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Article

Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation

by
Suparat Pinsupa
1,
Keasinee Tongmark
2,
Wanchana Aesomnuk
2,
Kannika Srikaewtung
2,
Sriprapai Chakhonkaen
2,
Patcharaporn Summart
2,
Numphet Sangarwut
2,
Wanwarang Pathaichindachote
3,4,
Samart Wanchana
2,
Kittipat Ukokit
1 and
Amorntip Muangprom
2,*
1
Department of Biotechnology, Faculty of Science and Technology, Thammasat University, Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand
2
National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand
3
Department of Agricultural Sciences, Faculty of Agriculture, Natural Resources and Environment, Naresuan University, Phitsanulok 65000, Thailand
4
Center of Excellent in Research for Agricultural Biotechnology, Faculty of Agriculture, Natural Resources and Environment, Naresuan University, Phitsanulok 65000, Thailand
*
Author to whom correspondence should be addressed.
Horticulturae 2023, 9(2), 127; https://doi.org/10.3390/horticulturae9020127
Submission received: 1 December 2022 / Revised: 23 December 2022 / Accepted: 27 December 2022 / Published: 17 January 2023

Abstract

:
Leptocybe invasa is a gall wasp causing significant damage to Eucalyptus species. This study used RNA sequencing (RNA-seq) to identify differentially expressed genes (DEGs) associated with early L. invasa infestation in eucalyptus parents and their F1-progenies. A total of 14,648 significant DEGs were identified from U22-tolerant and C153-susceptible parents, and extremely tolerant and susceptible pools of their F1-progenies. A total of 324/632 and 182/205 DEGs specific for the tolerant group and the susceptible group were up-regulated, respectively. Expression analysis by qRT-PCR of the selected DEGs was comparable with the results of RNA-seq. Expression analysis of the selected genes using the top five progenies from each pool was consistent with that in the parents. Three genes (RCA, SUI1, GCN5) were up-regulated after infestation in all tested tolerant plants, suggesting their important roles in the tolerant phenotype. Using expression and STRING analysis, our results suggest that early response at three days after gall wasp infestation increased protein and terpenoid synthesis, and increased transportation of these molecules. In addition, wounding also increased photosynthesis and glycolysis. These processes involved the interaction of several plant hormones, such as JA, Auxin, and ABA. The information obtained from this study could be useful for future Eucalyptus breeding programs.

1. Introduction

The Myrtaceae is a large family of dicotyledonous woody plants providing important economic resources such as fresh fruits and timber or fiber in multiple industries. The genus Eucalyptus is one of this family with approximately 700 species [1,2]. Eucalyptus camaldulensis is widely planted across the world for timber and pulp [3,4]. However, various species of Eucalyptus have been affected by major diseases and pests resulting in loss of production.
One of the most crucial insect pests is the Eucalyptus gall wasp, Leptocybe invasa Fisher & La Salle [5]. It originated in Australia and then was distributed to other regions wherever its host trees are found including several countries in the tropical and subtropical areas [6]. In India, wood production was destroyed due to heavy damage caused by gall wasp infestation [6,7,8]. The damages caused by gall wasps were also devastating in Egypt, Vietnam, Israel, China, Sri Lanka, Mexico, Tanzania, and Thailand [6,7,8,9,10,11,12,13,14]. The gall wasps cause leaf midribs, petioles, and young twigs to swell, deform, and grow abnormally. In the end, the death of a young tree may occur [5,6,13]. After attacking by laying eggs into vascular tissues, the life cycle of the tiny gall wasp is a parasite or an endophytic on the tree by using the nutrients from the plant vascular system as a food source [5,15,16,17]. Gall development is composed of five stages from egg to adult emergence [5]. Several researches studied the biology of this gall wasp. These studies have shown similar results in the different timelines of gall development depending on Eucalyptus species and their growing environments [5,8,14,17].
The insect can trigger plant defenses by signaling pathways through plant-insect interactions [16,18,19,20]. Several plant molecules associated with defensive responses to biotic stresses were reported in Eucalyptus, including terpenes, phenolic compounds [21,22,23], pathogenesis-related proteins or PR proteins [24], and heat shock proteins [25]. These defense-related genes were identified through resistant and susceptible phenotypic appearances. In plant-galling insect interaction, the first stage of the gall wasp life cycle occurs one to twoweeks after oviposition [5,14]. A recent study indicates that the response time to gall development in the susceptible clones differs from the resistant clones, especially the duration of the hatching of the wasp [26]. Early responses of Eucalyptus against gall wasp oviposition may lead to highly resistant or susceptible levels.
In recent years, RNA sequencing (RNA-seq) has been an approach for transcriptome analysis used to study and identify the differentially expressed genes (DEGs) by comparing different conditions [27,28,29]. RNA-seq reveals DEGs and leads to a new understanding of the genes or pathways associated with interesting traits [30,31,32,33]. In Eucalyptus spp., RNA sequencing has been used to identify genes against gall wasp [23], pathogens [34,35], wood and growth [36], and water stress [37].
This study used RNA-seq to investigate early response in terms of alterations of gene expression in Eucalyptus at three days after gall wasp oviposition. The tolerant and susceptible groups were used to identify DEGs under infested and un-infested conditions. The candidate DEGs were validated using RT-PCR. The potential gall-wasp-responsive genes could be useful for the development of tolerant Eucalyptus against gall wasps in future breeding programs.

2. Materials and Methods

2.1. Plant and Insect Materials

The galling insect, L. invasa, was collected in 2015 in Prachinburi province, Thailand. As gall stock plants, highly susceptible commercial eucalyptus clones (E. camaldurensis × E. deglupta) were grown in the greenhouse with a mesh enclosure. C153-S was chosen as a susceptible parent due to its high galling, meanwhile, U22-T was used as a tolerant parent due to its limited signs of oviposition but no galls. C153-S and U22-T were crossed in late 2015 to produce F1-progenies. In 2018, an experiment was conducted to determine susceptibility to gall wasp infestation of the F1-progenies.
After gall wasp infestation, developmental stages of gall formation by L. invasa were classified into 5 stages Stage 1, the first symptoms showed the oviposition scars at the oviposition site (oviposition signs) on the young vascular tissues. In this stage, the phenotype change was classified into grades 1 and 2 of the damage severity level. In stages 2–4, the gall was enlarged. The phenotype change was classified into grades 3 and 4 of the damage severity level. Finally, the adult emerged from the gall in stage 5 (Figure 1a). Based on the number of oviposition signs and galls visible on the whole tree [38,39], the phenotype changes were used to assess the damage severity level of two parents and F1-progenies that was divided into five-grade criteria (Figure 1b) as follows;
Grade 0 = no oviposition
Grade 1 = less than ten oviposition signs but without gall development
Grade 2 = 10 and more oviposition signs, multiple sprouts without gall development
Grade 3 = less than ten galls
Grade 4 = 10 and more galls
Ramets were observed on the whole plant for gall formation 90 days after sampling to confirm the identities of the tolerant and sensitive phenotypes in all samples. According to the five-grade criteria of the damage severity level, U22-T showed 2 signs of oviposition but without galls, while C153-S showed over 30 galls. Eighteen tolerant progenies showed signs of oviposition but without galls, while 19 susceptible progenies showed galls on midribs and petioles (Figure 1c). Eighteen extremely tolerant and nineteen extremely susceptible F1-progenies were used as 2 sample pools.

2.2. Gall Wasp Infestation Trial and Sample Collection

The two parents (C153-S, U22-T), as well as the selected 18 extremely tolerant and 19 extremely susceptible F1-progenies, were propagated using tissue culture techniques and kept in the greenhouse free of chemicals and insect infestation. Each clone at 60 days of age was assigned into two groups, control, and treatment. The experiment was conducted using a completely randomized design, with five replications. The control group did not receive insect inoculation, whereas the test group was inoculated with artificial insects. Each group was placed in a separate mesh-enclosed cage.
Gall stock plants that were extensively infested by L. invasa were gathered and kept in the mesh-enclosed greenhouse. Four gall stock plants carrying over 20 red galls were planted in the test cage after other herbivores and pathogens were carefully removed. The experimental trees were monitored and tagged on a daily basis in the test cage.
Whole infested leaf tissues, including petioles, were collected from each experimental tree’s shoots three days after gall wasp infestation. In the control cage, leaf tissues from the same experimental tree’s shoots were collected at the same time. All samples were immediately frozen in liquid nitrogen and kept in a freezer at −80 °C until used.

2.3. RNA Samples Preparation

For each experimental clone, whole-leaf tissues, including petioles from infested and un-infested shoots, were collected. The RNeasy Plant Mini Kit (QIAGEN, Hilden, Germany) was used to extract total RNA according to the manufacturer’s instructions. A Nanodrop spec-trophotometer was used to evaluate the quality and quantity of all RNA samples prior to sequencing (Thermo Scientific, Medison, WI, USA). Total RNA, 50 ng/µL, from each of 18 tolerant and 19 susceptible samples, were used to make tolerant and susceptible pools, respectively. The eight total RNA samples, including C153-S infested (susceptible parent infested; C153-SI), U22-T infested (tolerant parent infested; U22-TI), the F1 tolerant pool infested (non-galling infested; NGI), the F1 susceptible pool infested (galling infested; GI), C153-S un-infested (susceptible parent un-infested; C153-SC), U22-T un-infested (tolerant parent un-infested; U22-TC), the F1 tolerant pool un-infested (non-galling un-infested; NGC), and the F1 susceptible pool un-infested (galling un-infested; GC) were then sent to Novogene (Beijing, China) for RNA sequencing.

2.4. RNA Sequencing, Mapping, and Assembly

The complementary DNA (cDNA) libraries were prepared according to the manu-facturer’s instructions from the eight samples and were sequenced using the Illumina Hiseq2000 platform to create 150 bp paired-ends (PE150) sequence reads. Base-calling was used to transform the raw readings from Illumina into sequenced reads. Raw reads were saved in a FASTQ file that included sequence information (reads) and sequencing quality data. Base quality and Phred score relationship were analyzed with the Illumina CASAVA v1.8 software. To verify data quality, FASTQC was utilized. Trimmomatic was used to filter and trim raw reads to remove adaptor sequences, low-quality reads (Q value < 20), and poly N [40]. High-quality clean reads were used in all bioinformatic analyses. The Eucalyptus grandis genome and annotation files were obtained from the E. grandis phytozome database (http://www.phytozome.net/eucalyptus.php, as accessed on 28 June 2019). HISAT2 [41] with default parameters was used to map the high-quality clean reads to the E. grandis reference genome. StringTie was used to assemble mapped readings into transcripts and quantify them [42]. The differential gene expression analysis was examined after mapping, assembling, and quantifying. For the gene expression level, the number of fragments per kilobase of exon per mil-lion mapped reads (FPKM) was estimated.

2.5. Analysis of Differentially Expressed Genes

The edgeR [43] was used for differential expression analysis to assess and identify genes that are differentially expressed between infested and un-infested conditions of each sample, including the two parents (C153-S and U22-T), and the extreme F1 pools (tolerant and susceptible). FPKM was used to calculate the gene expression level. The log2 fold change (logFC) was calculated using the FPKM values as log2 (FPKM infested/FPKM un-infested). Values greater than zero were deemed up-regulated, whereas values less than zero were considered down-regulated [44]. Benjamini and Hochberg’s technique was used to estimate the p-value threshold for the false discovery rate (FDR) [45]. Differentially expressed genes were chosen using a 0.05 adjusted value criterion [36,37]. The logFC ≥ 1 and ≤−1, q-value ≤ 0.05, and FPKM > 1 were chosen as significant DEG for validation. Venn diagram in the Venny 2.1 software was used to assess significant DEGs between each sample [46].

2.6. Gene Functional Annotation

Gene Ontology (GO) functional classifications and enrichment analysis of individual DEGs were performed using the WEGO website (https://wego.genomics.cn, as accessed on 12 October 2021). The p-value was determined using the Pearson Chi-Square test. Significant enrichment was defined as a p-value threshold of less than 0.05 [47].

2.7. Expression Analysis

Using quantitative real-time PCR (qRT PCR), nine DEGs were chosen to validate the results of RNA-seq analysis using cDNA from two parents, U22-T and C153-S, under in-fested and un-infested conditions. These DEGs were selected because they showed specific expression in the tolerant group (U22-T and F1 tolerant pool). The cDNA was synthesized from the total RNA of each sample using the Thermo Scientific RevertAid First Strand cDNA Synthesis Kit according to the manufacturer’s instructions. The qRT-PCR was per-formed on the CFX96 Touch Real-Time PCR Detection System with the qPCRBIO-SYGreen Mix Lo-ROX (PCR Biosystems) (BIORAD). All PCR conditions were performed similarly to a previous study [46]. The CFX manager 3.0 (BIORAD) application was used to determine relative gene expression using the 2−∆∆Ct technique [48].
To determine expression patterns of the selected genes in F1 pools and F1 individuals, the reverse transcriptase PCR (RT-PCR) was performed using cDNA from two parents, two pools, five extremely tolerant individuals, and five extremely susceptible individuals un-der infested and un-infested conditions. Five tolerant and susceptible individuals were selected from the top 5 of each pool that showed the lowest or highest number of oviposition, respectively. Coding DNA Sequences (CDS) of the selected genes were retrieved from the NCBI database (www.ncbi.nih.gov/nuccore, as accessed on 22 October 2020) and the Primer-BLAST webserver (www.ncbi.nlm.nih.gov/tools/primer-blast, as accessed on 10 January 2021) was used to design gene-specific primers (Supplementary Table S1). For normalization, histone 2B (H2B) was employed as the reference gene [49]. All primers were synthesized by Macrogen (Seoul, Korea). The cDNA was synthesized as previously described. A thermal cycler (BIORAD) was used to perform RT PCR. All PCR conditions were performed similarly to a previous study [50,51]. The PCR products were used to visualize the gene expression levels using 2 percent agarose gels.

3. Results

3.1. Sequencing Analysis

To identify differentially expressed genes in early response to gall wasp infestation, a total of eight cDNA libraries, including C153-S infested (susceptible parent infested; C153-SI), U22-T infested (tolerant parent infested; U22-TI), the tolerant pool infested (non-galling infested; NGI), the susceptible pool infested (galling infested; GI), C153-S un-infested (susceptible parent un-infested; C153-SC), U22-T un-infested (tolerant parent un-infested; U22-TC), the tolerant pool un-infested (non-galling un-infested; NGC), and the susceptible pool un-infested (galling un-infested; GC), were constructed and sequenced.
A total of 0.43 billion raw reads were generated from the eight libraries. Reads per sample ranged from 43.0 to 63.3 million with an average of 53.7 million raw reads. After filtering and trimming, the high-quality clean reads of each sample were generated and ranged from 41.2 to 59.4 million with an average of 51.1 million. For all libraries, more than 97% of clean reads had a high-quality score at the Q20 level (error probability of 0.01), and more than 81% of clean reads were mapped to the E. grandis reference genome. GC content was similar among the samples and ranged from 50.8% to 51.6%. The average GC content was 51.2% (Table 1).
Subsequently, mapped reads were assembled and quantified with the StringTie. A total of 29,015 genes were identified from all samples and showed FPKM values greater than 0 and were considered as expressed.

3.2. Analysis of DEGs Responses to Gall Wasp Infestation

The differential gene expression in two parents and two pools under infestation and un-infestation conditions was analyzed with the edgeR. Genes that had an adjusted q-values threshold of 0.05 were selected as differentially expressed. U22-T revealed 5859 significant DEGs, of which 3694 were up-regulated, and 2165 were down-regulated. C153-S showed 4296 DEGs, of which 3198 were up-regulated, and 1098 were down-regulated. The tolerant pool revealed 2379 DEGs, of which 1375 were up-regulated, and 1004 were down-regulated. The susceptible pool showed 2114 DEGs, of which 1549 were up-regulated, and 565 were down-regulated genes (Figure 2a). The overlap area of U22-TI vs. U22-TC and NGI vs. NGC included 676 unique genes specific for the tolerant group, and the overlap area of C153-SI vs. C153-SC and GI vs. GC included 280 unique genes specific for the susceptible group (Figure 2b).
After analyzing and filtering data of up-and down-regulated DEGs, 632 out of 676 DEGs specifics for the tolerant group showed similar patterns of expression in both U22-T and the tolerant pool, of which 324 genes were up-regulated, and 308 genes were down-regulated. Meanwhile, 205 out of 280 DEGs specifics for the susceptible group, of which 182 up-regulated and 23 down-regulated, showed similar patterns of expression in both C153-S and the susceptible pool (Figure 3a).
For DEGs specific to the tolerant group, there are two genes, Eucgr.K00881 (encoded terpene synthase 03) and Eucgr.K02129 (encoded cytochrome P450, family 82, subfamily G), associated with response to the insect. Two genes, Eucgr.E03999 (encoded peroxidase) and Eucgr.H04662 (encoded linoleate 13S-lipoxygenase), are associated with wounding responses. Fifteen genes associated with stress responses, such as Eucgr.H01335 (encoded hydrophobic protein RCI2), Eucgr.B01155 (encoded endo-1,3-1,4-beta-D-glucanase), Eucgr.A02889 (encoded trehalose phosphatase), and Eucgr.G01884 (encoded protein phosphatase 2C). Eight genes, such as Eucgr.H00360, Eucgr.C02142, and Eucgr.E02163 contain the leucine-rich repeat domain that is associated with immune responses. In addition, several genes in our transcript analysis related to the biosynthesis of phytohormones and secondary metabolites.
Furthermore, Log2 Fold Change (logFC) values of 324 up-regulated and 308 down-regulated genes specific for the tolerant group were in the range from 1.3238 to 13.5874 and −15.7433 to −1.3117, respectively. The logFC values of 182 up-regulated and 23 down-regulated genes specific for the susceptible group were in the range from 1.4703 to 10.8553 and −10.0072 to −1.4807, respectively. The DEGs specific to the tolerant group was shown in Supplementary Table S2.
Based on the E. grandis genome, the highest number of the specific DEGs were present on chromosome 8 while the lowest number was found on chromosome 4. The number of DEGs specific for the tolerant and susceptible groups on the chromosomes of the Eucalyptus genome is shown in Figure 3b.

3.3. Functional Annotation and Enrichment Analysis

To understand the functions of DEGs specific for the tolerant and susceptible groups, WEGO was used to categorize and analyze all these DEGs. A total of 632 DEGs specific for the tolerant group (U22-T and the tolerant pool) and 205 DEGs specific for the susceptible group (C153-S and the susceptible pool) were mapped to terms in the GO databases and categorized into three main categories including biological process (BP), molecular function (MF), and cellular component (CC) of the GO classification. The WEGO analysis categorized 632 DEGs specific for the tolerant group (324 up-regulated and 308 down-regulated genes) into 33 functional terms. Meanwhile, 205 DEGs specific for the susceptible group (182 up-regulated and 23 down-regulated genes) were categorized into 23 functional terms. The susceptible group had a higher percentage of genes in the BP and MF categories than that in the tolerant group. Meanwhile, the tolerant group had a higher percentage of genes in the CC category than that in the susceptible group (Figure 4).
Moreover, the WEGO enrichment analysis was used to analyze DEGs specific for the tolerant and susceptible groups by comparing the tolerant and susceptible groups with p-value thresholds less than 0.05. A total of 632 DEGs specific for the tolerant group and 205 DEGs specific for the susceptible group were significantly enriched in seven main functional terms, in which five functional terms were under the biological processes, and two functional terms were under the molecular function. Five functional terms under the biological processes were metabolic processes (GO: 0008152), cellular processes (GO: 0009987), response to stimulus (GO: 0050896), biological regulation (GO: 0065007), and regulation of biological processes (GO: 0050789). In the functional term of the response to stimulus under the biological processes, genes associated with base-excision repair, mismatch repair, SOS response, and drug transmembrane transport were found in the tolerant groups, while genes associated with defense response to bacterium or fungus were found in the susceptible groups. Two functional terms under the molecular function were catalytic activity (GO: 0003824) and binding (GO: 0005488) (Figure 5).

3.4. Expression Analysis

To validate the expression patterns obtained by RNA-seq, the two parents were used as templates using the qRT-PCR method. Based on selection criteria, including (a) the logFC ≥ 1 and q-value ≤ 0.05, or (b) FPKM value that showed high or low expression in the tolerant group (U22-T and F1 tolerant pool), nine genes were selected. The nine genes were Eucgr.K00881 (encoded terpene synthase 03; TPS03), Eucgr.B02310 (encoded rubisco activase; RCA), Eucgr.F00808 (encoded translation initiation factor SUI1 family protein; SUI1), Eucgr.I00319 (encoded general control non-repressible 5; GCN5), Eucgr.E03228 (encoded HAESA-like 1; HSL1), Eucgr.F02183 (encoded tubulin alpha; TUA), Eucgr.G00649 (encoded glycosyl hydrolase family 3 C-terminal domain; GH3), Eucgr.H03228 (encoded leucine-rich repeats receptor-like kinase; LRR), and Eucgr.I00448 (encoded UDP-glucosyl transferase 73B3; UGT73B3) Histone 2B (H2B) gene was used as the reference gene in every experiment. According to the qRT-PCR results, the normalized expression patterns showed consistent patterns as observed in the RNA-Seq data, except for Eucgr.I00448 (Figure 6). The four genes, including TPS03, SUI1, RCA, and GCN5, showed significant up-regulation in the tolerant parent. These genes of interest were used for validation in the tolerant and susceptible pools.
To validate the expression patterns of the genes of interest from qRT-PCR results in two pools (the tolerant and susceptible pools) and the selected individual plants under infested and un-infested conditions, the RT-PCR method was utilized and the H2B gene was used as the internal control. The four genes of interest, including TPS03, SUI1, RCA, and GCN5, were found to be up-regulated in the tolerant parent (U22-T) and the tolerant pool, while they were down-regulated or did not show expression in the susceptible parent (C153-S). However, the susceptible pool did not show a similar pattern of expression with the susceptible parent (Figure 7a).
To investigate the expression patterns of the four genes in the individuals used in the pool samples, five tolerant individuals from the tolerant pool and five susceptible individuals from the susceptible pool were selected and used as templates. All four genes except TPS03 were found to be up-regulated in all five tolerant individuals similar to their tolerant parent. These genes were down-regulated or did not change the level of expression in most of the five susceptible individuals similar to their susceptible parent, except in S4 (Figure 7b).

4. Discussion

The Eucalyptus gall wasp, L. invasa, is a plant parasite. The plant’s defensive mechanisms were activated after the oviposition of the insect. Using RNA seq, this study identified DEGs associated with the early response three days after the infestation of L. invasa. The E. grandis genome v2.0 was utilized as a reference genome to map the clean reads from the transcriptome sequencing. Our transcript analysis identified 14,648 DEGs between infested and un-infested conditions. All the selected 18 F1-tolerant progenies did not have galls similar to their tolerant parent (U22-T), while the 19 F1-susceptible progenies had gall formation similar to their susceptible parent (C153-S). The tolerant and susceptible F1 pools were used to reduce the number of DEGs to identify specific DEGs for each group. The tolerant group was U22-T and the F1-tolerant pool, and the susceptible group was C153-S and the F1-susceptible pool. Our results demonstrated that the number of DEGs in the tolerant group was higher than those in the susceptible group, similar to the studies with cotton-whitefly [30], tobacco-phytophthora [52], and barley-powdery mildew [53]. Our results showed that the number of up-regulated genes was higher than the number of down-regulated genes, similar to other studies [23,30,52,53,54].
Our analysis indicated that the number of genes in the BP and MF categories was higher than in the CC category. The functional genes in terms of binding have the highest enrichment. These results are similar to other studies on plant pathogens in cotton [30], eucalyptus [35], tobacco [52], and wheat [55].

4.1. Several Genes Associated with Plant Hormones and Volatile Organic Compounds Involved in Response to Gall Wasp Infestation

After gall wasp infestation, the wound appeared where the eggs were laid. Plants produce volatile organic compounds under natural and stressed conditions, and these compounds may play an essential role in both abiotic and biotic interactions [56,57]. Monoterpenes are one common volatile compound that can be released and play an important role in plant-insect interactions [58]. The TPS-b subfamily is the group of genes related to monoterpene synthesis. The TPS03 gene belongs to the TPS-b subfamily [59,60]. The TPS03 gene was induced in Arabidopsis and poplar leaves in response to herbivore feeding [61,62]. Similar results were observed following the gall wasp infestation in our study. The TPS03 gene was reported to be highly expressed in the eucalyptus-resistant clone [23], comparable with our results. However, this gene did not show up-regulation in all the tested tolerant plants, suggesting that this gene may not be needed in all the tolerant plants in this stage of infection.
Our study showed that several genes encoding plant hormones were found to be DEGs involved in response to gall wasp infestation. Plant hormones act as a signal in signal transduction. They play a central role in regulating plant growth, development, and defense processes [63] as well as, play critical roles in response to wounding [64,65]. Three auxin-responsive gene families, including Aux/IAA, GH3, and SAUR (Small Auxin-Up RNA) were induced in response to auxin [66,67]. The expression of SAUR genes was reported to be rapidly induced by auxin and it was regulated at both the post-transcriptional and post-translational levels [68,69]. Our results showed that SAUR had higher expression in the tolerant group after infestation but showed similar levels in both conditions in the susceptible group. AtSAUR32 was reported to play an essential role in abiotic stress tolerance through mediated abscisic acid (ABA), which is well known as a stress plant hormone [70,71]. The ABA 8′-hydroxylase enzyme (CYP707A4) initiated the ABA catabolic pathway [72] and showed higher expression in plant tissues that recover from water stress [73]. Similarly, this gene was up-regulated in our tolerant group under an infested condition. Up-regulation of these genes in our findings suggests that they may be associated with the early stage of responses to eucalyptus gall wasp infestation resulting in the tolerant phenotype.

4.2. Changes in Interesting Genes in the Tolerant and Susceptible Groups

Most of the expression patterns of the selected nine genes by qRT-PCR were consistent with the results of RNA-seq, suggesting that the RNA-seq results are reliable. Four genes, including TPS03, RCA, SUI1, and GCN5, were selected to validate in two pools, and in the individual extreme plants due to the high statistical significance in up-regulated expression in the tolerant parent after infestation. The results of using RT-PCR were comparable with the results of qRT-PCR and the RNA-seq analysis in most of the samples. Although all progenies in the susceptible pool presented gall formation, the susceptible pool in our results showed some inconsistencies in the expression analysis compared with their susceptible parent. A wide range of different degrees of susceptibility among progenies in the pool may affect our expression results. The three genes, RCA, SUI1, and GCN5 showed expression levels in the five individuals from the tolerant pool consistent with those in their specific pool and the tolerant parent, while TPS03 showed high expression levels in most of the tolerant samples. Although terpene synthase was reported to be associated with response to gall wasp infestation for seven days [23], it may not be needed for all tolerant responses in the early stage of gall wasp infestation. The expression patterns of some genes in S4, one of five individuals used in the susceptible pool, were not consistent with others, probably due to some variation in its genotype. However, most of the susceptible samples were consistent with their specific pool.
Eucgr.B02310 gene encodes Rubisco activase; RCA. This gene was up-regulated in all the tested tolerant plants and was down-regulated or did not change in expression level in all the tested susceptible plants. The RCA enzyme is crucial in photosynthesis because it mediates the activation of inactive Rubisco by interacting with ATP [74,75]. Photosynthesis is the primary metabolic mechanism and a key component of light, carbon, and nitrogen signaling pathways [76]. After plant-insect interaction, tolerant plants can maintain photosynthetic capacity and rates in barley, wheat [76], and maize [77], suggesting that insect-resistant genotypes have a higher photosynthetic potential than susceptible plants. Moreover, tolerances showed a highly expressed level of RCA in wheat [78], and Arabidopsis [79] under drought and heat stress. Furthermore, the RCA gene was reported to play a direct role in reducing JA-induced defensive responses in tobacco [80]. Our results complied with these reports by showing up-regulation of this gene in the tolerant plants, suggesting its role in the tolerant phenotype.
One of the largest protein families is the ATP-binding cassette (ABC) transporter superfamily [81,82]. ABC transporters are involved in transporting plant hormones and secondary metabolites and responding to biotic stresses [81,83,84,85,86]. The functional characterization of plant ABCFs revealed that they are involved in various activities. Eucgr.I00319 gene encoded general control non-repressible 5; GCN5 or ABC transporter F family member 5; ABCF5. ABCF5, Gorai.007G244600, showed high up-regulation in cotton under virus infection. Their results suggested that ABC genes might play an important role in enhancing resistance to viral infection [83]. Similarly, this gene showed up-regulation in the tolerant plants after infestation in our study. This result demonstrated that ABCF5 might enhance resistance to gall wasp infestation.
Eucgr.F00808 gene encoded SUI-homologous translation initiation factor eIF1 (eIF1); SUI 1. This gene plays an important regulatory role in the recognition of the start codon, AUG, to initiate the translation process in protein synthesis [87,88,89]. Moreover, this gene plays a crucial role in the tolerant responses to abiotic stresses [90]. SUI 1 showed high up-regulation in abiotic tolerance in yeast and Arabidopsis [91], rice [92], kashgar tamarisk [93], and mango [94]. Similarly, this gene showed up-regulation in our tolerant plants after gall wasp infestation. Our results indicated that SUI 1 could be an essential factor in the tolerant responses to gall wasp infestation.
Using the STRING database, the three genes specific to the tolerant group showed a functional association. The protein-protein interactions showed the relationship associated with response to biotic and abiotic stresses and stimuli. Protein-protein interaction of the selected genes is shown in Figure 8. RCA was shown to be directly associated with fructose-bisphosphate aldolase 2 (FBA2) that which is a glycolytic enzyme in the glycolysis and gluconeogenesis, as well as in the Calvin cycle. Some studies showed the role of FBA2 in response to the herbivory of the two-spotted spider mite, brown planthopper large black chafer, and whiteflies [95]. FBA2 was considerably higher in our tolerant group. Moreover, they were shown to be associated with ABCF5 or GCN5 through ZKT, a member of a novel protein family present in the plant kingdom, which contains a PDZ, a K-box, and a TPR motif. ZKT is related to phosphorylation after wounding [96]. Additionally, ABCF5 was associated with SUI1, AT5G54760, through translation elongation factors that related to the volatile compound. TPS03 was directly associated with cytochrome P450, family 82, subfamily G, polypeptide 1 (CYP82G1) which was significantly increased in our tolerant group. CYP82G1 was reported to be involved in the biosynthesis of a volatile terpenoid compound [97] that is associated with the jasmonic acid (JA) signaling pathway [98]. Lipoxygenases (LOXs) play an important function in regulating JA biosynthesis and transport when a wound occurs [99]. In Arabidopsis, JA biosynthesis depends on LOX2, LOX3, LOX4, and LOX6 genes. LOX6 gene was expressed in the phloem and xylem of leaves. We showed that LOX6 was shown to be associated with TPS03 through LOX5. Our transcript analysis indicated that the expression of LOX6, encoded PLAT/LH2 domain-containing lipoxygenase family protein, significantly increased in the tolerant group after the oviposition of gall wasp eggs into vascular tissue. Moreover, LOX6 was shown to be directly associated with hydroperoxide lyase 1 (HPL1), a member of the cytochrome p450, family 74 subfamily B (CYP74B) [100,101]. HPL1 was involved in the production of C6 volatile compounds, which function as signaling molecules for insect defense [102]. HPL1 was significantly decreased in our tolerant group. Similar results were demonstrated that the mutant hpl1, which is unable to synthesize C6 volatile compounds, was more resistant to bacterial pathogens in Arabidopsis [102] and rice [103]. In addition, the ABA 8′-hydroxylase enzyme (CY707A4) that initiated the ABA catabolic pathway was shown to be associated with LOX2 through BGLU18; beta-D-glucopyranosyl abscisate beta-glucosidase, that contributes to the initiation of intracellular signaling [104].
Using expression and STRING analysis, our results suggested that early response at three days after gall wasp infestation increased protein synthesis (via SUI1), terpenoid synthesis (via TPS03 and CYP82G1), and increased transportation of these molecules (via ABCF5). In addition, wounding also increased photosynthesis and glycolysis (via RCA and FBA2). These processes involved several plant hormones, such as JA, Auxin, and ABA. Increased expression of the genes involved in these processes is important for tolerant defensive systems against gall wasp infestation, supporting the hypothesis that the infestation of gall wasps induces some genes encoding enzymes induced by wounding and these genes play essential roles for the tolerant phenotype. Future investigation into sequence variations of these genes could be useful for marker development and functional studies.

5. Conclusions

This study identified differentially expressed genes via RNA sequencing. This approach can reveal interesting genes associated with a tolerant response in eucalyptus against gall wasp infestation. Our results demonstrate that the various responses were induced in the early stage, at three days after infestation, for tolerant appearance. Some of these genes are promising candidate genes for the identification of SNPs and Indels, which can be used for further research and future eucalyptus breeding programs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae9020127/s1, Table S1: The specific primers for each candidate genes and reference gene; Table S2: The DEGs specific for the tolerant group.

Author Contributions

Conceptualization, A.M.; methodology, S.P., K.S., K.T., S.C., P.S. and N.S.; software and data analysis, S.W., W.A. and S.P.; writing-original draft preparation, S.P. and W.P.; writing-editing, A.M. and K.U. Funding acquisition, A.M. and K.U. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded in some parts by Ph.D. scholarship from Thammasat University, and Agricultural Research Development Agency.

Data Availability Statement

Not applicable.

Acknowledgments

We thank Peera Jaruampornpan for her critical reading and comments on the manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Grattapaglia, D.; Kirst, M. Eucalyptus applied genomics: From gene sequences to breeding tools. New Phytol. 2008, 179, 911–929. [Google Scholar] [CrossRef] [PubMed]
  2. Grattapaglia, D.; Vaillancourt, R.E.; Shepherd, M.; Thumma, B.R.; Foley, W.; Külheim, C.; Potts, B.M.; Myburg, A.A. Progress in Myrtaceae genetics and genomics: Eucalyptus as the pivotal genus. Tree Genet. Genomes 2012, 8, 463–508. [Google Scholar] [CrossRef] [Green Version]
  3. Jantapanon, K.T.; Apisitwanich, S.; Peyachoknagul, S. DNA fingerprinting of eucalyptus clones using microsatellite markers. Thai J. Genet. 2009, 3, 31–40. [Google Scholar]
  4. Kellison, R.C.; Lea, R.; Marsh, P. Introduction of Eucalyptus spp. into the United States with Special Emphasis on the Southern United States. Int. J. For. Res. 2013, 2013, 189393. [Google Scholar]
  5. Mendel, Z.; Protasov, A.; Fisher, N.; La Salle, J. Taxonomy and biology of Leptocybe invasa gen. & sp. n. (Hymenoptera: Eulophidae), an invasive gall inducer on Eucalyptus. Aust. J. Èntomol. 2004, 43, 101–113. [Google Scholar]
  6. Thu, P.Q.; Dell, B.; Burgess, T.I. Susceptibility of 18 eucalypt species to the gall wasp Leptocybe invasa Fisher & La Salle in the nursery and young plantations in Vietnam. ScienceAsia 2009, 35, 113–117. [Google Scholar]
  7. Petro, R.; Iddi, S. Leptocybe invasa and its effects on young plantations of commercial Eucalyptus species in Tanzania. Int. J. Agric. For. 2017, 7, 23–27. [Google Scholar]
  8. Jacop, P.J.; Kumar, A.R. Incidence of galls induced by Leptocybe invasa on seedlings of Eucalyptus camaldulensis and E. tereticornis from different seed sources in Southern India. Int. J. Ecol. Environ. Sci. 2009, 35, 187–198. [Google Scholar]
  9. ABD EL-Raheem, A.M.; Heikal, H.M. First record of the genus Leptocybe spp. as Eucalyptus gall wasp, (Hymenoptera: Eulophidae) in Egypt. Int. J. Zool. Res. 2014, 4, 23–28. [Google Scholar]
  10. Tong, Y.-G.; Ding, X.-X.; Zhang, K.-C.; Yang, X.; Huang, W. Effect of the gall wasp Leptocybe invasa on hydraulic architecture in Eucalyptus camaldulensis plants. Front. Plant Sci. 2016, 7, 130. [Google Scholar] [CrossRef] [Green Version]
  11. Jacob, J.P.; Senthil, K.; Sivakumar, V.; Seenivasan, R.; Chezhian, P.; Kumar, K.N. Gall wasp Leptocybe invasa (Hymenoptera: Eulophidae) management in Eucalypts. J. Biol. Control. 2015, 29, 20–24. [Google Scholar] [CrossRef]
  12. Huang, Z.-Y.; Li, J.; Lu, W.; Zheng, X.-L.; Yang, Z.-D. Parasitoids of the eucalyptus gall wasp Leptocybe spp.: A global review. Environ. Sci. Pollut. Res. Int. 2018, 25, 29983–29995. [Google Scholar] [CrossRef] [PubMed]
  13. Sangtongpraow, B.; Charernsom, K.; Siripatanadilok, S. Longevity, fecundity and development time of eucalyptus gall wasp, Leptocybe invasa Fisher&La Salle (Hymenoptera Eulophidae) in Kanchanaburi province, Thailand. Thai J. Agric. Sci. 2011, 44, 155–163. [Google Scholar]
  14. Sangtongpraow, B.; Charernsom, K. Biological traits of Quadrastichus mendeli (Hymenoptera, Eulophidae), parasitoid of the eucalyptus gall wasp Leptocybe invasa (Hymenoptera, Eulophidae) in Thailand. Parasite 2019, 26, 8. [Google Scholar] [CrossRef] [Green Version]
  15. Egan, S.P.; Hood, G.R.; Martinson, E.O.; Ott, J.R. Cynipid gall wasps. Curr Biol. 2018, 28, 1370–1374. [Google Scholar] [CrossRef] [Green Version]
  16. Tooker, J.F.; Rohr, J.R.; Abrahamson, W.G.; De Moraes, C.M. Gall insects can avoid and alter indirect plant defenses. New Phytol. 2008, 178, 657–671. [Google Scholar] [CrossRef]
  17. Roychoudhury, N.; Vaishy, N.; Mishra, R.K. Morphometric analysis of Eucalyptus gall insect, Leptocybe invasa. Van Sangyan 2020, 7, 19–23. [Google Scholar]
  18. Rosa, D.D.; Furtado, E.L.; Boava, L.P.; Marino, C.L.; Mori, E.S.; Guerrini, I.A.; Veline, E.D.; Wilcken, C.F. Eucalyptus ESTs involved in mechanisms against plant pathogens and environmental stresses. Summa Phytopathol. 2010, 36, 282–290. [Google Scholar] [CrossRef] [Green Version]
  19. Erb, M.; Meldau, S.; Howe, G.A. Role of phytohormones in insect-specific plant reactions. Trends Plant Sci. 2012, 17, 250–259. [Google Scholar] [CrossRef]
  20. Alba, J.M.; Glas, J.J.; Schimmel, B.C.J.; Kant, M.R.; Cano, J.M.A. Avoidance and suppression of plant defenses by herbivores and pathogens. J. Plant Interact. 2011, 6, 221–227. [Google Scholar] [CrossRef]
  21. Mazid, M.; Khan, T.A.; Mohammad, F. Role of secondary metabolites in defense mechanisms of plants. Biol. Med. 2011, 3, 232–249. [Google Scholar]
  22. War, A.R.; Paulraj, M.G.; Ahmad, T.; Buhroo, A.A.; Hussain, B.; Ignacimuthu, S.; Sharma, H.C. Mechanisms of plant defense against insect herbivores. Plant Signal. Behav. 2012, 7, 1306–1320. [Google Scholar] [CrossRef] [Green Version]
  23. Oates, C.N.; Kulheim, C.; Myburg, A.A.; Slippers, B.; Naidoo, S. The transcriptome and terpene profile of Eucalyptus grandis reveals mechanisms of defense against the insect pest, Leptocybe invasa. Plant Cell Physiol. 2015, 56, 1418–1428. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Naidoo, S.; Kulheim, C.; Zwart, L.; Mangwanda, R.; Oates, C.N.; Visser, E.A.; Wilken, F.E.; Mamni, T.B.; Myburg, A.A. Uncovering the defence responses of Eucalyptus to pests and pathogens in the genomics age. Tree Physiol. 2014, 34, 931–943. [Google Scholar] [CrossRef] [Green Version]
  25. Nabity, P.D. Insect-induced plant phenotypes: Revealing mechanisms through comparative genomics of galling insects and their hosts. Am. J. Bot. 2016, 103, 979–981. [Google Scholar] [CrossRef] [Green Version]
  26. Sarmento, M.I.; Pinto, G.; Araujo, W.L.; Silva, R.C.; Lima, C.H.O.; Soares, A.M.; Sarmento, R.A. Differential development times of galls induced by Leptocybe invasa (Hymenoptera: Eulophidae) reveal differences in susceptibility between two Eucalyptus clones. Pest Manag. Sci. 2021, 77, 1042–1051. [Google Scholar] [CrossRef]
  27. Pareek, C.S.; Smoczynski, R.; Tretyn, A. Sequencing technologies and genome sequencing. J. Appl. Genet. 2011, 52, 413–435. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  28. Kukurba, K.R.; Montgomery, S.B. RNA sequencing and analysis. Cold Spring Harb Protoc. 2015, 11, 951–969. [Google Scholar] [CrossRef] [Green Version]
  29. Barrera-Redondo, J.; Pinero, D.; Eguiarte, L.E. Genomic, Transcriptomic and Epigenomic tools to study the domestication of plants and animals: A field guide for beginners. Front. Genet. 2020, 11, 742. [Google Scholar] [CrossRef]
  30. Li, J.; Zhu, L.; Hull, J.J.; Liang, S.; Daniell, H.; Jin, S.; Zhang, X. Transcriptome analysis reveals a comprehensive insect resistance response mechanism in cotton to infestation by the phloem feeding insect Bemisia tabaci (whitefly). Plant Biotechnol. J. 2016, 14, 1956–1975. [Google Scholar] [CrossRef]
  31. Duarte, J.; Riviere, N.; Baranger, A.; Aubert, G.; Burstin, J.; Cornet, L.; Lavaud, C.; Lejeune-Henaut, I.; Martinant, J.-P.; Pichon, J.-P.; et al. Transcriptome sequencing for high throughput SNP development and genetic mapping in Pea. BMC Genom. 2014, 15, 126. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Naqvi, R.Z.; Zaidi, S.S.-E.; Akhtar, K.P.; Strickler, S.; Woldemariam, M.; Mishra, B.; Mukhtar, M.S.; Scheffler, B.E.; Scheffler, J.A.; Jander, G.; et al. Transcriptomics reveals multiple resistance mechanisms against cotton leaf curl disease in a naturally immune cotton species, Gossypium arboreum. Sci. Rep. 2017, 7, 15880. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Long, J.A. The ‘omics’ revolution: Use of genomic, transcriptomic, proteomic and metabolomic tools to predict male reproductive traits that impact fertility in livestock and poultry. Anim. Reprod. Sci. 2020, 220, 106354. [Google Scholar] [CrossRef] [PubMed]
  34. Meyer, F.E.; Shuey, L.S.; Naidoo, S.; Mamni, T.; Berger, D.K.; Myburg, A.A.; Bergelson, N.; Naidoo, S. Dual RNA-sequencing of Eucalyptus nitens during Phytophthora cinnamomi challenge reveals pathogen and host factors influencing compatibility. Front. Plant Sci. 2016, 7, 191. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Santos, S.A.; Vidigal, P.M.P.; Guimarães, L.M.S.; Mafia, R.G.; Templeton, M.D.; Alfenas, A.C. Transcriptome analysis of Eucalyptus grandis genotypes reveals constitutive overexpression of genes related to rust (Austropuccinia psidii) resistance. Plant Mol. Biol. 2020, 104, 339–357. [Google Scholar] [CrossRef]
  36. Thavamanikumar, S.; Southerton, S.; Thumma, B. RNA-Seq using two populations reveals genes and alleles controlling wood traits and growth in Eucalyptus nitens. PLoS ONE 2014, 9, e101104. [Google Scholar] [CrossRef]
  37. Thumma, B.R.; Sharma, N.; Southerton, S.G. Transcriptome sequencing of Eucalyptus camaldulensis seedlings subjected to water stress reveals functional single nucleotide polymorphisms and genes under selection. BMC Genom. 2012, 13, 364. [Google Scholar] [CrossRef] [Green Version]
  38. Goud, K.B.; Kumari, N.K.; Vastrad, A.S.; Bhadragoudar, M.; Kulkarni, H. Screening of eucalyptus genotypes against gall wasp, Leptocybe invasa Fisher and La Salle (Hymenoptera: Eulophidae). Karnataka J. Agric. Sci. 2010, 23, 213–214. [Google Scholar]
  39. Zhang, M.; Zhou, C.; Song, Z.; Weng, Q.; Li, M.; Ji, H.; Mo, X.; Huang, H.; Lu, W.; Luo, J.; et al. The first identification of genomic loci in plants associated with resistance to galling insects: A case study in Eucalyptus L’Hér. (Myrtaceae). Sci. Rep. 2018, 8, 2319. [Google Scholar] [CrossRef] [Green Version]
  40. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [Green Version]
  41. Kim, D.; Langmead, B.; Salzberg, S.L. HISAT: A fast spliced aligner with low memory requirements. Nat. Methods 2015, 12, 357–360. [Google Scholar] [CrossRef]
  42. Pertea, M.; Kim, D.; Pertea, G.M.; Leek, J.T.; Salzberg, S.L. Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie and Ballgown. Nat. Protoc. 2016, 11, 1650–1667. [Google Scholar] [CrossRef]
  43. Robinson, M.D.; McCarthy, D.J.; Smyth, G.K. edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 2010, 26, 139–140. [Google Scholar] [CrossRef] [Green Version]
  44. De Cremer, K.; Mathys, J.; Vos, C.; Froenicke, L.; Michelmore, R.W.; Cammue, B.P.; De Coninck, B. RNAseq-based transcriptome analysis of Lactuca sativa infected by the fungal necrotroph Botrytis cinerea. Plant Cell Environ. 2013, 36, 1992–2007. [Google Scholar] [PubMed]
  45. Benjamini, Y.; Yosef, H. Controlling the False Discovery Rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 1995, 57, 289–300. [Google Scholar] [CrossRef]
  46. Rathod, V.; Hamid, R.; Tomar, R.S.; Patel, R.; Padhiyar, S.; Kheni, J.; Thirumalaisamy, P.P.; Munshi, N.S. Comparative RNA-Seq profiling of a resistant and susceptible peanut (Arachis hypogaea) genotypes in response to leaf rust infection caused by Puccinia arachidis. 3 Biotech 2020, 10, 284. [Google Scholar] [CrossRef] [PubMed]
  47. Ye, J.; Fang, L.; Zheng, H.; Zhang, Y.; Chen, J.; Zhang, Z.; Wang, J.; Li, S.; Li, R.; Bolund, L.; et al. WEGO: A web tool for plotting GO annotations. Nucleic Acids Res. 2006, 34, 293–297. [Google Scholar] [CrossRef] [PubMed]
  48. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef]
  49. de Almeida, M.R.; Ruedell, C.M.; Ricachenevsky, F.K.; Sperotto, R.A.; Pasquali, G.; Fett-Neto, A.G. Reference gene selection for quantitative reverse transcription-polymerase chain reaction normalization during in vitro adventitious rooting in Eucalyptus globulus Labill. BMC Mol. Biol. 2010, 11, 73. [Google Scholar] [CrossRef] [Green Version]
  50. Chunthong, K.; Pitnjam, K.; Chakhonkaen, S.; Sangarwut, N.; Panyawut, N.; Wasinanon, T.; Ukoskit, K.; Muangprom, A. Differential drought responses in F-box gene expression and grain yield between two rice groups with contrasting drought tolerance. J. Plant Growth Regul. 2017, 36, 970–982. [Google Scholar] [CrossRef]
  51. Khlaimongkhon, S.; Chakhonkaen, S.; Tongmark, K.; Sangarwut, N.; Panyawut, N.; Wasinanon, T.; Sikaewtung, K.; Wanchana, S.; Mongkolsiriwatana, C.; Chunwonges, J.; et al. RNA sequencing reveals rice genes involved in male reproductive development under temperature alteration. Plants 2021, 10, 663. [Google Scholar] [CrossRef] [PubMed]
  52. Meng, H.; Sun, M.; Jiang, Z.; Liu, Y.; Sun, Y.; Liu, D.; Jiang, C.; Ren, M.; Yuan, G.; Yu, W.; et al. Comparative transcriptome analysis reveals resistant and susceptible genes in tobacco cultivars in response to infection by Phytophthora nicotianae. Sci. Rep. 2021, 11, 809. [Google Scholar] [CrossRef] [PubMed]
  53. Li, Y.; Guo, G.; Zhou, L.; Chen, Y.; Zong, Y.; Huang, J.; Lu, R.; Liu, C. Transcriptome analysis identifies candidate genes and functional pathways controlling the response of two contrasting barley varieties to powdery mildew infection. Int. J. Mol. Sci. 2019, 21, 151. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  54. Zhu, C.; Shi, F.; Chen, Y.; Wang, M.; Zhao, Y.; Geng, G. Transcriptome analysis of chinese chestnut (Castanea mollissima Blume) in response to Dryocosmus kuriphilus Yasumatsu Infestation. Int. J. Mol. Sci. 2019, 20, 855. [Google Scholar] [CrossRef] [Green Version]
  55. Odilbekov, F.; He, X.; Armoniené, R.; Saripella, G.V.; Henriksson, T.; Singh, P.K.; Chawade, A. QTL mapping and transcriptome analysis to identify differentially expressed genes induced by septoria tritici blotch disease of wheat. Agronomy 2019, 9, 510. [Google Scholar] [CrossRef] [Green Version]
  56. Kigathi, R.N.; Weisser, W.W.; Reichelt, M.; Gershenzon, J.; Unsicker, S.B. Plant volatile emission depends on the species composition of the neighboring plant community. BMC Plant Biol. 2019, 19, 58. [Google Scholar] [CrossRef]
  57. Bouwmeester, H.; Schuurink, R.C.; Bleeker, P.M.; Schiestl, F. The role of volatiles in plant communication. Plant J. 2019, 100, 892–907. [Google Scholar] [CrossRef] [Green Version]
  58. Mumm, R.; Posthumus, M.A.; Dicke, M. Significance of terpenoids in induced indirect plant defence against herbivorous arthropods. Plant Cell Environ. 2008, 31, 575–585. [Google Scholar] [CrossRef]
  59. Zeng, X.; Liu, C.; Zheng, R.; Cai, X.; Luo, J.; Zou, J.; Wang, C. Emission and accumulation of monoterpene and the key terpene synthase (TPS) associated with monoterpene biosynthesis in Osmanthus fragrans Lour. Front. Plant Sci. 2016, 6, 1232. [Google Scholar] [CrossRef] [Green Version]
  60. Zapata, F.; Fine, P.V. Diversification of the monoterpene synthase gene family (TPSb) in Protium, a highly diverse genus of tropical trees. Mol. Phylogenetics Evol. 2013, 68, 432–442. [Google Scholar] [CrossRef]
  61. Huang, M.; Abel, C.; Sohrabi, R.; Petri, J.; Haupt, I.; Cosimano, J.; Gershenzon, J.; Tholl, D. Variation of herbivore-induced volatile terpenes among Arabidopsis ecotypes depends on allelic differences and subcellular targeting of two terpene synthases, TPS02 and TPS03. Plant Physiol. 2010, 153, 1293–1310. [Google Scholar] [CrossRef]
  62. Chen, F.; Tholl, D.; Bohlmann, J.; Pichersky, E. The family of terpene synthases in plants: A mid-size family of genes for specialized metabolism that is highly diversified throughout the kingdom. Plant J. 2011, 66, 212–229. [Google Scholar] [CrossRef] [PubMed]
  63. Wang, C.; Liu, Y.; Li, S.-S.; Han, G.-Z. Insights into the origin and evolution of the plant hormone signaling machinery. Plant Physiol. 2015, 167, 872–886. [Google Scholar] [CrossRef] [Green Version]
  64. Savatin, D.V.; Gramegna, G.; Modesti, V.; Cervone, F. Wounding in the plant tissue: The defense of a dangerous passage. Front Plant Sci. 2014, 5, 470. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  65. Ikeuchi, M.; Iwase, A.; Rymen, B.; Lambolez, A.; Kojima, M.; Takebayashi, Y.; Heyman, J.; Watanabe, S.; Seo, M.; Veylder, L.; et al. Wounding Triggers Callus Formation via Dynamic Hormonal and Transcriptional Changes. Plant Physiol. 2017, 175, 1158–1174. [Google Scholar] [CrossRef] [Green Version]
  66. Markakis, M.N.; Boron, A.K.; Van Loock, B.; Saini, K.; Cirera, S.; Verbelen, J.-P.; Vissenberg, K. Characterization of a small auxin-up RNA (SAUR)-like gene involved in Arabidopsis thaliana development. PLoS ONE 2013, 8, e82596. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  67. Zhang, H.; Yu, Z.; Yao, X.; Chen, J.; Chen, X.; Zhou, H.; Lou, Y.; Ming, F.; Jin, Y. Genome-wide identification and characterization of small auxin-up RNA (SAUR) gene family in plants: Evolution and expression profiles during normal growth and stress response. BMC Plant Biol. 2021, 21, 4. [Google Scholar] [CrossRef]
  68. Xie, R.; Dong, C.; Ma, Y.; Deng, L.; He, S.; Yi, S.; Lv, Q.; Zheng, Y. Comprehensive analysis of SAUR gene family in citrus and its transcriptional correlation with fruitlet drop from abscission zone A. Funct. Integr. Genom. 2015, 15, 729–740. [Google Scholar] [CrossRef]
  69. Jain, M.; Tyagi, A.K.; Khurana, J.P. Genome-wide analysis, evolutionary expansion, and expression of early auxin-responsive SAUR gene family in rice (Oryza sativa). Genomics 2006, 88, 360–371. [Google Scholar] [CrossRef] [Green Version]
  70. He, Y.; Liu, Y.; Li, M.; Lamin-Samu, A.T.; Yang, D.; Yu, X.; Izhar, M.; Jan, I.; Ali, M.; Lu, G. The Arabidopsis SMALL AUXIN UP RNA32 protein regulates ABA-mediated responses to drought stress. Front. Plant Sci. 2021, 12, 625493. [Google Scholar] [CrossRef]
  71. Nejat, N.; Mantri, N. Plant immune system: Crosstalk between responses to biotic and abiotic stresses the missing link in understanding plant defence. Curr Issues Mol Biol. 2017, 23, 1–16. [Google Scholar] [CrossRef] [PubMed]
  72. Umezawa, T.; Okamoto, M.; Kushiro, T.; Nambara, E.; Oono, Y.; Seki, M.; Kobayashi, M.; Koshiba, T.; Kamiya, Y.; Shinozaki, K. CYP707A3, a major ABA 8’-hydroxylase involved in dehydration and rehydration response in Arabidopsis thaliana. Plant J. 2006, 46, 171–182. [Google Scholar] [CrossRef]
  73. Krochko, J.E.; Abrams, G.D.; Loewen, M.K.; Abrams, S.R.; Cutler, A.J. (+)-Abscisic acid 8′-hydroxylase is a cytochrome P450 monooxygenase. Plant Physiol. 1998, 118, 849–860. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Bhat, J.Y.; Thieulin-Pardo, G.; Hartl, F.U.; Hayer-Hartl, M. Rubisco activases: AAA+ chaperones adapted to enzyme repair. Front. Mol. Biosci. 2017, 4, 20. [Google Scholar] [CrossRef] [Green Version]
  75. Perdomo, J.A.; Capo-Bauca, S.; Carmo-Silva, E.; Galmes, J. Rubisco and rubisco activase play an important role in the biochemical limitations of photosynthesis in rice, wheat, and maize under high temperature and water deficit. Front. Plant Sci. 2017, 8, 490. [Google Scholar] [CrossRef] [Green Version]
  76. Kerchev, P.I.; Fenton, B.; Foyer, C.; Hancock, R.D. Plant responses to insect herbivory: Interactions between photosynthesis, reactive oxygen species and hormonal signaling pathways. Plant Cell Environ. 2012, 35, 441–453. [Google Scholar] [CrossRef]
  77. Chavez-Arias, C.C.; Ligarreto-Moreno, G.A.; Ramirez-Godoy, A.; Restrepo-Diaz, H. Maize responses challenged by drought, elevated daytime temperature and arthropod herbivory stresses: A physiological, biochemical and molecular view. Front. Plant Sci. 2021, 12, 702841. [Google Scholar] [CrossRef]
  78. Kumar, R.R.; Goswami, S.; Singh, K.; Dubey, K.; Singh, S.; Sharma, R.; Verma, N.; Kala, Y.K.; Rai, G.K.; Grover, M.; et al. Identification of putative rubisco activase (TaRca1) the catalytic chaperone regulating carbon assimilatory pathway in Wheat (Triticum aestivum) under the heat stress. Front. Plant Sci. 2016, 7, 986. [Google Scholar] [CrossRef] [Green Version]
  79. Wijewardene, I.; Mishra, N.; Sun, L.; Smith, J.; Zhu, X.; Payton, P.; Shen, G.; Zhang, H. Improving drought-, salinity-, and heat-tolerance in transgenic plants by co-overexpressing Arabidopsis vacuolar pyrophosphatase gene AVP1 and Larrea Rubisco activase gene RCA. Plant Sci. 2020, 296, 110499. [Google Scholar] [CrossRef]
  80. Mitra, S.; Baldwin, I.T. RuBPCase activase (RCA) mediates growth-defense trade-offs: Silencing RCA redirects jasmonic acid (JA) flux from JA-isoleucine to methyl jasmonate (MeJA) to attenuate induced defense responses in Nicotiana attenuata. New Phytol. 2014, 201, 1385–1395. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  81. Kang, J.; Park, J.; Choi, H.; Burla, B.; Kretzschmar, T.; Lee, Y.; Martinoia, E. Plant ABC Transporters. Arab. Book 2011, 9, e0153. [Google Scholar] [CrossRef]
  82. Banasiak, J.; Jasinski, M. ATP-binding cassette transporters in nonmodel plants. New Phytol. 2021, 233, 1597–1612. [Google Scholar] [CrossRef]
  83. Dong, Q.; Magwanga, R.O.; Cai, X.; Lu, P.; Kirungu, J.N.; Zhou, Z.; Wang, X.; Wang, X.; Xu, Y.; Hou, Y.; et al. RNA-Sequencing, physiological and rnai analyses provide insights into the response mechanism of the abc-mediated resistance to Verticillium dahlia Infection in Cotton. Genes 2019, 10, 110. [Google Scholar] [CrossRef] [Green Version]
  84. Kooliyottil, R.; Gadhachanda, K.R.; Solo, N.; Dandurand, L.-M. ATP-binding cassette (ABC) transporter genes in plant-parasitic nematodes: An opinion for development of novel control strategy. Front. Plant Sci. 2020, 11, 582424. [Google Scholar] [CrossRef] [PubMed]
  85. Borghi, L.; Kang, J.; Ko, D.; Lee, Y.; Martinoia, E. The role of ABCG-type ABC transporters in phytohormone transport. Biochem. Soc. Trans. 2015, 43, 924–930. [Google Scholar] [CrossRef]
  86. Yazaki, K. ABC transporters involved in the transport of plant secondary metabolites. FEBS Lett. 2006, 580, 1183–1191. [Google Scholar] [CrossRef] [Green Version]
  87. Ivanov, I.P.; Loughran, G.; Sachs, M.S.; Atkins, J.F. Initiation context modulates autoregulation of eukaryotic translation initiation factor 1 (eIF1). Proc. Natl. Acad. Sci. USA 2010, 107, 18056–18060. [Google Scholar] [CrossRef] [Green Version]
  88. Pestova, T.V.; Borukhov, S.I.; Hellen, C.U.T. Eukaryotic ribosomes require initiation factors 1 and 1A to locate initiation codons. Nature 1998, 394, 854–859. [Google Scholar] [CrossRef] [PubMed]
  89. Dutt, S.; Parkash, J.; Mehra, R.; Sharma, N.; Singh, B.; Raigond, P.; Joshi, A.; Chopra, S.; Singh, B.P. Translation initiation in plants: Roles and implications beyond protein synthesis. Biol. Plant. 2015, 59, 401–412. [Google Scholar] [CrossRef]
  90. Echevarria-Zomeno, S.; Yanguez, E.; Fernandez-Bautista, N.; Castro-Sanz, A.B.; Ferrando, A.; Castellano, M.M. Regulation of translation initiation under biotic and abiotic stresses. Int. J. Mol. Sci. 2013, 14, 4670–4683. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  91. Rausell, A.; Kanhonou, R.; Yenush, L.; Serrano, R.; Ros, R. The translation initiation factor eIF1A is an important determinant in the tolerance to NaCl stress in yeast and plants. Plant J. 2003, 34, 257–267. [Google Scholar] [CrossRef]
  92. Diedhiou, C.J.; Popova, O.V.; Golldack, D. Comparison of salt-responsive gene regulation in rice and in the salt-tolerant Festuca rubra ssp. litoralis. Plant Signal Behav. 2009, 4, 533–535. [Google Scholar] [PubMed] [Green Version]
  93. Yang, G.; Yu, L.; Wang, Y.; Wang, C.; Gao, C. The translation initiation factor 1A (TheIF1A) from Tamarix hispida is regulated by a dof transcription factor and increased abiotic stress tolerance. Front. Plant Sci. 2017, 8, 513. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  94. Li-shu, L.; Cong, L.; Zhen-yu, A.; Zhao-liang, L.; Long, D.; Hai-xia, Y.; Xin-hua, H. Molecular characterization, expression and function analysis of eukaryotic translation initiation factor (eIF1A) in Mangifera indica. J. Integr. Agric. 2019, 18, 2505–2513. [Google Scholar]
  95. Ganji, Z.; Fatehi, F.; Mehraban, F.H.; Haynes, P.A.; Naveh, V.H.; Farrokhi, N. Comparative Pistacia vera leaf proteomics in response to herbivory of the common pistachio psylla (Agonoscena pistaciae). Arthropod-Plant Interact. 2022, 16, 215–226. [Google Scholar] [CrossRef]
  96. Ishikawa, A.; Tanaka, H.; Kato, C.; Iwasaki, Y.; Asahi, T. Molecular characterization of the ZKT gene encoding a protein with PDZ, K-Box, and TPR motifs in Arabidopsis. Biosci Biotechnol Biochem. 2005, 69, 972–978. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  97. Ginglinger, J.F.; Boachon, B.; Hofer, R.; Paetz, C.; Kollner, T.G.; Miesch, L.; Lugan, R.; Baltenweck, R.; Mutterer, J.; Ullmann, P.; et al. Gene coexpression analysis reveals complex metabolism of the monoterpene alcohol linalool in Arabidopsis flowers. Plant Cell. 2013, 25, 4640–4657. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  98. Lee, S.; Badieyan, S.; Bevan, D.R.; Herde, M.; Gatz, C.; Tholl, D. Herbivore-induced and floral homoterpene volatiles are biosynthesized by a single P450 enzyme (CYP82G1) in Arabidopsis. Proc. Natl. Acad. Sci. USA 2010, 107, 21205–21210. [Google Scholar] [CrossRef] [Green Version]
  99. Kang, J.N.; Lee, W.H.; Won, S.Y.; Chang, S.; Hong, J.P.; Oh, T.J.; Lee, S.M.; Kang, S.H. Systemic Expression of Genes Involved in the Plant Defense Response Induced by Wounding in Senna tora. Int. J. Mol. Sci. 2021, 22, 10073. [Google Scholar] [CrossRef]
  100. Bate, N.; Sivasankar, S.; Moxon, C.; Riley, J.; Thompson, J.; Rothstein, S. Molecular Characterization of an Arabidopsis Gene Encoding Hydroperoxide Lyase, a Cytochrome P-450 That Is Wound Inducible. Plant Physiol. 1998, 117, 1393–1400. [Google Scholar] [CrossRef] [Green Version]
  101. Duan, H.; Huang, M.Y.; Palacio, K.; Schuler, M.A. Variations in CYP74B2 (Hydroperoxide lyase) gene expression differentially affect hexenal signaling in the Columbia and Landsberg erecta ecotypes of Arabidopsis. Plant Physiol. 2005, 139, 1529–1544. [Google Scholar] [CrossRef] [Green Version]
  102. Scala, A.; Mirabella, R.; Mugo, C.; Matsui, K.; Haring, M.A.; Schuurink, R.C. E-2-hexenal promotes susceptibility to Pseudomonas syringae by activating jasmonic acid pathways in Arabidopsis. Front. Plant Sci. 2013, 4, 74. [Google Scholar] [CrossRef] [PubMed]
  103. Tong, X.; Qi, J.; Zhu, X.; Mao, B.; Zeng, L.; Wang, B.; Li, Q.; Zhou, G.; Xu, X.; Lou, Y.; et al. The rice hydroperoxide lyase OsHPL3 functions in defense responses by modulating the oxylipin pathway. Plant J. 2012, 71, 763–775. [Google Scholar] [CrossRef] [PubMed]
  104. Han, Y.; Watanabe, S.; Shimada, H.; Sakamoto, A. Dynamics of the leaf endoplasmic reticulum modulate beta-glucosidase-mediated stress-activated ABA production from its glucosyl ester. J. Exp. Bot. 2020, 71, 2058–2071. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Phenotype changes in eucalyptus leaf during L. invasa infestation. After gall wasp oviposition on normal tissues or immature tissues, the development stage of gall formation involves five stages: (a) The first symptoms showed the oviposition scars at the oviposition site in stage 1; The gall enlarged, and the adult emerged from the gall in stages 2–5; (b) The damage severity levels were divided into five-grade criteria; (c) A susceptible clone, C153-S, had phenotypic changes in the highest galling, while a tolerant clone, U22-T, showed phenotypic changes in a few signs of oviposition but without gall; Samples of the tolerant F1-progenies showed signs of oviposition but without gall, while samples of the susceptible F1-progenies had galls on midribs and petioles.
Figure 1. Phenotype changes in eucalyptus leaf during L. invasa infestation. After gall wasp oviposition on normal tissues or immature tissues, the development stage of gall formation involves five stages: (a) The first symptoms showed the oviposition scars at the oviposition site in stage 1; The gall enlarged, and the adult emerged from the gall in stages 2–5; (b) The damage severity levels were divided into five-grade criteria; (c) A susceptible clone, C153-S, had phenotypic changes in the highest galling, while a tolerant clone, U22-T, showed phenotypic changes in a few signs of oviposition but without gall; Samples of the tolerant F1-progenies showed signs of oviposition but without gall, while samples of the susceptible F1-progenies had galls on midribs and petioles.
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Figure 2. Differential gene expression analysis of U22-T (tolerant parent), C153-S (susceptible parent), the tolerant pool, and the susceptible pool under infested and un-infested conditions at three days after gall wasp infestation: (a) The number of up-regulated and down-regulated genes in U22-T (tolerant parent), C153-S (susceptible parent), the tolerant pool (non-galling; NG), and the susceptible pool (galling; G) in response to gall wasp infestation. The up-regulated genes are presented in blue, and the down-regulated genes are shown in red; (b) The numbers in the Venn diagram indicate the numbers of unique and overlapping genes between the four groups; I = infested, C = control un-infested conditions.
Figure 2. Differential gene expression analysis of U22-T (tolerant parent), C153-S (susceptible parent), the tolerant pool, and the susceptible pool under infested and un-infested conditions at three days after gall wasp infestation: (a) The number of up-regulated and down-regulated genes in U22-T (tolerant parent), C153-S (susceptible parent), the tolerant pool (non-galling; NG), and the susceptible pool (galling; G) in response to gall wasp infestation. The up-regulated genes are presented in blue, and the down-regulated genes are shown in red; (b) The numbers in the Venn diagram indicate the numbers of unique and overlapping genes between the four groups; I = infested, C = control un-infested conditions.
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Figure 3. Differential gene expression analysis of the tolerant and the susceptible groups under infested and un-infested conditions at three days after gall wasp infestation: (a) The number of up-regulated and down-regulated genes specific for the tolerant group, including U22-T and the tolerant pool, and the susceptible group including C153-S and the susceptible pool. The up-regulated genes are presented in blue, and the down-regulated genes are shown in red; (b) The number of the DEGs specific for the tolerant and susceptible groups on the chromosomes of the Eucalyptus genome, n = 11.
Figure 3. Differential gene expression analysis of the tolerant and the susceptible groups under infested and un-infested conditions at three days after gall wasp infestation: (a) The number of up-regulated and down-regulated genes specific for the tolerant group, including U22-T and the tolerant pool, and the susceptible group including C153-S and the susceptible pool. The up-regulated genes are presented in blue, and the down-regulated genes are shown in red; (b) The number of the DEGs specific for the tolerant and susceptible groups on the chromosomes of the Eucalyptus genome, n = 11.
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Figure 4. Gene Ontology (GO) analysis of the DEGs specific for the tolerant and susceptible groups under infested and un-infested conditions at three days after infestation. The GO term classified a total of 632 DEGs specific for the tolerant group and 205 DEGs specific for the susceptible group into three categories; CC, MF, and BP. The left y-axis indicates the percentage of ex-pressed genes in that category. The right y-axis shows the number of expressed genes in a category.
Figure 4. Gene Ontology (GO) analysis of the DEGs specific for the tolerant and susceptible groups under infested and un-infested conditions at three days after infestation. The GO term classified a total of 632 DEGs specific for the tolerant group and 205 DEGs specific for the susceptible group into three categories; CC, MF, and BP. The left y-axis indicates the percentage of ex-pressed genes in that category. The right y-axis shows the number of expressed genes in a category.
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Figure 5. GO enrichment analysis of the specific DEGs. A total of 632 DEGs specific for the tolerant group and 205 DEGs specific for the susceptible group were significantly enriched in seven main functional terms (p-value < 0.05).
Figure 5. GO enrichment analysis of the specific DEGs. A total of 632 DEGs specific for the tolerant group and 205 DEGs specific for the susceptible group were significantly enriched in seven main functional terms (p-value < 0.05).
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Figure 6. Validation of RNA-Seq results using qRT-PCR. Nine genes were validated in the susceptible (C153-S) and tolerant (U22-T) parents under infested and un-infested conditions at three days after infestation. The x-axis indicates C153-SC, C153-SI, U22-TC, and U22-TI, respectively. Histograms indicate the relative normalized expression value in three replicates obtained by qRT-PCR; the solid lines in all plots indicate the log10 FPKM values obtained by RNA-seq.
Figure 6. Validation of RNA-Seq results using qRT-PCR. Nine genes were validated in the susceptible (C153-S) and tolerant (U22-T) parents under infested and un-infested conditions at three days after infestation. The x-axis indicates C153-SC, C153-SI, U22-TC, and U22-TI, respectively. Histograms indicate the relative normalized expression value in three replicates obtained by qRT-PCR; the solid lines in all plots indicate the log10 FPKM values obtained by RNA-seq.
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Figure 7. RT-PCR analysis of the four genes associated with the tolerant response at three days after infestation: (a) The expression levels of these genes in two parents and two pools; (b) The expression patterns of the genes in five tolerant individuals, and five susceptible individuals. H2B represents the internal control. S1-5 and T1-5 are individual samples used in the susceptible and tolerant pools, respectively. C and I were un-infested and infested conditions, respectively.
Figure 7. RT-PCR analysis of the four genes associated with the tolerant response at three days after infestation: (a) The expression levels of these genes in two parents and two pools; (b) The expression patterns of the genes in five tolerant individuals, and five susceptible individuals. H2B represents the internal control. S1-5 and T1-5 are individual samples used in the susceptible and tolerant pools, respectively. C and I were un-infested and infested conditions, respectively.
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Figure 8. The functional association. Genes in the tolerant group that associated with response to biotic and abiotic stress were use as query to search orthologous proteins in Arabidopsis thaliana database: The STRING interaction network represents the known and predicted protein interactions. The red arrows showed up- or down-regulated genes that found in our analysis. The node color represents functional enrichments. Line thickness indicates the confidence of the association.
Figure 8. The functional association. Genes in the tolerant group that associated with response to biotic and abiotic stress were use as query to search orthologous proteins in Arabidopsis thaliana database: The STRING interaction network represents the known and predicted protein interactions. The red arrows showed up- or down-regulated genes that found in our analysis. The node color represents functional enrichments. Line thickness indicates the confidence of the association.
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Table 1. Summary of sequencing data.
Table 1. Summary of sequencing data.
SampleRaw ReadsClean ReadsMapped (%)Error (%)Q20GC (%)
C153-SC43,014,14841,261,40483.10.0197.551.3
U22-TC56,087,17854,007,41881.20.0197.351.3
GC59,730,66456,347,48882.70.0197.551.6
NGC59,156,75655,977,60881.40.0197.651.0
C153-SI49,390,89247,423,82081.90.0197.651.1
U22-TI56,073,57853,098,22881.40.0197.450.8
GI63,264,92459,410,37883.30.0197.751.2
NGI43,097,80041,502,12282.40.0197.451.2
Sum429,815,940409,028,466
Mean53,726,99351,128,55882.20.0197.551.2
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Pinsupa, S.; Tongmark, K.; Aesomnuk, W.; Srikaewtung, K.; Chakhonkaen, S.; Summart, P.; Sangarwut, N.; Pathaichindachote, W.; Wanchana, S.; Ukokit, K.; et al. Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation. Horticulturae 2023, 9, 127. https://doi.org/10.3390/horticulturae9020127

AMA Style

Pinsupa S, Tongmark K, Aesomnuk W, Srikaewtung K, Chakhonkaen S, Summart P, Sangarwut N, Pathaichindachote W, Wanchana S, Ukokit K, et al. Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation. Horticulturae. 2023; 9(2):127. https://doi.org/10.3390/horticulturae9020127

Chicago/Turabian Style

Pinsupa, Suparat, Keasinee Tongmark, Wanchana Aesomnuk, Kannika Srikaewtung, Sriprapai Chakhonkaen, Patcharaporn Summart, Numphet Sangarwut, Wanwarang Pathaichindachote, Samart Wanchana, Kittipat Ukokit, and et al. 2023. "Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation" Horticulturae 9, no. 2: 127. https://doi.org/10.3390/horticulturae9020127

APA Style

Pinsupa, S., Tongmark, K., Aesomnuk, W., Srikaewtung, K., Chakhonkaen, S., Summart, P., Sangarwut, N., Pathaichindachote, W., Wanchana, S., Ukokit, K., & Muangprom, A. (2023). Transcriptome Analysis Reveals Genes Involved in Responses of Eucalyptus to Gall Wasp Infestation. Horticulturae, 9(2), 127. https://doi.org/10.3390/horticulturae9020127

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