Screening and identification of the ncRNA-mRNA regulatory network associated with DNA methylation in goose embryonic myoblasts.

Abstract

BACKGROUND: Local goose breeds Shitou and Wuzong exhibit distinct growth rates, implying divergent embryonic muscle development. This study used embryonic myoblasts from the Magang goose, an established model with superior growth traits, to explore the underlying common regulatory mechanisms. Extending our previous findings that 5-AZA (DNA methylation inhibitor) and BC339 (DNA hydroxylation inhibitor) oppositely affect myoblast proliferation and differentiation, we performed whole-transcriptome sequencing on inhibitor-treated goose embryonic myoblasts. This aimed to identify DNA methylation-mediated ncRNA-mRNA networks governing myoblast fate, with key interactions being functionally validated. RESULT: 5-AZA significantly promotes cell proliferation and differentiation by inhibiting DNA methyltransferase activity and reducing DNA methylation levels, whereas BC339 significantly suppresses cell proliferation and differentiation by inhibiting demethylation and increasing DNA methylation levels. Specifically, we identified 6,309 mRNAs, 579 lncRNAs, 194 miRNAs, and 825 circRNAs that were differentially expressed in response to 5-AZA and BC339 treatment. Based on GO and KEGG enrichment analyses, differentially expressed genes related to muscle development were selected to construct a ceRNA network. This network comprises 5 differentially expressed lncRNAs (DELs: MSTRG.17572.1, XR_001211738.1, MSTRG.1886.1, XR_001212555.1, MSTRG.8995.2), 2 differentially expressed circRNAs (DECs: novel_circ_029953, novel_circ_017636), 11 differentially expressed miRNAs (DEMs: miR-383-x, miR-10174-y, miR-191-x, miR-24-x, miR-9619-y, novel-m0303-5p, novel-m0105-3p, miR-204-x, miR-211-z, novel-m0075, miR-26-y), 5 differentially expressed genes (DEGs: KIF3A, CCND1, PPM1A, Table 2, TGFBR1), forming a total of 24 interactions. This study identified miR-9619-y as a critical negative regulator of goose embryonic myoblast development through targeted inhibition of CCND1. Dual-luciferase reporter assays confirmed the direct binding of miR-9619-y to the 3'-untranslated region of CCND1. Functional experiments demonstrated that overexpression of miR-9619-y significantly reduced the EdU-positive cell ratio and myotube area percentage, accompanied by cell cycle arrest at the G0/G1 phase. Conversely, inhibition of miR-9619-y promoted myoblast proliferation and differentiation while decreasing the proportion of cells in G0/G1 phase. During the proliferation stage, miR-9619-y overexpression significantly suppressed CCND1 expression at both mRNA and protein levels, down-regulated MyoD expression, and reduced Myf5 mRNA abundance; whereas miR-9619-y inhibition up-regulated these genes and their corresponding proteins. During the differentiation stage, overexpression of miR-9619-y similarly decreased the mRNA levels of CCND1, Myh1, and MyoG, as well as the protein levels of MyHC and CCND1, with inhibition producing the opposite effects. CONCLUSION: In this study, we predicted a ceRNA network based on bioinformatics analysis governing goose embryonic myoblast development, identifying key molecular components including mRNAs, miRNAs, lncRNAs, and circRNAs, along with 24 regulatory axes. Functional experiments further demonstrated that miR-9619-y arrests cell cycle progression and negatively regulates the proliferation and differentiation of goose embryonic myoblasts, as evidenced by its impact on both the mRNA and protein expression of key myogenic factors through targeted inhibition of CCND1. These findings, together with the bioinformatically predicted ceRNA network, suggest potential complex post-transcriptional regulatory mechanisms underlying myogenesis in geese and offer candidate molecular targets for genetic improvement of meat production performance in waterfowl breeding programs.