LncRNA RORB-IT1 Encoding a Micropeptide Regulates Progesterone Synthesis, Proliferation and Apoptosis in Chicken Granulosa Cells
Jie Cao, Qingqing Wei, Li Kang, Yi Sun, Yunliang Jiang

TL;DR
A new long non-coding RNA, RORB-IT1, and its micropeptide regulate progesterone, cell growth, and death in chicken egg cells, offering potential for improving poultry breeding.
Contribution
Discovery of RORB-IT1, a bifunctional lncRNA/micropeptide that regulates granulosa cell function in chickens.
Findings
RORB-IT1 is specifically expressed in chicken granulosa cells and promotes progesterone synthesis and cell proliferation.
RORB-IT1 and its micropeptide have opposing effects on apoptosis, revealing a unique RNA–peptide balance mechanism.
RORB-IT1 is upregulated by hormones like FSH, P4, and E2, and may improve egg-laying efficiency in poultry.
Abstract
What are the main findings? We identify RORB-IT1 as a novel lncRNA that is specifically expressed in chicken follicular granulosa cells and encodes a functional micropeptide, RORB-34aa.The RORB-IT1 RNA and its encoded RORB-34aa micropeptide synergistically promote progesterone synthesis and proliferation but have opposing effects on apoptosis, revealing a unique RNA–peptide balance mechanism. We identify RORB-IT1 as a novel lncRNA that is specifically expressed in chicken follicular granulosa cells and encodes a functional micropeptide, RORB-34aa. The RORB-IT1 RNA and its encoded RORB-34aa micropeptide synergistically promote progesterone synthesis and proliferation but have opposing effects on apoptosis, revealing a unique RNA–peptide balance mechanism. What are the implications of the main findings? This work expands the functional landscape of lncRNAs in avian reproduction by…
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Figure 7- —Key Research and Development Program of Shandong Province
- —National Key Research and Development Program of China
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Taxonomy
TopicsReproductive Physiology in Livestock · Reproductive Biology and Fertility · Cancer-related molecular mechanisms research
1. Introduction
The regulation of follicular development and selection in the avian ovary represents a complex and precisely coordinated physiological process. Avian follicles spontaneously establish a hierarchical system. During peak egg production, one small yellow follicle (6–8 mm) is selected daily in the hierarchical follicle cohort, followed by rapid growth and eventual ovulation—a process termed follicle selection [1]. During the transition from pre-hierarchical follicles to hierarchical follicles, theca cells and granulosa cells perform different roles. Theca cells secrete estrogen precursors to promote follicular maturation and prevent atresia [2], while the granulosa cells of selected dominant follicles undergo functional differentiation and initiate to synthesize substantial progesterone in hierarchical follicles [3,4]. Follicle selection is classically driven by the FSH/LH endocrine axis, which regulates steroidogenic enzyme expression (e.g., StAR, P450scc) in granulosa cells [4]. However, the precise intracellular mechanisms by which granulosa cells integrate these hormonal signals to coordinate proliferation, differentiation, and steroidogenic output remain incompletely understood. Deciphering these cell-autonomous regulatory networks is crucial for understanding the precise control of avian follicular development.
Emerging evidence indicates that, in addition to hormonal signaling, epigenetic and post-transcriptional regulation constitute a crucial dimension of avian follicular development. LncRNAs (>200 nt), a major class of epigenetic and post-transcriptional regulators, have been increasingly implicated in this process, including chromatin remodeling [5], transcriptional interference [6,7] and acting as competing endogenous RNAs (ceRNAs) to sponge microRNAs [8,9]. Notably, many lncRNAs contain small open reading frames (ORFs) encoding functional micropeptides [10] involved in diverse biological contexts, ranging from embryogenesis [11] to cell metabolism [12,13]. In the avian ovary, lncRNA MSTRG.4701.7 has been implicated in regulating granulosa cell apoptosis and function [14]. lncHLEF promotes hepatic lipid synthesis both as a ceRNA and as a source of micropeptides in chicken liver [15]. Despite these progresses, the functional landscape of lncRNAs in chicken follicular development remains poorly understood.
RORB, a member of the retinoic acid receptor-related orphan receptor (ROR) subfamily of nuclear receptors, is a key regulator of circadian rhythms and may be related to chicken egg production. For example, studies in mice have demonstrated that RORB displays rhythmic expression patterns in the pineal gland and retina, and its knockout results in circadian rhythm disruptions [16]. Notably, RORB exhibits differential expression patterns in chicken follicles between hens with high egg-laying rates and low egg-laying rates [17].
In our previous study, RORB-IT1, a novel lncRNA located in the intron of RORB, was identified in chicken granulosa cells through Oxford Nanopore Technologies (ONT) transcriptome sequencing [18]. However, it remains unknown whether RORB-IT1 participates in regulating the development of chicken ovarian follicles. In this study, we further characterized the expression pattern of RORB-IT1 and explored its role in regulating the progesterone synthesis, proliferation and apoptosis of chicken granulosa cells. This discovery extends the current insights into the roles of lncRNAs in avian reproduction and provides a theoretical foundation for developing targeted strategies to enhance poultry breeding efficiency and sustainable production.
2. Materials and Methods
2.1. Animals and Sample Collection
Hy-Line Brown laying hens (35–40 weeks of age) with regular egg-laying cycles were obtained from a commercial farm in Linxi Village, Daiyue District, Tai’an, China. The hens were kept under a consistent light cycle (16 h light:8 h dark) and provided free access to feed and water throughout the study.
For each independent biological replicate, granulosa cells were pooled from three hens to minimize individual variations. Three such independent biological replicates were performed for the entire study. Prior to the anticipated ovulation (approximately 12–14 h), hens were euthanized via cervical dislocation. Ovaries were promptly excised, and follicles were dissected and categorized by diameter as follows [19]: small white follicles (SWF, 1–3.9 mm), large white follicles (LWF, 4–5.9 mm), small yellow follicles (SYF, 6–8.9 mm), large yellow follicles (LYF, 9–11.9 mm), and hierarchical follicles (F6–F1, 12–40 mm). All dissected follicles were placed in cold phosphate-buffered saline (PBS; Solarbio, Beijing, China)) and stored at 4 °C until processing. For functional grouping, SWF, LWF, and SYF were pooled as pre-hierarchical follicles, whereas F6–F1 follicles were classified as hierarchical follicles. All experimental procedures were approved by the Institutional Animal Care and Use Committee of Shandong Agricultural University (protocol code SDAUA-2022-36).
2.2. Primary Cell Isolation and Culture
Granulosa and theca cells were isolated from chicken ovarian follicles as described previously [20]. Briefly, follicles were dissected, and the granulosa cell layer was mechanically separated from theca tissue after puncture and washing in PBS. Granulosa cells from pre-hierarchical follicles (Pre-GCs) were digested with 1 mg/mL collagenase II (Coolaber, Beijing, China) for 5 min, while those from hierarchical follicles (Post-GCs) were digested with 0.25% trypsin-EDTA (Gibco, Grand Island, NY, USA) for 8 min. Theca cells from both stages were digested with collagenase II for 30 min. Digestion was terminated with M199 (Gibco, Grand Island, NY, USA) medium containing 1% FBS and antibiotics (Gibco, Grand Island, NY, USA). Post-GCs and hierarchical theca cells (Post-TCs) were cultured in a medium supplemented with 5% FBS. Cells were filtered through a 200-mesh sieve, centrifuged, resuspended, and seeded in culture plates maintained at 39 °C with 5% CO_2_. Cell identity was verified by phase-contrast microscopy based on characteristic morphologies (cobblestone-like for granulosa cells; spindle-shaped for theca cells), and only morphologically healthy cultures were used for experiments (Supplementary Figure S1).
For hormone treatments, cells at 80% confluence were incubated in serum-free M199 with indicated concentrations of 17β-estradiol (E2; Sigma-Aldrich, St. Louis, MO, USA), progesterone (P4; Sigma-Aldrich, MO, USA), or follicle-stimulating hormone (FSH; MedChemExpress, Shanghai, China) for 24 h before RNA extraction. The concentrations of FSH, E2, and P4 used were chosen based on previous studies investigating hormone responsiveness in chicken granulosa cells [21].
2.3. RNA Extraction and Real-Time Quantitative PCR (RT-qPCR)
Total RNA was extracted using the RNA Simple Total RNA Kit (TIANGEN, Beijing, China). RNA quality was verified spectrophotometrically and using gel electrophoresis. cDNA was synthesized from 1 µg RNA with the Evo M-MLV RT Mix Kit (Accurate Biotechnology, Changsha, China) following gDNA removal and reverse transcription steps as per manufacturer’s instructions. RT-qPCR was conducted on a LightCycler 96 system using SYBR Green ProTaq HS Premix (Accurate Biotechnology, Changsha, China). Each 20 µL reaction contained 10 µL master mix, 0.8 µL primers (10 µM; Table S1), 2 µL cDNA, and 7.2 µL water. No-template controls were included. Primer efficiency was validated via standard curves. Gene expression was normalized to GAPDH using the 2^−ΔΔCt^ method, with three biological and three technical replicates per sample. All experiments were performed in three independent repeats.
2.4. Rapid Amplification of cDNA Ends (RACE)
The full-length sequence of RORB-IT1 was confirmed by 5′ and 3′ RACE using the SMARTer RACE 5′/3′ Kit (Takara, Dalian, China). PCR amplification was performed with the kit’s Universal Primer Mix and gene-specific primers (Table S1) using 2× Phan-Q5 SuperMix High-Fidelity Enzyme (Kermey Biotech, Zhengzhou, China), according to the protocol described by Hu et al. [21]. The resulting amplicons were cloned into the pMD19-T vector (Takara, Dalian, China) and sequenced by Beijing Liuhe Bada Gene Technology Co., Ltd. (Beijing, China).
2.5. Construction of Overexpression Plasmids and Synthesis of Small Interfering RNAs (siRNAs)
The full-length RORB-IT1 sequence was amplified by PCR using 2× Phan-Q5 SuperMix High-Fidelity Enzyme with primers containing HindIII and XbaI restriction sites. The resulting amplicon was then ligated into the pcDNA3.1(+) vector to generate the pcDNA3.1-RORB-IT1 overexpression plasmid. In a similar procedure, the open reading frames ORF1 and ORF2 were PCR-amplified and cloned into the corresponding restriction sites of the pcDNA3.1-EGFP vector (HonorGene, Changsha, China) to yield the pcDNA3.1-ORF1-EGFP and pcDNA3.1-ORF2-EGFP plasmids, respectively. To investigate the function of the short peptide RORB-34aa, the corresponding coding sequence was cloned into pcDNA3.1(+) vectors (pcDNA3.1-RORB-34aa). Additionally, two specific point-mutation constructs were generated [22]. In both constructs, the start codon ATG of RORB-34aa was replaced with ATT to disrupt translation initiation. The pcDNA3.1-RORB-34aa-MUT plasmid was produced by introducing this mutation into the sequence encoding only the short peptide, while the pcDNA3.1-RORB-IT1-MUT plasmid was constructed by incorporating the same mutation into the full-length RORB-IT1 background within the pcDNA3.1(+) vector. All plasmids were extracted and purified with the EndoFree Plasmid Midi Kit (Aidlap, Beijing, China) and verified through Sanger sequencing. Purified plasmids were subsequently used for cell transfection experiments.
For siRNA-based knockdown experiments, siRNA oligonucleotides targeting specific sequences were designed and synthesized by Shanghai GenePharma Pharmaceutical Technology Co., Ltd. The corresponding siRNA sequences are provided in Table S2.
2.6. Isolation of Nuclear and Cytoplasmic Fractions
Nuclear and cytoplasmic RNA fractions were isolated from granulosa cells cultured in 6-well plates using the NE-PER Nuclear and Cytoplasmic Extraction Kit (Thermo Fisher Scientific, MA, USA) as previously described [23], following the manufacturer’s instructions. Briefly, cells were trypsinized, pelleted, and fractionated to obtain separate nuclear and cytoplasmic lysates. Total RNA from each fraction was extracted with TRIzol reagent (Accurate Biotechnology, Changsha, China) and reverse-transcribed into cDNA as described earlier. Subcellular RNA localization was assessed using quantitative PCR, with U6 and GAPDH mRNA used as nuclear and cytoplasmic controls, respectively. Relative transcript distribution was normalized to these endogenous markers.
2.7. Fluorescence In Situ Hybridization (FISH)
Cy3-labeled RORB-IT1-specific probes were designed and synthesized by Genepharma Co., Ltd. (Shanghai, China). Fluorescence in situ hybridization was performed using a commercially available Fluorescence in Situ Hybridization Kit (Genepharma, Shanghai, China) in accordance with the manufacturer’s protocol [15]. Images were acquired using a Dragonfly High-Speed Confocal Live Cell Imaging System (Andor, Belfast, UK). The sequences of the RNA probes used were as follows: RORB-IT1 Probe 1: 5′-TTTCCCAACAGCGGTATCTTT-3′; RORB-IT1 Probe 2: 5′-GTCAAATAATAAGGGACCAACACGA-3′; RORB-IT1 Probe 3: 5′-TCTTCACGGTAAAGCCTGTTCT-3′; Negative Control Probe: 5′-TGCTTTGCACGGTAACGCCTGTTTT-3′.
2.8. Cell Transfection
Cells were cultured until they reached approximately 80% confluence, after which the culture medium was replaced with serum-free medium. For plasmid transfection, either the pcDNA3.1-RORB-IT1 overexpression plasmid or the empty pcDNA3.1 vector was introduced into cells using Lipofectamine™ LTX transfection reagent (Thermo Fisher Scientific, Waltham, MA, USA). For siRNA transfection, Lipofectamine™ RNAiMAX transfection reagent (Thermo Fisher Scientific, Waltham, MA, USA) was employed at a final concentration of 75 nM. All transfections were performed in Opti-MEM medium (Gibco, Grand Island, NY, USA) following the manufacturer’s recommended protocols.
2.9. Enzyme-Linked Immunosorbent Assay (ELISA)
Progesterone (P4) secretion was quantified in culture supernatants collected 48 h after transfection. P4 levels were measured using a commercial Chicken P4 (PROG) ELISA Kit (Enzyme-linked Biotechnology, Yancheng, China) according to the manufacturer’s protocol [21]. Absorbance was read at the recommended wavelength, and concentrations were calculated based on the included standard curve.
2.10. Cell Counting Kit-8 (CCK-8) Assay
Cell proliferation was evaluated using the Cell Counting Kit-8 (Beyotime, Shanghai, China). Granulosa cells were seeded in 96-well plates and transfected according to the previously described protocol [21]. At 0, 12, 24, 36, and 48 h after transfection, CCK-8 solution was added to each well. Following a two-hour incubation period, the absorbance at 450 nm was measured with an ELx808 microplate reader (BioTek, Winooski, VT, USA).
2.11. 5-Ethynyl-2′-Deoxyuridine (EdU) Assay
The proliferative activity of granulosa cells was assessed using the BeyoClick™ EdU Cell Proliferation Kit with Alexa Fluor 555 (Beyotime, Shanghai, China) according to the manufacturer’s protocol [21]. Granulosa cells were cultured in 6-well plates and transfected as described previously. At 24 h after transfection, EdU reagent was added to the culture medium, and cells were incubated for an additional 2 h. Following incubation, cells were fixed and stained with Hoechst 33342 to label nuclei. Fluorescence images were acquired using an Olympus fluorescence microscope (Olympus, Tokyo, Japan). The numbers of EdU-positive cells and total cells were quantified from the captured images with ImageJ software.
2.12. Flow Cytometry Analysis
Apoptosis and cell cycle distribution in transfected granulosa cells were evaluated using flow cytometry. Apoptosis was detected using the Annexin V-FITC/PI Apoptosis Detection Kit (Vazyme, Nanjing, China) according to the supplier’s protocol [24], while cell cycle analysis was performed with the Cell Cycle and Apoptosis Analysis Kit (Beyotime, Shanghai, China), following established methodologies. At 24 h after transfection, cells and corresponding culture supernatants were collected and stained following the respective kit protocols. Samples were then analyzed on a Beckman Coulter flow cytometer (Beckman Coulter, Brea, CA, USA). Data were acquired and processed using Attune™ Cytometric Software version 5.3.0.
2.13. Western Blotting
Protein samples were separated using SDS-PAGE on 16.5% pre-cast gels (Wansheng Haotian, Shanghai, China) at 150 V for 1 h and 20 min. Electrophoresis was stopped once the bromophenol blue dye front reached the bottom of the gel. Target bands were then excised and transferred onto 0.45 μm polyvinylidene fluoride (PVDF) membranes using NcmBlot transfer buffer (NCM, Suzhou, China) via a wet transfer system for 20 min [24]. Membranes were blocked and subsequently incubated overnight at 4 °C with the following primary antibodies: Anti-EGFP tag Mouse mAb (1:1000, Engibody, Shanghai, China) and Cyclophilin B Mouse Monoclonal Antibody (1:1000, Biodragon, Suzhou, China). After washing, membranes were incubated with horseradish peroxidase (HRP)-labeled goat anti-rabbit/anti-mouse IgG (1:4000, Beyotime, Shanghai, China) as secondary antibodies for 2 h at room temperature. Protein signals were detected using BeyoECL Plus (Beyotime, Shanghai, China) and imaged on an Azure C300 imaging system (Azure Biosystems, Dublin, CA, USA). Band intensities were quantified with ImageJ 1.46r software, and Cyclophilin B was used as the loading control for normalization.
2.14. Statistical Analysis
Statistical analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, IL, USA). Data are presented as mean ± standard error of the mean (SEM). Differences between two groups were assessed with the independent Student’s t-test, while comparisons among multiple groups were analyzed using one-way ANOVA followed by Tukey’s post hoc test. A p-value < 0.05 was considered statistically significant.
3. Results
3.1. Identification and Subcellular Localization of RORB-IT1 in Post-GCs
To verify the sequence accuracy of the identified lncRNA RORB-IT1, 5′ and 3′ RACE was performed in chicken granulosa cells. The 5′ and 3′ ends were extended by 63 bp and 21 bp, respectively, yielding a full-length sequence of 383 bp (Figure 1A). Ensembl analysis (NM_205093.2) revealed that RORB-IT1 is located on the Z chromosome of Hy-Line Brown hens within the RORB-203 transcript (Z:37,158,101–37,324,007). The chicken RORB-203 gene comprises 11 exons, and RORB-IT1 (37,298,170–37,298,552) is located in its 10th intron (Figure 1B). The subcellular localization of RORB-IT1 in both the nucleus and cytoplasm was analyzed using RNA FISH (Figure 1C) and nuclear-cytoplasmic fractionation assays (Figure 1D). Furthermore, the Open Reading Frame Viewer predicted two complete coding-potential ORFs within RORB-IT1 (Figure 1E). To validate its coding capacity, both ORFs were cloned into a pcDNA3.1 vector with an EGFP tag (Figure 1F) and transfected into chicken granulosa cells. After 48 h, Western blotting with an anti-EGFP antibody detected a 4 kDa micropeptide encoded by ORF1 (Figure 1G). Based on the established convention in molecular biology for designating functionally characterized micropeptides, the small peptide encoded by ORF1 of the lncRNA RORB-IT1 is formally named RORB-34aa (Figure 1H).
3.2. RORB-IT1 Is Specifically Expressed in Post-GCs and Regulated by Sex Hormones
To elucidate the functional role of RORB-IT1 during follicular development in chickens, we first examined its mRNA expression patterns in granulosa cells and theca cells isolated from chicken pre-hierarchical and hierarchical follicles during the peak egg production period. RT-qPCR analysis demonstrated a stage-specific expression of RORB-IT1, with significantly elevated mRNA levels in Post-GCs compared to the nearly undetectable expression in pre-GCs (Figure 2A). Notably, the expression of RORB-IT1 remained at basal levels in theca cells regardless of the follicular developmental stage. To further investigate the hormonal regulation of the expression of RORB-IT1, Post-GCs were treated with increasing concentrations (0, 5, 50, and 100 nM) of FSH, E2, or P4 for 24 h. Intriguingly, while E2 and P4 treatment resulted in a consistent dose-dependent upregulation of RORB-IT1 expression, FSH exhibited a biphasic regulatory pattern (Figure 2B–D). Specifically, RORB-IT1 expression peaked at 50 nM FSH treatment but showed an attenuated response at higher concentrations (100 nM).
3.3. RORB-IT1 Promotes Progesterone Synthesis in Post-GCs
To investigate the effect of RORB-IT1 on progesterone synthesis in granulosa cells, overexpression plasmids (Figure 3A) and siRNAs (Figure 3B) targeting RORB-IT1 were transfected into Post-GCs. RT-qPCR analysis revealed that the overexpression of RORB-IT1 significantly upregulated the mRNA expression of key steroidogenic genes, including steroidogenic acute regulatory protein (StAR) and 3β-hydroxysteroid dehydrogenase (HSD3B), whereas the expression of cytochrome P450 family 11 subfamily A member 1 (CYP11A1) remained unchanged (Figure 3C). In contrast, the knockdown of RORB-IT1 markedly downregulated the mRNA levels of StAR and HSD3B (Figure 3D). The functional impact of these transcriptional changes was assessed by measuring P4 production. The ELISA analysis of culture supernatants collected 48 h post-transfection showed that RORB-IT1 overexpression significantly increased P4 secretion (Figure 3E). Conversely, RORB-IT1 knockdown led to a significant decrease in P4 production (Figure 3F).
3.4. RORB-IT1 Promotes the Proliferation of Post-GCs
To investigate the potential regulatory role of RORB-IT1 in granulosa cell proliferation, CCK-8 assays were performed at 0, 12, 24, 36, and 48 h after the overexpression or knockdown of RORB-IT1 in in vitro isolated and cultured Post-GCs. The results showed that RORB-IT1 overexpression continuously enhanced the granulosa cell proliferation ability at 12, 24, and 36 h (Figure 4A), while the knockdown of RORB-IT1 significantly inhibited Post-GC proliferation at 12, 24, and 36 h (Figure 4B). To further confirm the promotive effect of RORB-IT1 on granulosa cell proliferation, EdU staining was conducted. The results showed that the proportion of EdU-positive cells was significantly increased when RORB-IT1 was overexpressed and decreased when it was silenced (Figure 4C–F). Furthermore, we detected the mRNA expression levels of key cell cycle-related genes using RT-qPCR. The results showed that RORB-IT1 overexpression significantly increased the mRNA levels of cyclin D1 (CCND1), cyclin D2 (CCND2), cyclin-dependent kinase 1 (CDK1), and cyclin-dependent kinase 2 (CDK2) (Figure 4G). In contrast, the knockdown of RORB-IT1 led to a significant reduction in the expression of CDK1 and CCND1 (Figure 4H). Flow cytometry cell cycle analysis (Figure 4I–L) showed that RORB-IT1 overexpression significantly increased the proportion of cells in the G2/M phase and decreased the proportion of cells in the G0/G1 phase, which is consistent with an enhanced proliferative activity.
3.5. RORB-IT1 Suppresses the Apoptosis of Post-GCs
To investigate the effect of RORB-IT1 on apoptosis in follicular Post-GCs, flow cytometry was performed 24 h post-transfection. The results demonstrated that the overexpression of RORB-IT1 significantly inhibited apoptosis in Post-GCs (Figure 5A,B). Conversely, the knockdown of RORB-IT1 significantly promoted apoptosis under the same conditions (Figure 5C,D). Subsequently, the mRNA expression levels of key apoptosis-related genes were analyzed using RT-qPCR. The overexpression of RORB-IT1 significantly reduced the mRNA level of Caspase3, consistent with the observed reduction in apoptosis. The mRNA level of the anti-apoptotic gene BCL2 was also downregulated upon RORB-IT1 overexpression (Figure 5E). In contrast, the knockdown of RORB-IT1 markedly increased the expression of pro-apoptotic genes Caspase3 and Caspase8, as well as BCL2 (Figure 5F).
3.6. RORB-34aa Localized in the Cytoplasm and Nucleus Promotes Progesterone Synthesis
To investigate the role of RORB-34aa in chicken follicular development, we first analyzed its subcellular localization by inserting it into a pcDNA3.1 vector with an EGFP tag. After staining the nucleus with DAPI, observation under a high-speed confocal live cell imaging system revealed the presence of EGFP green fluorescence (Figure 6A) in both the cytoplasm and nucleus, indicating that RORB-34aa is distributed in both compartments. Subsequently, the negative control (pcDNA3.1-NC), RORB-34aa overexpression vector (pcDNA3.1-RORB-34aa), RORB-34aa initiation codon mutant vector (pcDNA3.1-RORB-34aa-MUT), and RORB-34aa initiation codon mutant vector within RORB-IT1 (pcDNA3.1-RORB-IT1-MUT) were transfected into the Post-GCs (Figure 6B,C). ELISA analysis (Figure 6D) showed that, compared with the control group, transfection with the RORB-34aa overexpression plasmid for 48 h significantly increased progesterone levels in the cell culture supernatant, while the mutation of the RORB-34aa initiation codon or mutation of the RORB-34aa initiation codon within RORB-IT1 eliminated this progesterone synthesis-promoting effect. Meanwhile, after the overexpression of RORB-34aa, the mRNA expression level of HSD3B in Post-GCs was significantly increased (Figure 6E). Collectively, RORB-34aa distributed in the cytoplasm and nucleus can promote progesterone synthesis in chicken granulosa cells.
3.7. RORB-34aa Promotes Proliferation and Apoptosis of Post-GCs
We next explored whether the RORB-34aa encoded by RORB-IT1 influences the proliferation and apoptosis of Post-GCs. The CCK-8 assay (Figure 7A) confirmed that RORB-34aa overexpression significantly increased the optical density value of granulosa cells during the 12–48 h period, and the RORB-IT1-MUT overexpression group also significantly increased the optical density value of Post-GCs, while the increase in optical density values was eliminated when overexpressing the RORB-34aa initiation codon mutant alone. EdU staining assay (Figure 7B,C) revealed that, compared with the empty vector control group, the density of EdU-positive cells in the RORB-34aa overexpression group was significantly higher. This promoting effect disappeared after mutating the RORB-34aa initiation codon, while the number of EdU-positive cells increased again relative to the NC group when the RORB-IT1 with the mutated RORB-34aa initiation codon was added. Subsequently, the RT-qPCR detection of key cell cycle-related genes showed that RORB-34aa overexpression significantly increased the mRNA level of CDK1 (Figure 7D). Flow cytometry detection (Figure 7E,F) showed that, compared with the control group, RORB-34aa overexpression for 48 h significantly increased the apoptosis rate, while the mutation of the RORB-34aa initiation codon completely eliminated this pro-apoptotic effect. Notably, a consistent phenotypic reversal was also observed when the RORB-34aa initiation codon was mutated within RORB-IT1. Meanwhile, the RT-qPCR detection of apoptosis-related genes showed that RORB-34aa overexpression significantly increased the mRNA expression levels of Caspase 8 and Caspase 9 (Figure 7G).
4. Discussion
Follicular development is tightly regulated by hypothalamic–pituitary–gonadal (HPG) axis hormones and growth factors [1,25]. Some lncRNAs related to follicular development have been proven to be regulated by hormones. For example, lncRNA MSTRG.5970.28 was downregulated by hCG and FSH in goose granulosa cells [26]. LncRNA HAND2OT was upregulated by E2 and downregulated by P4 and FSH in chicken follicular theca cells [23]. Similarly, our data showed that RORB-IT1 expression is induced by key reproductive hormones (FSH, E2, P4), positioning it as a downstream effector within these classic signaling cascades. Certainly, beyond hormonal regulation, several confounding factors, including the genetic background [27], nutritional status [28], stress [29], and environmental cues such as photoperiod [30], may influence the expression of RORB-IT1 in vivo. All items warrant further investigation.
Recently, several studies have revealed that some lncRNA transcripts contain short ORFs (sORFs) that code for functional micropeptides, which participate in various cellular activities [15,31,32]. For instance, three novel peptides encoded by lncHLEF could directly interact with ACLY protein to delay its degradation to subsequently promote ACLY protein expression, thus leading to the activation of triglyceride and cholesterol synthesis signaling pathways in chickens [15]. LncRNA H19-Encoded Micropeptide altH19 promotes DNA replication and mitosis in myeloma cells by enhancing the phosphorylation of CDK2 at threonine 160 [33]. In this study, we also find that lncRNA RORB-IT1 encodes a functional micropeptide, RORB-34aa. Moreover, this micropeptide can regulate the survival and function of granulosa cells in chickens.
Previous studies have revealed that some lncRNAs regulate hormone synthesis in ovarian follicular granulosa cells. In mice, LncRNA Gm2044 promotes the binding of EEF2 to Nr5a1 mRNA and then enhances Nr5a1 mRNA translation, and the upregulated NR5A1 protein can strengthen estradiol synthesis [34]. LncGSAR controls ovine ovarian granulosa cell steroidogenesis via sponging MiR-125b to activate the SCAP/SREBP pathway [35]. In this study, we found that RORB-IT1 or RORB-34aa encoded by RORB-IT1 can upregulate the expression of steroidogenic genes and progesterone synthesis. However, the promotion effect on progesterone synthesis disappeared when RORB-IT1 lost the potency to encode micropeptide. Therefore, the effect on progesterone synthesis is induced by the micropeptide RORB-34aa. But the mechanism by which RORB-34aa regulates progesterone synthesis requires further investigation.
LncRNAs have been reported to exert their functions by serving as RNA molecules or encoded peptides. For instance, HAND2OT regulates the survival and function of chicken theca cells via its RNA moiety and the HAND2OT-66aa micropeptide it encodes [23]. lncGRN promoted chicken follicular atresia through the lncGRN/miR-103-3p/FBXW7 axis and the translated micropeptide GRN-122aa [32]. In this study, the pro-proliferation effect on granulosa cells still remains when the transcript of RORB-IT1 cannot encode a micropeptide. That is to say, RORB-IT1 regulates cell proliferation through both RNA- and peptide-mediated mechanisms.
It was reported that the roles of lncRNAs and encoded peptides might be entirely different. For instance, LINC00665 contributed to breast cancer progression through miR-379-5p/LIN28B [36], whereas the micropeptide CIP2A-BP encoded by LINC00665 blocked breast cancer progression [37]. In this study, we also observed opposing effects of the RORB-IT1 RNA scaffold and its encoded micropeptide RORB-34aa on granulosa cell apoptosis, suggesting that they may act through independent mechanisms. We speculated that the RORB-IT1 RNA may function as a scaffold or ceRNA, while the RORB-34aa peptide may bind with critical regulators within pathways such as MAPK or PI3K/AKT [38,39], leading to opposite apoptotic outcomes. This model positions RNA and peptides at different regulatory layers within signaling networks. Elucidating these molecular pathways is therefore essential for deciphering how this intramolecular feedback loop is orchestrated through integrating transcriptomics, phosphoproteomics, IP-MASS, and others in future studies. Moreover, the relative physiological significance of the anti-apoptotic function of RORB-IT1 RNA versus the pro-apoptotic effect of RORB-34aa under endogenous conditions remains to be determined.
BCL2 has been reported to be an anti-apoptotic regulator by binding pro-apoptotic protein (Bax, Bak) to prevent the release of cytochrome c from mitochondria. Cytosolic cytochrome c leads to formation of the apoptosome and activates the caspase cascade, ultimately leading to cell death [40]. Curiously, we find that BCL2 mRNA exhibited the same trend of expression change with Caspase family genes when RORB-IT1 was overexpressed or silenced for 24 h. Maybe this is a phenomenon of the compensatory regulation of cells in response to stress. Moreover, the activity of BCL2 is influenced by phosphorylation. The detection of the protein levels of BCL2, BAX/BAK and cleaved CASPASE may be helpful for elucidating this. Additionally, mitochondrial function, such as mitochondrial membrane potential (MMP), mitochondrial permeability transition pore (MPTP) and reactive oxygen species (ROS), should be evaluated to determine if the influence of RORB-IT1 or RORB-34aa on apoptosis was induced through a mitochondrial-CASPASE signaling pathway.
RORB, a key nuclear receptor governing circadian rhythms and metabolism [41], may also be associated with chicken egg production [17]. Previous research revealed that intronic lncRNA can function through regulating the expression of transcripts encoded by the host gene [42]. As an intronic lncRNA, the potential cis-regulatory relationship between RORB-IT1 and its host gene RORB warrants careful consideration. We hypothesize that RORB-IT1 may modulate RORB expression, thereby integrating follicular developmental signals.
It should be noted that the encoding of RORB-34aa in this study was based on in vitro overexpression conditions. Due to the small size of the micropeptide, we were unable to confirm its native expression using peptide-specific antibodies under the current experimental conditions. Endogenous translation and steady-state levels of RORB-34aa therefore await validation by more sensitive techniques such as mass spectrometry or ribosome profiling. Furthermore, the function of lncRNA RORB-IT1 was validated with primary cell cultures in vitro, which may not fully recapitulate the complex hormonal and cellular interactions within the intact ovarian follicle in vivo. Additional studies using larger animal cohorts, in vivo models (such as genetic manipulation in avian systems), and direct measurements of the endogenous peptide are required to corroborate our findings and explore their potential for poultry breeding.
5. Conclusions
Our study characterized the lncRNA RORB-IT1 and uncovered a co-regulatory mechanism involving its RNA molecule and the encoded micropeptide that finely tunes the steroidogenesis, proliferation and apoptosis of Post-GCs.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1Johnson A. The Avian Ovary and Follicle Development: Some Comparative and Practical Insights Turk. J. Vet. Anim. Sci.20143866066910.3906/vet-1405-6 · doi ↗
- 2Hrabia A. Sechman A. Rzasa J. Independent, Non-IGF-I Mediated, GH Action on Estradiol Secretion by Prehierarchical Ovarian Follicles in Chicken. In Vitro Study Folia Biol.20126021321710.3409/fb 60_3-4.213-21723342919 · doi ↗ · pubmed ↗
- 3Tilly J.L. Kowalski K.I. Johnson A.L. Stage of Ovarian Follicular Development Associated with the Initiation of Steroidogenic Competence in Avian Granulosa Cells Biol. Reprod.19914430531410.1095/biolreprod 44.2.3051849025 · doi ↗ · pubmed ↗
- 4Johnson A.L. Woods D.C. Dynamics of Avian Ovarian Follicle Development: Cellular Mechanisms of Granulosa Cell Differentiation Gen. Comp. Endocrinol.2009163121710.1016/j.ygcen.2008.11.01219059411 · doi ↗ · pubmed ↗
- 5Wei J.-W. Huang K. Yang C. Kang C.-S. Non-Coding RN As as Regulators in Epigenetics (Review)Oncol. Rep.2017373910.3892/or.2016.523627841002 · doi ↗ · pubmed ↗
- 6Tu J. Chen Y. Li Z. Yang H. Chen H. Yu Z. Long Non-Coding RN As in Ovarian Granulosa Cells J. Ovarian Res.2020136310.1186/s 13048-020-00663-232503679 PMC 7275442 · doi ↗ · pubmed ↗
- 7Kopp F. Mendell J.T. Functional Classification and Experimental Dissection of Long Noncoding RN As Cell 201817239340710.1016/j.cell.2018.01.01129373828 PMC 5978744 · doi ↗ · pubmed ↗
- 8Gao N. Li Y. Li J. Gao Z. Yang Z. Li Y. Liu H. Fan T. Long Non-Coding RN As: The Regulatory Mechanisms, Research Strategies, and Future Directions in Cancers Front. Oncol.20201059881710.3389/fonc.2020.59881733392092 PMC 7775490 · doi ↗ · pubmed ↗
