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Article

Full-Length Transcriptome Analysis of the Secondary-Growth-Related Genes of Pinus massoniana Lamb. with Different Diameter Growth Rates

by
Zijing Zhou
,
Guijie Ding
,
Zhengchun Li
and
Fuhua Fan
*
Institute for Forest Resources and Environment of Guizhou Province/Key Laboratory of Forest Cultivation in Plateau Mountain of Guizhou Province/College of Forestry, Guizhou University, Guiyang 550025, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(4), 811; https://doi.org/10.3390/f14040811
Submission received: 9 March 2023 / Revised: 3 April 2023 / Accepted: 13 April 2023 / Published: 15 April 2023
(This article belongs to the Section Genetics and Molecular Biology)
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Abstract

:
Secondary growth is the main source of wood accumulation and has an extremely complex regulation process. Pinus massoniana Lamb. is one of the main timber tree species in China and it is of great significance in the study of the secondary growth process. The full-length transcriptome from the stems of P. massoniana with different diameter growth rates was obtained by PacBio and 15,448 full-length transcripts were identified. A comparative transcriptome analysis revealed that 408 genes were differentially expressed between the fast-growing wood (FGW) and slow-growing wood (SGW). The important regulatory genes involved in the secondary growth of P. massoniana (cell division, cell wall biosynthesis, lignification, and programmed cell death), such as ARL8, POD, EXPA8, Ecm33, and RhoA, were identified by a GO and KEGG annotation analysis. The differential expression of the key genes in the lignin synthesis pathway were obtained, such as PAL, 4CL, CCR, HCT, and PER. In addition, the abscisic acid receptor gene PYL and the ethylene biosynthesis key gene EFE were screened for their involvement in the regulation of the secondary growth of P. massoniana. It is speculated that these genes coordinate the processes of secondary growth to promote the rapid growth of FGW. This study preliminarily explored the differential mechanism of the growth rate of P. massoniana and provided a reference for obtaining new P. massoniana germplasm with a high quality and excellent yield.

1. Introduction

Secondary growth is an increase in the circumference of plant organs, and includes cell division, cell expansion, cell wall biosynthesis, lignification, and programmed cell death [1]. Cell division is the starting point of plant secondary growth and the direction of this cell division is crucially important for plant growth and development. The direction of cell division in vascular tissue is regulated by the interaction between the receptor kinase (PXY) expressed in mitotic cells and its peptide ligand (CLE41) located in adjacent phloem cells [2]. The secondary growth of the plant stem is caused by the cell division of the vascular cambium. The cambium forms xylem inward and phloem outward [3,4]. The expansion of cells in the secondary xylem and phloem leads to an increase in stem diameter. This process is the main source of wood accumulation [5]. The cell wall is the main component of wood biomass and the plant cell wall is a complex extracellular matrix, which is mainly composed of lignin, cellulose, and hemicellulose [6]. The cell wall regulates plant growth and morphology at the levels of the cell, tissue, and organism, and plays a vital role in providing mechanical support and protection for plants [7]. Lignification is a process in which lignin is deposited on the cell wall by the oxidative polymerization of lignin monomers [8]. It mainly occurs in the secondary xylem, which can make the xylem cell wall harder, making the plant better at transporting water over long distances and more resistant to stress [9]. Lignification mainly goes through three developmental processes: lignin monomers are synthesized in the cytoplasm [10], the lignin monomers are transported through the cell membrane [9], and the lignin monomers are oxidized and polymerized on the cell wall [11,12]. After this lignification, tubular molecules and fibrous cells enter the stage of programmed cell death. The programmed death process of these tubular molecules includes the degradation of organelles, accompanied by the degradation of protoplasts and some unlignified secondary walls [13].
Plant secondary growth is an extremely complex process, and it is a hot issue studied by the majority of researchers because of the importance of wood in the construction industry. The secondary growth of Arabidopsis thaliana (L.) Heynh. occurs in stems, roots, and hypocotyls [14]. Previous studies have demonstrated the transcriptome profile changes in A. thaliana during secondary growth using 8.3 K Arabidopsis genome arrays. These have shown that 20% of the genes related to wood formation exhibit different expressions in stems [1]. A total transcriptome analysis has revealed that the expression profiles of these genes related to signal transduction and transcriptional regulation were the main reasons for the major differences between the stems of secondary growth and those of only primary growth [15]. Many researches have documented that plant hormones such as auxin [16,17], gibberellin [18,19], brassinosteroid [20,21], jasmonic acid [22], ethylene [23,24], and abscisic acid [25] play a vital role in plant secondary growth. However, the molecular framework of secondary growth is largely based on the study of the annual herb A. thaliana. Poplars are more common in woody plants [26,27,28], whereas there are few studies on gymnosperms.
Pinus massoniana Lamb. is a unique conifer species in China which has an important utilization value in pulp material utilization and wood processing [29]. However, in its cultivation process, the diameter growth rates of P. massoniana with the same family, tree age, site condition, and cultivation model were different. The difference in their gene expression levels is a research content that needs to be explored, and it is unknown whether these differentially expressed genes may be involved in the secondary growth of P. massoniana. Due to the lack of a whole genome sequence of P. massoniana, there is little information about the molecular regulation of the wood formation in P. massoniana. Therefore, full-length transcriptome sequencing, combined with an RNA-Seq of P. massoniana with different diameter growth rates, was carried out to identify the genes related to the secondary growth in P. massoniana. This study provides a theoretical foundation for the regulation mechanism of secondary growth and also provides candidate genes for the breeding of fast-growing P. massoniana.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The samples of P. massoniana were collected from the superior families of the P. massoniana experimental forest farm of the Nanning Forestry Science Research Institute in Guangxi. The afforestation time was 1994 and the address was located in Luoxu Town, Wuming Country. The sample collection site belongs to the subtropical monsoon climate. Its annual average temperature is 21.7 °C and its annual average rainfall is 1100–1700 mm. The research materials of this study were 6 P. massoniana from the same family at 24 years old from this experimental forest. The highly significant differences within the family were observed for their phenotypic values, especially their diameters at breast height (DBH). Based on the DBHs, the three largest individuals (about 29 cm) and the three smallest individuals (about 16 cm) within the same family were recorded as fast-growing wood (FGW) and slow-growing wood (SGW), respectively. At the breast height of the trees, bark and primary phloem were removed, and cambium and surrounding tissue were stripped from the trees, frozen immediately in liquid nitrogen, and then stored in a −80 °C cryogenic refrigerator.

2.2. Total RNA Extraction and Assessment of Quality

An RNAprep Pure polysaccharides and polyphenols plant total RNA extraction kit (Tiangen, Beijing, China) was used to extract the total RNA. The RNA degradation and contamination were assessed on 1% agarose gels. The Keyo K5500 spectrophotometer (Keyo, Beijing, China) was used to determine the purity of the sample. The Agilent 2100 RNA Nano 6000 test kit (Agilent Technologies, Santa Clara, CA, USA) was used to detect the concentration and integrity of the RNA.

2.3. PacBio Iso-Seq Library Preparation, Sequencing and Data Analysis for Building Reference Sequence

The total RNA from six independent samples (FGW and SGW with three biological replicates) was mixed at equal ratios. After qualification, the RNA with a PolyA tail was enriched by Oligo(dT). The SMARTer®PCR cDNA Synthesis Kit (Clontech Laboratories, Mountain View, CA, USA) was used for the reverse transcription of RNA into cDNA. Additionally, the KAPA HiFi PCR kit (KAPA Byosystems, Wilmington, MA, USA) was used to amplify the synthesized cDNA. The library was constructed with a SMRTbell template prep kit (Pacific Biosciences, Menlo Park, CA, USA) after a fragment screening by BluePippin. The stem annular sequencing connectors were connected at both ends of the DNA fragments and the fragments that failed to connect were removed with exonuclease. The library templates and enzyme complexes of a certain concentration and volume were transferred into the nanopores of the PacBio Sequel sequencer and sequenced after the quantification. The cDNA libraries were sequenced on the third-generation sequencing platform of PacBio. The obtained Polymerase Reads were filtered to remove the sequences with a short read length and low quality. Lima software was used to identify and remove the dock sequence, ICE (isoform-level clustering algorithm) was used to cluster and correct the transcripts, and finally, a high-quality full-length sequence was obtained. The Trinotate annotation tool was used to annotate ORF against the following databases, including homology search (NCBI-BLAST, https://blast.ncbi.nlm.nih.gov/Blast.cgi (accessed on 5 April 2021)), protein domain identification (Pfam, http://pfam.xfam.org/ (accessed on 7 April 2021)), protein signal prediction (SingalP, http://www.cbs.dtu.dk/services/SignalP/ (accessed on 10 April 2021)), Uniprot (https://www.uniprot.org/ (accessed on 13 April 2021)), eggNOG (http://eggnog5.embl.de/#/app/home (accessed on 15 April 2021)), GO (http://geneontology.org/ (accessed on 18 April 2021)), and KEGG (http://www.genome.jp/kegg (accessed on 23 April 2021)). The genes annotated to BLASTX (http://www.ncbi.nlm.nih.gov/BLAST/ (accessed on 25 April 2021)), BLASTP (http://www.ncbi.nlm.nih.gov/BLAST/ (accessed on 26 April 2021)), NR (http//www.ncbi.nlm.nih.gov/ (accessed on 28 April 2021)), and NT (https://www.ncbi.nlm.nih.gov/nucleotide/ (accessed on 29 April 2021)) were counted and a Wayne diagram was made.

2.4. Illumina Transcriptome Library Preparation, Sequencing, and Data Analysis for Gene Expression

The differential expression genes (DEGs) of the FGW and SGW in the wood formation were identified by a comparative transcriptome analysis. The integrity and quantity of the total RNA from the six independent samples (FGW and SGW with three biological replicates) were detected using the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). The oligo(dT) beads were used to enrich the mRNA and a fragment buffer was used to split the mRNA into short fragments, which were reverse-transcribed into cDNA by random primers. RNase H, DNA polymerase I, dNTPs, and a buffer were used to synthesize the second-strand cDNA. The QiaQuick PCR extraction kit (Qiagen, Hilden, Germany) was used to purified the cDNA fragments, followed by end repair, poly(A) sequence addition, and Illumina sequencing adapter ligation. Agarose gel electrophoresis was used to select the size of the ligation products, which was then amplified by a PCR. Finally, the sequencing was performed on the Illumina platform with a PE150 sequencing strategy. The low-quality sequence, the sequence of joint contamination, and the sequence containing more than 5% N in raw reads were removed to get clean reads. The clean reads were assembled using Trinity (Trinity Release V2.4.0) to obtain the transcripts. A post-assembly evaluation was performed using Bowtie2. The coding region of unigene was identified by TransDecoder (TransDecoder Release v3.0.1). Trinotate (Trinotate Release v3.0.2) was used for a functional annotation of ORF. The level of gene expression was detected by RPKM. Using a DESeq2 analysis of the DEGs of the FGW and SGW, the |log2(fold change)| ≥ 1 and q < 0.05 genes were identified as DEGs. The GO (Gene Ontology, http://geneontology.org/ (accessed on 10 May 2020)) enrichment of the DEGs was implemented by the hypergeometric test, in which the p-value was calculated and adjusted as a q-value, and the data background was the genes in the whole genome. The GO terms with q < 0.05 were considered to be significantly enriched. The GO enrichment analysis could exhibit the biological functions of the DEGs. The KEGG (Kyoto Encyclopedia of Genes and Genomes, http://www.kegg.jp/ (accessed on 10 May 2020)) database was used for the enrichment analysis of the KEGG pathways. The KEGG enrichment of the DEGs was implemented by the hypergeometric test, in which the p-value was adjusted by multiple comparisons as a q-value. The KEGG terms with q < 0.05 were considered to be significantly enriched.

2.5. RT-qPCR Validation of DEGs

A real-time quantitative PCR assay (RT-qPCR) was used for the validation of the DEGs’ expression profiles. Primers were designed with Primer Premier 5.0 software (Primier Biosof international., Quebec, QC, Canada). According to the manufacturer’s instructions, an RT-qPCR was performed using the talent fluorescence quantitative detection kit (Tiangen, Beijing, China) on a four-channel gradient fluorescence CFX96 quantitative PCR system (BioRad, Hercules, CA, USA). A 10 µL reaction containing 1 µL of synthesized cDNA, 5 µL of 2-TB Green Premix Ex Taq mix, 0.5 µL of 10 mM forward primer, 0.5 µL of 10 mM reverse primer, and 3 µL of sterile distilled water was amplified. The PCR amplification was performed as follows: preheating at 94 °C for 10 min, followed by 40 cycles at 94 °C for 15 s, 58 °C for 30 s, 72 °C for 30 s, and the melting curves were generated from 65 °C to 95 °C with increments of 0.5 °C every 5 s. UBC (TRINITY_DN51309_c0_g1) was selected as the reference gene [30]. Each sample was conducted with three biological and three technical replicates. The relative expression levels of the genes were calculated by the 2−∆∆Ct method [31]. A univariate analysis of variance (ANOVA) and Duncan’s multipole difference test were used to analyze the differences in the gene expression levels under the different treatments. The primers used for the RT-qPCR are listed in Table S1.

3. Results

3.1. Full Length Transcriptome Sequencing and Annotation

To obtain a more comprehensive understanding of the transcript information of P. massoniana, the total RNAs of the wood with different diameter growth rates were collected and reverse transcribed into cDNA. Based on the PacBio Sequel platform, a total of 13,517,119 subreads with an average length of 1764 bp were generated. By removing the adapters and artifacts, 407,731 CCSs were obtained from the subreads. In total, 357,605 ROI (Reads of Insert) were obtained after identifying and removing the dock sequence using the Lima software (Table S2). In the process of the transcriptional group sequencing, there were a large number of redundant sequences in the isoform. Here, the redundant sequences were clustered together by the ICE (isoform-level clustering) algorithm to gain new consistent sequences. Then, the untested complete insert sequence was compared to the consistent sequence with an error correction using default values, and a total of 39,402 high-quality transcripts with an accuracy greater than 0.99 were obtained (Table S3). Finally, 15,448 genes with complete ORF were obtained, with the shortest ORF length being 297 bp, the longest being 6030 bp, and the average length being 1257 bp (Figure 1A). Trinotate (20140717) was used to annotate the function of ORF. The numbers of the genes annotated to BLASTX, BLASTP, NR, and NT were 10,844, 10,413, 12,496, and 12,082, respectively, of which 9873 genes were annotated in the four databases (Figure 1B).
After the GO analysis by Blast2GO, all the genes were annotated, with a total of 65 terms in the biological process, cellular component, and molecular function. The major subgroups of the biological process were the “cellular process” and “metabolic process”. In the cellular component category, most genes were involved in the “cell part” and “organelle”. For the molecular function classification, the major categories were “binding” and “catalytic” (Figure 1C). In order to better understand the biological functions of the genes, a KOG annotation analysis was performed and 7907 genes were annotated into 24 function classes. The most abundant was “general function prediction only”, followed by “posttranslational modification, protein turnover, chaperones”, “signal transduction mechanisms”, “translation, ribosomal structure and biogenesis”, and “carbohydrate transport and metabolism” (Figure 1D).

3.2. Analysis of Differentially Expressed Genes

To explore the differences in the gene expressions between the FGW and SGW in the wood formation, the DEGs were identified by the DESeq2 setting |log2 fold change| ≥ 1 and q < 0.05 (Table S4). The results showed that 408 genes were differentially expressed between the FGW and SGW, of which 203 were significantly up-regulated and 205 were down-regulated in the FGW (Figure 2).
The GO analysis showed that the DEGs were summarized into three categories: biological process, cellular component, and molecular function. Among them, 24 GO items were significantly enriched in the biological process, and the top three were defense response, response to other organism, and response to external biotic stimulus, respectively. They were enriched in three GO entries in the cellular component, including cell periphery, plasma membrane, and ribosome. They were only significantly enriched in ADP binding in the molecular function (Figure 3A).
Based on the pathways in the KEGG database, 408 DEGs were annotated functionally. The DEGs were classified into five sections including “Metabolism”, “Genetic Information Processing”, “Environmental Information Processing”, “Cellular Processes”, and “Organismal Systems”. The pathway with the most DEG enrichment was “Metabolism” (Figure 3B). In addition, a scatter plot of the KEGG enrichment analysis was generated, including only the top 20 enriched pathways. “Ribosome” was the most enriched pathway (Figure 3C).

3.3. Characterization of Differentially Expressed Genes Related to Cell Wall Organization or Biogenesis

In total, 16 DEGs that were directly related to secondary growth were identified, with the functions of cell division, cell expansion, cell wall biosynthesis, lignification, and programmed cell death (Figure 4A). Among the differentially expressed genes, ADP-ribosylation factor-like protein (ARL8, TRINITY_DN50292_c0_g1) and peptide transporter 2 (PTR2, TRINITY_DN49574_c1_g1) were found to be involved in regulating cell division. A total of 11 DEGs annotated in the cell wall organization or biogenesis were found by the GO analysis, and 8 of them were up-regulated. Peroxidase (POD, TRINITY_DN54940_c1_g1) was involved in hydrogen peroxide detoxification, auxin catabolism, lignin biosynthesis, and stress response. Expansin (EXPA8, TRINITY_DN53400_c0_g1 and EXPB1, TRINITY_DN55448_c0_g1) loosened and extended the plant cell walls by disrupting the non-covalent bonding between the cellulose microfibrils and matrix glucans. The cell wall organization protein (Ecm33, TRINITY_DN54506_c0_g4/TRINITY_DN80574_c0_g1) was an important part of the cell wall, which may be very important for the integrity of the cell wall. The GTP-binding protein (RhoA, TRINITY_DN50385_c0_g1) promoted the formation of stress fibers and focal adhesions and regulated cell shape, attachment, and motility. A total of four down-regulated DEGs were identified as cellulose synthase-like protein (CSLE6, TRINITY_DN51048_c0_g1), pectin acetylesterase (PAE7, TRINITY_DN61871_c1_g1 and PAE8, TRINITY_DN61871_c1_g3), and glycoside hydrolase (YHZ7, TRINITY_DN61629_c3_g5). An enhanced disease susceptibility 1 (EDS1, TRINITY_DN59754_c2_g4) and phytoalexin deficient 4 (PAD4, TRINITY_DN56155_c0_g7/TRINITY_DN61947_c3_g1) were closely related to the programmed cell death.
It was found that “Phenylpropanoid biosynthesis” was significantly enriched in the KEGG enrichment analysis. It is well known that lignin synthesis is related to “Phenylpropanoid biosynthesis”. We identified the genes in the lignin biosynthesis pathway and found that key enzymes, such as phenylalanine ammonia-lyase (PAL), 4-coumarate CoA ligase (4CL), cinnamoyl-CoA reductase (CCR), shikimate hydroxycinnamoyl transferase (HCT), caffeic acid O-methyltransferase (COMT), and peroxidase (PER), were differentially expressed (Figure 4B).
Plant hormones were also an indispensable part of secondary growth. Based on the analysis of the differentially expressed genes (Figure 4C), it was found that the abscisic acid receptor gene PYL (TRINITY_DN52090_c0_g1/TRINITY_DN53551_c0_g1) in abscisic acid signal transduction was significantly up-regulated in the FGW. Most of the genes involved in ethylene signal transduction were up-regulated in the FGW, despite no statistically significant difference being investigated between them. However, the expression of EFE (TRINITY_DN47565_c0_g1), a key gene in ethylene biosynthesis, was significantly up-regulated in the FGW. To test the accuracy of the RNA sequencing results, an RT-qPCR was performed to test four randomly selected DEGs (Figure 4D). Additionally, they may play important roles in the secondary growth of P. massoniana. The results showed that the expression of these genes was basically consistent with the transcriptome results, indicating that the mRNA sequencing data in this study were reliable.

4. Discussion

P. massoniana is an important timber species in China, and its accumulation of wood is mainly produced through the secondary growth process. Therefore, the transcriptome data of P. massoniana wood with different diameter growth rates were compared, and many genes involved in its secondary growth process (cell division, cell wall biosynthesis, lignification, and programmed cell death) were obtained. ARL (ADP-ribosylation factor-like protein) is one of the two subfamilies of ARF (ADP-ribosylation factor). The structure of the ARL protein is similar to that of ARF, with a 40%–60% homology [32]. ARF is a kind of protein that exists widely in eukaryotes and is highly conserved. It was found that ARF was widely involved in the growth and development of plants. In the ARF1 knock out mutant of A. thaliana, an abnormal Golgi apparatus blocks the transportation of proteins, inhibiting the plant growth and development [33]. The biomass of switchgrass with overexpressed ARF genes was about twice as much as that of wild-type plants [34]. The plant size and growth rate of A. thaliana with overexpressed maize ARF genes were increased [35]. Additionally, other studies have found that ARFs play a positive role in plant resistance to biotic and abiotic stresses [34,36]. The ARL8 obtained in this study was annotated into the GO term “cell division”. Additionally, ARL8 was significantly up-regulated in the FGW. Therefore, we speculated that it may be involved in cell division in the secondary growth process of P. massoniana, or may play more roles in its other aspects, thus making it one of the candidate genes that may affect the differences in the growth rate of P. massoniana.
POD (peroxidase) is a polygene family widely distributed in plants. It is involved in hydrogen peroxide detoxification [37,38], auxin catabolism [39], and stress response [40]. Some studies have proven that POD is a key enzyme in the lignin biosynthesis pathway. Lignin is one of the main components of the plant cell wall, which can increase the strength of the cell wall and promote the resistance of the plant to mechanical stress [41]. After the peroxidase isoenzyme (TP60) in tobacco was down-regulated by the antisense strategy, the lignin content of tobacco was 40% and 50% lower than that of its wild-type [42]. The lignin content of Gerbera Jamesonii Bolus was significantly increased after the overexpression of the POD gene [43]. In this study, the expression of POD in the FGW was significantly higher than that in the SGW, indicating that POD may play an important role in the secondary growth of P. massoniana.
Expansin is a unique family of plant cell wall proteins, which are involved in cell wall modification during the development of many plants [44]. In the present study, two kinds of expansin were significantly upregulated in the FGW, in which EXPA8 belongs to α-expansin and EXPB1 belongs to β-expansin. Rice EXPA8 was confirmed to be located on the cell wall by transient expression, and the inhibition of its expression would significantly reduce plant growth [45]. On the contrary, the overexpression of EXPA8 would significantly improve the plant growth [46]. Early studies have shown that the expression of the β-expansin gene promoted rapid internode elongation in deepwater rice [47]. The overexpression of EXPB1 in wheat has also proved that the gene could promote the growth and development of plants [48]. Thus, expansin may be involved in the growth and development of P. massoniana.
PAD4 and EDS1 are important components of the mechanism of programmed cell death in plants, and play a key role in regulating plant nutrition and reproductive growth [49]. At the same time, PAD4 plays an important role in plant resistance to biological stress. The salicylic acid SA-dependent and SA-independent defense pathways were promoted by PAD4 in conjunction with its interacting partner protein, EDS1 [50,51]. In this study, the expressions of PAD4 and EDS1 in the FGW were significantly higher than those in the SGW, suggesting that PAD4 and EDS1 may make the FGW have a faster growth rate by regulating the programmed cell death and enhancing the defense ability.
Lignin is an important macromolecular substance in plants, which widely exists in vascular plants. Additionally, lignin also plays an important role in water transport, plant mechanical support, and resistance to external adverse environments [41]. Several key genes or enzymes involved in the lignin synthesis pathway were differentially expressed in this study. PAL (Phenylalanine ammonia-lyase) is one of the key enzymes in the phenylpropanoid pathway. The overexpression of RcPAL significantly increased the activity of PAL, the staining depth of the xylem cells, and the content of the lignin [52]. 4CL (4-Coumarate: coenzyme A ligase) is one of the important enzymes in lignin biosynthesis. In 5-year-old Pto4CL1-modified poplar, the lignin content increased from 33.11% to 46.65% with the up-regulation of Pto4CL1 [53]. CCR (Cinnamoyl-CoA reductase) catalyzes hydroxycinnamoyl-CoA to hydroxy cinnamaldehyde as the first enzyme in the lignin-specific biosynthetic pathway [54]. The overexpression of LcCCR13 increased the CCR activity and lignin content in Liriodendron chinense (Hemsl.) Sarg. [55]. HCT (Hydroxycinnamoyl-CoA shikimate hydroxycinnamoyl transferase) is one of the key enzymes in the lignin biosynthesis pathway. The lignin contents of HCT-downregulated transgenic poplar stems were significantly decreased [56]. The differential expressions of these genes or enzymes would directly affect the lignin content of plants. This may be an important factor for the differences in diameter growth rates of P. massoniana. In this study, the expressions of PAL (TRINITY_DN49176_c0_g6), 4CL (TRINITY_DN62730_c2_g5), CCR (TRINITY_DN53539_c1_g4, TRINITY_DN53539_c1_g2), and HCT (TRINITY_DN58522_c3_g1) were higher in the FGW than the SGW. Therefore, it is speculated that these genes may act as markers of FGW.
Plant hormones are one of the important endogenous factors affecting secondary growth. In this study, we found that the abscisic acid receptor gene PYL in abscisic acid signal transduction and the key gene EFE in ethylene biosynthesis were significantly up-regulated in the FGW. It was speculated that plant hormones may be the influencing factor of the growth rate differences in P. massoniana. It has been found that ABA regulates the SCW deposition and lignification in A. thaliana at the transcriptional and translational levels [57]. Additionally, the function of ABA in plants is realized by the recognition of the intracellular PYL receptor families [25]. Therefore, it can be seen that PYL is the key gene of ABA affecting the secondary growth of P. massoniana. The ethylene-forming enzyme (EFE) is a key gene for ethylene production [58]. Ethylene plays an important role in the regulation of cell wall metabolism. Strawberry fruit was treated with an ethylene-releasing reagent ethephon, which resulted in higher contents of hemicellulose, cellulose, and neutral sugar [59]. Studies have shown that ethylene could induce the internode expansion of pea [24]. At the same time, it affected the expression of the cell-wall-related genes in Gramineae plants [60]. However, there are few studies on woody plants, so the findings of this study provide a new point for subsequent studies on secondary growth.
In summary, we obtained some genes related to secondary growth, and they are up-regulated in the FGW. ARL8 (TRINITY_DN50292_c0_g1) was annotated into cell division. EXPA8 (TRINITY_DN53400_c0_g1), EXPB1 (TRINITY_DN55448_c0_g1), and POD (TRINITY_DN54940_c1_g1) were related to cell wall biosynthesis. PAD4 (TRINITY_DN56155_c0_g7, TRINITY_DN61947_c3_g1) and EDS1 (TRINITY_DN59754_c2_g4) were involved in the programmed cell death in plants. PAL (TRINITY_DN49176_c0_g6), 4CL (TRINITY_DN62730_c2_g5), CCR (TRINITY_DN53539_c1_g4, TRINITY_DN53539_c1_g2), and HCT (TRINITY_DN58522_c3_g1) were key genes or enzymes in the lignin synthesis pathway. These results indicate that these genes may be markers of FGW.

5. Conclusions

The full-length transcriptome from the stems of P. massoniana with different diameter growth rates was obtained by PacBio and 15,448 full-length transcripts were identified. After the transcriptome sequencing, 408 differentially expressed genes were obtained from the FGW and SGW. Some genes related to secondary growth processes (cell division, cell wall biosynthesis, lignification, and programmed cell death) were significantly up-regulated in the FGW. The differential expressions of the key genes or enzymes in the lignin synthesis pathway were obtained. At the same time, the abscisic acid receptor gene PYL and ethylene biosynthesis key gene EFE were also significantly up-regulated in the FGW. It is speculated that these genes coordinate the processes of cell division, cell wall biosynthesis, lignification, programmed cell death, and hormone regulation to promote the rapid growth of FGW. Our results provide a theoretical foundation for exploring the difference mechanism of the diameter growth rates of P. massoniana.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14040811/s1; Table S1: The primer sequence of genes used for RT-qPCR validation; Table S2: Statistical table of transcript sequences of Pinus massoniana; Table S3: Statistical table of transcript error correction of PacBio sequencing; Table S4: Statistical table of differentially expressed genes.

Author Contributions

Conceptualization, F.F., G.D. and Z.Z.; methodology, F.F.; software, Z.Z. and Z.L.; validation, Z.Z. and F.F.; resources, F.F.; data curation, Z.Z.; writing—original draft preparation, Z.Z.; writing—review and editing, Z.Z. and F.F.; supervision, F.F.; funding acquisition, F.F. and G.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Subsidies for National Key Research and Development Program (Guizhou Science and Technology Cooperation Platform Talents [2018] No. 5261), the First-class Discipline Construction Project of Guizhou Province (GNYL [2017]007) and the Postgraduate Research Project of Guizhou Province (Qianjiaohe YJSCXJH [2019]021).

Data Availability Statement

The transcriptome data in this study are available at the Sequence Read Archive (SRA) database of NCBI (http://www.ncbi.nlm.nih.gov/sra (accessed on 4 April 2023)) under accession number PRJNA951280.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Basic information and annotation analysis of full-length transcripts. (A) ORF length distribution. (B) Comment result Venn diagram. (C) GO enrichment analysis of full-length transcripts for cellular component, biological process, and molecular function. (D) KOG annotation analysis of full-length transcripts.
Figure 1. Basic information and annotation analysis of full-length transcripts. (A) ORF length distribution. (B) Comment result Venn diagram. (C) GO enrichment analysis of full-length transcripts for cellular component, biological process, and molecular function. (D) KOG annotation analysis of full-length transcripts.
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Figure 2. Statistics of the DEGs. (A) Number statistics of the DEGs. There were 408 DEGs, of which 203 were significantly up-regulated and 205 were significantly down-regulated in FGW. (B) Differential multiple distribution of the DEGs.
Figure 2. Statistics of the DEGs. (A) Number statistics of the DEGs. There were 408 DEGs, of which 203 were significantly up-regulated and 205 were significantly down-regulated in FGW. (B) Differential multiple distribution of the DEGs.
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Figure 3. Enrichment analysis of DEGs. (A) GO enrichment analysis of DEGs for cellular component, biological process, and molecular function. (B) Functional classification of DEGs based on KEGG pathways. X axis represents number of DEGs, whereas Y axis indicates second KEGG pathway terms. (C) KEGG enrichment of DEGs. The color and size of dots represent the q-value and the gene number, respectively.
Figure 3. Enrichment analysis of DEGs. (A) GO enrichment analysis of DEGs for cellular component, biological process, and molecular function. (B) Functional classification of DEGs based on KEGG pathways. X axis represents number of DEGs, whereas Y axis indicates second KEGG pathway terms. (C) KEGG enrichment of DEGs. The color and size of dots represent the q-value and the gene number, respectively.
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Figure 4. Characterization of differentially expressed genes related to cell wall organization or biogenesis. (A) Expression analysis of 16 secondary growth-related DEGs in FGW and SGW. The expression levels of genes are indicated according to the value of log10(FPKM+1), as shown in the color bar. (B) Expressed genes involved in lignin biosynthesis pathway of P. massoniana. Key genes or enzymes were displayed at nodes. According to the value of log10(FPKM+1), the expression of node matching and DEGs is marked at the side of each node, as shown in the color bar. The left and right columns of expression pattern represent FGW and SGW, respectively. PAL: phenylalanine ammonia-lyase; C4H: cinnamate 4-hydroxylase; 4CL: 4-coumarate: CoA ligase; CCR: cinnamoyl-CoA reductase; CAD: cinnamyl alcohol dehydrogenase; PER: peroxidase; HCT: hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase; C3′H: p-coumaroyl shikimate 3′-hydroxylase; CCoAOMT: caffeoyl-CoA O-methyl transferase; F5H: ferulic acid/coniferaldehyde/coniferyl alcohol 5-hydroxylase; and COMT: caffeic acid O-methyltransferase. (C) Endogenous hormone biosynthesis and signal transduction of abscisic acid and ethylene. The red box indicates that the gene is significantly up-regulated. The yellow box indicates that gene expression is insignificantly induced. (D) RT-qPCR validation of DEGs.
Figure 4. Characterization of differentially expressed genes related to cell wall organization or biogenesis. (A) Expression analysis of 16 secondary growth-related DEGs in FGW and SGW. The expression levels of genes are indicated according to the value of log10(FPKM+1), as shown in the color bar. (B) Expressed genes involved in lignin biosynthesis pathway of P. massoniana. Key genes or enzymes were displayed at nodes. According to the value of log10(FPKM+1), the expression of node matching and DEGs is marked at the side of each node, as shown in the color bar. The left and right columns of expression pattern represent FGW and SGW, respectively. PAL: phenylalanine ammonia-lyase; C4H: cinnamate 4-hydroxylase; 4CL: 4-coumarate: CoA ligase; CCR: cinnamoyl-CoA reductase; CAD: cinnamyl alcohol dehydrogenase; PER: peroxidase; HCT: hydroxycinnamoyl-CoA: shikimate hydroxycinnamoyl transferase; C3′H: p-coumaroyl shikimate 3′-hydroxylase; CCoAOMT: caffeoyl-CoA O-methyl transferase; F5H: ferulic acid/coniferaldehyde/coniferyl alcohol 5-hydroxylase; and COMT: caffeic acid O-methyltransferase. (C) Endogenous hormone biosynthesis and signal transduction of abscisic acid and ethylene. The red box indicates that the gene is significantly up-regulated. The yellow box indicates that gene expression is insignificantly induced. (D) RT-qPCR validation of DEGs.
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Zhou, Z.; Ding, G.; Li, Z.; Fan, F. Full-Length Transcriptome Analysis of the Secondary-Growth-Related Genes of Pinus massoniana Lamb. with Different Diameter Growth Rates. Forests 2023, 14, 811. https://doi.org/10.3390/f14040811

AMA Style

Zhou Z, Ding G, Li Z, Fan F. Full-Length Transcriptome Analysis of the Secondary-Growth-Related Genes of Pinus massoniana Lamb. with Different Diameter Growth Rates. Forests. 2023; 14(4):811. https://doi.org/10.3390/f14040811

Chicago/Turabian Style

Zhou, Zijing, Guijie Ding, Zhengchun Li, and Fuhua Fan. 2023. "Full-Length Transcriptome Analysis of the Secondary-Growth-Related Genes of Pinus massoniana Lamb. with Different Diameter Growth Rates" Forests 14, no. 4: 811. https://doi.org/10.3390/f14040811

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