Using hexamers to predict cis-regulatory motifs in Drosophila

Background  

Cis-regulatory modules (CRMs) are short stretches of DNA that help regulate gene expression in higher eukaryotes. They have been found up to 1 megabase away from the genes they regulate and can be located upstream, downstream, and even within their target genes. Due to the difficulty of finding CRMs using biological and computational techniques, even well-studied regulatory systems may contain CRMs that have not yet been discovered.     

The histone deacetylase Rpd3p is required for transient changes in genomic expression in response to stress

Background  

Yeast responding to stress activate a large gene expression program called the Environmental Stress Response that consists of approximately 600 repressed genes and approximately 300 induced genes. Numerous factors are implicated in regulating subsets of Environmental Stress Response genes; however, a complete picture of Environmental Stress Response regulation remains unclear. We investigated the role of the histone deacetylase Rpd3p, previously linked to the upstream regions of many Environmental Stress Response genes, in producing Environmental Stress Response gene expression changes in response to stress.     

More robust detection of motifs in coexpressed genes by using phylogenetic information

Background  

Several motif detection algorithms have been developed to discover overrepresented motifs in sets of coexpressed genes. However, in a noisy gene list, the number of genes containing the motif versus the number lacking the motif might not be sufficiently high to allow detection by classical motif detection tools. To still recover motifs which are not significantly enriched but still present, we developed a procedure in which we use phylogenetic footprinting to first delineate all potential motifs in each gene. Then we mutually compare all detected motifs and identify the ones that are shared by at least a few genes in the data set as potential candidates.     

Exact distribution of a pattern in a set of random sequences generated by a Markov source: applications to biological data

Background  

In bioinformatics it is common to search for a pattern of interest in a potentially large set of rather short sequences (upstream gene regions, proteins, exons, etc.). Although many methodological approaches allow practitioners to compute the distribution of a pattern count in a random sequence generated by a Markov source, no specific developments have taken into account the counting of occurrences in a set of independent sequences. We aim to address this problem by deriving efficient approaches and algorithms to perform these computations both for low and high complexity patterns in the framework of homogeneous or heterogeneous Markov models.     

XcisClique: analysis of regulatory bicliques

Background  

Modeling of cis-elements or regulatory motifs in promoter (upstream) regions of genes is a challenging computational problem. In this work, set of regulatory motifs simultaneously present in the promoters of a set of genes is modeled as a biclique in a suitably defined bipartite graph. A biologically meaningful co-occurrence of multiple cis-elements in a gene promoter is assessed by the combined analysis of genomic and gene expression data. Greater statistical significance is associated with a set of genes that shares a common set of regulatory motifs, while simultaneously exhibiting highly correlated gene expression under given experimental conditions.     

The GATA-binding protein CGF-1 is closely related to GT-1

Many light-regulated genes contain a conserved GATA motif in their 5-upstream region. We have characterized in detail the GATA-binding factor, CGF-1, which binds within a 73 bp TATA-proximal light/circadian regulatory element in the Arabidopsis cab2 promoter and to two more sites farther upstream. CGF-1 was found to be distinct from other metal-dependent GATA-binding factors, but to have the same sequence requirements for binding and similar physical and chemical properties as GT-1, a factor required for light regulation of the tobacco rbcS-3A gene. CGF-1 was found to be constitutively present in extracts and was shown to be immunologically related to GT-1. The close similarity between CGF-1 and GT-1 suggests that a GT-1-like factor is involved in the phytochrome/circadian regulation of the cab2 gene. CGF-1 and GT-1 were also found to have similar sequence specificities to another constitutively-regulated GATA factor, IBF-2b, which binds the I box region of the tomato nitrate reductase gene. Of three complexes detected using an IBF-2b-specific probe, only one was identical to CGF-1/GT-1. The other two were similar to IBF-2b, demonstrating that CGF-1/GT-1, although very similar, are actually distinct from IBF-2b. These data indicate that more than one factor can bind to the same short sequence and may indicate how constitutively present factors like GT-1 can play a role in light regulation.     

Differential selection on gene translation efficiency between the filamentous fungus <Emphasis Type="Italic">Ashbya gossypii</Emphasis> and yeasts

Background  

The filamentous fungus Ashbya gossypii grows into a multicellular mycelium that is distinct from the unicellular morphology of its closely related yeast species. It has been proposed that genes important for cell cycle regulation play central roles for such phenotypic differences. Because A. gossypii shares an almost identical set of cell cycle genes with the typical yeast Saccharomyces cerevisiae, the differences might occur at the level of orthologous gene regulation. Codon usage patterns were compared to identify orthologous genes with different gene regulation between A. gossypii and nine closely related yeast species.     

Gene expression model (in)validation by Fourier analysis

Background  

The determination of the right model structure describing a gene regulation network and the identification of its parameters are major goals in systems biology. The task is often hampered by the lack of relevant experimental data with sufficiently low noise level, but the subset of genes whose concentration levels exhibit an oscillatory behavior in time can readily be analyzed on the basis of their Fourier spectrum, known to turn complex signals into few relatively noise-free parameters. Such genes therefore offer opportunities of understanding gene regulation quantitatively.