Whole transcriptome profiling reveals a lncMDP1 that regulates myogenesis by adsorbing miR-301a-5p targeting CHAC1

Chen, Bingjie; Cai, Hanfang; Niu, Yufang; Zhang, Yushi; Wang, Yanxing; Liu, Yang; Han, Ruili; Liu, Xiaojun; Kang, Xiangtao; Li, Zhuanjian

doi:10.1038/s42003-024-06226-1

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Published: 02 May 2024

Whole transcriptome profiling reveals a lncMDP1 that regulates myogenesis by adsorbing miR-301a-5p targeting CHAC1

Bingjie Chen¹^na1,
Hanfang Cai¹^na1,
Yufang Niu¹,
Yushi Zhang¹,
Yanxing Wang¹,
Yang Liu¹,
Ruili Han^1,2,
Xiaojun Liu^1,2,
Xiangtao Kang ORCID: orcid.org/0000-0002-9628-7135^1,2 &
…
Zhuanjian Li ORCID: orcid.org/0000-0002-7595-0604^1,2

Communications Biology volume 7, Article number: 518 (2024) Cite this article

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Abstract

Myoblast proliferation and differentiation are essential for skeletal muscle development. In this study, we generated the expression profiles of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in different developmental stages of chicken primary myoblasts (CPMs) using RNA sequencing (RNA-seq) technology. The dual luciferase reporter system was performed using chicken embryonic fibroblast cells (DF-1), and functional studies quantitative real-time polymerase chain reaction (qPCR), cell counting kit-8 (CCK-8), 5-Ethynyl-2′-deoxyuridine (EdU), flow cytometry cycle, RNA fluorescence in situ hybridization (RNA-FISH), immunofluorescence, and western blotting assay. Our research demonstrated that miR-301a-5p had a targeted binding ability to lncMDP1 and ChaC glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1). The results revealed that lncMDP1 regulated the proliferation and differentiation of myoblasts via regulating the miR-301a-5p/CHAC1 axis, and CHAC1 promotes muscle regeneration. This study fulfilled the molecular regulatory network of skeletal muscle development and providing an important theoretical reference for the future improvement of chicken meat performance and meat quality.

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Introduction

Skeletal muscle is the main component of meat. Both of muscle growth rate and meat quality are important economic traits in the broiler industry, so investigation of the molecular mechanisms underlying skeletal muscle growth and development can help us to improve the meat output rate and meat quality in the livestock industry^1,2,3. The growth and development of skeletal muscle is a long and complex multistage process⁴. Initially, somites differentiate firstly into muscle precursor cells and then into myogenic precursors that proliferate and differentiate into myoblasts, which further differentiate into myotubes and then fuse into multinucleated myotubes, and myotubes then aggregate into bundles to form muscle fibers, and eventually mature into skeletal muscle tissue^5,6,7. The proliferation and differentiation of myoblasts can simulate the growth and development of muscles, and this process is regulated by multiple molecular, including coding genes, transcription factors, signaling pathways, noncoding RNAs, and the interaction networks among them. Therefore, extensive in vitro studies performed to explore their synergistic effects provide insight into the molecular regulatory mechanisms involved in skeletal muscle development⁸.

Recent studies have shown that noncoding RNAs play a key role in the regulation of skeletal muscle growth and development. MicroRNAs (miRNAs) are a class of endogenous noncoding small noncoding RNAs that can silence RNAs and regulate gene expression at the posttranscriptional level^9,10,11. LncRNAs and miRNAs can interact with each other through direct binding or competitive endogenous RNA (ceRNA) mechanisms, thereby exerting important functions such as regulating cell proliferation and differentiation, and individual development^12,13,14. Recent studies have found that lncIRS1 can act as a ceRNA of the miR-15 family, which in turn regulates the expression of the IRS1 gene, thereby promoting skeletal muscle myogenesis for the treatment of muscle atrophy¹⁵. Lnc-ORA suppresses skeletal muscle production in mice by acting as a sponge of miR-532-3p and regulating IGF2BP2 expression¹⁶. However, the biological function played by ceRNA mechanisms in the skeletal muscle development of chickens is rarely reported.

The Arbor Acres broiler (AA broiler) is a modern commercial broiler with a fast growth rate, high feed conversion rate, full development of breast and leg muscles, and good carcass quality. Chickens are often used for muscle growth and development research, in order to reveal the key genes and molecular regulatory mechanisms of chicken skeletal muscle growth and development. Therefore, in this study, chicken primary myoblasts (CPMs) at key developmental stages of proliferation and differentiation were collected for whole transcriptome sequencing, including CPMs proliferating to 50% (G1) and 100% (G2), differentiation to day 1 (D1), day 2 (D2), day 4 (D4), day 6 (D6) and day 8 (D8), which covers the pre, middle and late stages of proliferation and differentiation, which is helpful for a comprehensive understanding of the myoblast growth process. As a result, a lncRNA-miRNA-mRNA interaction network associated with chicken skeletal muscle development was drawn. These findings enrich our understanding of the regulatory network and molecular mechanisms of chicken muscle development.

Results

Construction of CPMs at different developmental stages

CPMs were isolated and cultured from the leg muscles of normal AA broilers at the 11 embryonic (E11). The freshly isolated myoblasts were round, fully adherent and extended into a spindle shape, and then proliferated rapidly. We collected cells when the confluence of myoblasts reached 50% and 100%. Myoblasts were spindle-shaped monocytes before the induction of differentiation. A large number of proliferating myoblasts became elongated on 1^st day after differentiation and presented a parallel arrangement, and the cells aggregated into bundles and became fibrillar. On the 2nd day of induction, the cells fused to form long multinucleated tubular primary myotubes, which continuously increased in size. On the 4th day, the number of myotubes further increased, and on 6th day, the myotubes became thinner and began to detach. On the 8th day, the myotubes showed a large area of detachment (Supplementary Fig. 1). The cells at different developmental times (proliferation to 50 and 100%, differentiation to D1, D2, D4, D6, and D8) were collected for RNA sequencing (RNA-seq).

Identification of differentially expressed mRNAs, miRNAs, lncRNAs (DEmRNAs, DEmiRNAs, DElncRNAs), and construction of interactive network

We performed a whole-transcriptome analysis of CPMs at different differential stages. We demonstrated the sources of variance in our data by PCA analysis of two principal components (PC1 and 2). As shown in Supplementary Fig. 2, PC1, and PC2 contributed 59.7% and 24.3%, respectively. It can be seen from Supplementary Fig. 2 that the three samples we collected at each time point clustered closely together and also separated from others at different differential stages, indicating low variance in this analysis and showing good data repeatability for the following analysis. A total of 6937 DEmRNAs were obtained when the samples from every two of differential time points were compared (Supplementary Tab. 1). 1048 DEmRNAs (393 upregulated and 655 downregulated) were identified in the proliferative G1-vs.-G2 group (Fig. 1a), while the differentiation (G2-vs.-D1, G2-vs.-D2, G2-vs.-D4, G2-vs.-D6, and G2-vs.-D8) groups showed 536 possible key genes that regulated differentiation (Fig. 1b). To further explore the dynamic expression patterns of genes during the developmentally expressed stages of myoblasts, we clustered the expression patterns of all differential genes throughout the developmental stages of CPMs differentiation through trend analysis, which showed 2 highly significantly enriched gene sets, (P < 0.00, Fig. 1c), profile 0 and profile 19, with a total of 4920 differentially expressed genes.

**Fig. 1: Overview of DEmRNAs, and lncRNA‒miRNA‒mRNA ceRNA network of target genes, n = 3 biologically independent samples.**

In this study, genes were divided into 17 modules (color coded) with similar expression patterns via weighted gene correlation network analysis (WGCNA), as shown in the tree diagram (Supplementary Fig. 3),each branch formed a module and each leaf in the branch represents a gene. The number of genes in each module was shown in Supplementary Fig. 4. Next, we performed correlation analysis on these 17 modules (Supplementary Fig. 5). According to current researches, we selected 14 marker genes related to myoblast proliferation (CDK1, CCNB1, PCNA), differentiation (MYH1C, MYOD1, MyoG, MCF2, MYH1F, MYH15), fusion (SMAD3, TGFB3, ACVR1B), and myogenesis (MEF2C, MYF6), and their gene expression patterns were used to indicate the differential stages of CPMs (Supplementary Fig. 6)¹⁷. As shown in Fig. 1d we found that six modules, MM.black, MM.green, MM.magenta, MM.cyan, MM.grey60, and MM.lightgreen were significantly associated with the 14 genes representing specific developmental stages mentioned above, including 7,433 genes, so that the corresponding modules could be selected for further study. The expression levels of 6,937 differentially expressed genes were further investigated by Pearson correlation coefficient analysis with 14 marker genes, and thehighly correlated differentially expressed genes might present synergistic effect with them, and a total of 957 differential genes were obtained according to a Pearson correlation coefficient ≥0.95.

The Venn diagram results showed that 196 DEmRNAs may play critical roles throughout all developmental stages after a combined analysis based on the four methods (Fig. 1e). Gene ontology (GO) term enrichment and kyoto encyclopedia of genes and genomes (KEGG) pathway analysis of these 196 DEmRNAs were performed to investigate the important pathways and related biological functions of DEGs. GO analysis revealed that the differentially expressed mRNAs were mainly associated with cell cycle terms, including cell cycle, mitosis and DNA conformational changes (Fig. 1f). Additionally, KEGG pathway analysis showed that these mRNAs were highly enriched in the cell cycle, DNA replication, glutathione metabolism, valine, leucine, and isoleucine biosynthesis and P53 signaling pathway (Fig. 1g).

Meanwhile, we found 890 DEmiRNAs, and 942 DElncRNAs from sequencing results. The volcano plot showed that there were 145 DEmiRNAs and 117 DElncRNAs in the proliferative phase G1-vs.-G2 group (Supplementary Fig. 7a, d). The Venn diagram of the five groups (G2-vs.-D1, G2-vs.-D2, G2-vs.-D4, G2-vs.-D6, and G2-vs.-D8) in the differentiation phase showed that 50 DEmiRNA and 65 DElncRNAs might be essential in regulating differentiation (Supplementary Fig. 7b, e). To further explore the dynamic expression patterns of miRNAs and lncRNAs during chicken muscle development, we analyzed the expression patterns of all differential miRNAs and lncRNAs throughout the differentiation stages of CPMs by trend analysis. The clustering results of differentially expressed miRNAs showed 2 highly significantly enriched gene sets, profile0, and profile19, with a total of 567 differential miRNAs (Supplementary Fig. 7c). The clustering results of DElncRNAs showed 4 highly significantly enriched gene sets, profile0, profile19 with a total of 368 differential lncRNAs (Supplementary Fig. 7f).

Subsequently, we constructed the lncRNA‒miRNA‒mRNA interaction network based on the expression profiles. The interactions among lncRNAs, miRNAs, and mRNAs may control how CPMs develop. To reduce the number of possible key genes affecting the development of CPMs, we focused on the 196 key DEmRNAs described above. A total of 41 differentially expressed genes which were enriched in KEGG iterms cell growth and death, replication and repair, nucleotide metabolism and amino acid metabolism pathways were selected. Only 21 genes were included in a ceRNA network with related differential lncRNAs and miRNAs. We used Cytoscape (version 3.6.0) to construct a lncRNA‒miRNA-mRNA coexpression visualization network (Fig. 1h). Interestingly, we found that ChaC glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) had the largest number of ceRNAs network, which indicated that this gene may play an important role in skeletal muscle development. There were 33 miRNAs and 24 lncRNAs in this ceRNA network produced by CHAC1. Among them, lncRNA-MSTRG5399.1 had a high expression level and was significantly correlaed to CHAC1 (r = 0.943, P = 0.927), named lncMDP1 (myoblast proliferation and differentiation 1). miR-301a-5p had a significantly negative correlation with the expression of lncMDP1 (P = -0.746). Moreover, the results of the quantitative real-time polymerase chain reaction (qPCR) assay verified the corrlelation of expression among lncMDP1, miR-301a-5p, and CHAC1 in RNA-seq (Supplementary Fig. 8).

LncMDP1 promotes myoblast proliferation and differentiation

We first detected the subcellular distribution of lncMDP1 by RNA fluorescence in situ hybridization (RNA-FISH) and qPCR. The results showed that lncMDP1 was mostly located in the cytoplasm (Fig. 2a, b). From the temporal expression profile of the leg muscles of AA broilers, it was found that lncMDP1 was continuously highly expressed during the embryonic period, and its expression level decreased sharply 1 day after hatching. On 1st day, lncMDP1 was relatively high in the spleen, muscular stomach, and glandular stomach, followed by the leg and breast muscles (Fig. 2c and Supplementary Fig. 9). After interfering with lncMDP1, the expression levels of myoblast proliferation-promoting (CDK1, PCNA, CCND1, CCNB2) and proliferation-inhibiting marker genes (P21) showed opposite trends (Fig. 2d) and interfering with lncMDP1 significantly promoted CDK1 (P < 0.001) protein expression (Fig. 2e and Supplementary Fig. 10a, unedited original blots in Supplementary Fig. 19, Supplementary Fig. 25). LncMDP1 interference results in a significant reduction of cells entering S phase (P < 0.05) in the cell cycle (Fig. 2f and Supplementary Fig. 11a). Cell counting kit-8 (CCK-8) and 5-Ethy nyl-2′-deoxyuridine (EdU) staining also showed that proliferation was significantly (P < 0.05) inhibited upon interference compared to control cells (Fig. 2g, h). According to qPCR analysis, interference with lncMDP1 significantly (P < 0.01) inhibited myoblast differentiation, presented down-regulated expression of differentiation marker genes (MyHC, MyoD, MyoG, and Myomarker) (Fig. 2i), and significantly (P < 0.01) inhibited protein expression of MyHC (Fig. 2j and Supplementary Fig. 10b, unedited original blots in Supplementary Fig. 20, Supplementary Fig. 26) compared with control cells. By immunofluorescence staining, we found that interference with lncMDP1 significantly (P < 0.01) reduced total myotube area and inhibited myoblast differentiation (Fig. 2k). In conclusion, the data suggest that lncMDP1 promoted myoblast development.

**Fig. 2: *LncMDP1* promotes the proliferation and differentiation of myoblasts.**

LncMDP1 might function as a sponge for miR-301a-5p

We first examined the biological expression characteristics of miR-301a-5p in chickens. The temporal expression profile of miR-301a-5p in leg muscles showeds a gradual increase. Its expression after birth was significantly higher than the embryonic period. Moreover, we also found that miR-301a-5p was significantly negatively correlated with lncMDP1 expression in the leg muscles of AA broilers (Fig. 3a, b, and Supplementary Fig. 12). Subsequently, we predicted the binding site of lncMDP1 to miR-301a-5p by bioinformatics analysis (Supplementary Fig. 13a). Their relationship was validation by dual luciferase reporter gene analysis and qPCR showed that lncMDP1 and miR-301a-5p could interact directly, and miR-301a-5p could influence the mRNA expression of lncMDP1 (Fig. 3c, d). To further observe the effect of miR-301a-5p on the proliferation and differentiation of myoblasts, we transfected myoblasts with miRNA mimics or negative control miRNA (miR-NC). It was found that the change of expression of marker genes were reversed (Fig. 3e, f). Also, miR-301a-5p significantly (P < 0.05) decreased the protein expression level of CDK1 (Fig. 3g and Supplementary Fig. 14a, unedited original blots in Supplementary Fig. 21, Supplementary Fig. 28). Cell proliferation were then measured by flow cytometry analysis, the CCK-8 assay, and EdU staining. The CCK-8 and EdU results showed that transfection with miR-301a-5p mimic significantly (P < 0.05) decreased myoblast proliferation compared with transfection with miR-NC (Fig. 3h, j), and the results of treatment with miR-301a-5p inhibitors were opposite (Fig. 3i, j). Flow cytometry analysis of the cell cycle showed that myoblasts transfected with a miR-301a-5p mimic were arrested in S phase (Fig. 3k and Supplementary Fig. 11b), and the opposite result was observed after transfection with a miR-301a-5p inhibitor (Fig. 3l and Supplementary Fig. 11c). After immunofluorescence staining, we found that miR-301a-5p overexpression inhibited myoblast differentiation and significantly reduced the total myotubes area, whereas the opposite result was obtained after the interference of miR-301a-5p (Fig. 3m). The expression of myoblast differentiation marker genes (MyoD, MyHC, MyoG) was downregulated after transfection with miR-301a-5p mimics (Fig. 3n), and the protein expression level of MyHC was significantly (P < 0.05) reduced (Fig. 3p and Supplementary Fig. 14b, unedited original blots in Supplementary Fig. 21, Supplementary Fig. 29); the results were reversed with the treatment of miR-301a-5p interference (Fig. 3o, p and Supplementary Fig. 14b, unedited original blots in Supplementary Fig. 21, Supplementary Fig. 29). In a conclusion, the data suggested that lncMDP1 act as a sponge for miR-301a-5p, and miR-301a-5p inhibits the proliferation and differentiation of myoblasts.

LncMDP1 regulateed myoblast proliferation and differentiation through the miR-301a-5p/CHAC1 axis

The temporal expression profile of CHAC1 in the leg muscles showed a downward trend with the embryonic anddevelopment and was significantly negatively correlated with the expression of miR-301a-5p, while it showed a decreasing and then increasing trend after incubation (Fig. 4a, b). Expression was high in the leg and breast muscles in 1-day-old tissues (Supplementary Fig. 15). It supposed that CHAC1 was involved in both chicken embryonic and postnatal muscle development. We predicted the binding site of CHAC1 to miR-301a-5p by bioinformatics analysis (Supplementary Fig. 13b). To further validate the interaction relationship between lncMDP1/miR-30a-5p/CHAC1, we examined it by RNA-FISH and the results showed that lncMDP1 and CHAC1 were co-localized in intracellular (Fig. 4c). Meanwhile, dual luciferase reporter gene analysis and qPCR showed that CHAC1 and miR-301a-5p could interact directly, and miR-301a-5p could influence the mRNA expression of CHAC1 (Fig. 4d, e). After CHAC1 overexpression or interference in myoblasts, we found that the expression levels of pro-proliferation (CDK1, PCNA, CCND1, CCNB1, CCNB2) and anti-proliferation marker genes (P21, CDKN1A) showed the opposite trend (Fig. 4f, g). In addition, the protein expression level of CDK1 and CHAC1 presented a significant (P < 0.05) upregulation after CHAC1 overexpression. However, an opposite result was obtained after interference of CHAC1 (Fig. 4h and Supplementary Fig. 16a, unedited original blots in Supplementary Fig. 22, Supplementary Fig. 30, Supplementary Fig. 31). Overexpression of CHAC1 significantly (P < 0.001) increased the number of cells in S phase (Fig. 4i and Supplementary Fig. 11d), whereas the number of cells in S phase significantly (P < 0.05) reduced after CHAC1 interference (Fig. 4j and Supplementary Fig. 11e). The flow cytometry and CCK8 results showed that CHAC1 overexpression significantly (P < 0.01) promoted myoblast proliferation (Fig. 4k) and that the interference of CHAC1 inhibited myoblast proliferation (Fig. 4l). EdU staining results showed that overexpression of CHAC1 significantly (P < 0.001) promoted cell increase compared with the control group. Conversely, interference with CHAC1 significantly inhibited myoblast proliferation (Fig. 4m). By immunofluorescence staining, we found that overexpression of CHAC1 significantly (P < 0.05) increased the total myotube area and promoted myoblast differentiation, whereas CHAC1 interference decreased myoblast differentiation (Fig. 4n). Compared with controls, CHAC1 overexpression significantly promoted myoblast differentiation, significantly (P < 0.05) up-regulated the expression of differentiation-associated marker genes (MyHC, MyoD, MyoG, and Myomarker), and up-regulated the protein expression of MyHC, while the interference of CHAC1 downregulated their expression (Fig. 4o–q and Supplementary Fig. 16b, unedited original blots in Supplementary Fig. 22, Supplementary Fig. 32). In summary, the results of CHAC1 and lncMDP1 interference were consistent. Combined with the analysis of miR-301a-5p, it was concluded that lncMDP1 acted as a molecular sponge to adsorb miR-301a-5p affecting the proliferation and differentiation of myoblasts to regulate CHAC1.

**Fig. 4: *LncMDP1* regulates *CHAC1* expression through the adsorption of miR-301a-5p.**

CHAC1 promotes skeletal muscle regeneration

To further investigate the biological function of CHAC1 in the regeneration of skeletal muscle, firstly, we injected BaCl₂ into the gastrocnemius (GAS) muscle of AA broilers to cause muscle damage after injection of the adeno virus CHAC1-3xFLAG. Subsequently, we performed H&E staining on GAS muscles at four different time points. It was found that with the time change, the diameter of muscle fibers and the cross-sectional area (CSA) of muscle fibers in the GAS overexpressing CHAC1 gradually increased compared to the control group. By 7th day, the inflammatory cells in the GAS overexpressing CHAC1 were reduced and gradually replaced by newly formed muscle fibers, and the muscle fiber structure became intact and clear (Fig. 5a–c). Meanwhile, qPCR and western blotting results showed that CHAC1 expression was significantly upregulated during muscle injury compared to controls and peaked at 3rd day (Fig. 5d, h, and Supplementary Fig. 17, unedited original blots in Supplementary Fig. 23, Supplementary Fig. 33). In addition, we also examined marker genes associated with promoting muscle regeneration and showed that GAS muscle after overexpression of CHAC1 was significantly upregulated compared to controls in terms of expression of adult MyHC (aMyHC), embryonic MyHC (eMyHC) and Desmin (Fig. 5e–h and Supplementary Fig. 17, unedited original blots in Supplementary Fig. 23, Supplementary Fig. 34). Taken together, CHAC1significantly promote muscle regeneration.

LncMDP1 acts as a miR-301a-5p sponge to attenuate its inhibitory of CHAC1

To further determine that lncMDP1 attenuates its inhibitory effect on CHAC1 by adsorption of miR-301a-5p, we performed a functional rescue experiment. The results of qPCR and western blotting showed that the expression of CHAC1 was significantly decreased by transfection with si-lncMDP1 and miR-301a-5p mimic compared to si-NC and mimic NC (P < 0.05). The expression of pro-proliferative (CDK1, PCNA, CCND1, and CCNB1) and pro-differentiation (MyHC, MyoG, and Myomaker) marker genes were also significantly (P < 0.05) decreased while the expression of the proliferation inhibitory marker gene P21 was significantly (P < 0.05) increased, indicating that interference with lncMDP1 enhanced the inhibitory effect of miR-301a-5p on CHAC1 (Fig. 6a–d and Supplementary Fig. 18a, unedited original blots in Supplementary Fig. 24, Supplementary Fig. 35–37), consistent with the above results after interference with CHAC1. Meanwhile,cotransfection of lncMDP1 rescued the inhibitory effect of miR-301a-5p on CHAC1 and then restored the role of CHAC1 on proliferation and differentiation of CPMs (Fig. 6e–h and Supplementary Fig. 18b, unedited original blots in Supplementary Fig. 25, Supplementary Fig. 38–40). In summary, these results suggested that lncMDP1 acted as a sponge for miR-301a-5p and attenuate the inhibitory effect of miR-301a-5p CHAC1, thereby promoting the proliferation and differentiation of CPMs.

Discussion

Sequencing technology has long played an important role in various studies of biology, providing many new insights that will help us understand complex biological systems¹⁸. Transcriptomics can be used to explore the interaction between mRNA and non-coding RNA¹⁹. Studies have shown that in mammals there are less than 2% of the genome-encoding proteins²⁰. Researchers have found that not only a large number of mRNAs are the main regulators in the growth and development of skeletal muscle, but also many ncRNAs play an important synergistic regulatory role²¹. However, there are few studies on ncRNA in skeletal muscle development. In our study, to find the key factors affecting the growth and development of skeletal muscle in chickens, whole transcriptome sequencing was performed on seven stages (G1, G2, D1, D2, D3, D4, D6, D8) of proliferation and differentiation of CPMs. A total of 21 cDNA libraries were obtained to understand the dynamic expression profiles of mRNA, miRNA, and lncRNA during myoblast development. A total of 6,937 DEmRNAs, 890 DEmiRNAs, and 942 DElncRNAs related to myoblast proliferation and differentiation were identified.

In this study, we identified a total of 196 DEmRNAs by comparing differentially expressed genes in the proliferative and differentiation periods. GO and KEGG enrichment analysis indicated that these DEmRNAs weresignificantly enriched in the cell cycle, p53 signaling pathway, DNA replication, and pathways related to amino acid metabolism, and so on. It has been shown that all these pathways play an important role in regulating skeletal muscle development^22,23,24,25. For example, the proliferation and differentiation of myoblasts are closely related to the cell cycle, and muscle-specific transcription is activated when myoblasts are blocked from entering the S phase, causing them to stagnate in G0/G1 phase^26,27. miR-16-5p can directly target SESN1 to regulate the p53 signaling pathway to inhibit myoblasts proliferation and differentiation, and promote apoptosis²⁸. It has been shown that CDK1 plays an important role in myoblasts proliferation, myofiber hypertrophy, and muscle regeneration^29,30. PCNA can regulate the cell cycle and thus the proliferation of skeletal muscle myoblasts³¹. Therefore, the differentially expressed genes that we found to be enriched in these signaling pathways are likely to be involved in muscle growth and development.

In recent years, large amounts of research data have demonstrated that some lncRNAs play an important role in the myogenesis and hypertrophy of skeletal muscle by affecting the proliferation and differentiation of myoblasts^32,33,34. In our study, a total of 942 lncRNAs were identified that were differentially expressed during the growth and development of CPMs. LncMDP1 was significantly upregulated during CPMs differentiation, suggesting that it may influenc skeletal muscle growth and development. Through our studies in vitro, it was shown that lncMDP1 significantly inhibited myoblast proliferation and differentiation after it was disturbed. Additionally, this lncRNA was highly expressed in the leg muscles of AA broilers at the embryonic stage, and its expression gradually decreased after birth.

Currently, studies, the ceRNA network was identified to be a key regulatorymechanisms throughout the development of organisms, including cancer treatment, cell proliferation, differentiation, and growth and development^35,36,37. For example, lncRNA-Six1 can act as a molecular sponge for miR-1611, thereby participating in the regulation of Six1 expression and regulating skeletal muscle development³⁸. Lnc-mg promotes myogenesis and acts as a ceRNA competitively binding miR-125b thereby regulating IGF2 expression³⁹. LncRNA MEG3 regulates the expression of ABCA1 through the adsorption of miR-361-5p, thereby regulating smooth muscle cell development⁴⁰. A key ceRNA network of lncRNAs‒miRNAs‒mRNAs that may be involved in the growth and development of CPMs was constructed in our study, and CHAC1 was the core gene in this network, which is significantly enriched in glutathione metabolic pathway. It has been shown that CHAC1 may be involved in the regulation of muscle growth and development in zebrafish⁴¹. Within this network, based on sequencing data and real-time fluorescence quantification, miR-301a-5p and lncMDP1 and CHAC1 showed opposite expression patterns in the CPMs induction differentiation model, while miR-301a-5p was negatively correlated with lncMDP1 and CHAC1 expression in AA chicken leg muscle, suggesting that they may be involved through interacting in the developmental regulation of myoblast relationships. In this study, we confirmed the presence of miR-301a-5p binding sites to lncMDP1, and CHAC1 targets by qPCR and dual luciferase reporter gene assay. Results from in vitro experiments showed that CHAC1 and lncMDP1 could promote the proliferation and differentiation of myoblasts, in contrast to the biological function of miR-301a-5p. Furthermore, we found that CHAC1 could promote muscle regeneration by inducing muscle damage in chickens. Finally, it was further confirmed by rescue assays that lncMDP1 regulates the expression of CHAC1 by adsorbing miR-301a-5p. Our results suggested that lncMDP1, as a miR-301a-5p sponge, has a timulative effect on CHAC1, which in turn promotes the proliferation, differentiation, and muscle regeneration of CPMs.

In a conclusion, we systematically constructed a panorama of proliferation and differentiation of CPMs (mRNA, miRNA, lncRNA) by whole transcriptome sequencing analysis of a total of 21 samples from 7 different growth and developmental stages of CPMs. And a lncRNA named lncMDP1 was identified, which was consistently upregulated during myoblasts differentiation and could act as a ceRNA that regulates CHAC1 by competitively binding miR-301a-5p, thereby promoting myoblast proliferation, differentiation, and muscle regeneration. Our findings further enrich the understanding of the regulatory network and molecular mechanism of chicken skeletal muscle and provide a theoretical basis and new ideas for improving chicken meat performance and quality in the future.

Methods

Cell culture

CPMs were isolated from the leg muscles of 11-day-old chicken embryos (Henan Yue Poultry Agriculture and Animal Husbandry Group Co., Ltd, Jiaozuo, China)⁴². After the skin was removed, the leg muscles were placed in a Petri dish containing high-sugar DMEM (HyClone, Logan, UT) supplemented with 15% FBS (BI, Kibbutz BeitHaemek, Israel) and 0.2% penicillin/streptomycin (Solarbio, Beijing, China), and the bones were removed with forceps. The hamstring tissues were cut into 1.5 mL centrifuge tubes and subsequently transferred to a 50 mL centrifuge tube. The suspension was vortexed 30-40 times and then passed through a 70 mm sieve to obtain a single cell suspension. This procedure was repeated 3 times, each time adding the appropriate amount of prepared complete high-sugar DMEM to obtain additional cells. Cell pellets were collected by centrifugation at room temperature and the liquid was discarded. The cells were resuspended in complete high-sugar DMEM and placed in cell culture flasks. Finally, sequential differential replating was performed three times to remove fibroblasts, and the final obtained CPMs were cultured in a humidified environment at 37 °C in a 5% CO₂ incubator. Cell samples were collected daily, depending on the degree of cell fusion observed (50% or 100%), and during days 1, 2, 4, 6, and 8 of CPMs differentiation (induction of myoblast differentiation with 2% horse serum medium). Three biological replicates were collected at each time point for whole transcriptome sequencing.

The mRNA, lncRNA, and miRNA sequencing analysis

The quality of RNA obtained from CPMs was checked with RNase-free agarose gel electrophoresis as assessed using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, USA). Reads were then filtered with fastp (version 1.18.0) to get high quality and clean reads. Mapping reads to the rRNA database was performed using Bowtie2 (version 2.2.8). The coding capability of novel transcripts was anticipated by two softwares, CPC and CNCI. Differential expression of mRNA and lncRNA between two different groups was analyzed with DESeq2 software, and differential expression analysis of mRNA and lncRNA between two samples was determined with edgeR⁴³. We judged mRNA and lncRNA to be different separately subject to the conditions of false discovery rate (FDR) < 0.05 and absolute (FC) ≥ 2 DEmiRNAs analysis between groups and samples were performed in the same way as above, and DEmiRNAs were identified with a fold change (FC) ≥ 2 and P value < 0.05. Their target genes were analyzed and predicted using both Miranda (version 3.3a) and TargetScan (version 7.0) software⁴⁴.

GO and KEGG pathway enrichment analysis

DEmRNAs were subjected to GO analysis through the Gene Ontology database⁴⁵, and their enrichment pathway analysis was performed using KEGG pathway analysis⁴⁶.

WGCNA

WGCNA can be used to analyze and characterize patterns of correlation between genes in large sample sizes. It can also identify highly correlated gene modules and correlate modules with sample expression patterns for analysis. The intramodal connectivity (K.in) and modular correlation (MM) were calculated for all genes using the R package of WGCNA, and hub genes tend to be characterized by high connectivity and may play an important role. The visualization of the network was implemented using Cytoscape_3.3.0⁴⁷.

Trend analysis

The expression patterns of genes across multiple samples were analyzed using gene expression pattern analysis, We used Short Time-series Expression Miner software (STEM, version 1.3.13) for clustering analysis to identify the expression patterns of differential genes⁴⁸. We considered clustering profiles with p-values ≤ 0.05 as significant profiles.

Construction of lncRNA-miRNA-mRNA interaction network

Previous research has demonstrated that mRNAs and noncoding RNAs with one or more common miRNA response elements (MREs) can competitively bind to miRNAs and regulate one another as ceRNAs⁴⁹. To ascertain the correlations between miRNA‒mRNA or miRNA‒lncRNA, interaction networks could be used to predict the probable roles of the expressed genes. Before analyzing the positive correlation relationship between the expression levels of potential ceRNAs, the targeting relationship between miRNAs and candidate ceRNAs (lncRNA, mRNA) and the negative correlation relationship between expression levels were examined. Finally, we performed the construction of ceRNA regulatory networks using the obtained candidate ceRNAs as well as their shared miRNA pairs (i.e., lncRNA‒miRNA-mRNA relationship pair). Visualization networks were plotted using Cytoscape software (v3.6.0). (http://www.cytoscape.org/).

RNA extraction, cDNA synthesis, and qPCR

Total RNA in AA broiler tissues and CPMs was extracted using TRIzol reagent (Takara, Tokyo, Japan). The amount of RNA was measured with a spectrophotometer (Thermo, Waltham, USA). Using the PrimeScript RT kit and gDNA eraser, synthesized cDNA was reverse transcribed (Takara, Tokyo, Japan). The ReverTra Ace qPCR RT kit was used to reverse-transcribe miRNA (Takara, Tokyo, Japan). qPCR was performed using SYBR Green master mix (Takara, Tokyo, Japan) and LightCycler 96 qPCR system (Roche, Basel, Switzerland) for experiments. mRNA and miRNA internal reference genes were GAPDH and U6. All experiments were performed in triplicate. The relative quantification of genes was performed using the 2^-ΔΔCt method⁵⁰. Specific primers, mimics, and inhibitors dedicated to BmLge-Loop miRNA qPCR were designed by RiboBio (RiboBio, Guangzhou, China). The primer sequences are listed in Supplementary Tab. 2.

Plasmid construction and dual‑luciferase reporter assay

The full-length coding sequence (CDS, NM_001199656.2) of ChaC glutathione-specific gamma-glutamylcyclotransferase 1 (CHAC1) and partial sequences of lncMDP1 were amplified from chicken leg muscle cDNA to construct an overexpression vector, which was ligated to the pcDNA3.1-3xFLAG vector (Promega, Madison, USA) via two restriction enzyme sites, EcoR I and Xho I. We used the Bibiserv2 website to predict the binding site sequences between miR-301a-3p and CHAC1 and lncMDP1 (https://bibiserv.cebitec.uni-bielefeld.de/genefisher2/), which in turn led to the construction of the psiCHECKTM-2 dual luciferase reporter vector (Promega, Wisconsin, USA)⁵¹. The wild-type sequences of CHAC1 3’UTR and lncMDP1 amplified from AA broiler leg muscle cDNA were ligated to the psiCHECK TM-2 vector using Xho I and Not I restriction enzyme sites. We changed the binding site of miR-301a-5p from TTGTCAG to GGTCTCT to generate mutant sequences of CHAC1 3’UTR and lncMDP1. CHAC1-WT or CHAC1-MT reporter plasmids and lncMDP1-WT or lncMDP1-MT reporter plasmids, combined with NC mimics or miR-301a-5p mimics were cotransfected into DF-1 cells (American Type Culture Collection, Virginia, USA) to study the miR-301a-5p binding of CHAC1 3’UTR and lncMDP1 sites⁵². Then, 36 h post-transfection, the cells were treated according to the manufacturer’s instructions, and firefly and renilla luciferase activities were assayed using a dual luciferase reporter system (Promega, Wisconsin, USA).

Flow cytometry, CCK-8, and EdU assays

CCK-8 analysis: Cell viability was determined using a CCK-8 kit (Vazyme, Nanjing, China). CPMs cultured in 96-well plates were assayed for cell viability at 450 nm every 12 h for two days using a fluorescence multimode digest (BD BioTek, Winooski, USA). The cell plates were incubated at 37 °C in a 5% CO₂ incubator after adding 10 μL of CCK-8 solution to each well 2 h before the assay according to the manufacturer’s instructions.

EdU assay: We transfected CPMs inoculated in 24-well plates and fixed the cells after 36 h. The cells were incubated for 2 h with the Cell-Light EdU Apollo 567 in vitro kit (RiboBio, Guangzhou, China) according to the manufacturer’s instructions⁵³. The images were acquired using a fluorescent microscope (Olympus, Tokyo, Japan). All experiments were repeated three times.

Flow cytometry: We performed transfection of CPMs inoculated in 6-well plates confluent to 70% (pcDNA3.1-3xFLAG) and 40% (siRNA), respectively. Cells were observed to fuse to 90–100% when cells were processed, first washed with PBS, digested with trypsin, and terminated with complete medium to obtain cell precipitates and then resuspended with 70% ethanol and subsequently placed at -4 °C to fix the cells. Cell cycle analysis we were performed using a BD Accuri C6 flow cytometer (BD Biosciences, California, USA).

Immunofluorescence

We performed MyHC immunofluorescence detection for CPMs inoculated in 12-well plates by co-incubation with anti-MyHC antibody (DHSB, USA; B103) and anti-mouse Cy3-coupled antibody (Proteintech, Wuhan, China), and nuclear staining was performed using DAPI (Solarbio, Beijing, China). Images were still acquired using a fluorescence microscope (Olympus, Tokyo, Japan).

RNA-FISH

CPMs were inoculated in 6-well plates, slides were placed in the cell culture plates in advance, and cells were fixed using in situ hybridization fixative when they reached 80–90% confluence. After the cells were then permeabilized with 0.1% Triton X-100, the cells were incubated with lncMDP1 and CHAC1 probes (Servicebio, Wuhan, China) respectively at 37 °C for 12 h. The nuclei were stained using DAPI and observed and photographed by laser confocal microscopy (Nikon, Tokyo, Japan).

Western blotting assay

We lysed the CPMs inoculated in 6-well plates in lysis buffer (EpiZyme, Shanghai, China). Cellular protein concentration was determined by the BCA protein assay kit method (A53225, Thermo, Waltham, USA). Protein denaturation was subsequently performed by using 5 × loading buffer at 100 °C for 10 min after protein denaturation, and the denatured samples could be directly used for protein blotting analysis. We first separated the total cellular proteins using 12% SDS-PAGE and then transferred them to PVDF membranes (Millipore, MA, USA), followed by sealing the membranes with 5% skim milk in Tris-buffered saline containing 0.5% Tween-20 for 1 h on a decolorization shaker, followed by the use of anti-MYHC (1:400, B103; DHSB, Iowa City, USA), anti-CDK1 (1:1000, 19532-1-AP, Proteintech, Wuhan, China), anti-CHAC1 (1:1000, 15207-1-AP; Proteintech, Wuhan, China), anti-Desmin (1:5000, 16520-1-AP; Proteintech, Wuhan, China), and anti-GAPDH (1:10000, 60004-1-Ig; Proteintech, Wuhan, China) were incubated overnight at 4 °C, and the next day secondary antibodies coupled with HRP (1:2000, SA00001-1; Proteintech, Wuhan, China) were placed at room temperature for 1 h. Finally, the membranes were incubated by Images obtained by Odyssey FC (LI-COR, Nebraska, USA) and the signal was enhanced using ECL solution (EpiZyme, Shanghai, China) before taking pictures. GAPDH was used to normalize protein expression⁵². Each experiment is guaranteed to have three biological replicates. The grayscale values of each band were calculated using ImageJ software (NIH, Bethesda, USA). In this study, western blot was performed on different membranes for proteins with a molecular weight difference of fewer than 5 kDa (similar protein size, difficult to distinguish), and the sample size was consistent under the premise of detecting protein concentration. In this case, the sample and the loading control ran on different gels and thus transferred to different membranes. In addition, for proteins with a molecular weight difference greater than 5 kDa (similar protein size, difficult to distinguish), the loading amount and the loading control ran on the same gel, transferring to different membranes.

Skeletal muscle injury and regeneration

Muscle injury was induced by injecting 50 μL of 50 mM BaCl₂ in saline into the GAS muscle of 3-week-old AA males⁵⁴. After the injury, 6 × 10⁶ plaque-forming unit (PFU) of pAV-CHAC1-3xFLAG and pAV-3xFLAG as control adenovirus were injected into the GAS muscle, and the GAS muscle was collected on days 1, 3, 5, and 7 of adenovirus injection for subsequent muscle regeneration assays. Our method of euthanasia for chickens is cervical dislocation.

Statistics and reproducibility

All data in this study were statistically analyzed using SPSS software (SPSS for Windows, standard version 24.0; SPSS, New York, USA). Whether the values were statistically significantly different between the different two groups (*P < 0.05; **P < 0.01, ***P < 0.001) was statistically analyzed by using the t test, all experiments included at least three biological replicates, and the data were expressed as mean ± S.E.M. The source data behind the graphs in the figure were in supplementary data 1. The statistical results of relevant data in the article were in supplementary data 2.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Data availability

All study data results are available from the text. Whole transcriptome sequencing results have been uploaded to the NCBI Database Sequence Read Archive under the login numbers PRJNA909444 and PRJNA908949. All other data are available from the corresponding author on reasonable request. The source data and the statistical data can be found in the Supplementary Data 1 and 2.

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (32372873), the Program for Science & Technology Innovation Talents in Universities of Henan Province (22HASTIT038) and the Zhongyuan Youth Talent Support Program (ZYYCYU202012156).

Author information

These authors contributed equally: Bingjie Chen, Hanfang Cai.

Authors and Affiliations

College of Animal Science and Technology, Henan Agricultural University, Zhengzhou, 450046, China
Bingjie Chen, Hanfang Cai, Yufang Niu, Yushi Zhang, Yanxing Wang, Yang Liu, Ruili Han, Xiaojun Liu, Xiangtao Kang & Zhuanjian Li
Henan Key Laboratory for Innovation and Utilization of Chicken Germplasm Resources, Zhengzhou, 450046, China
Ruili Han, Xiaojun Liu, Xiangtao Kang & Zhuanjian Li

Authors

Bingjie Chen
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Hanfang Cai
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Yufang Niu
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Yushi Zhang
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Yanxing Wang
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Yang Liu
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Ruili Han
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Xiaojun Liu
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Contributions

B.C. and H.C. analysis of data, complete validation work, and completion of the first draft of the written article. Y.N. and Y.Z. assist in the validation process. Y.W. and Y.L. visualization of data. R.H. and X.L. collation of study data and refining research methods. X.K. and Z.L. overall conceptualization of this study and further revision of the article. The author(s) read and approved the final manuscript.

Corresponding authors

Correspondence to Xiangtao Kang or Zhuanjian Li.

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In this study, animal care was performed by the Regulations for the Management of Animal Experiments (Ministry of Science and Technology, China, 2004) approved by the Animal Care and Use Committee (IACUC) of Henan Agricultural University (approval number: 11-0085), China, and animals were used only after written informed consent was obtained from Henan Agricultural University. We conducted this study in strict accordance with the ARRIVE guidelines. We have complied with all relevant ethical regulations for animal use.

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Chen, B., Cai, H., Niu, Y. et al. Whole transcriptome profiling reveals a lncMDP1 that regulates myogenesis by adsorbing miR-301a-5p targeting CHAC1. Commun Biol 7, 518 (2024). https://doi.org/10.1038/s42003-024-06226-1

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Received: 11 September 2023
Accepted: 22 April 2024
Published: 02 May 2024
DOI: https://doi.org/10.1038/s42003-024-06226-1

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