SBP‐Box Transcription Factor JcSPL9 Regulates Both Seed Yield and Oil Content in the Biofuel Plant Jatropha curcas

ABSTRACT

Jatropha curcas is a promising feedstock for biodiesel and bio‐jet fuels production; however, its seed yield is constrained by limited inflorescences. SPL9 is a member of the SBP‐box gene family that promotes the juvenile‐to‐adult phase transition. Accumulating evidence demonstrated that the miR156/SPL module plays important roles in regulating diverse plant developmental processes. Here, we reveal that JcSPL9 regulates both seed yield and oil content in Jatropha. JcSPL9 is highly expressed in fruits and upregulated with age in Jatropha. Overexpression of miR156‐resistant JcSPL9 (rJcSPL9) significantly increased seed yield and oil content, whereas overexpression of JcmiR156a had the opposite effects. The highest seed yield in rJcSPL9 transgenic plants was 80.76% greater than that in the WT plants, with a concomitant 12.6% increase in seed oil content. Correspondingly, JcmiR156a transgenic plants displayed 51.67% lower seed yield and 8.28% lower seed oil content compared to WT. Additionally, seed oil fatty acid composition was significantly altered in both rJcSPL9 and JcmiR156a transgenic Jatropha and Arabidopsis, as well as in Arabidopsis spl9 mutants. The key oil biosynthesis genes, including JcWRI1, JcDGAT1, JcDGAT2, and JcOLEOSIN, were upregulated in rJcSPL9 transgenic seeds but downregulated in JcmiR156a transformants. This study provides the first evidence that the miR156/SPL9 module regulates lipid accumulation and fatty acid biosynthesis in seeds. These results highlight SPL9 as a promising target for enhancing oil yield and quality in Jatropha and other oilseed crops.

Abbreviations

AP1

APETALA1

AP2

APETALA2

CaMV

cauliflower mosaic virus

DU

degree of unsaturation

FA

fatty acid

FT

FLOWERING LOCUS T

FUL

FRUITFULL

IPA1

IDEAL PLANT ARCHITECTURE 1

KRN

KERNEL ROW NUMBER

LD

long‐day conditions

LFY

LEAFY

OS

oxidative stability

qRT‐PCR

quantitative reverse transcription polymerase chain reaction

SBP

SQUAMOSA PROMOTER BINDING PROTEIN

SOC1

SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1

SPL

SQUAMOSA PROMOTER BINDING PROTEIN‐LIKE

tsh4

tasselsheath4

UB3

Unbranched3

WAP

week‐after‐pollination

WFP

WEALTHY FARMER'S PANICLE

1. Introduction

The American Department of Energy predicted that global demand for energy would increase by approximately 35% between 2005 and 2030 (Sun et al. 2017). With the decreasing availability of fossil fuels and the increasing trend of environmental pollution, biodiesel has garnered significant attention as an alternative fuel (Ali et al. 2020; Mardhiah et al. 2017; Mofijur et al. 2016). The use of sustainable biofuels as a source of energy is predicted to be a major contributor to future threats to food security. The use of agricultural plants such as maize, rice, and soybean as feedstocks for large‐scale biofuel production would also conflict with food production, causing food supply shortages, increased food prices, and ethical conflicts (Callegari et al. 2020; Marriott et al. 2016). One potential solution to the food crisis is to produce biofuels from plant species capable of growing on marginal lands (Kazamia and Smith 2014; Sun et al. 2017).

Jatropha curcas (hereafter referred to as Jatropha), a perennial woody plant species that belongs to the Euphorbiaceae family, is monoecious, with male and female flowers borne on the same inflorescence (Divakara et al. 2010; Pandey et al. 2012; Wu et al. 2011). This species has been propagated as a staple biodiesel and bio‐jet fuels crop because of its multipurpose value, including its high oil content, high biomass productivity, adaptability to marginal lands under a variety of agro‐climatic conditions, and lack of competition with food production (Akashi 2012; Alherbawi et al. 2021; Khalil et al. 2013; Mardhiah et al. 2017; Pandey et al. 2012; Pua et al. 2011). However, the potential of Jatropha as a biofuel plant is limited by its low seed production (Akagi et al. 2019). Jatropha exhibits an overabundance of vegetative shoots and leaves; thus, a reduction in undesired vegetative growth is imperative (Ghosh et al. 2010; Tjeuw et al. 2015). In addition, poor flowering and branching are important factors that contribute to low seed productivity in crop species (Cui et al. 2014; Divakara et al. 2010). Several strategies have been reported to improve the seed production of Jatropha, including promotion of early flowering through JcFT overexpression flowering time (Ye et al. 2014), interspecific crossing with Jatropha integerrima (Bai et al. 2025), cytokinin‐mediated increases in female flower numbers (Pan et al. 2016; Pan and Xu 2011), and JcARF19 overexpression to increase seed size (Sun et al. 2017).

In the plant kingdom, microRNA (miR) 156 and miR172 play pivotal regulatory roles in the transition from the vegetative to the reproductive phase (Akagi et al. 2014; Carles and Fletcher 2003; Cheng et al. 2021; Gao et al. 2025). The transcription of miR172 is positively regulated by SQUAMOSA PROMOTER BINDING PROTEIN‐LIKE 9 (SPL9) and SPL10 (Wu et al. 2009). Moreover, SPLs are the direct targets of miR156 (Fornara and Coupland 2009); thus, SPL is involved in a miR156 and miR172 signalling cascade (Yu et al. 2015). In Arabidopsis, miR156 is highly expressed during early shoot development but decreases as the plants develop, while SPL9 exhibits an inverse temporal expression pattern (Axtell and Bowman 2008; Wu et al. 2009). Similar patterns were observed in the expression of these two genes in woody species such as Acacia confusa , Acacia colei, Eucalyptus globulus , Hedera helix , and Quercus acutissima (Wang et al. 2011). Members of the SPL family, which represent a class of plant‐specific transcription factors, influence the juvenile‐to‐adult phase transition (Bu et al. 2025; Carles and Fletcher 2003; Hu et al. 2023; Li et al. 2023; Schwab et al. 2005). SPL genes have been found in nearly all plant species, including algae and moss. All members of the SPL family contain a highly conserved DNA‐binding domain (SBP domain) that is 76 amino acids in length (Wang and Wang 2015).

There are 16 members of the SPL family in Arabidopsis (Chuck et al. 2007). Overexpression of miR156, which downregulates AtSPL genes, prolongs the juvenile phase. Constitutive overexpression of different AtSPLs accelerates the juvenile‐to‐adult phase transition (Wang et al. 2009; Wu et al. 2009; Zhao, Liu, et al. 2022), and AtSPL9, AtSP13, and AtSPL15 play more important roles in this process than do other SPLs (Wang et al. 2021; Xu et al. 2016). AtSPL9 directly activates the expression of miR172b to facilitate flowering by suppressing the APETALA2 (AP2) protein (Aukerman and Sakai 2003; Wang et al. 2009), which is also involved in seed‐related phenotypes, such as seed mass, yield, and oil biosynthesis (Jofuku et al. 2005). In addition, AtSPL9 is involved in the regulation of plastochron length and organ size, response to stress, the repression of adventitious root development, anthocyanin biosynthesis, cauline leaf identity, and trichome distribution (Cui et al. 2014; Manuela et al. 2025; Rankenberg et al. 2021; Stief et al. 2014; Wang et al. 2008; Xu et al. 2016; Yu et al. 2010; Zhao, Shi, et al. 2022). Overexpression of SPL9 can also accelerate flowering in rice ( Oryza sativa ) and Chinese cabbage (Luo et al. 2012; Wang et al. 2014). SPL9 homologues from a basal eudicot tree species ( Platanus acerifolia ) can induce early flowering in Arabidopsis (Han et al. 2016). In the tree species Fortunella hindsii , the miR156‐SPL module regulated the initial phases of somatic embryogenesis induction (Long et al. 2018).

Of the 19 SPL genes in the rice genome, OsSPL14, which is also known as ideal plant architecture 1 (IPA1) or WFP (WEALTHY FARMER'S PANICLE), is the most similar to AtSPL9 (Xie et al. 2006). Many studies have shown that enhanced expression of OsSPL14 increased panicle branching and grain weight together with increased culm strength (Giaume and Fornara 2021; Jiao et al. 2010; Miura et al. 2010; Wang et al. 2018, 2015; Zhang et al. 2017). And Wang et al. (2018) demonstrated that OsSPL14 promotes both yield and immunity in rice. In maize, Unbranched3 (UB3), an orthologue of OsSPL14, is responsible for the quantitative variation in kernel row number by negatively modulating the size of the inflorescence meristem; moreover, ub3 mutants present increased kernel row numbers and decreased branching (Du et al. 2017; Liu et al. 2015). Moderate expression of UB3 suppressed tillering slightly but promoted panicle branching, resulting in increased grain number per panicle in rice (Du et al. 2017; Li, Wang, et al. 2022). Recently, Cao et al. (2021) showed that the wheat TaSPL14 also regulated spike development and thousand‐grain weight. In soybean, four GmSPL9 genes redundantly regulate plant architecture (Bao et al. 2019). SPL9 and SPL13 bind to the promoters of BOP1/BOP2 directly to repress their expression, resulting in delayed establishment of proliferative regions in leaves, which promotes more blade outgrowth and suppresses petiole development (Hu et al. 2023).

Jatropha is a perennial plant that has vigorous vegetative growth but relatively poor reproductive growth and low seed yield (Ghosh et al. 2010; Li, Wang, et al. 2022). 15 JcSPL genes were identified in Jatropha, but only JcSPL3 was ectopically expressed in Arabidopsis (Yu et al. 2020). As mentioned above, SPL9 in Arabidopsis (AtSPL9) promotes flowering; and AtSPL9 orthologues in rice, maize, and wheat are involved in the control of seed yield (Cao et al. 2021; Chuck et al. 2014; Giaume and Fornara 2021; Jiao et al. 2010; Miura et al. 2010; Wu et al. 2009). In the Euphorbiaceae family, MeSPL9 clustered with MeSPL15 in the same branch, and overexpression of rMeSPL9 increased the soluble sugar of cassava (Li, Cheng, et al. 2022). The phylogenetic analysis of the SPL family in Jatropha exhibited that JcSPL9 clustered in an individual branch (Yu et al. 2020). Therefore, Jatropha SPL9 (JcSPL9), an orthologue of AtSPL9, may also play an important role in promoting reproductive growth in Jatropha. In this study, we cloned JcSPL9 and analysed its roles in growth and development in Jatropha. We demonstrate that JcSPL9 regulates both seed yield and oil content. In particular, we provide the first evidence that miR156/SPL module plays a role in regulating fatty acid biosynthesis and lipid accumulation in seeds.

2. Materials and Methods

2.1. Plant Materials and Growth Conditions

The roots, stems, young and mature leaves, male and female flowers, and fruits of an individual Jatropha tree were collected during the summer from the Xishuangbanna Tropical Botanical Garden (XTBG; 21°54′ N, 101°46′ E, 580 m above sea level) of the Chinese Academy of Sciences located in Mengla County, Yunnan Province, Southwest China. Young transgenic Jatropha plants were grown in a greenhouse. Mature transgenic Jatropha plants were planted in a field plot within the XTBG in 2018–2024. The T1 transgenic Jatropha were germinated in August and transferred into the field in November 2020. The cotyledons and young leaves of different‐age Jatropha were collected from Kunming, Yunnan Province, China. All tissues prepared for real‐time quantitative reverse transcription polymerase chain reaction (qRT‐PCR) were immediately frozen in liquid N₂ and stored at −80°C until use. The phenotypes of T0 and T1 Jatropha plants were analysed. For each Jatropha genotype, more than 25 plants were used for characterisation. The shoot apexes of 5‐month‐old T1 transgenic Jatropha plants and the flower buds of 9‐month‐old T1 transgenic Jatropha plants were harvested to analyse mRNA transcription levels. spl9‐4 mutant and spl9‐4 spl15‐1 double mutant Arabidopsis seeds were purchased from the TAIR website (https://www.arabidopsis.org/). The wild type, mutants, and transgenic Arabidopsis were germinated on 1/2 MS medium over a one‐week period, after which seedlings were transferred to peat soil in plant growth chambers at 22°C ± 2°C under long‐day (LD) (16 h light/8 h dark) conditions. For each Arabidopsis genotype, more than 50 plants were used for collecting seeds.

2.2. Cloning of miR156‐Resistant JcSPL9 ( rJcSPL9 ) cDNA

Total RNA was extracted from young leaves of Jatropha in accordance with the protocol described by Ding et al. (2008). First‐strand cDNA was synthesised using Moloney murine leukemia virus (M‐MLV) reverse transcriptase according to the manufacturer's instructions (TAKARA, Dalian, China). The PCR primers used for cloning of rJcSPL9 were designed according to the predicted cDNA sequence of JcSPL9 in Jatropha Genome Database (ID: Jcr4S01955.50 or XM_012232354; http://www.kazusa.or.jp/jatropha/) (Sato et al. 2011). All primers used in this research are listed in Table S3. The first round of PCR was amplified via the primers XA39/XA42 and XA40/XA41, which yielded two rJcSPL9 fragments with mutations. The full‐length sequences of rJcSPL9 were generated via overlap PCR with the PCR products of the first round by using the primers XA39 and XA40, which introduced KpnI and SalI recognition sites, respectively. JcmiR156a was generated via PCR with genomic DNA as template by using the primer XA43 and XA44, which introduced KpnI and SalI recognition sites. The PCR products were subsequently cloned into pGEM‐T vectors (Promega Corporation, Madison, WI, USA) for sequencing.

2.3. Construction of Overexpression Binary Vector and Plant Transformation

To construct the plant overexpression binary vector 35S:rJcSPL9 and 35S:JcmiR156a, the full‐length cDNA sequences of rJcSPL9 and JcmiR156a were excised from the pGEM‐T vector (Promega) using the restriction enzymes KpnI and SalI, and then cloned into a pOCA30 vector containing the cauliflower mosaic virus (CaMV) 35S promoter, respectively. Transformation of Jatropha was transformed with Agrobacterium strain EHA105 carrying 35S:rJcSPL9 and 35S:JcmiR156a constructs using the protocol previously described by Pan and Xu (2011) and Fu et al. (2015). Transgenic Arabidopsis plants were obtained by Agrobacterium tumefaciens‐mediated floral dip (Clough and Bent 1998). Double overexpression lines were produced by genetic crossing. The hybrid lines were obtained by artificial pollination prior to anthesis. Transgenic plants were verified by genomic PCR and RT‐PCR.

2.4. Real Time Quantitative Reverse Transcription Polymerase Chain Reaction (qRT‐PCR Analysis

Jatropha total RNAs were extracted from frozen tissues as described by Ding et al. (2008). First‐strand cDNA was synthesised from 1 μg of total RNA using the PrimeScript RT Reagent Kit with gDNA Eraser (TAKARA, Dalian, China). The cDNA templates were diluted 5 times with first‐strand cDNA using sterilised double‐distilled water; qRT‐PCR was performed using SYBR Premix Ex Taq II (TAKARA) on a Roche 480 Real‐Time PCR Detection System (Roche Diagnostics, Indianapolis, IN, USA). The primers used for qRT‐PCR are listed in Table S3. qRT‐PCR was performed using three independent biological replicates and three technical replicates per sample. The data were analysed via the 2^−ΔΔCT method as described by Livak and Schmittgen (2001). The transcript levels of specific genes were normalised using the JcActin1 gene (Zhang et al. 2013).

2.5. Analysis of Flower, Fruit, and Seed Phenotypes

The flower and fruit anatomy were examined and imaged with a Leica DFC425 camera (Leica, Heerbrugg, Switzerland) equipped with a light Leica DM IRB anatomical lens (Leica). The fruit length and width as well as the seed length, width, and height were measured with an electronic Vernier calliper (to 0.1 mm), and seed weight was measured via an electronic balance. The Arabidopsis seed length and width were measured using the analyses function of Leica software.

2.6. Analysis of Stem Components

Two‐month‐old T1 transgenic Jatropha seedlings growing in the greenhouse were harvested to measure the diameter of their middle stems. The stems were stained with 5% potassium permanganate solution (KMnO₄) and 5% red ink (Akagi et al. 2018). The stems were then measured for their phloem, xylem, and pith thickness to calculate the areas of the phloem, xylem, and pith, respectively.

2.7. Seed Oil Determination by Soxhlet Extraction Method

Seed oil content was measured by AOAC method no. 920.85 (AOAC 1990) with an automatic Soxhlet apparatus (Soxtec 2050, FOSS, Denmark) following the manufacturer's guidelines. The Jatropha seed kernels and Arabidopsis seeds were ground using a Philips mill and passed through a 16‐mesh sieve. The dried seed powder (0.8–2.5 g) was packed in a thimble and the oil was extracted with petroleum ether (boiling point: 60°C–90°C) for 1.5 h. Upon completion of the oil extraction, the oil was dried at 105°C for 5 h to remove residual water and petroleum ether. The oil content of the samples was calculated on the basis of dry weight of the seeds using the following equation:

$$\text{Oil content}\left(\mathrm{mg}/\mathrm{g}\right)=\left[\left(W_b-W_a\right)\times 1000\right]/\text{kernel powder weight}$$

where W _a was the weight of empty flask and W _b refers to weight of flask containing the extracted oil.

2.8. Seed Oil Determination by Time‐Domain Nuclear Magnetic Resonance (TD‐NMR)

TD‐NMR determination of seed oil content was carried out with the minispec mq‐one Seed Analyser (Bruker Optik GmbH, Ettlingen, Germany), equipped with a sample tube of 40‐mm diameter. For oil determination in Jatropha seeds, fresh seeds were dried at 65°C until constant weight (for about 48 h), whereas dry seeds with moisture contents less than 5% were used without drying. A calibration curve was obtained from reference samples of oil extracted by Soxhlet method from mature seeds of Jatropha.

2.9. Determination of Fatty Acid Composition by Gas Chromatography–Mass Spectrometry (GC–MS)

Approximately 100 μL of Jatropha or Arabidopsis seed oil was converted to methyl esters with 1 mL of methanol‐sulfuric acid (2.5 M) under 70°Cin a thermostat water bath for 30 min (Khayoon et al. 2012). Then, the crude methyl esters were extracted with 1 mL of hexane before being injected into the GC. The individual fatty acid methyl esters were analysed by an Agilent Technologies 7890A gas chromatograph, equipped with mass spectrometer 5975C (Agilent Technologies, USA). A polar DB‐WAX capillary column (30 m × 0.25 mm i.d. × 0.25 μm film thickness) (Agilent Technologies, USA) was utilised for the separation. The helium carrier gas flow rate was set at 1 mL/min. One microliter of the sample was injected in the split mode at a ratio of 1:30. The oven temperature was initially held at 40°C for 2 min, and then increased to 220°C at a rate of 5°C/min, and finally maintained at 220°C for 10 min (total run time 48 min). The temperatures of the front inlet, transfer line, and ion source were set at 250°C, 250°C, and 230°C, respectively. The MS was taken at 70 eV with a mass range of m/z 35–500. The identification of each fatty acid methyl ester was confirmed by comparing the mass spectra and retention times with those of authentic standards analysed under the same conditions.

The degree of unsaturation (DU) of seed oil and oxidative stability (OS) of biodiesel were calculated according to Feng et al. (2020) by using the following equations:

$$\begin{array}{cc}\mathrm{DU}=\hfill & \left(\text{monounsaturated}\mathrm{Cn}:1,\%\right)+2\times \left(\text{polyunsaturated}\mathrm{Cn}:2,\%\right)\hfill \\ \hfill & +3\times \left(\text{polyunsaturated}\mathrm{Cn}:3,\%\right)+4\times \left(\text{polyunsaturated}\mathrm{Cn}:4,\%\right);\mathrm{OS}\hfill \\ \hfill & =-0.0384\times \mathrm{DU}+7.770.\hfill \end{array}$$

2.10. Determination of Soluble Sugar by High‐Performance Liquid Chromatography

Weigh ~0.5 g of powdered sample into a centrifuge tube, add 4 mL of deionised water, vortex for 30 s and sonicate at room temperature for 30 min. After centrifugation at 5000 r min⁻¹ for 5 min, transfer the supernatant to a 5 mL volumetric flask, dilute to volume with water, filter through a 0.22 μm aqueous membrane, and analyse sucrose, D‐fructose, and D‐glucose by high‐performance liquid chromatography.

2.11. Analysis of Seed Protein and Starch Contents

The kernel powder was subjected to nitrogen content analysis by the micro‐Kjeldahl method (Bremner 1965), and its protein content was evaluated by multiplying the N content by a conversion constant of 5.75 (Mosse 1990). Total starch content was estimated by the anthrone–sulfuric acid method using a spectrophotometer at 630 nm (Hodge and Hofreiter 1962).

3. Results

3.1. Expression Patterns of JcSPL9 in Jatropha

JcSPL9 expression profiles across Jatropha development stages were determined by qRT‐PCR. The results show that the expression levels of JcSPL9 increased with age (Figure 1A). The lowest expression level occurred in the first leaf of the seedlings; as the age increased, the JcSPL9 expression level increased continuously. The highest expression level occurred in the seedling cotyledons. The second‐highest expression was detected in young leaves of 5‐year‐old flowering Jatropha (Figure 1A). JcSPL9 age‐dependent expression patterns in Jatropha were consistent with those reported in other tree species (Wang et al. 2011). We also examined the JcSPL9 expression levels in different organs of a single Jatropha plant. As shown in Figure 1B, JcSPL9 was expressed in all organs. Expression peaked in fruits, remained high in roots and leaves, and was lowest in stems and female flowers (Figure 1B). These results show that JcSPL9 expression varied considerably across organs and developmental stages in Jatropha, consistent with reports in Arabidopsis vegetative tissues (Wang et al. 2009, 2008). In Arabidopsis, SPL9 mRNA was detected in leaf primordia and declined as leaves matured. In the inflorescence apex, AtSPL9 mRNA was transiently expressed only in the youngest floral primordia (Wang et al. 2009, 2008).

FIGURE 1.

Analysis of the expression patterns of JcSPL9 in Jatropha and prediction of JcmiR156 target site in JcSPL9. (A) Expression levels of JcSPL9 in cotyledons and young leaves of different ages. Co: Cotyledon, FL: The first leaf of Jatropha seedlings, 3 M: Young leaves of 3‐month‐old non‐flowering Jatropha, 6 M: Young leaves of 6‐month‐old non‐flowering Jatropha, 1Y/3Y: Young leaves of 1/3‐year‐old non‐flowering Jatropha, 3YF/5YF: Young leaves of 3/5‐year‐old flowering Jatropha. (B) Expression levels of JcSPL9 in different tissues of a mature Jatropha plant. R: Roots, S: Stems, YL: Young leaves, ML: Mature leaves, MF: Male flowers, FF: Female flowers, Fr: Fruits. The qRT‐PCR results were obtained from three independent biological replicates and three technical replicates for each sample; the error bars showed standard deviation. The levels of detected amplicons were normalised using the amplified products of the JcActin1. (C) Predicted JcmiR156 target positions in JcSPL9 mRNA, the JcSPL9 transcripts resistant to miR156 (rJcSPL9) was generated via mutation of the miR156‐ target site using synonymous codons; rJcSPL9 sequence showed only 12 nucleotides match with miR156.

3.2. 35S: rJcSPL9 Exhibited a Stronger Phenotype Than 35S: JcSPL9 Did in Arabidopsis

miR156‐resistant JcSPL9 (rJcSPL9) was generated by synonymous codon substitution at the miR156 target site. The rJcSPL9 sequence showed only 12 nucleotides complementary toJcmiR156a (Figure 1C), which was insufficient for miR156 recognition. Transgenic Arabidopsis expressing 35S:JcSPL9 and 35S:rJcSPL9 were generated. In this study, 35 lines of 35S:rJcSPL9 transgenic Arabidopsis were obtained; 20 (57%) exhibited early flowering. Line L18, showing the strongest phenotype, was selected for flowering time analysis and genetic crosses. Thirty‐two 35S:JcSPL9 lines were obtained; 5 (16%) showed early flowering, with line L11 selected for further analysis. Then the 35S:JcmiR156a transgenic L7 was used as the female parent to get 35S:JcmiR156a (L7) × 35S:rJcSPL9 (L18) and 35S:JcmiR156a (L7) × 35S:JcSPL9 (L11) hybrid transgenic plants. Thirteen and fourteen positive F1 plants of two kinds cross combination were identified by PCR, respectively (Figure 2A,B). Subsequently, the flowering time of WT, 35S:rJcSPL9 (L18), 35S:JcmiR156a (L7) × 35S:rJcSPL9 (L18), 35S:JcSPL9 (L11), 35S:JcmiR156a (L7) × 35S:JcSPL9 (L11), and 35S:JcmiR156a (L7) was analysed. These results demonstrated that the flowering time of 35S:rJcSPL9 was earlier than 35S:JcSPL9 (Figure 2C, Table S1); after crossing with 35S:JcmiR156a, the flowering time of 35S:JcmiR156a (L7) × 35S:rJcSPL9 (L18) was not obviously changed, and the expression level of rJcSPL9 was not decreased (Figure 2D). However, the early flowering phenotype of 35S:JcSPL9 (L11) was lost in 35S:JcmiR156a (L7) × 35S:JcSPL9 (L11) plants; the expression level of JcSPL9 was decreased to 25% (Figure 2D). These results indicated miR156‐resistant JcSPL9 exhibited stronger activity than 35S:JcSPL9 in Arabidopsis, leading us to select rJcSPL9 for Jatropha transformation.

FIGURE 2.

35S:rJcSPL9 lines flowered earlier than 35S:JcSPL9 lines in Arabidopsis. (A, B) Identification of 35S:JcmiR156a × 35S:rJcSPL9/JcSPL9 hybrids through PCR. DNA templates were isolated from artificially pollinated plants. The primer XT126 and XA40 were used to detect JcSPL9, and a 1420 bp fragment was amplified. The primer XT126 and XA44 were used to detect JcmiR156a, and a 220 bp fragment was amplified. (C) 30‐day‐old Arabidopsis of WT, 35S: rJcSPL9, 35S:JcmiR156a × 35S:rJcSPL9, 35S:JcSPL9, 35S:JcmiR156a × 35S:JcSPL9, and 35S:JcmiR156a. Bar = 5 cm. (D) The relative expression levels of JcSPL9, miR156, AtSPL3, AtSPL9, and AtSPL15 in WT, 35S:rJcSPL9, 35S:JcmiR156a × 35S:rJcSPL9, 35S:JcSPL9, 35S:JcmiR156a × 35S:JcSPL9, and 35S:JcmiR156a plants, AtActin2 as a reference. The y‐axes represent the relative expression levels of mRNAs to the reference gene. Error bars indicate standard deviations of three biological replicates.

3.3. Overexpression of rJcSPL9 Promotes Xylem Development and Floral Production in Jatropha

In the vegetative stage, rJcSPL9 overexpression increased axillary bud number and length (Figure S2). Moreover, xylem thickness in transgenic Jatropha was 0.15–0.35 mm thicker than that of the WT xylem (Figure S3A,B), and the layers of the xylem thickening expanded significantly in rJcSPL9 transgenic plants (Figure S3C). These results suggest that JcSPL9 regulated the stem development by strongly promoting xylem formation and inhibiting phloem and pith development. Furthermore, epidermal wax accumulation was enhanced in rJcSPL9 transgenic Jatropha (Figure S4). During reproductive growth, 35S:rJcSPL9 transgenic plants flowered earlier than WT (Figure S5) and exhibited significantly increased female and male flower numbers per inflorescence (Table S2). WT plants produced 8.75 female and 143.63 male flowers per inflorescence. 35S:rJcSPL9 transgenic plants produced 12.83–14.12 female and 181.28–220.75 male flowers per inflorescence. However, the female‐to‐male ratio did not differ between genotypes (Table S2). Compared to the size of reproductive organ, we found inflorescences, male and female flowers, infructescences and fruits were all smaller than WT (Figure 4 and Figure S12).

FIGURE 4.

rJcSPL9 transgenic Jatropha produced smaller fruits and seeds. (A, B) Comparison of fruit length (A) and width (B) between WT and rJcSPL9 transgenic Jatropha (L21, L41, and L54). (C) Statistical analysis of fruit length and width in WT and the rJcSPL9 transgenic Jatropha, N = 30. (D, E) Comparison of seed length (D) and width (E) between WT and the rJcSPL9 transgenic Jatropha. (F) Statistical analysis of seed length, width, and thickness in WT and the rJcSPL9 transgenic Jatropha, N = 30. (G) Statistical analysis of seed weight, N = 100. Values are means ± standard deviation (Student's t‐test: **, p < 0.01). Bars = 1 cm.

Transgenic plants produced significantly more inflorescences and infructescences (Figure 3). Flower number and inflorescence number are two key factors that control seed yield. Therefore, we compared the inflorescence and infructescence numbers on the main stems: 1–3 inflorescences/infructescences were produced on the main stem of the WT plants (Figure 3A,B; Figures S8A and S9A), whereas 5–10 inflorescences/infructescences were produced on the main stem of the transgenic plants (Figure 3C,D; Figures S8B–D and S9B–D). By comparing the inflorescence and infructescence numbers on each plant, both one‐year‐old T0 (Figure S8E) and T1 (Figure 3E) transgenic plants exhibited significantly higher than those of the WT plants. Specifically, WT plants produced ~11 structures per plant in the first year, while T1 transgenic plants produced 18–28 (Figure 3E). As the number of primary branches of the transgenic plants increased, their inflorescence and infructescence numbers were 2 to 3 times greater than those of the WT plants; moreover, compared with that of the WT plants, the fruit number of each infructescence of the L54 plants increased by approximately 3.5 (Figure 3E). The infructescence number of 3‐year‐old WT plants is about 40, whereas the infructescence numbers of 3‐year‐old transgenic plants are more than 70 (Figures S11 and S12A). The increase in flower and inflorescence numbers may be the result of rJcSPL9 upregulating several genes that affect inflorescence and floral meristem determination, including JcmiR172, JcAP1, JcLFY, and JcSOC1 (Figure S6C–G). These results indicated that JcSPL9 was involved in inflorescence meristem and floral meristem determination in Jatropha.

FIGURE 3.

Overexpression of rJcSPL9 increased the number of inflorescences and infructescences in transgenic Jatropha. (A) Ten‐month‐old WT Jatropha, with flowers and fruits; (B) high‐magnification image of the boxed portion shown in (A) showing the infructescence, which is indicated by red circles; (C) 10‐month‐old rJcSPL9 transgenic Jatropha, with flowers and fruits; (D) high‐magnification image of the boxed portion shown in (C) showing the inflorescence and infructescence, which are indicated by blue circles and red circles, respectively; (E) Analysis of inflorescence (Ifl) and infructescence (Ifr) numbers per plant and fruit (Fr) number per infructescence. Values are means ± standard deviation (Student's t‐test: *, p < 0.05; **, p < 0.01). The error bars indicate the standard deviations of 20 plants.

3.4. Overexpression of rJcSPL9 Alters Fruit and Seed Morphology

Fruit length and width were significantly reduced in rJcSPL9 transgenic Jatropha (Figure 4). L41 plants produced the smallest fruits compared with those of the WT fruit, with length and width reduced by approximately 7 mm (Figure 4C). Transgenic seeds were also smaller than WT seeds (Figure 4D,E). The length and width of the transgenic seeds were significantly decreased (Figure 4F). Moreover, 1‐seed weight was reduced by approximately 0.3–1.0 g in transgenic lines compared to WT (Figure 4G). Specifically, the average weights of 10 seeds were 6.44 g, 6.12 g, 6.90 g, and 7.30 g for L21, L41, L54 and WT, respectively (Figure 4G). Similar results were also found in the following years (Figure 5I). These data indicated that JcSPL9 played a vital role in the regulation of fruit and seed development in Jatropha.

FIGURE 5.

JcSPL9 positively regulates seed yield in Jatropha. (A) WT plant in fruit. (B) A branch of WT in (A). (C) 35S:RrJcSPL9 transgenic plant (L54). (D) A branch of 35S:RrJcSPL9 transgenic plant in (C). (E) 35S:JcmiR156a transgenic plant (L8). (F) A branch of 35S:JcmiR156a transgenic plant in (E). (G) Comparison of primary branch numbers in one‐year‐old WT, 35S:RrJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha. (H) Comparison of seed yield per plant of WT, 35S:rJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha, N = 15. (I) Weight of 10 seeds of WT, 35S:rJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha, N = 100. All plants were planted via cutting propagation in 2021. Values are means ± standard deviation (Student's t‐test: *, p < 0.05; **, p < 0.01).

3.5. JcSPL9 Positively Regulates Seed Yield in Jatropha

As mentioned previously, 35S:rJcSPL9 transgenic Jatropha produced more fruits and smaller seeds than WT did. These traits suggest that JcSPL9 substantially impacts Jatropha agronomic performance. To evaluate seed yield, 100 T1 transgenic plants were field‐grown and first‐year seed production was compared with WT. Per‐plant seed weight analysis revealed first‐year average yields of 181.13 g, 199.38 g, and 235.71 g for L21, L41, and L54, respectively, compared to 130.40 g for WT (Figure S10A); the seed yield of transgenic line L54 was 80.76% greater than that of WT. To confirm the results, seed yield was monitored over the following 2 years. In the third year, transgenic plants also generated more infructescence and achieved higher seed yield (Figure S12A). The average seed yield of each transgenic plant were 914.36 g, 914.36 g, and 1128.34 g for L21, L41, and L54, respectively, compared to 708.25 g for WT (Figures S11 and S12A); Line L54 exhibited a 59.31% yield increase over WT.

Additionally, WT, 35S:rJcSPL9, and 35S:JcmiR156a T1 plants were propagated by cuttings in 2021 for seed yield analysis in 2022. Results showed that the average seed yield were 499.29 g, 505.45 g, and 765.23 g for L21, L41, and L54, respectively, whereas the average seed yield of each WT plant was only 422.65 g. The average seed yield of 35S:JcmiR156a T1 transgenic plants was 241.04 g for L8, and 305.62 g for L28 (Figure 5A–G). Notably, L54 exhibited an 81.06% increase in seed yield over WT, while 35S:JcmiR156a line L8 showed a 51.67% decrease. JcSPL9 expression in 35S:JcmiR156a transgenic plants was reduced to 25% of WT levels (Figure S6A). These results indicate that JcSPL9 positively regulates seed yield in Jatropha.

3.6. JcSPL9 Regulates Oil Content and Fatty Acid (FA) Composition

When the oil content of dry seeds of T1 plants was measured, the results showed that the oil content of transgenic seeds was 346.4 mg/g, 315.1 mg/g, and 318.5 mg/g for L21, L41, and L54, respectively, while the oil content of the WT seeds was approximately 307.7 mg/g (Figure S10B). The highest oil content was observed in L21, representing an increase of approximately 39.1 mg/g (12.63% relative increase). However, kernel percentage did not differ significantly among genotypes (Figure S10C). Oil content in transgenic kernels increased by 10.4 mg/g to 37.1 mg/g (2.14% to 7.76% relative increase). Specifically, kernel oil content was 518.0 mg/g, 493.9 mg/g, 491.8 mg/g, and 481.8 mg/g for L21, L41, L54, and WT, respectively (Figure S10D). The highest oil content was observed in L21 kernels, representing an increase of 36.2 mg/g (7.54% relative increase). Based on these data, oil production per plant was 40.12 g, 62.74 g, 62.83 g, and 75.07 g for WT, L21, L41, and L54 in the first year, respectively, representing increases to 1.564, 1.566, and 1.871‐fold for L21, L41, and L54, respectively. Furthermore, seed oil content in rJcSPL9 line L21 increased by 36.0 mg/g (11.11% relative increase) and 41.2 mg/g increase (12.01% relative increase) in the second and third years, respectively, despite slight decreasing in seed weight (Figure S12C, Figure 6A). To confirm that JcSPL9 regulates oil content, we determined the oil content in T1 35S:JcmiR156a transgenic Jatropha plants. The results showed that seed oil content of 35S:JcmiR156a lines L8 and L28 was 314.8 mg/g and 325.2 mg/g, (Figure 6A), which exhibited an 8.28% and 5.22% relative decrease, respectively. The kernel oil content was also significantly decreased in 35S:JcmiR156a plants (Figure 6B). We also analysed the contents of crude protein, starch, and soluble sugars; these results showed that the contents of these components were almost decreased in rJcSPL9 transgenic plants but increased in JcmiR156a transgenic plants (Figure 6C–E).

FIGURE 6.

Comparison of the oil, protein, starch, soluble sugar content, and fatty acid composition of seeds from WT, 35S:rJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha. (A, B) The seed oil content (A), and kernel oil content (B) among WT, rJcSPL9 (L21, L41, and L54), and 35S:JcmiR156a T1 transgenic Jatropha. (C–E) The crude protein (C), starch (D), and soluble sugar contents (E) in WT, rJcSPL9 T1 transgenic Jatropha and JcmiR156a T1 transgenic seeds. (F) Comparison of the kernel fatty acid composition of WT, rJcSPL9, and JcmiR156a transgenic Jatropha. (G) Comparison of the degree of unsaturation (DU) and oxidative stability (OS) of seed oil from WT, rJcSPL9, and JcmiR156a transgenic Jatropha. (H) Fatty acid composition of seeds by GC–MS. The plants used for this experiment were planted by cutting propagation in 2021. Values are means ± standard deviations, which were calculated from at least 100 seeds independently collected from three independent WT, rJcSPL9, and JcmiR156a transgenic plants. Asterisks denote significance compared with WT plants (Student's t‐test: *, p < 0.05; **, p < 0.01).

To further confirm the function of SPL9 in the regulation of oil accumulation in Arabidopsis, we compared the oil content in WT, spl9 mutant, and 35S:JcmiR156a transgenic Arabidopsis. These results exhibited that the oil contents were 392.5 mg/g, 344.0 mg/g, 350.5 mg/g, 373.0 mg/g, and 378.2 mg/g in WT, spl9 mutant, spl9 spl15 double mutant and 35S:JcmiR156a transgenic Arabidopsis L2 and L7, respectively (Figure S15C). The oil content in spl9 mutant, spl9 spl15 double mutant, and 35S:JcmiR156a transgenic Arabidopsis significantly decreased, with an approximately 48.5 mg/g (12.36% relative) decrease in spl9 mutant, a 42.0 mg/g (10.70% relative) decrease in spl9 spl15 double mutant and a 19.5 mg/g and 14.3 mg/g (4.97% and 3.65% relative) decrease in 35S:JcmiR156a transgenic Arabidopsis. Overexpression of rJcSPL9 in WT and spl9‐4 mutant plants also increased seed oil content (Figure S15D). These results indicate that, in addition to regulating seed yield, JcSPL9 also regulates lipid accumulation in seeds.

Fatty acid (FA) composition of oil from rJcSPL9 and JcmiR156a transgenic seeds was detected by GC–MS. These results exhibited that the C16:0 mol% decreased significantly by 3.70%–9.25% in rJcSPL9 transgenic seeds; the C18:0 decreased significantly by 15.01%–20.45% in rJcSPL9 transgenic seeds but increased by 3.52%–4.21% in JcmiR156a transgenic seeds. C18:1 increased significantly by 3.54%–7.04% in rJcSPL9 seeds but decreased significantly by 5.02%–5.45% in JcmiR156a transgenic seeds. C18:2 decreased by 4.08%–5.75% in rJcSPL9 transgenic seeds, whereas it increased by 4.73%–5.81% in JcmiR156a transgenic seeds (Figure 6F). These FA composition changes significantly reduced the degree of unsaturation (DU) in rJcSPL9 transgenic seed oil, potentially improving biodiesel oxidative stability (OS) compared to WT, while the DU and OS of the JcmiR156a transgenic seeds were opposite (Figure 6H).

To verify the role of SPL9 in regulating FA composition, individual FAs were also determined in oil extracted from Arabidopsis seeds of wild‐type, spl9 mutant, 35S:JcmiR156a transgenic WT and spl9 mutant Arabidopsis. These results showed that C18:0, C18:2, and C20:1 mol% were significantly increased in spl9 mutant, spl9/spl15 double mutant, and JcmiR156a transgenic Arabidopsis, whereas both C18:1 and C18:3 mol% were significantly decreased in the mutants and JcmiR156a transgenic Arabidopsis (Figure S15E). Additionally, in contrast to the spl9 mutant, the spl9/spl15 double mutant showed significant changes in C16:0 mol% (Figure S15E). These results indicate that miR156 and its target SPL9 are involved in regulating FA biosynthesis in both Arabidopsis and Jatropha.

3.7. JcSPL9 Upregulates the expression of Oil Biosynthesis Genes

Fruit and seed morphology as well as oil content were analysed at different developmental stages. These results showed that seed weight and oil content increased slowly during early stages, especially before 5 week‐after‐pollination (WAP), but rapidly during late stages, especially the stages 7–8 WAP (Figure 7E,F). Expression of oil biosynthesis genes in the seed at the 4–8 WAP was further detected by qRT‐PCR. During seed development, expression levels of JcWRI1, JcDGAT1, JcDGAT2, and JcOLEOSIN were lower at 4 WAP, then increased at 6 WAP, and peaked at 6–7 WAP (Figure 7G–J). Combined with these results, the stage with higher oil‐related gene expression corresponded to the key oil biosynthesis stage (Figure 7F).

FIGURE 7.

Comparison of oil content and oil biosynthesis gene expression at different stages. (A) 4‐ to 8‐week‐old fruits from WT and transgenic Jatropha lines 35S:RrJcSPL9 (L21) and 35S:JcmiR156a(L8), bar = 1 cm. (B) 4‐ to 8‐week‐old fruits and seed from WT, 35S:rJcSPL9 (L21), and 35S:JcmiR156a (L8) T1 transgenic Jatropha, bar = 1 cm. (C, D) Statistic analyse the fruit length (C) and fruit width (D) from WT, 35S:RrJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha from 4 weeks to 8 weeks. (E) Statistic analyzes the weight of 10 seeds of WT, 35S:RrJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha from 4 weeks to 8 weeks. (F) The seed oil content of WT, 35S:RrJcSPL9, and 35S:JcmiR156a T1 transgenic Jatropha from 4 weeks to 8 weeks. (G‐J) Oil biosynthesis gene expression levels, including those of JcWRI1 (G), JcDGAT1 (H), JcDGAT2 (I), and JcOLEOSIN (J), in seeds at different develop stages in WT and transgenic plants. Values are means ± standard deviations, which were calculated from at least 15 fruits or 40 seeds from each line.

In this study, oil content increased in rJcSPL9 transgenic seeds and decreased in 35S:miR156 transgenic seeds compared to WT Jatropha. When comparing across genotypes and developmental stages, differences in seed weight and oil content occurred at 6–8 weeks after pollination and persisted until maturity (Figure 7F). Differential expression of oil biosynthesis genes was observed at 4–7 week‐after‐pollination (Figure 7G–J); gene expression divergence occurred slightly earlier than did oil content divergence. Comparison of oil biosynthesis gene expression revealed that the expression abundances of JcWRI1, JcDGAT1, JcDGAT2, and JcOLEOSIN were all increased in the rJcSPL9 transgenic seeds but decreased in the 35S:JcmiR156a transgenic Jatropha seeds (Figure 7G–J).

4. Discussion

4.1. JcSPL9 Positively Regulates Seed Yield in Jatropha

Plant branching patterns are crucial for light interception efficiency and resource adaptation. 35S:rJcSPL9 transgenic plants developed more axillary buds at the young seedling stage and more branches at the mature stage (Figure S2, Figure 5). 35S:rJcSPL9 transgenic Jatropha produced more branches, inflorescences, and infructescences than WT (Figure 3, Figures S8, S9, S11, S12A). In this study, 35S:rJcSPL9 transgenic plants developed more axillary buds at the young seedling stage and more branches at the mature stage (Figure S2, Figure 5). The SPL module's conserved function in tillering/branching has been confirmed in many plant species. In rice, OsSPL14 (the AtSPL9 homologue) negatively regulates axillary bud outgrowth while positively regulates panicle branch number by enhancing meristematic activity and cell proliferation (Jiao et al. 2010; Luo et al. 2012). High OsSPL14 expression increases primary and secondary branches (Miura et al. 2010). Effects of other SPL genes (such as SPL7/13/16/17) on tillering and panicle branching have also been observed in rice (Si et al. 2016; Wang et al. 2015, 2012). In Arabidopsis, SPL9 physically interacts with DELLA proteins (Wang et al. 2019; Yu et al. 2012). In Jatropha, overexpression of rJcSPL9 promoted axillary bud outgrowth and branching (Figure 1), consistent with previous reports that GA promoted shoot branching (Ni et al. 2015, 2017). We propose that GA promotes branching in Jatropha might by regulating DELLA‐JcSPL9 interactions. This notion is supported by a recent study showing that GA represses Arabidopsis axillary bud formation by modulation of DELLA‐SPL9 complex activity (Zhang et al. 2020). However, further work is needed to elucidate how GAs modulate shoot branching via opposing pathways in Jatropha and Arabidopsis. Thus, increased branching indirectly improved the seed yield in rice and Jatropha (Figure 5H, Figure S10).

Increased inflorescence and flower numbers, combined with earlier flowering time (Figure S5, Table S2), led to significantly more infructescence (Figure 3E, Figures S8E and S12A). Although the fruit and seed sizes of transgenic plants were smaller, all 35S:rJcSPL9 transgenic Jatropha plants produced significantly higher seed yield, and the seed yield of transgenic line L54 plants was 80.76% greater than that of the WT plants (Figure 5H, Figures S10A and S12A). On the contrary, the seed yield of JcSPL9 decreased plants generated by overexpressing miR156 was significantly reduced (Figure 5G). The expression of flowering‐related genes, including JcLFY, JcSOC1, JcAP1, JcFUL, and JcmiR172, was upregulated in rJcSPL9 transgenic plants (Figure S6). Therefore, we concluded that JcSPL9 activated flower identity genes and directly promoted reproductive growth, which increased the inflorescence and flower numbers and further led to an increase in the seed yield.

Studies reporting that SPL genes positively regulate seed yield have been documented in rice and tomato (Cui et al. 2020; Wang, Yu, et al. 2017). Both the grain weight and yield increased in lines overexpressing OsSPL13, OsSPL14, or OsSPL16 (Miura et al. 2010; Si et al. 2016; Wang and Wang 2015; Wang et al. 2015, 2012). Moreover, overexpression of OsSPL14 increased the thousand‐grain weight from 27.2 g in control plants to 30.2 g in transgenic plants (Jiao et al. 2010). Moreover, the varieties in which OsSPL14 was upregulated presented a 10% increase in grain yield in test plots (Jiao et al. 2010). In tomato, both miR156‐overexpression lines and SlSPL13‐RNAi plants exhibited reduced numbers of flowers and fruits, leading to a significant decrease in yield per plant (Cui et al. 2020). In maize, UB3 is an orthologue of AtSPL9 and is also homologous to UB2 and TSH4. Double mutants of ub2 and ub3 displayed reduced kernel row numbers in maize (Chuck et al. 2014; Du et al. 2017; Liu et al. 2015). The loss‐of‐function phenotypes of ub2/ub3/tsh4 mutants in maize are associated with reduced yields (Chuck et al. 2014), which are opposite to the phenotypes of two dominant gain‐of‐function alleles in rice, OsSPL14 ^ipa1 and OsSPL14 ^WFP, which improve grain yield by increasing panicle branching (Jiao et al. 2010; Miura et al. 2010).

The seed yield of all 35S:rJcSPL9 transgenic lines were significantly increased, with the line L54 producing the highest yield (Figure 5G, Figures S10A and S12A). However, line L54 exhibited the lowest JcSPL9 expression level (Figure S6A). The seed yield of 35S:JcmiR156a transgenic Jatropha were 51.67% less than that of WT (Figure 5G), and the expression level of JcSPL9 was reduced to a quarter of WT in 35S:JcmiR156a transgenic plants (Figure S6). Similarly, Wang et al. (2015) reported that moderate SPL gene expression may constitute a strategy for increasing rice yield in breeding. Weaker expression of OsSPL14 leads to the optimal combination of tiller number and panicle size as well as increased grain yields in rice (Zhang et al. 2017). Moreover, both tiller and panicle branching are greatly reduced by overexpressing all OsSPL7/14/16/17, indicating that SPLs promote panicle branching only at optimal levels (Wang, Qiao, et al. 2017). This conclusion is further strengthened by maize UB3, which enhances rice panicle branching in moderate‐overexpression lines, but the opposite effect was observed in high‐overexpression lines (Du et al. 2017). Therefore, SPL expression must be fine‐tuned to favourable levels to increase productivity. In addition, SPL genes can also control fruit ripening and fruit yield in tomato and kernel row number in maize in a dosage‐dependent manner (Cui et al. 2020; Liu et al. 2015; Wang and Wang 2015), suggesting that modifying SPL expression offers a feasible strategy for crop improvement. Furthermore, recent studies have shown that OsSPL14 promotes both yield and immunity in rice (Wang et al. 2018).

4.2. Regulation of Oil Content and Fatty Acid Composition by JcSPL9

Several RNA‐seq and bioinformatic studies have predicted that miR156 and its target SPL genes might be involved in fatty acid and lipid metabolism in seeds of several species, including Brassica napus (Picq et al. 2014; Wang et al. 2016; Wang, Qiao, et al. 2017), oil palm (Zheng et al. 2019), and tree peony (Yin et al. 2018). In this study, for the first time, we demonstrate that the seed oil content and fatty acid composition were significantly altered in rJcSPL9 transgenic Jatropha and spl9 mutants of Arabidopsis, and in JcmiR156a‐overexpressing Jatropha and Arabidopsis (Figures 6, 7 and Figures S13 and S15). The seed oil content in both Jatropha and Arabidopsis was positively regulated by SPL9 (Figure 6A and Figure S15C,D). There was no significant difference in oil content of seeds collected before 6 WAP in WT, rJcSPL9 and JcmiR156a overexpressing plants (Figure 7). After 6 WAP, the seed oil content was obviously increased in rJcSPL9 transgenic Jatropha and decreased in JcmiR156a transgenic Jatropha (Figure 7). Ultimately, transgenic plants exhibited a 112.63% increase in relative seed oil content, corresponding to an absolute increase of 39.1 mg/g. In the first year, oil production per plant increased by 35 g (1.87‐fold) and further rose to 134 g (1.55‐fold) in the second year. Correspondingly, the expression levels of JcWRI1, JcDGAT1, JcDGAT2, and JcOLEOSIN were increased in rJcSPL9 transgenic Jatropha and decreased in JcmiR156a transgenic plants; especially in seeds at 5–7 WAP (Figure 7F). These results indicate that JcSPL9 may regulate lipid accumulation through activating expression of JcWRI1, JcDGAT1, JcDGAT2, and JcOLEOSIN in seeds.

At the metabolic level, increased oil accumulation in the rJcSPL9 transgenic plants was accompanied by significant reductions in crude protein and starch contents in the seed kernels. Specifically, crude protein content decreased by approximately 25 mg/g DW in the most affected line (Figure 6C), while starch content decreased by about 13 mg/g DW (Figure 6D). Soluble sugar content also showed a slight decline (Figure 6E). The decreases in crude protein, starch, and soluble sugar contents closely matched the 41.2 mg/g increase in oil content. The comparative transcriptome analysis revealed that in the transgenic kernels 5–7 weeks after pollination, the expression levels of genes related to lipid synthesis, protein metabolism, and glycolysis had undergone significant changes in most cases (Figure S14). We propose that JcSPL9 regulates carbon flux allocation between metabolic pathways, thereby coordinating oil biosynthesis and promoting optimal carbon partitioning during Jatropha seed development. Overexpressing SWEET15 in upland cotton reduces fibre length, seed size and oil content (Le et al. 2025). In this study, the expression of SWEET10 was down regulated in rSPL9 transgenic plants.

Biodiesel quality is mainly determined by the FA composition of vegetable oils (Feng et al. 2020; Ramos et al. 2009; Tang et al. 2022). Since polyunsaturated FAs reduce OS of biodiesel, vegetable oils rich in monounsaturated FAs with low DU are preferable to those containing polyunsaturated FAs (Feng et al. 2020; Ye et al. 2013). A gene silencing approach has been applied to improve the oil quality of Jatropha seeds (Qu et al. 2012; Ye et al. 2013). Silencing of JcFAD2‐1 encoding a fatty acid desaturase 2, which catalyses the conversion of oleic acid (C18:1) to linoleic acid (C18:2) (Tao et al. 2019), showed a significant increase in oleic acid content by more than 78% (Qu et al. 2012). In this study, the rJcSPL9 transgenic Jatropha exhibited a significant increase in oleic acid (C18:1) and a corresponding decrease in linoleic acid (C18:2) in the seed oil (Figure 6F and Figure S9E), which resulted in a significantly decreased DU of the seed oil. Therefore, an improved biodiesel with higher OS was detected in seed oil of rJcSPL9 transgenic Jatropha than in that of WT (Figure 6G and Figure S9F).

In conclusion, we show that JcSPL9 is involved in the regulation of both seed yield and oil productivity in Jatropha, and for the first time, we demonstrate, by using the rJcSPL9 and JcmiR156a transgenic Jatropha, that SPL9 has a novel function in regulating fatty acid biosynthesis and lipid accumulation in seeds. The results suggest a possible method for developing high‐yield, high‐oil content transgenic germplasms to enhance seed yield and oil traits in woody oilseed plants. The breeding biotechnology, which employs a mutant of miR156 target sequence, can also be applied to developing new varieties of other oil crops. Due to the substantial regulatory hurdles in transgenic variety registration mandating long‐term safety assessments, regulatory approval for these new varieties has yet to be secured. Despite this, the technology and methodology could point to a promising new direction for agriculture. The cross‐disciplinary integration of molecular precision breeding biotechnologies with artificial intelligence and robotics will reshape future market landscapes, ignite industrial vitality, and foster breakthrough products. JcSPL9 represents a promising tool for increasing seed yield, oil productivity, and quality in Jatropha, with potential applications to other oilseed crops. Further studies should elucidate the molecular mechanisms underlying JcSPL9‐mediated regulation of fatty acid and lipid metabolism in seeds. A new function of SPL9 was also found in Arabidopsis, i.e. cuticular wax regulation by the miR156‐SPL9 module in Arabidopsis (Clark et al. 1993; Huang et al. 2024) and enhanced soluble sugar accumulation in cassava roots through rMeSPL9 overexpression (Li, Cheng, et al. 2022).

Author Contributions

Mingyong Tang designed and performed the experiments, analysed the data, and wrote the paper. Xue Bai performed the experiments, analysed the data, and revised the paper. Yaoping Xia and Ping Huang helped collect the data. Zeng‐Fu Xu conceived the experiments and revised the manuscript. All authors reviewed and approved the final manuscript.

Funding

This work was supported by the Natural Science Foundation of China (32371836), the Guangxi Specific Project for Science and Technology Bases and Talents (AD23026337), and the Natural Science Foundation of Yunnan Province (202501AS070081, 202205AC160030, 202401AT070225).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: pbi70558‐sup‐0001‐Supinfo.docx.

Data Availability Statement

No new sequence data was published in the present paper. sequence data included in our manuscript can be obtained from the publicly available genome of Jatropha curcas (https://www.ncbi.nlm.nih.gov/bioproject/PRJNA694573/). Under the following accession numbers: JcSPL9 (XM_012232354); JcmiR156a (XR_002284867); JcmiR172 (XR_002283652); JcAP1(KR013222); JcLFY (XM_012235184); JcSOC1 (XM_012228124); JcFUL (XP_020537425), JcACTIN1 (NM_112764); JcDGAT1 (NM_001305997); JcDGAT2 (NM_001306044); JcOLEOSIN (JQ806305); JcWRI1 (NM_001306018).