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Circular RNAs (circRNAs) are key gene regulators that are involved in many fundamental biological processes. Skeletal muscle cannot develop normally without the involvement of circRNA. We found that a circRNA from the ATP Citrate Lyase (ACLY) gene regulates skeletal muscle development through sponging miRNA. The results of ribonuclease R (RNase R) digestion and subcellular localization assays verified that circACLY is a circRNA that is mainly localized to the cytoplasm. Dual-luciferase and co-transfection assay findings showed that gga-miR-6660-3p binds directly to the predicted binding sites of circACLY and Ectonucleotide Triphosphate Diphosphohydrolase 7 (ENTPD7). Furthermore, circACLY increased the expression of ENTPD7 by adsorbing gga-miR-6660-3p. Cell proliferation assays showed that circACLY promoted, whereas gga-miR-6660-3p inhibited myoblast proliferation. Assays of induced differentiation, differentiation marker gene mRNA expression and protein levels showed that gga-miR-6660-3p inhibited, whereas circACLY facilitated myoblast differentiation. Furthermore, circACLY inhibited, whereas gga-miR-6660-3P promoted myoblast apoptosis, and they regulate inosine monophosphate synthesis (IMDNS) de novo by respectively promoting and inhibiting it. Our findings confirmed that circACLY from the ACLY gene regulates IMDNS by sponging- gga-miR-6660-3P to promote myoblast proliferation and differentiation and inhibit myoblast apoptosis.

Background: Long noncoding RNAs (lncRNAs) play an important regulatory role in various biological processes as a key regulatory factor. However, there are largely unknown for the function and expression profile of lncRNAs in milk fat synthesis of dairy cows. Results: In this study, RNA sequencing (RNA-seq) was used to research the whole genome expression of lncRNAs and mRNA transcripts in bovine mammary epithelial cells (BMECs) of dairy cows with high and low milk fat percentage (MFP), and joint analysis was carried out. We identified a total of 47 differentially expressed genes (DEGs) and 38 differentially expressed lncRNAs (DELs, Padj < 0.05), 11 candidate DEGs that may regulate milk fat metabolism were screened by enrichment analysis. Downregulated differential gene ENPP2 and upregulated differential gene BCAT1 are more likely to participate in the milk fat metabolism, and its function needs further experiments verification. The enrichment analysis of target genes predicted by DELs identified 7 cis (co-localization) and 10 trans (co-expression) candidate target genes related to milk lipid metabolism, corresponding to a total of 18 DELs. Among them, the targeting relationship between long intervening/intergenic noncoding RNA (lincRNA) TCONS_00082721 and FABP4 gene that predicts milk fat metabolism by co-localization and co-expression is worthy of attention. Based on the expression information of DELs, differential microRNAs (miRNAs), and lipid metabolism-related target genes, 156 competing endogenous RNAs (ceRNAs) interaction regulation networks related to milk fat metabolism were constructed. The regulatory network centered on miR-145 will be the focus of subsequent experimental research. The ceRNAs regulatory network related to TCONS_00082721 and TCONS_00172817 are more likely to be involved in milk fat synthesis. Conclusions: These results will provide new ways to understand the complex biology of dairy cow milk fat synthesis and provide valuable information for the breed improvement of Chinese Holstein cattle.

Background: Improving broiler production efficiency and delivering good quality chicken has become an exciting area of research. Many factors affect the quality of chicken, and the IMF content is one of the critical factors determining the quality of chicken. At present, there are many reports on the molecular mechanism of IMF-specific deposition in chicken; however, only a few reports discuss the specific deposition of IMF in different parts of a chicken.Methods: In order to analyze the molecular mechanism of IMF specific deposition in different parts of chickens, the present study has selected 180-days old Jingyuan chicken breast and leg muscles as the research materials, using proteomics technology and screening of PRM protein quantitative detection methods, identification and quantitative verification of proteins that control the IMF-specific deposition in the leg muscles and breast muscles of Jingyuan chickens. The protein was analyzed by advanced bioinformatics using GO, KEGG, R language, Gallus_gallus_UniPort, and other biological software, including tools and related databases for screening and identification.Results: By screening and identifying LC-MS/MS mass spectrometry data and comparing it with the Gallus_gallus_UniPort database, a total of 1940.0 proteins were screened and identified, of which 1317.0 proteins were quantified. Compared with the breast muscles, there are 190 differentially expressed proteins between leg and breast muscles. In the leg muscles, 121 proteins are up-regulated, whereas 69 are down-regulated. Gene Ontology (GO) function annotation and enrichment analysis were done for 190 differential proteins. These proteins participate in a biological process (BP), cellular component (CC), and molecular function (MF) pathways. However, a total of 286 signaling pathways involved 190 differential proteins using a KEGG pathway. Significantly different proteins between the leg and breast muscles were primarily enriched with gga00500Starchandsucrosemetabolism, gga00071 Fattyaciddegradation, gga01212Fattyacidmetabolism, gga03320PPAR signaling pathway. PRM was used to confirm and identify the differential proteins by screening quantitatively; 10 of them are related to fat deposition, namely E1BTT4, E1C0Q5 (ACAT1), F1NC38 (ACADL), Q5F420 (ACSL1), A0A1D5P3S9 (ECI1), Q5ZL56 (ACADS), F1NUQ3 (FABP3), A0A1D5PL36 (ACAA2), F1NR44 (ECHS1), Q5ZIR7 (FABP5) using STRING and Cytoscape software to analyze the network interactions of 10 differentially expressed proteins, resulting in 19 network interaction paths.Conclusion: We used modern omics technology, omics software, and related databases to screen and identify 3 key signal pathways, including 10 key functional proteins that control IMF-specific deposition in different parts of chickens. At the same time, the present results can be used for different parts of the chicken. Specifically, the molecular mechanism of IMF-specific deposition has been explained, and a key regulatory role is played by the network interaction analysis of proteins that control IMF-specific deposition in different parts of chickens. The results have a scientific value and theoretical significance for improving chicken quality and molecular breeding of high-quality local chicken breeds.