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Article

Insights into Loquat Flowering Regulation Through Analysis of Alternative Splicing of Flowering-Time Genes and Functions of EjCO1 Isoforms

by
Wendong Wu
1,2,†,
Chongbin Zhao
1,2,†,
Jie Jiang
1,2,
Huijie Li
1,2,
Wenbing Su
3,
Yuanyuan Jiang
4,
Xianghui Yang
1,2,* and
Ze Peng
1,2,*
1
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou 510642, China
2
Key Laboratory of Innovation and Utilization of Horticultural Crop Resources in South China, Ministry of Agriculture and Rural Affairs, College of Horticulture, South China Agricultural University, Guangzhou 510642, China
3
Fruit Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350013, China
4
College of Biology and Agriculture, Shaoguan University, Shaoguan 512005, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Horticulturae 2025, 11(9), 1064; https://doi.org/10.3390/horticulturae11091064
Submission received: 17 July 2025 / Revised: 28 August 2025 / Accepted: 29 August 2025 / Published: 4 September 2025
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Abstract

Loquat (Eriobotrya japonica), an important subtropical fruit crop, blooms in autumn/winter, which is distinctive compared with other fruit trees such as apple, pear, and peach in Rosaceae. Currently, alternative splicing (AS) of flowering time genes remains understudied in loquat. In this study, full-length transcriptome sequencing of mixed tissues composed of leaves and shoot apical meristems/flower buds was performed and analyzed. A total of 94,194 high-quality isoforms and 44,186 complete open reading frames (ORFs) were obtained out of the 41.79 Gb of subread data. Further analysis revealed 25,988 AS events among 7461 genes, of which the most abundant type was intron retention (IR) occupying 55.32%. Importantly, 197 loquat genes homologous to Arabidopsis or Rosaceae flowering time genes were found to be alternatively spliced, including an important player CONSTANS (EjCO1) that contained three different isoforms (EjCO1-1, EjCO1-2, and EjCO1-3). To investigate the effect of AS on gene function, we overexpressed the three EjCO1 isoforms in Arabidopsis. The results showed that overexpression of EjCO1-1 and EjCO1-3 significantly promoted early flowering of transgenic Arabidopsis plants, whereas overexpressing EjCO1-2 did not significantly change the flowering time. Dual-luciferase reporter assays showed that EjCO1-1 and EjCO1-3 could significantly activate the expression of FLOWERING LOCUS T (EjFT2), while EjCO1-2 had no significant effect on the promoter activity of EjFT2. The results from this study systematically cataloged AS events of flowering time genes and illustrated the important effect of AS on gene functions, which provides insights into the molecular regulation of flowering time by AS in loquat.

1. Introduction

Flowering is an important part of plant development, essential for their survival and reproduction. Current studies have revealed that the flowering process in plants is regulated by multiple genetic pathways, including the photoperiod, age, autonomous, vernalization, hormonal, sugar, and circadian clock pathways [1,2,3,4]. These pathways operate both independently and interactively, forming a highly intricate and fine-tuned regulatory network that governs floral induction. Among them, the photoperiod pathway, which responds to seasonal changes in day length, plays a particularly critical role. Over the course of evolution, plants have developed sophisticated mechanisms to monitor day length as an environmental cue, enabling them to initiate flowering during periods with optimal climatic conditions to maximize reproductive success [5].
For most fruit trees in Rosaceae, such as apple and pear, flower bud differentiation occurs in summer or autumn, followed by a winter dormancy period, with flowering taking place the following spring [6]. However, loquat (Eriobotrya japonica Lindl.), an important fruit tree crop in Rosaceae, exhibits a distinct flowering pattern. Unlike other temperate fruit trees in Rosaceae, loquat bypasses the typical dormancy phase after flower bud differentiation and instead proceeds directly into reproductive development, ultimately flowering in autumn or winter [7,8]. This unusual flowering habit suggests that loquat may employ a unique regulatory mechanism governing floral induction. Investigating the flowering regulation of loquat could therefore lead to novel insights and possibly serve as a valuable supplement to our current understanding of flowering control in plants.
To date, several flowering-related genes have been identified and cloned from cultivated loquat, including APETALA1 (EjAP1), LEAFY (EjLFY), SUPPRESSOR OF OVEREXPRESSION OF CO 1 (EjSOC1), Squamosa promoter-binding-like (EjSPL3/4/5/9), TERMINAL FLOWER 1 (EjTFL1), FRIGIDA (EjFRI), RAV TEMPRANILLO (EjRAV1/2), and Gibberellic Acid-stimulated Arabidopsis (EjGASA6) [8,9,10]. Functional analyses suggest that these genes play relatively conserved roles in flowering regulation in loquat and Arabidopsis. In addition, it has been shown that among the two FLOWERING LOCUS T (EjFT) genes identified in loquat (EjFT1 and EjFT2), only EjFT2 is functionally involved in floral induction [11,12].
Previous studies have demonstrated that CONSTANS (CO), a central regulator in the photoperiod pathway, promotes the transcriptional activation of FT [13,14]. Interestingly, in Arabidopsis, CO undergoes alternative splicing (AS) to produce two isoforms, COα and COβ, which have been shown to exert different effects on flowering time regulation [15]. AS is a crucial post-transcriptional regulatory mechanism that contributes extensively to plant growth and development [16,17,18,19]. AS has been reported in various Rosaceae species, including chestnut rose (Rosa roxburghii Tratt.) [20], strawberry [21], apple [22,23], and white pear [24]. Several flowering-related genes, including FT [25], SPL4 [26], and EARLY FLOWERING 3 (ELF3) [27], have been reported to undergo AS in multiple plant species. However, to date, no studies have addressed the role of AS in flowering-related genes in loquat, and our understanding of AS remains largely unexplored in loquat.
With the advancement of high-throughput sequencing technologies, RNA-seq has become a widely used approach for studying gene expression regulation [28,29,30,31]. However, due to its limitation in read length, conventional RNA-seq cannot provide full-length transcript information [32]. In contrast, full-length transcriptome sequencing enables the direct acquisition of complete mRNA sequences, including 5′ untranslated regions (5′ UTRs), 3′ UTRs, and poly(A) tails, along with accurate transcript structure information. This technology has been increasingly applied to the study of AS and gene fusion events [33,34,35]. A study in peach integrated Iso-seq and RNA-seq to investigate tissue- or development stage-specific AS events [36]. In loquat, full-length transcriptome sequencing has already been employed in stress-related studies [37]. To the best of our knowledge, no studies have utilized this technology to investigate AS events during the floral transition or related with flowering in loquat.
In this study, we utilized full-length transcriptome sequencing to systematically characterize AS events in the shoot apical meristems and leaves covering the flowering process of loquat. Furthermore, we investigated the biological functions of different EjCO1 spliced variants and compared their transcriptional regulatory activity on downstream target genes through a series of molecular assays. Our findings provide preliminary insights into the molecular mechanisms by which EjCO1 isoforms participate in the regulation of flowering time in loquat. This study not only enhances our understanding of AS involved in the flowering regulatory network in loquat, but also offers a theoretical foundation for flowering time modulation and cultivar improvement.

2. Materials and Methods

2.1. Plant Materials

Samples for PacBio single-molecule real-time (SMRT) sequencing were collected from a loquat cultivar ‘Jiefangzhong’ (15-year-old) grown under standard management conditions in the Eriobotrya Germplasm Resource Nursery (EGRN) at South China Agricultural University (Latitude 23°9′37″ N, Longitude 113°21′22″ E, Elevation 32.5 m). EGRN is an outdoor facility located at Tianhe District, Guangzhou, China, which has a humid subtropical climate with dry winters (average annual air temperature 22.2 °C~23.1 °C, annual rainfall 1680 mm~1950 mm). In 2023, based on a previous observation of the flowering phenology of ‘Jiefangzhong’ [38], sampling of shoot apical meristems or floral buds was conducted biweekly starting from one month prior to floral bud differentiation until the initial flowering stage. To investigate gene/isoform expression patterns at different day times, mature leaves were also collected over a 24 h window (S1: 20:00, S2: 0:00, S3: 4:00, S4: 8:00, S5: 12:00, S6: 16:00) starting on 2 October 2023. All samples were collected from three ‘Jiefangzhong’ trees (vegetative clones) as three biological replicates, and they were immediately placed in liquid nitrogen and stored in −80 °C. Wildtype Col-0 and transgenic Arabidopsis, as well as Nicotiana benthamiana plants were grown in a growth chamber at 22 °C under a 16 h light/8 h dark photoperiod. Illumination was provided by full-spectrum white LED lights (FSL-T8/LED), with a light intensity of 100–120 μmol·m−2·s−1.

2.2. RNA Extraction and qRT-PCR

The FastPure Universal Plant Total RNA Isolation Kit (Vazyme, Nanjing, China) was used for RNA extraction following the manufacturer’s instructions. Gel electrophoresis (1% agarose gel) and Nanodrop were used for quality and quantity evaluation. cDNA was obtained using the Hifiar III 1st SrandcDNA Synthesis SuperMix for qPCR (gDNA digest plus) (Yeasen, Shanghai, China). Primers for qRT-PCR were designed based on ‘Jiefangzhong’ reference genome [39]. TransStart® Green qPCR SuperMix and LightCycler 480ⅡqPCR machine (Roche, Basel, Switzerland) were used. The ACTIN gene (EjACT) was used as an internal reference gene for quantitative real-time polymerase chain reaction (qRT-PCR) in loquat following previous descriptions [40]. The TUBULIN ALPHA-2 CHAIN gene (AtTUA2) was used as an internal reference gene for Arabidopsis [41]. Primer sequences are provided in Table S1.

2.3. PacBio SMRT Sequencing and Data Analysis

The RNA samples (RIN > 8 based on Agilent 2100) from shoot apical meristems/floral buds and leaves of ‘Jiefangzhong’ were mixed together in equal proportions. Samples were sent to Biomarker Company (Qingdao, China) for full-length transcriptome sequencing. After library construction, the sequencing was performed using the PacBio Sequel II platform (Pacific Biosciences, Menlo Park, CA, USA).
In this study, raw PacBio sequencing data were processed using the Iso-Seq3 pipeline (https://github.com/PacificBiosciences/IsoSeq, accessed on 19 April 2024), which includes three major steps: the generation and correction of circular consensus sequences (CCS), the identification of full-length non-chimeric (FLNC) reads, and isoform clustering. First, raw subreads were converted into CCS reads using CCS v6.2.0, with the following parameters: --min-rq 0.9 --min-passes 3 --min-length 200. Next, the Refine module of Iso-Seq3 was used to identify full-length reads, based on the presence of both 5′ and 3′ cDNA primers and poly(A) tails. The Lima tool (v2.1.0) was then employed to remove the 5′ and 3′ cDNA primers, and poly(A) tails were trimmed using the trim_polyA module of Iso-Seq3, yielding high-quality full-length reads. The isoform-level clustering of the full-length reads was performed using the ICE algorithm, with a sequence similarity threshold of 0.95, resulting in a set of high-quality, non-redundant full-length transcript isoforms. The polished consensus sequences were aligned to the reference genome of ‘Jiefangzhong’ [39] using minimap2 (v2.20-r1061), with parameters -ax splice -uf --secondary = no -C5. The resulting alignments were processed using the cDNA_Cupcake (v28.0.0) package to remove redundant isoforms. Transcript isoforms with sequence identity below 0.9 and coverage less than 0.85 were filtered out. Additionally, transcripts differing only at the 5′ exon boundaries were collapsed and merged to generate a final set of non-redundant transcript isoforms.

2.4. Alternative Splicing Analysis and Validation

Based on the genome annotation file of ‘Jiefangzhong’, AStalavista 4.0 [42] was used to identify alternative splicing (AS) events. AS events were classified into five types: (1) Alternative 5′ Splice Site (A5SS), (2) Alternative 3′ Splice Site (A3SS), (3) Exon Skipping (ES), (4) Intron Retention (IR), and (5) Mutually Exclusive Exons, (MX). To identify candidate flowering time genes in loquat orthologous to those in Arabidopsis, the known flowering time genes in FlOR-ID database (http://www.phytosystems.ulg.ac.be/florid/, accessed on 19 April 2024) were downloaded. OrthoFinder (v2.5.5) was used to identify loquat genes orthologous to those known flowering time genes. Additionally, the floral genes reported previously in Rosaceae [43] were also retrieved to identify orthologs in loquat using Blastp (e-value < 1 × 10−10). In order to verify the authenticity of the AS events, four candidate flowering time genes (Ej000036236, Ej00096158, Ej00043172, Ej00055553) were randomly selected for RT-PCR verification. Primers were designed for each isoform (Table S1), and previous RNA samples used for SMRT sequencing were used for validation. The amplified products were electrophoresed on a 1% agarose gel alongside a 2000 bp DNA ladder (Yeasen, China). The isoforms were considered validated if the amplified fragment lengths were consistent with that from full-length transcriptome analysis results. The three isoforms of EjCO1 were sequenced using the Sanger method.

2.5. Prediction of LncRNA

To systematically identify and characterize long non-coding RNAs (LncRNAs), we employed a multi-tiered computational pipeline incorporating Coding Potential Calculator (CPC) [44], Coding-Non-Coding Index (CNCI) [45], Pfam domain search [46], and Coding Potential Assessment Tool (CPAT) [47]. Transcripts predicted as non-coding by all four methods were retained as high-confidence lncRNA candidates.

2.6. Subcellular Localization

To investigate the subcellular localization of EjCO1-1, EjCO1-2, and EjCO1-3, their full-length coding sequences (CDS) (excluding the stop codon) were amplified using the samples for full-length transcriptome sequencing and cloned into the pBE-GFP vector, which carries a GFP reporter gene under the control of the CaMV 35S promoter (primers provided in Table S1). The resulting fusion constructs (35S::EjCO1-1-GFP, 35S::EjCO1-2-GFP, and 35S::EjCO1-3-GFP) along with the empty vector control (35S::GFP) were introduced into Agrobacterium tumefaciens strain GV3101 (pSoup). Transient expression was carried out in Nicotiana benthamiana leaves via Agrobacterium-mediated infiltration, following the method described by Sparkes et al. [48]. An mCherry fusion protein containing a nuclear localization signal (PHB-SV40-mCherry) was co-infiltrated to visualize the nucleus. After incubation in the dark for 24 h, followed by 24 h under light conditions, fluorescence signals were observed using a Zeiss Axio Imager D2 laser scanning confocal microscope (Zeiss, Jane, Germany).

2.7. Genetic Transformation of Arabidopsis

The full-length coding sequences of the three EjCO1 isoforms were amplified and cloned into the pGreenII-35S-HA vector [49] to generate overexpression constructs. The overexpression vectors were introduced into Agrobacterium tumefaciens GV3101 (pSoup). Col-0 Arabidopsis plants were transformed using the floral dip method [50]. T1 seeds were harvested and screened on medium containing 15 mg/L Basta. Putative transgenic T3 lines were confirmed by PCR with EjCO1-specific primers, and target gene expression was quantified via qRT-PCR using AtTUA2 as the internal reference [41].

2.8. Yeast Two-Hybrid Assay

Yeast two-hybrid (Y2H) assays were performed using the GAL4-based system (Clontech, Mountain View, CA, USA) to assess protein–protein interactions. The coding sequences of EjCO1-1, EjCO1-2, and EjCO1-3 were cloned into the pGADT7 (activation domain) and pGBKT7 (binding domain) vectors to generate recombinant constructs. These constructs, along with the corresponding empty vectors as negative controls, were co-transformed into Saccharomyces cerevisiae strain Y2H Gold following the manufacturer’s instructions (Weidi, Shanghai, China). Transformed yeast cells were initially selected on SD/-Leu/-Trp (SD/-L-W) medium and incubated at 30 °C for 3–4 days. Protein–protein interactions were evaluated by plating the transformants on stringent selection medium SD/-Ade/-His/-Leu/-Trp (SD/-A-H-L-W), with or without X-α-Gal (20 μg/mL). Plates were photographed after 3 days of incubation, and all assays were performed with three independent biological replicates.

2.9. Dual LUC Assay

To evaluate transcriptional activation, the coding sequences of EjCO1-1, EjCO1-2, and EjCO1-3 were cloned into the pGreenII 62-SK vector to generate effector constructs. The promoter region of EjFT2 was inserted upstream of the firefly luciferase (LUC) gene in the pGreenII 0800-LUC vector to create the reporter construct. Effector and reporter plasmids were mixed at a 9:1 ratio and co-infiltrated into Nicotiana benthamiana leaves via Agrobacterium tumefaciens-mediated transient transformation, as previously described by Sparkes et al. [48]. Leaves infiltrated with the reporter construct and the empty pGreenII 62-SK vector served as negative controls. After infiltration, luminescence signals were measured using the Dual-Luciferase Reporter Assay System (Yeasen, China) on a Fluoroskan Ascent FL microplate reader (Thermo Fisher Scientific, Waltham, MA, USA). Firefly luciferase activity was normalized to Renilla luciferase activity, in accordance with the manufacturer’s instructions [51].

3. Results

3.1. Summary of SMRT Sequencing

As leaves and shoot apical meristems are the two major types of tissues involved in the flowering process, the RNA samples of them from ‘Jiefangzhong’ were mixed and subjected to PacBio Sequel II platform sequencing. A total of 30.35 million subreads with an average length of 1383 bp totaling 41.97 Gb of data were obtained. After filtering and correction (full passes ≥ 3, read quality ≥ 0.9), 516,184 circular consensus sequence (CCS) reads were obtained. Further clustering of 418,868 full-length non-chimeric (FLNC) reads led to 172,106 high-quality isoforms. After removing redundancy, 94,194 transcript sequences were finally obtained (Table 1).

3.2. Alternative Splicing of Flowering Time Homologs and Validation

Alternative splicing (AS) analysis identified 25,988 AS events corresponding to 7461 genes (Table S2). Among those AS events, intron retention was the most abundant type (55.32%), followed by alternative 3′ splice site (19.59%), exon skipping (12.66%), alternative 5′ splice site (11.25%), and mutually exclusive exon (1.19%) (Figure 1A). By comparing loquat genes with known flowering time genes in Arabidopsis in the FLOR-ID database, as well as with those reported in Rosaceae, we identified 521 homologs in loquat. Further comparing these 521 homologs with the 7461 genes with AS events, we finally obtained 197 flowering time candidate genes in loquat that were alternatively spliced (Figure 1B, Table S2). To validate the reliability of these AS events, we randomly selected four genes, including homologs of SHORT VEGETATIVE PHASE (SVP, Ej00036236), CONSTITUTIVELY PHOTOMORPHOGENIC 1 (COP1, Ej00096158), Cryptochromes 2 (CRY2, Ej00043172), and CO (Ej00055553), for primer design and RT-PCR validation of different spliced isoforms. The results supported the validity of AS analysis (Figure 1C and Figure S1). In addition, we identified 4063 genes with alternative polyadenylation (APA), among which 2291 genes had at least three poly(A) sites (Figure S2).

3.3. LncRNA Prediction

We applied four methods for long non-coding RNA (LncRNA) prediction, including CPC, CNCI, pfam, and CPAT, which identified 8075, 3512, 2903, and 7878 LncRNAs, respectively. The 2903 common LncRNAs predicted by all four methods were further analyzed (Figure 2A). By comparing their positions with the GFF, we found that the majority of them were long intergenic non-coding RNA (LincRNA) (78.7%), followed by sense LncRNA (14.2%), antisense-LncRNA (6.8%), and intronic-LncRNA (0.2%) (Figure 2B).

3.4. Comparison and Interaction Among Three Isoforms of EjCO1

CO is an important player controlling flowering time by integrating photoperiod signals and directly activating the expression of FT [52]. In loquat, we identified three alternatively spliced isoforms of EjCO1, namely EjCO1-1, EjCO1-2, and EjCO1-3 (Figure 1C). It turned out that EjCO1-1 corresponds to the version in the gene annotation file (GFF) of ‘Jiefangzhong’ with two exons and one intron (Figure 3A). The generation of EjCO1-2 and EjCO1-3 was due to intron retention which is the most abundant type of AS. EjCO1-1 encodes 393 amino acids, while the other two encode shorter peptides, with EjCO1-2 encoding 291 amino acids and EjCO1-3 encoding 290 amino acids (Figure 3A,B). The AS events influenced the CCT motif of the EjCO1 protein.
To investigate the expression patterns of EjCO1 isoforms, primers that could differentiate these three isoforms were designed for qRT-PCR. Expressions were investigated during a time window (at noon, 13 June~22 August 2023) covering flower bud differentiation (Figure 3C) based on previous observations. It showed that EjCO1-1 was predominantly expressed, followed by EjCO1-2, whereas EjCO1-3 was almost undetectable. However, when under a shorter daytime condition (24 h window, starting from 2 October 2023), EjCO1-3 was expressed at a higher level compared with EjCO1-2, while EjCO1-1 was still predominantly expressed (Figure 3D). These results showed that all three isoforms exist although in different proportions at different times throughout the year.
Consistent with the localization pattern of the two AtCO isoforms in Arabidopsis [15], all three EjCO1 isoforms were also localized in the nucleus (Figure 4A). To investigate whether the three types of proteins were interactive with each other, yeast two-hybrid assay was carried out. The results showed that all three pairs were interactive with each other (Figure 4B).

3.5. Functional Differentiation Among EjCO1 Isoforms

To investigate whether different EjCO1 versions play different functions in controlling flowering time, the CDS of each EjCO1 was cloned into a pGreenII-35S-HA vector and overexpressed in Arabidopsis. The results showed that overexpression of EjCO1-1 and EjCO1-3 significantly promoted early flowering of transgenic Arabidopsis plants, whereas no significant difference was observed for EjCO1-2 (Figure 5A,B). Similarly, the rosette leaf numbers of 35S:EjCO1-1 and 35S:EjCO1-3 transgenic plants were significantly smaller than that of the wildtype, whereas no significant difference was observed for 35S:EjCO1-2 plants (Figure 5C). Consistent with the phenotype, the expressions of AtAP1, AtFT, and AtSOC1 were significantly promoted in 35S:EjCO1-1 and 35S:EjCO1-3 transgenic plants, whereas no significant difference was observed for 35S:EjCO1-2 plants (Figure 5D–F). Collectively, the results showed that two of the isoforms (EjCO1-1 and EjCO1-3) were functional in promoting early flowering, but EjCO1-2 did not influence flowering time.

3.6. Differential Regulation of EjFT2 Promoter Activity by EjCO1 Isoforms

In Arabidopsis, CO-FT is a central hub of flowering time regulation. To explore the possible reason for functional differences among EjCO1 isoforms, a promoter sequence of 2000 bp of EjFT2, which was previously proven to play a role in controlling flowering time of loquat [12], was cloned into the pGreenII 0800-LUC vector as a reporter. The full-length coding sequences of the three isoforms were cloned into the pGreenII 62SK vector as the effectors (Figure 6A). Dual-luciferase assays were applied to evaluate differential transcriptional activation capacities of different EjCO1 isoforms on EjFT2 promoter. The results showed that EjCO1-1 and EjCO1-3 significantly activated the expression of EjFT2, whereas no activation effect was identified for EjCO1-2 (Figure 6B). This result was consistent with that of the above genetic transformation experiments.

4. Discussion

Alternative splicing (AS), an important post-transcriptional regulatory mechanism, is widely involved in plant development and environmental responses [16,17,18]. Previous studies have shown that several key flowering time-related genes undergo AS, such as CO in Arabidopsis thaliana [15], ELF3 in pear [27], and FT6/8 in Asiatic lily [25]. However, to date, no studies have systematically examined alternative splicing events during the floral transition in loquat, nor have the biological functions of different isoforms of flowering time-related genes been explored. In this study, we applied full-length transcriptome sequencing to systematically catalog AS events potentially associated with flowering and demonstrated that the three isoforms of EjCO1 exhibit distinct biological functions in regulating loquat flowering. In addition, we identified 4063 genes potentially involved in post-transcriptional regulation through alternative polyadenylation (APA), as well as 2903 long non-coding RNAs (LncRNAs), which may serve as valuable resources for future investigations into the post-transcriptional regulatory mechanisms of flowering. Our findings not only provide new insights into the molecular regulation of AS on flowering in loquat, but also offer a theoretical foundation for manipulating flowering time and breeding new cultivars for loquat.
Due to the short-read limitations of NGS, it is unable to capture full-length transcript information. In contrast, full-length transcriptome sequencing offers distinct advantages in identifying novel isoforms and resolving complex AS events. While this technology has shown promising applications in stress-related studies of loquat [37], we primarily employed it to investigate AS events potentially associated with flowering time regulation in loquat. Among the 25,988 AS events detected across 7461 genes, intron retention (IR) was the most prevalent type, accounting for 55.32% of all AS events. This splicing pattern is consistent with findings in Arabidopsis [53] and potato (Solanum tuberosum) [34], where IR was also the most frequent AS event type. In Phyllostachys edulis (Moso bamboo), PeCOL13 undergoes IR to produce two isoforms, CONSTANS-like (PeCOL13α) and PeCOL13β, which have been shown to perform distinct functions during floral induction [54]. Similarly, in Arabidopsis, the CO gene generates two splice variants, COα and COβ, via intron retention, and these isoforms have antagonistic effects on flowering time regulation [15]. These findings collectively demonstrate that IR is not only a widespread and abundant alternative splicing event in plants, but also that the resulting isoforms may differ significantly in their biological functions.
Using four computational approaches, CPC, CNCI, Pfam, and CPAT, we identified a total of 2903 LncRNAs based on the intersection of predictions. Increasing evidence has shown that LncRNAs play essential roles in various biological processes, ranging from the regulation of flowering to the control of lateral root development [55,56]. In Arabidopsis thaliana, LncRNAs such as COLDAIR and AG-intron-4 have been reported to participate in the transcriptional silencing of key flowering genes FLOWERING LOCUS C (FLC) and AGAMOUS (AG), thereby influencing flowering time [57,58]. Therefore, the lncRNAs identified in this study may serve as candidates for future investigations into their potential roles in regulating flowering time.
CO is a central integrator in the photoperiodic flowering pathway [59], coordinating various internal and external environmental cues to regulate the floral transition in Arabidopsis [13]. In this study, we identified three distinct CO transcript variants in loquat, with one canonical and the remaining two generated through intron retention. qRT-PCR analysis revealed that during floral bud differentiation, the canonical isoform EjCO1-1 was predominant, followed by EjCO1-2, while EjCO1-3 was barely detectable. Under short-day conditions, EjCO1-1 remained the major transcript, but EjCO1-3 was expressed at higher levels than EjCO1-2. This finding suggests that the expression of CO isoforms is likely influenced by environmental conditions. Similar findings have been reported in apple. AS of MdFLC1 generates three isoforms, MdFLC1a, MdFLC1b, and MdFLC1c, among which MdFLC1c retains the complete MIKC-type MADS protein structure, whereas MdFLC1a and MdFLC1b undergo intron retention, resulting in the loss of protein domains [23]. During the juvenile phase, MdFLC1b and MdFLC1c are highly expressed, but their expressions are significantly reduced in both the transitional and adult phases. Notably, in the regulation of seasonal flowering, the expression patterns of all three MdFLC1 isoforms are highly correlated with those of flowering-related genes such as MdFT and MdTFL. Subcellular localization experiments demonstrated that all three EjCO1 isoforms are localized in the nucleus, and yeast two-hybrid assays confirmed protein–protein interactions among the isoforms. These results are consistent with those reported in Arabidopsis, where two CO isoforms interact at the protein level [15]. However, unlike Arabidopsis, which only produces two CO isoforms, loquat possesses three, indicating that while CO function is conserved between species to some extent, species-specific diversification may also exist.
The genetic transformation experiments in Arabidopsis showed that overexpression of EjCO1-1 and EjCO1-3 significantly promoted the expression of key flowering genes FT and SOC1, as well as the floral meristem identity gene AP1, leading to early flowering in transgenic Arabidopsis. In contrast, overexpression of EjCO1-2 did not significantly alter flowering time, nor did it affect the expression levels of FT, SOC1, or AP1. Dual-luciferase reporter assays further demonstrated that EjCO1-1 and EjCO1-3 strongly activated the EjFT2 promoter, whereas EjCO1-2 had no significant effect on EjFT2 promoter activity. These results indicate that the three CO isoforms in loquat exhibit functional divergence: EjCO1-1 and EjCO1-3 promote flowering by activating EjFT2 expression, while EjCO1-2 has lost this regulatory capacity due to its inability to activate EjFT2 transcription. This finding differs somewhat from observations in Arabidopsis, where the two CO isoforms were reported to have antagonistic roles in flowering regulation [15]. It is likely that the functional divergence among the three EjCO1 isoforms arises primarily from variations in the CCT motif of the protein, a hypothesis that warrants further in-depth experimental investigation. Collectively, our results suggest that although the biological function of canonical CO transcripts is conserved across species, alternative splicing can produce isoforms with distinct functional roles. In white pear, PpDAM1 undergoes alternative splicing to generate three mRNA isoforms [24]. Alternative splicing of PpDAM1 does not alter its nuclear localization or dimerization ability, but it affects the nuclear transport of PpDAM1 dimers. Overexpression experiments have shown that only the PpDAM1.2 isoform can delay flowering in Arabidopsis, which is highly consistent with our experimental results. This highlights the complexity and diversity of post-transcriptional regulation in plant development. In addition to this functional divergence, seasonal variations in the expression of the isoforms themselves may also contribute to differential EjFT2 expression and, consequently, to variations in flowering behavior. However, further systematic and in-depth studies on their seasonal expression patterns are needed.
In summary, the full-length transcriptome data, the catalog of AS events, and the functional characterization of different EjCO1 isoforms provide valuable insights into the molecular regulation of flowering time by AS in loquat and lay a solid foundation for future research.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/horticulturae11091064/s1, Figure S1: Sequence comparison of three EjCO1 isoforms and validation using Sanger sequencing; Figure S2: Distribution of the number of genes with polyadenylation sites; Table S1: Primer sequences used in this study; Table S2: Summary of alternative splicing events.

Author Contributions

Conceptualization, Z.P. and X.Y.; methodology, W.W. and C.Z.; formal analysis, W.W., C.Z. and Z.P.; investigation, W.W., C.Z., J.J., H.L., W.S. and Y.J.; resources, Z.P. and X.Y.; data curation, W.W. and Z.P.; writing—original draft preparation, W.W. and C.Z.; writing—review and editing, Z.P. and X.Y.; visualization, W.W., C.Z., J.J., W.S. and Y.J.; supervision, Z.P. and X.Y.; project administration, Z.P. and X.Y.; funding acquisition, Z.P., X.Y. and W.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Natural Science Foundation of China (32202429), Natural Science Foundation of Guangdong Province (2022A1515012273, 2024A1515013141), Fujian Academy of Agricultural Sciences External Cooperation Project (DWHZ2024-11), Guangzhou Science and Technology Project (202201010345), the Open Fund of the Guangdong Provincial Key Laboratory of Utilization and Conservation of Food and Medicinal Resources in Northern Region (Grant number FMR2022009Z).

Data Availability Statement

The raw SMRT sequencing data have been deposited in the Genome Sequence Archive in National Genomics Data Center, China National Center for Bioinformation under accession number CRA027905. The non-redundant transcripts and LncRNAs have been deposited in the Zenodo database (https://doi.org/10.5281/zenodo.16882376).

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Alternative splicing analysis and validation. (A) Proportions of five different types of alternative splicing events. (B) Venn diagram comparing a list of candidate flowering time genes and the list of genes with alternative splicing. (C) Gel electrophoresis results from RT-PCR showing experimental validation of alternative splicing events for homologs of SVP2 (Ej00036236), COP1 (Ej00096158), CRY2 (Ej00043172), and CO1 (Ej00055553). From top to bottom, the sizes of the marker bands are: 2000 bp, 1000 bp, 750 bp, 500 bp, 250 bp, and 100 bp.
Figure 1. Alternative splicing analysis and validation. (A) Proportions of five different types of alternative splicing events. (B) Venn diagram comparing a list of candidate flowering time genes and the list of genes with alternative splicing. (C) Gel electrophoresis results from RT-PCR showing experimental validation of alternative splicing events for homologs of SVP2 (Ej00036236), COP1 (Ej00096158), CRY2 (Ej00043172), and CO1 (Ej00055553). From top to bottom, the sizes of the marker bands are: 2000 bp, 1000 bp, 750 bp, 500 bp, 250 bp, and 100 bp.
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Figure 2. Summary of predicted LncRNAs. (A) Venn diagram showing the number of LncRNAs identified with the four methods. (B) Classification of LncRNAs based on their location in the GFF.
Figure 2. Summary of predicted LncRNAs. (A) Venn diagram showing the number of LncRNAs identified with the four methods. (B) Classification of LncRNAs based on their location in the GFF.
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Figure 3. Comparisons of structures and expressions among the three EjCO1 isoforms. (A) Illustration of alternative splicing events of EjCO1. The three isoforms share the same first exon but differ at the second exon. ‘F’ and ‘R’ indicate the schematic representation of the forward and reverse primer design, respectively. (B) Comparison of amino acid sequences of the three isoforms. (C) Expression patterns of three EjCO1 isoforms at 12:00 noon on six different days in 2023 (P1: 13 June, P2: 27 June, P3: 11 July, P4: 25 July, P5: 8 August, 22 August). (D) Expression patterns of three EjCO1 isoforms during a 24 h window (S1: 20:00, S2: 0:00, S3: 4:00, S4: 8:00, S5: 12:00, S6: 16:00) starting on 2 October 2023. The error bars in (C,D) represent standard deviations from three biological replicates. In (C,D), ‘**’ indicates significant difference (p < 0.01) among all pairwise comparisons of the three transcripts based on t-test.
Figure 3. Comparisons of structures and expressions among the three EjCO1 isoforms. (A) Illustration of alternative splicing events of EjCO1. The three isoforms share the same first exon but differ at the second exon. ‘F’ and ‘R’ indicate the schematic representation of the forward and reverse primer design, respectively. (B) Comparison of amino acid sequences of the three isoforms. (C) Expression patterns of three EjCO1 isoforms at 12:00 noon on six different days in 2023 (P1: 13 June, P2: 27 June, P3: 11 July, P4: 25 July, P5: 8 August, 22 August). (D) Expression patterns of three EjCO1 isoforms during a 24 h window (S1: 20:00, S2: 0:00, S3: 4:00, S4: 8:00, S5: 12:00, S6: 16:00) starting on 2 October 2023. The error bars in (C,D) represent standard deviations from three biological replicates. In (C,D), ‘**’ indicates significant difference (p < 0.01) among all pairwise comparisons of the three transcripts based on t-test.
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Figure 4. Subcellular localization and protein–protein interactions of the three EjCO1 isoforms. (A) Subcellular localization of three EjCO1 proteins expressed in tobacco epidermal cells. The bar indicates 50 µm. (B) Yeast two-hybrid assay of the EjCO1 proteins. Blue colors indicate positive interactions between a pair of proteins.
Figure 4. Subcellular localization and protein–protein interactions of the three EjCO1 isoforms. (A) Subcellular localization of three EjCO1 proteins expressed in tobacco epidermal cells. The bar indicates 50 µm. (B) Yeast two-hybrid assay of the EjCO1 proteins. Blue colors indicate positive interactions between a pair of proteins.
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Figure 5. Phenotypic observation of transgenic Arabidopsis plants and expressions of related genes. (A) Phenotypic observation of 35S:EjCO1-1, 35S:EjCO1-2, 35S:EjCO1-3, and wildtype Col-0 Arabidopsis plants. (B) The number of days from sowing seeds to flowering. The error bar represents standard deviations (n = 15). Different letters indicate significant differences (p < 0.05). (C) The number of rosette leaves at flowering. The error bar represents standard deviations (n = 15). Different letters indicate significant differences (p < 0.05). (D) Expression of AtAP1 in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. (E) Expression of AtFT in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. (F) Expression of AtSOC1 in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. Statistical analysis is based on t-test. For (B–F), each column represents a transgenic line overexpressing each of the construct, while Col-0 indicates the wildtype plant. ‘*’ indicates p < 0.05; ‘**’ indicates p < 0.01; ‘***’ indicates p < 0.001; ‘****’ indicates p < 0.0001; ‘ns’ indicates no significant difference.
Figure 5. Phenotypic observation of transgenic Arabidopsis plants and expressions of related genes. (A) Phenotypic observation of 35S:EjCO1-1, 35S:EjCO1-2, 35S:EjCO1-3, and wildtype Col-0 Arabidopsis plants. (B) The number of days from sowing seeds to flowering. The error bar represents standard deviations (n = 15). Different letters indicate significant differences (p < 0.05). (C) The number of rosette leaves at flowering. The error bar represents standard deviations (n = 15). Different letters indicate significant differences (p < 0.05). (D) Expression of AtAP1 in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. (E) Expression of AtFT in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. (F) Expression of AtSOC1 in transgenic and wildtype Arabidopsis plants. The error bar indicates standard deviations from 5 biological replicates. Statistical analysis is based on t-test. For (B–F), each column represents a transgenic line overexpressing each of the construct, while Col-0 indicates the wildtype plant. ‘*’ indicates p < 0.05; ‘**’ indicates p < 0.01; ‘***’ indicates p < 0.001; ‘****’ indicates p < 0.0001; ‘ns’ indicates no significant difference.
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Figure 6. Differential regulation of EjFT2 by three EjCO1 isoforms. (A) Illustration of Reporter and Effector vectors. (B) The relative LUC/REN ratios for different combination of EjCO1 isoforms and EjFT2 promoter. ‘**’ indicates p < 0.01; ‘ns’ indicates no significant difference.
Figure 6. Differential regulation of EjFT2 by three EjCO1 isoforms. (A) Illustration of Reporter and Effector vectors. (B) The relative LUC/REN ratios for different combination of EjCO1 isoforms and EjFT2 promoter. ‘**’ indicates p < 0.01; ‘ns’ indicates no significant difference.
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Table 1. Summary statistics of SMRT full-length transcriptome sequencing.
Table 1. Summary statistics of SMRT full-length transcriptome sequencing.
ItemInformation
Subreads base (bp)41,973,500,803
Number of subreads30,346,772
Average subreads length (bp)1383
Number of CCS reads516,184
Average CCS read Length (bp)1683
Number of full-length non-chimeric reads418,868
Number of consensus isoforms172,158
Average read length of consensus isoforms (bp)1598
Number of high-quality isoforms172,106
Number of non-redundant high-quality isoforms94,194
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Wu, W.; Zhao, C.; Jiang, J.; Li, H.; Su, W.; Jiang, Y.; Yang, X.; Peng, Z. Insights into Loquat Flowering Regulation Through Analysis of Alternative Splicing of Flowering-Time Genes and Functions of EjCO1 Isoforms. Horticulturae 2025, 11, 1064. https://doi.org/10.3390/horticulturae11091064

AMA Style

Wu W, Zhao C, Jiang J, Li H, Su W, Jiang Y, Yang X, Peng Z. Insights into Loquat Flowering Regulation Through Analysis of Alternative Splicing of Flowering-Time Genes and Functions of EjCO1 Isoforms. Horticulturae. 2025; 11(9):1064. https://doi.org/10.3390/horticulturae11091064

Chicago/Turabian Style

Wu, Wendong, Chongbin Zhao, Jie Jiang, Huijie Li, Wenbing Su, Yuanyuan Jiang, Xianghui Yang, and Ze Peng. 2025. "Insights into Loquat Flowering Regulation Through Analysis of Alternative Splicing of Flowering-Time Genes and Functions of EjCO1 Isoforms" Horticulturae 11, no. 9: 1064. https://doi.org/10.3390/horticulturae11091064

APA Style

Wu, W., Zhao, C., Jiang, J., Li, H., Su, W., Jiang, Y., Yang, X., & Peng, Z. (2025). Insights into Loquat Flowering Regulation Through Analysis of Alternative Splicing of Flowering-Time Genes and Functions of EjCO1 Isoforms. Horticulturae, 11(9), 1064. https://doi.org/10.3390/horticulturae11091064

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