Data Mining and Validation of AMPK Pathway as a Novel Candidate Role Affecting Intramuscular Fat Content in Pigs.
Chaogang YaoDaxin PangChao LuAishi XuPeixuan HuangHongsheng OuyangHao YuPublished in: Animals : an open access journal from MDPI (2019)
Intramuscular fat (IMF) is an important economic trait for pork quality and a complex quantitative trait regulated by multiple genes. The objective of this work was to investigate the novel transcriptional effects of a multigene pathway on IMF deposition in the longissimus dorsi (LD) muscles of pigs. Potential signaling pathways were screened by mining data from three gene expression profiles in the Gene Expression Omnibus (GEO) database. We designed quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR) arrays for the candidate signaling pathways to verify the results in the LD muscles of two pig breeds with different IMF contents (Large White and Min). Western blot analysis was used to detect the expression levels of several candidate proteins. Our results showed that the AMPK signaling pathway was screened via bioinformatics analysis. Ten key hub genes of this signaling pathway (AMPK, ADIPOR1, ADIPOR2, LKB1, CAMKKβ, CPT1A, CPT1B, PGC-1α, CD36, and ACC1) were differentially expressed between the Large White and Min pigs. Western blot analysis further confirmed that LKB1/CaMKK2-AMPK-ACC1-CPT1A axis dominates the activity of AMPK signaling pathway. Statistical analyses revealed that AMPK signaling pathway activity clearly varied among the two pig breeds. Based on these results, we concluded that the activation of the AMPK signaling pathway plays a positive role in reducing IMF deposition in pigs.
Keyphrases
- signaling pathway
- bioinformatics analysis
- pi k akt
- skeletal muscle
- gene expression
- induced apoptosis
- genome wide
- epithelial mesenchymal transition
- protein kinase
- adipose tissue
- dna methylation
- south africa
- high resolution
- electronic health record
- cell proliferation
- poor prognosis
- transcription factor
- emergency department
- long non coding rna
- fatty acid
- big data
- high density
- endoplasmic reticulum stress
- quality improvement
- single cell
- human health