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Updated: Sep 4, 2025

JUMPn: A Streamlined Application for Protein Co-Expression Clustering and Network Analysis in Proteomics
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Multi-omics analysis reveals expression complexity and functional diversity of mouse kinome.

Xin Huang1, Ling Li2, Suiping Zhou3

  • 1Institute of Crop Science and Institute of Bioinformatics, College of Agriculture and Biotechnology, Zhejiang University, Hangzhou, China.

Proteomics
|July 20, 2022
PubMed
Summary

This study comprehensively analyzes the mouse kinome, investigating protein kinase gene variations, expression patterns, and their links to cellular functions and phenotypes. Understanding these kinases offers insights into signaling pathways and potential drug targets.

Keywords:
BXD miceC57BL/6JDBA/2JPheWASkinase activitykinomemouseomicsprotein expressionprotein kinaseproteome

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Area of Science:

  • Genomics
  • Proteomics
  • Systems Biology

Background:

  • Protein kinases are vital signaling molecules regulating cellular processes like growth and migration.
  • Understanding the kinome is key to deciphering phosphorylation signaling and identifying therapeutic targets.

Purpose of the Study:

  • To conduct a systems-level analysis of the mouse kinome.
  • To investigate protein kinase expression, variation, and functional associations.

Main Methods:

  • Utilized multi-omics data including bulk and single-cell transcriptomics.
  • Analyzed deep brain phosphoproteomics and performed phenome-wide association studies.
  • Compared C57BL/6J and DBA/2J mouse strains and their reciprocal hybrids, including BXD recombinant inbred mice.

Main Results:

  • Defined tissue- and cell-type-specific expression patterns of protein kinases.
  • Identified sequence and expression variations between mouse strains.
  • Inferred kinome activity and associated kinase variants with phenotypes.

Conclusions:

  • Provides a comprehensive analysis of the mouse kinome.
  • Highlights the importance of genetic variation and expression in kinase function.
  • Offers insights into kinase-mediated signaling and potential disease associations.