Multi-omics analysis reveals expression complexity and functional diversity of mouse kinome.
Xin HuangLing LiSuiping ZhouDehui KongJie LuoLu LuHai-Ming XuXusheng WangPublished in: Proteomics (2022)
Protein kinases are a crucial component of signaling pathways involved in a wide range of cellular responses, including growth, proliferation, differentiation, and migration. Systematic investigation of protein kinases is critical to better understand phosphorylation-mediated signaling pathways and may provide insights into the development of potential therapeutic drug targets. Here we perform a systems-level analysis of the mouse kinome by analyzing multi-omics data. We used bulk and single-cell transcriptomic data from the C57BL/6J mouse strain to define tissue- and cell-type-specific expression of protein kinases, followed by investigating variations in sequence and expression between C57BL/6J and DBA/2J strains. We then profiled a deep brain phosphoproteome from C57BL/6J and DBA/2J strains as well as their reciprocal hybrids to infer the activity of the mouse kinome. Finally, we performed phenome-wide association analysis using the BXD recombinant inbred (RI) mice (a cross between C57BL/6J and DBA/2J strains) to identify any associations between variants in protein kinases and phenotypes. Collectively, our study provides a comprehensive analysis of the mouse kinome by investigating genetic sequence variation, tissue-specific expression patterns, and associations with downstream phenotypes.
Keyphrases
- single cell
- poor prognosis
- binding protein
- signaling pathway
- escherichia coli
- amino acid
- protein protein
- rna seq
- long non coding rna
- electronic health record
- emergency department
- gene expression
- big data
- small molecule
- adipose tissue
- copy number
- skeletal muscle
- artificial intelligence
- adverse drug
- multiple sclerosis
- data analysis
- deep learning
- high fat diet induced
- functional connectivity