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Article

Transcriptome Analysis of Populus Overexpression in SVL Transcription Factor

by
Dongli Wang
1,2,†,
Renwu Cheng
3,†,
Yunshan Liu
2,
Shengkun Wang
2,
Zhende Yang
1,* and
Sen Meng
2
1
Guangxi Colleges and Universities Key Laboratory for Forestry Science and Engineering, College of Forestry, Guangxi University, Nanning 530004, China
2
State Key Laboratory of Tree Genetics and Breeding, Research Institute of Tropical Forestry, Chinese Academy of Forestry, Guangzhou 510520, China
3
Guangzhou Institute of Forestry and Landscape Architecture, Guangzhou 510520, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to the work.
Forests 2023, 14(9), 1692; https://doi.org/10.3390/f14091692
Submission received: 17 July 2023 / Revised: 14 August 2023 / Accepted: 15 August 2023 / Published: 22 August 2023
(This article belongs to the Section Genetics and Molecular Biology)
Browse Figures
Versions Notes

Abstract

:
Flowering is an essential part of the productive process, and flowering time is determined by endogenous genetic components and many ambient factors. SHORT VEGETATIVE PHASE (SVP), a MADS-box transcription factor, regulates floral transition by repressing floral integrator genes and is involved in ABA-mediated drought stress. In this study, we transformed the poplar (Populus) clone “84K” with the SVP-Like gene, while stable overexpression transgenic lines were obtained. Transcriptome analysis of the leaves of the transgenic lines and WT (Wide Type) poplars revealed that a total of 477 genes showed significantly altered expression, overexpressing SVL genes, including 342 upregulated and 135 downregulated genes. Ten subclusters in DEGs were analyzed, and KEGG terms of the largest subcluster were associated with two key pathways: hormone-related genes and glutathione metabolism. Meanwhile, many transcriptional factors were involved. Our results are helpful for in-depth analysis of the MADS transcriptional factor in poplars. This work provides the basis for studying woody plant growth, and development and molecular mechanisms responded to environmental stresses.

1. Introduction

Stem/progenitor cells that sustain the post-embryonic growth of all plant organs are encompassed by meristems [1]. In such meristems, the central zone contains stem cells, where cells differentiate into organs at the periphery of the meristem primordia [2]. The primordia develop into leaves during the vegetative phase, and a floral transition is established during the generative phase, when the shoot apical meristem becomes an inflorescence meristem (IM) [2]. In Arabidopsis, floral meristems were developed from the IM in a spiral manner, and a number of floral organs were produced precisely in a similar way.
Photoperiod and vernalization are important environmental cues for flowering in many annual and perennial plants, including horticultural, woody, and crop plants. FLOWERING LOCUS T (FT) is closely associated with flowering on long days, and the TWIN SISTER OF FT (TSF) probably acts in a similar way to FT. The FT-FLOWERING LOCUS D (FD) complex activates the expression of flowering genes, shown as a network in the shoot meristem. Compared with wild-type Arabidopsis and in response to long days, transcription of SUPPRESSOR OF OVEREXPRESSION OF CONSTANS 1 (SOC1) is delayed in ft tsf double mutants or fd single mutant. When overexpressing SOC1 is derived from the 35S promoter, Arabidopsis displayed early flowering under both long-day and short-day [3,4,5]. Meanwhile, many other MADS transcription factors, such as SHORT VEGETATIVE PHASE (SVP), are also involved in floral transitions.
SVP, first cloned by transposon tagging and identified as a flowering repressor in Arabidopsis thaliana, is a key and central regulator of the flowering regulatory network [6,7,8]. Further functional analyses have shown that SVP serves as a negative regulator to flower and is overcome by exposure to long days. Moreover, it also plays a similar role in the face of low temperatures, where it forms a heterodimer with another potent repressor, FLOWERING LOCUS C (FLC), which strongly represses flowering [7]. Repression of SVP activity allows the plant to flower under high temperatures, where it interacts with LOCUS M (FLM)-β, the β form of the product of FLM transcript alternative splicing [9]. Increased gibberellin (GA) at the shoot apex by environmental cues affects flowering, as mutants of SVP plants increase GA levels by inducing the expression of GA20-OXIDASE 2 (GA20ox2), an important enzyme to limit active GA biosynthesis [10,11,12]. SVP directly activates or represses genes whose promoters include specific DNA elements called CArG-boxes, which correspond to a 10-nucleotide sequence, CC(A/T)6GG, as determined by ChIP–chip and ChIP–seq analysis [7,13].
ChIP–seq analyses, combined with tiling array expression analysis, induction experiments, and qRT-PCR, were performed to compare the DNA binding profile of SVP between vegetative and reproductive development on a genome-wide scale and to identify biologically relevant binding sites. Approximately 3000 genes were found to bind the specific site of the SVP promoter in the herbaceous plant Arabidopsis. Some genes were regulated by SVP at two stages, whereas others were specific to one of the stages [2]. There were researchers who conducted a multiple-year field study in order to explore whether SVL affected flowering in poplars, and overexpression was associated with a delay in the onset of flowering, using three different poplar genotypes on a long-time scale, and a reduction in floral abundance once flowering began [14]. Three MADS-box genes of the SVP clade upregulated in wheat, vrn1 ful2 double mutants, were identified by comparing the transcriptomes of tillers, which were transformed from spikelets and normal spikes, and a critical network for spikelet and floral development was established [15,16].
However, systematic studies on the potential interaction genes of SVL genes in woody plant are very lacking at the transcriptional and genomic levels. In this study, we obtained the target transcription factor in poplars and obtained transgenic lines when overexpressed by constructing an expression vector. We sequenced transgenic and wild-type seedlings by transcriptome sequencing technology, expecting to obtain the potential physiological mechanism or other key functions of the target gene and lay a good foundation for future research.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

The transcriptomes of 3 independent wild-type seedlings (Populus alba × Populus tremula glandulosa (84K)) with the same growth conditions and the same number of independent and consistent transgenic seedlings were compared. Both wild-type and transgenic seedlings were grown on 1/2 MS medium with 0.05 mg/L IBA and 0.05 mg/L NAA under 16 h light/8 h dark conditions at 25 °C and then were transplanted into soil and grown naturally for 4 to 5 weeks.

2.2. Vector Construction and Production of Transgenic Plants

The full-length cDNAs encoding PagSVL (Potri.007G010800.2) were amplified using PCR from the cDNA of the hybrid poplar (Populus alba × Populus tremula var. glandulosa, 84K). For PagSVL-3 × FLAG chimeric gene construction, a 3 × FLAG sequence was added to PagSVL cDNA. The chimeric gene was inserted downstream of the CaMV35S promoter into the pBWA(V)HS vector (BioRun, Wuhan, China). The construct used in this study was verified using DNA sequencing at Rui Biotech (Beijing, China). The promoters and primers used for amplification are listed in Table S1.
The poplar transformation protocol followed that described in Meng et al. [17]. The overexpression vector was introduced into Agrobacterium tumefaciens (EHA105), after which the transgenic bacteria were transferred to 84K poplar plants using the leaf disc method. After one night culture for Agrobacterium, and when its OD600 reached approximately 0.7, Agrobacterium was centrifuged and resuspended in 1/2 MS liquid medium containing 1.8 g/L galactose, 250 mg/L 2-(N-morpholino) ethanesulfonic acid (MES), and 50 mg/L acetosyringone (pH = 5.0). Leaf discs of aseptic 84K plantlets were cut into small pieces with a sterile razor blade, syringed with an Agrobacterium suspension for approximately 20 min, and then co-cultured on MS medium (pH = 5.8, 10 μM 1-naphthaleneacetic acid, 5 μM 2-ip, 250 mg/L cefotaxime, 3 mg/L hygromycin, and 0.80% (w/v) agar) for the selection of transformed calli. After 3 weeks, explants were cultured using shoot-selection medium (0.2 μM thidiazuron, 250 mg/L cefotaxime, and 0.80% (w/v) agar) for 2–3 months, during which time they were subcultured every 3–4 weeks. The regenerated shoots were further screened for kanamycin resistance by rooting on 1/2 MS medium supplemented with 0.05 mg/L indolebutyric acid and 0.05 mg/L NAA. The successful overexpression seedlings were identified using DNA sequencing at Rui Biotech (Beijing, China), and the primer sequences used for amplification are listed in Table S1 (Supplementary Data).

2.3. RNA Quantification and Qualification

Leaves of WT and transgenic poplars were harvested for RNA sequencing (RNA-seq) using liquid nitrogen and immediately stored at −80 °C until analysis. Total RNA was extracted from the leaves according to the Qiagen RNAeasy kit manual (Qiagen, Hilden, Germany). The quality of the RNA samples was measured using a NanoDrop ND-1000 and an Agilent 2100 Bioanalyzer after purification and DNA digestion.

2.4. Library Preparation for Transcriptome Sequencing

A NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, Ipswich, MA, USA) was prepared for the libraries. A 3 μg subsample of quantified RNA from each plant was enriched using magnetic beads with oligo (dT) and then broken into fragments. Using mRNA as the template, the first strand of cDNA was synthesized using random hexamer primers and M-MuLV reverse transcriptase (RNaseH). Second-strand cDNA was synthesized using DNA polymerase I and RNase H. Library fragments were purified using the AMPure XP system (Beckman Coulter, Beverly, MA, USA) and eluted with EB buffer for terminal repair. Agarose gel electrophoresis was performed after performing end repair and adding polyA, and library quality was assessed using an Agilent Bioanalyzer 2100 system. Clustering was performed using the TruSeq PE Cluster Kitv3-cBot-HS. The library was sequenced using an Illumina HiSeq 2100 platform.

2.5. Quality Control, Mapping Reads to the Reference Genome, and Annotation

An equivalent nucleotide sequence was transformed from image data obtained from the Illumina platform. The original sequencing data were first filtered to obtain high-quality sequencing data (clean data) to ensure the smooth progress of subsequent analysis. Reads were treated as failed or low-quality reads as follows: (1) without the inserted fragment, (2) with an N of >10% ratio, (3) with a quality value <10, or (4) with a length <50 bp after adapter and quality trimming. The SeqPrep (https://github.com/jstjohn/SeqPrep) and Sickle (https://github.com/najoshi/sickle) (accessed on 15 October 2021) programs were used to control quality.
The sequences were aligned to poplar reference genomes (http://plants.ensembl.org/Populus_trichocarpa/Info/Index, Pop_tri_v3, accessed on 16 July 2023). Multiple alignment statistical models were used to consider the structural features during sequence alignment. Gene and RNA expression levels were normalized using an FPKM indicator, which signified the fragments per kilobase of transcripts per million mapped fragments. The expression levels and differential gene expression were calculated using the standard read mode within the reference gene regions using Cufflink software (Version 2.2.1) [18].

2.6. Quantification of Gene Expression Levels

Reads corresponding to sequence joints from each sample were mapped to transcripts and spliced using Bowtie2 (http://bowtie-bio.sourceforge.net/bowtie2, Version 2.4.1, accessed on 16 July 2023). Standard RESM was used to evaluate the expression abundance and gene expression levels represented by read counts. DESeq2 software (Version 1.10.1) was used to calculate fold change, a p-value was used for hypothesis testing, and a gene with a fold change of >1 (upregulated) or <1 (downregulated); p-value <0.05 was considered to be a differentially expressed gene (DEG) [19,20]. The presentation of differential genes was displayed within a volcano plot using the R language.

2.7. GO Enrichment and KEGG Pathway Enrichment Analyses

The probability of the Gene Ontology (GO) term was calculated using the R package GOsEq to identify biological functions relevant to the DEGs. The function was considered enriched when the corrected p-value was <0.05 [21]. KEGG pathway enrichment was also performed using KOBAS software (Version 2.1.1) with Benjamini–Hochberg (BH) correction applied to the false discovery rate (FDR) parameter to elucidate the main biochemical, metabolic, and signal transduction pathways. The pathway was reported as enriched when FDR ≤ 0.05 [22].

2.8. Phylogenetic Analysis

Protein sequences for the SVP of different species from the NCBI data and previously published articles were aligned, and a phylogenetic tree was developed using MEGA7 (Version 7.0) software [23]. The parameters of the program were as follows: neighbor-joining method with 1000 bootstraps and Poisson correction method with the unit number of amino acid substitutions per site.

3. Results

3.1. Candidate Populus SVL Homologs and Overexpression of SVL

DORMANCY-ASSOCIATED MADS-box (DAM) and SHORT VEGETATIVE PHASE (SVP) genes are implicated in regulating perennial winter dormancy. We acquired a MADS TF named SVL (SVP-Like) from the 84K poplar (Populus alba × P. glandulosa). A phylogenetic tree showed that the hybrid aspen SVL was more homologous to the Arabidopsis floral repressor SVP, kiwifruit, and apple SVP than to the other MADS-box or apple DAM genes (Figure 1a and Table S2). The SVL overexpression vector was transformed at 84K, and a transgenic event was obtained (Figure 1b,c).

3.2. Illumina Sequencing and Alignment to the Reference Genome

Six cDNA libraries derived from the OE1–OE3 (transgenic) and WT1–WT3 (wild-type) lines were analyzed on an Illumina platform. A total of 46.6–55.0 million raw reads were generated whose Q20% or Q30% score was high enough to ensure accuracy, and GC content was reasonable from the samples; after removing reads of unreliable quality, 46.1–54.4 million reads were processed for analysis (Table 1). Finally, the clean reads were mapped to the reference genome sequences of Populus trichocarpa. Of the total reads, more than 70% aligned with the reference genomes because of the general dissimilarity of Populus.
Cufflinks were used to assemble the mapped reads and compare the assembled reads with the reference genome. A total of 91,642 transcripts ranged from 200 to >1800 bp. Analysis of the dataset (Figure 2) showed that 39,553 expressed transcripts in the >1800 bp range accounted for 43.1% of the expressed genes, which was the maximum. The number of expressed genes ranged from 201 to 400 bp, accounting for only 5.6%. The percentage of transcripts of <1000 bp was similar to that of transcripts ranging from 1000 to 1800 bp, accounting for approximately 25%.
The relationships among expressed genes between the six samples, including three wild-type poplars (WT1, WT2, and WT3) and three poplars overexpressing SVL genes (OE1, OE2, and OE3), are illustrated in Figure 3, which shows the distribution of expressed genes. The two plant types shared 24,049 of the 25,412 total transcripts expressed in both the WT and OE plants. We found that the number of genes expressed was similar between the two sample types and biological replicates.

3.3. Analysis of DEGs between Transgenic and Non-Transgenic Poplars

The gene expression profiles of the two types of poplar were analyzed and compared in order to identify DEGs. The fold-change values between samples were calculated according to the TPM. Genes with a p-value <0.05, calculated with DESeq2, were regarded as DEGs. A total of 477 genes showed significantly altered expression in poplar-overexpressing SVL genes. Most (342) showed upregulated expression; the remaining 135 genes were downregulated (Figure 4; Table S3).
DEGs from the six samples were clustered to fully explore the relationships among DEGs; 10 major clusters with distinct transcriptional dynamics were identified Figure 4 and Figure S1). Subcluster 4 consisted of the largest number (152 genes) of up- or downregulated genes. KEGG analysis revealed that hormone-related genes and glutathione metabolism were enriched in this cluster and GO analysis revealed that oxidoreductase activity was enriched (Figure 5 and Figure 6; Figure S2 and Table S4).
These results suggest that the overexpression of exogenous genes results in remarkable changes in the transcriptome of transgenic poplars, primarily by increasing the expression of hundreds of genes.

3.4. Identification of Transcription Factors by Transcriptome Analysis

Proteins containing a DNA-binding domain that recognizes a specific DNA sequence are usually defined as transcription factors (TFs), which regulate the first step of gene expression. Early studies on TFs revealed their typical structure, containing DNA-binding domains (DBDs) and critical activation domains (ADs), which were required for transcription [24]. Transcriptional regulation plays a pivotal role in controlling gene expression in plants. To better understand the role of SVL transcription factors, we screened the DEGs to identify potential transcription factors. Finally, 34 transcriptional factors were identified, except for the overexpressed target gene, Potri.007G010800 (Table 2). Four WRKY transcription factors, which act as differentially regulated genes, play important roles in development, senescence, defense responses, and stress tolerance. WRKY41 is involved in plant development, such as seed dormancy, and defends plants against Pseudomonas syringae pv. tabaci 6605 [25]. WRKY6 is associated with plant senescence processes as well as plant defense responses [26]. WRKY57 confers drought tolerance in rice and Arabidopsis and enhances the resistance of Arabidopsis against Botrytis cinerea infection [27]. WRKY53 plays a central role in the stress response and during the early stages of leaf senescence [28,29]. In addition to the WRKY transcription factors, the expression levels of NAC, MYB, ERF, bZIP, and GRAS plant-specific transcription factors were also altered. For example, Arabidopsis NAC domain-containing proteins 56 and 55.

3.5. Validation of RNA-Seq Results by qRT–RCR

Quantitative real-time (qRT)–PCR was performed on nine randomly selected genes with increased or decreased transcript abundances in transgenic poplars to confirm the accuracy and reproducibility of the Illumina RNA-Seq results. The correlation between the RNA-Seq and qRT–PCR data was evaluated using log2-fold change measurements, defined as ΔΔCT (comparative threshold cycle). Of the nine genes examined, the qRT–PCR expression data showed similar trends to the RNA-Seq data (Figure 7). The fold changes in the expressions of the nine genes were generally in agreement with the RNA-Seq data. Specifically, the fold changes in the expressions of seven genes (WRKY53-Like, TCP12-Like, MYB transcription factor, Hombox12-Like, WRKY41-Like, WRKY6-Like, and bZIP transcription factor) were higher than those obtained with RNA-Seq. The remaining two genes (HMP1-Like and TGA1.1-Like) showed slightly lower expression levels than the RNA-Seq data (Figure 7).

4. Discussion

Transcription factors regulate complex networks with downstream signaling genes characterized by specific responsive elements to participate in plant development and stress responses. In most eukaryotic plants, the MADS-box family transcription factors, serving as key determinants of gene regulatory networks, always are involved in responses to stress and development in plants [54]. The MADS-domain factor SVP is present in the leaves and SAM during the vegetative phase and serves as a negative regulator of floral transition and an important floral meristem gene. SVP was repressed in the meristem when the plant entered reproductive development, while sufficient SVP transcriptional activity was detectable in the inflorescence apex and the primordia of the coflorescences at the very early flower stage [8,55,56]. In Arabidopsis, SVP regulates ABA catabolism by directly binding to the CArG motifs of CYP707A1/3 and AtBG1 promoters and plays a key role in plant responses to water-limiting assays and long-drought stress [57]. SVP represses plant growth regulator gibberellin (GA) biosynthesis under inductive photoperiods, contributing to delayed flowering [10]. In Populus, SVL, a homolog of Arabidopsis SVP, acts as a negative regulator in bud break by two antagonistic plant hormones, gibberellin and abscisic acid [12]. In yellowhorn, AGAMOUS-LIKE22-regulated ABA biosynthesis and overexpression of yellowhorn AGL22 helped poplars increase resistance to drought stress [58].
Gregis et al. employed ChIP-seq analysis to study SVP binding behavior in Arabidopsis at the genome-wide level, and approximately 3000 genes were identified [2]. In this study, we performed differential gene expression analysis using Illumina HiSeq 2000 paired-end sequencing (RNA-Seq) performed in transgenic poplars. At least 46.6 million raw reads with Q20% or Q30% scores that were sufficiently high to ensure accurate sequence reads were generated. Approximately 75.14% of the sequences mapped to the reference genome sequence of P. trichocarpa. Global analysis of gene expression revealed transcriptome reprogramming in the transgenic poplar (OE1-3) compared with that in non-transgenic WT poplar. A total of 477 genes showed significantly altered expression in poplars overexpressing SVL genes, including 342 upregulated and 135 downregulated genes, indicating that flowering inhibitors play a key role in the insertion/expression of transgenes in poplars. Additionally, 34 transcriptional factors were identified. The RNA-seq data were validated using qRT–PCR analysis of nine genes. The expressions of the nine genes revealed by qRT–PCR analysis (Figure 7) showed that they may be associated with the introduction of exogenous genes and may be involved in different regulatory networks.
The defining features of WRKY transcription factors were several almost nonchanged amino acid sequences at the N-terminus and an atypical zinc-finger structure at the C-terminus, which was called the WRKY domain. Accumulating evidence has revealed that WRKY proteins play diverse roles in response to ambient stresses and plant growth, as well as development, by binding to the W-box cis-elements of target genes [59]. In rice, WRKY53 acted as an important regulator of BR signaling. Phenotypic analyses showed that the leaf angles of the OsWRKY53 overexpression line were enlarged, revealing a novel role for OsWRKY53 in mediating crosstalk between hormones and other signaling pathways [60]. In addition, WRKY53 transcriptionally represses GA biosynthesis genes to regulate male fertility in the anthers, leading to changes in breeding potential when rice is subjected to cold stress [61]. WRKY6 played key roles in plant senescence, pathogen defense, ambient stress, seed oil accumulation, and fatty acid composition [39]. WRKY41 was an important regulator of ABSCISIC ACID INSENSITIVE 3 (ABI3) expression, which played an essential role in seed dormancy [37]. When poplars overexpressed SVL, the expression of the WRKY53-Like, WRKY6-Like, and WRKY41-Like genes in the poplar also increased, consistent with the integration of SVL into plant hormone signaling to mediate senescence, pathogen defense, and abiotic stress.
The TEOSINTE BRANCHED1/CYCLOIDEA/PROLIFERATING CELL FACTOR (TCP) has been characterized as a semiredundant regulator in plant cell elongation and proliferation, stature, germination, flowering time, pollen development, and leaf morphology [62]. TCPs have also been implicated in several plant hormones’ biosynthesis and signaling pathways, including jasmonic acid (JA), salicylic acid (SA), cytokinin (CK), ABA, auxin, and BR [63,64,65]. AtTCP8 positively responded to early immune signaling, and when combined with mutations in AtTCP14 and AtTCP15, additional layers of defense signaling in Arabidopsis. The target genes of TCP8, along with other TCP members by pathogen effectors, may be modulators of BR and other plant hormone signaling pathways [66]. TCP12 and TCP18, renamed as BRC1 and BRC2 based on their similarity to teosinte branched1 (tb1) from maize, were the only Arabidopsis TCP genes that retained a respective role in branching and axillary bud development [67]. In poplars, the expression of TCP12-Like genes increased when SVL was overexpressed, implying that SVL may play a role in axillary bud development. The MYB, bZIP, Homebox12-Like, and TGA1.1-Like transcription factors were also upregulated.
Meanwhile, PME35-Like (PECTIN METHYLESTERASE 35), which encoded a pectin methylesterase, was significantly upregulated in our transcriptome. The stem of the loss-of-function mutant of Arabidopsis pme35 exhibited a pendant phenotype and an increased deformation rate [68]. In plants, pectin methylesterases are involved in vegetative as well as reproductive processes, including wood, pollen formation, and plant–pathogen interactions [69]. Dodder is a stem parasite with haustoria which is an important tool to extract necessary nutrients and water when it is attached to its host. Cuscuta haustoria showed the phenotype of reducing pectin digestion and lacking searching hypha when growing on CcLBD25 RNAi tomatoes, indicating that there was a correlation between pectin digestion and parasitism [70]. Our study provides preliminary insights into genes affected by SVL by means of transcriptome analysis. The specific functions of these genes mediated by SVL require further experimental validation in future studies.

5. Conclusions

In the present study, we cloned the SHORT VEGETATIVE PHASE (SVP)-Like gene in the poplar, an MADS-box transcription factor and a repressor for flowering, and transformed the poplar clone “84K” with the SVP-Like gene, and obtained stable overexpression transgenic lines. Transcriptome analysis of the leaves of the transgenic and WT lines revealed that there were 342 upregulated and 135 downregulated genes. Ten subclusters in DEGs were analyzed, and the KEGG terms of the largest subcluster were associated with two key pathways: hormone-related genes and glutathione metabolism. Meanwhile, many transcriptional factors were involved. Overall, our results contributed to a deeper understanding of how candidate genes were regulated by the SVP-Like gene using overexpression and transcriptome technology and provided target genes for plant senescence, pathogen defense, and abiotic stress in the future.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f14091692/s1, Table S1: Primer sequences for gene cloning, vector construction validation, and RT-qPCR. Table S2: Protein sequences of Arabidopsis, kiwifruit, apple, and Populus SVP, MADS-box, or DAM genes. Table S3: List of DEGs in our transcriptome. Table S4: 10 subclusters of DEGs. Figure S1: Normalized expression of DEGs 10 subclusters. Figure S2: GO enrichment analysis (subcluster 4).

Author Contributions

D.W., S.M. and Z.Y. conceived and designed the study. D.W. and R.C. wrote the manuscript. D.W., Y.L. and S.W. conducted and assisted with the experiments. All authors have read and agreed to the published version of the manuscript.

Funding

This research was sponsored by grants from the Forestry Science and Technology Innovation Project of Guangdong Province (2022KJCX023), Basic and Applied Research Program of Guangzhou, Guangdong (SL2022A04J00577), and Guangzhou Basic and Applied Basic Research Foundation (202201011313).

Data Availability Statement

Data will be made available on request.

Acknowledgments

We thank Xihang Ai for his help in reviewing and correcting the references.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Identification of candidate Populus SVL homologs and schematic diagram of overexpression construct vector. (a) Phylogenetic analysis of Populus SVL. The phylogenetic tree of Populus SVL (Potri.007G010800) with genes encoding MADS box proteins from Populus, including other MADS box proteins similar to SVP (Potri.002G105600, Potri.005G155700, Potri.005G155300, Potri.017G044200), Arabidopsis SVP, and AGL24, and kiwifruit and apple SVP-clade genes; Pt, Populus trichocarpa; At, Arabidopsis thaliana; Ad, Actinidia deliciosa; Md, Malus domestica. (b) Schematic diagram of the SVL overexpression construct. p35S, cauliflower mosaic virus 35S promoter; flag, Flag-tag Protein; Tnos, nos terminal; TR T-border. (c) Phenotype of wide-type and SVL overexpression (transgenic) of the poplar.
Figure 1. Identification of candidate Populus SVL homologs and schematic diagram of overexpression construct vector. (a) Phylogenetic analysis of Populus SVL. The phylogenetic tree of Populus SVL (Potri.007G010800) with genes encoding MADS box proteins from Populus, including other MADS box proteins similar to SVP (Potri.002G105600, Potri.005G155700, Potri.005G155300, Potri.017G044200), Arabidopsis SVP, and AGL24, and kiwifruit and apple SVP-clade genes; Pt, Populus trichocarpa; At, Arabidopsis thaliana; Ad, Actinidia deliciosa; Md, Malus domestica. (b) Schematic diagram of the SVL overexpression construct. p35S, cauliflower mosaic virus 35S promoter; flag, Flag-tag Protein; Tnos, nos terminal; TR T-border. (c) Phenotype of wide-type and SVL overexpression (transgenic) of the poplar.
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Figure 2. Distribution of gene sequences detected in Populus alba × P. glandulosa cv “84K”.
Figure 2. Distribution of gene sequences detected in Populus alba × P. glandulosa cv “84K”.
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Figure 3. Identification of transcript numbers. (a) Venn diagram of transcripts between wild-type plants and overexpressing SVL plants; (b,c) Venn diagrams of transcripts in wild-type and overexpressing SVL plants.
Figure 3. Identification of transcript numbers. (a) Venn diagram of transcripts between wild-type plants and overexpressing SVL plants; (b,c) Venn diagrams of transcripts in wild-type and overexpressing SVL plants.
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Figure 4. Volcano plots for the DEGs.
Figure 4. Volcano plots for the DEGs.
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Figure 5. Cluster analysis of DEGs collected in six samples.
Figure 5. Cluster analysis of DEGs collected in six samples.
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Figure 6. KEGG pathway of subcluster 4.
Figure 6. KEGG pathway of subcluster 4.
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Figure 7. qRT-PCR validation of differentially expressed genes of transgenic poplar.
Figure 7. qRT-PCR validation of differentially expressed genes of transgenic poplar.
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Table 1. Comparative statistics of sequencing data output and reference genomes.
Table 1. Comparative statistics of sequencing data output and reference genomes.
Line
WT1WT2WT3OE1OE2OE3
Total reads54,972,75046,585,19054,662,37449,276,57247,526,72047,288,042
Remained reads54,427,83846,086,36054,135,99248,817,67847,114,48446,871,232
Aligned reads40,659,657
(74.7%)		34,628,473
(75.14%)		40,477,343
(74.77%)		36,452,608
(74.67%)		34,956,172
(74.19%)		34,884,122
(74.43%)
GC content (%)44.9144.9844.6944.9144.7344.86
Q20 (%)97.7797.7897.7297.8297.8597.87
Q30 (%)93.7293.7993.693.8893.9693.98
Table 2. List of differentially regulated transcriptional factors in the DEGs.
Table 2. List of differentially regulated transcriptional factors in the DEGs.
PopulusArabidopsisGene NameGene DescriptionCArG SitesReferences
Potri.001G404400AT3G15510NAC regulated seed morphology 1Regulates the development of integuments and degeneration of embryogenesis.
Establishes a top-down signal that drives meristem asymmetric cell division of phloem sieve elements.		4Hyoujin Kim et al.
2020 [30];
Kunieda et al. 2008 [31].
Potri.001G409500AT5G48150Phytochrome a signal transduction 1Specifically involved in phytochrome A signal transduction.11Patricia Torres-Galea et al. 2013 [32].
Potri.001G415200AT5G48150Phytochrome a signal transduction 1Specifically involved in phytochrome A signal transduction.9Patricia Torres-Galea et al. 2013 [32].
Potri.002G002200AT1G43000Platz transcription factor 0
Potri.002G018400AT2G17770bZIP transcription factorInteracts with FD and FT.51Maida Romera-Brancha et al. 2020 [33].
Potri.002G119300AT5G04340ZAT6, C2H2 zinc finger transcription factorIncreases salt stress tolerance by decreasing lipid peroxidation, increasing the content of abscisic acid and GA8, and enhancing antioxidant enzyme activities.
Helps Arabidopsis positively mediate heavy metal Cd stress.		1Wei Tang et al. 2018 [34];
Jian Chen et al. 2016 [35].
Potri.003G065400AT3G13840GRAS transcription factor 9
Potri.003G080600AT4G17490ERF subfamily B-3 of ERF/AP2 transcription factorA central activator to inhibit leaf growth and induce stress tolerance genes.5Dubois M et al. 2013 [36].
Potri.003G138600AT4G11070WRKY transcription factor 41Involved in primary seed dormancy and thermoinhibition.
Key regulator in cross talk of SA and JA pathways.		2Zhong Jie Ding et al. 2014 [37];
Kuniaki Higashi et al. 2008 [25].
Potri.004G007500AT1G62300WRKY transcription factor 6Serves a function in plant senescence, pathogen defense, abiotic stress, and accumulation of FAs.5Ge Song et al. 2020 [38].
Potri.004G203400AT1G08320bZIP transcription factor (TGACG motif binding protein 9)Positive regulator of autophagy.
In tga9 tga10 Arabidopsis mutants, adaxial and abaxial anther lobe development is differentially affected.		2Ping Wang et al. 2020 [39];
Jhadeswar Murmu et al. 2010 [40].
Potri.005G082000AT5G65210bZIP transcription factor (TGACG motif binding protein 1)An early N-responsive TF, perturbs the maximum rates of N-dose transcriptomic responses (V max), Km, as well as the rate of N-dose-responsive plant growth.3Joseph Swift et al. 2020 [41].
Potri.005G195000AT5G50080Ethylene response factor 110Putative novel ethylene signaling component.6Li H et al. 2009 [42].
Potri.005G257200AT2G45430AT hook motif nuclear localized protein 22Regulates flowering time through modifying FLOWERING LOCUS T (FT) chromatin.2Ju Yun et al. 2012 [43].
Potri.007G010800AT2G22540MADS-box transcription factorFloral repressor that functions within the thermosensory pathway.
Potri.007G085700AT5G65210bZIP transcription factor (TGACG motif binding protein 1)An early N-responsive TF, perturbs the maximum rates of N-dose transcriptomic responses (V max), Km, as well as the rate of N-dose-responsive plant growth.8Joseph Swift et al. 2020 [41].
Potri.008G094000AT1G69310WRKY DNA-binding protein 57Confers drought tolerance and response to Botrytis cinerea infection.6Yanjuan Jiang et al. 2016 [27];
Yanjuan Jiang and Diqiu Yu 2016 [44].
Potri.008G117100AT1G25560RAV transcription factor that contains AP2 and B3 binding domainsOverexpression causes late flowering and repression of expression of FT.5Hongmiao Hu et al. 2021 [45].
Potri.008G122100AT1G25340MYB116Enhanced drought tolerance, increased MeJA content, and decreased H2O2 level under drought stress.2Yuanyuan Zhou et al. 2019 [46].
Potri.008G142700AT1G31050bHLH transcription factor; Pericycle factor type A1Confers competence for auxin-induced cell division.4Ye Zhang et al. 2021 [47].
Potri.009G101900AT4G34410AP2 transcription factor; Redox responsive transcription factor 1Involved in eATP-regulated seedling growth. Exogenous adenosine triphosphate inhibits green seedling root growth and induces hypocotyl bending of etiolated seedlings.3Ruojia Zhu et al. 2020 [48].
Potri.009G164300AT1G08320bZIP transcription factor (TGACG motif binding protein 9)Positive regulator of autophagy.
In maize, mutation of the TGA9 homolog LIGULELESS2 causes defects in the formation of the blade–sheath boundary in leaves and delayed flowering.		3Ping Wang et al. 2020 [39];
Jhadeswar Murmu et al. 2010 [40].
Potri.011G123300AT3G15500NAC domain containing protein 55Particates in pathogen response pathway induced by chitin. Appears to be dependent on ANAC055.2Richard Hickman
et al. 2013 [49].
Potri.011G131100AT1G50600Scarecrow-like 5 7
Potri.012G023700AT2G46680Arabidopsis thaliana homeobox 7Promotes leaf development, chlorophyll levels, and photosynthesis; reduces stomatal and delays senescence processes.3Delfina A Ré et al. 2014 [50].
Potri.012G134100AT5G51990Dehydration responsive element binding protein 1DImproved drought tolerance.4Satish K Guttikonda
et al. 2014 [51].
Potri.014G007100AT2G22850Basic leucine zipper 6 5
Potri.014G096200AT4G23810WRKY53WRKY53 and histone deacetylase HDA9 are antagonists in response to plant stress.
Node of multilayer regulation in the network of senescence.		8Yu Zheng et al. 2020 [29].
Ulrike Zentgraf and Jasmin Doll 2019 [28].
Potri.014G103000AT3G61890Arabidopsis thaliana homeobox 12Positive regulator of endoreduplication and cell growth during leaf development.
Negatively regulates inflorescence stem growth by decreasing gibberellin 20-oxidase gene expression.		6Yoon-Sun Hur et al. 2015 [52];
Ora Son et al. 2010 [53].
Potri.015G050500AT1G68800TCP domain protein 12Arrests axillary bud development and prevents axillary bud outgrowth.6
Potri.015G136400AT5G51990Dehydration responsive element binding protein 1DImproved drought tolerance.4Satish K Guttikonda
et al. 2014 [51].
Potri.016G047900AT5G06800Similar to MYB transcription factor 6
Potri.016G126100AT2G38340Dehydration responsive element binding protein 19Involved in response to drought.3
Potri.017G147000AT1G01490Heavy metal transport/detoxification superfamily protein. 2
Potri.T127400AT2G04890SCARECROW-Like 21 0
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Wang, D.; Cheng, R.; Liu, Y.; Wang, S.; Yang, Z.; Meng, S. Transcriptome Analysis of Populus Overexpression in SVL Transcription Factor. Forests 2023, 14, 1692. https://doi.org/10.3390/f14091692

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Wang D, Cheng R, Liu Y, Wang S, Yang Z, Meng S. Transcriptome Analysis of Populus Overexpression in SVL Transcription Factor. Forests. 2023; 14(9):1692. https://doi.org/10.3390/f14091692

Chicago/Turabian Style

Wang, Dongli, Renwu Cheng, Yunshan Liu, Shengkun Wang, Zhende Yang, and Sen Meng. 2023. "Transcriptome Analysis of Populus Overexpression in SVL Transcription Factor" Forests 14, no. 9: 1692. https://doi.org/10.3390/f14091692

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