ArticleScientific reports2024
Transcriptome analysis of mRNA and miRNA in the development of LeiZhou goat muscles.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Meat Quality Characteristics of Mongolian Horses in Inner Mongolia: Regional Superiority and Transcriptomic Insights into Tenderness Differences Between Muscular Locations.Animals : an open access journal from MDPI · 2026Article
- Predominant miRNAs in Animal-Source Foods and Bioinformatic Analysis.Current issues in molecular biology · 2026Article
- Comparative transcriptome analysis of pectoralis major muscles affected by white striping, wooden breast and spaghetti meat in male and female broiler chickens.BMC genomics · 2025Article
- Transcriptome analysis of muscle atrophy in Leizhou black goats: identification of key genes and insights into limb-girdle muscular dystrophy.BMC genomics · 2025Article
- Transcriptome integration analysis revealed that miR-103-3p regulates goat myoblast proliferation by targeting FGF18.BMC genomics · 2025Article
- Transcriptomic sequencing and differential analysis of Kazakh horse muscles from various anatomical locations.Frontiers in veterinary science · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
9 authors.
Funding
Abstract
The progression of muscle development is a pivotal aspect of animal ontogenesis, where miRNA and mRNA exert substantial influence as prominent players. It is important to understand the molecular mechanisms involved in skeletal muscle development to enhance the quality and yield of meat produced by Leizhou goats. We employed RNA sequencing (RNA-SEQ) technology to generate miRNA-mRNA profiles in Leizhou goats, capturing their developmental progression at 0, 3, and 6 months of age. A total of 977 mRNAs and 174 miRNAs were found to be differentially expressed based on our analysis. Metabolic pathways, calcium signaling pathways, and amino acid synthesis and metabolism were found to be significantly enriched among the differentially expressed mRNA in the enrichment analysis. Meanwhile, we found that among these differentially expressed mRNA, some may be related to muscle development, such as MYL10, RYR3, and CSRP3. Additionally,, we identified five muscle-specific miRNAs (miR-127-3p, miR-133a-3p, miR-193b-3p, miR-365-3p, and miR-381) that consistently exhibited high expression levels across all three stages. These miRNAs work with their target genes (FHL3, SESN1, PACSIN3, LMCD1) to regulate muscle development. Taken together, our findings suggest that several miRNAs and mRNAs are involved in regulating muscle development and cell growth in goats. By uncovering the molecular mechanisms involved in muscle growth and development, these findings contribute valuable knowledge that can inform breeding strategies aimed at enhancing meat yield and quality in Leizhou goats.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.