Integrated analysis of yeast regulatory sequences for biologically linked clusters of genes

Funct Integr Genomics. 2003 Jul;3(3):125-34. doi: 10.1007/s10142-003-0086-6. Epub 2003 Jun 25.

Abstract

Dramatic progress in deciphering the regulatory controls in Saccharomyces cerevisiae has been enabled by the fusion of high-throughput genomics technologies with advanced sequence analysis algorithms. Sets of genes likely to function together and with similar expression profiles have been identified in diverse studies. By fusing an advanced pattern recognition algorithm for identification of transcription factor binding sites with a new method for the quantitative comparison of binding properties of transcription factors, we provide an integrated means to move from expression data to biological insights. The Yeast Regulatory Sequence Analysis system, YRSA, combines standard functions with a novel pattern characterization procedure in an intuitive interface designed for use by a broad range of scientists. The features of the system include automated retrieval of user-defined promoter sequences, binding site discovery by pattern recognition, graphical displays of the observed pattern and positions of similar sequences in the specified genes, and comparison of the new pattern against a collection of binding patterns for characterized transcription factors. The comprehensive YRSA system was used to study the regulatory mechanisms of yeast regulons. Analysis of the regulatory controls of a battery of genes induced by DNA damaging agents supports a putative mediating role for the cell-cycle checkpoint regulatory element MCB. YRSA is available at http://yrsa.cgb.ki.se. [YRSA: ancient Scandinavian name meaning old she-bear (Latin Ursus arctos = brown bear/grizzly).]

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Binding Sites
  • Cell Cycle / physiology
  • DNA Damage
  • Multigene Family*
  • Promoter Regions, Genetic*
  • Saccharomyces cerevisiae / genetics*
  • Sequence Analysis, DNA / methods*
  • Transcription Factors / metabolism

Substances

  • Transcription Factors