Characterization of genes associated with TGA7 during the floral transition

Background The TGACG-binding (TGA) family has 10 members that play vital roles in Arabidopsis thaliana defense responses and development. However, their involvement in controlling flowering time remains largely unknown and requires further investigation. Results To study the role of TGA7 during floral transition, we first investigated the tga7 mutant, which displayed a delayed-flowering phenotype under both long-day and short-day conditions. We then performed a flowering genetic pathway analysis and found that both autonomous and thermosensory pathways may affect TGA7 expression. Furthermore, to reveal the differential gene expression profiles between wild-type (WT) and tga7, cDNA libraries were generated for WT and tga7 mutant seedlings at 9 days after germination. For each library, deep-sequencing produced approximately 6.67 Gb of high-quality sequences, with the majority (84.55 %) of mRNAs being between 500 and 3,000 nt. In total, 325 differentially expressed genes were identified between WT and tga7 mutant seedlings. Among them, four genes were associated with flowering time control. The differential expression of these four flowering-related genes was further validated by qRT-PCR. Conclusions Among these four differentially expressed genes associated with flowering time control, FLC and MAF5 may be mainly responsible for the delayed-flowering phenotype in tga7, as TGA7 expression was regulated by autonomous pathway genes. These results provide a framework for further studying the role of TGA7 in promoting flowering. Supplementary Information The online version contains supplementary material available at 10.1186/s12870-021-03144-w.

Background TGACG-binding (TGA) transcription factors (TFs) belong to the bZIP TF family. There are 10 members in the TGA family, and they play essential roles in Arabidopsis thaliana defense responses and development [1][2][3]. These TGAs can interact with non-repressor of pathogenesis-related gene 1 (NPR1), which is involved in salicylic acid (SA)-mediated gene expression (similar to PR-1) and disease resistance [4,5]. These TGAs bind to cis-regulatory TGACG elements [6], and this element is present in PR1 promoters, which are required for PR1 gene expression in response to SA and interact with NPR1 [4,[7][8][9]. However, NPR1 cannot bind directly to the PR-1 promoter, but is recruited to the promoter by its physical interaction with TGAs to regulate the expression of PR-1 [4,[6][7][8][9].
The NPR1 protein interacts with 7 of the 10 Arabidopsis TGAs [7,8,10]. These seven TGAs are further classified into three subclades, with clade I containing TGA1 and TGA4; clade 2 containing TGA2, TGA5, and TGA6; and clade III containing TGA3 and TGA7 [11]. In Arabidopsis, only TGA1 and TGA4 interact with NPR1 in SA-induced leaves, whereas the other TGAs constitutively interact with NPR1 [12]. Thus, all seven TGAs are the important components of the plant defense system.
In addition to their involvement in plant defenses, TGAs also act in plant development. For instance, when grown under low-nitrate conditions, tga1/tga4 shows an altered root architecture [13,14]. TGA1 and TGA4 are also expressed around flower organ boundaries and are required for inflorescence architecture, meristem maintenance, and flowering [3].
In this study, we showed that TGA7 plays an important role in flowering time control. The loss of TGA7 function delayed flowering in Arabidopsis. To reveal the molecular mechanisms of TGA7 in flowering time control, the transcriptomic changes between WT and tga7 mutant seedlings at 9 days after germination (DAG) were analyzed by RNA-sEq. A total of 325 differentially expressed genes (DEGs) were identified, and 4 DEGs were associated with flowering time pathways. These results provide insights into the genes potentially related to flowering time control in the tga7 mutant and will be useful for further studies on the molecular mechanisms of TGA7 in floral transition.

Plasmid construction and transgenic plant generation
To construct 35 S:TGA7, the TGA7 coding sequence was amplified and then cloned into the binary vector pCAMBIA1300-35 S. The primers used for plasmid construction are listed in Additional file 1. Transgenic plants were generated through Agrobacterium tumefaciens-mediated transformation using the floral-dipping method. Transformants containing 35 S:TGA7 were selected on MS medium supplemented with hygromycin (30 mg L − 1 ).

Total RNA isolation
The isolation of total RNA was performed using an RNAprep Pure Plant Kit (TIANGEN, Beijing, China) in accordance with the manufacturer's instructions. DNase I was added to the mixture to eliminate genomic and plastid DNA.

mRNA library construction
Total RNA was analyzed using a NanoDrop and Agilent 2100 bioanalyzer (Thermo Fisher Scientific, MA, USA). To purify mRNA, oligo(dT) magnetic beads were used. Then, the mRNA was sheared into small fragments in the fragmentation buffer. The first-strand cDNA was synthesized by reverse transcription using random hexamer primers, and the second-strand cDNA was synthesized by DNA polymerase. Afterwards, adapters were added to the double-stranded cDNA. To amplify the cDNA fragments, PCR was performed, and the resulting PCR products were purified and dissolved in elution buffer. Then, the PCR products were heat-denatured to produce the final library. The sequencing was performed on a BGIseq500 platform (BGI-Shenzhen, China). The transcriptome data sets have been submitted to the NCBI (accession number PRJNA649868).

De novo assembly and functional annotation of sequencing
The transcriptome data were filtered and analyzed in accordance with a previously published protocol with minor modifications [17]. A differential expression analysis was performed, and the significance levels of gene ontology (GO) terms were all determined, using Q value ≤ 0.05.

qRT-PCR
For the expression analysis, 1 µg RNA was used for reverse transcription. The cDNA was synthesized using a FastKing gDNA Dispelling RT SuperMix kit (TIAN-GEN) in accordance with the manufacturer's instructions. qRT-PCR was performed using the UltraSYBR Mixture (with ROX; CWBio, Beijing, China) and the CFX96 real-time PCR detection system (Bio-Rad). The expression levels of detected genes were normalized to TUB2 expression. Error bars denote standard deviations of three biological replicates [18]. The primers used for the expression analysis are listed in Additional file 1.

Regulation of Arabidopsis flowering time by TGA7
To reveal the function of TGA7 in controlling flowering time, we analyzed the TGA7 phenotype using a tga7 mutant that contained a point mutation in the seventh exon (Fig. 1a). The C to T mutation led to the loss of an EcoRV site in the TGA7 gene and resulted in an amino acid change from Ser to Leu in the TGA7 protein ( Fig. 1a, b, Additional file 2). All the tga7 mutant plants had delayed flowering compared with wild-type (WT) seedlings under both LD and SD conditions ( Fig. 1c-e), suggesting that TGA7 promotes flowering independently of the day length conditions. To determine whether the point mutation in the TGA7 gene is truly responsible for the observed phenotype, the mutants were backcrossed with the WT (Col-0). The F 1 seedlings showed a WT phenotype (Additional file 3a, b), and F 2 seedlings showed a segregation ratio of 3:1 (31:12, WT:tga7 phenotypes, χ 2 = 0.19 < χ 2 0.05 = 3.84; P > 0.05). We then analyzed all the 12 F 2 seedlings having the tga7 mutant phenotype. These 12 F 2 seedlings all displayed a homozygous point mutation in the TGA7 gene (Additional file 3c, d). We then transformed the tga7 mutant with a construct containing the coding sequence of TGA7 driven by the 35 S promoter. Two independent tga7 35 S:TGA7 transgenic lines exhibited flowering times comparable to those of WT plants ( Fig. 1 g-i), indicating that TGA7 was responsible for the flowering phenotype of the tga7 mutant and that excess amounts of TGA7 do not further accelerate flowering.
We then examined TGA7 expression in different tissues of WT plants by qRT-PCR and found that the highest TGA7 expression occurred in adult rosette leaves, whereas there was almost no expression of TGA7 in siliques (Fig. 1f).

Autonomous and thermosensory pathways regulate TGA7 expression
Because TGA7 is involved in floral transition, we examined which flowering genetic pathways may be involved in flowering time control. The expression of TGA7 remained steady in the photoperiod pathway mutants (Fig. 2a), and the phenotype of the tga7 mutant was delayed flowering under LD and SD conditions (Fig. 1c-e), suggesting that TGA7 may not be involved in the photoperiod pathway. In addition, there were almost no effects on TGA7 expression after a gibberellin treatment (Fig. 2b). In both WT and FRI-Col plants, a vernalization treatment did not alter TGA7 expression (Fig. 2c). These observations suggest that the gibberellin and vernalization pathways did not influence TGA7. By contrast, in the autonomous pathway mutants fca-2 and fve-4, the TGA7 expression level increased, whereas it decreased in fld-3and flk-1 (Fig. 2d), suggesting that the autonomous pathway may affect TGA7 expression.
The SVP gene plays crucial roles in the thermosensory pathway, and the svp-41 mutant displays a steady flowering phenotype under different temperature conditions [19]. We also analyzed TGA7 expression at different temperatures. The TGA7 expression increased along with the temperature (Fig. 2e). Furthermore, TGA7 expression was steady in WT, svp-41, and 35 S:SVP plants at 16℃, whereas TGA7 expression was higher in 35 S: SVP but lower in svp-41 at 23℃ (Fig. 2f). These findings demonstrate that the thermosensory pathway may also regulate TGA7 expression at ambient temperatures. In addition, tga7 flowered in a temperature-sensitive manner from 16 to 23°C, but also flowered in a partial temperature-insensitive pattern from 23℃ to 27℃ (Fig. 2g). Thus, TGA7 may partially mediate the effect of the thermosensory pathway on flowering time.

Transcriptomes of WT and tga7 mutant seedlings
To understand how TGA7 affects flowering time, we identified genes downstream of TGA7 that might be involved in its role in promoting flowering. The RNA-seq analyses of WT and tga7 mutant seedlings were performed, and mRNAs were extracted, with three biological replicates, from WT and tga7 mutant seedlings at 9 DAG. In total, six RNA-seq libraries were constructed for transcriptome sequencing.
The raw data were qualified and filtered, yielding approximately 6.67 Gb of sequence data per library (Additional file 4). A Pair-wise Pearson's correlation coefficients analysis of three replicates of each sample indicated that the sequencing data were highly   expression is regulated by several pathways. a TGA7 expression in photoperiod-pathway mutants at 9 DAG. b TGA7 expression after a gibberellin (GA) treatment. WT seedlings were grown under SD conditions for 2 weeks and then treated with 100 µM GA 3 or 0.1 % ethanol weekly. Seedlings treated for 3 (W3) and 5 weeks (W5) were collected for further analyses. c TGA7 expression after a vernalization treatment. The seedlings were vernalized at 4°C for 8 weeks. The 9-day-old seedlings were collected for further analyses. d TGA7 expression in autonomouspathway mutants at 9 DAG. e The TGA7 expression level in WT seedlings grown at 16℃, 23℃, and 27℃ under LD conditions until 9 DAG.  (Fig. 3a). To gain an overview of the variations among the sequencing data, a principal components analysis (PCA) was performed, and the values of PC1 and PC2 were 97.58 and 2.21 %, respectively (Fig. 3b). The PCA clearly separated the six RNA-seq libraries into two groups, WT and tga7 mutant. The size distributions of the mRNAs are shown in Fig. 3c. The majority of mRNAs (84.55 %) were between 500 bp and 3,000 bp, and only 1.60 % of the mRNAs were > 5,000 bp.

Identification of DEGs between WT and tga7 mutant seedlings
The reads per kb per million reads values were calculated to determine the DEGs between WT and tga7 mutant seedlings at 9 DAG. In total, 325 DEGs were identified, of which 133 genes were induced and 192 genes were repressed (Fig. 4a). Among the 325 DEGs, AT3G55970, AT5G45570, AT5G44590, AT5G44440, and AT4G12480 were the most up-regulated genes, whereas AT3G01345, AT4G36700, AT3G56980, AT5G28520, and AT4G36700 were the most down-regulated genes. The heatmap in Fig. 4b shows the expression profiles of the DEGs between WT and tga7 mutant seedlings. A GO term enrichment analysis of these DEGs was performed and the top five most represented GO terms in biological process were "photosynthesis, light harvesting in photosystem I", "photosynthesis, light harvesting", "protein-chromophore linkage", "photosynthesis", and "photosynthesis, light harvesting in photosystem II". In molecular function, they were "chlorophyll binding", "protein domain specific binding", "RNA polymerase II regulatory region sequence-specific DNA binding", "hydrolase activity, acting on glycosyl bonds", and "carbohydrate kinase activity". In cellular component, the top five most represented GO terms were "photosystem I", "photosystem II", "plastoglobule", "chloroplast thylakoid membrane", and "chloroplast" (Fig. 4c).  [20][21][22]. Among the 325 DEGs identified between WT and tga7 mutant seedlings (Figs. 4), 4 DEGs were involved in flowering time pathways. The expression levels of FLC, MAF5, and SMZ were upregulated, whereas that of NF-YC2 was downregulated in tga7 mutant seedlings, compared with WT seedlings (Additional file 5).

Validation of the expression levels of flowering timerelated DEGs
To validate the expression of the four flowering timerelated DEGs (FLC, MAF5, SMZ, and NF-YC2) identified by RNA-seq (Additional file 5), three independent biological duplicates of WT and tga7 mutant seedlings collected at 9 DAG were analyzed by qRT-PCR. The expression levels and trends of the four floweringrelated DEGs were consistent with the RNA-seq results (Fig. 5), which indicated that the RNA-seq data are reliable. Fig. 4 Transcriptional profiles of WT and tga7 mutant seedlings at 9 DAG. a The numbers of genes that were up-regulated or down-regulated between WT and tga7 mutant seedlings at 9 DAG. b Expression profiles of the DEGs between WT and tga7 mutant seedlings at 9 DAG shown using a heatmap. c GO term enrichment analysis of the DEGs between WT and tga7 mutant seedlings

Discussion
In the present study, Arabidopsis that had lost TGA7 function showed a delayed-flowering phenotype (Fig. 1). To uncover the role of TGA7 in flowering time control, transcriptomic analyses between WT and tga7 mutant seedlings at the same developmental stage (9 DAG) revealed 325 DEGs, among which NF-YC2, SMZ, MAF5, and FLC were involved in flowering time pathways (Fig. 5; Additional file 5).
NF-Y, a heterotrimeric TF family, consists of three subfamilies, NF-YA, NF-YB, and NF-YC. NF-YB and NF-YC form dimers with a histone-folding domain, whereas NF-YA confers sequence specificity [23,24]. The heterotrimeric NF-Y complex binds to promoters having CCAAT elements and then regulates the expression of target genes [23,24]. Although each member of the NF-Y family in yeast and mammals is encoded by a single gene, they can be spliced into multiple isoforms post-translationally modified [25,26]. In mammals, the NF-Y complex plays important roles in many processes, including endoplasmic reticulum stress, DNA damage, and cell cycle regulation [27][28][29]. However, in plants, every NF-Y is encoded by multiple genes and then forms sub-families [30]. There are 10 NF-YA, 13 NF-YB, and 13 NF-YC genes in the Arabidopsis genome [31]. As with other plant TFs, duplicate members in the NF-Y family also have similar functions in Arabidopsis [30,32]. The NF-Y complex plays crucial roles in plant stress responses, as well as growth and development [26,30,33].
SCHLAFMÜTZE (SMZ), together with its paralog SCHNARCHZAPFEN (SNZ), belongs to the AP2-type TF family that represses flowering. Both SMZ and SNZ are targets of miR172, an important regulator in the ageing pathway [38]. SMZ delays flowering under LD conditions. When expressed in leaves, SMZ represses flowering by directly binding to the FT genomic locus, down-regulating FT expression [38,39]. Thus, the elevated SMZ expression level may at least partially account for the delayed flowering of the tga7 mutant.
Furthermore, the FLC and MAF5 expression levels were increased in the tga7 mutant compared with the WT. FLC, encoding an MADS-box protein, is a critical repressor in the flowering regulatory network [40][41][42]. MAF1-5 are five FLC homologs in Arabidopsis, and FLC and MAF1-5 are MADS-box TFs that repress floral transition [43]. Many flowering regulatory genes in the autonomous pathway promote flowering by directly repressing FLC expression, and the mutants of these genes, including FLD and FLK in the autonomous pathway, result in the delayed-flowering phenotype under both LD and SD conditions [44][45][46].
FLD encodes a histone demethylase in Arabidopsis and is a homolog of the human LSD1 (histone H3K4 demethylase) [47,48]. It represses FLC expression through histone modifications [47][48][49][50]. FLD physically interacts with FPA and FCA, two autonomous pathway genes [50]. The roles of FCA and FPA on regulating FLC expression and floral transition may depend on FLD [50,51]. Moreover, FLD also interacts with HDA5 and HDA6, two histone deacetylases, to regulate FLC expression. FLK contains RNA-binding domains and only exists in plants [52,53]. FLK may repress the FLC expression level by binding FLC RNAs [54,55]. However, how FLD and FLK regulate FLC expression needs further investigation. Here, we found that TGA7 expression decreased in fld-3 and flk-1 mutant lines (Fig. 2d). Because the expression levels of FLC and MAF5, the closest homolog of FLC, increased dramatically in tga7 compared with WT seedlings (Additional file 5, Fig. 5), and because the tga7 mutant displayed a delayed-flowering phenotype under both LD and SD conditions (Fig. 1c, d, e), we propose that FLD and FLK regulate FLC expression through TGA7.

Conclusions
In summary, six cDNA libraries from WT and tga7 mutant Arabidopsis seedlings at 9 DAG were constructed independently for sequencing. Through bioinformatics mining, 325 DEGs were identified, and 4 genes, NF-YC2, SMZ, MAF5, and FLC, were associated with flowering time control. The differential expression levels of these flowering time-related genes were analyzed and validated by qRT-PCR. Among them, FLC and MAF5 may be mainly responsible for the delayed-flowering phenotype in tga7, because TGA7 expression was regulated by autonomous pathway genes. Further studies should elucidate how TGA7 effects FLD and FLK in regulating FLC expression and deepen our knowledge of the autonomous pathway's role in controlling flowering.

Availability of data and materials
The datasets supporting the conclusions of this article are available in the NCBI Short Read Archive with accession number PRJNA649868.

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