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ISSN : 1225-5009(Print)
ISSN : 2287-772X(Online)
Flower Research Journal Vol.33 No.1 pp.34-48
DOI : https://doi.org/10.11623/frj.2025.33.1.05

Transcriptome Analysis of Four Cultivars of Lilium spp. Infected by Cucumber mosaic virus

Yun-Im Kang1, Youn Jung Choi1, Kyung Hye Seo1, Myung Suk Ahn1, Hyun Hwan Jung1, Su Young Lee1, Young-Ran Lee1, Yun-Jae Ahn2,3*
1Floriculture Research Division, National Institute of Horticultural & Herbal Science, Wanju-gun 55365, Korea
2Department of Horticultural Science, Kyungpook National University, Daegu 41566, Korea
3Institute of Agricultural Science and Technology, Kyungpook National University, Daegu 41566, Korea


Correspondence to Yun-Jae Ahn Tel: +82-53-950-5726 E-mail: yjahn0121@gmail.com ORCID: 0000-0002-6510-3532
24/01/2025 17/02/2025

Abstract


Cucumber mosaic virus (CMV) poses a considerable threat to a diverse array of crops in global agriculture. CMV impacts commercially important cut lilies by diminishing both yield and flower quality. We used RNA sequencing (RNA-seq) to investigate the changes in gene expression in the leaves and bulbs of four distinct cultivars of cut lily, ‘Cancun,’ ‘Brunello,’ ‘Connecticut King,’ and ‘Casa Blanca’ following CMV infection. Notably, CMV affected photosynthetic processes by significantly downregulating genes associated with photosynthesis. In addition, CMV infection was detrimental to chloroplast function and energy production. We observed differential expression of genes associated with both dominant and recessive resistance pathways that are crucial for preventing virus entry, replication, and systemic spread within the plant. Based on functional annotation and differential gene expression analysis, we identified the regulatory genes involved in triggering immune responses, modulating signal transduction, and specific host factors during CMV infection. To validate the RNA-seq findings, we selected four genes involved in resistance, virus multiplication, and virus spread and analyzed them using real-time quantitative reverse transcription PCR (qRT-PCR) with specific primers. The qRT-PCR results aligned closely with those from RNA-seq, showing consistent fold-change responses for the genes that were differentially expressed, indicating that the RNA-seq results were reliable. These results deepen our understanding of the complex genetics behind plant-virus interactions while also providing information for breeding programs that aim to develop CMV-resistant lily cultivars.



differentially expressed genes , dominant resistance , lily , recessive resistance , RNA sequencing

초록

    Introduction

    Cucumber mosaic virus (CMV) is a widely prevalent and economically significant pathogen that affects a broad range of agricultural crops globally (Ando et al. 2019). This virus is classified within the genus Cucumovirus and the family Bromoviridae, and has been documented to infect over 1,200 plant species, thereby causing considerable damage and economic losses (Fan et al. 2019). By interfering with normal plant physiological processes, CMV often leads to stunted growth, the appearance of mosaic patterns on leaves, and a reduction in productivity, which ultimately results in diminished crop yield and quality (Ando et al. 2019;Fan et al. 2019;Kang et al. 2010).

    CMV poses a severe threat to cut lilies, which are crucial commercial crops in the floriculture industry (Chung et al. 2003;Goo et al. 2013;Kim et al. 2001;Zhang et al. 2019). The symptoms of CMV infection in lilies range from leaf mosaics and necrotic spots to severe stunting, contributing to reduced aesthetic value and commercial viability (Chung et al. 2003). These symptoms not only decrease the marketability of lilies but also lead to substantial financial losses owing to reduced flower quality and bulb yield (Kim et al. 2001;Zhang et al. 2019).

    Understanding the resistance mechanisms associated with plant-virus interactions is essential for developing effective strategies to combat pathogens like CMV. These resistance mechanisms against CMV prevent virus entry and uncoating, reduce restricted replication, and obstruct long-distance viral movement within host cells (Ando et al. 2019;Kumar and Dasgupta 2021;Lecoq et al. 2004;Liu et al. 2019;Sett et al. 2022). Plant defense mechanisms against pathogens include intricate gene-for-gene interactions, in which resistance (R) genes respond to pathogenic avirulence (Avr) genes, triggering the activation of immune responses through dominant pathways (Kang et al. 2005;Kim et al. 2021;Takahashi et al. 2002). Recessive resistance arises when specific host factors necessary for successful pathogen invasion and proliferation are absent, thereby preventing the infection from taking hold. (Calil and Fontes 2017;Liu et al. 2019).

    Developing effective disease control strategies in breeding programs requires a thorough understanding of plant responses to viral infections (Zhu et al. 2018). Given the intricate nature of these responses, transcriptomic studies have offered valuable insights into how plants respond to viruses (Fu et al. 2017;Zhu et al. 2018). By leveraging next-generation sequencing technology, RNA sequencing (RNA-seq) provides a comprehensive view of transcriptome in organisms (Fu et al. 2017). Analyzing expression levels and transcript variations offers to infer the roles of genes under physiological and pathological conditions (Zanardo et al. 2019). This approach has facilitated the understanding of how plants alter gene expression and deploy various defense strategies in response to viral threats (Hashimoto et al. 2016;Rubiales et al. 2015). In ornamental plants, such as the genus Lilium, RNA-seq is used to dissect the genetic basis of traits such as color, fragrance, and disease resistance (Zheng et al. 2021). Lilium species have large genomes and diverse phenotypes (Du et al. 2017;Lee et al. 2015), benefiting from the ability of RNA-seq to effectively manage large, complex genetic information (Malik 2016).

    In this research, next-generation sequencing was employed on four cut lily cultivars, ‘Cancun’, ‘Brunello’, ‘Connecticut King’, and ‘Casa Blanca’ to analyze their transcriptomic responses to CMV infection. The investigation focused on identifying differences in gene expression among cultivars in virus-infected samples and various organs, such as leaves and bulbs, following CMV infection. This study aimed to elucidate the molecular mechanisms underlying the response and resistance of cut lilies to CMV infection. Moreover, these results contributed to the exploration of candidate resistance genes related to CMV by examining the differential expression of genes associated with plant growth and disease resistance among the four lily cultivars.

    Materials and Methods

    Plant materials and virus inoculation

    Nine cultivars of Lilium, comprising five Asiatic hybrids (‘Brunello’, ‘Dublin’, ‘Cancun’, ‘Rodrigo’, and ‘Connecticut King’), two Oriental hybrids (‘Casa Blanca’ and ‘Siberia’), and two Oriental-Trumpet hybrids (‘Avocado’ and ‘Acapulco’), were employed to assess their resistance to CMV and to select samples for RNA-seq analysis via next-generation sequencing (NGS). Each cultivar was propagated through meristem culture to generate virus-free bulbs, which were subsequently subjected to a two-month cold treatment. These bulbs were planted on July 31, 2015, in isolation benches within a greenhouse equipped with 32-cell trays. For biological assays, tobacco (Nicotiana tabacum cv. Xanthi-nc) plants were inoculated with the CMV lily isolate CMV-Teaan, sourced from the National Institute of Agricultural Sciences. Inocula were prepared using 5 mL of 0.1M phosphate buffer per gram of infected leaf tissue displaying mosaic symptoms, adjusted to pH 7.2 with KH2PO4 and Na2HPO4. Inoculations were carried out in two sessions on August 25, 2015, and September 1, 2015. To verify successful inoculation, CMV inoculated leaf samples were detected by RT-PCR using CMV coat protein specific primers (forward primer: 5’-CGTCGTGGTTCCCGCTCCG-3’ and reverse primer: 5’-AGCGCGCATCGCCGAAAGAT-3’; size: 473bp, KT923118). For comparison of expression, primers for 18S rRNA (forward primer: 5’-GACGGAGAATTAGGGTTCGATT-3’ and reverse primer: 5’-CTCCACTCCTGGTGGTGCC-3’; size: 813bp, D29775.1) were used.

    Material selection, RNA extraction, library construction, and Illumina sequencing

    Three Lilium Asiatic hybrids, including ‘Brunello’ (resistant), ‘Cancun’ (susceptible), ‘Connecticut King’ (moderately resistant), and one Lilium Oriental hybrid ‘Casa Blanca’ (moderately resistant), were chosen for RNA-seq analysis. Leaf samples were collected from all cultivars at non-inoculation (0 day) and 28 days post-inoculation, crushed for RNA extraction immediately afterward, and frozen. Bulb samples were collected at non-inoculation (0 day) and 28 days post-inoculation in ‘Cancun’ and ‘Connecticut King’ cultivars. The Qiagen RNeasy Plant Mini Kit (Qiagen, Hilden, Germany) was used to extract the total RNA. The Agilent Bioanalyzer 2100 system (Agilent Technologies, Waldbronn, Germany) was used to assess the quality and quantity of RNA with an RNA integrity value greater than seven. An Illumina TruSeq RNA Sample Preparation Kit (Illumina, CA, USA) was used to construct the libraries. Poly A tail selection was used to enrich the total mRNAs. The libraries were sequenced on a HiSeq™ 2000 platform (Illumina, Inc., San Diego, CA, USA), generating 100 bp paired-end reads. RNA extraction and cDNA library construction were performed in accordance with the manufacturer’s instructions.

    De novo transcriptome assembly and functional annotation

    The Illumina adapter sequence was removed from the sequencing data using cutadapt, and read preprocessing was performed with the SolexaQA package, employing DynamicTrim and LengthSort (Cox et al. 2010). De novo transcriptome assembly was performed using Velvet and Oases software based on the de Bruijn graph algorithm (Schulz et al. 2012;Zerbino and Birney 2008). Trimming resulted in reads with a mean length of 88.57 bp across all samples and a minimum length of 25 bp. The final assembled transcripts, which were obtained by optimizing the k-mer and removing duplicate sequences, were used for the analysis (Kim et al. 2016). The reads were then mapped to the assembled sequences using Bowtie2 (Langmead et al. 2012) and normalized with the DESeq package to avoid bias due to differences in sequencing amount (Anders and Huber 2010). Assembled transcripts were functional annotated by direct comparison with gene sequences in the euKaryotic Orthologous Groups (KOG) and the NCBI non-redundant (NR) databases, and the Kyoto Encyclopedia of Gene and Genomes (KEGG). This was accomplished by using the BLASTX algorithm with a significant threshold of e-value of 1e-10.

    Gene ontology analysis and clustering analysis

    Gene Ontology (GO) analysis was performed to annotate the functional classification of each gene based on the sequence similarity of the protein in the Gene Ontology database, with an e-value cutoff of 1e-10 and the best hits (Ashburner et al. 2000). Differentially expressed genes were analyzed to identify genes with significant changes in expression levels, employing a fold-change and binomial test with an adjusted e-value of 1e-10 or less. Proteins with the highest sequence similarity were retrieved for analysis. Hierarchical clustering was performed using the AMAP library in R, and Pearson’s correlation was used to calculate gene expression patterns (Antoine 2014). Grouping was performed using the complete method. GO enrichment was analyzed using reference GO information and classified into Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) categories. The significance level was set to 0.05, using Blast2GO, and the number of assembled transcripts assigned a GO term was counted using in-house scripts from SEEDERS Co (Conesa et al. 2005).

    Gene expression qRT-PCR analysis

    To validate the RNA-seq results, quantitative real-time reverse-transcription polymerase chain reaction (qRT-PCR) analysis using the RNA samples was performed. Total RNA was extracted using the Qiagen RNeasy Plant Mini Kit (Qiagen, Hilden, Germany), according to the manufacturer’s instructions. First-strand cDNA was synthesized using the PrimeScript 1st Strand cDNA Synthesis Kit (Takara, Shiga, Japan), following the guidelines provided by the manufacturer’s instructions. The qRT-PCR reactions were carried out in a 10 μL solution containing 0.5 μL of forward and 0.5 μL of reverse primers, and 2ul of cDNA template. The qRT-PCR was performed using the SYBR Green method on a Rotor-Gene Q Real-Time PCR machine (QIAGEN, Hilden, Germany) under the following conditions: 95°C for 3 min, 61°C for 30 s, 72°C for 2 min, and 30 cycles. Relative gene expression analyses were performed using the full quantification method with 18S rRNA (forward primer: 5’-CACGGAAGTTTAGGCAA TAAC-3’ and reverse primer 5’-GACCTAGGCTATAAACTCGTTGG-3’; size: 108 bp, D29775.1) as the internal control gene. At least two biological replicates were used for each experiment. The primers used for qRT-PCR are listed in Table 4. The 2−ΔΔCT method was employed for relative quantification (Liu et al. 2019;Schmittgen and Livak 2008).

    Results and Discussion

    Differential susceptibility of Lilium cultivars to Cucumber mosaic virus

    Nine different Lilium cultivars were chosen to assess differential susceptibility. These cultivars included five Asiatic hybrids (‘Brunello’, ‘Dublin’, ‘Cancun’, ‘Rodrigo’, and ‘Connecticut King’), two Oriental hybrids (‘Casa Blanca’ and ‘Siberia’), and two Oriental-Trumpet hybrids (‘Avocado’ and ‘Acapulco’). These cultivars were inoculated with CMV to evaluate their susceptibility to the virus and select candidates for transcriptome analysis via NGS (Table 1). The results showed that CMV was present in the leaves and bulbs of the inoculated plants, with varying levels of susceptibility among cultivars. Among the Asiatic hybrids, ‘Cancun’ and ‘Dublin’ had the highest virus detection in their leaves, with all inoculated plants testing positive. ‘Brunello’ and ‘Connecticut King’ showed less susceptibility, with virus detection in some but not all of their leaves. ‘Cancun’ had the highest levels of CMV in the bulbs. These results implied that variations in virus detection across cultivars and plant tissues (leaves and bulbs) are likely due to the complex interplay between viral strategies and host defenses. The distribution of viruses within plant parts is often uneven, and may vary over time, age, and location (Kominek et al. 2009;Sánchez-Navarro et al. 2007). The concentration of viruses can differ during different growth phases and in different tissue systems. Research has shown that younger leaves tend to have higher concentrations of viruses than older leaves, basal part of the inflorescence axis, dormant bulbs, and newly formed bulbs (Majumder and Yadav 2021). To identify cultivars with varying levels of susceptibility to CMV infection, including ‘Brunello’, ‘Casa Blanca’, ‘Connecticut King’, and ‘Cancun’, a comprehensive detection process was conducted, and these four cultivars were selected for further transcriptome analysis to understand the genetic responses to CMV infection.

    De novo assembly of the lily leaf and bulb transcriptome and functional annotation

    Transcriptome analysis of four cultivars of cut lilies in response to CMV infection was performed using next-generation sequencing (NGS). The study involved three Lilium Asiatic hybrids ‘Brunello’ (resistant), ‘Cancun’ (susceptible), and ‘Connecticut King’ (moderately resistant) and one Lilium Oriental hybrid, ‘Casa Blanca’ (moderately resistant). To explore differentially expressed genes (DEGs) and perform functional annotation, eight leaf samples pre- and post-inoculation were used for each cultivar, along with four bulb samples from ‘Connecticut King’ and ‘Cancun’, yielding a total of 12 samples for RNA-seq analysis. The sequencing produced 535,068,876 short reads. Quality control and trimming were conducted using the SolexaQA package dynamicTrim, setting a cut-off based on a Phred score ≥20. Post-trimming, data analysis was performed using LengthSort, excluding short read lengths of <25 bp, resulting in a total of 480,177,982 cleaned reads. These cleaned reads were mapped back onto the total transcripts, expression values were calculated, and normalization was performed, achieving an average mapping coverage of 84.54% across the samples.

    Functional annotation was conducted using previously assembled de novo lily representative transcripts (unpublished data), resulting in the identification of 51,985 transcripts with detectable expression and 27,969 transcripts with functional descriptions. These transcripts were utilized in the functional annotation analysis, which contributed to 22,768 in NR, 23,507 in KOG annotations, 5,406 in KEGG pathways, and 18,372 in GO terms. KOG analysis revealed 26 functional categories, with the majority classified under general function prediction only (5,481 transcripts), and significant annotations in signal transduction mechanisms (2,751), nuclear structure (2,107), posttranslational modification, protein turnover, chaperones (1,875), transcription (1,596), and carbohydrate transport and metabolism (1,339), covering 59% of the annotations (Fig. 1). KEGG analysis results were categorized into five main groups: Metabolism (5,154), Genetic Information Processing (953), Environmental Information Processing (651), Organismal Systems (269), and Cellular Processes (254). In Genetic Information Processing, the predominant categories identified were Folding, sorting, and degradation, Translation, and Transcription. Within the metabolic category, the most frequently observed subcategories were Carbohydrate metabolism, Amino acid metabolism, Biosynthesis of other secondary metabolites, Lipid metabolism, and Energy metabolism (Table 2).

    Functional upregulation in response to virus infection has been reported in categories such as posttranslational modification, protein turnover, chaperones, intracellular trafficking, secretion and vesicular transport, and RNA processing and modification, whereas downregulation has been observed in carbohydrate transport and metabolism, energy production and conversion, and inorganic ion transport and metabolism (Das et al. 2019). Plant host-virus interactions induce basal defense systems by accumulating defense-related proteins, such as pathogenesis-related proteins (Sun et al. 2010). Therefore, a dual focus is necessary: First, on genes related to plant resistance against viruses, and second, on host factors that facilitate viral infection and replication.

    Clustering analysis and Gene Ontology analysis

    Cluster Set evaluated gene expression patterns across different lily cultivars comparing pre- and post-CMV inoculation at day 0 (0d) and day 28 (28d) using ‘Connecticut King’ as the reference. The comparisons included Bru_leaf_0d vs. CK_leaf_0d, Bru_leaf_28d vs. CK_leaf_28d, Casa_leaf_0d vs. CK_leaf_0d, Casa_leaf_28d vs. CK_leaf_28d, Cancun_leaf_0d vs. CK_leaf_0d, Cancun_leaf_28d vs. CK_leaf_28d, Cancun_bulb_0d vs. CK_bulb_0d, and Cancun_bulb_28d vs. CK_bulb_28d (Fig. 2). The analysis of the Cluster Set displayed data visually using heatmaps to represent relative gene expression levels, which were dissected through hierarchical clustering. These analyses allowed for the classification of twelve distinct expression patterns across clusters, with DEGs distributed differently among the groups (Fig. 2). Clusters were arranged to identify DEGs and 7,259 genes (Table 3).

    The first cluster in the Cluster Set contained 1,350 DEGs, indicating significant regulatory differences between the cultivars compared to the reference cultivar ‘Connecticut King’. GO analysis of this cluster identified significant GO terms across three categories: 360 for biological processes, 76 for cellular components, and 38 for molecular functions (Fig. 3). The most significant results included 82 genes involved in photosynthesis (GO:0015979), 104 genes associated with thylakoid structures (GO:0009579), and 48 genes related to ribosome structural constituents (GO:0003735). These results underline the impact of CMV infection on photosynthetic activity in chloroplasts, both physiologically and morphologically (Chen et al. 2021;Das et al. 2019). Virus infection notably damages key components of plant photosynthesis, including thylakoids, and previous studies have associated decreased photosynthesis with increased viral accumulation. Upon pathogen recognition, plants trigger rapid defense responses, activating numerous signaling pathways that are crucial for plant resilience and stress management (Chen et al. 2021). The ribosome is critical for protein synthesis via a process known as translation, which is the central dogma of biology (Dhaliwal et al. 2023). Following inoculation, the first cluster showed reduced photosynthesis, biosynthetic processes, and molecular functions.

    The second cluster contained the largest number of DEGs, totaling 1,575 genes. Decreased expression was observed in the comparison pairs of Bru_leaf_28d vs. CK_leaf_28d and Casa_leaf_28d vs. CK_leaf_28d, whereas the decrease was less significant in the Cancun_leaf_28d vs. CK_leaf_28d comparison (Fig. 4). Gene Ontology (GO) analysis of this second cluster identified statistically significant enrichments in several categories: 478 GO terms in biological processes (BP), 125 in cellular components (CC), and 88 in molecular functions (MF). Within the BP category, notable processes included intracellular transport involving 124 genes (GO:0046907) and vesicle-mediated transport involving 123 genes (GO:0016192). Pathogens utilize plant-derived amino acids for nutrition and, in some cases, may actively manipulate host amino acid transport pathways to increase amino acid availability at infection sites (Sonawala et al. 2018). In the CC category, 353 genes related to cytosol (GO:0005829) and 100 genes related to cytoplasmic vesicles (GO:0031410) were statistically significant. The virus depends on the host translation and protein-processing machinery, which are crucial and differentially regulated within the host cytoplasm. Host factors, such as cytosolic chaperones and calreticulin, play critical roles in viral replication, transport, and assembly of RNA virus virions (Verchot 2012). In the MF category, the significant terms included nucleoside phosphate binding (GO:1901265), nucleoside binding (GO:0000166), and heterocyclic compound binding (GO:1901363). These are fundamental to life activities, and the GO analysis results suggested that the virus might regulate the transcription, translation, and modification of proteins (Gao et al. 2020). Recessive resistance arises from the absence of specific host factors that are necessary for the successful invasion and proliferation of pathogens, thereby preventing infection. Hence, the analysis of host factors is essential (Kim et al. 2021;Takahashi et al. 2002).

    DEGs selection and validation of DEGs by quantitative PCR

    This study identified several genes in Lilium spp. associated with resistance to CMV infection. Specific primers for quantitative gene expression and validation of these candidate genes were designed. Details of these genes and their primers are listed in Table 4. These candidate genes play critical roles in plant defense mechanisms and stress responses. The disease resistance protein (A coiled-coil nucleotide-binding site leucine-rich repeat protein, CC-NBS-LRR class) family gene (SL002701t014), also known as RCY1, is involved in recognizing pathogen attack and activating plant immune responses (Ando et al. 2019;Sett et al. 2022). The eukaryotic translation initiation factor, eIF4G (SL020891t002), is crucial for the translation initiation process by facilitating the recruitment of messenger RNAs to the ribosomal complex and has been identified as vital for viral infection (Calil and Fontes 2017;Liu et al. 2019). The Tobamovirus multiplication 1 gene, TOM1 (SL010682t003), is associated with viral replication and movement within the host (Yamanaka et al. 2000). Lastly, the Pectin methylesterase, PME (SL017422t001), plays a crucial role in cell wall modification and pathogen movement (Kumar and Dasgupta 2021). To validate the DEGs results, four genes involved in resistance, virus multiplication, and virus movement were selected for qRT-PCR analyses using specific primers (Table 4). The results of both RNA-seq and qRT-PCR showed that all genes were differentially expressed with concordant responses of fold change (Fig. 5), indicating that the RNA-seq results were reliable.

    Plants employ various defense strategies to combat pathogens, particularly through complex gene-for-gene interactions that lead to inducible defense responses (Kang et al. 2005). These interactions occur between R genes of a plant and Avr genes of a pathogen, resulting in dominant resistance mechanisms (Takahashi et al. 2002). In ‘Brunello’, the analysis of DEGs revealed the candidate gene for RCY1 in lilies, and the expression levels were less suppressed in comparison to ‘Connecticut King’ after inoculation. Although only a few R proteins, such as RCY1 (RESISTANCE TO CMV(Y)1), have been identified in the context of host resistance against CMV, they play a crucial role. RCY1 specifically recognizes the coat protein of the CMV strain, triggering R-gene-mediated resistance characterized by hypersensitive cell death and the activation of defense-related gene expression (Ando et al. 2019;Sett et al. 2022).

    The relationship between viruses and host plants is characterized by complex molecular interactions that enable successful viral infection and symptom development (Calil and Fontes 2017;Liu et al. 2019). Since RNA viruses lack translational machinery and viral replication proteins in their virions, they depend on efficiently recruiting ribosomes from infected host cells to produce replication proteins and form the viral replication complex (Hyodo and Okuno 2016). Many host factors are essential for life across all forms and are often integrated into viral replication complexes to facilitate viral replication processes (Zhang and Hu 2023). DEGs analysis revealed that, in some varieties, candidate genes for eIF4G and TOM1 increased after inoculation, although a decreasing trend was also observed.

    The movement of viruses is influenced by both viral and host cellular elements such as membranes and cytoskeletal components (Garcia-Ruiz 2018). An essential aspect of this process is the regulation of the plasmodesmata, which enables the exchange of macromolecules, including viral particles. This regulation is aided by cellular factors such as cell wall-associated pectin methylesterase (PME) (Kumar and Dasgupta 2021). In the ‘Casa Blanca’, candidate genes for PME decreased after virus inoculation. These changes varied among cultivars and organs.

    The presence of viruses can vary among various organs and tissues (Han et al. 2006;Majumder and Yadav 2021). These viruses are transmitted via the phloem for efficient long-distance travel, targeting rapidly growing tissues, such as young leaves, where higher concentrations of viruses are often observed (Kappagantu et al. 2020;Majumder and Yadav 2021). The vascular phloem regulates a range of responses that affect not only viral biology but also plant development and homeostasis (Kappagantu et al. 2020). Furthermore, it is hypothesized that this is due to a decrease in the host growth response following virus infection, and the initial responses post-inoculation need to be investigated in this study. These results imply that each cultivar employs distinct mechanisms to resist viral infection, indicating the necessity for diverse approaches to comprehensively understand post-inoculation changes. The observed differences in gene expression patterns among the cultivars show the intricacy of plant-virus interactions and suggest the importance of tailored strategies to enhance resistance in Lilium species.

    Acknowledgments

    This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No. PJ00926803)" Rural Development Administration, Republic of Korea.

    Figure

    FRJ-33-1-34_F1.gif

    Functional annotation classification was shown using euKaryotic Orthologous Groups (KOG) analysis based on representative transcripts. As a result, a total of 26 functions were identified. A; RNA processing and modification. B; Chromatin structure and dynamics, C; Energy production and conversion, D; Cell cycle control, cell division, chromosome partitioning, E; Amino acid transport and metabolism, G; Carbohydrate transport and metabolism, H; Coenzyme transport and metabolism, I; Lipid transport and metabolism, J; Translation, ribosomal structure and biogenesis, K; Transcription, L; Replication, recombination and repair, M; Cell wall/membrane/envelope biogenesis, N; Cell motility, O; Posttranslational modification, protein turnover, chaperones, P; Inorganic ion transport and metabolism, Q; Secondary metabolites biosynthesis, transport and catabolism, R; General function prediction only, S; Function unknown, T; Signal transduction mechanisms, U; Intracellular trafficking, secretion, and vesicular transport, V; Defense mechanisms, W; Extracellular structures, X; Nuclear structure, Y; Cytoskeleton, Z; Unnamed protein/Neuronal membrane glycoprotein/Myelin proteolipid protein.

    FRJ-33-1-34_F2.gif

    Heatmap and line plot analysis for the Cluster set. The differences of expression in cultivars compared control cultivar ‘Connecticut King’ in ‘Brunello’ inoculated before and after 28days (Bru_leaf_0d vs CK_leaf_0d, sample ① and Bru_leaf_28d vs CK_leaf_28d, sample ②), ‘Casa Blanca’ inoculated before and after 28days (Casa_leaf_0d vs CK_leaf_0d, sample ③ and Casa_leaf_28d vs CK_leaf_28d, sample ④), ‘Cancun’ inoculated before and after 28 days in leaf and bulb (Cancun_leaf_0d vs CK_leaf_0d, sample ⑤ and Cancun_leaf_28d vs CK_leaf_28d, sample ⑥, Cancun_bulb_0d vs CK_bulb_0d, sample ⑦, and Cancun_bulb_28d vs CK_bulb_28d, sample ⑧) were compared and analyzed, and each showed twelve expression pattern.

    FRJ-33-1-34_F3.gif

    Gene Ontology (GO) analysis is divided into three functional categories: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) in cluster 1 of the Cluster set; a total of 1,350 related DEGs expressed as 360 GO Term in BP, 76 GO Term in CC, and 38 GO Term in MF were analyzed.

    FRJ-33-1-34_F4.gif

    Gene Ontology (GO) analysis is divided into three functional categories: Biological Process (BP), Cellular Component (CC), and Molecular Function (MF) in cluster 2 of the Cluster set; a total of 1,575 related DEGs expressed as 472 GO Term in BP, 125 GO Term in CC, and 88 GO Term in MF were analyzed.

    FRJ-33-1-34_F5.gif

    Validation of the expression of the selected genes from RNA sequencing (Gray) using qRT-PCR (Black). Error bars represent the standard errors of the qRT-PCR signals. The 18S rRNA gene was used as a control to normalize the qRT-PCR analysis.

    Table

    Results of CMV detection in lily seedlings inoculated using RT-PCR.

    zCultivars were divided to 3 groups; (A) Asiatic hybrids, (O) Oriental hybrids, (OT) Oriental-Trumpet interspecific hybrid.
    yResults were from RT-PCR for CMV detection in leaves and bulbs with CMV coat protein gene primers. The 18S rRNA gene primers was used as a control.

    Analysis of metabolism and pathways confirmed through Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis targeting representative transcripts.

    The total number of differentially expressed genes (DEGs) detected through the Clustering set analysis and the number of annotated DEGs in each cluster.

    Description of candidate genes and primer designs for differentially expressed gene analysis from the RNA sequencing about four cultivars of cut lily in response to CMV infection.

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    2. Journal Abbreviation : 'Flower Res. J.'
      Frequency : Quarterly
      Doi Prefix : 10.11623/frj.
      ISSN : 1225-5009 (Print) / 2287-772X (Online)
      Year of Launching : 1991
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