Abstract

   Eggplant (Solanum melongena L.), which belongs to the Solanaceae
   family, is an important vegetable crop. However, its production is
   severely threatened by root-knot nematodes (RKNs) in many countries.
   Solanum torvum, a wild relative of eggplant, is employed worldwide as
   rootstock for eggplant cultivation due to its resistance to soil-borne
   diseases such as RKNs. In this study, to identify the RKN defense
   mechanisms, the transcriptomic profiles of eggplant and Solanum torvum
   were compared. A total of 5360 differentially expressed genes (DEGs)
   were identified for the response to RKN infection. Gene Ontology and
   Kyoto Encyclopedia of Genes and Genomes enrichment analysis showed that
   these DEGs are mainly involved in the processes of response to
   stimulus, protein phosphorylation, hormone signal transduction, and
   plant-pathogen interaction pathways. Many phytohormone-related genes
   and transcription factors (MYB, WRKY, and NAC) were differentially
   expressed at the four time points (ck, 7, 14, and 28 days
   post-infection). The abscisic acid signaling pathway might be involved
   in plant-nematode interactions. qRT-PCR validated the expression levels
   of some of the DEGs in eggplant. These findings demonstrate the
   nematode-induced expression profiles and provide some insights into the
   nematode resistance mechanism in eggplant.

   Keywords: eggplant, Solanum torvum, RNA-seq, root-knot nematode, ABA,
   resistance

1. Introduction

   Eggplant (Solanum melongena L.) is an important solanum genus vegetable
   crop, originating in India, and now widely grown in Asia, Africa, and
   the Mediterranean [[36]1]. In 2016, 46.63 million tons of eggplant were
   produced in the top three producing countries: China (32.03 million
   tons), India (12.55 million tons), and Egypt (1.19 million tons),
   according to the Food and Agriculture Organization of the United
   Nations (FAO; [37]http://faostat.fao.org, accessed on 1 October 2016).
   It has been reported that eggplant is susceptible to several bacterial
   and fungal pathogens, such as the Verticillium dahlia, fungus, and
   nematodes [[38]2,[39]3]. Root-knot nematodes (RKNs, Meloidogyne spp.)
   are devastating endoparasites that parasitize many cultivated plants
   and seriously threaten global food safety. The estimated crop globally
   losses due to RKN infections are approximate USD 157 billion annually.
   It parasitizes a variety of cultivated plants, including tomato
   (Solanum lycopersicum), carrot (Daucus carota), potato (Solanum
   tuberosum), eggplant (Solanum melongena), and watermelon (Citrullus
   vulgaris) [[40]4,[41]5].

   RKNs are among the most damaging plant pathogens that reduce yield.
   Once infected, large knots are formed on the roots of host plants. They
   ultimately result in giant cells, which provide fewer resources to the
   surrounding root tissues [[42]6,[43]7]. The southern root-knot nematode
   Meloidogyne incognita is one of the most sophisticated plant-parasitic
   nematodes in China. It is a sedentary endoparasite that completes its
   lifecycle inside the host roots in 4–6 weeks. M. incognita invades the
   plant roots at the second stage juveniles (J2s) and induces normal root
   cells to dedifferentiate into giant cells in its feeding site
   [[44]8,[45]9]. The giant cells are a kind of multinucleate and
   hypertrophied cells, which serve as a source of nutrition for growing
   nematodes. The J2s become sedentary and undergo a few rounds of molting
   to J3s, J4s, and adults. Then, adult female nematodes lay the eggs on
   the surface of the root and, following the hatch, generate infectious
   J2s, which start their next parasitic life cycle [[46]9,[47]10].

   When the RKNs invade the plants, they can respond with a succession of
   defense reactions. Several phytohormones, including auxin, cytokinins,
   salicylic acid, jasmonate, gibberellin, abscisic acid, and
   brassinosteroids (BRs), play important roles in response to abiotic
   stress. Auxin and cytokinin have been reported to modulate plant immune
   response pathways in plant-nematode interactions [[48]11]. In
   Arabidopsis, salicylic acid-related genes were induced in RKN-infected
   roots [[49]12]. In addition, transcription factors participate in
   response to RKN infection. WRKY is a class of transcription factors
   that are widely involved in the response to nematode infection. In
   pepper, WRKY2 was reported to be induced during incompatible
   interactions of host plants with RKNs [[50]13]. AtWRKY23 is an
   auxin-inducible gene that is expressed during the early stages of
   feeding site establishment [[51]14].

   Solanum torvum Sw., commonly known as turkey berry, is a wild relative
   of eggplant, widely cultivated in tropical and subtropical countries
   [[52]15]. Turkey berry is resistant to RKNs and the majority of serious
   soil-borne diseases, providing genetic resources for improving disease
   resistance in eggplant. In addition, the rootstock of turkey berry is
   also used for grafting in eggplant cultivation.

   Previous studies have reported that plant-nematode interactions result
   in gene expression changes in the host plant [[53]16]. Transcriptome
   analysis, especially RNA-Seq, has been widely employed to determine
   transcriptional changes in many plants [[54]16,[55]17]. The new and
   potent technique known as transcriptome analysis has been used to study
   susceptible or resistant plants during host-RKN interactions. Bagnaresi
   et al. (2013) combined 454 pyrosequencing and microarray technology to
   research the transcriptome profiling of Solanum torvum inoculated with
   the nematode M. incognita [[56]18]. RKN-infected root samples resulted
   in 390 differentially expressed genes (DEGs) and enhancement of several
   processes, such as chitin catabolism and sesquiterpenoids biosynthesis.
   Shukla et al. (2018) used RNA-Seq data to reveal the gene expression
   profiles and metabolic networks during nematode responses in tomato
   [[57]19]. In rice, transcriptional analysis of galls at 3 days after an
   infection with Meloidogyne graminicola (Mg) revealed that many DEGs are
   involved in the plant hormone biosynthesis and signaling pathways
   [[58]20]. In many crops, the genetic mechanism of resistance to RKN has
   been preliminarily identified and characterized [[59]4]. However, few
   studies have been published on the genetic mechanisms of RKN resistance
   in eggplant.

   In this study, the transcriptome profiles of RKN-infected eggplants
   root in Solanum torvum (RKN-resistant) and Solanum melongena
   (RKN-susceptible) were analyzed. Differentially expressed genes were
   identified in eggplants following M. incognita inoculation. Our results
   provide important insights into the underlying mechanism of the
   eggplant response to M. incognita, which provides a basis for further
   research.

2. Results

2.1. Analysis of RKN Infection in Eggplant Roots

   After the RKN invasion, the number and diameter of root knots increased
   with the increase in inoculation days during the observation period
   ([60]Figure 1A). A small amount of root nodes could be observed in
   cultivated eggplant (Sme), indicating that J2S had reached the feeding
   point and began to settle down at this stage (7 dpi), while root node
   formation was not observed in wild eggplant turkey berry (Tor). At 14
   dpi, root knots were observed in the root tips of lateral roots at all
   levels of cultivated eggplant ([61]Figure 1B), and some roots formed
   clusters, indicating that the cells at feeding sites began to form root
   knot galls around the enlarged giant cells ([62]Figure 1B). The root
   growth of wild eggplant was normal, the taproot was obvious, and there
   were no obvious root knots in the root tip and the parts far from the
   root tip. At 28 dpi, the root nodes of cultivated eggplant seedlings
   continued to thicken and significantly increased, and piriform body
   appeared ([63]Figure 1B).

Figure 1.

   [64]Figure 1
   [65]Open in a new tab

   Morphological changes of roots infected by root-knot nematodes (RKNs)
   at different stages. (A) The different root morphologies between Sme
   and Tor in CK and at 7, 14, and 28 days post infection (dpi). (B)
   Comparison of the expansion feeding sites and maintenance feeding sites
   between ‘Sme’ and ‘Tor’. ‘Sme’ and ‘Tor’ stand for cultivated eggplant
   and wild eggplant, respectively.

2.2. Overview of RNA Sequencing

   Twenty-four cDNA libraries were constructed from total RNA extracted
   from the torvum (Tor) and eggplant (Sme) roots (three replicates for
   each sample). The cDNA libraries were subjected to pair-end reading
   with the Illumina Hiseq 2500 platform, and generated 52–59 million and
   67–87 million paired-end raw reads in Sme and Tor, respectively
   ([66]Table S1). After removing low-quality reads and trimming adapter
   sequences using Trimmomatic, we obtained 50–58 million and 64–83
   million clean reads for the Sme and Tor libraries, respectively. Three
   biological replicates were performed for each sample. Correlation
   analyses showed that the coefficient of the samples confirmed the
   consistency among the three biological replicates, indicating the
   test’s high reliability for further analyses ([67]Figure S1).

   For Sme samples, we used the Eggplant Genome Database
   ([68]http://eggplant.kazusa.or.jp/, accessed on 1 October 2014) as the
   reference genome. After quality control, the majority of the reads from
   Sme samples (83.16–91.18%) were successfully aligned to the reference
   genome ([69]Table S1). Most of the reads were aligned to a single
   position.

2.3. De Novo Assembly of Tor Transcriptome

   Since the reference genome of Solanum torvum has not been reported, we
   here de novo assembled the transcriptome reads of the twelve Tor
   samples. In total, a range of 76.62–80.11% of the clean reads was
   mapped and assembled into contigs ([70]Table S1). These contigs were
   then clustered into 152,489 transcripts and 78,228 unigenes ([71]Table
   S2). The N50 values of transcripts and unigenes were 1942 and 1584
   ([72]Figure S2 and Table S2). The results were higher than the previous
   study of Turkey berry [[73]21], which provided more information for
   further identification of the resistant genes in Tor (Turkey berry).
   Additionally, a total of 12,359 unigenes were annotated by the five
   databases using BLAST with E-value ≤ 1 × 10^−5 ([74]Figure S2). In
   addition, we identified 12,317 pairs of SSR primers which are valuable
   markers for genetic diversity analysis ([75]Table S3).

2.4. Identification of Differentially Expressed Genes under RKN Infection

   To investigate the response to RKN infections, the gene expression
   profiles at the three stages (7, 14, and 28 dpi) of Sme and Tor were
   analyzed. In total, 6852, 6945, and 6621 up-regulated DEGs and 6091,
   6525, and 6223 down-regulated DEGs were identified in Sme compared with
   CK, respectively, while a total of 6246, 8106, 9232 DEGs, and 4060,
   5595, and 5427 DEGs were up-regulated and down-regulated in Tor
   ([76]Figure 2A). Compared with Sme, more up-regulated DEGs were
   identified in Tor at 14 dpi and 28 dpi ([77]Figure 2A). A total of 8148
   and 4761 DEGs were found to be common genes for the comparisons of
   three stages in Sme and Tor, respectively ([78]Figure 2B,C). Gene
   Ontology (GO) enrichment analysis of the Tor responsive DEGs showed
   that the terms of response to oxidation stress, protein modification,
   response to stimulus, and signal transduction are significantly
   overrepresented ([79]Figure 2D).

Figure 2.

   [80]Figure 2
   [81]Open in a new tab

   Differentially expressed genes (DEGs) of eggplant infected by root-knot
   nematodes (RKNs) with control (CK) and between the adjacent stages
   (7/14, and 14/28 dpi) in Sme and Tor. (A) The number of up- and
   down-regulated genes in Sme and Tor; (B) Venn diagrams showing the
   intersection of DEGs identified in Sme; (C) Venn diagrams showing the
   intersection of DEGs identified in Tor; (D) Gene Ontology (GO)
   enrichment analysis of the DEGs identified in Tor.

2.5. Comparisons of Transcriptomes between Sme and Tor Responses to RKN
Infection

   To investigate the mechanisms of RKN invasion and gall formation, gene
   expression profiles between RKN-sensitive Sme and RKN-tolerant Tor were
   analyzed. Many DEGs were up- and down-regulated among the four stages
   between Sme and Tor ([82]Figure 3A). A total of 5360 DEGs were shared
   by Sme and Tor during the four stages after RKN invasion, which could
   be the core genes involved in eggplant’s response to RKN ([83]Figure 3B
   and [84]Table S4). We found 741 DEG overlaps between the core genes and
   the DEGs identified in Tor, indicating these DEGs might be involved in
   the resistance to RKN infections ([85]Figure 3C). We identified dozens
   of pathogen-related and disease-resistance genes that were
   differentially expressed during the four stages between Sme and Tor
   ([86]Table S4). The DEGs included genes encoding the
   pathogenesis-related protein, late blight resistance protein, and
   disease resistance protein ([87]Figure 3D). In addition, many R genes
   were detected, including NBS-LRR and RLK (LRR receptor-like kinases)
   ([88]Figure 3D and [89]Table S4). A total of 24 DEGs encoding R genes
   were identified with an NBS-LRR domain ([90]Table 1 and [91]Table S4).
   Most of these R genes were up-regulated in Tor among the three stages,
   but some of them were highly expressed in Sme compared with Tor
   ([92]Table 1). For example, RGA4 (Sme2.5_10927.1_g00001.1), which
   encodes an NBS-LRR type R protein, was highly induced in all four
   stages ([93]Table 1).

Figure 3.

   [94]Figure 3
   [95]Open in a new tab

   Differentially expressed genes (DEGs) of eggplant infected by RKNs at
   four stages between Sme and Tor and the expression patterns of disease
   resistance genes. (A) The number of up- and down-regulated genes
   between Sme and Tor at each stage (CK, 7, 14, and 28 dpi). (B) Venn
   diagrams showing the overlapping DEGs between Sme and Tor. (C) Overlap
   among RKN-responsive genes in Tor and DEGs between Sme and Tor. (D)
   Heatmaps showing the expression patterns of disease resistance genes,
   including pathogenesis-related, late blight resistance, and disease
   resistance genes.

Table 1.

   Some R genes identified for disease resistance of RKN in eggplant.
   Gene ID Alias CK ^a 7 dpi 14 dpi 28 dpi Annotation
   Sme2.5_00077.1_g00005.1 RPP13 1.73 1.13 0.68 1.58 Disease resistance
   protein RPP13
   Sme2.5_03872.1_g00001.1 RGA1 0.61 0.32 0.63 0.37 Disease resistance
   protein RGA1
   Sme2.5_03872.1_g00002.1 RGA4 0.39 0.25 0.21 0.26 Disease resistance
   protein RGA4
   Sme2.5_00130.1_g00024.1 RPM1 0.38 1.47 0.13 0.06 Disease resistance
   protein RPM1
   Sme2.5_00345.1_g00018.1 RPP8 0.37 0.84 0.64 0.33 Disease resistance
   protein RPP8
   Sme2.5_07918.1_g00005.1 RPM1 7.79 2.74 3.66 3.23 Disease resistance
   protein RPM1
   Sme2.5_02954.1_g00001.1 RPV1 0.98 2.20 3.86 2.65 Disease resistance
   protein RPV1
   Sme2.5_05922.1_g00005.1 RPM1 0.07 0.09 0.03 0.10 Disease resistance
   RPM1
   Sme2.5_10927.1_g00001.1 RGA4 7.92 4.52 5.64 6.58 Disease resistance
   protein RGA4
   Sme2.5_06008.1_g00004.1 RGA3 0.56 0.10 0.08 0.10 Disease resistance
   protein RGA3
   Sme2.5_16574.1_g00002.1 R13L4 0.58 0.87 1.20 1.34 Disease resistance
   RPP13-like protein 4
   Sme2.5_13369.1_g00002.1 RGA4 0.20 0.28 0.11 0.26 Disease resistance
   protein RGA4
   Sme2.5_19803.1_g00001.1 R13L4 0.88 0.29 0.27 1.14 Disease resistance
   RPP13-like protein 4
   [96]Open in a new tab

   ^a The relative expression between Sme and Tor, FPKM value (Sme)/FPKM
   value (Tor).

2.6. Specific Differentially Expressed Gene in Tor Responses to RKN Infection

   Since Solanum torvum is a wild relative of eggplant, there may be some
   DEGs that were only involved in Tor in responsive to RKN infection. In
   our study, we identified 2711 DEGs were specific differentially
   expressed in the Tor ([97]Figure 4A and [98]Table S5). GO enrichment
   analysis also showed many of these DEGs were involved in ‘response to
   stimulus’, ‘defense response’ and ‘response to auxin’. The results
   indicate that more defense and resistance genes might be involved in
   the RKN infection of Solanum torvum than eggplant. The expression
   patterns of some specific DEGs in Tor revealed that these genes were
   up-regulated during the infection, including genes associated with the
   cell wall, resistance genes, and some WRKY transcription factors
   ([99]Figure 4C).

Figure 4.

   [100]Figure 4
   [101]Open in a new tab

   Tor-specific DEGs in responsive to RKNs. (A) Venn diagrams showing the
   specific responsive DEGs in Tor. (B) GO enrichment analysis the
   specific DEGs in Tor. (C) Heatmap showing the expression patterns of
   some specific DEGs in Tor.

2.7. Analysis of Nematode-Responsive Hormone-Relative Genes and Transcription
Factors

   KEGG pathway analysis revealed that the DEGs between Sme and Tor are
   involved in plant hormone signal transduction, plant–pathogen
   interaction, basal transcription factors, and phenylpropanoid
   biosynthesis ([102]Figure 5A). Many of the DEGs are involved in the
   plant–pathogen interaction pathway, including CDPK, FLS2, RIN4, and
   WRKY ([103]Figure S3 and [104]Table 2). PR genes and WRKYs were highly
   expressed in Sme, which might participate in the phytoalexin
   accumulation and defense response ([105]Table 2). Many of the genes
   encoding LRR receptor-like serine/threonine-protein kinase and TMV
   resistance protein were also up-regulated in Sme ([106]Figure S4).
   However, eleven of the eighteen FLS2 (LRR receptor-like
   serine/threonine-protein kinase) genes were down-regulated in Sme
   ([107]Table S4). In addition, some genes related to the cell wall were
   up-regulated in Sme, indicating these genes involved in the resistance
   to RKNs ([108]Table 3).

Figure 5.

   [109]Figure 5
   [110]Open in a new tab

   (A) The top 20 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG)
   pathways for DEGs between Sme and Tor. Rich factor represents the ratio
   of the number of DEGs with the number of genes in the pathway. (B)
   Heatmap illustrating the DEGs related to phytohormones (auxin, abscisic
   acid (ABA), ethylene, GA and SA) between Sme and Tor.

Table 2.

   Expression patterns of plant-pathogen interaction pathway genes in Sme
   and Tor.
   Gene ID Alias CK ^a 7 dpi 14 dpi 28 dpi Annotation
   Sme2.5_00057.1_g00028.1 PR1 2.651 1.797 1.175 1.868
   Pathogenesis-related protein 1
   Sme2.5_05922.1_g00005.1 RPM1 0.071 0.093 0.028 0.096 Disease resistance
   protein RPM1
   Sme2.5_03682.1_g00009.1 DRL27 0.258 0.047 0.144 0.292 Disease
   resistance protein DRL27
   Sme2.5_09833.1_g00003.1 GSO2 0.865 4.465 0.425 0.399 LRR receptor-like
   serine/threonine-
   protein kinase GSO2
   Sme2.5_00365.1_g00011.1 CML16 0.135 0.140 0.169 0.100 Calcium-binding
   protein CML16
   Sme2.5_02438.1_g00002.1 CDPK8 0.238 0.222 0.224 0.435 Calcium-dependent
   protein kinase 8
   Sme2.5_00959.1_g00002.1 CDPK2 3.369 0.940 0.942 1.091 Calcium-dependent
   protein kinase 2
   Sme2.5_00572.1_g00003.1 CNG18 0.304 0.340 0.241 0.289 Cyclic
   nucleotide-gated ion channel 18
   Sme2.5_00629.1_g00003.1 MRK7 5.936 12.89 8.233 9.426 Mitogen-activated
   protein kinase kinase 7
   Sme2.5_00861.1_g00010.1 MRK3 3.917 4.601 5.035 7.191 Mitogen-activated
   protein kinase kinase 3
   Sme2.5_01071.1_g00003.1 WRKY22 1.240 2.136 2.084 2.632 WRKY
   transcription factor 22
   Sme2.5_00297.1_g00009.1 HSP90 1.240 2.136 2.084 2.632 Heat shock 90 kDa
   protein
   [111]Open in a new tab

   ^a The relative expression between Sme and Tor, FPKM value (Sme)/FPKM
   value (Tor).

Table 3.

   Expression patterns of genes associated with cell wall in Sme and Tor.
   Gene ID CK ^a 7 dpi 14 dpi 28 dpi Annotation
   Sme2.5_00236.1_g00007.1 6.104 1.235 1.871 2.275 Chitin-inducible
   gibberellin-responsive protein
   Sme2.5_18829.1_g00001.1 111.4 72.32 4.060 2.670 Basic endochitinase A
   Sme2.5_03222.1_g00007.1 11.86 65.26 26.70 74.93 Endochitinase 1
   Sme2.5_00287.1_g00007.1 1.346 16.19 2.376 3.592 Wound-induced protein
   Sme2.5_03391.1_g00004.1 1.911 5.025 2.275 0.807 Lignin-forming anionic
   peroxidase
   Sme2.5_03391.1_g00006.1 3.010 2.131 3.572 1.007 Lignin-forming anionic
   peroxidase
   Sme2.5_00295.1_g00005.1 0.679 0.189 0.026 0.394 Laccase-3
   Sme2.5_00135.1_g00019.1 7.591 2.562 2.642 2.476 Xyloglucan
   endotransglucosylase/hydrolase 16
   Sme2.5_03583.1_g00006.1 1.745 1.184 0.443 0.226 Xyloglucan
   endotransglucosylase/hydrolase 2
   Sme2.5_00498.1_g00013.1 0.031 0.052 0.410 0.000 Xyloglucan
   endotransglucosylase/hydrolase 26
   Sme2.5_00096.1_g00018.1 8.966 1.924 1.952 2.720 Xyloglucan
   endotransglucosylase/hydrolase 25
   [112]Open in a new tab

   ^a The relative expression between Sme and Tor, FPKM value (Sme)/FPKM
   value (Tor).

   Plant hormones are widely involved in the response to RKN infections in
   many plants [[113]7]. In our study, we identified many DEGs related to
   phytohormones, such as auxin, abscisic acid (ABA), ethylene,
   gibberellic acid (GA), salicylic acid (SA), cytokinin, and
   brassinosteroid (BR) ([114]Figure 5 and [115]Table S6). Most of the
   auxin- and ethylene-associated genes were up-regulated in Sme
   ([116]Figure 5B). However, many ABA-related genes were induced by RKN
   infection in Tor, such as 9-cis-epoxycarotenoid dioxygenase (NCED) and
   PYL8 ([117]Figure 5A). PYL genes have been reported to be abscisic acid
   receptors, which play important roles in the resistance to stress
   [[118]22]. The expression patterns of genes involved in ABA metabolism
   pathway under RKN infection were investigated. The NCED gene showed
   higher expression level in Tor than in Sme at all four stages. The
   other five ABA metabolism genes also showed differential expression
   between Sme and Tor ([119]Figure S5). Two homologs of
   brassinosteroid-insensitive-1-associated receptor kinase (BAK1)
   (Sme2.5_03931.1_g00001.1, Sme2.5_03931.1_g00003.1), which are BR
   biosynthesis genes, were up-regulated in the Tor ([120]Table S5).

   Among the 5360 core genes, ARF TFs were the most abundant (22),
   followed by HSP (14), ERF (13), MYB (11), bHLH (9), WRKY (9), and NAC
   (6) ([121]Table S4). Most of these TFs were induced by the RKN
   infection. WRKY TFs constitute a large family of transcriptional
   regulators that respond to biotic stress, particularly disease
   resistance. In our study, 9 WRKY TFs were identified among the
   different stages after RKN infection ([122]Figure 6 and [123]Table S4).
   Using MapMan, DEGs at 7 and 14 dpi were classified into different
   processes. Many hormone signaling pathways (auxin, BR, ABA, and SA),
   redox signaling, transcription factors (ERF, WRKY, and MYB), and HSPs
   were involved in the response to biotic stress ([124]Figure 7).

Figure 6.

   [125]Figure 6
   [126]Open in a new tab

   Heatmap showing the DEGs of transcription factors after infection by
   RKNs: (A) MYB, (B) HSP, (C) ERF, (D) WRKY, and (E) NAC.

Figure 7.

   [127]Figure 7
   [128]Open in a new tab

   Overview of the DEGs of eggplant roots infected by RKNs assigned to
   regulation category by MapMan at (A) 7 and (B) 14 dpi.

   To confirm the DEGs identified from the RNA-seq data between the root
   samples of Sme and Tor in the four stages, six DEGs related to the RKNs
   resistance, including PR gene, WRKY, and MYB, were selected for qRT-PCR
   analysis ([129]Figure 8). These genes showed different expression
   patterns, consistent with those obtained from the RNA-Seq between Sme
   and Tor.

Figure 8.

   [130]Figure 8
   [131]Open in a new tab

   Validation of the expression levels of some differentially expressed
   genes (DEGs) in Sme and Tor using qRT-PCR: (A) PR; (B) WRKY69; (C)
   WRKY75; (D) SOD; (E) LOX; and (F) MYB44. The blue column represents Sme
   sample, and the orange column represents Tor sample.

3. Discussion

   As an important vegetable crop, eggplant is severely threatened by
   abiotic and biotic stresses, especially root-knot nematodes (RKNs). The
   wild relatives of eggplant, such as Solanum torvum (Tor), have been
   documented to be resistant to RKNs [[132]18,[133]23]. Identification of
   the genes for Tor resistance could be valuable for cultivated eggplants
   [[134]18,[135]23]). However, few studies have reported the molecular
   mechanisms of the defense responses of eggplant to RKNs. In this study,
   we attempted to shed more light on the issue by performing root
   transcriptome analysis of eggplant infected with RKN Meloidogyne
   incognita, comparing the transcription profiling of Tor with that of
   Sme.

   Generally, differential expression changes in genes involved in stress
   and defense response, metabolism, the cell wall, and signal
   transduction respond to nematode infection in plants
   [[136]24,[137]25,[138]26]. In the transcriptome analysis, 8148 and 4761
   DEGs were induced in Sme and Tor in all the stages under RKN infection
   ([139]Figure 2B,C). A total of 5360 DEGs were identified between Sme
   and Tor among the four stages, suggesting that these genes might play
   important roles in the resistance of eggplant to RKN ([140]Figure 3).
   GO and KEGG enrichment analysis showed that response to stimulus,
   response to hormone, cell wall biogenesis/organization, plant hormone
   signal transduction, and plant–pathogen interaction were
   overrepresented ([141]Figure 2 and [142]Figure 5). Nitrogen compound
   metabolic process and transport were enriched at 7 and 14 dpi compared
   with CK, implying that nutrient transport might be important in these
   stages ([143]Figure 2D). In addition, the metabolic activity of roots
   might be inhibited after RKN infection, and many DEGs were enriched in
   different metabolism pathways ([144]Figure 5A).

   Due to the antimicrobial activity, PRs are well-known in the response
   to biotic stress [[145]27]. The presence of a large number of PRs in
   the susceptible line Sme compared with the resistant Tor might be due
   to the basal defense responses ([146]Figure 3D). Nucleotide-binding
   site–leucine-rich repeat (NBS-LRR) is a family of resistance genes that
   respond to biotic stress in many plants [[147]28,[148]29]. These R
   genes contain two typical domains: NBS and C-terminus LRR, which is an
   effector-binding domain that recognizes the pathogen effector molecules
   [[149]23,[150]30]. NBS-LRR motifs are widely found in nematode R genes
   in plants [[151]28]. In tomato, one R gene, Mi-1.2, which belongs to
   the NBS-LRR class, has been reported to confer resistance against three
   species of Meloidogyne [[152]31]. In our study, we identified 24 DEGs
   of NBS-LRR R genes ([153]Table 1 and [154]Table S4). Most of these R
   genes were up-regulated in Sme, suggesting that they are associated
   with RKNs resistance in eggplant.

   Calcium signaling plays a key role in the plant response to
   environmental change. Previous research demonstrated
   calcium/calmodulin-mediated defense signaling is a key mechanism for
   nematode resistance in wild Glycine soja [[155]32]. Our study also
   revealed that many DEGs encoding calcium-dependent protein kinase are
   highly expressed in the wild relative of eggplant, Tor ([156]Table 2).

   In plants, the cell wall is the first structural barrier to infection
   by many pathogens [[157]23]. In the present study, some DEGs were
   related to the response to wound, chitin and lignin catabolic process
   ([158]Figure 7 and [159]Table 3). Dozens of genes participated in cell
   wall were up-regulated in Sme, indicating it may be a defense strategy.
   Xyloglucan endotransglucosylases (XETs) are enzymes that have specific
   activity on xyloglucans. Additionally, the structural changes in cell
   wall xyloglucans are associated with cell expansion, which is essential
   for nematode feeding sites formation [[160]23]. Our study showed that
   many XETs (Sme2.5_00135.1_g00019.1, Sme2.5_00096.1_g00018.1) were
   repressed in Tor by RKN infection ([161]Table 3).

   Phytohormones such as SA, GA, and ABA play important roles in the
   regulation of the defense responses [[162]33,[163]34,[164]35]. SA and
   GA signaling pathways have been reported to be mutually antagonistic,
   while the ABA has mostly been considered to negatively regulate disease
   resistance [[165]36]. In Arabidopsis, SSI4 which encoded a R protein of
   the TIR-NBS-LRR class was induced by SA [[166]36,[167]37]. In the
   present study, DEGs encoding four SA and eleven GA-related genes were
   identified ([168]Table S5). Interestingly, many ABA-related genes were
   differentially expressed between Sme and Tor ([169]Table S6). The NCED
   is thought to be a key enzyme in ABA biosynthesis and the expression
   level of one NCED gene was up-regulated in Tor ([170]Figure 5B and
   [171]Figure S5). Additionally, two abscisic acid hydroxylase (ABH)
   genes were also differential expression ([172]Table S6). These results
   suggest that the ABA signaling pathway was related to the response to
   RKNs in eggplant. In addition, BR biosynthesis gene BAK1 is highly
   expressed in Tor. The BAK1 and FLS2 genes play important roles in the
   plant immune response, and the RKN effectors may interact with BAK1 an
   FLS2 during invasions [[173]16]. Thus, BR might be important for the
   defense against RKNs.

   MapMan mapping also showed the transcription factors (ERF, MYB, WRKY,
   and HSP) involved in the defense against RKNs ([174]Figure 6 and
   [175]Figure 7). Previous studies reported that ethylene signaling can
   positively regulate the plant response to RKN invasion via activating
   jasmonate biosynthesis [[176]24,[177]38]. In our study, a large number
   of ERFs were differentially expressed in Sme and Tor ([178]Figure 6 and
   [179]Table S5). WRKY is a large family of transcriptional regulators in
   plant–pathogen interactions. Previous studies reported that WRKY23
   influences the early response to RKN infection [[180]7]. We also
   identified many WRKYs that were differentially expressed between Sme
   and Tor ([181]Table S4). The expression levels of WRKY69 and WRKY75
   were validated by qRT-PCR ([182]Figure 8). Therefore, the WRKY genes
   are involved in the pathogen resistance of the eggplant plant host. In
   addition, NAC TFs have been reported to regulate cell wall remodeling
   after RKN infection in Cucurbitaceae crops [[183]7].

4. Materials and Methods

4.1. Plant Material and Nematode Infection

   Seeds of Solanum torvum Sw accession TG1 (RKN-resistant) and eggplant
   (Solanum melongena L., RKN-susceptible) breeding line Sme were sown in
   a seed plot for germination according to Gousset et al. (2005)
   [[184]39]. Seedlings at the fifth-leaf stage were transplanted into 15
   cm diameter plastic pots, with 500 cc of a mixture of sterilized sandy
   soil [[185]40]. The pots were maintained in controlled chambers at 28
   °C, 70% humidity, with a 14 h light/10 h dark. Then, the resistant
   (torvum (Tor)) and susceptible (Sme) lines were inoculated at the base
   of the plant stem with hatched root-knot nematode (Meloidogyne
   incognita, RKN) at the second larval stage (J2). RKNs were maintained
   in the greenhouse on eggplant; eggs masses were extracted as described
   by Shukla et al. (2018) [[186]19]. For transcriptome study, the Sme and
   Tor lines were sampled at the uninfected stage (CK) and 7, 14, and 28
   days post-infection (dpi) in the susceptible response. The soil was
   removed from the root tissues collected from each type of plant, the
   plants were washed with water and then frozen in liquid nitrogen to
   prevent RNA degradation. Finally, root samples were stored at –80 °C
   until RNA isolation.

4.2. RNA Extraction and Library Preparation for Transcriptome Sequencing

   Total RNA was extracted from S. torvum (Tor) and eggplant (Sme) roots
   with three biological replicates for each condition using the Trizol
   RNA extraction Kit (Tiangen, Beijing, China). RNA quality was assessed
   using an Agilent Bioanalyzer 2100 (Agilent Technologies, Foster, CA,
   USA). In all the samples tested, the RNA integrity number (RIN) was
   above 9, whereas the concentration ranged from 200 to 300 ng/μL. Then,
   1μg of RNA per sample was used as the input material for RNA sample
   preparation. Sequencing libraries were produced using NEB ultra RNA
   Library Prep Kit for Illumina (NEB, Columbia, MA, USA) following the
   manufacturer’s recommendations. The quality of the PCR libraries was
   assessed on an Agilent Bioanalyzer 2100 system (Agilent Technologies,
   Foster, CA, USA). Finally, PCR libraries were sequenced on an Illumina
   Hiseq4000 platform and 150 bp paired-end reads were generated. All the
   clean reads were deposited in the National Center for Biotechnology
   Information (NCBI) Sequence Read Archive under accession: PRJNA688588.

4.3. De Novo Assembly of S. torvum Transcriptome and Functional Annotation

   Using Trinity, the clean reads of Tor samples were assembled in
   transcripts and unigenes [[187]41]. Then, the sequences of these
   unigenes were further searched against to four protein databases by
   BLASTx with E-value < 1 × 10^−5. The databases included NCBI
   non-redundant protein (NR) database, NCBI nucleotide (NT) database,
   Pfam, Clusters of eukaryotic Orthologous Groups of proteins (KOG)
   database, Swiss-Prot, Gene Ontology (GO) and Kyoto Encyclopedia of
   Genes and Genomes (KEGG) pathway database. Moreover, the homologous
   genes of Tor for eggplant were identified using BLASTn. FPKM (fragments
   per kilobases of exon per million fragments mapped) values for each
   sample were counted using RSEM software [[188]42].

4.4. Identification of Differentially Expressed Genes

   After sequencing, the raw data, in FASTQ format, were filtered through
   the FASTX-Toolkit. The clean reads were obtained by trimming the
   adapter contaminants, removing low-quality reads, and reads containing
   poly-N. Q20 and Q30 scores and the GC content of the clean data were
   calculated by FastaQC. All the downstream analyses were based on
   high-quality clean reads. TopHat2 (version 2.1.0) was used to map these
   paired-end clean reads to the Eggplant Genome Database reference genome
   ([189]http://eggplant.kazusa.or.jp/, accessed on 1 October 2014)
   [[190]43]. Transcript assembly was conducted using Cufflinks software
   version 2.2.1 [[191]44]. DESeq2 was used to identify DEGs with the
   fragments per kilobases of exon per million fragments mapped (FPKM)
   values [[192]45]. The significant difference was determined with a
   false discovery rate (FDR) threshold of 0.05 and log2 fold change of ≥1
   or ≤−1.

4.5. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
Pathway Enrichment Analysis

   To assign the function annotation, all the assembled transcripts were
   searched using Blastx (E-value < 1 × 10^−5) against Pfam
   ([193]http://pfam.janelia.org/, accessed on 1 October 2020), Swiss-prot
   (UniProt), and NR (NCBI). The DEGs were annotated with Gene Ontology
   (GO) terms to investigate the putative functions. Additionally, GO
   enrichment analysis was performed using the AgriGO program [[194]46].
   The statistical significance of GO terms was measured by a Fisher’s
   exact test corrected by an FDR of <0.05. The Kyoto Encyclopedia of
   Genes and Genomes (KEGG) pathways were determined using KOBAS3.0
   ([195]http://kobas.cbi.pku.edu.cn/, accessed on 1 October 2020) with an
   enrichment p-value < 0.05 [[196]47]. Moreover, the differentially
   modulated genes between Sem and Tor at 7 dpi and 14 dpi were mapped
   using MapMan v3.6.0. Additionally, the transcript regulation categories
   were classified.

4.6. Quantitative Real-Time PCR (qRT-PCR) Analysis

   Total RNA was extracted from the roots of Sme samples at four stage
   using Trizol (Invitrogen, Carlsbad CA, USA) according to the
   manufacturer’s instructions. Approximately 2 μg of total RNA was
   reverse transcribed using a RevertAid First Strand cDNA Synthesis Kit
   (Fermentas, Waltham, MA, USA). Then, the cDNA was synthesized and
   qRT-PCR was performed in 20 μL of reaction mixture with the ABI One
   step plus Real-Time Detection System (Applied Biosystems, Foster, CA,
   USA) using the Toybo SYBR Mix with ROX (CWBIO, Beijing, China). The
   thermal profile for qPCR was 95 °C for 3 min, followed by 45 cycles of
   95 °C for 15 s, and 60 °C for 1 min. Three biological replicates were
   performed for each sample. All the primers used in this study are
   listed in [197]Table S1. A melting curve analysis was performed to
   determine the specificity of the products. The reference gene (tubulin
   gamma (Sme2.5_03686.1_g00005.1)) was used for normalization. The
   relative gene expression level for each gene was analyzed using the
   comparative 2^△△CT method [[198]48].

5. Conclusions

   In this study, we investigated the transcriptome profiles of eggplant
   and its relative species and the defense mechanisms against RKN
   invasion. In total, we identified 9214 DEGs in response to RKN
   infection at four time points (ck, 7, 14, and 28 dpi). GO and KEGG
   enrichment analysis revealed that these DEGs are mainly involved in
   hormone signal transduction and plant-pathogen interaction pathways.
   Many pathogen-associated genes and NBS-LRR genes were induced during
   the RKN infection. Some plant hormone (auxin, ethylene, and
   ABA)-related genes were also differentially expressed, indicating their
   roles in the defense resistance. Our findings are important for further
   research on the defense mechanisms of eggplant against RKNs invasion.
   Furthermore, the transcription factors and ABA signaling genes
   identified in our study might be useful for developing
   nematode-resistant cultivars in eggplant breeding.

Supplementary Materials

   The following are available online at
   [199]https://www.mdpi.com/article/10.3390/pathogens10040470/s1, Figure
   S1: Sample correlation between the 24 samples. Figure S2: Detailed
   information if the transcriptome assemblies of Tor. Figure S3:
   Schematic of the plant-pathogen interaction pathway category from the
   Kyoto Encyclopedia of Genes and Genomes (KEGG). Figure S4: Heatmap
   showing the expression patterns of genes encoding F-box/LRR-repeat and
   TMV resistance protein. Figure S5: The relative expression of genes
   involved in the abscisic acid (ABA) metabolism pathway. Table S2:
   Summary of the sequence data generated by RNA-Seq. Table S2: Summary of
   the transcriptome assemblies of Tor. Table S3 Detailed information of
   simple sequence repeat (SSR) and primers in Tor. TableS4: The
   expression patterns of the 5360 differentially expressed core genes for
   root-knot nematode (RKN) infection. Table S5: The expression patterns
   of 4020 differentially expressed genes for resistance to RKNs. Table
   S6: The expression patterns of differentially expressed genes related
   to phytohormones and transcription factors. Table S7: KEGG pathways of
   differentially expressed genes between Sme and Tor. Table S8: Primers
   used for qRT-PCR in the study.
   [200]Click here for additional data file.^ (9.5MB, zip)

Author Contributions

   M.Z., H.Z. and X.X. designed the study. M.Z., H.Z., J.T., S.H. and X.C.
   carried out the experiment, data analysis, and interpretation of the
   results. M.Z. drafted the manuscript. M.Z., X.X. and D.J. provided
   funding, supervised the work and revised the manuscript. All authors
   have read and agreed to the published version of the manuscript.

Funding

   This work was financially supported by the National Key Research and
   Development Program of China (2017YFD0101904), the Wuhan Science and
   Technology Planning Project (Grant No. 2020020601012260) and the
   Natural Science Foundation of Hubei Province (Grant No.
   ZRMS2019001222).

Institutional Review Board Statement

   Not applicable.

Informed Consent Statement

   Not applicable.

Data Availability Statement

   Not applicable.

Conflicts of Interest

   The authors declare no conflict of interest.

Footnotes

   Publisher’s Note: MDPI stays neutral with regard to jurisdictional
   claims in published maps and institutional affiliations.

References