Background

Leaves are the main photosynthetic organs of plants and they play an important role in plant growth and biomass accumulation. Leaves develop from the shoot apical meristem and the growth and development of leaves is a dynamic process. The transition from small primordia to mature leaves is regulated by two key processes, namely, cell division and expansion [1, 2].

Leaves are divided into two distinct components, the leaf blade and the petiole, which are structurally and physiologically distinct entities [1]. The leaf blade has a wide and flat layer-like structure, in which the palisade and sponge tissue layers absorb incident light. The petiole functions as a stem that physically supports the leaf [3]. To date, few studies have investigated the differences between the two components of leaves (i.e., leaf blades and petioles) and leaf primordia, and the mechanisms underlying the differentiation of leaf blades and petioles have scarcely been explored. Some studies have demonstrated that the cells of leaf blades and petioles originate from a region of proliferation located between these cells. The AN3 gene plays a key role in maintaining the proliferation of the primordia, and the bop gene plays a role in spatial regulation [4]. The development and characteristics of petioles are affected by several factors, including genetic factors, endogenous hormones, and environmental conditions such as light and temperature [5,23]. To explore the cis-regulatory functions of the DElncRNAs, a co-expression network comprising 93 DEmRNAs and 63 DElncRNAs was constructed in this study. The results demonstrated that with the exception of eight DElncRNA–DEmRNA pairs which exhibited one-to-one interactions, all the other DElncRNA–DEmRNA pairs exhibited one-to-many interactions (Fig. S2).

The target genes of the DElncRNAs were subjected to GO analysis (Table S4, Fig. 4b). The findings revealed that 2298 target genes were enriched in 2394 GO terms, of which “nucleus,” “biological process,” “molecular function,” and “integral component of membrane” were the most enriched terms. The target genes were significantly enriched in 35 GO terms (p < 0.05), consisting of 16 (45.7%), 4 (11.4%), and 15 (42.9%) terms from the biological process, cellular component, and molecular function categories, respectively. The target genes of the DElncRNAs were enriched in “biological process” and “regulation of transcription, DNA-templated” terms under the biological process category; “nucleus,” “integral component of membrane,” and “plasma membrane” terms under the cell component category; and “nucleus function,” “protein binding,” and “ATP binding” terms under the molecular function category.

The results of KEGG analysis demonstrated that 1229 target genes of DElncRNAs were enriched in 127 metabolic pathways (Table S5, Fig. 4c), of which three pathways, namely, “plant–pathogen interaction,” “starch and sucrose metabolism,” and “plant hormone signal transduction,” were the most enriched. These pathways could be involved in hormone and energy regulation during leaf development.

Identification and functional enrichment analysis of DEcircRNAs between ‘leaf’ and ‘pet’

A total of 886 circRNAs were differentially expressed between the ‘leaf’ and ‘pet’ samples, and a total of 7 DEcircRNAs were identified using the screening criteria |log2 (fold-change)|> 1 and p < 0.05 (Table S2). Of these, 3 (42.86%) and 4 (57.14%) DEcircRNAs were upregulated and downregulated, respectively, in the ‘pet’ samples compared with the ‘leaf’ samples. The DEcircRNAs identified in this study were unknown and their host genes were not predicted.

Identification and functional enrichment analysis of DEmiRNAs between ‘leaf’ and ‘pet’

In this study, sRNA libraries of the ‘leaf’ and ‘pet’ samples were constructed and sequenced, aiming to obtain comprehensive insights into the miRNAs related to leaf and petiole development in Chinese cabbage. A total of 8,228,461–9,645,577 valid reads were obtained after screening the sequencing data obtained with an Illumina HiSeq2000/2500 platform. More than 69% of the valid reads could be mapped to pre-miRNAs or reference genomes (Table S6). A total of 1070 miRNAs were identified, of which 195 were differentially expressed between the ‘leaf’ and ‘pet’ samples. A total of 77 (39.49%) and 118 (60.51%) DEmiRNAs were upregulated and downregulated, respectively in the ‘pet’ samples compared with the ‘leaf’ samples (Table S2, Fig. 5a).

Fig. 5
figure 5

Identification of miRNAs that were differentially expressed between ‘leaf’ and ‘pet’ samples. a Statistical analysis of the DEmiRNAs that were upregulated and downregulated between the ‘leaf’ and ‘pet’ samples. b GO annotations of the DEmiRNAs; c KEGG pathway assignments of the DEmiRNAs

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The functions of the target genes of the DEmiRNAs were investigated by GO and KEGG enrichment analyses (Tables S4 and S5, Fig. 5b, c). The findings revealed that 20,977 target genes were enriched in 5878 GO terms. The majority of the genes were enriched in the “nucleus,” “plasma membrane,” “cytoplasm,” “ATP binding,” and “cytosol” terms; 544 GO terms were significantly enriched at p < 0.05. A total of 277 (50.9%) GO terms in the biological process category were enriched, primarily in the “biological process,” “regulation of transcription, DNA-templated,” and “transcription, DNA-templated” terms. The 67 enriched GO terms of the cellular component category mainly included the terms “nucleus,” “integral component of membrane,” and “plasma membrane”. The 200 enriched GO terms of the biological function category primarily included the “molecular function,” “ATP binding,” and “protein binding” terms. KEGG analysis demonstrated that 12,130 DE target genes of the miRNAs were enriched in 137 KEGG metabolic pathways, of which 24 were significantly enriched (p < 0.05). The DE genes were most enriched in the “plant–pathogen interaction” pathway, followed by the “starch and sucrose metabolism” pathway.

Construction of ceRNA network

To explore the regulatory network of ncRNAs and mRNAs related to leaf development, DEmRNAs that may play a key role in leaf development were selected based on the results of gene annotation to establish a ceRNA–miRNA–target gene regulatory network. The ceRNA network comprised 41 DEmiRNAs, 18 DEmRNAs, 9 DElncRNAs, and 1 DEcircRNA. A total of 85 pairs of ceRNA relationships were determined, including 71 DEmiRNA–DEmRNA, 12 DEmiRNA–DElncRNA, and 2 DEmiRNA–DEcircRNA pairs (Table S7, Fig. 6). Analysis of the ceRNA network revealed that most of the miRNAs interacted with circRNAs or lncRNAs, while few miRNAs simultaneously interacted with circRNAs and lncRNAs. It is known that multiple miRNAs can act on the same mRNA and consequently affect gene expression. Functional enrichment analysis of the genes in the ceRNA network revealed that the genes were highly correlated with leaf development. The DE genes were significantly enriched in various GO terms related to leaf development, including “leaf development,” “leaf morphogenesis,” and “cell differentiation” [18]. The majority of DE genes were also significantly enriched in the “plant hormone signal transduction” pathway. The mRNAs and ncRNAs in the ceRNA network can provide insights into the potential molecular mechanisms underlying leaf development or aid in the discovery of novel functional genes.

Fig. 6
figure 6

Construction of the ceRNA network related to leaf and petiole development, consisting of DEmRNAs, DElncRNAs, DEcircRNAs, and DEmiRNAs

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The ceRNA network comprised several transcription factors and proteins that play an important role in leaf development, including the TCP transcription factors, ATHB protein, and expansin precursor. TCP transcription factors play an important role in cell division and the shape of leaves [24]. The findings revealed that BraA01g036950.3C was regulated by ath-miR159c_L-1R + 3_1ss7TC, ath-miR159c_R-1, ath-miR319a_L + 1R-1, ath-miR319a_R + 1_1ss15GA, ath-miR319c_L + 1R-1, bra-miR319-3p, cme-miR319c_R + 3, gma-miR319c_L + 1R + 1, mes-miR319g_R + 3, mtr-miR319a-3p_L + 1R + 1_1ss21CT, mtr-miR319a-3p_R + 1, mtr-miR319a-3p_R + 1_1ss15GA, circRNA693, MSTRG.7481.1, and MSTRG.18783.1; BraA05g013580.3C was regulated by ath-miR319a_R + 1_1ss15GA, bra-miR319-3p, and mtr-miR319a-3p_R + 1_1ss15GA; BraA05g032060.3C was regulated by ath-miR319a_R + 1_1ss15GA, ath-miR319c_L + 1R-1, bra-miR319-3p, and mtr-miR319a-3p_R + 1_1ss15GA; BraA03g036760.3C was regulated by ath-miR319a_R + 1_1ss15GA, ath-miR319c_L + 1R-1, bra-miR319-3p, and mtr-miR319a-3p_R + 1_1ss15GA; and BraA01g009870.3C was regulated by ath-miR319a_R + 1_1ss15GA, ath-miR319c_L + 1R-1, and bra-miR319-3p.

The ATHB protein belongs to the HD-ZIP transcription factor family and regulates leaf morphology and development of petiolar vascular bundles [25,26,27]. Our analysis revealed that BraA06g002210.3C, BraA08g002260.3C, and BraA09g034560.3C were regulated by aly-miR166a-3p, ath-miR166a-3p, ath-miR166a-3p_1ss21CA, bna-miR166a, bna-miR166f, cas-miR166e, gma-miR166a-3p_R + 1, mtr-miR166a_R + 1, and MSTRG.16998.1.

Expansin proteins and their precursors play an important role in regulating the elasticity of cell walls, which subsequently affects abscission and leaf development [28]. In this study, we observed that BraA03g021530.3C was regulated by ath-miR396a-3p and MSTRG.2295.1.

Network analysis also led to the identification of some mRNAs that were enriched in the “phytohormone signal transduction” KEGG pathway, which could be involved in hormone regulation during leaf development. The results demonstrated that BraA02g000170.3C was regulated by bra-MIR824-p3; BraA04g028240.3C was regulated by PC-5p-7936_421 and MSTRG.7557.2; BraA06g010130.3C was regulated by PC-3p-149837_29; BraA06g043820.3C was regulated by ath-miR157a-5p, bna-miR156b, bra-miR156a-5p, cca-miR156c_L + 4, gma-miR156a_L + 1, MSTRG.14452.2, and MSTRG.2335.1; BraA07g025310.3C was regulated by ath-miR393a-5p, bna-miR393_R + 1, csi-miR393b-5p_L-1R + 1_1ss22CT, gma-miR393a_R + 4, and ptc-miR393a-5p_R + 4; BraA07g028930.3C was regulated by bra-miR391-3p; and BraA09g058330.3C was regulated by gma-miR6300 and MSTRG.3332.1.

Verification by quantitative real-time polymerase chain reaction (qRT-PCR)

The results of RNA-seq analyses were validated by qRT-PCR for 6 mRNAs, 6 lncRNAs, 6 miRNAs, and 6 circRNAs that were differentially expressed between the leaves and petioles of Chinese cabbage (Fig. S3). The mRNA expression data were validated by selecting six genes that could be involved in regulating leaf development. BraA05g042610.3C and BraA02g040480.3C encode LIGHT-DEPENDENT SHORT HYPOCOTYLS proteins, BraA07g027780.3C encodes a bZIP44 transcription factor, BraA09g034560.3C encodes the ATHB protein, and BraA03g042150.3C and BraA03g055650.3C encode XTH proteins. Among the lncRNAs chosen for validation by qRT-PCR, the lncRNAs MSTRG.16998.1, MSTRG.14452.2, and MSTRG.11133.1 were present in the ceRNA regulatory network, and MSTRG.23158.1, MSTRG.3458.1, and MSTRG.19485.1 were found to be related to hormone regulation. As the functions of the identified circRNAs were unknown, six circRNAs (circRNA58, circRNA601, circRNA162, circRNA693, circRNA612, and circRNA136) were randomly selected from the results of RNA-seq for validation by qRT-PCR. A total of six miRNAs were selected for qRT-PCR validation of RNA-seq data, of which four (bra-miR319-3p, bra-miR156a-5p, bra-miR391-3p, and vvi-miR172d_L-2R + 1) were present in the ceRNA networks. The results of the qRT-PCR analyses were consistent with the results of RNA-seq analyses, which confirmed the reliability of the RNA-seq data.

Subcellular localization of BrLSH1, BrLSH2, and BrLSH3

Zhao et al. [29] observed that the function of LSH1 depends on photoregulation during seedling development, which is mediated by phytochromes. Overexpression of LSH1 results in the production of shorter hypocotyls and larger cotyledons in varying light conditions, and the petioles of A. thaliana plants overexpressing LSH1 are smaller than those of the wild-type [29]. Additionally, Lee et al. [30] demonstrated that the overexpression of AtLSH1 and AtLSH2 markedly reduces vegetative and reproductive growth in A. thaliana; however, the phenotypes of AtLSH1 and AtLSH2 knockout lines are not significantly different from those of the wild-type. The function of LSH genes in Chinese cabbage has not been explored. In this study, three LSH genes, namely, BrLSH1, BrLSH2, and BrLSH3, were screened from the transcriptome data, and the expression levels of these genes were found to be significantly higher in the petioles of Chinese cabbage than in the leaves. We speculate that LSH genes may affect the development of leaves and petioles in Chinese cabbage. Therefore, in order to further explore their functions, subcellular localization and overexpression transgenic verification were carried out.

Here, the subcellular localization of three LSH genes, namely, BrLSH1, BrLSH2, and BrLSH3, which were significantly differentially expressed between the ‘leaf’ and ‘pet’ samples of Chinese cabbage, was analyzed. The GFP overexpression vectors PBWA(V)HS1-3-GLosgfp, PBWA(V)HS2-2-GLosgfp, PBWA(V)HS6-3-GLosgfp, and mKATE, were co-transferred into mesophyll cell protoplasts of A. thaliana by PEG-mediated transformation, and the GFP signals of BrLSH1, BrLSH2, and BrLSH3 were observed using a laser scanning microscope. The results demonstrated that BrLSH1, BrLSH2, and BrLSH3 were localized in the nucleus, which indicated that BrLSH1, BrLSH2, and BrLSH3 encode nucleoproteins (Fig. 7).

Fig. 7
figure 7

Subcellular localization of BrLSH1 (a, b), BrLSH2 (c, d), and BrLSH3 (e, f). Note: Panels a, c, and e depict the empty carrier fluorescence channel, chloroplast fluorescence channel, bright field, and superposition diagram from left to right; Panels b, d, and f depict the fluorescence channel of the target protein, marker fluorescence channel, chloroplast fluorescence channel, bright field, and superposition diagram from left to right

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Phenotypic effects of BrLSH1, BrLSH2, and BrLSH3

To further explore the functions of BrLSH1, BrLSH2 and BrLSH3, the genes were overexpressed in wild-type Col-0 A. thaliana and the phenotypic effects were observed. The phenotypes of the plants with BrLSH1 and BrLSH3 overexpression did not differ significantly from that of wild-type plants. However, the phenotype of plants with BrLSH2 overexpression altered significantly 14 days after sowing compared with that of the wild-type plants. The plants overexpressing BrLSH2 had shorter hypocotyls, significantly elongated true leaves, curly cotyledons, shorter taproots, and more lateral roots (Fig. 8a–c). Additionally, the growth rate of the plants overexpressing BrLSH2 was slightly lower than that of the wild-type plants, especially after 28, 35, and 42 days (Fig. 8d–f). The growth of plants with BrLSH2 overexpression was significantly inhibited, and the length of the petioles and leaf area were significantly reduced compared with those of wild-type plants (Fig. 8i). The leaf buds underwent division and the petals were degenerated at the bolting stage in the inflorescence of plants overexpressing BrLSH2 (Fig. 8g, h). These findings indicated that the overexpression of BrLSH2 had an obvious inhibitory effect on the growth and development of A. thaliana.

Fig. 8
figure 8

Morphological characteristics of plants overexpressing BrLSH2. a–c Phenotypic differences between wild-type col plants (left) and A. thaliana plants overexpressing BrLSH2 (right) 14 days after sowing. d–f Phenotypic differences between the wild-type col plants (left) and A. thaliana plants overexpressing BrLSH2 (right) 28, 35, and 42 days after sowing. Flower buds of g wild-type A.thaliana and h plants overexpressing BrLSH2. i Statistics for the leaf area and petiole length of wild-type plants and A. thaliana overexpressing BrLSH2. j Expression levels of BrLSH2 in wild-type (col) plants and plants overexpressing BrLSH2 at different developmental stages

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The expression pattern of BrLSH2 at different stages of development was determined by qRT-PCR analysis of samples of A. thaliana plants overexpressing BrLSH2 (Fig. 8j). The results demonstrated that the expression of BrLSH2 was zero in wild-type plants without exogenous gene transfer, and the expression of BrLSH2 was evident in plants overexpressing BrLSH2. The expression of BrLSH2 was increased significantly in the seedling stage 14 days after sowing and at the commencement of the bolting stage 42 days after sowing, compared with that 28 days after sowing.

Discussion

Leaves produce energy and carbohydrates by photosynthesis to maintain plant growth. The development of leaves has been studied in several plants, especially A. thaliana. The size, shape, and differentiation of the leaves of A. thaliana are regulated by several genes, including genes encoding mRNAs and miRNAs [16, 31]. Although the regulatory mechanism underlying leaf development is being studied increasingly, the mechanisms of regulation of leaf development in Chinese cabbage remain unclear, and a complete ceRNA regulatory network related to leaf and petiole development has not been constructed to date. In this study, the high generation inbred “PHL” line of Chinese cabbage was selected based on the growth period and genetic background, and leaves and petioles were collected for sequencing and whole transcriptome analyses. A total of 10,646 mRNAs, 303 lncRNAs, 195 miRNAs, and 7 circRNAs of unknown function were identified in this study that were differentially expressed between the leaves and petioles. This study is the first to construct a ceRNA–miRNA–target gene regulatory network related to leaf and petiole development in Chinese cabbage, which can provide a basis for further studies on the molecular mechanisms underlying leaf and petiole development.

GO and KEGG enrichment analyses were performed to elucidate the functions of genes that were differentially expressed between the leaves and petioles of Chinese cabbage. GO enrichment analysis revealed that the majority of DE genes were enriched in the terms “membrane,” “plasma membrane,” and “cell wall.” Additionally, several GO terms related to hormone synthesis, cell proliferation, and expansion were identified, including “brassinosteroid-mediated signaling pathway,” “auxin-activated signaling pathway,” “growth regulation,” “cell proliferation,” and “leaf development”. The results of KEGG enrichment analysis revealed that the majority of DE genes were involved in “plant hormone signal transduction” and “starch and sucrose metabolism” pathways, which are involved in hormone regulation and energy supply during leaf development [32, 33]. These findings may aid in exploring the upstream and downstream genes of functional genes, which can provide further insights into the molecular mechanisms of leaf and petiole development in Chinese cabbage.

The cell wall is a unique structure of plant cells, and the expansion of plant cells depends on the relaxation of cell walls to increase water absorption by the cells. This process requires the involvement of several genes, including those encoding XTHs and expansins [34,35,36,37]. Some studies have demonstrated that petiolar elongation is closely related to the modification of the cell wall [38, 39]. In this study, 16 genes encoding XTHs (including 14 upregulated and two downregulated genes in ‘pet’ relative to ‘leaf’), and 27 genes encoding expansion proteins and their precursors (including 23 upregulated genes and four downregulated genes in ‘pet’ relative to ‘leaf’) were identified in the transcriptome data. These genes may participate in cell expansion and affect the development of leaves and petioles. The transcription factors TCP14 and TCP15 participate in the elongation of petioles and hypocotyls. These transcription factors inhibit the transition from mitosis to endoreduplication and promote cellular proliferation, and are inhibited by the negative growth regulator DA1 [40, 41]. In this study, BraA07g034590.3C and BraA02g019350.3C were predicted to encode the TCP15-like transcription factor. These genes were upregulated in ‘pet’ samples and may participate in petiolar elongation in Chinese cabbage.

The bHLH transcription factors of plants are involved in a wide range of activities, including stress response, flowering, cell proliferation, and expansion [42]. For instance, HBI1 encodes a bHLH transcription factor that directly regulates the expression of genes involved in cellular expansion, including the genes encoding the TCP14 and TCP15 transcription factors [43]. In this study, a total of 23 genes encoding bHLH transcription factors were identified, of which 8 and 15 genes were downregulated and upregulated, respectively, in the ‘pet’ samples compared with the ‘leaf’ samples.

A previous study demonstrated that the MtPHAN gene of Medicago truncatula inhibits the ectopic expression of ELONGATED PETIOLULE1 (ELP1), which encodes a LOB domain protein and subsequently promotes the elongation of petiolar cells, which alters the petiolar phenotype [9]. A total of 11 genes encoding LOB domain proteins were identified in our transcriptome data. These genes included BraA02g045520.3C which was downregulated in ‘pet’ compared with ‘leaf,’ and BraA07g017050.3C, BraA02g037830.3C, BraA03g044950.3C, BraA01g001340.3C, BraA05g014110.3C, BraA02g016770.3C, BraA03g060820.3C, BraA07g018870.3C, BraA07g010160.3C, and BraA09g041230.3C, which were upregulated in the ‘pet’ samples compared with the ‘leaf’ samples. These genes possibly affect the size of the petioles of Chinese cabbage.

Brassinosteroid (BR) is an endogenous plant hormone that is involved in several aspects of plant growth and development, and also regulates cellular expansion. Exogenous BRs promote the elongation of petioles in carrot by affecting cellular elongation, GA content, and cellulose deposition. DELLA proteins act as mediators between BRs and GAs. BES1 and BZR1 are two key transcription factors that are involved in BR biosynthesis and the regulation of plant growth [51]. The miRNA targets were subsequently subjected to GO and KEGG enrichment analyses.

Construction of ceRNA network

ceRNA analysis was divided into two parts, namely, prediction of miRNA–mRNA pairs and prediction of miRNA–lncRNA/circRNA pairs. The Targetfinder software was used for predicting miRNA–mRNA pairs, and the degree of match between the target genes and miRNAs was used as the screening criterion [67]. The Ssearch36 software v36.3.6 and target mimics were used for screening and predicting miRNA–lncRNA/circRNA pairs [68, 69]. Perl scripts were used for integrating the circRNA/lncRNA–miRNA–mRNA networks, and the regulatory relationships were visualized with Cytoscape (https://cytoscape.org) [70]

qRT-PCR validation

A Trizol kit (Invitrogen, USA) and Evo M-MLV RT Kit II (Accurate Biotechnology, AG11711, China) were used to extract total RNAs of ‘leaf’ and ‘pet’ samples, which were reverse-transcribed into cDNA. Oligo dT and random 6-mer primers were used for reverse transcription of the lncRNAs and mRNAs. Reverse transcription of the circRNAs was performed using downstream primers in qRT-PCR and random 6-mer primers. The reverse transcription of miRNA was performed using primers downstream of U6 and specific stem-loop primers. A SYBR® Green Premix Pro Taq HS qPCR Kit (Accurate Biotechnology) was used to perform qRT-PCR using an ABI 7300 RT-PCR system (Thermo Fisher Scientific, Waltham, MA, USA). The protocols and conditions for qRT-PCR have been described previously, by Shi et al. [66]. The miRNA expression levels were normalized to those of U6 miRNA, which was used as the endogenous control. The expression levels of the mRNAs, lncRNAs, and miRNAs were normalized to those of actin. The primer sequences used for RT-PCR are listed in Table S8. qRT-PCRs were performed with three technical replicates and four biological replicates.

Analysis of subcellular localization

To determine the functions and expression patterns of genes that were possibly involved in leaf development, three ALOG family genes, namely BraA03g031670.3C, BraA05g042610.3C, and BraA02g040480.3C (referred to as BrLSH1, BrLSH2, and BrLSH3, respectively), which were significantly upregulated in the ‘pet’ samples relative to the ‘leaf’ samples were selected for subcellular localization analysis. The full-length coding sequences of BrLSH1, BrLSH2, and BrLSH3 were amplified using the genomic cDNA of Chinese cabbage. The primers used for amplification are listed in Table S9, where the uppercase letters indicate AarI restriction sites. The products of PCR amplification were digested with AarI and ligated to the N-terminal fusion vector, pBWA(V)HS-ccdb-GLosgfp, for expression driven by the GFP 35S promoter. The GFP overexpression vectors PBWA(V)HS1-3-GLosgfp, PBWA(V)HS2-2-GLosgfp, PBWA(V)HS6-3-GLosgfp were subsequently constructed. The 35S:GFP vector was selected as the negative control. The constructed vectors were transformed into mesophyll cell protoplasts of A. thaliana [71]. The GFP signals of the target genes were observed using a laser scanning microscope (Leica TCS SP8, Wetzlar, Germany) with an excitation wavelength of 488 nm. The excitation wavelengths for mKATE and chlorophyll autofluorescence were 561 and 640 nm, respectively. The emission wavelengths for mKATE, GFP, and chlorophyll autofluorescence were 580, 510, and 675 nm, respectively.

Genetic transformation of A. thaliana

Three overexpression vector plasmids, namely PBWA(V)HS1-3-GLosgfp, PBWA(V)HS2-2-GLosgfp, and PBWA(V)HS6-3-GLosgfp, were separately introduced into the GV3101 strain of Agrobacterium tumefaciens (syn. Rhizobium radiobacter) using the freeze–thaw method. Arabidopsis thaliana was transformed using the floral infiltration method [72]. Transformation-positive plants were screened using a medium containing hygromycin. The transgenic homozygous plants of the T3 generation were obtained by multigeneration selfing. The phenotypes of the plants in the T3 generation were observed 14, 28, 35, and 42 days after sowing. The length of the petioles and leaf area were measured using ImageJ software [73].