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Skeletal muscle myogenesis is a crucial factor influencing meat production in livestock. MicroRNAs (miRNAs) play a significant role in skeletal muscle myogenesis. The objective of this study was to identify key miRNAs involved in the process of goat skeletal muscle satellite cell (MuSC) differentiation into myotubes. We performed miRNA expression profiling analysis during the proliferation phase (cultured in growth medium, GM) and the differentiation phase (cultured in differentiation medium for 1 day and 5 days, classified as DM1 and DM5, respectively) of goat skeletal muscle satellite cells (MuSCs). A total of 1846 miRNAs were identified in MuSC samples, of which 677 differentially expressed miRNAs (DEmiRNAs) were screened through pairwise comparisons across three groups (GM vs. DM1, GM vs. DM5, and DM1 vs. DM5), and the results were further confirmed by a quantitative real-time PCR assay. Time-series expression profiling facilitated the categorization of the DEmiRNAs into eight distinct clusters, one of which demonstrated a significantly downregulated expression pattern (p < 0.05). Functional enrichment analysis revealed that the target genes of DEmiRNAs are involved in several pathways that are critical for myogenesis, including Hippo, TGF-β, MAPK and cell adhesion molecules. Interaction network analysis identified 19 miRNAs and 56 mRNAs associated with muscle cell development. Notably, novel-m0047-5p emerged as a key regulator, exhibiting strong negative correlations (r = -0.88 to -0.89, q < 0.01) with muscle-related target genes FOSB, CPT1B, and MYOZ2. These findings elucidate miRNA-mediated regulatory networks in goat myogenesis and provide candidate molecular targets for genetic improvement of meat production traits.
Pubmed ID: 41892310
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Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.
View all literature mentionsSoftware ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
View all literature mentionsSoftware repository for R packages related to analysis and comprehension of high throughput genomic data. Uses separate set of commands for installation of packages. Software project based on R programming language that provides tools for analysis and comprehension of high throughput genomic data.
View all literature mentionsThe Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsBioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.
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