-LRR-encoding genes in Arabidopsis. Plant Cell 2003, 15, 809–834. [Google Scholar] [CrossRef] [PubMed]
  20. Liu, W.; Ghouri, F.; Yu, H.; Li, X.; Yu, S.; Shahid, M.Q.; Liu, X. Genome wide re-sequencing of newly developed Rice Lines from common wild rice (Oryza rufipogon Griff.) for the identification of NBS-LRR genes. PLoS ONE 2017, 12, e0180662. [Google Scholar] [CrossRef]
  21. Liu, J.; Qiao, L.Y.; Zhang, X.J.; Li, X.; Zhan, H.X.; Guo, H.J.; Zheng, J.; Chang, Z.J. Genome-wide identification and resistance expression analysis of the NBS gene family in Triticum urartu. Genes Genom. 2017, 39, 611–621. [Google Scholar] [CrossRef]
  22. Ameline-Torregrosa, C.; Wang, B.B.; O’Bleness, M.S.; Deshpande, S.; Zhu, H.; Roe, B.; Young, N.D.; Cannon, S.B. Identification and characterization of nucleotide-binding site-leucine-rich repeat genes in the model plant Medicago truncatula. Plant Physiol. 2008, 146, 5–21. [Google Scholar] [CrossRef] [PubMed]
  23. Wang, T.; Jia, Z.H.; Zhang, J.Y.; Liu, M.; Guo, Z.R.; Wang, G. Identification and Analysis of NBS-LRR Genes in Actinidia chinensis Genome. Plants 2020, 9, 1350. [Google Scholar] [CrossRef] [PubMed]
  24. Garcia-Hernandez, M.; Berardini, T.Z.; Chen, G.; Crist, D.; Doyle, A.; Huala, E.; Knee, E.; Lambrecht, M.; Miller, N.; Mueller, L.A.; et al. TAIR: A resource for integrated Arabidopsis data. Funct. Integr. Genomics 2002, 2, 239–253. [Google Scholar] [CrossRef] [PubMed]
  25. Lu, S.; Wang, J.; Chitsaz, F.; Derbyshire, M.K.; Geer, R.C.; Gonzales, N.R.; Gwadz, M.; Hurwitz, D.I.; Marchler, G.H.; Song, J.S.; et al. CDD/SPARCLE: The conserved domain database in 2020. Nucleic Acids Res. 2020, 48, D265–D268. [Google Scholar] [CrossRef] [PubMed]
  26. Letunic, I.; Khedkar, S.; Bork, P. SMART: Recent updates, new developments and status in 2020. Nucleic Acids Res. 2021, 49, D458–D460. [Google Scholar] [CrossRef] [PubMed]
  27. Tamura, K.; Stecher, G.; Kumar, S. MEGA11: Molecular Evolutionary Genetics Analysis Version 11. Mol. Biol. Evol. 2021, 38, 3022–3027. [Google Scholar] [CrossRef]
  28. Xie, J.; Chen, Y.; Cai, G.; Cai, R.; Hu, Z.; Wang, H. Tree Visualization By One Table (tvBOT): A web application for visualizing, modifying and annotating phylogenetic trees. Nucleic Acids Res. 2023, 51, W587–W592. [Google Scholar] [CrossRef] [PubMed]
  29. Chou, K.C.; Shen, H.B. Cell-PLoc: A package of Web servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 2008, 3, 153–162. [Google Scholar] [CrossRef]
  30. Gasteiger, E.; Gattiker, A.; Hoogland, C.; Ivanyi, I.; Appel, R.D.; Bairoch, A. ExPASy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res. 2003, 31, 3784–3788. [Google Scholar] [CrossRef]
  31. Chen, C.; Chen, H.; Zhang, Y.; Thomas, H.R.; Frank, M.H.; He, Y.; Xia, R. TBtools: An Integrative Toolkit Developed for Interactive Analyses of Big Biological Data. Mol. Plant 2020, 13, 1194–1202. [Google Scholar] [CrossRef] [PubMed]
  32. Lescot, M.; Dehais, P.; Thijs, G.; Marchal, K.; Moreau, Y.; Van de Peer, Y.; Rouze, P.; Rombauts, S. PlantCARE, a database of plant cis-acting regulatory elements and a portal to tools for in silico analysis of promoter sequences. Nucleic Acids Res. 2002, 30, 325–327. [Google Scholar] [CrossRef] [PubMed]
  33. Lupas, A.; Van Dyke, M.; Stock, J. Predicting coiled coils from protein sequences. Science 1991, 252, 1162–1164. [Google Scholar] [CrossRef] [PubMed]
  34. Shao, Z.Q.; Xue, J.Y.; Wu, P.; Zhang, Y.M.; Wu, Y.; Hang, Y.Y.; Wang, B.; Chen, J.Q. Large-Scale Analyses of Angiosperm Nucleotide-Binding Site-Leucine-Rich Repeat Genes Reveal Three Anciently Diverged Classes with Distinct Evolutionary Patterns. Plant Physiol. 2016, 170, 2095–2109. [Google Scholar] [CrossRef] [PubMed]
  35. Wang, J.; Song, W.; Chai, J. Structure, biochemical function, and signaling mechanism of plant NLRs. Mol. Plant 2023, 16, 75–95. [Google Scholar] [CrossRef] [PubMed]
  36. Zhang, H.; Chen, C.; Li, L.; Tan, X.; Wei, Z.; Li, Y.; Li, J.; Yan, F.; Chen, J.; Sun, Z. A rice LRR receptor-like protein associates with its adaptor kinase OsSOBIR1 to mediate plant immunity against viral infection. Plant Biotechnol. J. 2021, 19, 2319–2332. [Google Scholar] [CrossRef]
  37. Ke, Y.-J.; Zheng, Q.-D.; Yao, Y.-H.; Ou, Y.; Chen, J.-Y.; Wang, M.-J.; Lai, H.-P.; Yan, L.; Liu, Z.-J.; Ai, Y. Genome-Wide Identification of the MYB Gene Family in Cymbidium ensifolium and Its Expression Analysis in Different Flower Colors. Int. J. Mol. Sci. 2021, 22, 13245. [Google Scholar] [CrossRef] [PubMed]
  38. Ahmad, S.; Chen, G.; Huang, J.; Yang, K.; Hao, Y.; Zhou, Y.; Zhao, K.; Lan, S.; Liu, Z.; Peng, D. Beauty and the pathogens: A leaf-less control presents a better image of Cymbidium orchids defense strategy. Front. Plant Sci. 2022, 13, 1001427. [Google Scholar] [CrossRef]
  39. Saucet, S.B.; Ma, Y.; Sarris, P.F.; Furzer, O.J.; Sohn, K.H.; Jones, J.D.G. Two linked pairs of Arabidopsis TNL resistance genes independently confer recognition of bacterial effector AvrRps4. Nat. Commun. 2015, 6, 6338. [Google Scholar] [CrossRef]
  40. Pedley, K.F.; Martin, G.B. Molecular Basis of Pto-Mediated Resistance to Bacterial Speck Disease in Tomato. Annu. Rev. Phytopathol. 2003, 41, 215–243. [Google Scholar] [CrossRef]
  41. Ercoli, M.F.; Luu, D.D.; Rim, E.Y.; Shigenaga, A.; Teixeira de Araujo, A.; Chern, M.; Jain, R.; Ruan, R.; Joe, A.; Stewart, V.; et al. Plant immunity: Rice XA21-mediated resistance to bacterial infection. Proc. Natl. Acad. Sci. USA 2022, 119, e2121568119. [Google Scholar] [CrossRef] [PubMed]
  42. Li, M.; Dong, L.; Li, B.; Wang, Z.; Xie, J.; Qiu, D.; Li, Y.; Shi, W.; Yang, L.; Wu, Q.; et al. A CNL protein in wild emmer wheat confers powdery mildew resistance. New Phytol. 2020, 228, 1027–1037. [Google Scholar] [CrossRef] [PubMed]
  43. Staal, J.; Kaliff, M.; Dewaele, E.; Persson, M.; Dixelius, C. RLM3, a TIR domain encoding gene involved in broad-range immunity of Arabidopsis to necrotrophic fungal pathogens. Plant J. 2008, 55, 188–200. [Google Scholar] [CrossRef] [PubMed]
  44. Meyers, B.C.; Dickerman, A.W.; Michelmore, R.W.; Sivaramakrishnan, S.; Sobral, B.W.; Young, N.D. Plant disease resistance genes encode members of an ancient and diverse protein family within the nucleotide-binding superfamily. Plant J. 1999, 20, 317–332. [Google Scholar] [CrossRef] [PubMed]
  45. Jiang, Z.; Zhao, M.; Qin, H.; Li, S.; Yang, X. Genome-wide analysis of NBS-LRR genes revealed contribution of disease resistance from Saccharum spontaneum to modern sugarcane cultivar. Front. Plant Sci. 2023, 14, 1091567. [Google Scholar] [CrossRef]
  46. Tetreault, H.M.; Grover, S.; Scully, E.D.; Gries, T.; Palmer, N.A.; Sarath, G.; Louis, J.; Sattler, S.E. Global Responses of Resistant and Susceptible Sorghum (Sorghum bicolor) to Sugarcane Aphid (Melanaphis sacchari). Front. Plant Sci. 2019, 10, 145. [Google Scholar] [CrossRef] [PubMed]
  47. Li, Q.; Jiang, X.-M.; Shao, Z.-Q. Genome-Wide Analysis of NLR Disease Resistance Genes in an Updated Reference Genome of Barley. Front. Genet. 2021, 12, 694682. [Google Scholar] [CrossRef] [PubMed]
  48. Qian, L.-H.; Wang, Y.; Chen, M.; Liu, J.; Lu, R.-S.; Zou, X.; Sun, X.-Q.; Zhang, Y.-M. Genome-wide Identification and Evolutionary Analysis of NBS-LRR Genes From Secale cereale. Front. Genet. 2021, 12, 771814. [Google Scholar] [CrossRef] [PubMed]
  49. Xiao, S.; Ellwood, S.; Calis, O.; Patrick, E.; Li, T.; Coleman, M.; Turner, J.G. Broad-spectrum mildew resistance in Arabidopsis thaliana mediated by RPW8. Science 2001, 291, 118–120. [Google Scholar] [CrossRef]
  50. Cannon, S.B.; May, G.D.; Jackson, S.A. Three Sequenced Legume Genomes and Many Crop Species: Rich Opportunities for Translational Genomics. Plant Physiol. 2009, 151, 970–977. [Google Scholar] [CrossRef]
  51. Xue, J.Y.; Zhao, T.; Liu, Y.; Liu, Y.; Zhang, Y.X.; Zhang, G.Q.; Chen, H.; Zhou, G.C.; Zhang, S.Z.; Shao, Z.Q. Genome- Wide Analysis of the Nucleotide Binding Site Leucine-Rich Repeat Genes of Four Orchids Revealed Extremely Low Numbers of Disease Resistance Genes. Front. Genet. 2019, 10, 1286. [Google Scholar] [CrossRef]
  52. Loutre, C.; Wicker, T.; Travella, S.; Galli, P.; Scofield, S.; Fahima, T.; Feuillet, C.; Keller, B. Two different CC-NBS-LRR genes are required for Lr10-mediated leaf rust resistance in tetraploid and hexaploid wheat. Plant J. 2009, 60, 1043–1054. [Google Scholar] [CrossRef] [PubMed]
  53. Rushton, P.J.; Reinstädler, A.; Lipka, V.; Lippok, B.; Somssich, I.E. Synthetic plant promoters containing defined regulatory elements provide novel insights into pathogen- and wound-induced signaling. Plant Cell 2002, 14, 749–762. [Google Scholar] [CrossRef] [PubMed]
  54. Spoel, S.H.; Koornneef, A.; Claessens, S.M.C.; Korzelius, J.P.; Van Pelt, J.A.; Mueller, M.J.; Buchala, A.J.; Métraux, J.-P.; Brown, R.; Kazan, K.; et al. NPR1 Modulates Cross-Talk between Salicylate- and Jasmonate-Dependent Defense Pathways through a Novel Function in the Cytosol. Plant Cell 2003, 15, 760–770. [Google Scholar] [CrossRef] [PubMed]
  55. Yang, W.; Zhang, W.; Wang, X. Post-translational control of ABA signalling: The roles of protein phosphorylation and ubiquitination. Plant Biotechnol. J. 2016, 15, 4–14. [Google Scholar] [CrossRef]
  56. Yang, J.; Xiong, C.; Li, S.; Zhou, C.; Li, L.; Xue, Q.; Liu, W.; Niu, Z.; Ding, X. Evolution patterns of NBS genes in the genus Dendrobium and NBS-LRR gene expression in D. officinale by salicylic acid treatment. BMC Plant Biol. 2022, 22, 529. [Google Scholar]
Figure 1. Phylogenetic tree of NBS-LRR proteins from C. ensifolium and A. thaliana. Different colors represent different NBS-LRR subfamilies. Solid squares and circles, respectively, represent C. ensifolium and A. thaliana. Percent bootstrap values (1000 iterations) are indicated in every branch.
Figure 1. Phylogenetic tree of NBS-LRR proteins from C. ensifolium and A. thaliana. Different colors represent different NBS-LRR subfamilies. Solid squares and circles, respectively, represent C. ensifolium and A. thaliana. Percent bootstrap values (1000 iterations) are indicated in every branch.
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Figure 2. Localization and distribution of 31 NBS-LRR genes onto 8 C. ensifolium chromosomes. The scale represents the chromosomal distances (Mbp). The colors of chromosomes represent the gene distribution density on different chromosomes: red represents high gene density, while blue represents low gene density.
Figure 2. Localization and distribution of 31 NBS-LRR genes onto 8 C. ensifolium chromosomes. The scale represents the chromosomal distances (Mbp). The colors of chromosomes represent the gene distribution density on different chromosomes: red represents high gene density, while blue represents low gene density.
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Figure 3. Conserved motif and gene structure analysis of NBS-LRR genes in C. ensifolium. (a). Conserved motifs are shown by colored boxes. (b). Conserved domains are shown by colored columns. (c). Distribution of introns and exons.
Figure 3. Conserved motif and gene structure analysis of NBS-LRR genes in C. ensifolium. (a). Conserved motifs are shown by colored boxes. (b). Conserved domains are shown by colored columns. (c). Distribution of introns and exons.
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Figure 4. Collinearity analysis of NBS-LRR genes among C. ensifolium, A. thaliana, and O. sativa. Gray lines represent all syntenic areas between C. ensifolium and the other two genomes. The collinear pairs of NBS-LRR genes are highlighted by the blue lines.
Figure 4. Collinearity analysis of NBS-LRR genes among C. ensifolium, A. thaliana, and O. sativa. Gray lines represent all syntenic areas between C. ensifolium and the other two genomes. The collinear pairs of NBS-LRR genes are highlighted by the blue lines.
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Figure 5. Collinearity analysis of CeNBS-LRR genes on chromosomes. Differently colored bars represent different chromosomes. The green line between chromosomes indicates segmentally duplicated genes. The heap map of bars represents the gene distribution density on different chromosomes.
Figure 5. Collinearity analysis of CeNBS-LRR genes on chromosomes. Differently colored bars represent different chromosomes. The green line between chromosomes indicates segmentally duplicated genes. The heap map of bars represents the gene distribution density on different chromosomes.
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Figure 6. Analysis of the cis-elements of the promoter of the NBS-LRR gene of C. ensifolium. (a). The statistics of the cis-acting elements were visualized by a heat map and 19 cis-acting elements were classified into four categories represented by different colors. (b). Distribution of NBS-LRR gene cis-acting elements. Various elements are represented by the blocks of different colors.
Figure 6. Analysis of the cis-elements of the promoter of the NBS-LRR gene of C. ensifolium. (a). The statistics of the cis-acting elements were visualized by a heat map and 19 cis-acting elements were classified into four categories represented by different colors. (b). Distribution of NBS-LRR gene cis-acting elements. Various elements are represented by the blocks of different colors.
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Figure 7. The expression of CeNBS-LRR genes in response to Fusarium wilt infection post-inoculation at 0 h, 6 h, 12 h, and 24 h.
Figure 7. The expression of CeNBS-LRR genes in response to Fusarium wilt infection post-inoculation at 0 h, 6 h, 12 h, and 24 h.
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Figure 8. qRT-PCR analysis of eight NBS-LRR genes in C. ensifolium in response to Fusarium wilt infection. Error bars indicate the SD of three biological replicates.
Figure 8. qRT-PCR analysis of eight NBS-LRR genes in C. ensifolium in response to Fusarium wilt infection. Error bars indicate the SD of three biological replicates.
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Table 1. Classification of the NBS-LRR genes in the C. ensifolium, A. thaliana, and O. sativa genomes.
Table 1. Classification of the NBS-LRR genes in the C. ensifolium, A. thaliana, and O. sativa genomes.
TypeDomainC. ensifoliumA. thalianaO. sativa
CNLCC NBS LRR1118199
CNCC NBS9361
NLNBS LRR432123
NNBS66109
TNLTIR NBS LRR01010
TNTIR NBS023
RNLRPW8 NBS LRR150
RNRPW8 NBS010
Total 31168495
Table 2. Physicochemical properties and subcellular localization of NBS-LRR family proteins in Cymbidium ensifolium.
Table 2. Physicochemical properties and subcellular localization of NBS-LRR family proteins in Cymbidium ensifolium.
Sequence IDLength/bpSize/aaMW/KdapIIIAIGRAVYSubcellular Location
JL00093769323019,641.85.4648.0899.61−0.381Cytoplasm. Nucleus.
JL00093935791192136,675.626.0846.76102.42−0.243Cytoplasm.
JL0033062655884100,476.439.2357.12103.82−0.16Cytoplasm.
JL005200245781893,067.126.3247.07104.82−0.145Cytoplasm.
JL00571631921063121,322.265.6554.08106.01−0.114Cell membrane. Cytoplasm.
JL00644237051234138,792.657.1344.0495.43−0.252Cell membrane. Cytoplasm.
JL00644531561051118,860.115.5245.63103.42−0.153Cell membrane. Cytoplasm.
JL0143052865954109,640.256.2742.86104.25−0.233Cytoplasm.
JL01514332791092124,529.056.2244.61101.77−0.187Cytoplasm.
JL015159216672182,248.036.645.93103.43−0.21Cytoplasm.
JL01803234081135128,937.116.4543.25101.26−0.2Cytoplasm.
JL01803634171138128,968.936.4545.21100.07−0.177Cytoplasm.
JL018038222674184,065.557.2642.34106.67−0.119Cytoplasm.
JL021699150049958,741.935.4752.3294.33−0.323Cytoplasm.
JL02170560019922,529.594.6746.8994.47−0.184Cytoplasm. Nucleus.
JL02170738412714,328.636.9140.37104.96−0.102Cytoplasm.
JL022987195665174,820.487.5739.599.69−0.28Cell membrane. Cytoplasm.
JL023790242480793,218.675.4356.4799.42−0.247Cytoplasm.
JL02445631501049119,420.277.9940.32102.76−0.202Cytoplasm.
JL02462732161071121,917.885.6751.0597.4−0.19Cell membrane. Cytoplasm.
JL0247622871956110,390.186.7651.6795.65−0.292Cytoplasm.
JL024805152750857,241.58.6759.5495.08−0.267Cell membrane. Cytoplasm.
JL02480675625128,129.138.8644.4105.620.063Cytoplasm.
JL024807198065974,718.977.1949.5199.59−0.113Cytoplasm.
JL024816232277387,897.626.7152.46105.27−0.182Cytoplasm.
JL0256552943980113,173.426.4750.3195.3−0.252Cytoplasm.
JL02593270223327,012.085.362.7297.04−0.141Cytoplasm. Nucleus.
JL02593397232337,748.465.3761.9496.56−0.218Cytoplasm.
JL027518152450757,848.738.944.18106.77−0.084Cell membrane. Cytoplasm.
JL027520188465475,060.628.741.99105.7−0.1Cell membrane. Cytoplasm.
JL028743147048956,510.415.747.0885.75−0.504Chloroplast. Cytoplasm.
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Yan, L.; Su, B.-X.; Li, J.-J.; Li, Y.-Y.; Chen, S.-Y.; Feng, C.-Y.; Tian, Y.; Ai, Y.; Zhang, Q.-H. Genome-Wide Identification of Nucleotide-Binding Site–Leucine-Rich Repeat Gene Family in Cymbidium ensifolium and Expression Profiles in Response to Fusarium Wilt Infection. Horticulturae 2024, 10, 634. https://doi.org/10.3390/horticulturae10060634

AMA Style

Yan L, Su B-X, Li J-J, Li Y-Y, Chen S-Y, Feng C-Y, Tian Y, Ai Y, Zhang Q-H. Genome-Wide Identification of Nucleotide-Binding Site–Leucine-Rich Repeat Gene Family in Cymbidium ensifolium and Expression Profiles in Response to Fusarium Wilt Infection. Horticulturae. 2024; 10(6):634. https://doi.org/10.3390/horticulturae10060634

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Yan, Lu, Bin-Xian Su, Jin-Jin Li, Yu-Yan Li, Shu-Yi Chen, Cai-Yun Feng, Yang Tian, Ye Ai, and Qing-Hua Zhang. 2024. "Genome-Wide Identification of Nucleotide-Binding Site–Leucine-Rich Repeat Gene Family in Cymbidium ensifolium and Expression Profiles in Response to Fusarium Wilt Infection" Horticulturae 10, no. 6: 634. https://doi.org/10.3390/horticulturae10060634

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