ArticleBMC genomics2021
Genome-wide identification of enhancers and transcription factors regulating the myogenic differentiation of bovine satellite cells.
Article in BMC genomics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 29 citations in OpenAlex.
- Integrated transcriptomic and functional analysis reveals tissue-specific molecular pathology in adolescent idiopathic scoliosis.HGG advances · 2026Article
- The Transcriptomic Landscape and Regulatory Signaling Features of Bovine Skeletal Muscle Cells Used for Cultured Meat Production.Foods (Basel, Switzerland) · 2026Article
- Article
- DCMS analysis revealed differential selection signatures in the transboundary Sahiwal cattle for major economic traits.Scientific reports · 2025Article
- Article
- Transcriptomic Insights into Post-Spawning Death and Muscle Atrophy in Ayu (International journal of molecular sciences · 2025Article
- Branched-Chain Amino Acids Target miR-203a/fosb Axis to Promote Skeletal Muscle Growth in Common Carp (Aquaculture nutrition · 2025Article
- Epigenetic landscape revealsFrontiers in nutrition · 2025Article
- Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma.Journal of translational medicine · 2024Article
- Chromatin profiling reveals TFAP4 as a critical transcriptional regulator of bovine satellite cell differentiation.BMC genomics · 2024Article
- Effects of DNA Methylation on Gene Expression and Phenotypic Traits in Cattle: A Review.International journal of molecular sciences · 2023Review
- Influence of Media Composition on the Level of Bovine Satellite Cell Proliferation.Animals : an open access journal from MDPI · 2023Article
- Determining the Potential Roles of Branched-Chain Amino Acids in the Regulation of Muscle Growth in Common Carp (Aquaculture nutrition · 2023Article
- Identification of Robust and Key Differentially Expressed Genes during C2C12 Cell Myogenesis Based on Multiomics Data.International journal of molecular sciences · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSatellite cells are the myogenic precursor cells in adult skeletal muscle. The objective of this study was to identify enhancers and transcription factors that regulate gene expression during the differentiation of bovine satellite cells into myotubes.
resultsChromatin immunoprecipitation followed by deep sequencing (ChIP-seq) was performed to identify genomic regions where lysine 27 of H3 histone is acetylated (H3K27ac), i.e., active enhancers, from bovine satellite cells before and during differentiation into myotubes. A total of 19,027 and 47,669 H3K27ac-marked enhancers were consistently identified from two biological replicates of before- and during-differentiation bovine satellite cells, respectively. Of these enhancers, 5882 were specific to before-differentiation, 35,723 to during-differentiation, and 13,199 common to before- and during-differentiation bovine satellite cells. Whereas most of the before- or during-differentiation-specific H3K27ac-marked enhancers were located distally to the transcription start site, the enhancers common to before- and during-differentiation were located both distally and proximally to the transcription start site. The three sets of H3K27ac-marked enhancers were associated with functionally different genes and enriched with different transcription factor binding sites. Specifically, many of the H3K27ac-marked enhancers specific to during-differentiation bovine satellite cells were associated with genes involved in muscle structure and development, and were enriched with binding sites for the MyoD, AP-1, KLF, TEAD, and MEF2 families of transcription factors. A positive role was validated for Fos and FosB, two AP-1 family transcription factors, in the differentiation of bovine satellite cells into myotubes by siRNA-mediated knockdown.
conclusionsTens of thousands of H3K27ac-marked active enhancers have been identified from bovine satellite cells before or during differentiation. These enhancers contain binding sites not only for transcription factors whose role in satellite cell differentiation is well known but also for transcription factors whose role in satellite cell differentiation is unknown. These enhancers and transcription factors are valuable resources for understanding the complex mechanism that mediates gene expression during satellite cell differentiation. Because satellite cell differentiation is a key step in skeletal muscle growth, the enhancers, the transcription factors, and their target genes identified in this study are also valuable resources for identifying and interpreting skeletal muscle trait-associated DNA variants in cattle.
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.