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Article

A Comparative Transcriptomic Analysis of miRNAs and Their Target Genes During the Formation of Melanin in Apis mellifera

by
Xiangjie Zhu
1,2,†,
Yuanmingyue Tian
1,†,
Mingjie Cao
1,
Chenyu Zhu
1,
Jiaqi Shang
1,
Jiaqi Sun
1,
Yiming Liu
1,
Bingfeng Zhou
1,2,
Shujing Zhou
1,2,* and
Xinjian Xu
1,2,*
1
College of Bee Science and Biomedicine, Fujian Agriculture and Forestry University, Fuzhou 350002, China
2
Honeybee Research Institute, Fujian Agriculture and Forestry University, Fuzhou 350002, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agriculture 2025, 15(9), 992; https://doi.org/10.3390/agriculture15090992
Submission received: 5 April 2025 / Revised: 28 April 2025 / Accepted: 29 April 2025 / Published: 3 May 2025
(This article belongs to the Section Farm Animal Production)
Browse Figures
Versions Notes

Abstract

:
Melanin is an important component of the body color of honeybees, and its formation changes with the age of a capped brood of bees. However, up to now, the regulatory mechanism of melanin formation in honeybees remains unclear. To analyze the differential expression profile of microRNAs (miRNAs) in worker bees of Apis mellifera and to reveal the regulatory roles of differentially expressed miRNAs (DEmiRNAs) and mRNAs in the formation process of melanin during the capped brood stage, we used sRNA-seq technology and related software to analyze samples from four key developmental stages during the capped brood stage, when body color develops in Apis mellifera, namely, mature larvae (L0), pre-pupae (PP3), early pupae (P6) and mid-pupae (P9). A total of 1291 miRNAs were identified by bioinformatics. Three comparison groups were analyzed: L0 vs. PP3, PP3 vs. P6, and P6 vs. P9. A total of 171, 94, and 19 DEmiRNAs were identified in these groups, respectively, which regulate 1481, 690, and 182 differentially expressed target mRNAs (target DEmRNAs). The functional analysis of target DEmRNAs indicated that DEmiRNAs might regulate the formation of capped brood melanin in honeybees by activating expression changes in key genes in signaling pathways, such as the Wnt signaling pathway, melanogenesis, and the Toll and Imd signaling pathway, through activating miR-315-x, miR-8, ple, yellow family genes, wnt1, etc. Our research provides a theoretical basis for future analysis of the regulatory role of miRNAs in the formation of melanin in honeybees.

1. Introduction

The color of the body is a crucial phenotypic trait that adds richness and diversity to the insect world. Body color is crucial for the survival and adaptation of organisms, playing key roles in regulating body temperature [1,2], resisting microbial invasion [3,4,5], camouflage and defense [6], UV protection [7,8], and wear resistance [9]. The mechanism for the formation of body color is complex, varying among species, developmental stages, and different body parts. In recent years, there has been extensive research on the coloration mechanisms of organisms, but the study of key genes and molecular mechanisms underlying color formation is still incomplete. The yellow-black striped coloration of bees serves as a warning signal in their long-term survival competition, making potential predators hesitant to attack. Bees can provide a good research sample for studying the mechanism of color formation.
The melanization response in honeybees constitutes a critical element of their innate immune defense, primarily mediated by the phenoloxidase (PO) enzymatic cascade [10]. This process combats pathogens through dual mechanisms: physical encapsulation and antimicrobial activity [11]. Melanin encapsulates pathogens to form mechanical barriers (e.g., melanized capsules or nodules), effectively restricting their proliferation within the host. Concurrently, reactive intermediates generated during melanogenesis—such as semiquinone radicals and reactive oxygen species (ROS)—exert cytotoxic effects on pathogens by inducing oxidative stress and structural damage [12].
MiRNAs are essential for regulating gene expression at the post-transcriptional level in organisms. They are short, non-coding RNAs that can bind to the 3′UTR of target gene mRNAs. The first miRNA, lin-4, was discovered in Caenorhabditis elegans in 1993 [13], followed by the identification of the conserved let-7 miRNA [14]. Victor R. Ambros and Gary Ruvkun were awarded the 2024 Nobel Prize in Physiology or Medicine for their groundbreaking discovery of miRNAs and their role in gene regulation. A single miRNA can bind to multiple target genes, thereby concurrently regulating the expression of multiple mRNAs [15,16], exerting its influence in various physiological processes.
The process of melanization formation in insects is based on the accumulation of melanin and the influence of other pigments derived from tyrosine. Tyrosine hydroxylase (TH) and PO catalyze the conversion of tyrosine to 3,4-dihydroxyphenylalanine (DOPA) [17,18], which is further converted to dopamine by Dopa decarboxylase (DDC) [19]. Laccase oxidizes DOPA and dopamine to dopaquinone and dopaminequinone [20]. These quinone substances are then transformed by the dopachrome conversion enzyme (DCE), encoded by the yellow gene family, to form dihydroxyindole and 5,6-dihydroxyindole-2-carboxylic acid [21]. Subsequent oxidation catalyzed by laccase and other enzymes leads to the formation of black eumelanin and dopamine-melanin [22].
MiRNAs play essential regulatory roles in body coloration processes across diverse species. However, the specific regulatory mechanisms of miRNAs in body color in bees remain unclear. For example, miR-8 was identified as the first miRNA to regulate cuticle pigmentation in insects, as demonstrated by the reduced abdominal pigmentation in female adult fruit flies lacking miR-8 [23]. In Bicyclus anynana, mir-193 directly targets and regulates the expression of genes associated with melanin formation, such as ebony, Esp1, and yellow-e3 [24]. In locusts, miR-133 negatively regulates pale expression, leading to decreased dopamine production [25]. The involvement of novel-miR-11, novel-miR-195, and novel-miR-123 in the epigenetic phenomenon of nutritional crossbreeding-induced queen’s body color change has been suggested [26]. The delivery of miR-133 agomir effectively suppresses henna and pale expression, leading to reduced dopamine production and a consequent behavioral transition from the gregarious to the solitary phase [27].
Given that a typical representative of insects, the study of the body color formation mechanism of honeybees can provide a reference for research on body color evolution in insects and even a wider range of biological groups. Understanding the role of miRNA in honeybee body color formation can help elucidate how body color in honeybees gradually evolves and adapts to the environment through genetic changes, providing a new perspective and evidence for exploring the molecular mechanisms of color-adaptive evolution in biological evolutionary processes.

2. Materials and Methods

2.1. Samples

Four representative developmental stages of Apis mellifera worker bees were selected for sampling: mature larvae, pre-pupae, early pupae, and mid-pupae. Samples of honeybees were collected from colonies in the growth stage from April to June. The age consistency of the samples was ensured by limiting the queen’s egg-laying, and capped brood obtained 2 h after capping was designated as the starting time of L0 [28]. The newly capped brood cells were placed in a constant temperature and humidity chamber (35 ± 0.2 °C, RH 75%) for 3 days, 6 days, and 9 days (labeled as PP3, P6, and P9) for cultivation [29]. For each group, the sample was prepared with three different colonies, with 10 capped broods in each colony. Then, a total of 120 capped broods were used in this study. All samples were immediately frozen in liquid nitrogen and stored at −80 °C in Ultra Low Temperature Freezers (Thermo Fisher Scientific Inc., 81 Wyman Street, Waltham, MA, 02454, USA).

2.2. Quality Control and Assessment of Sequencing Data

A total of 12 libraries were constructed. The construction of sample libraries and high-throughput sequencing was outsourced to Guangzhou Omicshare Biotechnology Co., Ltd. (Building A5, Smart Valley, Guangzhou University Town) in May 2019. They utilized the Illumina HiSeqTM 4000 platform (San Diego, CA, United States). The raw data obtained were subjected to initial filtering to obtain small RNA data, which were further processed to generate clean small RNA tag sequences for subsequent analysis.

2.3. Screening of DEmiRNAs and Prediction of Target Genes

Three comparative groups were formed between consecutive age stages: L0 vs. PP3, PP3 vs. P6, and P6 vs. P9. The screening criteria for differentially expressed miRNAs (DEmiRNAs) were set at |log2FC| ≥ 1 and p ≤ 0.05. The prediction of the DEmiRNAs’ target genes was carried out using RNAhybrid (v2.1.2) + svm_light (v6.01), Miranda (v3.3a), and TargetScan (Version: 7.0), with the intersection of the results from these three methods serving as the predicted target genes for DEmiRNAs.

2.4. Differentially Expressed Target mRNAs and Their Functional Analysis

In order to improve prediction accuracy and refine the analysis scope, we identified the intersection between the predicted target genes and high-quality DEmRNAs obtained from previous laboratory transcriptome data (GDR6374_std_1). This intersection was defined as the target DEmRNAs. Basic analysis, Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of target DEmRNAs in the three comparison groups were performed using the OmicShare and OmicSmart cloud platforms. Subsequently, a regulatory network of DEmiRNAs, target DEmRNAs, and pathways was constructed using Cytoscape v3.10.2.

2.5. Stem-Loop RT-qPCR Validation of DEmiRNAs

Five DEmiRNAs (let-7-x, novel-m0169-3p, miR-2504-x, ame-miR-210-3P, miR-1-3P) were randomly selected. Primers (Table 1) were synthesized by Fuzhou Shangya Biotechnology Co., Ltd. in March 2025. Total RNA was extracted from samples using the SteadyPure Quick RNA Extraction Kit (Accurate Biotechnology (Hunan) Co., Ltd., Changsha, China). The extracted RNA was reverse transcribed using the miRNA First-Strand cDNA Synthesis Kit (Accurate Biotechnology (Hunan) Co., Ltd.) and the Evo M-MLV RT Mix Kit (Accurate Biotechnology (Hunan) Co., Ltd.) with gDNA Clean for qPCR Ver.2. Stem-loop primers were designed for reverse transcription using the reverse-transcribed cDNA as a template, and RT-qPCR reactions were performed using the SYBR Green Premix Pro Taq HS qPCR Kit (Rox Plus) (Accurate Biotechnology (Hunan) Co., Ltd.). RT-qPCR detection was performed on a QuantStudioTM 5 fluorescent quantitative PCR system (Thermo Fisher Scientific Inc., 81 Wyman Street, Waltham, MA, 02454), following the conditions: 95 °C pretreatment, 30 s; 95 °C denaturation, 5 s; 60 °C annealing extension, 30 s; a total of 40 cycles; and melting curve program default system settings. The reaction system was as follows: 10 μL of 2X SYBR Green Pro Taq HS Premix (Accurate Biotechnology (Hunan) Co., Ltd., Changsha, China), 0.4 μL each of upstream and downstream primers (Table 1), cDNA templates, and RNase-free water to a volume of 20 μL. The U6 was used as an internal reference. The expression levels of the samples were calculated using the comparative Ct method (2−ΔΔCt) and statistically analyzed. Three biological replicates and three technical replicates were performed for each age group, and the data were visualized using GraphPad Prism 9.

3. Results

3.1. Small RNA Library Sequencing and Sequence Analysis

We constructed 12 small RNA libraries from samples of worker mature larvae (L0), pre-pupae (PP3), early pupae (P6), and mid-pupae (P9). Following high-throughput sequencing, the average clean reads for L0, PP3, P6, and P9 were 13,328,832; 12,384,157; 15,314,052; and 14,716,274, respectively. Post-quality control, the average clean tags obtained were 11,510,675; 9,449,732; 12,359,786; and 13,370,042, suitable for subsequent analysis (Table 2). The alignment of the raw reads to the reference genome of Apis mellifera revealed alignment rates of 76.21%, 90.07%, 89.58%, and 86.26% for each sample (Table 3). A comparison with GenBank, Rfam, and literature references identified 93.05% of the clean reads as miRNAs, with the remaining reads including rRNA, snRNA, snoRNA, tRNA, exon sense, and unann (Figure 1). Analysis of miRNA length characteristics showed the smallest RNA length to be between 18 and 24 nucleotides, with the longest miRNA at 22 nucleotides. Additionally, precursor miRNAs recognized and cleaved by the Dicer enzyme exhibit a bias toward a U base at the first position of the 5′ end. Therefore, we conducted a nucleotide bias analysis on the obtained precursor miRNAs, illustrating the bias at the first nucleotide of different length markers in the precursor miRNA-labeled sequences and a nucleotide bias statistics chart, with U base content being predominant (Figures S1–S4).

3.2. Analysis of Differentially Expressed miRNAs

As the development progresses and the capped broods mature, the number of DEmiRNAs decreases. The results of upregulation and downregulation of DEmiRNAs in the three comparisons (L0 vs. PP3, PP3 vs. P6, and P6 vs. P9) are shown in Figure 2. During the transition from mature larvae (L0) to pre-pupae (PP3), 171 DEmiRNAs were identified, including 53 upregulated and 118 downregulated. A distinct regulatory shift occurred in the subsequent PP3 vs. P6 comparison, whereby a total of 94 upregulated miRNAs were detected without any downregulated counterparts. In the final transition (P6 vs. P9), the number of DEmiRNAs decreased significantly to 19 (3 upregulated, 16 downregulated), reflecting a predominance of downregulation during late pupal maturation.
In the L0 vs. PP3 comparison, the top three upregulated DEmiRNAs were miR-7851-y (log2(fc) = 8.72), novel-m0129-5p (log2(fc) = 7.61), miR-3793-x (log2(fc) = 7.47); the top five downregulated DEmiRNAs were miR-11980-x (log2(fc) = −11.00), miR-101-y (log2(fc) = −10.54), miR-8117-y (log2(fc) = −10.24), miR-2137-y (log2(fc) = −9.77), and miR-459-x (log2(fc) = −9.44) (Figure 3A, Table S1).
In the PP3 vs. P6 comparison, the top five upregulated DEmiRNAs were miR-486-x (log2(fc) = 17.66), miR-142-x (log2(fc) = 16.42), miR-150-x (log2(fc) = 14.94), miR-151-x (log2(fc) = 14.88), and miR-28-x (log2(fc) = 14.49) (Figure 3B, Table S2).
In the P6 vs. P9 comparison, the top five upregulated DEmiRNAs were novel-m0095-5p (log2(fc) = 6.09), miR-6060-x (log2(fc) = 5.98), and ame-miR-277-3p (log2(fc) = 2.35). The top three downregulated DEmiRNAs included miR-2504-x (log2(fc) = −10.92), miR-8392-x (log2(fc) = −10.79), and miR-5443-y (log2(fc) = −10.41) (Figure 3C, Table S3).
No shared DEmiRNAs were detected across the three developmental comparisons (L0 vs. PP3, PP3 vs. P6, and P6 vs. P9), with each transition displaying a distinct miRNA signature: 141 unique DEmiRNAs were identified in L0 vs. PP3, 57 in PP3 vs. P6, and only 4 in P6 vs. P9. This observation underscores the highly stage-specific nature of miRNA regulation during honeybee metamorphosis, whereby sequential developmental stages were characterized by limited overlap in miRNA expression profiles (Figure 4).
In both the L0 vs. PP3 and PP3 vs. P6 comparisons, a total of 26 miRNAs were found to be shared, which notably included miR-11980-x, ame-miR-193-3p, miR-143-y, ame-miR-263a-5p, miR-101-y, miR-126-y, miR-22-y, miR-192-x, miR-199-x, ame-miR-2788-3p, miR-263-x, ame-miR-315-5p, let-7-x, miR-363-y, miR-199-y, miR-26-x, ame-miR-263b-5p, miR-486-x, miR-181-x, miR-21-x, miR-30-x, miR-16-x, miR-146-x, miR-15-x, miR-148-y, and miR-315-y. In the intergroup comparisons of PP3 vs. P6 and P6 vs. P9, a total of 11 DEmiRNAs were found to be shared, specifically ame-miR-3720-5p, ame-miR-6052-5p, miR-2504-x, miR-3806-y, miR-5443-y, miR-8392-x, novel-m0008-5p, novel-m0138-5p, novel-m0169-3p, novel-m0172-3p, and novel-m0173-3p. Lastly, the comparison between L0 vs. PP3 and P6 vs. P9 revealed four common DEmiRNAs: ame-miR-2765-5p, ame-miR-277-3p, novel-m0129-5p, and miR-2765-x (Figure 4).

3.3. Acquisition of Differentially Expressed Target mRNAs

In the L0 vs. PP3 comparison, 171 DEmiRNAs collectively predicted 5355 target genes, while in the PP3 vs. P6 comparison, 94 DEmiRNAs collectively predicted 4285 target genes. In the P6 vs. P9 comparison, 19 DEmiRNAs collectively predicted 1558 target genes. The intersection of the predicted target genes with DEmRNAs in the transcriptome yielded 1481, 690, and 180 target DEmRNAs in the subsequent analyses of the three comparison groups, respectively (Figure 5).
In L0 vs. PP3 comparison, the top five target DEmRNAs are novel-m0057-3p (334), miR-5325-x (189), ame-miR-6041-3p (185), miR-315-x (135), and ame-miR-315-5p (128). In PP3 vs. P6 comparison, the top five target DEmRNAs are miR-126-x (88), miR-186-x (76), miR-185-x (68), ame-miR-315-5p (64), and miR-374-x (55). In the P6 vs. P9 comparison, the top five target DEmRNAs are ame-miR-6052-5p (34), ame-miR-277-3p (29), novel-m0169-3p (26), miR-8392-x (22), and novel-m0008-5p (17).

3.4. Functional Analysis of Target DEmRNAs in Different Comparison Groups

3.4.1. L0 vs. PP3

The GO analysis revealed that the top five enriched terms with the highest number of target DEmRNAs are as follows: molecular function (1095), biological process (1082), cellular process (872), cellular component (842), and binding (794) (Figure 6).
The KEGG enrichment analysis revealed that the target DEmRNAs were enriched in 217 KEGG pathways, with 25 pathways showing significant enrichment (p < 0.05). The bubble plot displays the top 20 significantly enriched pathways in descending order of significance (Figure 6).
As indicated in the network diagram (Figure 7), 123 DEmiRNAs target 38 target DEmRNAs, influencing pathways critical for melanogenesis, including the Toll and Imd signaling, melanogenesis, the MAPK signaling pathway, the MAPK signaling pathway-fly, and the Wnt signaling pathway, orchestrating pre-pupal melanin formation in mature larvae.

3.4.2. PP3 vs. P6

The GO analysis revealed that the top five enriched terms with the highest number of target DEmRNAs are as follows: molecular function (482), biological process (471), cellular component (365), cellular process (359), and single-organism process (355) (Figure 8).
The KEGG enrichment analysis revealed that the target DEmRNAs were enriched in 201 KEGG pathways, with 37 pathways showing significant enrichment (p < 0.05). The bubble plot displayed the top 20 significantly enriched pathways in descending order of significance (Figure 8).
As shown in the network graph (Figure 9), 62 DEmiRNAs target 27 DEmRNAs, impacting pathways associated with melanin biosynthesis, including the MAPK signaling pathway, the MAPK signaling pathway-fly, tyrosine metabolism, melanogenesis, the Toll and Imd signaling pathway, and the Wnt signaling pathway, thus regulating melanin formation from pre-pupal to early-pupal stages.

3.4.3. P6 vs. P9

The GO analysis revealed that the top five enriched terms with the highest number of target DEmRNAs are as follows: molecular function (134), biological process (129), cellular component (109), single-organism process (99), and cellular process (96) (Figure 10).
The KEGG enrichment analysis revealed that the target DEmRNAs were enriched in 95 KEGG pathways, with 12 pathways showing significant enrichment (p < 0.05). The bubble plot displayed the top 20 significantly enriched pathways in descending order of significance (Figure 10).
According to the network diagram (Figure 11), seven DEmiRNAs target six target DEmRNAs in pathways including the MAPK signaling pathway-fly, tyrosine metabolism, melanogenesis, and the Wnt signaling pathway, which are linked to melanin formation. These regulatory mechanisms facilitate melanin formation from the early-pupal to the mid-pupal stages.

3.5. RT-qPCR Analysis

Five DEmiRNAs were randomly selected from three comparisons for validation through RT-qPCR experiments. The results, as shown in Figure 12, revealed a similar expression pattern of DEmiRNAs between the RT-qPCR data and sRNA-seq data.

4. Discussion

In various biological processes, miRNAs play a crucial role in promoting mRNA degradation or inhibiting mRNA translation. Increasing evidence indicates that their dysregulation has impacts on skin differentiation and pigmentation [31]. The formation of insect body color is related to melanin synthesis, which is influenced by various factors such as non-coding RNA, genetic factors, and external environmental changes. In order to explore the regulatory mechanism of miRNA in the formation of the body color of capped broods in workers of Apis mellifera, we characterized and analyzed the miRNA expression profiles of the four developmental stages (L0, PP3, P6, and P9) of capped broods using sRNA-seq technology.
Notwithstanding the visual melanization of compound eyes (post-P6) and body pigmentation (post-P9) continuing through to adult eclosion, the strongest miRNA-mediated regulation of melanogenesis occurred during the initial pupation phase (L0 vs. PP3 comparison). This paradoxical finding highlights that molecular regulatory mechanisms precede overt morphological changes [32,33], with the highest number of DEmiRNAs (171) detected precisely when cuticular melanization programs are transcriptionally activated. Functional enrichment analysis indicated that these miRNAs target key components of the dopamine melanization pathway, including tyrosine hydroxylase and dopachrome conversion enzyme, suggesting that pre-emptive miRNA regulation primes the integument for subsequent pigment deposition during late pupal development.
During the development of Apis mellifera, miRNAs regulate the immune system in a stage-specific manner. Comparing different developmental stages of DEmiRNAs, it was found that during the transition from mature larvae (L0) to pre-pupae (PP3), up to 44 DEmiRNAs cooperatively activate the Toll and Imd signaling pathway. However, during the transition from pre-pupae (PP3) to early-pupae (P6), there is a fundamental change in the regulatory pattern, with only miR-126-x maintaining its regulatory role in the pathway. By the mid-pupal stage (P6 vs. P9), there are no DEmiRNAs involved in the activation of the Toll and Imd signaling pathway. This study provides new research directions and a theoretical basis for further exploration of the molecular mechanisms of immune regulation in honeybees.

4.1. L0 vs. PP3

During the transition from mature larvae to pupae, the highest number of DEmiRNAs was detected. This finding aligns with studies on insect developmental regulation [34,35], in which miRNA-mediated gene expression plays a critical role in metamorphic processes. For instance, in species such as Galeruca daurica, dynamic miRNA profiles have been observed during diapause maintenance stages, which coincide with major developmental transitions [36]. These regulatory RNAs are implicated in controlling key pathways including hormonal signaling, lipid metabolism, and stress responses—processes central to pupal development. Similarly, comparative analyses across insect taxa reveal that stage-specific miRNA expression patterns are particularly pronounced during the larval–pupal transformation, underscoring their functional importance in coordinating morphological and physiological remodeling [37].
From the mature-larval stage to the pre-pupal stage, as many as 14 DEmiRNAs (ame-miR-1-3p, ame-miR-252b-5p, ame-miR-315-5p, ame-miR-375-3p, ame-miR-iab-4-5p, miR-1-y, miR-26-x, miR-315-x, miR-375-y, miR-9995-y, mir-iab-4-x, novel-m0057-3p, novel-m0104-3p, and novel-m0170-5p) regulate the upregulation of yellow-x1 (LOC724293); ame-let-7-5p, ame-miR-315-5p, ame-miR-9864-5p and miR-315-x jointly regulate the upregulation of yellow-h (LOC724153). Yellow is related to pigmentation in both larvae and adults [38]. After interference with the yellow-y of Blattella germanica, melanin is significantly reduced, and the cuticle becomes softer and more transparent [39]. After Amyellow-y is knocked out in Apis mellifera using CRISPR/Cas9, melanin synthesis is disrupted, resulting in a lighter coloration in the head, abdomen, and legs of the adults [40]. Previous research has indicated that miR-315-x is mainly expressed in the nervous system of Drosophila [41]. In our research, miR-315-x is upregulated and targets yellow-x1 and yellow-h, thereby regulating those genes. Both yellow-x1 and yellow-h are key genes in the melanin formation process. We speculate that during development from the larval stage to the pre-pupal stage, miR-315-x may be a key miRNA regulating melanin formation.
In Drosophila, female adult flies lacking miR-8 exhibit reduced pigmentation on the dorsal and ventral sides [23]. miR-8 plays important roles in Insulin, Notch, and wingless signaling, as well as signaling via the fly steroid hormone ecdysone [42,43,44,45]. In our study, miR-8-x was found to upregulate the expression of LOC726262 (Adcy8, adenylate cyclase 78C). miR-8-x was enriched in signaling pathways such as melanogenesis and Insulin secretion. LOC726262 is a member of the adenylyl cyclase superfamily. Adenylyl cyclases (ACs) are enzymes that generate cAMP and, thus, are key components of the cAMP signaling pathways. ACs catalyze the conversion of ATP to cAMP. We speculate that miR-8, during the development from the mature-larval to the pre-pupal stage, in addition to mediating melanogenesis through activating the melanogenesis pathway, can also regulate signal transduction.
The Toll and Imd signaling pathway, as the core signaling hub of insect innate immunity, plays a crucial role in insect immune defense [46,47]. In the L0 vs. PP3 comparison, up to 44 DEmiRNAs are involved in the regulation of this pathway. Considering our previous findings that the PP3 stage is sensitive to adverse environmental conditions [48,49,50], it can be inferred that during the critical developmental stage of transitioning from mature larvae (L0) to pre-pupae (PP3), the honeybee organism activates the immune pathway by mobilizing a large number of DEmiRNAs to enhance its ability to resist unfavorable environments.

4.2. PP3 vs. P6

During the transition from newly formed pre-pupae to early pupae in honeybees, as many as 94 upregulated DEmiRNAs were detected, with no downregulated DEmiRNAs observed. This marked directional shift in miRNA expression contrasts with previous findings in other holometabolous insects [34], where both upregulation and downregulation typically occur during metamorphic transitions. For example, in Drosophila melanogaster, balanced miRNA regulation is critical for coordinating cuticle formation and histolysis during pupation [43]. The exclusive upregulation in honeybees suggests a unique regulatory strategy, possibly related to the accelerated development of specialized pupal structures required for colony-specific tasks. Transcriptomic analysis indicates these upregulated miRNAs target genes involved in chitin biosynthesis, neural development, and caste-specific differentiation pathways, underscoring their role in sculpting both morphological and behavioral traits during this critical life stage.
We speculate that during the development from the pre-pupal stage to the early-pupal stage, miR-374-x promotes tyrosine-to-DOPA conversion by upregulating the expression of ple, thereby increasing melanin production. In recent years, several studies have revealed the crucial regulatory functions of miR-374 family members in cell growth, differentiation [51], calcium regulation in the kidney [52], different types of cancers [53], and epilepsy [54]. In our study, miR-374-x was upregulated and regulated LOC408930 (tyrosine hydroxylase ple, ple) to increase its expression. Ple encodes tyrosine hydroxylase (TH), which can convert tyrosine to DOPA, and DOPA is an important precursor substance for melanin formation. In silkworms, interfering with BmTH delayed pupal cuticle pigmentation [55], and in Plagiodera versicolora, interfering with PverTH led to the lightening of the cuticle pigmentation in larvae, pupae, and adults [56]. In Gryllus bimaculatus, knocking out TH using CRISPR/Cas9 resulted in the transformation of adult cuticles from black to light brown [57].
In the PP3 vs. P6 comparison, only miR-126-x was detected to regulate the downregulation of LOC726289 (Jun-related antigen, Jra), which is enriched in the Toll and Imd signaling pathway. miR-126-x has been previously shown to be involved in the regulation of cell proliferation and apoptosis [58]; however, its potential role in the immune defense mechanisms of bees remains to be further investigated.

4.3. P6 vs. P9

In the P6-to-P9 transition, the number of DEmiRNAs dramatically declined to 19 (16 downregulated vs. 3 upregulated), reflecting a transcriptional shift toward repressive miRNA regulation during terminal pupal maturation. This reduction coincides with the stabilization of pupal morphology and is associated with processes like cuticle hardening and metabolic reprogramming, essential for preparing the insect for adult emergence.
From the early-pupal stage to the mid-pupal stage, melanin accumulates continuously in the body of Apis mellifera, and the body color deepens. The MAPK signaling pathway-fly, tyrosine metabolism, melanogenesis, and the Wnt signaling pathway may be related to melanin formation. miR-2504-x is the most significantly downregulated DEmiRNAs, and it regulates the downregulation of LOC413502 (Wg, Wnt family member 1 wingless, wnt1). Wnt1 is a member of the Wnt family and is enriched in the Wnt signaling pathway, Hippo signaling pathway, and melanogenesis pathways. Wnt1 can regulate the expression of genes related to melanin formation, such as yellow, to affect the pigmentation of fruit fly wings [59], and it can also regulate the expression of the nuclear effect gene Pangolin of wnt/β-catenin to control the formation of the crescent- and star-shaped patterns on the surface of the silkworm epidermis [60].
Tyrosine (Tyr) is a non-essential amino acid required for melanin synthesis. LOC725400 (4-hydroxyphenylpyruvate dioxygenase) is a key enzyme in the tyrosine metabolic pathway, responsible for catalyzing the degradation of tyrosine [61]. In our study, novel-m0138-5p regulates the downregulation of LOC725400 expression. LOC725400 is enriched in tyrosine metabolism [62] and phenylalanine metabolism pathways. Phenylalanine can be converted to tyrosine by phenylalanine hydroxylase (PAH) as the substrate for tyrosinase [63], and tyrosinase then undergoes a series of reactions to generate melanin. We speculate that novel-m0138-5p may increase the content of tyrosine in the pupae by activating tyrosine metabolism and phenylalanine metabolism pathways and regulating the expression of LOC725400, thereby promoting melanin production.

5. Conclusions

This study is the first to conduct an in-depth analysis of the miRNA expression profiles of Apis mellifera at different developmental stages, namely, the mature-larval, pre-pupal, early-pupal, and mid-pupal stages, using sRNA-seq technology. A total of 1291 miRNAs were identified, among which 171, 94, and 19 DEmiRNAs were identified in the three comparisons of L0 vs. PP3, PP3 vs. P6, and P6 vs. P9, respectively. Functional studies on the target DEmRNAs of DEmiRNAs revealed that DEmiRNAs might regulate the formation of the body color in capped broods of honeybees by activating expression changes in key genes in signaling pathways such as the Toll and Imd signaling pathway, melanogenesis, the MAPK signaling pathway-fly, the MAPK signaling pathway, the Wnt signaling pathway, tyrosine metabolism, and genes in the melanin formation pathway, such as ple, yellow family genes, and wnt1. Our research provides a theoretical basis for exploring the mechanism of body color formation in honeybees.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agriculture15090992/s1, Table S1: differentially expressed miRNAs of L0 vs. PP3; Table S2: differentially expressed miRNAs of PP3 vs. P6; Table S3: differentially expressed miRNAs of P6 vs. P9; Figure S1: miRNA base preference in L0; Figure S2: miRNA base preference in PP3; Figure S3: miRNA base preference in P6; Figure S4: miRNA base preference in P9.

Author Contributions

Conceptualization, X.Z., Y.T., S.Z. and X.X.; methodology, Y.T., X.Z., Y.L. and X.X.; software, Y.T. and C.Z.; validation, Y.T.; formal analysis, X.X., Y.T., C.Z., J.S. (Jiaqi Shang) and B.Z.; investigation, X.X., Y.T., C.Z., J.S. (Jiaqi Shang) and J.S. (Jiaqi Sun); resources, X.Z., B.Z. and S.Z.; data curation, Y.T.; original draft preparation, Y.T.; writing—review and editing, X.X., M.C., B.Z. and X.Z.; visualization, M.C.; supervision, X.X., S.Z. and B.Z.; project administration, X.X. and X.Z.; funding acquisition, X.Z, X.X., S.Z. and B.Z. All authors reviewed the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the earmarked fund for China Agriculture Research System (CARS-44-KXJ11), Fujian Natural Science Foundation Project (2021j01079), Fujian Provincial Innovation Funds for Undergraduates (S202310389087 and S202110389080), FAFU Innovation Funds for research (KFA20064A, KFB23197, and KFB23101A), and Quanzhou Introducing High-level Qualification Teams Program (2023CT015).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed toward the corresponding authors.

Acknowledgments

We are grateful for the sequencing platform and/or bioinformation analysis of Gene Denovo Biotechnology Co., Ltd. (Guangzhou, China). We also appreciate the comments and suggestions from three anonymous reviewers.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. The type of identification and characterization analysis of small RNA. Statistical analysis of the types of small RNA fragments after comparison with the database, including miRNA (existing miRNAs, known miRNAs, and novel miRNAs), rRNA, snRNA, snoRNA, tRNA, exon sense, and unann. Unann refers to sRNA sequences for which no annotation information exists in the database.
Figure 1. The type of identification and characterization analysis of small RNA. Statistical analysis of the types of small RNA fragments after comparison with the database, including miRNA (existing miRNAs, known miRNAs, and novel miRNAs), rRNA, snRNA, snoRNA, tRNA, exon sense, and unann. Unann refers to sRNA sequences for which no annotation information exists in the database.
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Figure 2. Expression analysis of Apis mellifera in L0 vs. PP3, PP3 vs. P6, and P6 vs. P9. Red represents upregulation of expression, while green represents downregulation.
Figure 2. Expression analysis of Apis mellifera in L0 vs. PP3, PP3 vs. P6, and P6 vs. P9. Red represents upregulation of expression, while green represents downregulation.
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Figure 3. The radar maps of DEmiRNAs in the L0 vs. PP3 (A), PP3 vs. P6 (B), and P6 vs. P9 (C) comparison groups. Red circles represent upregulation, while blue circles represent downregulation. The larger the circles, the greater the difference.A: Dark green represents abundance of L0; light green represents abundance of PP3. B: Dark green represents abundance of PP3; light green represents abundance of P6. C: Dark green represents abundance of P6; light green represents abundance of P9.
Figure 3. The radar maps of DEmiRNAs in the L0 vs. PP3 (A), PP3 vs. P6 (B), and P6 vs. P9 (C) comparison groups. Red circles represent upregulation, while blue circles represent downregulation. The larger the circles, the greater the difference.A: Dark green represents abundance of L0; light green represents abundance of PP3. B: Dark green represents abundance of PP3; light green represents abundance of P6. C: Dark green represents abundance of P6; light green represents abundance of P9.
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Figure 4. The Venn analysis of the DEmiRNAs in the L0 vs. PP3, PP3 vs. P6, and P6 vs. P9 comparison groups.
Figure 4. The Venn analysis of the DEmiRNAs in the L0 vs. PP3, PP3 vs. P6, and P6 vs. P9 comparison groups.
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Figure 5. Venn analysis of target genes versus transcriptome DEmRNAs. Blue represents predicted target genes, while green represents transcriptome differential genes.
Figure 5. Venn analysis of target genes versus transcriptome DEmRNAs. Blue represents predicted target genes, while green represents transcriptome differential genes.
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Figure 6. The GO and KEGG enrichment analysis of target DEmRNAs in the L0 vs. PP3 comparison. The bubbles indicate target DEmRNAs enriched in corresponding pathways; the larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
Figure 6. The GO and KEGG enrichment analysis of target DEmRNAs in the L0 vs. PP3 comparison. The bubbles indicate target DEmRNAs enriched in corresponding pathways; the larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
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Figure 7. Regulatory network diagram of target DEmiRNAs, DEmRNAs, and pathways in L0 vs. PP3 comparison.
Figure 7. Regulatory network diagram of target DEmiRNAs, DEmRNAs, and pathways in L0 vs. PP3 comparison.
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Figure 8. The GO and KEGG enrichment analysis of the target DEmRNAs in PP3 vs. P6 comparison. The bubbles indicate target DEmRNAs enriched in the corresponding pathways. The larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
Figure 8. The GO and KEGG enrichment analysis of the target DEmRNAs in PP3 vs. P6 comparison. The bubbles indicate target DEmRNAs enriched in the corresponding pathways. The larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
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Figure 9. Regulatory network diagram of DEmiRNAs, target DEmRNAs, and pathways in PP3 vs. P6 comparison.
Figure 9. Regulatory network diagram of DEmiRNAs, target DEmRNAs, and pathways in PP3 vs. P6 comparison.
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Figure 10. The GO and KEGG enrichment analysis of the target DEmRNAs in the P6 vs. P9 comparison. The bubbles indicate target DEmRNAs enriched in the corresponding pathways. The larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
Figure 10. The GO and KEGG enrichment analysis of the target DEmRNAs in the P6 vs. P9 comparison. The bubbles indicate target DEmRNAs enriched in the corresponding pathways. The larger the bubbles, the greater the amount of target DEmRNAs, and the smaller the bubbles, the fewer the target DEmRNAs. Different colors represent the p-values of different pathways; the red color indicates higher p-values, while the blue color indicates lower p-values.
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Figure 11. Regulatory network diagram of DEmiRNAs, target DEmRNAs, and pathways in P6 vs. P9 comparison.
Figure 11. Regulatory network diagram of DEmiRNAs, target DEmRNAs, and pathways in P6 vs. P9 comparison.
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Figure 12. Validation of differentially expressed miRNAs confirmed by RT-qPCR analysis.
Figure 12. Validation of differentially expressed miRNAs confirmed by RT-qPCR analysis.
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Table 1. The primers used in the present study.
Table 1. The primers used in the present study.
miRNA-NamePrimer Sequences (5′ to 3′)
U6 [30]F: GTTAGGCTTTGACGATTTCG
R: GGCATTTCTCCACCAGGTA
let-7-xloop: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCACATATCA
let-7-xF: GCCGAGCTGAGGTAGTAGGT
novel-m0169-3ploop: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCCGTGTTTT
novel-m0169-3pF: GCCGAGGATCCATGTTCTCAGAC
miR-2504-xloop: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCATCTACAA
miR-2504-xF: GCCGAGGACTCACGTCGACTG
ame-miR-210-3Ploop: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCTCGCCGAT
ame-miR-210-3PF: GCCGAGTTGTGCGTGTGAC
miR-1-3Ploop: CTCAACTGGTGTCGTGGAGTCGGCAATTCAGTTGAGCCATACCTC
miR-1-3PF: GCCGAGTGGAATGTAAAGAA
RCTCAACTGGTGTCGTGGA
Table 2. An overview of small RNA sequencing.
Table 2. An overview of small RNA sequencing.
SampleAverage
Clean_Reads		Average
High_Quality		Average
3′ Adapter_Null		Average
Insert_Null		Average
5′ Adapter_Contaminants		Average
polyA		Average
Clean_Tags
L013,328,83213,191,028
(98.9737%)		52,011
(0.3910%)		63,994
(0.4911%)		14,667
(0.1776%)		181
(0.0014%)		11,510,675
(86.9480%)
PP312,384,15712,261,662
(99.0195%)		57,079
(0.4641%)		53,185
(0.5405%)		41,691
(0.341%)		73
(0.0006%)		9,449,732
(76.9709%)
P615,314,05215,136,387
(98.84%)		75,408
(0.4991%)		53,553
(0.3537%)		46,680
(0.3078%)		90.3
(0.0006%)		12,359,786
(81.6854%)
P914,716,27414,593,037
(99.1875%)		35,494
(0.2404%)		46,142
(0.3197%)		9757
(0.0670%)		167
(0.0011%)		13,370,042
(91.5706%)
Table 3. Clean reads and reference genome alignment results.
Table 3. Clean reads and reference genome alignment results.
SampleAverage
Total_Abundance		Average
Match_Abundance
L011,510,6758,772,800 (76.21%)
PP39,449,7328,511,842 (90.07%)
P612,359,78611,071,779 (89.58%)
P913,370,04211,532,683 (86.26%)
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Zhu, X.; Tian, Y.; Cao, M.; Zhu, C.; Shang, J.; Sun, J.; Liu, Y.; Zhou, B.; Zhou, S.; Xu, X. A Comparative Transcriptomic Analysis of miRNAs and Their Target Genes During the Formation of Melanin in Apis mellifera. Agriculture 2025, 15, 992. https://doi.org/10.3390/agriculture15090992

AMA Style

Zhu X, Tian Y, Cao M, Zhu C, Shang J, Sun J, Liu Y, Zhou B, Zhou S, Xu X. A Comparative Transcriptomic Analysis of miRNAs and Their Target Genes During the Formation of Melanin in Apis mellifera. Agriculture. 2025; 15(9):992. https://doi.org/10.3390/agriculture15090992

Chicago/Turabian Style

Zhu, Xiangjie, Yuanmingyue Tian, Mingjie Cao, Chenyu Zhu, Jiaqi Shang, Jiaqi Sun, Yiming Liu, Bingfeng Zhou, Shujing Zhou, and Xinjian Xu. 2025. "A Comparative Transcriptomic Analysis of miRNAs and Their Target Genes During the Formation of Melanin in Apis mellifera" Agriculture 15, no. 9: 992. https://doi.org/10.3390/agriculture15090992

APA Style

Zhu, X., Tian, Y., Cao, M., Zhu, C., Shang, J., Sun, J., Liu, Y., Zhou, B., Zhou, S., & Xu, X. (2025). A Comparative Transcriptomic Analysis of miRNAs and Their Target Genes During the Formation of Melanin in Apis mellifera. Agriculture, 15(9), 992. https://doi.org/10.3390/agriculture15090992

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