Skip to main content

Genome-wide identification of GA2ox genes family and analysis of PbrGA2ox1-mediated enhanced chlorophyll accumulation by promoting chloroplast development in pear



Chlorophyll (Chl) is an agronomic trait associated with photosynthesis and yield. Gibberellin 2-oxidases (GA2oxs) have previously been shown to be involved in Chl accumulation. However, whether and how the PbrGA2ox proteins (PbrGA2oxs) mediate Chl accumulation in pear (Pyrus spp.) is scarce.


Here, we aimed to elucidate the role of the pear GA2ox gene family in Chl accumulation and the related underlying mechanisms. We isolated 13 PbrGA2ox genes (PbrGA2oxs) from the pear database and identified PbrGA2ox1 as a potential regulator of Chl accumulation. We found that transiently overexpressing PbrGA2ox1 in chlorotic pear leaves led to Chl accumulation, and PbrGA2ox1 silencing in normal pear leaves led to Chl degradation, as evident by the regreening and chlorosis phenomenon, respectively. Meanwhile, PbrGA2ox1-overexpressing (OE) tobacco plants discernably exhibited Chl built-up, as evidenced by significantly higher Pn and Fv/Fm. In addition, RNA sequencing (RNA-seq), physiological and biochemical investigations revealed an increase in abscisic acid (ABA), methyl jasmonate (MeJA), and salicylic acid (SA) concentrations and signaling pathways; a marked elevation in reducing and soluble sugar contents; and a marginal decline in the starch and sucrose levels in OE plants. Interestingly, PbrGA2ox1 overexpression did not prominently affect Chl synthesis. However, it indeed facilitated chloroplast development by increasing chloroplast number per cell and compacting the thylakoid granum stacks. These findings might jointly contribute to Chl accumulation in OE plants.


Overall, our results suggested that GA2oxs accelerate Chl accumulation by stimulating chloroplast development and proved the potential of PbrGA2ox1 as a candidate gene for genetically breeding biofortified pear plants with a higher yield.

Peer Review reports


Pear (Pyrus spp.) is one of the top three widely cultivated fruit crops globally, with a high nutritional, medicinal, and economic value [1]. The yield and quality of pear are closely related to photosynthesis, which is responsible for carbon fixation, energy supply, and plant growth [2]. The ability of plants to photosynthesize is determined by the level of photosynthetic pigments in the leaves to a certain extent. Of these pigments, chlorophyll, a tetrapyrrole metabolite, is essential for photosynthesis [3, 4]. Thus, fine-tuning Chl is important for enhancing photosynthetic efficiency and increasing fruit crop yield [5]. In other words, plants with greater Chl concentration are of great interest and warrant special attention.

Gibberellin 2-oxidases (GA2oxs) are a distinct class of 2-oxoglutarate-dependent dioxygenase [6]. These enzymes mediate gibberellin (GA) deactivation by irreversibly catalyzing the bioactive GA9/4 and GA1/20 or their precursors GA12/53 into inactive GA8/34 via 2β-hydroxylation reaction [7]. Due to the crucial functions of GA in plant growth and development [8] and the typical roles of GA2ox genes (GA2oxs) in GA metabolism, GA2oxs have been characterized and widely studied in several plant species, such as Arabidopsis [9], tomato [10], rice [11], maize [12], apple [13], and switchgrass [14]. Moreover, extensive research has unveiled the impacts of GA2oxs on plant architecture, flowering time, hypocotyl elongation, and seed dormancy in a GA-dependent manner [9, 15, 16].

Notably, apart from the phenotypes of retarded growth, delayed flowering time, and inhibited seed germination [9, 15, 16], GA2oxs-overexpressing plants exhibit surprisingly high Chl content. In Arabidopsis, AtGA2ox2 overexpression reportedly facilitates Chl accumulation [17]. Similarly, overexpression of BnGA2ox2/BnGA2ox6 and PpGA2ox in Arabidopsis has been shown to significantly increase Chl content [17,18,19]. In addition, PcGA2ox1 and GhGA2ox1 have also been reported to enhance Chl accumulation [20, 21], and transgenic maize and rapeseed plants overexpressing AtGA2ox1 and AtGA2ox8 have been stated to display high Chl concentrations [22,23,24]. These studies highlight the role of GA2oxs in Chl accumulation. However, relevant studies revealing how GA2oxs work are lacking, whereas the essential role of the pear GA2ox gene family in Chl accumulation still needs to be elucidated.

With the inexorable advancement in the RNA sequencing (RNA-seq) technique, there has been an enhancement in the mining and analysis of key factors that are responsible for specific plant traits, making it possible to unveil the regulatory mechanisms underlying the variations in plant characteristics [25]. Previously, RNA-seq helped to reveal the fundamental determinants that contribute to interstock-induced dwarfism in sweet persimmon [26], and altitude-dependent potato tuber coloring [27]. Moreover, RNA-seq has also been widely utilized to derive novel insights into the functions of several genes, such as the SlWRKY35-activated carotenoid biosynthesis in tomatoes [28], MdMYB94-induced ester biosynthesis in apples [29], and TgbHLH95- and TgbZIP44-targeted terpene biosynthesis in ‘xiang fei’ (Torreya grandis) nuts [30]. Thus, RNA-seq can help efficiently explore the potential mechanisms underlying phenotypic alterations arising from gain-of-function or loss-of-function of genes.

Here, to reveal the role of PbrGA2oxs (GA2oxs from Pyrus spp.) in Chl accumulation and to identify the underlying functional mechanism, the members of PbrGA2oxs in pear were isolated using TBtools. We investigated the role of PbrGA2ox1 in Chl accumulation by transiently overexpressing PbrGA2ox1 in chlorotic pear leaves, transiently silencing PbrGA2ox1 in normal leaves, and stably overexpressing it in tobacco plants. Subsequently, we dissected the intrinsic regulatory patterns underlying PbrGA2ox1-induced Chl accumulation using transcriptomic analysis on PbrGA2ox1-overexpressing (OE) and wild-type (WT) tobacco plants. Fortunately, we identified several key pathways that might contribute to Chl accumulation in OE plants. The role of these pathways was further confirmed by measuring relevant physiological indexes. Furthermore, we explored and verified the effect of PbrGA2ox1 on Chl synthesis and chloroplast development via transmission electron microscopy. Overall, this study systematically illustrates the role of PbrGA2ox1 in Chl accumulation, which might broaden our understanding of GA2oxs-facilitated Chl accumulation and offer primary insights into the underlying regulatory mechanism.


Genome‑wide identification of pear GA2ox genes family and screening of PbrGA2ox1

Protein searches of the pear database revealed a total of 13 PbrGA2oxs with lengths ranging from 156 to 395 amino acids (Fig. 1a). These proteins were clustered into three phylogenetic group types (Fig. S1a in Additional File 1) based on the classification of AtGA2ox1; Class I, Class II, and Class III [24]. The proteins harbored only one relatively longer conserved PLN02984 or PLN02156 domain (Fig. 1a). There were ten motifs in PbrGA2oxs, with three to eight motifs randomly distributed in each of these proteins (Fig. 1b). Only one conserved motif was shared by all proteins. The corresponding genes for these 13 PbrGA2oxs possessed at least two introns between the coding sequences (Fig. 1c). and most of them exhibited longer introns, such as Pbr000192.1 and Pbr033679.1 (Fig. 1c). These findings showed a diversity in the gene structure of PbrGA2oxs. In general, PbrGA2oxs in the same class had similar exon–intron structures (Fig. 1c), particularly in terms of number of exons, suggesting that the gene sequence and exon–intron structures are highly conserved within PbrGA2oxs of the same class.

Fig. 1
figure 1

Identification and bioinformatics analysis of pear GA2ox-family genes. a Conserved domain and (b) conserved motifs analysis of pear GA2ox proteins. Different domains and motifs are displayed in different colored boxes. c Structure analysis of pear GA2ox genes. The exons (coding sequences, CDS) and introns of the genes are marked with yellow boxes and black solid lines, respectively. The untranslated regions (UTR) located upstream or downstream of the genes are indicated by green boxes. d Neighbor-likelihood (NL) phylogenetic tree of 13 PbrGA2ox proteins and seven GA2ox proteins involved in chlorophyll accumulation, including three proteins from Arabidopsis (AtGA2ox1, accession number: AT1G78440.1; AtGA2ox2, accession number: AT1G30040.1; AtGA2ox8, accession number: AT4G21200.1), one protein from flowering bean (PcGA2ox8, accession number: AJ132438), one protein from cotton (GhGA2ox1, accession number: XP_016703412), and two proteins from rapeseed (BnGA2ox2, accession number: XP_013671430; BnGA2ox6, accession number: NP_001302845). The tree was constructed in the MEGA 7.0 program with 1000 bootstrap replications

To identify the PbrGA2oxs potentially involved in Chl accumulation, we performed a phylogenetic tree analysis with GA2oxs that are known to be involved in Chl accumulation (Table S1 in Additional File 2) [17,18,19,20,21,22,23,24]. The three PbrGA2oxs, Pbr025274.1, Pbr039586.1, and Pbr009085.1, clustered close to the majority of the other functional GA2oxs (Fig. 1d), indicating that these three genes might contribute to Chl accumulation. Of these three, Pbr025274.1 was selected for further analyses owing to its higher expression in normal pear leaves than the other two genes (Fig. S1b in Additional File 1). Pbr025274.1 is annotated as a pear gibberellin 2-beta-dioxygenase 1-like gene in the National Center for Biotechnology Information (NCBI) database, and it was highly homologous to GhGA2ox1. Thus, Pbr025274.1 was designated as PbrGA2ox1 in this study.

Functional analysis of PbrGA2ox1 in Chl accumulation in pear plants

To investigate the role of PbrGA2ox1 in Chl accumulation, we generated a PbrGA2ox1 overexpression construct (PbrGA2ox1_OE) and transiently transferred it into the chlorotic leaves of ‘Akizuki’ and ‘Dangshansuli’ pear plants. The leaves injected with the empty vector (EV) were used as the control. To ascertain the efficiency of transformation, a qRT-PCR analysis was carried out with the control and PbrGA2ox1‐overexpressing pear leaves seven days post-transformation. The results showed that the PbrGA2ox1 transcript level in the injection sites of overexpressed leaves was higher than that in the sites of the control leaves in both pear types (Fig. S2a and b in Additional File 1), implying the effectiveness of the system. After 14 days, no significant changes appeared at the injection sites on the control leaves. However, a re-greening phenomenon was observed at the injection sites on the overexpressed leaves (Fig. 2a and b). These findings were further supported by a marked increase in Chl leaves in overexpressed leaves at the end time point (Fig. 2c and d).

Fig. 2
figure 2

Transient PbrGA2ox1 overexpression leads to a regreening phenomenon in the chlorotic pear leaf, while its silencing results in the chlorosis of the normal pear leaves. a, c The outward appearances, and (b, d) the chlorophyll content of chlorotic leaves from ‘Akizuki’ and ‘Dangshansuli’ pear plants at 14 days after injection with either empty vector (EV) or PbrGA2ox1-overexpression construct (PbrGA2ox1_OE). The area marked with a dotted circle indicates the injected site in each leaf. e, f Representative images, and g, h chlorophyll content of green leaves from ‘Dui’ pear plants and tobacco plants at 14 days after injection with wither either control vector (TRV2, left panel) or PbrGA2ox1-silenced construct (PbrGA2ox1_TRV2, left panel). Here, whole ‘Duli’ pear leaves and only half of the tobacco leaves were injected and examined, and the white solid circle indicated the injection sites

Meanwhile, to better understand the role of PbrGA2ox1 in Chl accumulation, we used the virus-induced genes silence (VIGS) technique to introduce PbrGA2ox1 knockdown (PbrGA2ox1_TRV2) construct in both tobacco and ‘Duli’ pear leaves. The leaves injected with the empty TRV2 vector were used as the control. Again, qRT-PCR was used to quantify PbrGA2ox1 expression in control and PbrGA2ox1-silenced pear leaves. PbrGA2ox1 expression was markedly suppressed in the silenced leaves than in control leaves (Fig. S2c and d in Additional File 1). These PbrGA2ox1-silenced plants were subsequently used for functional analysis. Notably, at 14 days after injection, no discernable differences were observed at the injection site on the control leaves (Fig. 2e and f). However, the injection sites on the silenced leaves exhibited typical chlorosis symptoms (Fig. 2e and f). Furthermore, the PbrGA2ox1-silenced exhibited significantly lower Chl content than the control leaves (Fig. 2g and h). These results suggest that PbrGA2ox1 positively regulates Chl accumulation in pears.

Effects of PbrGA2ox1 overexpression on Chl built-up in tobacco plants

To further validate the physiological impact of PbrGA2ox1 on Chl accumulation, three previously generated PbrGA2ox1_OE tobacco (Nicotiana benthamiana) plants (OE_1, OE_2, OE_4) [31] were used. The dynamic growth traits of WT and OE lines were monitored at the seedling stage, with a focus on the leaf color. The results showed that the OE lines exhibited dwarfism but were certainly greener than the WT lines throughout the seedling stages (Fig. 3a). During the later growth stages, Chl a, Chl b, and total Chl levels gradually increased in all plants (Fig. 3a and b). However, their levels in each recorded growth node in the OE plants were prominently higher than in the WT plants (Fig. 3b). Furthermore, the WT and OE lines exhibited discernable variation in the leaf color at 35 DAV (Fig. 3a).

Fig. 3
figure 3

Growth traits and chlorophyll content of wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco plants under long-day conditions. a Phenotypic features of WT and OE transgenic tobacco seedlings from seven days after vernalization (DAV) to 49 DAV. Scale bars = 2.5 cm. b Chlorophyll a, chlorophyll b, and the total chlorophyll levels in the leaves of WT and OE transgenic tobacco seedlings at different developmental stages. The data represent the mean ± SD (n = 3) of three independent biological experiments. c The net photosynthetic rate (Pn), water use efficiency (WUE), and maximal photochemical efficiency of PSII (Fv/Fm) of WT and OE plants at 35 DAV. The indicator on WT serves as the control. Asterisks used above the columns indicate a significant difference at p < 0.05 (one-way ANOVA) to the control based on Tukey’s test

Given the strong association between Chl content and photosynthesis or Chl fluorescence [4, 32,33,34,35], the gas exchange and Chl fluorescence parameters were subsequently evaluated. The Ci, Gs, and Tr values did not differ significantly between the OE and WT lines (Fig. S3b, c, and d in Additional File 1). However, we observed markedly higher Pn and WUE in the OE plants than in the WT plants (Fig. 3c, Fig S3a and e in Additional File 1). Furthermore, we did not observe significant differences between the Fm, Y(II), ETR, qP, F0, NPQ, and Y(NPQ) of WT and OE plants (Fig. S3f, g, i, j, k, l, and m in Additional File 1). However, the Fv/Fm value of the OE seedlings was markedly higher than that of WT seedlings (Fig. 3c, Fig. S3h in Additional File 1). Altogether, these outcomes suggest that PbrGA2ox1 overexpression accelerated Chl built-up in tobacco plants.

RNA-seq and sequencing quality analysis

RNA-seq was used to elucidate the mechanism underlying PbrGA2ox1 overexpression-mediated Chl accumulation. A total of six cDNA libraries were constructed from tobacco seedlings, including one each from three biological replicates of WT lines (WT_1, WT_2, WT_3) and the three transgenic lines at 35 DAV for transcriptome sequencing. After quality control, an average of 4.87 G of clean reads with GC content ranging from 43.35% to 44.11% was accessed from the RNA-seq data. Around 98% and 94.59% of these six libraries comprised Q20 and Q30 bases, respectively (Table S2 in Additional File 2), indicating that high-quality read sets were obtained. Given the absence of a high-quality reference genome for N. benthamiana, the clean reads were mapped to several reported tobacco genomes using TopHat2. An average highest mapping rate of 52.74% was obtained for these clean reads concerning the genome v2.0 of N. attenuate. Here, the uniquely mapped clean reads ranged from 50.01% to 51.71% from each library (Table S2 in Additional File 2), highlighting that many uncharacterized or unique genes were still present in N. benthamiana. However, owing to the adequate coverage of the RNA-seq data and the high proportions of Q20 and Q30 bases in the raw data (Table S2 in Additional File 2), the transcriptome sequencing data was utilized for subsequent analyses.

Identification of DEGs

The contigs were assembled into CDSs of 45899 unigenes with lengths ranging from 200 to 1800 bp, and only 16943 functional genes were annotated in the databases. The Venn diagram showed that 564 and 524 genes were specifically characterized in the OE and WT lines, respectively (Fig. 4a). Thus, 15855 annotated functional genes overlapped in both lines (Fig. 4a). Among the shared genes, the fragments per kilobase of transcript per million mapped reads (FPKM) value were analyzed to further identify the DEGs that might be involved in the Chl deposition in the leaves of OE lines. Thus, 1323 DEGs were identified using DESeq2, with 684 and 639 genes significantly upregulating and downregulating in the OE lines, respectively (Fig. 4b and c). These DEGs were grouped into eight subclusters based on their expression patterns (Fig. 4c and d). Among them, the DEGs from subclusters 2, 4, 7, and 8 were prominently upregulated, and those from subclusters1, 3, 5, and 6 were markedly downregulated in the OE lines compared to the WT lines (Fig. 4c and d). We then analyzed the top 10 upregulated genes with FPKM ≥ 1 from subclusters 2, 4, 7, and 8, and found that they were primarily related to plant responses to abiotic stresses. One of these genes was NIATv7_g23299, a member of the P450 family genes [36], which might be involved in regulating chloroplast function (Table S3 in Additional File 2). These results indicate the potential involvement of PbrGA2ox1 in regulating chloroplast function and abiotic stress responses.

Fig. 4
figure 4

Identification and functional enrichment analysis of differently expressed genes (DEGs). a Venn plot analysis of common and uniquely expressed genes in leaves of wild type (WT) and PbrGA2ox1-overexpressing (OE) seedlings at 35 days after vernalization (DAV) under long-day conditions. b The number of up-regulated and down-regulated DEGs in the comparison group namely OE vs. WT. c The expression heatmap of DEGs across total samples. The color indicates the expression level in the form of log2|FPKM| values. Blue represents a high expression level, and red represents a low expression level. Numbers above the groups indicate corresponding subclusters from one to eight. d Expression profile clustering of the DEGs in OE vs. WT. The red line indicates the average expression level of all DEGs in a subcluster. e Enriched gene ontology (GO) terms for DEGs identified from the RNA-seq data of the leaves from WT and OE seedlings. The DEGs were classified based on GO annotation and were categorized into biological process (BP), molecular function (MF), and cellular component (CC). The values indicate the number of genes in each classification, and the red marks highlight the most enriched category. f A bubble map of the top 20 KEGG enrichments for DEGs. The ordinate denotes the pathway name, the abscissa describes the richness factor, each circle in the map represents a pathway, the size of a circle indicates the number of DEGs in the pathway, and the color of a circle corresponds to different p-value ranges

Functional annotation of DEGs

To identify the PbrGA2ox1-regulated biological processes, GO term enrichment was conducted. The GO terms analysis revealed that the DEGs associated with PbrGA2ox1 overexpression were categorized into the biological process (BP), molecular function (MF), and cellular component (CC) (Fig. 4e). The enriched terms in BP include cellular process, metabolic progression, and biological regulation; those in MF include catalytic activity, binding, and transporter activity; and those in CC include cell part, membrane part, and organelle (Fig. 4e). Consistently, our analysis showed that the selected DEGs were relevant to molecular function (GO:0003674), catalytic activity (GO:0003824), lipid metabolic/biosynthetic process (GO:0006629 and GO:0008610), and DNA-binding transcription factor activity (GO:0003700) (Fig. S4a in Additional File 1). The majority of these genes were significantly upregulated in the OE lines compared to the WT lines (Fig. S5a, b, c, and e in Additional File 2). Therefore, these results indicate enhanced biocatalytic and transcriptional activities in the OE plants.

Next, we used the KEGG pathway enrichment to gain a broader view of the PbrGA2ox1-regulated biological functions. The results revealed that the relevant regulatory pathways related to the DEGs generated by PbrGA2ox1 overexpression were mainly assigned to metabolism, genetic information and processing, and environmental information processing (Fig. S4b in Additional File 1). These pathways comprise signal transduction, carbohydrate metabolism, terpenoid and polyketide metabolism, lipid metabolism, and amino acid metabolism (Fig. S4b in Additional File 1). Consistently, our analysis showed that the DEGs were enriched in plant hormone signal transduction (map04075), phenylpropanoid biosynthesis (map00940), starch and sucrose metabolism (map00500), and protein processing (map04141) (Fig. 4f). The map04075 pathway primarily comprised the genes related to indole-3-acetic acid (IAA) and ethylene (ETH) signal transduction, the genes related to brassinosteroid (BR) and cytokinin (CTK) signaling (Fig. 5a). In the IAA and ETH signaling, a growth-suppressible gene NIATv7_g02862 (which is homologous to AtIAA20) [37] and a chlorophyll-related gene NIATv7_g11268 (which is homologous to MsETR2) [38] was remarkedly upregulated in the OE lines than in the WT lines (Fig. 5a). This finding implies inhibited growth and increased Chl levels in OE plants.

Fig. 5
figure 5

Pathway analysis of differently expressed genes (DEGs). Schematic representation and expression heatmap of DEGs associated with (a) hormone signaling, and (b) starch and sucrose metabolism. The diagrams were constructed based on the corresponding Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and literary references. In (a), the neatly arranged cyan circles make up the cell membrane and the orange dotted lines comprise the nucleus. In (a) and (b), the function-annotated DEGs, filtered from the RNA sequencing (RNA-seq) data of the leaves from wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco seedlings at 35 days after vernalization (DAV) under long-day conditions, are marked with blue boxes. The expression levels for DEGs are shown as min–max normalized counts based on the fragments per kilobase of transcript per million mapped reads (FPKM) values and are presented in colors. The numbers in the boxes are the normalized values, and the blue-to-red gradient denotes a gradual increase in gene expression. The blue arrows indicate a significant decline, whereas the red arrows denote a marked rise in OE vs. WT

Moreover, compared to WT plants, three type-A Arabidopsis (Arabidopsis thaliana) response regulator (A-ARR) genes (involved in CTK signaling) and one touch-induced (TCH) gene (involved in) in BR signaling were notably upregulated, and one botrytis-induced kinase 1 (BIK1) and one TCH gene were prominently downregulated in the OE plants (Fig. 5a). Furthermore, seven DEGs, including two TGACG-binding (TGA) genes, one phytochrome-interacting factor 3 (PIF3), one gibberellin insensitive dwarf 1 (GID1) gene, one protein phosphatase 2C (PP2C) gene, one SNF1-related protein kinase 2 (SnRK2) gene, and one jasmonate response (JAR) gene, were involved in the GA, ABA, JA, and SA signal transduction pathways (Fig. 5a). Except for the PP2C gene and one TGA (NIATv7_g14145) gene, these genes were upregulated following PbrGA2ox1 overexpression (Fig. 5a). This outcome indicates that the ABA, SA, and JA signaling pathways were enhanced in the OE lines. Furthermore, we observed a marked elevation in the expression of the genes involved in the conversion of maltodextrin into maltose, UDP-glucose to intrehalose-6P, and cellulose to cellodextrin, including NbTPS, NbAMY, and NbCEL. This finding showed enhanced starch and sucrose metabolisms in the OE lines (Fig. 5b). Taken together, these results indicate the crucial roles of sugar and starch metabolism and hormone signaling in the regulating Chl accumulation of OE lines.

Expression analysis of DEGs related to Chl synthesis and chloroplast development

The emphasis of this work was to investigate the intrinsic mechanisms responsible for the markedly higher Chl content in leaves of OE plants compared to the leaves of WT plants, we analyzed, in-depth, the DEGs involved in Chl synthesis (map00860) (Fig. 6a). Interestingly, the expressions of most of the genes previously characterized to be responsible for the Chl synthesis in tobacco [39, 40] did not differ significantly in OE and WT plants. Based on the RNA-seq data, only three Chl synthesis-related DEGs were isolated in the current study (Fig. 6a). Among these, two DEGs, responsible for the formation of phytochromobilin and bacterio-chlorophyll a, were markedly upregulated in the OE plants than the WT plants (Fig. 6a). In contrast, the third DEG, which is involved in the conversion of protoporphyrin IX to Mg-protoporphyrin IX, was downregulated in the OE lines (Fig. 6a). Meanwhile, we noted that little DEGs existed in the Chl degradation pathway by checking the detail (Data not show). These data suggest that Chl accumulation in the OE plants was not significantly associated with Chl synthesis, as well as Chl degradation, and warrant further investigation to elucidate the primary reason behind Chl accumulation in the OE plants.

Fig. 6
figure 6

Expression profiles analysis of differently expressed genes (DEGs) involved in chlorophyll synthesis and chloroplast development. a Schematic representation and expression heatmap of DEGs related to chlorophyll synthesis in tobacco plants. The diagrams were constructed based on the corresponding Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and literary references. The function-annotated DEGs, filtered from the RNA sequencing (RNA-seq) data of the leaves from wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco seedlings at 35 days after vernalization (DAV) under long-day conditions, were marked with blue boxes. The expression levels for DEGs are shown as min–max normalized counts based on the fragments per kilobase of transcript per million mapped reads (FPKM) values and are presented in different colors. The numbers in the boxes are the normalized values, and the blue-to-red gradient denotes a gradual increase in gene expression. The blue arrows indicate a significant decline, whereas the red arrows denote a marked rise in OE vs. WT. Glu: glutamyl; NA: L-glutamyl-tRNA; GS: L-glutamyl-semialdehyde; ALA: 5-aminolevulimate; PBGD: porphobilinogen; Hmb: hydroxymethyl-bilane; Uro III: uropor-phynnogen III; Coprogen III: copropor phyrinogen III; Proto IX: proto IX; Mg-proto IX: Mg-protoporphyrin IX; Divinyl Pchl: divinyl-proto-chlorophyllide; Pchlide a: divinyl-proto-chlorophyllide a; Chlide a: chlorophyllide a; Chl a: chlorophyll a; Pchlide b: divinyl-proto-chlorophyllide b; Chlide b: chlorophyllide b; Chl b: chlorophyll b. b Dot chart of the expression level of DEGs directly (orange box) or indirectly (cyan box) regulating chloroplast development in plants. Values are presented in the form of log2 based on their FPKM obtained by RNA-seq, the values in WT serve as the control. Asterisks used above the columns indicate a significant difference at p < 0.05 (one-way ANOVA) to the control based on Tukey’s test

Chloroplasts serve as the essential organelles that facilitate Chl synthesis. The number, size, and morphology of chloroplasts directly correlate with the Chl concentration in plants [41]. Since PbrGA2ox1 overexpression only mildly impacted the expression of Chl synthesis-related DEGs, we examined if it modulated chloroplast development in tobacco. Since the literature on chloroplast development in tobacco is limited [42], we subsequently analyzed the tobacco genes homologous to functional genes previously reported to be directly and indirectly responsible for chloroplast development in Arabidopsis [43,44,45,46,47,48,49]. We noticed that most of the selected homologous genes were upregulated in the OE plants compared to the WT plants, with significantly elevated expressions of NbPDV1, NbMCD1B, NbPIC1, NbVAR2, NbPDM4, and NbCGF1A/1B (Fig. 6b). These findings demonstrate that PbrGA2ox1 overexpression might enhance chloroplasts development in the OE plants, which might account for the Chl built-up in.

Notably, we also observed the downregulation of two key anthocyanin-induced genes in the OE lines compared to the WT lines (Fig. S6a and b in Additional File 1), indicating suppressed anthocyanin synthesis in the OE plants, which represented an opposing trend to Chl accumulation [50, 51]. In addition, KEGG pathway enrichment also showed that some DEGs were closely associated with MAPK signaling and plant-pathogen interaction (Fig. S6c and d in Additional File 1), suggesting that PbrGA2ox1 might also play a functional role in MAPK signal transduction and disease resistance. Intriguingly, several stress-responsive transcription factors were also found to be upregulated in the OE lines compared with WT lines (Fig. S7 in Additional File 1), including the AtWRKY57 [52] homologous gene NIATv7_g19088, the AtDREB2A [53] homologous gene NIATv7_g17425, the AtEIN3 [54] homologous gene NIATv7_g18992, and the AtWRKY15 [55] homologous gene NIATv7_g21131 (Fig. S7 in Additional File 1). This observation also implied that OE lines might exhibit better acclimation to stress.

Validation of RNA-seq data using qRT-PCR

To verify the reproducibility of the transcriptomic analysis results, a total of 14 DEGs involved in plant hormone signaling, starch and sucrose metabolism, Chl and flavonoid synthesis, chloroplast development, MAPK signaling, and plant-pathology defense were randomly selected for qRT-PCR confirmation. We observed similar expression patterns for the selected genes in qRT-PCR as was observed during RNA-seq. However, we observed some discrepancies in the fold change of the genes, which might be attributed to the distinct detection ranges and sensitivities of the two analytical methods (Fig. 7a). Moreover, the correlation analysis was conducted using the log2 expression ratio of the qRT-PCR-based 2−ΔΔCt values and the log2 expression ratio of corresponding RNA-seq-derived FPKMOE/WT values to further validate the reliability of the transcriptomic data. Again, the expression profiles of all the selected genes detected using qRT-PCR were consistent with the RNA-seq results, with the Pearson coefficients (R2) value of 0.8612 (Fig. 7b), indicating the high reliability and accuracy of the transcriptomic data.

Fig. 7
figure 7

Validation of expression profiles of the 14 selected differently expressed genes (DEGs) by quantitative real-time PCR (qRT-PCR). a Relative expression levels of the 14 selected DEGs in leaves of wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco plants at 35 days after vernalization (DAV) under long-day conditions. The expression levels detected in WT were used as the control and normalized to ‘1’. NbActin was used as the internal reference gene. The values represent the mean ± SD of three biological replicates (n = 3). Asterisks above the bars indicate a statistically significant difference at p < 0.05 (one-way ANOVA) to the control based on Tukey’s test. The dashed trend lines in the bar charts were plotted from the FPKMOE/WT ratio. b Pearson correlation scattered plot analysis of the results of qRT-PCR and RNA sequencing (RNA-seq)

Changes in the levels of phytohormones, starch, and sugars in transgenic tobacco plants

Subsequently, we investigated the levels of some phytohormones, sugar, and starch in the leaves of WT and OE plants at 35 DAV. The results showed that the OE plants exhibited extremely lower IAA, bioactive gibberellins (BGAs, GA1+3+4+7), and 1-aminocyclopropane-1-carboxylic acid (ACC) (Fig. 8a, d, and f) compared to those of WT plants, whereas the contents of JA and JA-Ile did not differ significantly between OE and WT plants (Fig. 8g and h). In addition, a similar downward trend was observed for N6-(delta2-Isopentenyl) adenine and N6-(delta2-Isopentenyl) adenosine, two kinds of cytokinin (CTK), in OE seedlings (Fig. 8b and c). On the contrary, the OE seedlings possessed pronouncedly higher contents of ABA, MeJA, and SA than the WT seedlings (Fig. 8e, i, and j).

Fig. 8
figure 8

Differences in the levels of hormones and starch and sugar in leaves of wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco seedlings at 35 days after vernalization (DAV) under long-day conditions. a-j The concentration of hormones in the leaves of WT and OE tobacco seedlings at 35 DAV under long-day conditions. The hormones included (a) indoleacetic acid (IAA), cytokinin (b) N6-(delta2-Isopentenyl) adenine and (c) N6-(delta2-Isopentenyl) adenosine, d bioactive gibberellins (BGAs), e abscisic acid (ABA), f ethylene precursor 1-aminocyclopropyl-1-carboxylic acid (ACC), g jasmonic acid (JA), h jasmonic acid-isoleucine (JA-Ile), (i) methyl jasmonate (MeJA) and j salicylic acid (SA). k-o The abundance of starch and sugar in the leaves of WT and OE tobacco seedlings at 35 DAV under long-day conditions. k Starch visualization of WT and OE leaves. l Starch content, m sucrose content, n soluble sugar content, and o reducing sugar content in WT and OE leaves. Data are shown as the mean ± SD (n = 3) of three independent biological experiments. The indicator of WT serves as the control, ‘ns’ and asterisks used above the columns indicate insignificant and significant differences at p < 0.05 (one-way ANOVA) to the control based on Tukey’s test, respectively

We used histochemical staining to analyze the differences in the starch contents of WT and OE plants. We observed fewer staining spots and less intense staining on the leaves of OE seedlings than WT seedlings (Fig. 8k). Moreover, the quantitative analysis also revealed considerably lower starch and sucrose contents in the OE plants compared to the WT plant (Fig. 8l and m). Consistently, the activity of the β-amylase, a vital enzyme responsible for starch degradation [56], in OE plants was prominently higher, and the expression of its two encoding genes (BAMs) were also remarkably elevated in OE plants compared to those in WT plants (Fig. S8 in Additional File 1). More importantly, notably higher levels of soluble sugar and reducing sugar were detected in the OE lines than in the WT lines (Fig. 8n and o). Overall, these results demonstrated that PbrGA2ox1 overexpression-mediated Chl built-up was tightly regulated via the accumulation of ABA, JA, MeJA, soluble sugar (except for sucrose), reducing sugar, and the decline of IAA, BGAs, ACC, and CTK, starch, and sucrose.

Effects of PbrGA2ox1 overexpression on chloroplast morphology and ultrastructure

Next, we collected chloroplasts from equal areas of the leaves of the WT and OE lines and resuspended the precipitates in a chloroplast storage buffer. We observed that the solution containing the chloroplasts collected from the OE plants, especially for the OE4 plants, was greener than the solution containing the chloroplasts collected from the WT plants. This finding showed that the OE plants contained more chloroplasts than the WT plants (Fig. 9a). Further while analyzing of chloroplast ultrastructure using TEM, we found that while the chloroplasts in the WT plants were uniform, with overtly visible thylakoid granum stacks; however, the chloroplasts in OE4 plants were more strongly connected in a chain and attached more tightly to the cell walls (Fig. 9b).

Fig. 9
figure 9

Analysis of chlorophyll development in tobacco and expression profiles of related genes in pear. a Visualization of chloroplast abundance in the leaves (10 cm2 section) of wild-type (WT) and PbrGA2ox1-overexpressing (OE) tobacco seedlings at 35 days after vernalization (DAV) under long-day conditions using the grinding method. b The ultrastructure of chloroplasts from the leaves of WT and OE plants. C, chloroplast; S, starch granule; P, plastoglobuli; G, granum; TGS, thylakoid granum stacks. Scale bars: 10 μm (left) and 2 μm (right). c Number, and (d) size of chloroplasts per cell in the leaves of WT and OE seedlings at 35 DAV. The data represent the mean ± SD of values obtained from at least ten chloroplasts from five individual cells (n = 5). e Expression analysis of the genes related to chloroplast development in the spots injected with empty vector (EV) or PbrGA2ox1-overexpression construct (PbrGA2ox1_OE). The gene expression level detected in EV-injected spots was used as the control and set to ‘1’. PbrActin was used as the internal reference gene. Values shown are the mean ± SD of three biological replicates (n = 3). ‘ns’ and asterisks above the bars indicate insignificant and significant differences at p < 0.05 (one-way ANOVA) to the control based on Tukey’s test

More importantly, compared to the WT plants, the OE4 plants exhibited denser thylakoid granum stacks, and smaller starch granules (Fig. 9b). Moreover, we discovered an appreciably higher number of chloroplasts per cell in OE4 plants than in the WT plants (Fig. 9b and c). The size of the chloroplasts in OE4 plants was conspicuously smaller than in the WT plants (Fig. 9b and d). However, the cell size in the former was dominantly diminished than the latter (Fig. S9 in Additional File 1), demonstrating more cells per area and consequently, more chloroplasts per area in the OE plants. These observations showed that PbrGA2ox1 promotes Chl accumulation by facilitating chloroplast development in tobacco.

Therefore, given the crucial role of PbrGA2ox1 in facilitating chloroplast development, we used TEM to observe the chloroplasts ultrastructure of the infected spots in ‘Dangshansuli’ pear leaves (Fig. 2b), since they displayed a marked regreening phenomenon. Unfortunately, we failed (Fig. S6e in Additional File 1). Thereafter, we turned to focus on the expression of the genes related to chloroplast development in pear plants. Literature is scarce on the pear genes associated with chloroplast development. Hence, we used the BioEdit software to identify the pear genes that were homologous to the aforementioned genes related to chloroplast development in Arabidopsis and tobacco [42,43,44,45,46,47,48,49]. Based on their homology, the identified pear genes were designated as PbrFtsZ1, PbrARC5, PbrMCD1, PbrPDV2, PbrPIC1, PbrVAR2, PbrCDF1, PbrCDP1, and PbrPDM4. Of these, we observed no discernable differences in the expressions of PbrMCD1 and PbrPDV2 in control and OE spots, but the remaining genes were markedly upregulated in the latter (Fig. 9e), indicating that the development of chloroplast in the spots was also more or less stimulated. Altogether, these findings presented that PbrGA2ox-induced Chl accumulation was primarily dependent on improved chloroplast development, but not the Chl synthesis pathway.


Discovery of the GA2ox gene family in pear

Chl is a dominant pigment in plants and plays a vital role in photosynthesis [3]. It harvests light and converts it into chemical energy to facilitate the growth and development of plants [57]. Hence, Chl accumulation helps enhance photosynthesis, promote plant growth, and thus improve crop productivity [4]. GA2oxs are key players in GA inactivation [7], with critical roles in plant growth and development [58, 59]. Several previous studies have shown that besides regulating seed germination, plant flowering, and morphogenesis [9, 16], GA2oxs also modulate the Chl accumulation in many plants [17, 18, 20, 22, 24]. However, the role of GA2oxs in the Chl accumulation of pear is still unknown. Even the pear GA2oxs have not yet been identified. Therefore, identifying the pear GA2ox members and their role in Chl accumulation is of great significance.

In this study, a total of 13 PbrGA2oxs in pear were isolated and characterized based on their homology with AtGA2oxs (Fig. 1). The isolated PbrGA2oxs were divided into three classes (I, II, and III) based on the phylogenetic analysis. Classes I, II, and III comprised three, three, and seven members, respectively (Fig. S1a in Additional File 1), which followed the previous evolutionary works on GA2oxs [9, 10, 12]. Protein domain analysis revealed that the distribution pattern of the PLN02984 and PLN02156 domains across PbrGA2ox was similar to that of the AtGA2oxs [9] (Fig. 1a), suggesting a deterministic role of these domains in gene function. In addition, motif analysis uncovered the presence of a set of 10 motifs in PbrGA2oxs (Fig. 1b), several of which are identical to those found in GA2oxs of maize [12], rice [11], and Arabidopsis [9], implying a specific function of GA2oxs in plants. However, among the 10 identified motifs, only one motif was common across the 13 PbrGA2oxs (Fig. 1b), indicating functional diversity among PbrGA2oxs. Furthermore, gene structure analyses showed that the average intron length of these 13 PbrGA2oxs was longer than their average exon length (Fig. 1c), offering greater flexibility in terms of exon rearrangement, and thereby conferring the genes with unique function, such as the facilitation of Chl accumulation.

Exploration of PbrGA2ox1-driven Chl accumulation

We established a phylogenetic tree of the PbrGA2ox gene family with multiple other GA2oxs that are known to have participated in Chl accumulation [17,18,19,20,21,22,23,24]. Of these, Pbr025274.1, Pbr009085.1, and Pbr039586.1 exhibited closer relationships with most other GA2oxs, indicating that these might be the key regulators of Chl accumulation in pear (Fig. 1d). Among these three, Pbr025274.1 exhibited the highest expression level in normal pear leaves (Fig. S1b in Additional File 1). It was renamed as PbrGA2ox1 and was further analyzed for its role in Chl accumulation via transient overexpression and silencing in chlorotic and normal pear leaves, respectively (Fig. 2).

Callus and root transformation systems are efficient and rapid genetic transformation methods used to study the gene function in pears [60, 61]. Previous studies have used these systems to study the gene function in pears. However, these studies primarily focused on anthocyanin accumulation [62], stone cell formation [63], and abiotic stress responses [64]. Since the application of these methods has not been reported to assess Chl accumulation, we instead used transgenic tobacco plants with PbrGA2ox1 overexpression for an in-depth analysis of the role of this gene in Chl accumulation. We observed a superior Chl accumulation in the transgenic tobacco plants during dynamic development than in the WT plants (Fig. 3a and b). Furthermore, the OE plants exhibited notably enhanced Pn and Fv/Fm (Fig. 3c, Fig. S2a and h). These findings followed the previous studies stating that plants with the potential for Chl accumulation usually developed a dark green phenotype [65, 66] and typically exhibited better photosynthetic performance [67, 68]. Overall, these results were in line with the observation of transient assay on pear leaves and indicated that PbrGA2ox1 is involved in Chl accumulation, similar to AtGA2ox2 and GhGA2ox1 in Arabidopsis [17] and cotton [21].

Modified pathways in OE tobacco plants

Emerging evidence suggests that GA2oxs are important for Chl accumulation [17,18,19, 21, 22, 24]. However, the underlying mechanisms remain elusive. As a time-saving, sensitive, and efficient technique, transcriptomic analysis has been extensively applied to elucidate the intrinsic mechanisms inherent in the function of several genes [25, 69]. Therefore, to shed light on the regulatory metabolism underlying Chl accumulation mediated by PbrGA2ox1 overexpression, we constructed six cDNA libraries and employed the RNA-seq technique (Fig. 4, Table S2 in Additional File 2). GO enrichment analysis revealed that PrbGA2ox1 primarily regulated the genes involved in molecular function, catalytic activity, and lipid metabolic/biosynthetic processes (Fig. 4e, Fig. S4a in Additional File 1). In addition, the KEGG analysis showed that the modified genes were enriched in metabolism, genetic information, processing, and environmental information processing (Fig. 4f, Fig. S4b in Additional File 1). Furthermore, compared to the WT plants, the OE plants exhibited profound alterations in plant hormone signal transduction and starch and sucrose metabolic pathways (Fig. 5), which might be responsible for the dark green color of the leaves of OE plants.

Altered hormone signaling might account for PbrGA2ox1-promoted Chl built-up

Phytohormones are small molecules that modulate diverse physiological and cellular responses and play crucial roles in mediating Chl accumulation [70, 71]. Extensive investigations have revealed the positive roles of IAA, CTK, GA, and SA [72,73,74,75], and the negative roles of ETH, JA, and ABA in Chl accumulation [76,77,78]. However, Previous studies reported a marked decline in the Chl content in oil palm [79] and Arabidopsis [80] following GA3 and IAA treatments, respectively. On the other hand, some studies reported a marked elevation in the Chl level in Chinese cabbage [81] and citrus [82] after exogenous application of appropriate doses of ABA and MeJA, respectively. Moreover, wheat with markedly reduced active CTK due to the overexpression of cZOGT1, a cis-zeatin-O-glucosyltransferase gene, indeed displayed greener phenotypes than non-transformed plants [83]. These findings indicated that the impact of plant hormones on Chl accumulation varies widely based on the plant species and the dosages used.

In the current study, our results support that ABA, SA, and JA facilitated, and IAA, CTK, GA, and ETH inhibited Chl accumulation in plants, which was inferred from the observation of significantly declined contents of IAA, CTK, GA, and ACC, and the prominently escalated abundances of ABA, SA, and MeJA in the OE plants compared to WT plants (Fig. 8 a, b, c, d, e, f, g, h, and i). In agreement with the inference, we also found impaired IAA and ETH signaling, and enhanced ABA, SA, and JA signaling in OE plants compared to WT plants, as evident by the dramatically up-regulated expression of core repressors in IAA (AUX/IAA) and ETH signaling (ETR) and master facilitators in ABA (SnRK), JA (TGA), and JA signaling (JAR1) (Fig. 5a). Namely, PbrGA2ox1-stimulated Chl accumulation was found to be partially associated with hormone metabolism and signaling. Moreover, as plant growth regulators, IAA, GA, and CTK favor plant development, while ABA and JA restrict plant growth [84,85,86]. Thus, these changes in the levels of IAA, GA, CTK, ABA, and JA in OE plants (Fig. 8a, b, c, d, e, g, h, and i) could well explain the cause of the dwarfism among these plants.

Increased sugar levels might account for the PbrGA2ox1-sponsored Chl accumulation

In addition to the variations in hormonal levels, we also noted a striking reduction in starch and sucrose contents within the OE plants than the WT plants, followed by a pronounced rise in amylase activity and the levels of soluble and reducing sugar content (Fig. 8k, l, m, n, and o, Fig. S8a in Additional File 1). In line with the altered sugar content, we also observed a great upregulation of the genes responsible for starch and sucrose metabolism, such as NbTPS, NbAMY, NbCEL, and NbBAM in the OE plants (Fig. 5b, Fig. S8b, c in Additional File 1). These results suggested a significantly intensified conversion from polysaccharides to monosaccharides in the OE plants, which could partly explain the advanced starch and sucrose degradation in the greener OE plants (Fig. 8k, l, and m). For cost reasons, we could not concretely determine the contents of the respective components of the reducing and soluble sugars. However, the main sugars that exist in tobacco are glucose, fructose, and sucrose [87]. It’s well established that glucose and sucrose exhibit dual roles in mediating Chl accumulation in a dose- and species-dependent manner [88,89,90,91,92,93]. Therefore, alteration in the levels of endogenous sugars might be another key factor contributing to the Chl accumulation in the OE plants. Based on the obtained results, we speculate an accelerating and a suppressive effect of glucose and sucrose in Chl built-up, respectively. Nevertheless, few studies have focused on the effects of fructose on Chl content. Hence, we could not speculate on the relationship between fructose and Chl accumulation. These aspects need to be further investigated.

PbrGA2ox1-stimulated Chl accumulation primarily depends on the enhanced chloroplast development

Chl biosynthesis is an intricate process involving at least 15 enzymes encoded by more than 20 genes [94, 95]. An enhancement or weakening of any of these processes due to the overexpression or silencing of the related genes can considerably affect Chl levels in plants, resulting in yellow − dark green leaves [96, 97]. However, in the present work, we discovered that only three of these Chl biosynthetic genes were differentially expressed between OE and WT plants (Fig. 6a, Fig. S9 in Additional File 1), implying that PbrGA2ox1 overexpression has limited effects on enhancing the Chl synthesis system. Moreover, ABA/JA/SA- and sugar-induced Chl accumulation was also poorly correlated with the Chl biosynthesis.

The chloroplast is a central site for a myriad of fundamental cellular processes to take place. It is most well recognized for its role in Chl biosynthesis [41, 44]. Previous studies have reported that the Chl content in plants is tightly linked to the chloroplast development in the cells, including its biosynthesis and division (size and number), and integrity (morphology) [98, 99]. These characteristics are regulated by multiple chloroplast-encoded structural genes and nuclear-localized transcriptional genes [43, 44]. Consequently, we speculated that Chl accumulation in OE plants is closely associated with chloroplast development in these plants. Our analyses revealed a significant upregulation of the genes related to chloroplast development in OE plants compared to WT plants, in particular, NbPDV1, NbMCD1B, NbPIC1, NbPDM4 and NbCGF1A/1B (Fig. 6b). These results suggested more developed chloroplasts in OE plants than in WT plants. Consistently, compared to WT plants, we observed more chloroplasts per cell in OE plants, and the chloroplasts were better‐organized with denser thylakoids (Fig. 9a, b, and c). Though the chloroplasts in the OE plants were smaller than those in the WT plants (Fig. 9d), the number of chloroplasts per area in OE plants might be greater owing to the diminished cell size in these OE plants (Fig. S9 in Additional File 1). It further provides an opportunity for the OE plants to accumulate more Chl. These data aligned with the previous reports that proposed the positive effects of chloroplast size, number, and integrity on Chl accumulation [100, 101].

We could not analyze, in detail, the chloroplast ultrastructure in pear leaves suspended in the infiltration buffer containing PbrGA2ox1-targeted strains. However, these leaf samples exhibited notable upregulation of PbrFtsZ1, PbrARC5, PbrPIC1, PbrVAR2, PbrCDF1, PbrCDP1, and PbrPDM4 (Fig. 9e). These results are in agreement with the prior documented functions of PDV, MCD, VAR, PIC1, PDM, and CGF in regulating chloroplast development [42, 45,46,47,48,49]. These outcomes further proved that well-developed chloroplasts facilitate Chl accumulation [99, 101, 102]. On the whole, our results revealed a key mechanism underlying enhanced Chl accumulation in OE plants.

Beyond those, hormones and sucrose have been stated to critically influence chloroplast development [43, 103]. For instance, ABA and sucrose have respectively been found to positively and negatively regulate both thylakoid granum stacks and chloroplast differentiation [103, 104], which was in line with the denser thylakoid, dominantly increased ABA content, and strikingly declined sucrose content in the OE plants in the current study (Fig. 8e and m, Fig. 9e). Therefore, we deduced that modified metabolisms of hormones, starch, and sucrose might be involved in chloroplast development. Cumulatively, PbrGA2ox1 promotes Chl accumulation primarily by promoting chloroplast development, with a focus on the intensification of the thylakoid membrane.


In summary, a total of 13 PbrGA2oxs belonging to three subclusters were isolated and characterized from the pear database. Of these, PbrGA2ox1 was identified as a positive regulator of pear Chl accumulation. It was found to alter the composition of hormones and saccharides and modulate the expression of genes involved in chloroplast development, thereby mediating the relevant signaling pathways and comprehensively stimulating the proliferation and intensification of chloroplasts. This, in turn, typically provides more and better sites for Chl synthesis, ultimately resulting in enhanced Chl accumulation (Fig. 10). Collectively, our results show that PbrGA2ox1 contributes to Chl accumulation and provides evidence for enhanced chloroplast development as the core pathway underlying GA2oxs-promoted Chl accumulation in plants.

Fig. 10
figure 10

Schematic model showing the potential mechanism underlying PbrGA2ox1-induced chlorophyll accumulation in tobacco plants. WT, wild-type tobacco plants; OE, PbrGA2ox1-overexpresing tobacco plants; ACC, 1-aminocyclopropyl-1-carboxylic acid; SA, salicylic acid; ABA, abscisic acid; BGA, bioactive gibberellin; IAA, indoleacetic acid; MeJA, methyl jasmonate; 2365–40-4, N6-(delta2-isopentenyl) adenine; 7724–76-7, N6-(delta2-isopentenyl) adenosine. The red font and red arrows indicate a higher level and a faster conversion process, respectively, whereas the blue font and blue arrows imply a lower level and a slower conversion process, respectively. The tobacco model was accessed from the BioRender online website (

Materials and methods

Plant materials and growth conditions

All experiments were carried out with the permission of the relevant agencies or farmers in charge. Chlorotic and normal pear leaves use were obtained from four-year-old Japanese pear ‘Akizuki’ (Pyrus pyrifolia Nakai) plants in the open field of the Xiaoxian County, Anhui Province, China, and 55-year-old local ‘Dangshansuli’ (P. bretschneideri Rehd.) plants grafted onto ‘Duli’ (P. betulaefolia Bunge.) tree rootstocks in the open field of the Dangshan County, Anhui Province, China, respectively. The chlorosis of pear plants usually occurs due to improper management and excessive fertilizer use. All plants were positioned and pruned in an open area and spaced 4 m apart within rows at 6 m intervals, with crops in between them. In addition, for green leaves, two-month-old self-rooted ‘Duli’ plants were sprouted from the seeds obtained from the fruit tree teaching practice base of Anhui Agricultural University. All seeds were sand-stored in a refrigerator (4℃) for at least two months before being planted in pots filled with steam‐sterilized soil and raised in a growth chamber until further use.

Tobacco (N. benthamiana), obtained from the School of Horticulture, Anhui Agricultural University, Hefei City, Anhui Province, China, was used as the WT tobacco in this study. Previously obtained PbrGA2ox1-overexpressing (OE) plants in the WT background [31] were introduced in this study. The seeds from these plants were sown in pots containing steam‐sterilized soil (nutrient soil: vermiculite = 1:1, v/v) and were vernalized for 2 d at 4℃ in the darkness. The pots were then placed in a growth chamber under long-day conditions with a photoperiod of 16 h light/8 h dark (25℃ ± 1℃) under a relative humidity of 80%. Here, white fluorescence (12,000 lx light intensity) light was used. The dynamic growth traits were monitored at 7, 21, 35, and 49 days after vernalization (DAV). The Chl content was analyzed at each recorded point, and the photosynthetic parameters and Chl fluorescence parameters were analyzed at 35 DAV (Fig. 11). The leaf samples extracted at the indicated time points were immediately frozen in liquid nitrogen after collection and stored at − 80℃ for further analysis.

Fig. 11
figure 11

Flowchart of the summarized materials and methods introduced in this paper. The pictures were downloaded from the BioRender ( and Pinclipart online websites ( The numbers alongside the arrows indicate the order in which the experiments were carried out

Identification and fundamental analysis of PbrGA2oxs in pear

The sequences of nine reported Arabidopsis (Arabidopsis thaliana) GA2ox proteins (GA2oxs) [9] were accessed from TAIR ( The sequences were selected as the seed sequences (Table S1 in Additional File 2) to obtain the orthologs against the Chines white pear database ( using the TBtools software with a threshold of E-value ≤ 1e−5. The structural domains and motifs of the putative proteins were confirmed using the Batch CD-Search ( and MEME tools (, respectively. Based on the analytical results, PbrGA2oxs were ultimately isolated by eliminating the proteins with incomplete or duplicated sequences. Finally, a neighbor-likelihood (NL) phylogenetic tree was constructed in MEGA 7.0 software with bootstrap replications set to 1000 among the identified PbrGA2oxs with the nine AtGA2oxs. TBtools software was applied to visualize the conserved domains, motifs, and structures of PbrGA2oxs (Fig. 11). To identify the candidate PbrGA2oxs that might be involved in Chl accumulation, another NL phylogenetic tree was built using the identified PbrGA2oxs and other GA2oxs that are known to be involved in Chl accumulation. The tree was visualized using either MS PowerPoint 2016 or the EvolView tool (

Vector construction and transiently transformation

To induce transient overexpression in pear leaves, the full-length PbrGA2ox1 gene without the stop codon was amplified using the primer pair PbrGA2ox1-EGFP-F/R (Table S5 in Additional File 2) and framed into the p1300-EGFP vector digested at XbaI and BamHI sites to generate overexpression fusion constructs PbrGA2ox1_OE with upstream CaMV 35S promoter, termed as 35S: PbrGA2ox1 in our previous work [30]. Then, the PbrGA2ox1_OE fusion vector was transformed into the Agrobacterium tumefaciens GV3101-pSoup cells via thermal stimulation. The cells carrying either the fusion vector or the empty vector (EV) were grown on Luria–Bertani (LB) liquid medium at 28℃ until OD600 = 0.9. Then the cells were collected and resuspended at OD600 = 0.9 in infiltration buffer containing 10 mM MgCl2, 10 mM 4-morpholineethanesulfonic acid, and 0.2 mM acetosyringone, and placed in the dark for 2 − 3 h without shaking [105]. Next, the cell culture was infiltrated into the leaves of ‘Dangshansuli’ and ‘Akizuki’ pear plants using needle syringes. The infiltration experiments were conducted at nightfall to facilitate strain infection.

For virus-induced PbrGA2ox1 silencing in pear and tobacco leaves, tobacco rattle virus (TRV) was introduced, where an expression vector pTRV2 and an auxiliary vector pTRV1 must be used in conjunction. Briefly, approximately 400 bp conserved fragment of the target gene was cloned using PbrGA2ox1-TRV-F/R primer pair (Table S5 in Additional File 2) and inserted into the pTRV2 vector digested at BamHI and XbaI sites to produce the silencing fusion vector PbrGA2ox1_TRV2, along with the strong 35S promoter upstream (Fig. 11). The corresponding infiltration buffers carrying PbrGA2ox1_TRV2 vector, empty vector pTRV2 (TRV2), and pTRV1 were obtained as described previously for 35S: PbrGA2ox1. pTRV1 was incubated with an equal volume of either PbrGA2ox1_TRV2 or TRV2, followed by incubation in the dark for 2 − 3 h. Then, the cultures were separately infiltrated into 40-day-old ‘Duli’ pear green leaves and 35-day-old tobacco leaf epidermis using needle syringes [105, 106]. After undergoing Agro-infiltration for approximately 14 d, all the samples were collected and photographed using a camera at the end point time. Subsequently, the Chl contents were detected. At least two biological replicates were prepared and investigated for each treatment.

Determination of Chl, photosynthetic parameters, and Chl fluorescence parameters

The Chl levels of the leaves were qualitatively analyzed as described previously with some modifications [107]. A portable photosynthesis meter (CIRAS-3, PP Systems, Boston, USA) was used to compare the net photosynthetic rate (Pn), stomatal conductance (Gs), transpiration rate (Tr), intercellular CO2 concentration (Ci), and water use efficiency (WUE, WUE = Pn/Tr) of WT and OE plants at 35 DAV based on the method previously described by Tan et al. [108]. All measurements were conducted during 9:00 a.m.–11:00 a.m. on a sunny day. The operation parameters comprised relative humidity of 75%, a cuvette flow rate of 300 cc∙min−1, leaf temperature of 25 ± 1℃, leaf-to-air vapor pressure deficit (VPD) of 2.0 − 3.5 kPa, atmospheric CO2 concentration of 400 μM, and actinic light intensity of 1200 μmol∙m−2∙s−1 photosynthetic photon flux density (PPFD). A mixture of red (90%), blue (5%), and white (5%) LEDs were used as the light source in the leaf chamber (Fig. 11). All data were logged after test stabilization, and at least three measurements were recorded for each test.

Apart from these, a portable JUNIOR PAM device (WALZ, Effeltrich, Germany) was applied to determine the Chl fluorescence parameters. The fully expanded leaves of WT and OE plants at 35 DAV were selected and subjected to dark adaptation for 0.5 h before analysis (Fig. 11). The values of minimal fluorescence yield (F0), maximal fluorescence (Fm), maximal quantum yield of PSII (Fv/Fm), photochemical quantum yield of photosystem II [Y(II)], electron transport rate (ETR), photochemical quenching (qp), and quantum yield of regulated energy dissipation [Y(NPQ)] of the dark-adapted leaves were directly acquired after specific analysis using WinControl-3 software [109]. Three independent analyses were conducted for each plant.

Detection of hormone levels

To find out the differences in hormones metabolism, the concentrations of indole-3-Acetic acid (IAA), 1-aminocyclopropane-1-carboxylic acid (ACC), BGAs (GA1+3+4+7), jasmonic acid (JA), jasmonic acid-isoleucine (JA-Ile), methyl jasmonate (MeJA), salicylic acid (SA), abscisic acid (ABA), N6-(delta2-Isopentenyl) adenine, and N6-(delta2-Isopentenyl) adenosine, were detected in the leaves of OE and WT tobacco seedlings at 35 DAV as described previously by Balcke et al. [110] (Fig. 11). In total, a 0.1 g sample was extracted as homogenate using precooled 50% acetonitrile (v/v) at 4 °C using a mixer (TD-20, HIPIE, China). The homogenate was centrifugated at a speed of 12000 rpm at 4 °C for 3 min. The supernatant was purified using a C18 reversed-phase, polymer-based, solid-phase extraction (RP-SPE) cartridge. Then, the cartridge was flushed with 1 mL of 30% acetonitrile (v/v), and the fraction was collected. The fraction was subsequently dehydrated under a gentle stream of nitrogen and dissolved in insert-equipped vials containing 200 μL of 30% acetonitrile (v/v) for UPLC-ESI–MS/MS assay. The operating conditions for the UPLC analysis were set as previously described by Balcke et al. [110]. All experiments were carried out at least thrice per sample.

Quantification of starch, sucrose, reducing sugar, and amylase activities

Sugar and starch contents in plant leaves were determined as described previously [111] with some modifications. Namely, roughly 0.1 g dry tobacco leaf sample at 35 DAV was ground into a powder in the presence of liquid nitrogen. The powder was then mixed with 5 mL of 80% ethanol and homogenized at 200 rpm for 1 h. The homogenate was centrifuged at 12,000 rpm for 10 min at room temperature (RT).

To determine the reducing sugar content, 2 mL of the extracted supernatant was boiled dry and dissolved in distilled water. Then, the solution was mixed with 2 mL of 1% (m/v) 3,5-dinitrosalicylic acid. The absorbance of the solution was recorded at 540 nm using a spectrophotometer (TU-1810PC, PERSEE, Beijing, China). For evaluating soluble sugar content, the supernatant was mixed with an equal volume of chloroform. The centrifuged supernatant (50 μL) was boiled for 15 min with 4.95 mL of anthrone reagent (containing 72% H2SO4, 500 mg∙L−1 anthrone, 10 g∙L−1 thiourea). The absorbance of the reaction mixture was immediately read at 620 nm using a spectrophotometer.

For starch content examination, the precipitate was dextrinized with 2 mL distilled water at 100℃ for 15 min, and mixed with 2 mL of 9.2 M HClO4 after cooling at RT. Then, the fluid mixture was centrifuged at a speed of 8,000 rpm at RT for 10 min to obtain the supernatant (diluted to 25 mL). Finally, 2 mL of the diluted solution was used to quantify starch content using the method adopted for measuring soluble sugar content with a conversion coefficient of 0.9. Starch was visualized in situ using the method previously described by Li et al. [101], where 0.1 M iodine solution (10% potassium iodide + 5% iodine) was applied. The amylase activities were detected according to Zhang et al. [112]. Three biological replicates per plant were examined in each experiment.

Moreover, the resorcinol method was used to measure the sucrose content [111]. Briefly, the aforementioned supernatant in preparation stage was decolorized using approximately 0.1 mg activated carbon powder and transferred into a 10 mL volumetric flask. After that, 1 mL of the decolorized solution was concentrated to 100 µL at 100℃ and mixed with 0.1 mL of 30% (m/v) KOH and again boiled for 10 min. The mixture was then cooled and color-reacted using 3 mL of anthrone reagent at 40℃ for 15 min, the absorbance of the reaction buffer was immediately recorded at 620 nm. At least three biological replicates per plant were accessed. All aforementioned experiments could be seen in Fig. 11.

RNA isolation and sequencing

Leaves from three biological replicates of normally grown WT and OE transgenic tobacco plants at 35 DAV were selected for total RNA isolation using the Trizol reagent kit (R4801-01, Magen, Guangdong, China) following the manufacturer’s instructions. The concentration and quality of the total RNA isolated from each sample were measured by Nanodrop2000 (Thermo, Walsham, USA) at OD260 and OD280 (OD260/280 = 1.9 − 2.1). The integrity of the RNA was then verified by RNase-free agarose-gel electrophoresis, and the RNA Integrity Number (RIN) was determined by Agilent5300 (Agilent, California, USA). A total of 1 μg qualified RNA per sample was employed to construct cDNA libraries and sequences. The raw reads generated on the Illumina system were first trimmed and quality controlled by removing the adapters, paired reads with ˃10% unknown nucleotides (N), and low-quality primary sequences with a quality rating of < 50% (Q-value < 20) using FASTQ preprocessor ( The clean reads were then separately mapped to the reference genome ( The transcript expression level was statistically calculated and quantified as the number of fragments per kilobase of transcript per million mapped reads (FPKM). The differently expressed genes (DEGs) in comparison groups OE vs. WT were summarized according to the negative binomial distribution using the DESeq2 ( under the screening criteria of p-value < 0.05 and |Fold Change (FC, OE/WT)|≥ 1.5. The total number of DEGs and the upregulated and downregulated genes were subsequently counted (Fig. 11). The ChiPlot online tool ( and the software Graph Prism v.7.0 were used to construct the expression heatmap of DEGs.

Functional analysis of DEGs

The screened DEGs were annotated against the following public protein databases Diamond v0.8.37.99 ( and ID mapping tool ( Non-redundant (NR,, Pfam (, Swiss-Prot (, and Clusters of Orthologous Groups of proteins (COG, All annotated genes were subsequently subjected to functional enrichment analysis of Gene Ontology (GO, terms, and the Kyoto Encyclopedia of Genes and Genomes (KEGG, pathway enrichments, which were implemented using the GOATOOLS v1.2.4 ( and the KOBAS v2.0 software (, respectively. The enriched functional terms and pathways for the tested DEGs were regarded as ones with P-adjust < 0.05. Additionally, the STEM software ( was used to cluster the expression profiles of the DEGs based on their normalized log2|FPKMOE/WT| values (Fig. 11).

Gene expression analysis with quantitative real-time polymerase chain reaction (qRT-PCR)

The first-strand cDNAs were synthesized from the corresponding RNA using a fluorescence reverse transcription kit with genomic DNA (gDNA) remover (R323, Vazyme, Nanjing, China), and qRT-PCR was conducted on an ABI StepOne qRT-PCR detection system (Applied Biosystems, Foster City, CA, USA) to calculate the target gene expressions with three biological replicates (Fig. 11). Arabidopsis homologous genes in pear and tobacco plants were screened using the BioEdit v7.0.9 software. The sequences of the related genes were obtained against the genome of the Chinese white pear and the genome of N. attenuate. 14 tobacco genes were selected for qRT-PCR validation. Gene-specific primer pairs were designed using the Primer Premier 5.0 software. The primers are listed in Tables S4 and S5 in Additional File 2. Tobacco actin (NbActin) and pear actin (PbrActin) genes were used as the internal controls for the normalization of gene expression. The 2−ΔΔCt method was used to calculate the relative gene expression [113].

Chloroplast collection and transmission electron microscopy

To visualize the differences in chloroplast development of OE and WT plants, the chloroplasts in the fourth leaves from the top (area of each leaf ≈ 10 cm2) of WT and OE seedlings at 35 DAV were collected as described previously [114] with some modification (Fig. 11). The acquired fraction containing chloroplasts was subsequently resuspended in an equal volume of chloroplast storage buffer (330 mM sorbitol + 50 mM HEPES–KOH, pH 8), and photographed. The chloroplast ultrastructure was observed by following previous work [98] (Fig. 11). Briefly, the leaves of WT and OE plants at 35 DAV were excised and fixed in the TEM fixative under a vacuum. After ethanol dehydration, the samples were embedded in Spurr resin and were cut into ultrathin sections using an ultramicrotome (EMUC6, Leica, Wetzlar, Germany). Then, the prepared sections were examined, and the images were captured using a transmission electron microscope (H-7650, Hitachi, Tokyo, Japan). To this end, the number of chromoplasts per cell for WT and OE lines was compared using ImageJ, and the size of chromoplasts was manually counted. In addition, the cell morphology of OE and WT lines was investigated using a conventional inverted microscope, and the cell size was subsequently measured using the ImageJ software.

Statistical analysis

Unless specifically addressed, all the data in the present study are represented as mean ± standard deviation (SD) of at least three independent replicates. Microsoft Excel software (Version, 2017) was used for drawing histograms. The significance of differences was evaluated using Graph Prism v7.0 by one-way analysis of variance (ANOVA) followed by Tukey’s test, as indicated by asterisks or ‘ns’ (no significance). The level of the bars’ significance was determined by p < 0.05.

Availability of data and materials

The data that support the results of this study are available from the corresponding author upon reasonable request. The result of RNA-seq was archived in the National Center for Biotechnology Information (NCBI) BioProject under the accession number PRJNA1031366.


  1. Li X, Li X, Wang T, Gao W. Chapter 24 - nutritional composition of pear cultivars (Pyrus spp). Nutritional composition of fruit cultivars. Academic press, Elseiver; 2016. p. 573–608.

  2. Huang GJ, Peng SB, Li Y. Variation of photosynthesis during plant evolution and domestication: implications for improving crop photosynthesis. J Exp Bot. 2022;73(14):4886–96.

    Article  PubMed  CAS  Google Scholar 

  3. Croft H, Chen JM, Luo XZ, Bartlett P, Chen B, Staebler R. Leaf chlorophyll content as a proxy for leaf photosynthetic capacity. Global Change Bio. 2017;23:3513–24.

    Article  ADS  Google Scholar 

  4. Simkin AJ, Kapoor L, Doss CJP, Hofmann TA, Lawson T, Ramamoorthy S. The role of photosynthesis-related pigments in light harvesting, photoprotection and enhancement of photosynthetic yield in planta. Photosynth Res. 2022;152:23–42.

    Article  PubMed  CAS  Google Scholar 

  5. Leister D. Enhancing the light reactions of photosynthesis: strategies, controversies, and perspectives. Mol Plant. 2023;16(1):4–22.

    Article  PubMed  CAS  Google Scholar 

  6. Olszewski N, Sun TP, Gubler F. Gibberellin signaling: biosynthesis, catabolism, and response pathways. Plant Cell. 2002;14(Suppl 1):61-S80.

    Article  Google Scholar 

  7. Hedden P. The current status of research on gibberellin biosynthesis. Plant Cell Physiol. 2020;61:1832–49.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Daviere JM, Achard P. Gibberellin signaling in plants. Development. 2013;140(6):1147–51.

    Article  PubMed  CAS  Google Scholar 

  9. Li C, Zheng LL, Wang XN, Hu ZB, Zheng Y, Chen QH, Hao XC, Xiao X, Wang XB, Wang GD, Zhang YH. Comprehensive expression analysis of Arabidopsis GA2-oxidase genes and their functional insights. Plant Sci. 2019;285:1–13.

    Article  PubMed  CAS  Google Scholar 

  10. Chen S, Wang XJ, Zhang LY, Lin SS, Li DC, Wang QZ, Cai SY, Ei-Tanbouly R, Gan LJ, Li Y. Identification and characterization of tomato gibberellin 2-oxidases (GA2oxs) and effects of fruit-specific SlGA2ox1 overexpression on fruit and seed growth and development. Hortic Res. 2016;3:16059.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Zhang C, Nie X, Kong W, Deng X, Sun T, Liu X, Li Y. Genome-wide identification and evolution analysis of the gibberellin oxidase gene family in six gramineae crops. Genes. 2022;13(5): 863.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Li YD, Shan XH, Jiang ZL, Zhao L, Jin FX. Genome-wide identification and expression analysis of the GA2ox gene family in maize (Zea mays L.) under various abiotic stress conditions. Plant Physiol Bioch. 2021;166:621–33.

    Article  CAS  Google Scholar 

  13. Zhang SW, Gottschalk C, Nocker SV. Conservation and divergence of expression of GA2-oxidase homeologs in apple (Malus × Domestica Borkh.). Front. Plant Sci. 2023;14:1117069.

    Google Scholar 

  14. Wuddineh WA, Mazarei M, Zhang J, Poovaiah CR, Mann DG, Ziebell A, Sykes RW, Davis MF, Udvardi MK, Stewart CJ. Identification and overexpression of gibberellin 2-oxidase (GA2ox) in switchgrass (Panicum virgatum L.) for improved plant architecture and reduced biomass recalcitrance. Plant Biotechnol J. 2015;13:636–47.

    Article  PubMed  CAS  Google Scholar 

  15. Schomburg FM, Bizzell CM, Lee DJ, Zeevaart JAD, Amasino RM. Overexpression of a novel class of gibberellin 2-oxidases decreases gibberellin levels and creates dwarf plants. Plant Cell. 2003;15(1):151–63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  16. Otani M, Meguro S, Gondaira H, Hayashi M, Saito M, Han DS, Inthima P, Supaibulwatana K, Mori S, Jikumaru Y, Kamiya Y, Li T, Niki T, Nishijima T, Koshioka M, Nakano M. Overexpression of the gibberellin 2-oxidase gene from Torenia fournieri induces dwarf phenotypes in the liliaceous monocotyledon Tricyrtis sp. J Plant Physiol. 2013;170(6):1416–23.

    Article  PubMed  CAS  Google Scholar 

  17. Yan JD, Xiang FJ, Yang P, Zhong M, He RQ, Li XM, Peng WS, Liu XM, Zhao XY. Overexpression of BnGA2ox2, a rapeseed gibberellin 2-oxidase, causes dwarfism and increased chlorophyll and anthocyanin accumulation in Arabidopsis and rapeseed. Plant Growth Regul. 2021;93:65–77.

    Article  CAS  Google Scholar 

  18. Yan JD, Liao XY, He RQ, Zhong M, Feng PP, Li XM, Tang DY, Liu XM, Zhao XY. Ectopic expression of GA 2-oxidase 6 from rapeseed (Brassica napus L.) causes dwarfism, late flowering and enhanced chlorophyll accumulation in Arabidopsis thaliana. Plant Physiol Bioch. 2017;111:10–9.

    Article  CAS  Google Scholar 

  19. Tan PH, Zhang L, Yin SX, Teng K. Heterologous expression of a novel Poa pratensis gibberellin 2-oxidase gene, PpGA2ox, caused dwarfism, late flowering, and increased chlorophyll accumulation in Arabidopsis. Biol Plant. 2018;60(3):462–70.

    Article  Google Scholar 

  20. Dijkstra C, Adams E, Bhattacharya A, Page AF, Anthony P, Kourmpetli S, Power JB, Lowe KC, Thomas SG, Hedden P, Phillips AL, Davey MR. Overexpression of a gibberellin 2-oxidase gene from Phaseolus coccineus L. enhances gibberellin inactivation and induces dwarfism in Solanum species. Plant Cell Rep. 2008;27:463–70.

    Article  PubMed  CAS  Google Scholar 

  21. Shi JB, Wang N, Zhou H, Xu QH, Yan GT. The role of gibberellin synthase gene GhGA2ox1 in upland cotton (Gossypium hirsutum L.) responses to drought and salt stress. Biotechnol Appl Bioc. 2019;66(3):298–308.

    Article  CAS  Google Scholar 

  22. Zhou B, Peng D, Lin JZ, Huang XQ, Peng WS, He RQ, Guo M, Tang DY, Zhao XY, Liu XM. Heterologous expression of a gibberellin 2-oxidase gene from Arabidopsis thaliana enhanced the photosynthesis capacity in Brassica napus L. J Plant Biol. 2010;54:23–32.

    Article  Google Scholar 

  23. Zhou B, Lin J, Peng W, Peng D, Zhuo YH, Zhu DF, Huang XQ, Tang DY, Guo M, He RQ, Zhang JZ, Li XS, Zhao XY, Liu XM. Dwarfism in Brassica napus L. induced by the over-expression of a gibberellin 2-oxidase gene from Arabidopsis thaliana. Mol Breed. 2012;29:115–27.

    Article  CAS  Google Scholar 

  24. Chen ZQ, Liu Y, Yin YJ, Liu Q, Li N, Li X, He WZ, Hao DY, Li XG, Guo CH. Expression of AtGA2ox1 enhances drought tolerance in maize. Plant Growth Regul. 2019;59:203–15.

    Article  Google Scholar 

  25. Tyagi P, Singh D, Mathur S, Singh A, Ranjan R. Upcoming progress of transcriptomics studies on plants: an overview. Front Plant Sci. 2022;13: 1030890.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Shen YY, Zhuang WB, Tu X, GaoZH, Xiong AS, Yu XY, Li XH, Li FH, Qu SC. Transcriptomic analysis of interstock-induced dwarfism in Sweet Persimmon (Diospyros kaki Thunb). Hortic Res. 2019;6:51.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Liu YH, Li YM, Liu Z, Wang L, Bi ZZ, Sun C, Yao PF, Zhang JL, Zeng YT. Integrated transcriptomic and metabolomic analysis revealed altitude-related regulatory mechanisms on flavonoid accumulation in potato tubers. Food Res Int. 2023;170:112997.

    Article  PubMed  CAS  Google Scholar 

  28. Yuan Y, Ren SY, Liu XF, Su LY, Wu Y, Zhang W, Li Y, Jiang YD, Wang HH, Fu R, Bouzayen M, Liu MC, Zhang Y. SlWRKY35 positively regulates carotenoid biosynthesis by activating the MEP pathway in tomato fruit. New Phytol. 2022;234(1):164–78.

    Article  PubMed  CAS  Google Scholar 

  29. Li R, Yan D, Tan CY, Li C, Song MJ, Zhao QQ, Yang YM, Yin WJ, Li ZD, Ren XL, Liu CH. Transcriptome and metabolomics integrated analysis reveals MdMYB94 associated with esters biosynthesis in apple (Malus × Domestica). J Agr Food Chem. 2023;71(20):7904–20.

    Article  CAS  Google Scholar 

  30. Zhang ZY, Tao L, Gao YD, Suo JW, Yu WY, Hu YY, Wei CY, Farag MA, Wu JS, Song LL. Transcription factors TgbHLH95 and TgbZIP44 cotarget terpene biosynthesis gene TgGPPS in Torreya grandis nuts. Plant Physiol. 2023;9(2):1161–1117.

    Article  Google Scholar 

  31. Guo GL, Zhang HY, Dong WY, Xu B, Wang YY, Zhao QC, Liu L, Tang XM, Liu L, Ye ZF, Heng W, Zhu LW, Jia B. Overexpression of PbrGA2ox1 enhances pear drought tolerance through regulation of GA3-inhibited reactive oxygen species detoxification and abscisic acid signaling. J Integr Agr. 2024.

    Article  Google Scholar 

  32. Duan JJ, Fu BC, Kang HM, Song ZQ, Jia ML, Cao DM, Wei AL. Response of gas-exchange characteristics and chlorophyll fluorescence to acute sulfur dioxide exposure in landscape plants. Ecotox Environ Safe. 2018;171:122–9.

    Article  Google Scholar 

  33. Zhang Y, Liu GJ. Effects of cesium accumulation on chlorophyll content and fluorescence of Brassica juncea L. J Environ Radioactiv. 2018;195:26–32.

    Article  CAS  Google Scholar 

  34. Bhagooli R, Mattan-Moorgaw S, Kaullysin D, Louis YD, Gopeechun A, Ramah S, Soondur M, Pilly SS, Beesoo R, Wijayanti DP, Bachok ZB, Monras VC, Casareto BE, Suzuki Y, Baker AC. Chlorophyll fluorescence - A tool to assess photosynthetic performance and stress photophysiology in symbiotic marine invertebrates and seaplants. Mar Pollut Bull. 2021;165:112059.

    Article  PubMed  CAS  Google Scholar 

  35. Tang CJ, Luo MZ, Zhang S, Jia GQ, Tang S, Jia YC, Zhi H, Diao XM. Variations in chlorophyll content, stomatal conductance, and photosynthesis in Setaria EMS mutants. J Integr Agr. 2022;22(6):1618–30.

    Article  Google Scholar 

  36. Mellor SB, Behrendorff JBYH, Ipsen JØ, Crocoll C, Laursen T, Gillam EMJ, Pribil M. Exploiting photosynthesis-driven P450 activity to produce indican in tobacco chloroplasts. Front. Plant Sci. 2023;13:104917.

    Google Scholar 

  37. Sato A, Yamamoto KT. Overexpression of the non-canonical Aux/IAA genes causes auxin-related aberrant phenotypes in Arabidopsis. Physiol Plant. 2008;133(2):397–405.

    Article  PubMed  CAS  Google Scholar 

  38. Wang Y, Diao PF, Kong LQ, Yu RN, Zhang M, Zuo TT, Fan YY, Niu YD, Yan F, Wuriyanghan H. Ethylene enhances seed germination and seedling growth under salinity by reducing oxidative stress and promoting chlorophyll content via ETR2 pathway. Front Plant Sci. 2020;11:1066.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wang Y, Yu YT, Zhang HB, Huo YZ, Liu XQ, Che YH, Wang JC, Sun G, Zhang HH. The phytotoxicity of exposure to two polybrominated diphenyl ethers (BDE47 and BDE209) on photosynthesis and the response of the hormone signaling and ROS scavenging system in tobacco leaves. J Hazard Mater. 2022;426:128012.

    Article  PubMed  CAS  Google Scholar 

  40. Wang JC, Song JQ, Qi HL, Zhang HJ, Wang L, Zhang HB, Cui CC, Muhammad S, Sun GY, Zhang HH. Overexpression of 2-Cys Peroxiredoxin alleviates the NaHCO3 stress-induced photoinhibition and reactive oxygen species damage of tobacco. Plant Physiol Bioch. 2023;201:107876.

    Article  CAS  Google Scholar 

  41. Roston R, Jouhet J, Yu F, Gao HB. Editorial: structure and function of chloroplasts. Front. Plant Sci. 2018;9:1656.

    Google Scholar 

  42. Gong X, Guo CH, Terachi T, Cai HS, Yu DS. Tobacco PIC1 mediates iron transport and regulates chloroplast development. Plant Mol Biol Rep. 2015;33:401–13.

    Article  CAS  Google Scholar 

  43. Chen C, Mac-Cready JS, Ducat D, Osteryoung KW. The molecular machinery of chloroplast division. Plant Physiol. 2018;176(1):138–51.

    Article  PubMed  CAS  Google Scholar 

  44. Cackett L, Luginbuehl LH, Schreier TB, Lopez-Juez E, Hibberd JM. Chloroplast development in green plant tissues: the interplay between light, hormone, and transcriptional regulation. New Phytol. 2021;233(5):2000–16.

    Article  PubMed  Google Scholar 

  45. Chen L, Sun B, Gao W, Zhang QY, Yuan H, Zhang M. MCD1 associates with FtsZ filaments via the membrane-tethering protein ARC6 to guide chloroplast division. Plant Cell. 2018;30(8):1807–23.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Qi YF, Wang XM, Lei P, Li HM, Yan LR, Zhao J, Meng JJ, Shao JX, An LJ, Yu F, Liu XY. The chloroplast metalloproteases VAR2 and EGY1 act synergistically to regulate chloroplast development in Arabidopsis. J Biol Chem. 2020;295(4):1036–46.

    Article  PubMed  Google Scholar 

  47. Sun B, Zhang QY, Yuan H, Gao W, Han B, Zhang M. PDV1 and PDV2 differentially affect remodeling and assembly of the chloroplast DRP5B ring. Plant Physiol. 2020;182:1966–78.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  48. Wang XW, Zhao LR, Man Y, Li XJ, Wang L, Xiao J. PDM4, a pentatricopeptide repeat protein, affects chloroplast gene expression and chloroplast development in Arabidopsis thaliana. Front Plant Sci. 2020;11:1198.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Zhu RM, Chai S, Zhang ZZ, Ma CL, Zhang Y, Li S. Arabidopsis chloroplast protein for growth and fertility1 (CGF1) and CGF2 are essential for chloroplast development and female gametogenesis. BMC Plant Biol. 2020;20:172.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Zhou J, Guo JH, Chen QS, Wang BS, He XD, Zhuge Q, Wang P. Different color regulation mechanism in willow barks determined using integrated metabolomics and transcriptomics analyses. BMC Plant Biol. 2022;22:530.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  51. Zou SC, Zhuo MG, Abbas F, Hu GB, Wang HC, Huang XM. Transcription factor LcNAC002 coregulates chlorophyll degradation and anthocyanin biosynthesis in litchi. Plant Physiol. 2023;192(3):1913–27.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Jiang YJ, Liang G, Yu DQ. Activated expression of WRKY57 confers drought tolerance in Arabidopsis. Mol Plant. 2015;5(6):1375–88.

    Article  Google Scholar 

  53. Sakuma Y, Maruyama K, Osakabe Y, Qin F, Seki M, Shinozaki K, Yamaguchi-Shinozaki K. Functional analysis of an Arabidopsis transcription factor, DREB2A, involved in drought-responsive gene expression. Plant Cell. 2006;18(5):1292–309.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  54. Jin J, Essemine J, Xu Z, Duan JL, Shan C, Mei ZL, Zhu J, Cai WM. Arabidopsis ETHYLENE INSENSITIVE 3 directly regulates the expression of PG1β-like family genes in response to aluminum stress. J Exp Bot. 2022;73(14):4923–40.

    Article  PubMed  CAS  Google Scholar 

  55. Vanderauwera S, Vandenbroucke K, Inze A, Cotte BVD, Mühlenbock P, Rycke RD, Naouar R, Gaever TV, Montagu MCEV, Breusegem FV. AtWRKY15 perturbation abolishes the mitochondrial stress response that steers osmotic stress tolerance in Arabidopsis. P Natl Acad Sci USA. 2012;109(49):20113–8.

    Article  ADS  CAS  Google Scholar 

  56. Monroe JD, Storm AR. Review: The Arabidopsis β-amylase (BAM) gene family: diversity of form and function. Plant Sci. 2018;276:163–70.

    Article  PubMed  CAS  Google Scholar 

  57. Govindjee, Shevela D, Bjorn LO. Evolution of the Z-scheme of photosynthesis: a perspective. Photosynth Res. 2017;133:5–15.

    Article  PubMed  CAS  Google Scholar 

  58. Lo SF, Ho TD, Liu YL, Jiang MJ, Hsieh KT, Chen KT, Yu LC, Lee MH, Chen CY, Huang TP, Kojima M, Sakakibara H, Chen LJ, Yu SM. Ectopic expression of specific GA2 oxidase mutants promotes yield and stress tolerance in rice. Plant Biotechnol J. 2017;15:850–64.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Tian XL, Xia XC, Xu DA, Liu YQ, Xie L, Hassan MA, Song J, Li FJ, Wang DS, Zhang Y, Hao YF, Li GY, Chu CC, He ZH, Cao SH. Rht24b, an ancient variation of TaGA2ox-A9, reduces plant height without yield penalty in wheat. New Phytol. 2021;233(2):738–50.

    Article  PubMed  Google Scholar 

  60. Yang YJ, Wang DF, Wang CS, Wang XH, Li JN, Wang R. Construction of high efficiency regeneration and transformation systems of Pyrus ussuriensis Maxim. Plant Cell Tiss Org. 2017;131:139–50.

    Article  CAS  Google Scholar 

  61. Xiao YX, Zhang SC, Liu Y, Chen Y, Zhai R, Yang CQ, Wang ZG, Ma FW, Xu LF. Efficient Agrobacterium-mediated genetic transformation using cotyledons, hypocotyls and roots of ‘Duli’ (Pyrus Betulifolia Bunge). Sci Hortic. 2022;296:110906.

    Article  CAS  Google Scholar 

  62. Liu HN, Pei MS, Wu H, Shun Q, Su J, Lin-Wang K, Allan AC, Espley RV. The PyPIF5-PymiR156a-PySPL9-PyMYB114/MYB10 module regulates light-induced anthocyanin biosynthesis in red pear. Mol Hortic. 2021;1:14.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  63. Xue YS, Shan YF, Yao JL, Wang RZ, Xu SZ, Liu DL, Ye ZC, Lin J, Li XG, Xue C, Wu J. The transcription factor PbrMYB24 regulates lignin and cellulose biosynthesis in stone cells of pear fruits. Plant Physiol. 2023;192(3):1997–2014.

    Article  PubMed  CAS  Google Scholar 

  64. Liu Y, Yang TY, Lin ZK, Gu BJ, Xing GH, Zhao LY, Dong HZ, Gao JZ, Xie ZH, Zhang SL, Huang XS. A WRKY transcription factor PbrWRKY53 from Pyrus betulaefolia is involved in drought tolerance and AsA accumulation. Plant Biotechnol J. 2019;17(9):1770–87.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  65. Ampomah-Dwamena C, Thrimawithana AH, Dejnoprat S, Lewis D, Espley RV, Allan AC. A kiwifruit (Actinidia deliciosa) R2R3-MYB transcription factor modulates chlorophyll and carotenoid accumulation. New Phytol. 2018;221(1):309–25.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Li J, Gong J, Zhang LC, Shen H, Chen GP, Xie QL, Hu ZL. Overexpression of SlPRE5, an atypical bHLH transcription factor, affects plant morphology and chlorophyll accumulation in tomato. J Plant Physiol. 2022;273:153698.

    Article  PubMed  CAS  Google Scholar 

  67. Gang HX, Li RH, Zhao YM, Liu GF, Chen S, Jiang. Loss of GLK1 transcription factor function reveals new insights in chlorophyll biosynthesis and chloroplast development. J Exp Bot. 2019;70(12):3125–38.

    Article  PubMed  CAS  Google Scholar 

  68. Yu Y, He RH, Chen S, Zhang HJ, Zhang X, Wang XY, Liu ZJ, Li ZL, Wang YT, Liu WW, Gang HX, Chen S. The B-box transcription factor PabBBX27 in the regulation of chlorophyll biosynthesis and photosynthesis in poplar (Populus alba × P. Berolinensis). Ind Crop Prod. 2023;203:117159.

    Article  CAS  Google Scholar 

  69. Lowe R, Shirley N, Bleackley M, Dolan S, Shafee T. Transcriptomics technologies. PloS Comput Biol. 2017;13: e1005457.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  70. Liu XQ, Li Y, Zhong SW. Interplay between light and plant hormones in the control of Arabidopsis seedling chlorophyll biosynthesis. Front Plant Sci. 2017;8:1433.

    Article  PubMed  PubMed Central  Google Scholar 

  71. Kuai BK, Chen JY, Hottenstenier S. The biochemistry and molecular biology of chlorophyll breakdown. J Exp Bot. 2017;69(4):751–67.

    Article  Google Scholar 

  72. Dong YJ, Wan YS, Liu FZ, Zhuge YP. Effects of exogenous SA supplied with different approaches on growth, chlorophyll content and antioxidant enzymes of peanut growing on calcareous soil. J Plant Nutr. 2019;42(16):1869–83.

    Article  CAS  Google Scholar 

  73. Huan YN, Yang L, Liu Q, Liao MA, Wang ZH, Liang H, Tang Y, Lv XL, Wang J. Effects of indole acetic acid on the growth and selenium absorption characteristics of Cyphomandra betacea seedlings. Acta Physiol Plant. 2021;43:74.

    Article  CAS  Google Scholar 

  74. Keawmanee N, Ma G, Zhang LC, Yahata M, Murakami K, Yamamoto M, Kojima N, Kato M. Exogenous gibberellin induced regreening through the regulation of chlorophyll and carotenoid metabolism in Valencia oranges. Plant Physiol Bioch. 2022;173:14–24.

    Article  CAS  Google Scholar 

  75. Song YF, Li CX, Guo P, Wang Q, Zhang L, Wang ZH, Di H. Overexpression of ZmIPT2 gene delays leaf senescence and improves grain yield in maize. Front Plant Sci. 2022;13:963873.

    Article  PubMed  PubMed Central  Google Scholar 

  76. Zhu XY, Chen JY, Xie ZK, Gao J, Ren GD, Gao S, Zhou X, Kuai BK. Jasmonic acid promotes degreening via MYC2/3/4-and ANAC019/055/072-mediated regulation of major chlorophyll catabolic genes. Plant J. 2015;84(3):597–610.

    Article  PubMed  CAS  Google Scholar 

  77. Gao S, Gao J, Zhu XY, Li ZP, Ren GD, Zhou X, Kuai BK. ABF2, ABF3, and ABF4 promote ABA-mediated chlorophyll degradation and leaf senescence by transcriptional activation of chlorophyll catabolic genes and senescence-associated genes in Arabidopsis. Mol Plant. 2016;9(9):1272–85.

    Article  PubMed  CAS  Google Scholar 

  78. Wei Y, Jin JT, Xu YX, Liu WT, Yang GX, Bu HD, Li T, Wang AD. Ethylene-activated MdPUB24 mediates ubiquitination of MdBEL7 to promote chlorophyll degradation in apple fruit. Plant J. 2021;108(1):169–82.

    Article  PubMed  CAS  Google Scholar 

  79. Chai SK, Ooi SE, Ho CL, Ong-Abdullah M, Chan KL, Fitrianto A, Namasivayam P. Transcriptomic analysis reveals suppression of photosynthesis and chlorophyll synthesis following gibberellic acid treatment on oil palm (Elaies guineensis). J Plant Growth Regul. 2023;42:5683–99.

    Article  CAS  Google Scholar 

  80. Luo WG, Liang QW, Su Y, Huang C, Mo BX, Yu Y, Xiao LT. Auxin inhibits chlorophyll accumulation through ARF7-IAA14-mediated repression of chlorophyll biosynthesis genes in Arabidopsis. Front Plant Sci. 2023;14: 1172059.

    Article  PubMed  PubMed Central  Google Scholar 

  81. Thiruvengadam M, Kim SH, Chung IM. Exogenous phytohormones increase the accumulation of health-promoting metabolites, and influence the expression patterns of biosynthesis related genes and biological activity in Chinese cabbage (Brassica rapa Spp. Pekinensis). Sci Hortic. 2015;193:136–46.

  82. Qiu X, Xu YH, Xiong B, Dai L, Huang SJ, Dong TT, Sun GC, Liao L, Deng QX, Wang X, Zhu J, Wang ZH. Effects of exogenous methyl jasmonate on the synthesis of endogenous jasmonates and the regulation of photosynthesis in citrus. Physiol Plant. 2020;170(3):398–414.

    Article  PubMed  CAS  Google Scholar 

  83. Wang WQ, Zhang GQ, Wang WL, Wang AG, Lv YL, Guo FX, Di YD, Zhang JF, Wang YH, Wang W, Li YY, Hao QQ. Wheat cis-zeatin-O-glucosyltransferase cZOGT1 interacts with the Ca2+-dependent lipid binding protein TaZIP to regulate senescence. J Exp Bot. 2023;74(21):6619–30.

    Article  PubMed  CAS  Google Scholar 

  84. Santner A, Calderon-Villalobos LIA, Estelle M. Plant hormones are versatile chemical regulators of plant growth. Nat Chem Biol. 2009;5:301–7.

    Article  PubMed  CAS  Google Scholar 

  85. Yoshida T, Christmann A, Yamaguchi-Shinozaki K, Grill E, Fernie AR. Revisiting the basal role of ABA – roles outside of stress. Trends Plant Sci. 2019;24:625–35.

    Article  PubMed  CAS  Google Scholar 

  86. Waadt B. Phytohormone signaling mechanisms and genetic methods for their modulation and detection. Curr Opin Plant Biol. 2020;57:3140.

    Article  Google Scholar 

  87. Drapal M, Enfissi EMA, Fraser PD. Metabolic changes in leaves of N. Tabacum and N. benthamiana during plant development. J Plant Physiol. 2021;265:153–486.

    Article  Google Scholar 

  88. Momose T, Ozeki Y. Regulatory effect of stems on sucrose-induced chlorophyll degradation and anthocyanin synthesis in Egeria densa leaves. J Plant Res. 2023;126:859–67.

    Article  Google Scholar 

  89. Sami F, Hayat S. Effect of glucose on the morpho-physiology, photosynthetic efficiency, antioxidant system, and carbohydrate metabolism in Brassica juncea. Protoplasma. 2019;256:213–26.

    Article  PubMed  CAS  Google Scholar 

  90. Mortain-Bertrand A, Stammitti L, Telef N, Colardelle P, Brouquisse R, Rolin D, Gallusci P. Effects of exogenous glucose on carotenoid accumulation in tomato leaves. Physiol Plant. 2008;34(2):46–256.

    Google Scholar 

  91. Sunitibala Y, Gupta S, Mukherjee BB. Effect of sucrose on growth and chlorophyll synthesis of teak shoots in mixotrophic culture. J Plant Biochem Biotechnol. 2012;7:57–9.

    Article  Google Scholar 

  92. Aono Y, Asikin Y, Wang N, Tieman D, Klee H, Kusano M. High-throughput chlorophyll and carotenoid profiling reveals positive associations with sugar and apocarotenoid volatile content in fruits of tomato varieties in modern and wild accessions. Metabolites. 2021;11: 398.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Song XH, Guo HH, Liu Y, Wan FF, Zhang J, Chang XH. Effects of salicylic acid and sucrose on pigment content in Pistacia chinensis leaves. Sci Hortic. 2020;259: 108783.

    Article  CAS  Google Scholar 

  94. Gough SR, Westergren T, Hansson M. Chlorophyll biosynthesis in higher plants. Regulatory aspects of 5-Aminolevulinate formation. J Plant Biol. 2003;46:135–60.

    Article  CAS  Google Scholar 

  95. Beale SI. Green genes gleaned. Trends Plant Sci. 2005;10:309–12.

    Article  PubMed  CAS  Google Scholar 

  96. Papenbrock J, Pfundel E, Grimm B. Decreased and increased expression of the subunit CHL I diminish mg chelatase activity and reduces chlorophyll synthesis in transgenic tobacco plants. Plant J. 2000;22(2):155–64.

    Article  PubMed  CAS  Google Scholar 

  97. Li Q, Zhou SZ, Liu WY, Zhai ZZ, Pan YT, Liu CC, Chern M, Wang HW, Huang M, Zhang ZX, Tang JH, Du HW. A chlorophyll a oxygenase 1 gene ZmCAO1 contributes to grain yield and waterlogging tolerance in maize. J Exp Bot. 2021;72(8):3155–67.

    Article  PubMed  CAS  Google Scholar 

  98. Kirchhoff H. Chloroplast ultrastructure in plants. New Phytol. 2019;223(2):565–74.

    Article  PubMed  Google Scholar 

  99. Chang J, Zhang FY, Qin HY, Liu P, Wang JF, Wu S. Mutation of SlARC6 leads to tissue-specific defects in chloroplast development in tomato. Hortic Res. 2021;8:127.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  100. Meng LH, Fan ZQ, Zhang Q, Wang CC, Gao Y, Deng YK, Zhu BZ, Zhu HL, Chen JY, Shan W, Yin XR, Zhong SL, Grierson D, Jiang CZ, Luo YB, Fu DQ. BEL1-LIKE HOMEODOMAIN 11 regulates chloroplast development and chlorophyll synthesis in tomato fruit. Plant J. 2018;94(6):1126–40.

    Article  PubMed  CAS  Google Scholar 

  101. Liu GZ, Yu HY, Li CX, Ye J, Chen WF, Wang Y, Ge PF, Zhang JH, Ye ZB, Zhang YY. SlRCM1, which encodes tomato lutescent1, is required for chlorophyll synthesis and chloroplast development in fruits. Hortic Res. 2021;8:128.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  102. Li J, Chen G, Zhang J, Shen H, Kang J, Feng PP, Xie QL, Hu ZL. Suppression of a hexokinase gene, SlHXK1, leads to accelerated leaf senescence and stunted plant growth in tomato. Plant Sci. 2020;298: 110544.

    Article  PubMed  CAS  Google Scholar 

  103. Dingenen JV, Milde LD, Vermeersch M, Maleux K, Rycke RD, Bruyne MD, Storme V, Gonzalez N, Dhondt S, Inze D. Chloroplasts are central players in sugar-induced leaf growth. Plant Physiol. 2016;171:590–605.

    Article  PubMed  PubMed Central  Google Scholar 

  104. Deng JH, Jiao Q, Wang Y, Lei T, Ding ZL, Wang J, Jiang XY, Zhang FW. Transcriptomic and metabolomic effects of exogenous ABA application on tobacco seedling growth. Plant Growth Regul. 2023;101:399–414.

    Article  CAS  Google Scholar 

  105. Xue C, Yao JL, Qin MF, Zhang MY, Allan AC, Wang DF, Wu J. Pbrmir397a regulates lignification during stone cell development in pear fruit. Plant Biotechnol J. 2019;17(1):103–17.

    Article  PubMed  CAS  Google Scholar 

  106. Velasquez AC, Chakravarthy S, Martin GB. Virus-induced gene silencing (VIGS) in Nicotiana benthamiana and tomato. J Vis Exp. 2009;28:e1292.

    Google Scholar 

  107. Zhou Y, Fan XL, Lin YJ, Chen H. Determination of chlorophyll content in rice. Bio. 2018;101:e1010147.

    Google Scholar 

  108. Tan W, Meng QW, Brestic M, Olsovska K, Yang YH. Photosynthesis is improved by exogenous calcium in heat-stressed tobacco plants. J Plant Physiol. 2011;168(17):2063–71.

    Article  PubMed  CAS  Google Scholar 

  109. Farag M, Najeeb U, Yang J, Hu ZY, Fang ZM. Nitric oxide protects carbon assimilation process of watermelon from boron-induced oxidative injury. Plant Physiol Bioch. 2017;111:166–73.

    Article  CAS  Google Scholar 

  110. Balcke GU, Handrick V, Bergau N, Fichtner M, Henning A, Stellmach H, Tissier A, Hause B, Frolov A. An UPLC-MS/MS method for highly sensitive high-throughput analysis of phytohormones in plant tissues. Plant Methods. 2012;8: 47.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Han YY, Xu TY, Chen H, Tang M. Sugar metabolism and 14-3-3 protein genes expression induced by arbuscular mycorrhizal fungi and phosphorus addition to response drought stress in Populus cathayana. J Plant Physiol. 2023;288: 154075.

    Article  PubMed  CAS  Google Scholar 

  112. Zhang Y, Zhu J, Khan M, Wang Y, Xiao W, Fang T, Qu j, Xiao P, Li CL, Liu JH. Transcription factors ABF4 and ABR1 synergistically regulate amylase-mediated starch catabolism in drought tolerance. Plant Physiol. 2023;191(1):591–609.

    Article  PubMed  CAS  Google Scholar 

  113. Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) method. Methods. 2020;25:402–8.

    Article  Google Scholar 

  114. Ho J, Theg SW. The formation of stromules in vitro from chloroplasts isolated from Nicotiana Benthamiana. PLoS ONE. 2016;11(2):e0146489.

    Article  PubMed  PubMed Central  Google Scholar 

Download references


The authors sincerely thank Prof. Wei Heng (Anhui Agricultural University), Zhenfeng Ye (Anhui Agricultural University), Assoc. Prof. Liu Li (Anhui Agricultural University) for their technical guidance and assistance with the revision of this paper. The authors would like to appreciate Prof. Yinghua Zhu from the School of Agronomy of Anhui Agricultural University for kindly providing the portable JUNIOR PAM device and thank Yutian Shi, Feng Xiong, and Charlesworth ( for their linguistic assistance during the preparation of this manuscript.


This work was supported by the China Agriculture Research System (CARS-28-14) and Scientific Research Projects for Postgraduates of Anhui Universities (YJS20210207).

Author information

Authors and Affiliations



JB conceptualized and oversaw the experiments. TXM, LL, and ZLW helped design partial experiments and helped with plot and figure preparation. GGL performed most of the experiments. LL and STJ contributed to the performance of measurement and analysis of physiological indicators. WHZ, ZSQ, SY, and XGY analyzed the data and RNA-seq results. GGL wrote the original draft. TXM, LL, ZLW, and JB critically reviewed and edited the manuscript. JB and GGL were responsible for the supervision and funding acquisition. All authors read and approved the manuscript.

Corresponding author

Correspondence to Bing Jia.

Ethics declarations

Ethics approval and consent to participate

All field experiments were carried out with the permission of the relevant agencies or farmers in charge. For green leaves, two-month-old self-rooted ‘Duli’ plants were sprouted from the seeds obtained from the fruit tree teaching practice base of Anhui Agricultural University. Tobacco (Nicotiana benthamiana), obtained from the School of Horticulture, Anhui Agricultural University, Hefei City, Anhui Province, China, was introduced in this study. All the experiments were carried out in accordance with relevant guidelines and regulations.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Guo, G., Liu, L., Shen, T. et al. Genome-wide identification of GA2ox genes family and analysis of PbrGA2ox1-mediated enhanced chlorophyll accumulation by promoting chloroplast development in pear. BMC Plant Biol 24, 166 (2024).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: