CORECLUST: identification of the conserved CRM grammar together with prediction of gene regulation

Nucleic Acids Res. 2012 Jul;40(12):e93. doi: 10.1093/nar/gks235. Epub 2012 Mar 15.

Abstract

Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory 'grammar', or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila.

Publication types

  • Evaluation Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Body Patterning / genetics
  • Drosophila / embryology
  • Drosophila / genetics
  • Drosophila / metabolism
  • Enhancer Elements, Genetic
  • Gene Expression Regulation*
  • Gene Expression Regulation, Developmental
  • Muscles / metabolism
  • Position-Specific Scoring Matrices
  • Regulatory Elements, Transcriptional*
  • Sequence Analysis, DNA*
  • Software