A Global View of the Selection Forces in the Evolution of Yeast <i>Cis</i>-Regulation

Tanay, Amos; Gat‐Viks, Irit; Shamir, Ron

doi:10.1101/gr.2064404

Cited by 28 publications

(29 citation statements)

References 16 publications

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“…The PREGO algorithm was able to very strongly associate the motif CTCGAG with each of the three available Xbp1 profiles, confirming a previous report on Xbp1's binding consensus GCCTCGARGMGR (Mai and Breeden 1997). Interestingly, in a previous work (Tanay et al 2004a), we have identified CTCGAG as a possible motif using evolutionary analysis, but could not associate it with a TF. The Rtg3 factor was shown before to bind a GGTCAC motif, using mutational analysis of CIT2 UAS r (Jia et al 1997).…”

Section: Discovery Of Known and Novel Pwms Using Motif Regressionsupporting

confidence: 65%

“…The remarkable correlation between promoter sequences and low-affinity ChIP values, and the success of the regression approach in detecting PWM models that could not be detected in (Cliften et al 2003;Kellis et al 2003), and several models were suggested to describe the selective pressures affecting them (Moses et al 2003;Tanay et al 2004a). If binding of a TF to low-affinity promoters is functionally important, one would expect to observe selection operating not only on individual binding sites, but also on the total affinity of each promoter to that TF.…”

Section: Discovery Of Known and Novel Pwms Using Motif Regressionmentioning

confidence: 99%

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Extensive low-affinity transcriptional interactions in the yeast genome

Tanay¹

2006

Genome Res.

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238

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Major experimental and computational efforts are targeted at the characterization of transcriptional networks on a genomic scale. The ultimate goal of many of these studies is to construct networks associating transcription factors with genes via well-defined binding sites. Weaker regulatory interactions other than those occurring at high-affinity binding sites are largely ignored and are not well understood. Here I show that low-affinity interactions are abundant in vivo and quantifiable from current high-throughput ChIP experiments. I develop algorithms that predict DNA-binding energies from sequences and ChIP data across a wide dynamic range of affinities and use them to reveal widespread functionality of low-affinity transcription factor binding. Evolutionary analysis suggests that binding energies of many transcription factors are conserved even in promoters lacking classical binding sites. Gene expression analysis shows that such promoters can generate significant expression. I estimate that while only a small percentage of the genome is strongly regulated by a typical transcription factor, up to an order of magnitude more may be involved in weaker interactions. Low-affinity transcription factor–DNA interaction may therefore be important both evolutionarily and functionally.

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Section: Discovery Of Known and Novel Pwms Using Motif Regressionsupporting

confidence: 65%

Section: Discovery Of Known and Novel Pwms Using Motif Regressionmentioning

confidence: 99%

Extensive low-affinity transcriptional interactions in the yeast genome

Tanay¹

2006

Genome Res.

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238

204

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“…We have shown that computational techniques, merging previously uncharacterized data with well established evolutionary concepts, facilitate improved integration of genomic (sequence) and phenotypic (expression) data and their synthesis into a coherent reconstruction of the evolution of regulatory networks. The evolutionary context is crucial for the exploitation of these data and greatly enhances the potential of comparative methods (28). Whereas previous research in comparative genomics of regulatory networks focused on the identification of conserved cis-elements (29-31), our results emphasize the importance of accounting for changes, both gradual sequence divergence and dramatic innovation processes.…”

Section: Discussioncontrasting

confidence: 38%

Conservation and evolvability in regulatory networks: The evolution of ribosomal regulation in yeast

Tanay

Regev

Shamir

2005

Proc. Natl. Acad. Sci. U.S.A.

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254

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Transcriptional modules of coregulated genes play a key role in regulatory networks. Comparative studies show that modules of coexpressed genes are conserved across taxa. However, little is known about the mechanisms underlying the evolution of module regulation. Here, we explore the evolution of cis-regulatory programs associated with conserved modules by integrating expression profiles for two yeast species and sequence data for a total of 17 fungal genomes. We show that although the cis-elements accompanying certain conserved modules are strictly conserved, those of other conserved modules are remarkably diverged. In particular, we infer the evolutionary history of the regulatory program governing ribosomal modules. We show how a ciselement emerged concurrently in dozens of promoters of ribosomal protein genes, followed by the loss of a more ancient cis-element. We suggest that this formation of an intermediate redundant regulatory program allows conserved transcriptional modules to gradually switch from one regulatory mechanism to another while maintaining their functionality. Our work provides a general framework for the study of the dynamics of promoter evolution at the level of transcriptional modules and may help in understanding the evolvability and increased redundancy of transcriptional regulation in higher organisms.regulatory motifs ͉ transcriptional networks T ranscriptional modules, i.e., groups of coregulated genes, play a central role in the organization and function of regulatory networks (1-3). Comparative studies have demonstrated that various transcriptional modules are highly conserved across a wide variety of organisms from Escherichia coli to humans (4-6). A common tacit assumption is that conserved regulatory mechanisms underlie module conservation, because coregulation imposes tight constraints on the evolution of a module's promoters. Indeed, recent studies showed that orthologous transcriptional modules are often associated with conserved cis-elements (7).To gain new insights into the evolution of regulation of transcriptional modules, we developed an integrated method for comparative expression and sequence analysis. We applied our method to 17 fully sequenced yeast genomes and identified conserved transcriptional modules and the cis-elements that are associated with them in each species. Although the cis-elements associated with certain modules were conserved in all species, other modules were associated with distinct cis-elements in different species. Divergence of cis-elements in specific promoters has been documented, e.g., in refs. 8 and 9, but it is difficult to explain in a similar way the divergence we observed in a regulatory program associated with dozens of coexpressed genes. In particular, it is not clear how multiple promoters diverge in a coordinated way and how divergence occurs without adversely affecting the coexpression phenotype. To answer this question, we inferred the detailed evolutionary history of modules' regulatory programs and studied different evolutionary...

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“…One promising approach for detecting binding sites is phylogenetic footprinting, the identification of selectively constrained elements by their conservation across species. For example, the genome sequences of S. cerevisiae and several of its close relatives have been used to predict motifs likely to describe transcription-factor-binding sites (Chiang et al 2003;Cliften et al 2003;Kellis et al 2003;Pritsker et al 2004;Siddharthan et al 2004;Tanay et al 2004).…”

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confidence: 99%

Genome-wide regulatory complexity in yeast promoters: Separation of functionally conserved and neutral sequence

Chin¹,

Chuang²,

Li³

2005

Genome Res.

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To gauge the complexity of gene regulation in yeast, it is essential to know how much promoter sequence is functional. Conservation across species can be a sensitive means of detecting functional sequences, provided that the significance of conservation can be accurately calibrated with the local neutral mutation rate. By analyzing yeast coding and promoter sequences, we find that neutral mutation rates in yeast are uniform genome-wide, in contrast to mammals, where neutral mutation rates vary along chromosomes. We develop an approach that uses this uniform rate to estimate the amount of promoter sequence under purifying selection. This amount is ∼30%, corresponding to roughly 90 bp for a typical promoter. Furthermore, using a hidden Markov model, we are able to separate each promoter into distinct high and low conservation regions. Known regulatory motifs are strongly biased toward high conservation regions, while low conservation regions have mutation rates similar to that of the neutral background. Certain Gene Ontology groupings of genes (e.g., Carbohydrate Metabolism) have large amounts of high conservation sequence, suggesting complexity in their transcriptional regulation. Others (e.g., RNA Processing) have little high conservation sequence and are likely to be simply regulated. The separation of functionally conserved sequence from the neutral background allows us to estimate the complexity of cis-regulation on a genomic scale.[Supplemental material is available online at www.genome.org and http://genome.ucsf.edu/YeastReg.]The regulation of gene expression is a universal, yet complex, process in biological systems. In the model organism Saccharomyces cerevisiae, several hundred transcription factors are thought to be involved in the regulation of ∼6000 genes (Gene Ontology Consortium 2000; Dolinski et al. 2004). Much of this regulation is mediated by transcription-factor-binding sites in promoter sequences, making knowledge of these sites essential for understanding the logic of cis-regulation. One promising approach for detecting binding sites is phylogenetic footprinting, the identification of selectively constrained elements by their conservation across species. For example, the genome sequences of S. cerevisiae and several of its close relatives have been used to predict motifs likely to describe transcription-factor-binding sites (Chiang et al. 2003;Cliften et al. 2003;Kellis et al. 2003;Pritsker et al. 2004;Siddharthan et al. 2004;Tanay et al. 2004).Although a number of transcription factors and binding motifs have been studied in detail, some basic parameters of transcriptional regulation are not known. One important feature that has not been characterized is the amount of functional sequence under purifying selection in yeast promoters. This is crucial for assessing how many transcription factors bind a typical promoter, how prevalent combinatorial control is, and whether regulation is more complex for particular gene families.Inspection of aligned yeast promoters shows rich structure in conserva...

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A Global View of the Selection Forces in the Evolution of Yeast Cis-Regulation

Cited by 28 publications

References 16 publications

Extensive low-affinity transcriptional interactions in the yeast genome

Extensive low-affinity transcriptional interactions in the yeast genome

Conservation and evolvability in regulatory networks: The evolution of ribosomal regulation in yeast

Genome-wide regulatory complexity in yeast promoters: Separation of functionally conserved and neutral sequence

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