title: Transcriptional double-autorepression feedforward circuits act for multicellularity and nervous system development.
abstract: BACKGROUND
  The transcriptional regulatory network is considered to be built from a set of circuit patterns called network motifs. Experimental studies have provided instances where a feedforward circuit (FFC) appears with modification of autoregulation, but little is known systematically about such autoregulation-integrated FFCs. Therefore, we aimed to examine whether the autoregulation-integrated FFC is a network motif relevant to describing the human transcriptional regulatory systems, and explored the relationship of such network motifs with biological functions.
  
  
  RESULTS
  Based on human-mouse evolutionarily conserved transcription factor binding sites (TFBSs) in 76600 conserved blocks for 5169 genes, we compiled the human transcriptional connections into a matrix, and examined the number of FFC appearances in comparison with randomized networks. The results revealed that the configuration of autoregulation integrated in the FFC critically affects the abundance or avoidance of FFC appearances. In particular, an FFC comprising two repressors that are both autoregulated was revealed as a significant network motif, which we termed the double-autoregulation FFC (DAR-FFC). Interestingly, this network motif preferentially constitutes effecter transcriptional circuits with functions in cell-cell signaling and multicellular organization, and is particularly related to nervous system development.
  
  
  CONCLUSIONS
  We have revealed that the configuration of autoregulation integrated in the FFCs is a critical factor for abundance or avoidance of the appearance of the FFCs. In particular, we have identified the DAR-FFC as a distinctive integrated network motif endowed with properties that are indispensable for forming the transcriptional regulatory circuits involved in multicellular organization and nervous system development. This is the first report showing that the DAR-FFC is a significant network motif.
authors.affiliation: Life Science Research Center, Kagawa University, 1750-1 Ikenobe, Miki-cho, Kita-gun, Kagawa 761-0793, Japan. iwama@med.kagawa-u.ac.jp
authors.forename: Hisakazu
authors.initials: H
authors.lastname: Iwama
authors.forename: Koji
authors.initials: K
authors.lastname: Murao
authors.forename: Hitomi
authors.initials: H
authors.lastname: Imachi
authors.forename: Toshihiko
authors.initials: T
authors.lastname: Ishida
mesh_terms: D000818:Animals; D002450:Cell Communication / Q000235:genetics; D019295:Computational Biology; D053263:Gene Regulatory Networks / Q000235:genetics*; D006801:Humans; D051379:Mice; D009420:Nervous System / Q000254:growth & development* / Q000378:metabolism*; D012097:Repressor Proteins / Q000378:metabolism
chemical_list: D012097:Repressor Proteins