title: Characterizing genes with distinct methylation patterns in the context of protein-protein interaction network: application to human brain tissues.
abstract: BACKGROUND
  DNA methylation is an essential epigenetic mechanism involved in transcriptional control. However, how genes with different methylation patterns are assembled in the protein-protein interaction network (PPIN) remains a mystery.
  
  
  RESULTS
  In the present study, we systematically dissected the characterization of genes with different methylation patterns in the PPIN. A negative association was detected between the methylation levels in the brain tissues and topological centralities. By focusing on two classes of genes with considerably different methylation levels in the brain tissues, namely the low methylated genes (LMGs) and high methylated genes (HMGs), we found that their organizing principles in the PPIN are distinct. The LMGs tend to be the center of the PPIN, and attacking them causes a more deleterious effect on the network integrity. Furthermore, the LMGs express their functions in a modular pattern and substantial differences in functions are observed between the two types of genes. The LMGs are enriched in the basic biological functions, such as binding activity and regulation of transcription. More importantly, cancer genes, especially recessive cancer genes, essential genes, and aging-related genes were all found more often in the LMGs. Additionally, our analysis presented that the intra-classes communications are enhanced, but inter-classes communications are repressed. Finally, a functional complementation was revealed between methylation and miRNA regulation in the human genome.
  
  
  CONCLUSIONS
  We have elucidated the assembling principles of genes with different methylation levels in the context of the PPIN, providing key insights into the complex epigenetic regulation mechanisms.
authors.affiliation: College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
authors.forename: Yongsheng
authors.initials: Y
authors.lastname: Li
authors.forename: Juan
authors.initials: J
authors.lastname: Xu
authors.forename: Hong
authors.initials: H
authors.lastname: Chen
authors.forename: Zheng
authors.initials: Z
authors.lastname: Zhao
authors.forename: Shengli
authors.initials: S
authors.lastname: Li
authors.forename: Jing
authors.initials: J
authors.lastname: Bai
authors.forename: Aiwei
authors.initials: A
authors.lastname: Wu
authors.forename: Chunjie
authors.initials: C
authors.lastname: Jiang
authors.forename: Yuan
authors.initials: Y
authors.lastname: Wang
authors.forename: Bin
authors.initials: B
authors.lastname: Su
authors.forename: Xia
authors.initials: X
authors.lastname: Li
mesh_terms: D001921:Brain / Q000378:metabolism*; D019295:Computational Biology; D019175:DNA Methylation / Q000235:genetics*; D044127:Epigenesis, Genetic / Q000235:genetics*; D005786:Gene Expression Regulation / Q000235:genetics*; D005796:Genes / Q000235:genetics*; D006801:Humans; D035683:MicroRNAs / Q000378:metabolism; D060066:Protein Interaction Maps / Q000235:genetics*; D040901:Proteomics
chemical_list: D035683:MicroRNAs