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Comparative transcriptomic
analysis of loquat floral fragrance
and hormone synthesis
regulation across developmental
stages in petals and stamens
Jia-Qi Huang, Jia-Qi Wen, Fan Wu, Peng Zhou,
Jing-Jing Zhang, Lin-Xuan Wang and Hong-Liang Li*
Zhejiang Provincial Key Laboratory of Biometrology and Inspection & Quarantine, College of Life
Sciences, China Jiliang University, Hangzhou, China
Introduction: Loquat Eriobotrya japonica is a native plant in China that blooms at low
temperatures in early winter, and the floral fragrance volatiles from the petals and
stamens of loquats’flowers are attractive to wild pollinators like Chinese honeybees.
Thus, it was necessary to reveal the biosynthesis of floral fragrance and hormone
regulation involved in the insect pollination of loquats’flowers.
Methods: Here, the volatile contents of petals and stamens were significantly
higher than those of other parts of the loquat flower through the analysis of GC,
and a key loquat flowers’compound 4-methoxybenzaldehyde has the highest
content among all volatile components. The transcriptomics of six samples of
loquat flowers’petals and stamens at different developmental stages of bud (Bu),
exposed (Ex), and bloom (Bl) were obtained.
Results: PCA analysis indicates that petals developed earlier than stamens due to
the number of up-regulated petal genes being much higher than that of stamens
in the bud stage, and the number of up-regulated stamen genes increasing
rapidly at the stages of exposed and bloom. KEGG analysis revealed that petals
and stamens DEGs were enriched in two pathways of plant hormone signal
transduction and phenylpropanoid biosynthesis. Among them, some key genes
related to the synthesis of the fragrance components were screened, and
showing a strong positive correlation with phenethyl alcohol and 4-
methoxybenzaldehyde. The synthesis of hormones such as gibberellin and
growth hormone were also screened. Finally, real-time PCR was used to
validate the screening of 12 genes related to floral fragrance and hormone
synthesis. Except for ACO (1-Aminocyclopropane-1-carboxylate oxidase), most
othergeneslocatedinthepetalswereexpressedinsignificantly higher
abundance than in the stamens. Among these, the expression of PAAS
(Phenylacetaldehyde synthetase), OMT (O-methyltransferase), GA2OX
(Gibberellin 2-b-dioxygenase) were consistent with the development of
loquat flower.
Frontiers in Plant Science frontiersin.org01
OPEN ACCESS
EDITED BY
Zhiyong Lim,
Chinese Academy of Agricultural Sciences,
China
REVIEWED BY
Yuxiao Shen,
Henan Agricultural University, China
Qianyi Zhao,
Northwest A&F University, China
Lifei Chen,
Jilin Agriculture University, China
*CORRESPONDENCE
Hong-Liang Li
hlli@cjlu.edu.cn
RECEIVED 11 February 2025
ACCEPTED 09 April 2025
PUBLISHED 08 May 2025
CITATION
Huang J-Q, Wen J-Q, Wu F, Zhou P,
Zhang J-J, Wang L-X and Li H-L (2025)
Comparative transcriptomic analysis
of loquat floral fragrance and hormone
synthesis regulation across developmental
stages in petals and stamens.
Front. Plant Sci. 16:1574771.
doi: 10.3389/fpls.2025.1574771
COPYRIGHT
©2025Huang,Wen,Wu,Zhou,Zhang,Wang
and Li. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms.
TYPE Original Research
PUBLISHED 08 May 2025
DOI 10.3389/fpls.2025.1574771
Discussion: Their high expression promoted the synthesis and release of floral
fragrance and then may effectively attract pollinators. This study enriches the
molecular mechanism of the release, synthesis and regulation of loquat floral
fragrances and provides a theoretical basis for the co-evolutionary pollination
between Chinese honey bees and loquat flowers in early winter.
KEYWORDS
Eriobotrya japonica, transcriptome, floral fragrance synthesis, hormone synthesis gene,
real-time PCR
1 Introduction
As a famous native fruit plant, the loquat Eriobotrya japonica is
widely distributed around the Yangtze River basin in China. E.
japonica commonly blossoms in late fall and early winter from
October to February next year (Pinillos et al., 2011). Loquat mainly
relies on insects of the bees (67.8%) and hoverflies (21.57%) for
pollination, and these insects are essential for contributing fruits’
yield and quality (Saboor et al., 2021). During the period of blossom
and pollination, the loquat flowers have relatively well-developed
nectar glands, and emit distinctive and strong fragrances (Nyska
et al., 2014). Nine loquat floral fragrance could be sensed by insect
pollinators such as Chinese honey bees (Zhang, 2022), and the bees
were more attracted to pollinate due to some specific fragrances at
early winter temperatures (Huang et al., 2025). Although the main
volatile components of loquat flowers have been characterized
(Kuwahara et al., 2014), it was still unclear the mechanism of
release, synthesis and regulation of the loquat floral fragrance
during the winter blossom stage.
Floral fragrance was a significant means by which flowering
plants attract pollinators and was intimately related to flowering
behavior. Floral fragrance volatiles include terpenoids,
phenylpropanoids, fatty acids, and amino acid derivatives (Natalia
et al., 2013). The aromatic compound 4-methoxybenzaldehyde
from loquat flower could efficiently bind with Chinese honey
bees’olfactory-related protein at low temperature (Zhang et al.,
2023;Huang et al., 2025). It was reported to be synthesized by O-
methyltransferase from loquat flowers (Koeduka et al., 2016a), and
identified to be synthesized by benzaldehyde synthase in petunia
flowers (Huang et al., 2022). The loquat floral volatile b-
phenylethanol could also be attractive to Chinese honey bees at
early winter (Zhang, 2022), and it was generated by decarboxylases
located in the loquat flower (Koeduka et al., 2017).
On the other hand, the synthesis and release of plant floral
fragrance could be affected by the regulation of plants’flowering
process (Huber et al., 2005;Su et al., 2022), some genes of which
were involved in multiple signaling pathways for endogenous
hormones and metabolism. For instance, the different bloom
patterns regulate the growth hormone signaling genes (Guo
et al., 2017), which could control the production of floral
fragrances (Ke et al., 2019;Wang et al., 2021). Auxin-related
proteins were involved in regulating flowering time (Zhu et al.,
2020;Feng et al., 2022), and gibberellin-related genes were
strongly associated with both floral longevity and bud unfolding
(Yuan et al., 2024;Zhang et al., 2022b). Cytokinin-related genes
regulate the development of female organs and inflorescence
branching (Fu et al., 2022). However, these individual genes
related to loquat’sfloral fragrance synthesis and hormone
regulations do not represent the whole process, which needs
much more evidence to completely elucidate the synthesis and
regulation pathway.
Comparative transcriptomic investigation has been extensively
used in studies of floral development. For instance, the molecular
mechanism of eggplant flowers’anther dehiscence was identified
using transcriptomics, and genes associated with another
development were discovered (Yuan et al., 2021). The loquat has
the ability of flowering in winter, it suggests that loquat has unique
inner physiological mechanisms to adapt to low temperatures, and
the blossom genes in whole loquat flowers have also been
characterized by transcriptomics (Xia et al., 2020;An et al., 2021)
and those key genes in the hormone signaling pathway (Jing et al.,
2020). However, it was still unclear what the loquat flowers’
fragrance synthesis pathway and hormonal regulation were,
which was crucial for the pollination biology of typical winter
nectar plants like loquats.
Therefore, based on the GC characteristics of the fragrance of
loquat flowers in developmental stages and different parts, this
study investigates the transcriptomics of loquat flowers’petals
and stamens from various developmental stages, and analyzes
the key genes that differ in expression, and the metabolic
pathways to understand better the mechanism of fragrance
synthesis and metabolism of loquat flowers. This study aims to
reveal the pathways by which fragrance components and hormone
synthesis were regulated during the development of loquat flowers.
These findings help to interpret the molecular mechanism of
loquat flower fragrance synthesis and provide new research
viewpoints for the pollination biology of loquat flowers by
flower-visiting insects.
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2 Materials and methods
2.1 Plant materials
The materials used in this study were loquat flowers from the
campus of China Jiliang University (30°19′17.25″N; 120°21′41.328″
E). The flowers were collected from October to November 2023 and
were categorized into three stages dependent on their morphology
(Koeduka et al., 2016b): bud stage, exposed stage, and bloom stage.
2.2 Determination of loquat flowers’
volatiles by GC
Loquat flowers were collected at three stages (Figures 1A–C): bud
stage (Bu), exposed stage (Ex) and bloom stage (Bl) as well as dissected
petals and stamens, calyxes and pistils of loquat flowers at the bloom
stage, and volatiles from loquat flowers at different stages were collected
by headspace using a 65 mm PDMS/DVB SPME extraction column. The
samples were placed in a 20 mL headspace vial and SPME adsorbed for
30 min at 30°C in a water bath. Standard samples of phenethyl alcohol,
ethyl benzoate, 4-methoxybenzaldehyde, methyl 4-methoxybenzoate,
ethyl 4-methoxybenzoate, (2-nitroethyl) benzene, methyl cinnamate,
and (E)-ethyl cinnamate were diluted with methanol and analyzed by
external standard using a gas chromatography GC-2014C (Shimadzu,
Japan). The conditions of the GC analyseswereasfollows:usingaRtx
®-
1 (30 m×0.32 mm×0.25 mm, Shimadzu, Japan) column with nitrogen as
the carrier gas at a flow rate of 1 mL/min. The inlet temperature was 250°
C, the FID detector temperature was 280°C, and the column chamber
warming program was set at 50°C for 2 min, and then the temperature
was ramped up to 92.8°C at a rate of 20°C/min, and then ramped up
to 95°C at 0.1°C/min, and finally ramped up to 150 °C at a rate of 20°C/
min for a continuous period. The temperature was then increased to
150°C at a rate of 20°C/min for 10 minutes.
2.3 Total RNA extraction, library
construction, and transcriptome
sequencing
Fresh loquat flowers were collected from three different stages
(Figures 1A–C), and the petals (Figures 1D–F)andstamens
FIGURE 1
Loquat flowers, petals, and stamens from different stages. (A) loquat flower at the bud stage, (B) loquat flower at the exposed stage, (C) loquat
flower at the bloom stage, (D) petal at the bud stage, (E) petal at the exposed stage, (F) petal at the bloom stage, (G) stamen at the bud stage,
(H) stamen at the exposed stage, (I) stamen at the bloom stage.
Huang et al. 10.3389/fpls.2025.1574771
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(Figures 1G–I) were carefully dissected with sterilized ophthalmic
forceps. Furthermore, two biological replicates were set up for 12
samples, which were snap-frozen with liquid nitrogen and stored at
-80°C in the refrigerator for subsequent transcriptome sequencing.
We commissioned Hangzhou Lianchuan Biotechnology Co.,
Ltd. to perform reference-free transcriptome sequencing of loquat
flowers’petals and stamens from different stages. Total RNA was
extracted using the TRIzol method, and NanoDrop and Bioanalyzer
evaluated its amount, purity and integrity. Qualified RNA
(concentration >50 ng/mL, RIN >7.0, total amount >1 mg) was
captured with oligo(dT) magnetic beads for polyA mRNA,
fragmented, and reverse transcribed to cDNA. Double-strand
synthesis was doped with dUTP, end-repairing plus A base and
fragment ligations, and screening was performed. UDG enzyme
treatment was followed by PCR amplification, resulting in a 300 bp
± 50 bp library. Finally, transcriptome data were obtained by
double-ended PE150 sequencing using the Illumina Novaseq™
6000 platform.
2.4 Transcriptome sequencing raw data
processing
The downlinked data were in fastq format (Jing et al., 2022).
The data were de-joined, de-low-quality, and repetitive sequences
were removed to get the data formatted using fastq.gz, named Clean
reads. The clean data reads were de novo assembled using Trinity to
get the loquat flowers’transcription group Unigenes database.
Subsequently, the assembly quality of Unigenes was evaluated,
including the length, Q20, Q30, and GC content of Unigenes.
2.5 Functional annotation of differential
genes
Functional annotation of Unigenes was performed using the
new comparison software DIAMOND, and six authoritative
databases(NCBI_NR,GO,KEGG,Pfam,SwissProt,and
eggNOG) were used for the annotation. The NCBI_NR, Pfam,
SwissProt, and eggNOG databases retained all the best matches
(those that satisfied the threshold value of 0.00001 and retained the
smallest value). In contrast, the GO and KEGG databases retained
all the annotations that satisfied the threshold value. Set the
threshold of evalue 0.00001 and retain the annotation results with
the smallest evalue, and GO and KEGG databases retain all the
annotation results that satisfy the set threshold (evalue < 0.00001).
2.6 Functional enrichment analysis of
differentially expressed genes
Using |log
2
FC|≥1 & FDR<0.05 as the criteria (no differential
multiple for multi-group comparisons, and genes screened for
FDR<0.05 as statistically significant differences among multi-
groups). As a result, the genes screened for were considered
differentially expressed genes (DEGs). GO (KEGG) functional
significant enrichment analysis maps all significant differential
expression Unigenes to each item, pathway of GO and KEGG
annotation results of Unigenes. Additionally, using the
hypergeometric test, the GO and KEGG annotation results of all
the Unigenes were compared with the number of Unigenes for each
entry and route. GO entries and KEGG pathways that were
significantly enriched in differentially expressed Unigenes.
2.7 Expression trend analysis
In this study, STEM was utilized to distinguish different
expression trends of genes during petal and stamen development
in loquat flowers. The samples were set up according to the petal or
stamen development stage, from bud to bloom. Selection of
parameters: the data was processed using log normalization, and
the STEM Clustering Method was employed for clustering (p<0.05).
According to their expression patterns, the genes were divided into
16 modules, each representing a group of genes with comparable
expression trends throughout the development of loquat flowers’
petals and stamens. The horizontal coordinates of the modules were
Bu 1, Bu 2, Ex 1, Ex 2, Bl 1, and Bl 2, in that order, for a total of 6
samples. An inflection point represents a sample, and the vertical
coordinate represents the change in gene expression. The genes in
the expression module that showed an up-regulation trend were
analyzed for KEGG pathway enrichment.
2.8 Validation of qRT-PCR for floral flavor
and hormone-related genes
Six genes related to floral flavor and six genes related to
endogenous hormones were screened and validated based on the
enrichment results of the KEGG pathway, and the endogenous
reference gene was EjActin (Jing et al., 2020). Primers were
designed using Primer 5 (Supplementary Table S1). The RNA was
reverse transcribed to obtain cDNA using a reverse transcription kit.
Fluorescence quantitative detection was performed on a qRT-PCR
instrument (Thermo Fisher Scientific, USA) using uGreener Fast
qPCR 2×Mix reagent. The reaction program was as follows: pre-
denaturation 95°C, 30 s; PCR reaction 95°C, 5 s; 55°C, 30 s; 40 cycles,
and the samples were set up in three biological replicates using a
2
-ddCT
to calculate the relative expression of differential genes.
2.9 Data statistics and analysis
Prism 8.0 was used to draw heat maps, and qPCR data were
statistically analyzed. PCA, correlation analysis, Wayne plots,
enrichment analysis, trend analysis, and clustering heatmaps of
the transcriptome were done on the Lianchuan BioCloud platform
(https://www.omicstudio.cn/tool).
Huang et al. 10.3389/fpls.2025.1574771
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3 Results
3.1 Analysis of volatiles in different stages
and parts of loquat flowers
By the analysis of GC and external standard methods (Figure 2B),
the volatiles of loquat flowers at different stages showed a trend of
increasing during the developmental stages of loquat flowers
(Figure 2A). Further analysis revealed that the volatile contents of
petals and stamens were significantly higher than those of other parts
of the loquat flower. It was found that 4-methoxybenzaldehyde has
the highest content among all volatile components, which may be the
key source of the unique fragrance of loquat flowers. In addition, all
the three volatiles phenethyl alcohol, (2-nitroethyl) benzene and
methyl 4-methoxybenzoate were detected in the loquat flowers’
four different parts (petals, stamens, pistils and calyxes). The
distribution of methyl 4-methoxybenzoate (5) showed more
popular than others among these four parts (Figure 2C).
3.2 Transcriptome sequencing and
assembly quality assessment
Six samples from various loquat flowers’parts at different stages
of flowering—bud stage petals (Bu_p), bud stage stamens (Bu_s),
exposed stage petals (Ex_p), exposed stage stamens (Ex_s), bloom
stage petals (Bl_p), and bloom stage stamens (Bl_s)—were
subjected to differential transcriptomics sequencing. The RNA-
Seq data generated in this study (including samples from different
developmental stages of petals and stamens) had been deposited in
the SRA database, under accession numbers PRJNA1242521 and
PRJNA1242523. The results showed 78.35G of raw data and 65.83G
of valid data following preprocessing and assembly, with a valid
data percentage above 83.25% (Table 1). The GC content ranged
from 46.65% to 48.35%, and all Q20 and Q30 base proportions were
over 98% and 95%, respectively. These results suggested that the
transcriptome sequencing data matched the analytical standards
and could be utilized for further research.
FIGURE 2
Analysis of the volatiles of loquat floral fragrance at different stages (A) and different parts of the bloom stage (C).(B) Standard curve for standard
volatiles. The standard volatiles are: (1) phenethyl alcohol; (2) ethyl benzoate; (3) 4-methoxybenzaldehyde; (4) (2-nitroethyl) benzene; (5) methyl 4-
methoxybenzoate; (6) methyl cinnamate; (7) ethyl 4-methoxybenzoate; (8) (E)-ethyl cinnamate.
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3.3 Correlation analysis among
transcriptome samples
PCA analysis separated the six sample groups into six clustering
modules, as illustrated in Figure 3. Each sample group had distinct
differences and specificity in gene expression levels. For example,
the separation rates of PC1 and PC2 for different samples were
82.63% and 9.15%, respectively (Figure 3A). The PCA results
showed that the data of the same group of samples were
repetitive and differed between groups.
The inter-sample correlation coefficient analysis confirmed high
sample similarity within each group, and the correlation coefficient
tended to be approximately 1 (Figure 3B). Among them, the Ex_s
and Bu_p groups demonstrated the most significant difference
(Corr=0.16 ± 0.03). In contrast, the difference between the Bl_s
and the Ex_s groups was negligible (Corr=0.95 ± 0.02).
The most incredible intergroup difference was between bud and
bloom (Corr=0.50 ± 0.05), while the lowest was between bloom and
exposed (Corr=0.79 ± 0.05) among loquat flowers’petals at various
stages. The difference between the exposed and bloom stages was
the smallest (Corr=0.95 ± 0.01), while the contrast between bloom
and exposed was the biggest (Corr=0.23 ± 0.02), comparing the
stamens at different stages. Within the same stage, the bud stage
correlated 0.78 ± 0.01, the exposed stage correlated 0.19 ± 0.03, and
the bloom stage correlated 0.28 ± 0.07. Significant differences were
discovered in the samples from different stages and parts of loquat
flowers, indicating that the samples were well differentiated and
taxonomically reliable.
A detailed functional annotation of the Unigenes was
performed using the comparison tool DIAMOND. As indicated
in Table 2, the annotation method encompassed six well-known
database resources. Following analysis, 64645 and 60888 annotated
Unigenes were discovered in the petals and stamens of loquat
flowers, respectively. It offers a multitude of information for a
thorough grasp of the molecular characterization of loquat blooms.
3.4 Analysis of differentially expressed
genes
With high-quality transcriptome data and screening criteria, we
examined up- and down-regulated DEGs in petals and stamens from
the same stage and petals or stamens from different stages. In petals and
stamens of the same stage, 9592, 12048, and 4287 DEGs were detected
between Bu_s and Bu_p, Ex_s and Ex_p, and Bl_s and Bl_p,
respectively. Among them, 5603 DEGs were up-regulated and
expressed between Bu_s and Bu_p, 7554 DEGs were down-regulated
and expressed between Ex_s and Ex_p, and 3385 DEGs were down-
regulatedandexpressedbetweenBl_sandBl_p(Figure 4A).
In petals at different stages (Figure 4B), 5245 (with 3068 genes
down-regulated in the expression), 3717 (with 1989 genes down-
regulated in the expression), and 9074 (including 5472 genes down-
regulated in the expression) were detected in the comparisons
between Bu_p vs. Ex_p, between Ex_p vs. Bl_p, and between
Bu_p vs. Bl_p, respectively. Among the stamens in different
stages, Bu_s vs. Ex_s had the down-regulated DEGs with 7849,
2069 up-regulated DEGs between Ex_s vs. Bl_s, and 6466 up-
regulated DEGs between Bu_s vs. Bl_s (Figure 4C).
3.5 Functional enrichment of differentially
expressed genes
GO enrichment analysis was performed for different groups,
and results were displayed in Figure 5. The results were grouped
based on molecular function (MF), biological process (BP), and
TABLE 1 The RNA sequencing quality of floral bud development in loquat.
Sample
Raw Data Valid Data Valid
Ratio (Reads) Q20% Q30% GC
content%
Read Base Read Base
Bu_p1 42163834 6.32G 36236400 5.27G 85.94 98.51 95.28 47.23
Bu_p2 42179608 6.33G 35429254 5.13G 84.00 98.54 95.33 47.62
Ex_p1 47905732 7.19G 39880960 5.79G 83.25 98.65 95.68 47.25
Ex_p2 45329948 6.80G 38073956 5.53G 83.99 98.64 95.63 47.40
Bl_p1 43832010 6.57G 36656518 5.31G 83.63 98.60 95.54 47.76
Bl_p2 45187518 6.78G 39032212 5.68G 86.38 98.44 95.06 47.94
Bu_s1 44076802 6.61G 39575002 5.76G 89.79 98.62 95.61 46.73
Bu_s2 40899348 6.13G 36538930 5.31G 89.34 98.64 95.67 46.65
Ex_s1 41061754 6.16G 37246576 5.44G 90.71 98.67 95.74 47.61
Ex_s2 41914152 6.29G 37722960 5.50G 90.00 98.68 95.76 47.80
Bl_s1 45742630 6.86G 39055454 5.67G 85.38 98.54 95.34 48.35
Bl_s2 42092074 6.31G 37387176 5.44G 88.82 98.68 95.76 47.83
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cellular components (CC). The enrichment analysis histogram
showed that most differentially expressed genes were enriched in
the biological process (BP) entries. The primary enrichment was
in the biological process, regulation of transcription, DNA-
templated and transcription, DNA-templated. Cellular
component (CC) and molecular function (MF) come next; the
former was primarily enriched in the cytoplasm, plasma
membrane, and nucleus, while the latter was enriched mainly in
ATP binding, protein binding, and molecular function. Among
them, the Bu_s vs. Ex_s group DEGs had the comparatively most
number among the entries.
To visualize DEGs in metabolic pathways, we classified these
DEGs according to KEGG pathway enrichment analysis. The Bu_p
vs. Ex_p vs. Bl_p DEGs were mainly enriched in plant hormone
signal transduction (197), starch and sucrose metabolism (154),
phenylpropanoid biosynthesis (123), pentose and glucuronate
interconversions (106) and glycerolipid metabolism (59)
(Figure 6A). The DEGs of Bu_s vs. Ex_s vs. Bl_s were mainly
enriched in plant hormone signal transduction (320), starch and
sucrose metabolism (254), phenylpropanoid biosynthesis (181),
pentose and glucuronate interconversions (168), and cysteine and
methionine metabolism (143) (Figure 6B). In conclusion, DEGs
BFIGURE 3
Principal component analysis and inter-sample correlation analysis of gene expression levels. (A) Principal component analysis showed similarity
among replicate samples. (B) The inter-sample correlation coefficient, the clustering of 12 RNA-seq samples, represents the relationship between
the two parts of the three stages. The depth of blue represents the similarity between the samples, and the darker the color, the higher the
correlation. Bup, petal at the bud stage; Bus, stamen at the bud stage; Exp, petal at the exposed stage; Exs, stamen at the exposed stage; Blp, petal
at the bloom stage; Bls, stamen at the bloom stage. The same as follows.
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from petals and stamens of loquat flowers at different stages were
enriched in pathways of plant hormone signal transduction, starch
and sucrose metabolism, and phenylpropanoid biosynthesis.
3.6 Trend analysis of differentially
expressed genes
DEGs from petals were assigned to 16 trends (Figure 7A).
Among them, Profile 5, Profile 8, Profile 3, Profile 9, Profile 4, and
Profile 13 were significant trends. While the genes in Profile 9
indicated a continuous up-regulation trend from the bud stage to
the exposed stage to the bloom stage, the genes in Profile 5 indicated
a continuous down-regulation trend with the development of loquat
flowers. After comparing the genes in Profile 9 with the KEGG
database, 721 of the 3266 genes were annotated. Illustrated in
Figure 8A, they were primarily considerably enriched in flavonoid
biosynthesis (10), phenylpropane biosynthesis (15), and
phytohormone signaling (38).
DEGs from stamens were also assigned to 16 trends (Figure 7B).
Profile 5, Profile 8, Profile 3, Profile 9, Profile 4, and Profile 13 were
significant trends. The trends for Profile 5 and Profile 9 were the
same as in Petals. The genes in Profile 9 were compared with the
KEGG database; 738 of the 3068 genes were annotated in the KEGG
database. As shown in Figure 8B, the primary highly significant
enrichment was in plant-pathogen interactions (42), pentose and
glucuronate interconversions (36), and phenylpropanoid
biosynthesis (21).
3.7 Synthetic related genes of floral
fragrance and hormone
Functional annotation, functional classification, and metabolic
pathway and trend analysis of loquat flowers’transcriptome
sequencing results revealed that 19 and 27 DEGs related to floral
fragrance and endogenous hormones were screened, respectively.
Heat map clustering analysis could reflect the different gene
expressions of loquat flowers’petals and stamens in different
stages. As shown in Figure 9A, the gene expression of loquat
flowers’petals and stamens was divided into 2 clusters. Cluster I
had a higher expression in Ex_p, Bl_p, and Bl_s, and Cluster II had
a higher expression in Bu_p and Bu_s. Cluster I was only sparingly
expressed in the bud stage of early development, but it increases
dramatically following the development of petals and stamens into
the exposed and bloom stages. In contrast, the expression of cluster
II peaked at the early stage of flower development. It was
maintained relatively low as the flowers developed during the
exposed stage.
The correlation network diagram was drawn to illustrate the
significant correlations between different genes and specific volatile
compounds. As Figure 9B shown, OMT (O-methyltransferase),
TABLE 2 Unigenes annotation information.
Part Database of data Number of
Unigenes Percentage/%
Petal
GO 36935 57.14
KEGG 12726 19.69
Pfam 30788 47.63
swissprot 31802 49.19
eggNOG 39312 60.81
NR 38876 60.14
All 64645 100.00
Stamen
GO 34405 56.51
KEGG 12138 19.93
Pfam 29448 48.36
swissprot 29362 48.22
eggNOG 36721 60.31
NR 38235 62.80
All 60888 100.00
FIGURE 4
Venn diagram of genes expressed in different stages and locations of loquat flowers. (A) Venn diagram of differentially expressed genes between
stamens and petals in the same stage. (B) Venn diagram of differentially expressed genes in petals at different stages. (C) Venn diagram of
differentially expressed genes in stamens at different stages. The crossing points indicate the number of common genes. Red and blue numbers
indicate the number of up-regulated and down-regulated DEGs in the corresponding pair.
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ADH (Alcohol dehydrogenase), TAT (Tyrosine aminotransferase),
and GASA (Gibberellic acid-stimulated in Arabidopsis) showed a
strong positive correlation (labelled by solid red line) with
phenethyl alcohol, 4-methoxybenzaldehyde, (2-nitroethyl)
benzene, and methyl cinnamate. The rvalues of the OMT with 4-
methoxybenzaldehyde and PAAS (Phenylacetaldehyde synthase)
with phenethyl alcohol were 0.914 and 0.616, respectively.
Notably, methyl 4-methoxybenzoate was only positively
correlated with BS-b, with an rvalue of 0.769 (Figure 9B).
In this study, PAAS and OMT were discovered among 19 up-
regulated DEGs associated with synthesizing loquat floral fragrance
volatiles. Here, PAAS, being the highest expression in petals during
the bloom stage, was associated with phenylacetaldehyde synthesis.
OMT, associated with synthesis of 4-methoxybenzaldehyde, was
highly expressed in the stamens and petals during the bloom stage
(Figure 9C). Similarly, based on the screening among the 27 up-
regulated DEGs linked to loquat hormone anabolism, GA2OX
(Gibberellin 2-b-dioxygenase) about the synthesis of gibberellin,
showed strongly expressed in bloom petals. The growth hormone-
related ALDH (Aldehyde dehydrogenase) was substantially
expressed in both bloom petals and stamens (Figure 9D).
3.8 Validation of differential expression
gene by qRT-PCR
Six floral and six hormone anabolism-related DEGs were
screened from the transcriptome results. The qRT-PCR was used
to validate the expression changes of these 12 genes (Figure 10). The
results demonstrated that the relative expression patterns of these
genes aligned with the transcriptome sequencing results. The results
of the transcriptome data were confirmed to be credible. All the
genes except EjACO (1-Aminocyclopropane-1-carboxylate oxidase)
hadhigherexpressioninpetalsthaninstamens.Thefloral
fragrance-related genes, EjPAAS,EjOMT,EjTAT, and hormone-
related genes, EjFTIP (FT-Interacting protein), EjARG (Auxin-
induced protein), EjGASA,EjGA2OX, and EjLOG (Lonely·guy),
were all increased in expression with the development of petals and
stamens. It indicated that they might have a tight connection to the
development process of petals and stamens.
4 Discussion
4.1 The floral fragrance of petals and
stamens at the bloom stage
Flowering plants release different fragrance components at
different flowering stages and the fragrance of flowers generally
gradually increases. In this study, the loquat floral fragrance showed
the highest release at the bloom stage (Figure 2A). This highest
release of fragrance was able to attract pollinators for effective
visiting and nectar collecting (Koeduka, 2018). It was found in
the Paeonia lactiflora (Zhao et al., 2024) that the release of
monoterpenoids was highest at the S3 stage, i.e., the full blooming
stage, which was consistent with the increase in the intensity of
FIGURE 5
GO enrichment analysis of differentially expressed gene.
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floral fragrance in the senses, suggesting that the peak stage of floral
fragrance corresponded to the blooming stage of flowers.
Most studies reported that floral fragrance in plants were
mainly released from petals, but other floral organs such as
stamens, pistils, calyxes and nectar glands also contribute partially
to fragrance (Gerard et al., 2013). In this study, it was found that the
fragrance components of loquat flowers primarily came from the
petals and stamens (Figure 2B). Similarly, other studies have found
that the volatile components accumulated in the stamens of
Camellia were much higher than those of petals (Jullien et al.,
2008). In terms of five identified loquat floral volatile components in
this study, the previous similar reports showed that the major
loquat flowers’fragrances were (2-nitroethyl) benzene, 4-
methoxybenzaldehyde and methyl 4-methoxybenzoate, while
phenethyl alcohol were the minor components (Kuwahara et al.,
2014;Watanabe et al., 2021;Koeduka et al., 2016a).
4.2 DEGs of petals and stamens in different
developmental stages
The plant flowering process was significantly regulated by the
related hormones and flowering genes, which has been found in the
development of loquat terminal buds, several genes controlling
flowering timeof which were related to the ABA signaling
pathway (An et al., 2021). Some candidate genes might regulate
FIGURE 6
KEGG enrichment analysis of differentially expressed genes in petals (A) and stamens (B) at different stages.
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loquat flowering by exogenous gibberellin treatment and proposed a
hypothetical model for loquat flowering regulation (Jiang et al.,
2021). Furthermore, transcriptome analysis of loquat from
vegetative apex to flower bud transition revealed that the
EjAGL17 gene was flowering gene that significantly up-regulated
at the flower bud transition stage to promote loquat in blossoming
(Xia et al., 2020). Nevertheless, the genes related to synthesis and
release of plant floral voltiles were also involved in the present
transcriptome analysis.
In this study, we obtained the DEGs from petals and stamens
from three different stages of loquat flowers by the analyis of
transcriptome sequencing. It revealed that the number of up-
regulated genes in petals was much higher than that in stamens
during the bud stage (Figure 4A). Moreover, the number of up-
regulated genes in stamens increased rapidly as the flowers
developed into the exposed and blooming stages, suggested that
petals develop earlier than stamens. Therefore, it was hypothesized
that loquat flowers’petals might be the first to release floral
fragrance, enabling insects to detect the loquat flowers earlier. It
might extend the time for insects to visit the flowers and enhance
the pollination efficiency of loquat flowers.
In addition, the number of genes in the petals was significantly
higher between the bud and bloom stages than in the other two
groups (Figure 4B). It may be involved in petal expansion, pigment
accumulation, and the synthesis of fragrance compounds. There
were more down-regulated genes than up-regulated genes in petals
at the bloom stage, probably because petals at the bloom stage no
longer require genes with higher expression levels. On the contrary,
the down-regulation of genes may promote petal apoptosis, and
petals begin to enter the senescence phase. It has been reported that
the total number of up-regulated and down-regulated genes was the
highest in both the bud stage (FBE) and the bloom stage (FA) of
loquat flower development (Jing et al., 2020). It was consistent with
the results of this research, which showed that the highest intensity
of gene expression regulation was throughout the bud and bloom
stages of loquat flower development.
Interestingly, this study discovered a more significant number
of total up-and down-regulated genes between the bud and exposed
stages of stamens (Figure 4C). This implies that the dynamics of
gene expression were more dramatic during these two stages, which
could also be connected to the bud stage’s development of stamens
and pollen grain formation (Maura and Valentina, 2014).
4.3 Key pathway enrichments in hormone
and floral fragrance synthesis
This study conducted a GO enrichment analysis of loquat
flowers at different developmental stages (Figure 5). The results
indicate that loquat flowers play a key role in cellular energy
metabolism, signal transduction, and protein stability. Other
studies have also pointed out that loquat gene expression was
concentrated in cellular and metabolic processes, and was more
abundant in membranes, cells and organelles, mainly involving
binding, catalytic activity, and transport protein activity (Zhang
et al., 2022a), which was consistent with the findings of this study.
The results showed that the DEGs in loquat petals and
stamens were mainly enriched in the KEGG pathway in plant
FIGURE 7
Plot of gene expression trends at different developmental stages in petals (A) and stamens (B). The line graph trend represents the overall trend of
gene expression in this cluster over time. Significant clusters are highlighted with a colored background. The number at the top left of each line
graph was the name of the cluster.
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hormone signal transduction, starch and sucrose metabolism,
phenylpropanoid biosynthesis (Figure 6), and other related
research results also verified this point (Jing et al., 2020;Zhang
et al., 2022a), indicating that these metabolic pathways were
important for loquat flower development.
In this study, we further clarified the role of different parts in the
development of loquat flowers, and found that the expression of up-
regulated gene in petals and stamens (Figure 7), which may be
involved in the synthesis of aromatic compounds in petals and
pollen maturation. Plant hormone signaling was significantly
enriched in the gene expression trend of petals (Jing et al., 2020),
and it was speculated that it may regulate the production of floral
flavor volatiles. The biosynthesis of phenylpropanoid (Ramya et al.,
2017) and flavonoids affects the color of petals and stamens and
their attraction to pollinating insects, while changes in glucose
metabolism in stamens were associated with energy regulation.
4.4 Key genes in floral fragrance synthesis
The floral fragrance was a natural mechanism by which plants
attract pollinators. Floral fragrance consists of low molecular weight
volatile organic compounds (VOCs), typically produced by plants’
secondary metabolic pathways (Natalia et al., 2013). This study
discovered many phenylpropanoid biosynthesis-related genes in
loquat flowers’petals and stamens (Figure 8) in the top three
pathways. The specific loquat floral fragrance composition (2-
nitroethyl) benzen was reported to be oxidized by CYP94A90,
and produced from L-phenylalanine as a precursor (Yamaguchi
et al., 2021;Kuwahara and Asano, 2018). Based on the GC
(Figure 2) and transcriptome (Figure 9), PAAS (AADC), OMT,
and ADH, having the highest expression in petals at the bloom stage
verified by qPCR experiments (Figure 10B, 10D, 10E), were
positively correlated with volatile release (Figure 9B).
FIGURE 8
Metabolic pathways significantly enriched in petal (A) and stamen (B) in profile 9.
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Among them, the EjAADC1 was a key gene controlling the
biosynthesis of volatile benzene compounds in flowers (Koeduka
et al., 2017). EjAADC1 can convert L-phenylalanine into
phenylacetaldehyde, and was expressed explicitly in petals
(Koeduka et al., 2017). Similarly, the expression of PAAS in
Murraya paniculata was higher than that in Citrus maxima, with
the function of phenylacetaldehyde synthesis (Yang et al., 2023). For
the expression pattern of EjOMT, it was consistent with the changes
of volatile benzoates in the floral organs (Figure 10D). That
indicates that EjOMT1 has broad substrate specificity for
compounds with p-hydroxy and o-methoxy groups (Koeduka
et al., 2016a). In addition, the ADH family was involved in the
interconversion of various alcohols and aldehydes, including
phenylacetaldehyde (Strommer, 2011). Therefore, these key genes
identified in this study, PAAS,OMT, and ADH, were expressed in
the petals of loquat flowers at the complete bloom stage higher than
in the stamens. It suggests that they make a great contribution of
efficiently synthesizing volatile fragrance compounds in the petals
and thus attracts pollinators like bees.
In this study, we discovered that EjBS-bexpression of
benzaldehyde synthase was significantly higher in the petal
exposed stage than in the bloom stage (Figure 10A).
Benzaldehyde synthase was a heterodimeric enzyme consisting of
two subunits, aand b, which catalyze the synthesis of benzaldehyde
in the presence of both subunits together (Huang et al., 2022). The
significant up-regulation of the benzaldehyde synthase gene may
resulte in the synthesis and accumulation of benzaldehyde in the
petal exposed stage, and provide the base for the other derivatives in
the following blooming stage (Wickramasinghe and Munafo, 2020).
Therefore, the high concentrations of benzaldehyde and the
derivatives were released during the flowering period to attract
pollinators such as bees.
The ethylene biosynthesis gene EjACO was also discovered to be
expressed at a significantly higher level in loquat flowers’stamens
than in petals (Figure 10C). It implies that the cells of the stamen
part may have a higher demand or utilization efficiency for ethylene
synthesis during loquat flowers’stamen development. The same
example was discovered in carnations that flower senescence of
carnations was regulated by endogenous ethylene (Norikoshi et al.,
2022). In another study, one of four ACO genes in tomato flowers
had the highest expression and prompted the development of the
petals and pistils (Llop-Tous et al., 2000).
FIGURE 9
Gene heatmap of petals and stamens of loquat at different stages. (A) Hierarchical clustering analysis of key candidate DEGs for floral fragrance and
hormones. Z-score standardized gene expression level data. Red and blue represent up-regulated and down-regulated genes, respectively. Genes
related to floral fragrance synthesis (red annotation); genes related to hormones (black annotation). (B) Correlations between genes and volatile
compounds. The red and blue solid lines separately indicate positive and negative correlation, and the dotted line indicates a non-significant
correlation (p≥0.05). The higher the correlation coefficient (r. abs, absolute value), the thicker the line. The correlation coefficient of the heatmap is
Person’s r, red represents the higher rvalues. Gene expression patterns associated with floral fragrance volatiles (C) and hormone anabolism (D). The
corresponding synthetic pathways of phenethyl alcohol and 4-methoxybenzaldehyde, gibberellin (GA) and auxin (IAA) were analyzed at different
developmental stages of petals and stamens. Successive arrows indicate one-step enzymatic reactions, and dashed lines indicate unknown enzymes.
In the heat map, red and green indicate maximum and minimum values, respectively; each line was independent.
Huang et al. 10.3389/fpls.2025.1574771
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The expression of tyrosine aminotransferase EjTAT was
significantly higher in petals than in stamens during the dewlap
and bloom stages (Figure 10F). It has been reported in loquat, which
may produce methyl 4-methoxybenzoate, 4-methoxybenzaldehyde,
etc., through the metabolic pathway of tyrosine (Kuwahara and
Asano, 2018). The exposed stage may be when loquat blossoms get
ready to bloom to attract pollinators.
4.5 Key genes in hormone-related
This study discovered that the number of differential genes
engaged in plant hormone signal transduction was first in both
petals and stamens (Figure 6). The synergistic action of endogenous
hormones and flowering genes was critical to regulating blossoming
in loquat (Chi et al., 2020). The emission of floral fragrances was
indirectly influenced by phytohormones, which were crucial in
controlling flower development (Chandler, 2011).
In this study, we also discovered a positive correlation between
hormone genes and volatiles (Figure 9), and the expression of
hormone genes increases with the maturation of loquat flowers.
For example, the flowering hormone-associated effector protein
EjFTIP and EjGA2OX were increased only in petals, and its
expression in stamens was insignificant (Figures 10G,J). In
addition, OsFTIP1 has also been reported to be primarily
involved in regulating the flowering time in rice. It was
discovered that the degree of late flowering in OsFTIP1 RNAi
plants was mainly correlated with the down-regulated level of
FIGURE 10
qRT-PCR analysis of differentially expressed genes. (p<0.01).
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OsFTIP1 expression (Song et al., 2017). And it was reported that
JcGA2OX6 had a great impact on the vegetative and reproductive
growth of plants (Hu et al., 2017). Therefore, our results suggested
that EjFTIP and EjGA2OX may have a more pronounced impact
on petal development compared to stamens.
EjARG and EjGASA were significantly increased in petals and
up-regulated in stamens, with the lowest expression at the bud stage
(Figures 10H,I). Similar studies in roses showed that the expression
of ARG was up-regulated during flowering to promote flowering
(Guo et al., 2017). And in Prunus mume (Zhang et al., 2022b), nine
PmGASA have been discovered to be significantly increased in
expression during the bud opening stage. As regulators of loquat
blooming time, bud differentiation, and flower development,
PmGASA might be crucial to the flowering process of flower
buds. Thus, EjARG and EjGASA were commonly associated with
the flowering transition in loquat.
Only three petal stages in the current study showed
considerable up-regulation of EjLOG (Figure 10K), suggesting
that EjLOG was crucial for petal development. Key genes LOG1,
LOG3, and LOG7 in the cytokinin and gibberellin pathways of
chestnuts (Wu et al., 2022) have been reported to affect female
flower formation. In this study, EjPHY (Phytochrome) was
discovered to have the highest expression in petals at the exposed
stage (Figure 10L). The PHYB and PHYC were also discovered to
promote flowering through the photoperiodic pathway in Triticum
aestivum (Stephen et al., 2016). According to the information above,
photosensitive pigments control when flowers bloom during the
exposure stage. Petals may need to regulate PHY expression to
manage flowering timing and maximize pollination prospects.
5 Conclusion
In this study, GC analysis showed that the fragrance of loquat
flowers was primarily released in the blossom stage and from its
petals and stamens. The comparative transcriptomic analysis of
petals and stamens in the different developmental stages showed
that the development of petals occurs earlier than that of stamens,
and the changes in gene expression during the early and mid-
stages of stamens were more drastic. The KEGG enrichment
analysis revealed that the DEGs were primarily enriched in the
plant hormone signal transduction pathways related to
endogenous hormones and the phenylpropanoid biosynthesis
pathways associated with floral fragrance synthesis. PAAS and
OMT related to synthesis of key loquat floral volatiles were
screened from 19 up-regulated DEGs associated with
synthesizing loquat floral fragrance volatiles. GA2OX and ALDH
related to gibberellin and growth hormone were screened from 27
up-regulated DEGs linked to loquat hormone anabolism,
respectively. The expression of floral fragrance and hormone
synthesis genes in petals and stamens at different developmental
stages is positively correlated with the content of volatiles. Finally,
theexpressionof11candidategenes(5and6genesrelatedto
floral volatiles and hormone synthesis, respectively) were
validated by qRT-PCR.
Data availability statement
The datasets presented in this study can be found in online
repositories. The names of the repository/repositories and accession
number(s) can be found in the article/Supplementary Material.
Author contributions
J-QH: Data curation, Formal Analysis, Validation, Writing –
original draft, Writing –review & editing. J-QW: Data curation,
Validation, Writing –review & editing. FW: Formal Analysis,
Writing –review & editing. PZ: Data curation, Writing –review
& editing. J-JZ: Software, Writing –review & editing. L-XW:
Writing –review & editing. H-LL: Data curation, Formal
Analysis, Validation, Writing –review & editing.
Funding
The author(s) declare that financial support was received for the
research and/or publication of this article. This work was supported by
the National Natural Science Foundation of China (No. 32170531), and
the Three Agricultural Nine-party Science and Technology Collaboration
Projects of Zhejiang Province (2025SNJF083, 2023SNJF053).
Conflict of interest
The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Generative AI statement
The author(s) declare that no Generative AI was used in the
creation of this manuscript.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or
claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Supplementary material
The Supplementary Material for this article can be found online
at: https://www.frontiersin.org/articles/10.3389/fpls.2025.1574771/
full#supplementary-material
Huang et al. 10.3389/fpls.2025.1574771
Frontiers in Plant Science frontiersin.org15
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