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. 2021 Feb 19;27(2):237–249. doi: 10.1007/s12298-021-00953-z

De novo transcriptome assembly of transgenic tobacco (Nicotiana tabacum NC89) with early senescence characteristic

Heng Liu 1, Yu Liu 2, Nini Cheng 3,✉, Yuanhu Zhang 1,✉
PMCID: PMC7907299  PMID: 33707866

Abstract

The enzyme, α-farnesene synthase (AFS), which synthesizes α-farnesene, is the final enzyme in α-farnesene synthesis pathway. We overexpressed the α-farnesene synthase gene (previously cloned in our lab from apple peel) and ectopically expressed it in tobacco (Nicotiana tabacum NC89). Then, the transgenic plants showed an accelerated developmental process and bloomed about 7 weeks earlier than the control plants. We anticipate that de novo transcriptomic analyses of N. tabacum may provide useful information on isoprenoid biosynthesis, growth, and development. We generated 318,925,338 bp sequencing data using Illumina paired-end sequencing from the cDNA library of the apical buds of transgenic line and the wild-type line. We annotated and functionally classified the unigenes in a nucleotide and protein database. Differentially expressed unigenes may be involved in carbohydrate metabolism, nitrogen metabolism, transporter activity, hormone signal transduction, antioxidant systems and transcription regulator activity particularly related to senescence. Moreover, we analyzed eight genes related to terpenoid biosynthesis using qRT-PCR to study the changes in growth and development patterns in the transgenic plants. Our study shows that transgenic plants show premature senescence.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12298-021-00953-z.

Keywords: Nicotiana tabacum (NC89), Transcriptome, Sesquiterpenes, Senescence

Introduction

Isoprenoids are the largest and most diverse group of naturally occurring chemical compounds (Vranová et al. 2012). Isoprenoids are synthesized ubiquitously in prokaryotes and eukaryotes by mevalonate pathway (MVA) in cytosol and peroxisomes (1) or the 2-C-methyl-d-erythritol 4-P/1-deoxy-d-xylulose 5-P (MEP) pathway in the plastids (Rodríguez-Concepción and Boronat 2002). Most organisms utilize only one of the two-MEP and MVA-pathways for synthesizing isoprenoids; however, plants use both MEP and MVA. Because, the five-carbon precursor isopentenyl diphosphate (IPP) and dimethylally diphosphate (DMAPP) exchange can occur between different cellular compartments (Dudareva et al. 2005; Phillips et al. 2008). The synthesis of one isoprenoid may affect metabolic flux towards other metabolites (Robert et al. 2013).

Sesquiterpenes are a class of volatile terpenoids, which play an important role in plants, including defense against herbivorous pests and abiotic stress (Halitschke et al. 2008; Degenhardt et al. 2009). Sesquiterpenes can also act as a stress signal between leaves and participate in protecting plants from oxidative stress (Zebelo et al. 2012). Sesquiterpene synthases produce an array of monocyclic and polycyclic sesquiterpene products from 15-carbon substrate farnesyl diphosphate (Degenhardt et al. 2009). α-Farnesene is a sesquiterpene compound containing conjugated double bonds. It was first found in apple peel and play an important role in plant defense (Huelin and Murray 1966; Kännaste et al. 2008; Danner et al. 2011). For example, apples could produce large amounts of α-farnesene and attract new larvae after being infected by codling moths (Sutherland and Hutchins 1973).

The production of α-farnesene is through the mevalonate pathway of terpenoid metabolism. It is synthesized in the cytoplasm under the catalysis of α-farnesene synthase (AFS) using E, E-FPP as substrates (Rupasinghe et al. 1998). α-farnesene synthase is terminal enzyme of synthesis pathway of α-farnesene, which can synthesize monoterpenes using geranyl diphosphate (GPP) as substrates and synthesize sesquiterpenes using farnesyl pyrophosphate (FPP) as substrates (Pechous and Whitaker 2004; Green et al. 2009). It has been confirmed that α-farnesene synthase in Arabidopsis thaliana, grape, cucumber and apple also has monoterpene/sesquiterpene synthase characteristics (Huang et al. 2010; Martin et al. 2010; Mercke et al. 2004). This characteristic of using multiple substrates can make a terpene synthase produce a variety of terpenoids, which is considered to be of great significance for adapting to the environment during plant growth and development.

The research on α-farnese synthase mostly focuses on gene structure and protein, but not much is known about its function. Previously, our laboratory transferred apple α-farnesene synthase into tobacco to develop premature senescence phenotype and herein we further explored it through transcriptome. Moreover, tobacco (Nicotiana tabacum) can generate a large number of leaf tissues efficiently for fixing atmospheric CO2 as their carbon resource during the growth, making them a sustainable, and scalable plant material for sesquiterpene production (Schillberg et al. 2003; Andrianov et al. 2010). Our study examines the effect of numerous differentially expressed unigenes during N. tabacum growth and development. The transcriptome data in our study provides a reliable genetic resource for identifying potential functional genes involved in isoprenoid and phenylpropanoid biosynthetic pathways.

Materials and methods

Materials and growth conditions

MdAFS gene (Genbank: AY563622) for α-farnesene synthase, which was isolated from apple peel (white winter pearmain), was used to construct a plant expression vector PBI122 that contained a 35S ribosomal RNA promoter from cauliflower mosaic virus (CaMV35S). The 35S-MdAFS plasmid was introduced into Agrobacterium tumefaciens LBA4404, and the resulting plasmid was used to transform N. tabacum (NC89, saved by our laboratory) using the Agrobacterium-mediated method (Liang et al. 1997).

The seeds of T3-1, T3-2, T3-3, and wild type plants were allowed to germinate. The germinated seedlings were grown in MS medium for 3 weeks at 25 °C/20 °C day/night cycle and 16 h/8 h day/night and 300–500 μmol m−2 s−1 photon flux density, and were then transplanted into vermiculite. We selected transgenic and wild-type plants that grew for 60 days for RNA isolation and experimental analysis.

Determination of chlorophyll content

The leaves were immersed in 20 mL of 80% acetone in the dark for 40 h according to Zhang et al. (2020).

Ethylene content determination

Ethylene content was measured according to the method of Nara and Takeuchi (2002). The leaves of tobacco were sealed in a 1000 mL container for 2 h. 1 mL gas was extracted with a syringe and analyzed by gas chromatography (GC-14C, Shimadzu, Japan) equipped with a flame ionization detector. Ethylene release rate was calculated as ppm*v/(t*w), where ppm is the ethylene concentration, v is the container volume, t is the sealing time, and w is the sample weight, respectively.

Sampling RNA isolation and cDNA library construction

In order to obtain the widest possible transcriptome dataset, RNA was extracted from samples of wild-type and transgenic lines, and each line was subjected to three biological replicates. The integrity of total RNA was evaluated by both 1.4% denaturing formaldehyde agarose gel electrophoresis and the Agilent 2100 Bioanalyzer (Palo Alto, CA, USA). The RNeasy MinElute purification kit (Qiagen, Valencia, California) was used to concentrate the mRNA pool and used it as starting material for the cDNA library construction. The Agilent 2100 showed that the cDNA library ranged from 300 to 400 bp including an approximate 125-bp adapter sequence; the true length of the cDNA library was about 200 bp.

Transcriptome data processing, assembly, and gene expression profile building

Perl program was used to filter low-quality sequences from the original sequencing data. Then, high-quality reads were combined with software package Velvet_1.2.10 to construct unique consensus sequences (Zerbino and Birney 2008). Bowtie was used to map the trimmed solexa transcriptome to a unique common sequence (Langmead et al. 2009). The about studies, tobacco transcriptome sequencing, was finished in CapitalBio Corporation (Beijing).

Functional annotation and classification

BLASTN and BLASTX (Altschul et al. 1997) were used to compare unigenes with NCBI non-redundant nucleotide database and Non-redundant protein database. The single gene was identified by comparing the sequence similarity between SWISS-PROT and BLAST (Altschul and Gish 1996; Altschul et al. 1997). Unigenes were assigned functional annotation by sequence similarity comparison against Clusters of Orthologous Groups of proteins database (COG, Tatusov et al. 1997, 2003) with BLAST at E values ≤ 1e−10. Unigenes were compared with the Kyoto Encyclopedia of Genes and Genomes database (KEGG, release 58) using BLASTX (Kanehisa et al. 2006). Perl script was used to retrieve KO information from blast results after which pathway associations were established between the unigenes and the database (Mulder et al. 2003; Zdobnov and Apweiler 2001). Release 4.8 and functional assignments were mapped in Gene Ontology (GO, Harris et al. 2004).

qRT-PCR

To validate the results and provide a basis for further transcriptome analysis, the quantitative real-time PCR (qRT-PCR) method was used according to MIQE guide-lines (Bustin et al. 2009). The cDNA was synthesized using the Revert Aid reverse transcriptase (Tiangen, Beijing, China) and produced cDNA was diluted 1:10 with ddH2O. qRT-PCR system was made up with 1 μL of diluted cDNA samples and SYBR Green/Fluorescein qRT-PCR Mix (2X) (Tiangen, Beijing, China). The qRT-PCR reactions were performed in the Bio-RAD MyiQTM 9 Real-time PCR Detection System (Bio-Rad, California, USA). A total of three technical replicates were performed for each biological replicate and the primers were listed in table S1. 18 s rRNA was used as an internal control gene and relative expression levels of genes were calculated by 2−∆∆CT method (Livak and Schmittgen 2001).

Phenylalanine ammonia-lyase (PAL) activity and lignin measurements

0.5 g of samples were homogenized in 2 mL extracting buffer (pH 8.8) supplemented with 1.4 mL of sodium borate buffer, 0.2 mL of 20 mM EDTA, 0.2 mL of 50 mM β-mercaptoethanol, and 0.2 mL of 4% (w/v) polyvinylpyrrolidone (PVP). The crude enzyme extraction solution (0.5 mL) was incubated with 1.5 mL of borate buffer (50 mmol/L, pH 8.0) and 1 mL of l-phenylalanine (20 mmol/L), for 60 min at 37 °C. The reaction was stopped with 0.5 mL (6 mol/L) HCl. The activity of PAL was measured by the production of cinnamate, which was determined by the absorbance change at 290 nm. Lignin was assayed quantitatively by derivatization with thioglycolic acid, and the absorbance was measured at 280 nm (Bruce and West 1989).

Results

The tissue expression analysis of MdAFS  revealed that MdAFS had the highest expression in calyx, followed by petals, and the lowest expression in stems (Fig. 1a). The MdAFS overexpressing tobacco transgenic lines generated through Agrobacterium-mediated leaf disc transformation were confirmed by kanamycin resistance and genomic PCR (Fig. S1), and further verified homozygous lines by qRT-PCR. The relative levels of MdAFS1 were the highest for T3-2, followed by T3-1, and the lowest levels were observed in T3-3 (Fig. 1b). The three transgenic plants showed increased growth and remarkable variation as compared with wild-type plants. The height of wild-type plants was about 3.2 cm, while transgenic plants were approximately 550% higher than the wild-type (Fig. 1c). This significant change in plant height was the most obvious feature of transgenic plants. The tobacco stem sections revealed that the cells of the stems of transgenic plants were significantly larger than wild type (Fig. S2). The total biomass of transgenic plants was found much lower than that of wild type (Table 1). These results showed that overexpressing MdAFS1 tobacco had early senescence characteristics. The terpenoids content of the plants were determined by GC–MS, and it was found that the release of α-farnesene in transgenic plants was higher than that in wild type (Table 2). Our results also showed that the total chlorophyll and soluble protein content of the transgenic plants were reduced, while the ethylene content and ethylene production rate of the transgenic plants were increased (Fig. 2).

Fig. 1.

Fig. 1

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Analysis of α-farnesene synthase (MdAFS) expression and the phenotype observation. a Expression levels of MdAFS in different parts including root, stem, leaf, calyx, petal, stamen, and pistil. b Analysis of MdAFS expression in leaves of transgenic plants. c The phenotypes of α-farnesene synthase expressing transgenic plants

Table 1.

Biomass statistics in WT and transgenic plants

Biomass WT T3-1 T3-2 T3-3
Root 29.6 ± 1.6a 17.0 ± 0.6b 16.8 ± 0.7b 15.1 ± 0.8b
Stem 33.8 ± 3.5a 15.7 ± 1.1b 17.5 ± 0.2b 14.7 ± 1.3b
Leaf 60.2 ± 1.5a 21.0 ± 1.7b 21.6 ± 0.1b 19.1 ± 2.3b
The number of leaf 26.7 ± 1.1a 15.7 ± 0.4b 17.3 ± 0.4b 16.0 ± 0.7b
The number of capsule 24.0 ± 1.0a 16.0 ± 1.0b 17.0 ± 3.0b 16.3 ± 2.3b
Weight per 1000 grains (mg) 76.2 ± 1.5c 89.2 ± 3.5a 88.1 ± 1.8a 84.9 ± 2.2b
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Table 2.

The terpenoids statistics of tobacco flower by GC–MS

Compound name Compound formula Relative percentage content (%)
WT T3-2
Linalool C10H16 11.69 5.84
Caryophyllene C15H24 17.88 19.3
α-Caryophyllene C15H24 – 0.86
β-Myrcene C10H16 0.45 –
Farnesene C15H24 – 10.22
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Fig. 2.

Fig. 2

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Aging related physiological measurements. a Total chlorophyll content measurement. b Soluble protein content. c Ethylene content. d Ethylene release rate. Error bars indicate standard deviation (SD) based on three biological replicates. The data were analyzed by analysis of variance (ANOVA) and Duncan test of SPSS 22.0 software. Different letters indicate significant differences relative to the WT (p < 0.05)

Sequencing, de novo assembly and prediction of open reading frame (ORFs)

We generated 58,059,142 (5.70 G) paired-end reads for the WT line, and 60,805,968 (5.97 G) paired-end reads for the transgenic line (on average). These high-quality reads were assembled to construct unique sequences resulting in a total of 249,185 unigenes (N50: 2,052 bp; Minimum length: 100 bp; Maximum length: 17,342 bp; Mean length: 1279.87 bp) (Table 3). The high quality reads (46,659,631) were mapped to the genome, which corresponded to 86.55% of the total reads of the WT. The high quality reads (48,959,267) were mapped to the genome, which corresponded to 86.81% of the total reads of the transgenic plant. We generated 249,185 unigenes using the software Velvet_1.2.10 (Table 3), which predicted 210,820 ORFs.

Table 3.

Assembly length statistics

Length (bp) The number of transcripts The ratio of the transcripts (%)
≥ 100 249,185 100
≥ 200 227,479 91.3
≥ 300 199,217 79.9
≥ 400 181,014 72.6
≥ 500 167,532 67.2
≥ 600 156,216 62.7
≥ 700 145,987 58.6
≥ 800 136,608 54.8
≥ 900 127,814 51.3
≥ 1000 119,614 48
≥ 1500 83,243 33.4
≥ 2000 53,816 21.6
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Functional annotation and classification

In order to accurately identify the name, allele or biological function of the transcripts, we utilized various types of nucleotide and protein database functional annotations including the Non-redundant nucleotide database (Nt), Non-redundant protein database (Nr), SWISS-PROT, COG, KEGG, InterPro Scan, and GO. We observed that 187,506 (75.25%) out of 249,185 unigenes had significant similarities with known nucleotides in Nt database while 154,779 (62.11%) unigenes had significant similarities with known proteins in Nr database, and 112,983 (45.34%) unigenes had BLAST hits in SWISS-PROT database (Table 4). The unigenes annotations for the COG, KEGG, InterPro and GO databases are shown in Table 4 and detailed below.

Table 4.

Transcript annotation statistics

Database Total E cutoff
Number of annotated transcripts Ratio of annotated transcripts
Total transcripts 249,185
Nt 187,506 75.25 0.00001
Nr 154,779 62.11 0.00001
Swissprot 112,983 45.34 1E−10
COG 62,595 25.12 1E−10
KEGG 150,333 60.33 1E−10
Interpro 103,003 41.34 Interproscan 4.8
GO 85,703 34.39
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To functionally categorize the tobacco transcriptome, the unigenes were grouped as per  GO classification. Out of 249,185 unigenes, 85,703 (34.39%) were assigned at least one GO term (Table 4). In these unigenes, 68,345 (27.43%) were in cellular component category, 110,411 (44.31%) were in molecular function category and 122,666 (49.23%) were in biological process category (Fig. 3). Tobacco unigenes were divided into 46 functional groups based on GO annotation. For the cellular component, cells, cell parts (23,136 unigenes) and organelles (9685 unigenes) were the most highly represented. For the molecular functions, binding (54,872 unigenes) and catalytic activity (42,123 unigenes) were the highly represented categories. For the biological processes, metabolic processes (43,000 unigenes) and cellular processes (39,630 unigenes) were prominent.

Fig. 3.

Fig. 3

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Functional annotation of assembled sequences based on gene ontology categorization. The unigenes are summarized into three main categories: cellular location, molecular function, and biological processes. The right y-axis represents the number of transcripts in a category. The left y-axis represents the percentage of a specific category of transcripts in that main category

COG classification was performed on the transcriptome data, and 62,595 unigenes were identified (Fig. 4). These unigenes were classified into 24 COG categories and in the ‘general function prediction only’ category, the number of unigenes was the largest (23.64%). The next largest category was ‘posttranslational modification followed by protein turnover and chaperones’ cluster (9.18%), the ‘translation, ribosomal structure and biogenesis’ cluster (7.3%), the ‘carbohydrate transport and metabolism’ cluster (6.89%), the ‘amino acid transport and metabolism’ cluster (5.81%), the ‘replication, recombination and repair’ cluster (5.68%), the ‘energy production and conversion’ cluster (4.11%), and the ‘secondary metabolite biosynthesis, transport and catabolism’ cluster (2.26%).

Fig. 4.

Fig. 4

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COG functional distribution of the tobacco transcriptome

To identify the active metabolic pathways in tobacco, we mapped 150,333 unigenes to KEGG reference pathways. Out of the 150,333 assembled unigenes, 32,757 (21.79%) were assigned to 130 metabolic pathways. Among these identified KEGG pathways, peptidases were the largest, containing 1830 unigenes. Other pathways included protein kinase (1377 unigenes), glycolysis/gluconeogenesis (933 unigenes), starch and sucrose metabolism (920 unigenes), oxidative phosphorylation (855 unigenes), pyruvate metabolism (693 unigenes), photosynthesis proteins (610 unigenes) and nitrogen metabolism (280 unigenes).

We also identified a set of 1209 unigenes that control the metabolism of terpenoids and polyketides. These unigenes were located in MVA and the MEP pathways, and they are responsible for the synthesis of terpenoid. The metabolism of terpenoids and polyketides consists of brassinosteroid biosynthesis (35 unigenes), carotenoid biosynthesis (239 unigenes), diterpenoid biosynthesis (61 unigenes), geraniol degradation (36 unigenes), terpenoid backbone biosynthesis (308 unigenes), tetracycline biosynthesis (51 unigenes), zeatin biosynthesis (79 unigenes), and prenyltransferases (286 unigenes).

Analysis of differentially expressed genes (DEGs)

243,706 and 242,041 transcripts were expressed in the transgenic and WT lines, respectively. Of the differentially expressed transcripts, 3276 were up-regulated and 660 were down-regulated (Table 5, File. S3). Moreover, 436 of these transcripts showed very large changes in expression levels (≥ 5 and ≤ 0.2-fold change compared with the expression levels in the WT); 367 were up-regulated and 69 were down-regulated. According to differentially expressed transcripts, we performed cluster analysis, the results as follows (Fig. 5).

Table 5.

Differentially expressed transcripts between the transgenic and wild-type plants

Class Number of transcripts Ratio (%)
Total transcripts 249,185
Expressed transcripts 247,725 99.37
Expressed in transgenic 244,012 98.42
Expressed in WT 240,661 97.75
Expressed in both 236,948 96.16
Expressed only in transgenic 7064 2.25
Expressed only in WT 3713 1.58
Differentially expressed transcripts (p ≤ 0.01 and ratio ≥ 2 or ratio ≤ 0.5) Total transcripts 3936
Up-regulated transcripts 3276
Down-regulated transcripts 660
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Fig. 5.

Fig. 5

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Cluster analysis of the transgenic and wild-type plant. Red represents up-regulated unigenes and green represents down-regulated unigenes

Involved in carbohydrate metabolism, we found at least 97 up-regulated transcripts including 3-isopropylmalate dehydrate, hexokinase2, UDP-glucuronate 4-epimerase, beta-fructofuranosidase, pectinesterase, phosphoglucomutase, and so on. Moreover, 12 transcripts were down-regulated (File. S4). Nitrogen metabolism genes including Asparagine synthetase and Phenylalanine ammonia-lyase (PAL) were all up-regulated. The transporter activity unigenes were all up-regulated including the calcium ion transporter, glyceraldehyde 3-phosphate transporter, nitrate transporter, ammonium transporter, phosphate transporter, ABC transporter C family member, sugar transporter, cation/carnitine transporter, and magnesium transporter (File. S4).

To emphasisize the phenylpropanoid pathway, we used the KEGG database to categorize the functions of the genes in this pathway (File. S5). We found 42 up-regulated transcripts and no down-regulation in the phenylpropanoid pathway, including with 4-coumarate-CoA ligase, peroxidase 4, cinnamate-4-hydroxylase 1, O-hydroxycinnamoyltransferase, 4-Coumarate–CoA ligase, and phenylalanine ammonia-lyase (PAL, Fig. 6). 4-Coumarate-CoA ligase, which catalyzes the last step of phenylpropanoid pathway leading either to lignins or flavonoids, was induced in the transgenic plant. The physiological experiment suggested that PAL activity was increased by 162.1%, 146.1%, and 137.8% while the lignin content was increased by 114.0%, 120.7%, and 113.4% in transgenic plants, respectively (Fig. 7).

Fig. 6.

Fig. 6

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Different expression analysis of the phenylpropanoid biosynthesis pathway. The red box represents the single gene up-regulated expression, which mainly includes four kinds of genes, namely: 4-coumarate: coenzyme A ligase (6.2.1.12), Peroxidase 12 (1.11.1.7), phenylalanine ammonia lyase (4.3.1.24), Shikimate-O-hydroxycinnamoyltransferase (23.1.133)

Fig. 7.

Fig. 7

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Phenylalanine ammonia-lyase (PAL) activity (a) and lignin content (b) in the transgenic and WT plants. Each column represents an average of three replicates, and bars indicate SDs. The data were analyzed by analysis of variance (ANOVA) and Duncan test of SPSS 22.0 software. Different letters indicate significant differences relative to the WT (p < 0.05)

Verification of differentially expressed unigenes

We selected eight differently expression unigenes involved in plant defense responses, growth, and development, and validated the reliability of the transcriptome using qRT-PCR. Our results showed that jasmonate ZIM-domain protein 1, glutathione S-transferase, ethylene-responsive transcription factor 5, allene oxide synthase, late embryogenesis abundant protein 5, glycine-rich protein precursor, and nitrate reductase had higher expression levels, whereas the auxin efflux facilitator had a lower expression level in the transgenic plants (Fig. 8). All of the results were consistent with the transcriptome data, except for nitrate reductase.

Fig. 8.

Fig. 8

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Validation of transcription levels of nine candidate unigenes by quantitative PCR (qRT-PCR). Locus_6045: jasmonate ZIM-domain protein 1 [Nicotiana tabacum]; Locus_6424: glutathione S-transferase [Solanum commersonii]; Locus_5832: Ethylene-responsive transcription factor 5 [Nicotiana tabacum]; Locus_12878: allene oxide synthase [Solanum tuberosum]; Locus_17469: late embryogenesis abundant protein 5 [Nicotiana tabacum]; Locus_33821: Nitrate reductase [Nicotiana tabacum]; Locus_72229: glycine-rich protein precursor [Nicotiana tabacum]; Locus_19083: auxin efflux facilitator SlPIN4 [Solanum lycopersicum]. The standard error of the mean for three biological replicates is represented by the error bars

Analysis of the key genes in MVA and MEP pathway

Since the overexpression of the sesquiterpene synthase in tobacco resulted in a novel phenotype, we further explored the changes in the terpenoid biosynthesis pathway. For this, we selected the eight key genes of terpenoid biosynthetic pathway including 3-hydroxy-3-methylglutaryl CoA synthetase (HMGS), 3-hydroxy-3-methylglutaryl CoA reductase (HMGR), deoxyxylulose 5-phosphate reductoisomerase (DXR), 1-deoxy-d-xylulose-5-phosphate synthase (DXS), isopentenyl diphosphate isomerase (IDI), farnesyl diphosphate synthase (FPPS), geranyl diphosphate synthase (GPPS) for qRT-PCR analysis. Our results suggested that four key genes (HMGS, HMGR1, HMGR2, and DXR) were upregulated while four genes (DXS, IDI, FPPS, and GPPS) were downregulated (Fig. 9).

Fig. 9.

Fig. 9

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qRT-PCR analysis of 8 terpenoid-related genes on the MVA and MEP pathways. HMGS 3-hydroxy-3-methylglutaryl CoA synthetase, HMGR 3-hydroxy-3-methylglutaryl CoA reductase, DXR 1-deoxy-d-xylulose 5-phosphate reductoisomerase, DXS 1-deoxy-d-xylulose 5-phosphate synthase, IDI isopentenyl diphosphate isomerase, FPPS farnesyl diphosphate synthase, GPPS geranyl diphosphate synthase. The standard error of the mean for three biological replicates is represented by the error bars

Discussion

MdAFS is a terpene synthase and is the terminal enzyme of α-farnesene synthetic pathway, which directly determines the generation of α-farnesene (Yu et al. 2017). Studies have shown that GmAFS in soybeans had the function of defending against nematodes (Lin et al. 2016). Here, we found that overexpressing MdAFS in tobacco had early senescence characteristics. The typical characteristics of leaf senescence are the reduction of biomass and the degradation of chlorophyll and photosynthetic protein (Breeze et al. 2011; Lim et al. 2007). Ethylene is one of the most important hormones in the regulation of leaf senescence, which can trigger the senescence process (Noushina et al. 2017). Our study showed that overexpression of MdAFS decreased biomass and increased ethylene content (Table 1; Fig. 2), and the transgenic plants appeared prematurely senescence (Fig. 1c). We further explored the premature senescence of transgenic plants by RNA-seq analysis.

The main physiological purpose of senescence is salvaging nutrients such as the hydrolysis of macromolecules and subsequent remobilization to other parts (Himelblau and Amasino 2001; Bazargani et al. 2011). The apical bud is located at the top of the stem axis, which is one of the most active growing points in plants. Therefore, apical bud is a destination of nutrition remobilization. In the carbohydrate metabolism category, the unigenes for amino sugar and nucleotide sugar metabolism (19 upregulated), starch and sucrose metabolism (33 upregulated), and nitrogen metabolism, ammonium transporter, and nitrate transporter were up-regulated in transgenic plants (File S4). These unigenes indicated that primary metabolism was active in the apical bud of transgenic plants.

Flavonoids and terpenoids (isoprenoids) are the two largest types of metabolites in higher plants. Flavonoids and terpenoids are derived from different metabolic pathways but play complementary roles in coordinating the interactions between plant and environment. The expression of the SlCHI1 (chalcone isomerase) gene from its native promoter complements anthocyanin deficiency in an anthocyanin mutant. Moreover, overexpression of SlCHI1 also complements the defect in terpenoid production in glandular trichomes (Kang et al. 2014). Furthermore, the total amount of terpenes was correlated with the total levels of terpene synthase activities, and negatively correlated with the phenylpropanoids and phenylalanine ammonia lyase activity (Iijima et al. 2004). In our study, 42 differentially expressed unigenes were up-regulated in the phenylpropanoid pathway (File. S5; Fig. 6). The PAL activity and the lignin content were higher in transgenic plants than in WT (Fig. 7). The results indicated that the phenylpropanoid pathway was activated in transgenic plants.

Plant hormones such as auxins, gibberellic acid, brassinosteroids, and cytokinins promote growth and development. Auxin is transported throughout the plant in a polar manner through the PIN-FORMED family of auxin efflux carriers (Ljung 2013; Adamowski and Friml 2015). At least 21 down-regulated unigenes of the auxin efflux facilitator affect apical meristem auxin transport (File. S4). In contrast, ethylene promotes senescence. Compared with nonsenescing leaves, senescing leaves of Arabidopsis thaliana have higher concentrations of ethylene (Breeze et al. 2011). With respect to ethylene, 77 unigenes were up-regulated, including the ethylene-responsive transcription factor (ERF) and the AP2/ERF domain-containing transcription factor. The regulatory proteins have participated in the control of primary and secondary metabolism, and the developmental process. For example, the ectopic expression of ERF1 leads to a dwarf phenotype in Arabidopsis (Liu et al. 1998; Solano et al. 1998). AP2/ERF domain-containing transcription factors determine stem cell characteristics in Physcomitrella patens (Aoyama et al. 2012). ERF proteins are also involved in secondary metabolism, mainly in pharmaceutical applications; the characteristic feature of secondary metabolites is jasmonate responsiveness. COI1(F-box protein)/JAZs/MYC2 is the core JA signaling pathway module and JA-induced AtWRKY40, probable WRKY transcription factor 26, WRKY33, WRKY41, WRKY50, WRKY53, WRKY64, and WRKY70 are up-regulated unigenes. MYC2 is considered to be the main mediator of the JA signaling pathway, interacts with abscisic acid, ethylene, and the light signaling pathways, and positively regulates sesquiterpene biosynthesis (Hong et al. 2012). WRKYs, which regulate lignin production or deposition may also directly or indirectly affect flux through phenylpropanoid pathway (Besseau et al. 2007). In Arabidopsis, four members of the WRKY group IIIb proteins (WRKY30, WRKY53, WRKY54, and WRKY70) have participated in the regulation of plant senescence associated with SA (Besseau et al. 2012). Thus, auxin efflux carriers that inhibit senescence were downregulated in our study. Ethylene and JA signaling pathways were considered to promote senescence. We speculate that hormones regulate premature senescence in transgenic plants. Moreover, senescence-associated gene 21 (SAG21) was up-regulated. This result implied that senescence had started early in transgenic plants. MADS-box protein regulated flowering while the suppressor of overexpression of constans1 (SOC1) was upregulated.

KEGG pathway enrichment results showed that 1209 unigenes are involved in metabolism of terpenoids and polyketides including 308 unigenes that were annotated in terpenoid backbone biosynthesis (Table 4). The majority of unigenes -not functionally verified-will provide sequence source and facilitate further studies in terpenoid biosynthesis gene cloning and functional analysis. In MVA pathway, 3-hydroxy-3-methylglutaryl CoA synthetase (HMGS) catalyzes the conversion of acetyl-CoA and acetoacetyl-CoA to 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA; Lange et al. 2000; Liu et al. 2016). Next, 3-hydroxy-3-methylglutaryl CoA reductase (HMGR) catalyzes biosynthesis of mevalonate from HMG-CoA which is positively correlated with sterol (Sharpe and Brown 2013). Up-regulated HMGR only increased metabolic flux in MVA pathway. Since this function is coordinated with the function of other enzymes, the down-regulated farnesyl diphosphate synthase (FPPS) and isopentenyl diphosphate isomerase (IDI) may suppress the synthesis of terpenoids in the MVA pathway (Fig. 9). In MEP pathway, 1-deoxy-d-xylulose-5-phosphate synthase (DXS) and deoxyxylulose 5-phosphate reductoisomerase (DXR) participate in an important rate-limiting step in biosynthesis of MEP-derived isoprenoids such as chlorophylls, abscisic acid, and GAs. Although DXR is up-regulated, a suggestion of the dynamics of 2-C-methyl-d-erythritol-2, 4-cyclodiphosphate (MEcDP) mobility was provided by metabolic control analysis of MEP pathway, which indicated that DXS is the main controlling enzyme of this pathway (Wright et al. 2014). Therefore, GPPS, DXS, and IDI also restrict the products and metabolic flux of MEP pathway.

We analyzed the N. tabacum transcriptome and identified key genes of isoprenoid biosynthetic pathway and phenylpropanoid pathway. Our study shows that the overexpression of α-farnesene synthase in N. tabacum changes the isoprenoid biosynthetic pathway and activates the phenylpropanoid pathway. The analysis of differentially expressed unigenes and the transcription factors for hormone signal transduction highlighted their important role in senescence of transgenic plants. Transcriptomic data will provide a deeper insight in the process of senescence in transgenic tobacco.

Supplementary Information

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Supplementary file1 (DOCX 1318 KB) (1.3MB, docx)
Supplementary file2 (XLS 784 KB) (783.5KB, xls)
Supplementary file3 (XLS 44 KB) (43.5KB, xls)
Supplementary file4 (XLS 81 KB) (80.5KB, xls)
Supplementary file5 (DOCX 15 KB) (14.8KB, docx)

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Nos. 30970256, 31370359).

Author contributions

Designed the experiments: HL, NC and YHZ. Performed the experiments: HL and NC. Analyzed the data: HL, NC, YL. Wrote the paper: HL, NC and YL.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflicts of interest.

Footnotes

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Contributor Information

Nini Cheng, Email: chengnn2002@163.com.

Yuanhu Zhang, Email: yhzhang9@163.com.

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