Predicted mouse interactome and network-based interpretation of differentially expressed genes

Hai-Bo Zhang; Xiao-Bao Ding; Jie Jin; Wen-Ping Guo; Qiao-Lei Yang; Peng-Cheng Chen; Heng Yao; Li Ruan; Yu-Tian Tao; Xin Chen

doi:10.1371/journal.pone.0264174

Predicted mouse interactome and network-based interpretation of differentially expressed genes

PLoS One. 2022 Apr 7;17(4):e0264174. doi: 10.1371/journal.pone.0264174. eCollection 2022.

Authors

Hai-Bo Zhang¹, Xiao-Bao Ding¹, Jie Jin¹, Wen-Ping Guo¹, Qiao-Lei Yang², Peng-Cheng Chen², Heng Yao², Li Ruan¹, Yu-Tian Tao¹, Xin Chen^{1

2

3}

Affiliations

¹ Institute of Big Data and Artificial Intelligence in Medicine, School of Electronics & Information Engineering, Taizhou University, Taizhou, China.
² Institute of Pharmaceutical Biotechnology, School of Medicine, Zhejiang University, Hangzhou, China.
³ Joint Institute for Genetics and Genome Medicine between Zhejiang University and University of Toronto, Zhejiang University, Hangzhou, China.

Abstract

The house mouse or Mus musculus has become a premier mammalian model for genetic research due to its genetic and physiological similarities to humans. It brought mechanistic insights into numerous human diseases and has been routinely used to assess drug efficiency and toxicity, as well as to predict patient responses. To facilitate molecular mechanism studies in mouse, we present the Mouse Interactome Database (MID, Version 1), which includes 155,887 putative functional associations between mouse protein-coding genes inferred from functional association evidence integrated from 9 public databases. These putative functional associations are expected to cover 19.32% of all mouse protein interactions, and 26.02% of these function associations may represent protein interactions. On top of MID, we developed a gene set linkage analysis (GSLA) web tool to annotate potential functional impacts from observed differentially expressed genes. Two case studies show that the MID/GSLA system provided precise and informative annotations that other widely used gene set annotation tools, such as PANTHER and DAVID, did not. Both MID and GSLA are accessible through the website http://mouse.biomedtzc.cn.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Databases, Genetic*
Humans
Mammals*
Mice

Grants and funding

This work was financially supported by National Natural Science Foundation of China (81830073 and 31571356), the Humanities and Social Science Project of the Chinese Ministry of Education (20YJAZH033), Science and Technology Program of Taizhou (21ywb76 and 2003gy12), Research project of education department of zhejiang province(Y202045617). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.