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Differential Expression of MicroRNAs in Dark-Cutting Meat from Beef Carcasses
- Source :
- Applied Sciences; Volume 12; Issue 7; Pages: 3555
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- “Dark-cutting” meat in beef carcasses can result from conditions such as long-term stress and depleted glycogen stores, but some aspects of the physiological mechanisms that cause dark-cutting phenotypes remain poorly understood. Certain responses to stress factors in fully developed tissues are known to be regulated by specific microRNAs. We investigated microRNA expression in Longissimus lumborum biopsies from carcasses derived from a contemporary group of 78 steers from which a high incidence of dark-cutting meat occurred. Our objective was to identify any potential microRNA signatures that reflect the impact of environmental factors and stresses on genetic signaling networks and result in dark-cutting beef (also known as dark, firm, and dry, or DFD) in some animals. MicroRNA expression was quantified by Illumina NextSeq small RNA sequencing. When RNA extracts from DFD muscle biopsy samples were compared with normal, non-DFD (NON) samples, 29 differentially expressed microRNAs were identified in which expression was at least 20% different in the DFD samples (DFD/NON fold ratio ≤0.8 or ≥1.2). When correction for multiple testing was applied, a single microRNA bta-miR-2422 was identified at a false discovery probability (FDR) of 5.4%. If FDR was relaxed to 30%, additional microRNAs were differentially expressed (bta-miR-10174-5p, bta-miR-1260b, bta-miR-144, bta-miR-142-5p, bta-miR-2285at, bta-miR-2285e, bta-miR-3613a). These microRNAs may play a role in regulating aspects of stress responses that ultimately result in dark-cutting beef carcasses.
- Subjects :
- Fluid Flow and Transfer Processes
skeletal muscle
beef cattle
meat quality
dark cutter
DFD
stress
animal welfare
carcass trait
microRNA
RNA sequencing
gene network
miR-2422
Process Chemistry and Technology
General Engineering
food and beverages
General Materials Science
Instrumentation
Computer Science Applications
Subjects
Details
- ISSN :
- 20763417
- Volume :
- 12
- Database :
- OpenAIRE
- Journal :
- Applied Sciences
- Accession number :
- edsair.doi.dedup.....eb0434bac95bdab5b9fa963397a8a9bb
- Full Text :
- https://doi.org/10.3390/app12073555