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      Conservation and Evolution of Cis-Regulatory Systems in Ascomycete Fungi

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          Abstract

          Relatively little is known about the mechanisms through which gene expression regulation evolves. To investigate this, we systematically explored the conservation of regulatory networks in fungi by examining the cis-regulatory elements that govern the expression of coregulated genes. We first identified groups of coregulated Saccharomyces cerevisiae genes enriched for genes with known upstream or downstream cis-regulatory sequences. Reasoning that many of these gene groups are coregulated in related species as well, we performed similar analyses on orthologs of coregulated S. cerevisiae genes in 13 other ascomycete species. We find that many species-specific gene groups are enriched for the same flanking regulatory sequences as those found in the orthologous gene groups from S. cerevisiae, indicating that those regulatory systems have been conserved in multiple ascomycete species. In addition to these clear cases of regulatory conservation, we find examples of cis-element evolution that suggest multiple modes of regulatory diversification, including alterations in transcription factor-binding specificity, incorporation of new gene targets into an existing regulatory system, and cooption of regulatory systems to control a different set of genes. We investigated one example in greater detail by measuring the in vitro activity of the S. cerevisiae transcription factor Rpn4p and its orthologs from Candida albicans and Neurospora crassa. Our results suggest that the DNA binding specificity of these proteins has coevolved with the sequences found upstream of the Rpn4p target genes and suggest that Rpn4p has a different function in N. crassa.

          Abstract

          A systematic examination of the gene regulatory elements in ascomycete fungi reveals striking conservation along with some examples of the ways in which regulatory systems can evolve

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          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            The Clustal series of programs are widely used in molecular biology for the multiple alignment of both nucleic acid and protein sequences and for preparing phylogenetic trees. The popularity of the programs depends on a number of factors, including not only the accuracy of the results, but also the robustness, portability and user-friendliness of the programs. New features include NEXUS and FASTA format output, printing range numbers and faster tree calculation. Although, Clustal was originally developed to run on a local computer, numerous Web servers have been set up, notably at the EBI (European Bioinformatics Institute) (http://www.ebi.ac.uk/clustalw/).
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              Genomic expression programs in the response of yeast cells to environmental changes.

              We explored genomic expression patterns in the yeast Saccharomyces cerevisiae responding to diverse environmental transitions. DNA microarrays were used to measure changes in transcript levels over time for almost every yeast gene, as cells responded to temperature shocks, hydrogen peroxide, the superoxide-generating drug menadione, the sulfhydryl-oxidizing agent diamide, the disulfide-reducing agent dithiothreitol, hyper- and hypo-osmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. A large set of genes (approximately 900) showed a similar drastic response to almost all of these environmental changes. Additional features of the genomic responses were specialized for specific conditions. Promoter analysis and subsequent characterization of the responses of mutant strains implicated the transcription factors Yap1p, as well as Msn2p and Msn4p, in mediating specific features of the transcriptional response, while the identification of novel sequence elements provided clues to novel regulators. Physiological themes in the genomic responses to specific environmental stresses provided insights into the effects of those stresses on the cell.
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                Author and article information

                Journal
                PLoS Biol
                pbio
                PLoS Biology
                Public Library of Science (San Francisco, USA )
                1544-9173
                1545-7885
                December 2004
                9 November 2004
                : 2
                : 12
                : e398
                Affiliations
                [1] 1Genome Sciences Department, Genomics Division, Lawrence Berkeley National Laboratory , Berkeley, California, United States of America
                [2] 2Graduate Group in Biophysics, University of California Berkeley, CaliforniaUnited States of America
                [3] 3Department of Molecular and Cell Biology, University of California Berkeley, CaliforniaUnited States of America
                [4] 4Life Science Division, Lawrence Berkeley National Laboratory Berkeley, CaliforniaUnited States of America
                Article
                10.1371/journal.pbio.0020398
                526180
                15534694
                ef3d18ca-1231-4511-9d38-ec62d4ac93d1
                Copyright: © 2004 Gasch et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited
                History
                : 31 March 2004
                : 9 September 2004
                Categories
                Research Article
                Bioinformatics/Computational Biology
                Evolution
                Genetics/Genomics/Gene Therapy
                Yeast and Fungi

                Life sciences
                Life sciences

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