Conserved noncoding sequences highlight shared components of regulatory networks in dicotyledonous plants.

Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research.

Evolutionary analysis of regulatory sequences (EARS) in plants.

Identification of regulatory sequences within non-coding regions of DNA is an essential step towards elucidation of gene networks. This approach constitutes a major challenge, however, as only a very small fraction of non-coding DNA is thought to contribute to gene regulation. The mapping of regulatory regions traditionally involves the laborious construction of promoter deletion series which are then fused to reporter genes and assayed in transgenic organisms. Bioinformatic methods can be used to scan sequences for matches for known regulatory motifs, however these methods are currently hampered by the relatively small amount of such motifs and by a high false-discovery rate. Here, we demonstrate a robust and highly sensitive, in silico method to identify evolutionarily conserved regions within non-coding DNA. Sequence conservation within these regions is taken as evidence for evolutionary pressure against mutations, which is suggestive of functional importance. We test this method on a small set of well characterised promoters, and show that it successfully identifies known regulatory regions. We further show that these evolutionarily conserved sequences contain clusters of transcription binding sites, often described as regulatory modules. A version of the tool optimised for the analysis of plant promoters is available online at http://wsbc.warwick.ac.uk/ears/main.php.