Analysis of Liver Proteome and Identification of Critical Proteins Affecting Milk Fat, Protein, and Lactose Metabolism in Dariy Cattle with iTRAQ.
Lingna XuLijun ShiLin LiuRuobing LiangQian LiJianguo LiBo HanDongxiao SunPublished in: Proteomics (2019)
In this study, the proteomes of liver tissues are investigated in three periods of the lactation cycle of Holstein cows by using isobaric tag for relative and absolute quantification (iTRAQ) technique to obtain liver proteome and identify functional proteins/genes involved in milk synthesis in dairy cattle. Based on iTRAQ analysis, 3252 proteins are detected in the liver tissues (false discovery rate ≤0.01). Thirty-two differently expressed proteins (DEPs) are identified during the three periods by p-value <0.05 and fold change (FC) ≥2 or ≤0.5, and 183 DEPs based on p-value <0.05 and FC ≥1.5 or ≤0.67. In addition, 905 DEPs are obtained across the three periods by p-value <0.05 and FC ≥1.2, or ≤0.83, and the subsequent GO and KEGG pathway functional analysis indicate that 73 DEPs are significantly enriched into the metabolic terms and pathways involved in milk synthesis such as citrate cycle, fatty acid, starch and sucrose metabolism, and mTOR and PPAR signaling pathways. Further, 41 out of 73 DEPs are identified near to both the peak locations of the reported quantitative trait locus and significant single nucleotide polymorphisms that associate with milk yield and composition traits. In addition, the 41 DEPs are analyzed with the previous liver transcriptome data that used the same samples as this study, and considered nine proteins/genes-ALDH18A1, APOA4, CYP7A1, HADHB, PRKACA, IDH2, LDHA, LDHB, and MAT2A-to be the promising candidates for milk fat, protein, and lactose synthesis in dairy cattle. This study provides a new vision for identifying the potential critical genes associated with milk synthesis of dairy cattle.
Keyphrases
- fatty acid
- genome wide
- gene expression
- adipose tissue
- signaling pathway
- cell proliferation
- dna methylation
- mass spectrometry
- risk assessment
- machine learning
- rna seq
- deep learning
- epithelial mesenchymal transition
- artificial intelligence
- single cell
- skeletal muscle
- protein protein
- climate change
- heat stress
- single molecule
- atomic force microscopy
- induced apoptosis
- data analysis