RNA sequencing analysis of the longissimus dorsi to identify candidate genes underlying the intramuscular fat content in Anqing Six-end-white pigs.
Y L WangY H HouZ J LingH L ZhaoX R ZhengX D ZhangZ J YinY Y DingPublished in: Animal genetics (2023)
Intramuscular fat (IMF) is a significant marker for pork quality. The Anqing Six-end-white pig has the characteristics of high meat quality and IMF content. Owing to the influence of European commercial pigs and a late start in resource conservation, the IMF content within local populations varies between individuals. This study analyzed the longissimus dorsi transcriptome of purebred Anqing Six-end-white pigs with varying IMF content to recognize differentially expressed genes. We identified 1528 differentially expressed genes between the pigs with high (H) and low (L) IMF content. Based on these data, 1775 Gene Ontology terms were significantly enriched, including lipid metabolism, modification and storage, and regulation of lipid biosynthesis. Pathway analysis revealed 79 significantly enriched pathways, including the Peroxisome proliferator-activated receptor and mitogen-activated protein kinase signaling pathways. Moreover, gene set enrichment analysis indicated that the L group had increased the expression of genes related to ribosome function. Additionally, the protein-protein interaction network analyses revealed that VEGFA, KDR, LEP, IRS1, IGF1R, FLT1 and FLT4 were promising candidate genes associated with the IMF content. Our study identified the candidate genes and pathways involved in IMF deposition and lipid metabolism and provides data for developing local pig germplasm resources.
Keyphrases
- genome wide
- genome wide identification
- single cell
- acute myeloid leukemia
- protein protein
- fatty acid
- tyrosine kinase
- adipose tissue
- copy number
- signaling pathway
- dna methylation
- electronic health record
- poor prognosis
- small molecule
- machine learning
- binding protein
- pi k akt
- genome wide analysis
- bioinformatics analysis
- rna seq
- epithelial mesenchymal transition
- data analysis
- artificial intelligence
- quality improvement
- long non coding rna
- oxidative stress
- protein kinase
- cell wall