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Article

In Vitro Pollen Viability, Fluorescence Microscopy, and Transcriptomic Comparison of Self-Pollinated and Cross-Pollinated Inflorescence of Artemisia annua L. to Analyze Candidate Self-Incompatibility-Associated Genes

by
Yimei Zang
1,2,†,
Shengrong Cui
2,3,†,
Shugen Wei
4,
Limei Pan
4,
Lingyun Wan
4,
Xiaojun Ma
2,
Zuliang Luo
2,
Jine Fu
4,* and
Chongnan Wang
2,*
1
Biomedicine College, Beijing City University, Beijing 100094, China
2
State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-di Herbs, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100193, China
3
National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
4
Guangxi Botanical Garden of Medicinal Plants, Nanning 530023, China
*
Authors to whom correspondence should be addressed.
†
These authors contribute equally to this work.
Horticulturae 2025, 11(7), 790; https://doi.org/10.3390/horticulturae11070790
Submission received: 25 April 2025 / Revised: 25 June 2025 / Accepted: 30 June 2025 / Published: 3 July 2025
(This article belongs to the Section Medicinals, Herbs, and Specialty Crops)
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Abstract

Artemisia annua L., the primary source of the antimalarial compound artemisinin, is of great importance for malaria treatment. However, its self-incompatibility (SI) restricts selfing breeding and results in unstable artemisinin content which is vulnerable to environmental fluctuations. To address this, our study employed fluorescence microscopy and transcriptomic analysis on stigmas post self- and cross-pollination to explore the molecular mechanisms of SI in Artemisia annua L. Fluorescence microscopy observations indicate that, three hours after pollination, cross-pollinated pollen tubes mostly exhibit normal filamentous growth, whereas the growth of self-pollinated pollen tubes is significantly inhibited, with most appearing as growth-arrested pollen tubes. Using transcriptome analysis, we generated approximately 25.03 GB of data assembled into 69,498 genes and identified 620 differentially expressed genes (DEGs), including 10 classified as SI response genes. Several specific SI-related candidate genes were identified, such as the S-locus receptor kinase (SRK), Calmodulin-like (CML), modifier (MOD), and exocyst complex component (EXO) genes, between AasB and AahA. These DEGs provide vital information for studying A. annua’s SI molecular mechanisms. The putative DEGs between the two groups provided important information for a further study of the molecular mechanisms of SI in A. annua. Candidate SI-associated genes are essential for the genetic engineering of A. annua to overcome SI and to avoid breeding inbred lines.

1. Introduction

Self-incompatibility (SI) evolved as a barrier to prevent self-fertilization, promoting outcrossing to increase genetic diversity for the survival and evolution of plant populations [1]. It also has significant practical importance in hybrid breeding and the utilization of heterosis. SI occurs widely in angiosperms and flowering plants, which are sub-categorized into sporophytic self-incompatibility (SSI) and gametophytic self-incompatibility (GSI) based on the specific phase of rejection during fertilization and different genetic and molecular mechanisms [2,3]. In SSI, the incompatibility response is determined by the sporophytic genotype of both pollen (parental origin) and the stigma, resulting in pollen tube growth arrest prior to reaching the ovary. In contrast, under GSI, recognition relies on the haploid genotypes of pollen (gametophytic) and the pistil, allowing pollen tubes to germinate and penetrate the ovary but preventing their normal growth or ability to reach the ovules. The mechanism of SSI is best known in the Brassicaceae family plants [4], including Brassica oleracea, Brassica rapa, and Brassica napus. In these SSI plants, S-ribonuclease (S-RNase) harbors at least three key proteins: S-locus glycoprotein (SLG), S-locus receptor kinase (SRK), and S-locus cysteine-rich protein (SCR). Among these, SLG and SRK regulate the self-incompatibility response in the pistil, while SCR governs pollen self-incompatibility [5].
SI is widespread in Asteraceae plants, including Erigeron breviscapus [6], Cichorium intybus [7], Matricaria chamomilla [8], Tolpis coronopifolia [9], Lactuca sativa L. [10], and Chrysanthemum morifolium [11]. Tan et al. [11] tested 22 Chrysanthemum accessions for in vivo germination. After self-pollination, they used a fluorescence microscope to observe pollen germination on the stigma. In five accessions, the in vivo germination rate was much lower than the in vitro rate, demonstrating that these accessions exhibited SI [12]. Wang Fan et al. [13,14] selected the self-incompatible Chrysanthemum morifolium ‘Q10-22-2’ from 24 varieties. The transcriptome sequencing of stigmas and anthers at different developmental stages identified 15 candidate stigma S genes and 6 candidate pollen S genes. After cloning CmSRK1 and CmPCP1 and constructing vectors, the low fruit set rate in the resulting transgenic Arabidopsis hybrids confirmed these two genes as the stigma and pollen S genes of C. morifolium, indicating that the SI of chrysanthemum belonged to SSI.
Artemisia annua L. belongs to the Asteraceae family, which is the natural source of artemisinin, one of the most effective antimalaria antibiotics in existence [15,16]. A. annua has a very low natural content of artemisinin, and the drug is produced from the plant using a direct extraction method. Previous studies have shown that the artemisinin content in A. annua from the United States, India, Vietnam, and China is 0.05–0.21%, 0.42%, 0.86%, and 0.16–0.97%, respectively, rendering direct extraction inefficient [17,18,19]. It is reported that every 1% increase in artemisinin content will reduce extraction costs by 60–70%. Therefore, it has always been the main goal of breeders to obtain the best variety with high artemisinin content [18,20,21]. The long-term natural hybridization of A. annua has resulted in a highly variable artemisinin content. The artemisinin content of the same cultivar is significantly reduced after continuous planting. Inbred varieties, characterized by genotype homozygosity and phenotypic stability, are pivotal for hybrid breeding programs. However, A. annua exhibits strict self-incompatibility (SI) that prevents the utilization of elite inbred lines with desirable traits as parental plants. This limitation severely constrains the selection and combination of parental lines in hybridization strategies. To overcome this bottleneck, it is imperative to identify the self-incompatibility in A. annua and analyze its regulatory mechanisms.
In this study, we explored the self-incompatibility of Artemisia annua through morphological evaluation and transcriptomic data. Initially, in vitro culture determined the optimal pollen viability time. Next, fluorescence microscopy was used to observe pollen germination on stigmas from self-pollination and cross-pollination, identifying A. annua as SSI. Subsequently, the transcriptomic sequencing of stigmas was performed to uncover genes involved in SI, its general mechanism, and its development based on gene expression profiles. The candidate genes identified here are anticipated to elucidate the SI mechanism and accelerate the development of pure germplasm in A. annua.

2. Materials and Methods

2.1. Plant Material and Growth Conditions

The seeds of cultivars of Guihao 1 and Guihao 3 were collected from Guangxi Botanical Garden of Medicinal Plants (Nanning, China). A. annua cultivars Guihao 1 and Guihao 3 were identified by Prof. Xiaojun Ma from the Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences. The germination and transplant trials were completed in the horticultural nursery of Guangxi Botanical Garden of Medicinal Plants. Cultivation requires temperatures of 20–30 °C, with shading necessary above 35 °C. Full sunlight exposure (≥6 h/day of direct light) is essential. Watering frequency: seedlings every 3–5 days (5 L/m2 per session); rapid growth stage every 7–10 days (10 L/m2 per session); budding stage every 15 days (8 L/m2 per session).

2.2. Pollen In Vitro Germination

To evaluate the viability of pollen from Artemisia annua cultivar ‘Guihao 3’, we collected fresh pollen grains between 9:00 and 11:00 a.m. on sunny days using a soft brush. We prepared a culture medium containing 100 g/L sucrose, 20 mg/L H3BO3, 30 mg/L CaCl2, and 10% PEG-8000, adjusted to pH 7.0. This medium was dropped onto a concave slide, and pollen grains with different storage durations were evenly spread over it. The slide was then placed in a Petri dish lined with moist filter paper to maintain humidity, which is beneficial for pollen germination and reduces rapid evaporation of the medium. Subsequently, the Petri dish was incubated in a growth chamber at 25 °C with light. Generally, pollen viability declines within a few hours after being detached from the anther [12,22]. Therefore, pollen germination rates were observed microscopically at 3, 4, 5, and 6 h post incubation. Each treatment was replicated three times biologically, with three microscopic fields examined per replicate. Germination was determined according to pollen tubes extending beyond the grain diameter, and mean germination rates (%) were calculated based on these observations. Data analysis was performed using Excel 2019 to calculate the mean germination rate (%) and the relative standard deviation (RSD, %) for each treatment.

2.3. Fluorescence Microscopic Observation of Pollen Tube Growth

Artificial pollination was performed during anthesis from 9:00 to 11:00 a.m. on a sunny day. Pollination combinations were as follows: self-pollination (AasB) of Guihao 1 × Guihao 1, and cross-pollination (AahA) of Guihao 1 × Guihao 3. Flowers in the balloon stage were bagged after being self- or cross-pollinated.
Inflorescences were collected at 3, 12, and 24 h after self-pollination and cross-pollination, fixed in FAA fixative (90:5:5 ethanol/formaldehyde/acetic acid) for 24 h, rinsed with distilled water until free from acetic acid, then stored in 75% ethanol at 4 °C. For rehydration, they were treated sequentially in 60%, 50%, and 40% ethanol for 20 min each, washed with distilled water, and incubated in 2 mol/L NaOH for softening and decolorization. After washing, they were immersed in buffer (acetic acid + sodium hydroxide, pH 5.5–6.5) for 20 min. Pistils were carefully dissected with a needle and forceps, rinsed twice with distilled water, and stained overnight in aniline blue solution (0.1% aniline blue + 0.3 mol/L potassium phosphate). A coverslip was placed gently on the material without pressing, and pollen germination on the stigma and pollen tube growth in the style were observed and photographed under a fluorescence microscope.

2.4. Transcriptome Analysis of A. annua for Information

2.4.1. RNA Extraction and Quality Test

The pollination treatment was performed as described in Section 2.3. Since the rejection of incompatible pollen occurs rapidly, and the reduced pollen viability of the paternal parent may also contribute to the failure of interspecific hybridization in plants [23,24], we collected three replicates each of self-pollinated and cross-pollinated stigmas (approximately 200 mg per sample) 3 h after pollination. These samples were immediately frozen in liquid nitrogen and stored at −80 °C for subsequent transcriptome sequencing analysis.
Total RNAs were extracted from self- and cross-pollinated samples using a modified TriZol method [25]. The RNA yield and purity were checked using a Nanodrop spectrophotometer (Thermo Scientific, Waltham, MA, USA) and an Agilent 2100 Bioanalyzer (Santa Clara, CA, USA). All samples were confirmed to be of acceptable quality using the 260/280 nm absorption ratio (median ± SD: 2.02 ± 0.05) and RIN (RNA Integrity Number; median ± SD: 7.1 ± 1.1). A total of 6 RNA samples with 3 biological replicates in each group (AasB1, AasB2, AasB3, AahA1, AahA2, and AahA3) were prepared.

2.4.2. mRNA Library Construction, Assembly, and Annotation

The total RNAs from different groups were digested with DNase I to remove any potential DNA and rRNA contaminants. Treated mRNA samples were thermal fragmented to 130 nt-160 nt in a divalent cation fragmentation buffer followed by the sequential synthesis of the first-strand and second-strand cDNA. The synthesized cDNA library was further purified using oligo T-coupled magnetic beads (New England Biolabs, Ipswich, MA, USA), tailed with oligo A, ligated with a sequencing adaptor, and purified with the same magnetic beads. The libraries were constructed and PCR amplified. Their quality was assessed for concentration and length using the Agilent Technologies 2100 bioanalyzer.
The amplified cDNA library was subjected to high-throughput RNA sequencing analysis using the Illumina HiSeq platform. Raw data were collected and filtered to remove low-quality reads and linker contamination using Trinity v2.0.6 [26]. Clean reads were then assembled and clustered to identify genes based on algorithm Tgicl 2.0.6 [27]. Gene function was annotated based on the related databases assembled by Yao et al. [28].

2.4.3. Differentially Expressed Gene (DEG) Analysis

The expression of each gene was estimated based on fragments per KB per million (FPKM) of the mapped reads, which was calculated based on the universal reads from six separate libraries. Bowtie2 was used to compare the clean reads to the reference genome generating mapped data, then RNA-seq by expectation–maximization (RSEM) was used to calculate the gene expression level. DEGseq was used for differential gene testing. p-values were corrected to Q-values [29,30]. The genes with more than twice the difference and Q-value ≤ 0.001 were defined and screened for significant DEGs to improve their accuracy (false discovery rate ≤ 0.001 and |log2 Ratio| ≥ 1). The heatmap function in R 4.2.2 software was used for hierarchical clustering analysis based on the results of differential gene detection.

2.4.4. Quantitative Real-Time PCR (qRT-PCR) Verification

The RNA samples used for qRT-PCR assays were the same as those used for RNA sequencing. Gene-specific primers were designed according to the reference unigene sequences using Primer Premier 5.0 (Table S1) and were synthesized by Shanghai Sangon Biotechnology Co. Ltd. (Shanghai, China). qRT-PCR was performed using the TransStart Tip Green qPCR SuperMix kit (TransGen, Beijing, China) with an ABI PRISM 7500 Sequence Detection System (Applied Biosystems, Foster City, CA, USA). The enzyme reaction was initiated at a temperature of 94 °C and held for 30 s. The following step cycles were then used: 94 °C for 5 s; 55 °C for 15 s; then 72 °C for 10 s, 40 cycles. Three independent biological replicates were tested and the actin gene (GenBank: EU531837.1) was employed as an internal control. The actin gene (GenBank: EU531837.1) was used as the internal control, and relative mRNA levels were quantified using the 2−ΔΔCt method [31]. Data are expressed as the mean ± standard deviation (SD) from three independent biological replicates. Correlation analysis was conducted using SPSS software version 16.0. p-value < 0.05.

3. Results

3.1. Statistics of In Vitro Pollen Germination

Pollen viability was the highest after 3 h of incubation, with an average germination rate of 56.5%, and decreased for other time points, reaching a minimum of 11.13% at 6 h after excision (Table 1). The pollen germination results are shown in Figure 1A–D.

3.2. Statistics of Pollen Tube Growth

After pollination, the pistil was stained with aniline blue. Under UV light, pollen grains and pollen tubes showed bright blue-green fluorescence. In the case of cross-pollination, a large number of pollen grains germinated on the stigma to form filamentous pollen tubes after 3 h (Figure 2A,B). In contrast, after 3 h of self-pollination, the growth of pollen tubes was significantly slower, with only a few filamentous pollen tubes and some dotted pollen tubes observable (Figure 2C,D). This suggests that pollen from self-pollination hardly grows on the stigma, and it is speculated that the stigma may inhibit the growth of self-pollinated pollen tubes.

3.3. Transcriptome Analysis Results of A. annua for Information

3.3.1. RNA Sequencing and Transcriptome De Novo Assembly

Total RNA was prepared from the inflorescence of A. annua under self- and cross-pollinated conditions. Six libraries were built following adaptor ligation, three for each condition, and sent for second-generation sequencing using the Illumina HiSeq 2000 platform. In total, 25.03 GB of data was collected. Adaptor, nonsense, and low-quality reads were removed, and data were filtered into 20.82 MB clean reads corresponding to 4,163,617,800 clean bases. GC content ranged from 42.39% to 43.20%, with an average of 42.65%. The average % ≥ Q30 was 91.56%, indicating high-quality sequencing (Table 2).

3.3.2. Functional Annotation of Unigenes

To functionally annotate the transcriptome, 69,498 genes were subjected to BLASTX analysis against eight databases, namely, COG, NOG, NR, SwissProt, KOG, KEGG, GO, and Pfam. The majority of genes, up to 69,406 (93.9%), were functionally annotated in the NR database. BLASTX was used to further annotate and categorize the genes against the remaining databases, with 16,522 genes annotated in COG (22.3%), 53,608 in NOG (72.5%), 41,014 in SwissProt (55.5%), 32,269 in KOG (43.6%), 42,557 in KEGG (57.5%), 51,292 in GO (69.4%), and 47,394 in Pfam (64.1%).

3.3.3. Differential Gene Expression and Functional Enrichment Analysis

The expression level of single genes was measured using the FPKM value. Comparing AasB with AahA, 64,379 genes showed no significant change in expression across various conditions; however, there were 209 upregulated genes and 411 downregulated genes (Figure 3). This up- and down-expression of certain groups of genes suggests their strong correlation with the SI of A. annua (Figure 4 and Table S2).
DEGs were annotated in the GO and KEGG pathway databases to further predict the candidate genes and the processes responsible for SI. GO database clustering of DEGs suggested multiple biological processes, specific cellular components, and genes mapped to confined functions (Figure 5). In the molecular function category, genes with catalytic activity were the most enriched (282 genes), followed by genes responsible for binding (200 genes), molecular function regulator (22 genes), and other functions. Several biological processes are thought to be highly enriched during SI, including the metabolic process (231 genes), single-organism process (180 genes), and cellular process (134 genes). The clustering of the cellular components of the genes found that genes localized to the membrane (178), membrane part (162), and cell (95) were the most enriched during SI.
KEGG pathway enrichment further confirmed that genetic information processing and environmental information processing, especially signal transduction, is one of the most enriched DEG pathways. A large percentage of DEGs are responsible for biosynthesis of unsaturated fatty acids, fatty acid metabolism, tyrosine metabolism, isoquinoline alkaloid biosynthesis, and pentose and glucuronate interconversions (Figure 6). DEGs and metabolic pathways that are enriched during SI may show different effects from fertilization or non-fertilization.

3.3.4. qRT-PCR Verified Differentially Expressed Genes of A. annua

We randomly selected nine genes with an altered expression for qRT-PCR to validate the DEGs identified in the RNA-seq analysis. The expression patterns from qRT-PCR were compared with the results of the RNA-seq expression analysis. The results showed that all nine genes had the same expression patterns in the qRT-PCR analysis as in the RNA-seq analysis, which basically confirmed the reliability of the RNA-seq results (Figure 7). The RNA-seq data were compared with the transcript abundance patterns of the self-pollination and cross-pollination. Our results showed that several of the expression comparisons of qRT-PCR assay were in fairly good agreement with the RNA-seq data, even if the fold-change of some genes in their expression level detected with sequencing and qRT-PCR did not match perfectly.
Furthermore, the correlation coefficient of the results between the two methods was assessed and calculated using SPSS software. As a result, a positive correlation was evaluated with R2 = 0.479. The non-significant correlation between the qRT-PCR and RNA-seq results could be due to bioinformatic artifacts in the RNA-seq analyses, based on the estimation of transcript expression, to the extent that qPCR is the most robust experimental technique and it is not based on statistics [32].

3.3.5. DEG Analysis Identified Candidate Genes for SI

SRK is specifically expressed in the stigma and directly involved in the SI reaction [33]. The Ca2+ signaling pathway is also affected during SI, such that the activation of SRK interferes in calcium signaling, subsequently influencing the growth of pollen tubes and fertilization [2]. Phosphorylated SRK activates the MOD protein, which is a kind of aquaporin, through a series of signal transductions that stimulate water molecules to enter the stigma and avoid the pollen [34]. In addition, EXO70A1 belonging to exocytosis complex components may be the downstream signal receptor of ARC1 [35]. Ten candidate genes deemed to be involved in SSI were identified from the DEGs (Table 3). There were obvious differences in the expression levels of these candidates SSI genes, such as SRK, Calmodulin-like (CML), MOD, and EXO70A1 genes, between AasB and AahA.

4. Discussion

In flowering plants, fertilization starts when pollen grains hydrate and germinate on the stigma. The pollen tube then penetrates the papillae cells, grows through the style, enters the ovary, and reaches the ovule. Finally, two sperm cells are released into the embryo sac, combining with the egg and central cells to form a zygote and endosperm, completing double fertilization. This is a complex and precise process with strict spatial and temporal requirements, and any disruption can halt fertilization [36].
SI is a key factor preventing self-pollination. Depending on where it occurs, SI can be prezygotic or postzygotic. Prezygotic SI, which happens before fertilization, has four types: (1) sporophytic SI, where pollen fails to germinate on the stigma [37]; (2) gametophytic SI, where pollen tube growth is blocked in the style [38]; (3) the case where pollen tubes enter the ovary but cannot reach the ovules [39]; and (4) the case where pollen tubes reach the ovules but cannot complete fertilization [40]. The last two types are late-acting SI in the ovary. Postzygotic SI involves normal zygotes that undergo rapid programmed cell death after fertilization.
Fluorescence microscopy showed that in self-pollination, pollen germination is abnormal with disrupted pollen tube growth. In cross-pollination, pollen germinates and grows normally, with pollen tubes reaching the ovary. In self-pollinated Artemisia annua, at 3 h post pollination, some pollen grains start germinating. By 12 h, a few pollen tubes grow, but at 24 h, most pollen grains do not germinate normally. Many pollen tubes are arrested and fail to reach the style. Since pollen cannot germinate on the stigma, this indicates sporophytic SI. Thus, Artemisia annua is preliminarily considered sporophytically self-incompatible, though more experiments are needed for confirmation.
The results of GO enrichment analysis showed that, in the molecular function category, there were many genes enriched for catalytic activity and binding functions. In the biological process category, in addition to metabolic processes, single-organism processes, and cellular processes, 12 genes were enriched in the signaling pathway. In the cellular component category, most of the enriched genes were related to membranes and membrane parts. It is hypothesized that these differentially expressed genes may lead to changes in signal transduction, the catalytic and binding functions of stigma cells, and the structure and function of cell membranes in Artemisia annua L., thereby causing self-incompatibility. Based on the above research results, it is preliminarily determined that the self-incompatibility barrier in A. annua L. may occur at the initial stage of stigma/pollen interaction, such as during recognition and adhesion processes.
After foreign pollen enters the stigma, changes occur in the expression levels of S-ribonuclease (S-RNase) within the stigma during the initial phase of self-incompatibility recognition. The stigma-expressing SRK and the pollen-expressing SCR are two closely linked genes at the S locus of Brassicaceae [41]. The BoSRK3 gene mutation may suppress self-incompatibility completely, converting the self-incompatible line into a self-compatible line using the CRISPR/Cas9 gene-editing system [42]. EbSRLK1 has been cloned in self-incompatible Asteraceae species E. breviscapus, which is induced to express in self-pollinated flowers [43]. ARC1, as a positive regulator of SRK in the SI signaling pathway and its ubiquitination reaction on the stigma, promotes SI [44]. THL1/2 physically and genetically interacts with SRK and functions as a negative regulator of SRK activation [45,46]. In our study, the SCR, ARC1, and THL1/2 genes showed no expression difference between self- and cross-pollination. However, NewGene_8313 and gene29401 were annotated as SRK in our study, as its expression after self-pollinating is higher than after cross-pollinating. A functional analysis of the role of these candidate genes will be performed in a future study.
The Ca2+ signaling pathway is also affected during SI, such that the activation of SRK interferes in calcium signaling, subsequently influencing the growth of pollen tubes and fertilization [2]. The DEGs from A. annua contained a group of CML family proteins, including one upregulated gene, which need to be studied to explore the association between SI and the inhibition of Ca2+ signaling. Phosphorylated SRK activates the MOD protein in Brassica, which is a kind of aquaporin, through a series of signal transductions that stimulate water molecules to enter the stigma and avoid the pollen [35]. It is confirmed that aquaporins NIP4;1 and NIP4;2 play partially redundant roles in pollen development and pollination of angiosperms [47]. Moreover, the BrMOD gene may be the key factor for pollen hydration, germination, and tube penetration in the SI response of Chinese cabbage [48]. The group of predicted aquaporin family genes included one upregulated gene and two downregulated genes, suggesting a failure of stigma hydration and a rejection of self-pollination. We intend to use tissue-specific expressions to explore the relationship between aquaporin and SI.
In addition, Exo70A1 belonging to exocytosis complex components may be the downstream signal receptor of ARC1 [35]. When Exo70A1 was overexpressed in the transgenic stem of B. napus, the plant altered from SI to self-affinity, while the loss of Exo70A1 in Brassica and A. thaliana stigmas leads to the rejection of compatible pollen at the same stage as the SI response [49]. Thus, Exo70A1 is another SI negative regulator following THL1/2. In our study, the downregulated trend of gene9558 belonging to Exo70 was observed, which is consistent with previous reports and will help to clarify the mechanism of SI in A. annua in additional research.
Based on the above findings, we propose a hypothetical model for the multi-pathway regulatory network of self-incompatibility in Artemisia annua: the SI response may be primarily driven by atypical SRK activation, bypassing the canonical SCR-ARC1 pathway and achieving self-pollen rejection through a coordinated Ca2+-AQP-Exo70 network. However, this remains speculative, and functional validation studies of genes including SRK, CML, MOD, and EXO70A1 are required.

5. Conclusions

In this study, the self-incompatibility of A. annua was assessed by examining in vitro pollen germination and pollen tube growth after self-pollination and cross-pollination. Pollen grain observations found that pollen viability peaked at 3 h in vitro. Fluorescence microscopy revealed that at 3 h post pollination, the growth of pollen tubes from self-pollinated pollen grains was significantly inhibited by the stigma, while the pollen tubes from cross-pollinated pollen mostly displayed normal filamentous growth. In addition, ten genes related to A. annua SI were annotated. We hypothesize that the SRK, CML, MOD, and EXO70A1 genes and downstream effectors such as calcium signaling, exocytosis, and aquaporins are key for A. annua’s self-incompatibility response. This study improves our understanding of this response in A. annua and offers molecular evidence for its classification. The identified candidate genes provide insights into the detailed mechanisms underlying self-incompatibility in A. annua.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/horticulturae11070790/s1: Figure S1: Distribution of BUSCO test genes; Table S1: Primers of genes used for qRT-PCR analysis in this study; Table S2: AahA-VS-AasB DEG data;

Author Contributions

J.F. and C.W. designed this study; S.W. and L.P. performed the experiments and data analysis; L.W. finalized the figures and tables; Y.Z. and S.C. wrote the manuscript; Z.L. and X.M. helped in material collection. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the Guangxi Key R&D Program (GuiKe AB25069119), National Natural Science Foundation of China (8156140557), CAMS Innovation Fund for Medical Sciences (CIFMS) (2021-I2M-1-071), and Beijing City University 2024 Team Fund (KYTD202401).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AQPAquaporin
ARC1Armadillo repeat-containing protein 1
CMLCalmodulin-like
DEGsDifferentially expressed genes
EXOExocyst complex component
FPKMFragments per KB per million
GSIGametophytic self-incompatibility
SRKS-locus receptor kinase-like
MITEMiniature inverted-repeat transposable element
MODModifier
qRT-PCRQuantitative real-time PCR
RSEMRNA-seq by expectation–maximization
SCRS-locus cysteine-rich
SF3Sunflower 3
SISelf-incompatibility
SSISporophytic self-incompatibility
SSPStigma-specific peroxidase
THLThioredoxin-like
UDPUDP glycosyltransferase

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Horticulturae 11 00790 g001
Figure 1. Microscopic observation of pollen grain germination after 3 h in vitro culture.
Figure 1. Microscopic observation of pollen grain germination after 3 h in vitro culture.
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Figure 2. Pollen tube growth under fluorescence microscope at 3 h after cross-pollination (A,B) and self-pollination (C,D).
Figure 2. Pollen tube growth under fluorescence microscope at 3 h after cross-pollination (A,B) and self-pollination (C,D).
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Figure 3. A volcano plot of DEGs. (The x-axis represents -log10 transformed significance. The y-axis represents log2-transformed fold change. The red points represent upregulated DEGs. The green points represent downregulated DEGs. The black points represent non-DEGs.).
Figure 3. A volcano plot of DEGs. (The x-axis represents -log10 transformed significance. The y-axis represents log2-transformed fold change. The red points represent upregulated DEGs. The green points represent downregulated DEGs. The black points represent non-DEGs.).
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Figure 4. The results of hierarchical clustering analysis for DEGs. (The x-axis represents the sample name. The y-axis represents DEGs. The dark color indicates a high expression level, while the light color indicates a low expression level.).
Figure 4. The results of hierarchical clustering analysis for DEGs. (The x-axis represents the sample name. The y-axis represents DEGs. The dark color indicates a high expression level, while the light color indicates a low expression level.).
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Figure 5. Second-level GO classification statistics of DEGs’ annotation. The x-axis shows GO categories, with the y-axis indicating the percentage of genes (left) and the number of genes (right). The figure illustrates the enrichment of genes in GO second-level functions under both differentially expressed and entire gene backgrounds, highlighting the status of each function in both contexts.
Figure 5. Second-level GO classification statistics of DEGs’ annotation. The x-axis shows GO categories, with the y-axis indicating the percentage of genes (left) and the number of genes (right). The figure illustrates the enrichment of genes in GO second-level functions under both differentially expressed and entire gene backgrounds, highlighting the status of each function in both contexts.
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Figure 6. KEGG pathway enrichment scatter plot of differentially expressed genes. (Each circle represents a KEGG pathway. The vertical axis indicates pathway names. The horizontal axis shows the enrichment factor, calculated as the ratio of the proportion of differentially expressed genes in a pathway to the proportion of all genes in that pathway. A larger enrichment factor indicates more significant enrichment of differentially expressed genes in the pathway. Circle color reflects the q-value, a multiple testing-corrected p-value. Smaller q-values suggest more reliable enrichment significance. Circle size denotes the number of enriched genes in the pathway; larger circles mean more enriched genes).
Figure 6. KEGG pathway enrichment scatter plot of differentially expressed genes. (Each circle represents a KEGG pathway. The vertical axis indicates pathway names. The horizontal axis shows the enrichment factor, calculated as the ratio of the proportion of differentially expressed genes in a pathway to the proportion of all genes in that pathway. A larger enrichment factor indicates more significant enrichment of differentially expressed genes in the pathway. Circle color reflects the q-value, a multiple testing-corrected p-value. Smaller q-values suggest more reliable enrichment significance. Circle size denotes the number of enriched genes in the pathway; larger circles mean more enriched genes).
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Figure 7. DEGs of qRT-PCR verification analysis. (The FPKM values represent the RNA-sequencing results; the histograms represent the qRT-PCR verification results.).
Figure 7. DEGs of qRT-PCR verification analysis. (The FPKM values represent the RNA-sequencing results; the histograms represent the qRT-PCR verification results.).
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Table 1. Pollen viability assay results of Artemisia annua for different culture durations.
Table 1. Pollen viability assay results of Artemisia annua for different culture durations.
TimeMean Germination Rate (%)RSD (%)
3 h56.51.3
4 h39.51.7
5 h21.61.2
6 h11.131.8
Table 2. Quality statistical analysis of sequencing library for Artemisia annua.
Table 2. Quality statistical analysis of sequencing library for Artemisia annua.
SamplesClean ReadsClean BasesGC Content% ≥ Q30
AahA121,054,9784,210,995,60043.20%94.00%
AahA220,589,9374,117,987,40042.39%90.25%
AahA320,620,3504,124,070,00042.44%90.04%
AasB120,259,2994,051,859,80042.44%90.67%
AasB221,449,8974,289,979,40043.00%93.73%
AasB321,185,3864,237,077,20042.41%89.94%
Table 3. Candidate differential expression genes related to SSI.
Table 3. Candidate differential expression genes related to SSI.
Genelog2FC (AasB/AahA)Differential ExpressionGene FamilyPredicted Gene FunctionProcesses Involved in SSI
newGene_83131.1330UpSRKserine/threonine protein kinase ULK4SRK signaling
gene3938−1.3236DownSRKserine/threonine protein kinase Pto
gene294011.0157UpSRKserine/threonine protein kinase BSK3
gene8471−1.8452DownSRKserine/threonine protein kinase SAPK3-like
gene17743−2.3918DownSRKSerine/threonine protein kinase
gene225131.2668UpCMLCalcium-binding proteinSignaling/stigmatic interaction
gene223161.1274UpMODAquaporin TIP1-3-likeAquaporin-like/stigma hydration
gene53060−1.2181DownMODAquaporin PIP2-1
gene13907−1.3811DownMODAquaporin TIP2-1
gene9558−1.0234DownEXO70Exocyst complex component EXO70B1Exocyst complex component
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Zang, Y.; Cui, S.; Wei, S.; Pan, L.; Wan, L.; Ma, X.; Luo, Z.; Fu, J.; Wang, C. In Vitro Pollen Viability, Fluorescence Microscopy, and Transcriptomic Comparison of Self-Pollinated and Cross-Pollinated Inflorescence of Artemisia annua L. to Analyze Candidate Self-Incompatibility-Associated Genes. Horticulturae 2025, 11, 790. https://doi.org/10.3390/horticulturae11070790

AMA Style

Zang Y, Cui S, Wei S, Pan L, Wan L, Ma X, Luo Z, Fu J, Wang C. In Vitro Pollen Viability, Fluorescence Microscopy, and Transcriptomic Comparison of Self-Pollinated and Cross-Pollinated Inflorescence of Artemisia annua L. to Analyze Candidate Self-Incompatibility-Associated Genes. Horticulturae. 2025; 11(7):790. https://doi.org/10.3390/horticulturae11070790

Chicago/Turabian Style

Zang, Yimei, Shengrong Cui, Shugen Wei, Limei Pan, Lingyun Wan, Xiaojun Ma, Zuliang Luo, Jine Fu, and Chongnan Wang. 2025. "In Vitro Pollen Viability, Fluorescence Microscopy, and Transcriptomic Comparison of Self-Pollinated and Cross-Pollinated Inflorescence of Artemisia annua L. to Analyze Candidate Self-Incompatibility-Associated Genes" Horticulturae 11, no. 7: 790. https://doi.org/10.3390/horticulturae11070790

APA Style

Zang, Y., Cui, S., Wei, S., Pan, L., Wan, L., Ma, X., Luo, Z., Fu, J., & Wang, C. (2025). In Vitro Pollen Viability, Fluorescence Microscopy, and Transcriptomic Comparison of Self-Pollinated and Cross-Pollinated Inflorescence of Artemisia annua L. to Analyze Candidate Self-Incompatibility-Associated Genes. Horticulturae, 11(7), 790. https://doi.org/10.3390/horticulturae11070790

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