Transcriptome Analysis of Skeletal Muscle in Pigs with Divergent Residual Feed Intake Phenotypes
Overview
Molecular Biology
Authors
Affiliations
Residual feed intake (RFI) is defined as the difference between the observed and expected feed intake for maintenance and growth requirements. In this study, the expression profiles of mRNAs and long noncoding RNAs (lncRNAs) from skeletal muscle in Duroc pigs with divergent RFI phenotypes were investigated by Illumina sequencing. Finally, a total of 2195 annotated lncRNAs and 1976 novel lncRNAs were obtained. About 210 mRNAs and 43 lncRNAs were differentially expressed among high and low RFI pigs. The differentially expressed mRNAs were potentially involved in the biological processes of lipid metabolism, extracellular matrix organization, cell proliferation, and cell adhesion. The lipolysis in skeletal muscle was increased in high RFI pigs, suggesting that high RFI pigs might need more energy than low RFI pigs. However, skeletal muscle development was increased in low RFI pigs. These results suggested that low RFI pigs might be more efficient in energy utilization during skeletal muscle growth. The function of lncRNA was also analyzed by target prediction. Nine lncRNAs might be candidate lncRNAs for the determination of RFI phenotype, by the regulation of the biological processes of lipid metabolism, cell proliferation, and cell adhesion. This study should facilitate a further understanding of the molecular mechanism for the determination of RFI phenotype in pigs.
Wu L, Zhuang Z, Jia W, Li Y, Lu Y, Xu M Poult Sci. 2024; 104(1):104613.
PMID: 39631277 PMC: 11652873. DOI: 10.1016/j.psj.2024.104613.
Transcriptome analysis of divergent residual feed intake phenotypes in the of Wannan Yellow rabbits.
Huang D, Wang Y, Qi P, Ding H, Zhao H Front Genet. 2023; 14:1247048.
PMID: 37937196 PMC: 10625914. DOI: 10.3389/fgene.2023.1247048.
Fernandez-Barroso M, Garcia-Casco J, Nunez Y, Ramirez-Hidalgo L, Matos G, Munoz M Anim Genet. 2022; 53(3):352-367.
PMID: 35355298 PMC: 9314091. DOI: 10.1111/age.13195.
Karimi P, Bakhtiarizadeh M, Salehi A, Izadnia H Sci Rep. 2022; 12(1):2558.
PMID: 35169237 PMC: 8847365. DOI: 10.1038/s41598-022-06528-6.
Yang L, He T, Xiong F, Chen X, Fan X, Jin S BMC Genomics. 2020; 21(1):292.
PMID: 32272881 PMC: 7146967. DOI: 10.1186/s12864-020-6713-y.