Computational identification of developmental enhancers: conservation and function of transcription factor binding-site clusters in drosophila melanogaster and drosophila psedoobscura (2004)

Volume et al. Berman 2004 5, Issue 9, Article R61 Research Open Access comment Benjamin P Berman ¤ * , Barret D Pfeiffer ¤ † , Todd R Laverty ‡ , Steven L Salzberg § , Gerald M Rubin *†‡ , Michael B Eisen ¤ *¶¥ and Susan E Celniker ¤ † Computational identification of developmental enhancers: conservation and function of transcription factor binding-site clusters in Drosophila melanogaster and Drosophila pseudoobscura reviews Addresses: * Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA. † Berkeley Drosophila Genome Project, Genome Sciences Department, Life Sciences Division, Lawrence Orlando Berkeley National Laboratory, Berkeley, CA 94720, USA. ‡ Howard Hughes Medical Institute, Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA. § The Institute for Genomic Research, 9712 Medical Center Drive, Rockville, MD 20878, USA. ¶ Genome Sciences Department, Genomics Division, Lawrence Orlando Berkeley National Laboratory, Berkeley, CA 94720, USA. ¥ Center for Integrative Genomics, University of California, Berkeley, CA 94720, USA. ¤ These authors contributed equally to this work. reports Correspondence: Michael B Eisen. E-mail: mbeisen@lbl.gov Published: 20 August 2004 Genome Biology 2004, 5:R61 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2004/5/9/R61 Received: 14 July 2004 Revised: 4 August 2004 Accepted: 6 August 2004 deposited research © 2004 Berman et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ative sequence identification of developmental enhancers: conservation and function of transcription factor makes better use of in Dro- Measuring conservation of sequence methods that sophila melanogaster and Drosophila pseudoobscura examine only sequence identity. Computational data than commonly used features closely linked to function - such as binding-site clustering - binding-site clusters compar- refereed research Abstract Background: The identification of sequences that control transcription in metazoans is a major goal of genome analysis. In a previous study, we demonstrated that searching for clusters of predicted transcription factor binding sites could discover active regulatory sequences, and identified 37 regions of the Drosophila melanogaster genome with high densities of predicted binding sites for five transcription factors involved in anterior-posterior embryonic patterning. Nine of these clusters overlapped known enhancers. Here, we report the results of in vivo functional analysis of 27 remaining clusters. Results: We generated transgenic flies carrying each cluster attached to a basal promoter and reporter gene, and assayed embryos for reporter gene expression. Six clusters are enhancers of adjacent genes: giant, fushi tarazu, odd-skipped, nubbin, squeeze and pdm2; three drive expression in patterns unrelated to those of neighboring genes; the remaining 18 do not appear to have enhancer activity. We used the Drosophila pseudoobscura genome to compare patterns of evolution in and around the 15 positive and 18 false-positive predictions. Although conservation of primary sequence cannot distinguish true from false positives, conservation of binding-site clustering accurately discriminates functional binding-site clusters from those with no function. We incorporated conservation of binding-site clustering into a new genome-wide enhancer screen, and predict several hundred new regulatory sequences, including 85 adjacent to genes with embryonic patterns. Conclusions: Measuring conservation of sequence features closely linked to function - such as binding-site clustering - makes better use of comparative sequence data than commonly used methods that examine only sequence identity. Genome Biology 2004, 5:R61 interactions information