Computational verification of protein-protein interactions by orthologous co-expression

BACKGROUND: High-throughput methods identify an overwhelming number of protein-protein interactions. However, the limited accuracy of these methods results in the false identification of many spurious interactions. Accordingly, the resulting interactions are regarded as hypothetical and computational methods are needed to increase their confidence. Several methods have recently been suggested for this purpose including co-expression as a confidence measure for interacting proteins, but their performance is still quite poor. RESULTS: We introduce a novel computational method for verification of protein-protein interactions based on the co-expression of orthologs of interacting partners. The performance of our method is analysed using known S. cerevisiae interactions, and is shown to overcome limitations of previous methods. We present specific examples of known and putative interactions that are detected by our method and not by previous methods, and suggest that they represent transient interactions that might have been conserved and stabilized in other species. CONCLUSION: Co-expression of orthologous protein-pairs can be used to increase the confidence of hypothetical protein-protein interactions in S. cerevisiae as well as in other species. This approach may be especially useful for species with no available expression profiles and for transient interactions

Comparative analysis indicates regulatory neofunctionalization of yeast duplicates

Comparison of the expression profiles of S. cerevisiae duplicate pairs with that of their pre-duplication orthologs in C. albicans identified a class of genes that may present cases of regulatory neofunctionalization

Opposite GC skews at the 5' and 3' ends of genes in unicellular fungi

<p>Abstract</p> <p>Background</p> <p>GC-skews have previously been linked to transcription in some eukaryotes. They have been associated with transcription start sites, with the coding strand G-biased in mammals and C-biased in fungi and invertebrates.</p> <p>Results</p> <p>We show a consistent and highly significant pattern of GC-skew within genes of almost all unicellular fungi. The pattern of GC-skew is asymmetrical: the coding strand of genes is typically C-biased at the 5' ends but G-biased at the 3' ends, with intermediate skews at the middle of genes. Thus, the initiation, elongation, and termination phases of transcription are associated with different skews. This pattern influences the encoded proteins by generating differential usage of amino acids at the 5' and 3' ends of genes. These biases also affect fourfold-degenerate positions and extend into promoters and 3' UTRs, indicating that skews cannot be accounted by selection for protein function or translation.</p> <p>Conclusions</p> <p>We propose two explanations, the mutational pressure hypothesis, and the adaptive hypothesis. The mutational pressure hypothesis is that different co-factors bind to RNA pol II at different phases of transcription, producing different mutational regimes. The adaptive hypothesis is that cytidine triphosphate deficiency may lead to C-avoidance at the 3' ends of transcripts to control the flow of RNA pol II molecules and reduce their frequency of collisions.</p

Divergence of nucleosome positioning between two closely related yeast species: genetic basis and functional consequences

Inter-species hybrids can be used to dissect the relative contribution of cis and trans effects to the evolution of nucleosome positioning. Most (∼70%) differences in nucleosome positioning between two closely related yeast species are due to cis effects.Cis effects are primarily due to divergence of AT-rich nucleosome-disfavoring sequences, but are not associated with divergence of nucleosome-favoring sequences.Differences in nucleosome positioning propagate to multiple adjacent nucleosomes, supporting the statistical positioning hypothesis.Divergence of nucleosome positioning is excluded from regulatory elements and is not correlated with gene expression divergence, suggesting a neutral mode of evolution

Autocorrelation analysis reveals widespread spatial biases in microarray experiments

<p>Abstract</p> <p>Background</p> <p>DNA microarrays provide the ability to interrogate multiple genes in a single experiment and have revolutionized genomic research. However, the microarray technology suffers from various forms of biases and relatively low reproducibility. A particular source of false data has been described, in which non-random placement of gene probes on the microarray surface is associated with spurious correlations between genes.</p> <p>Results</p> <p>In order to assess the prevalence of this effect and better understand its origins, we applied an autocorrelation analysis of the relationship between chromosomal position and expression level to a database of over 2000 individual yeast microarray experiments. We show that at least 60% of these experiments exhibit spurious chromosomal position-dependent gene correlations, which nonetheless appear in a stochastic manner within each experimental dataset. Using computer simulations, we show that large spatial biases caused in the microarray hybridization step and independently of printing procedures can exclusively account for the observed spurious correlations, in contrast to previous suggestions. Our data suggest that such biases may generate more than 15% false data per experiment. Importantly, spatial biases are expected to occur regardless of microarray design and over a wide range of microarray platforms, organisms and experimental procedures.</p> <p>Conclusions</p> <p>Spatial biases comprise a major source of noise in microarray studies; revision of routine experimental practices and normalizations to account for these biases may significantly and comprehensively improve the quality of new as well as existing DNA microarray data.</p

Widespread remodeling of mid-coding sequence nucleosomes by Isw1

In yeast, the chromatin remodeler Isw1 shifts nucleosomes from mid-coding, to more 5’ regions of genes and may regulate transcriptional elongation

Coupled Evolution of Transcription and mRNA Degradation

mRNA levels are determined by the balance between transcription and mRNA degradation, and while transcription has been extensively studied, very little is known regarding the regulation of mRNA degradation and its coordination with transcription. Here we examine the evolution of mRNA degradation rates between two closely related yeast species. Surprisingly, we find that around half of the evolutionary changes in mRNA degradation were coupled to transcriptional changes that exert opposite effects on mRNA levels. Analysis of mRNA degradation rates in an interspecific hybrid further suggests that opposite evolutionary changes in transcription and in mRNA degradation are mechanistically coupled and were generated by the same individual mutations. Coupled changes are associated with divergence of two complexes that were previously implicated both in transcription and in mRNA degradation (Rpb4/7 and Ccr4-Not), as well as with sequence divergence of transcription factor binding motifs. These results suggest that an opposite coupling between the regulation of transcription and that of mRNA degradation has shaped the evolution of gene regulation in yeast

Promoter architecture and the evolvability of gene expression

Evolutionary changes in gene expression are a main driver of phenotypic evolution. In yeast, genes that have rapidly diverged in expression are associated with particular promoter features, including the presence of a TATA box, a nucleosome-covered promoter and unstable tracts of tandem repeats. Here, we discuss how these promoter properties may confer an inherent capacity for flexibility of expression

Chromatin regulators as capacitors of interspecies variations in gene expression

Deletion of eight chromatin regulators and one transcription factor increases the variability in gene expression between two closely related yeast species, suggesting that large-scale regulators often buffer variations in gene expression.Similar analysis of metabolic enzymes indicates that, unlike regulators, these enzymes do not buffer gene expression variations

On the relation between promoter divergence and gene expression evolution

Recent studies have characterized significant differences in the cis-regulatory sequences of related organisms, but the impact of these differences on gene expression remains largely unexplored. Here, we show that most previously identified differences in transcription factor (TF)-binding sequences of yeasts and mammals have no detectable effect on gene expression, suggesting that compensatory mechanisms allow promoters to rapidly evolve while maintaining a stabilized expression pattern. To examine the impact of changes in cis-regulatory elements in a more controlled setting, we compared the genes induced during mating of three yeast species. This response is governed by a single TF (STE12), and variations in its predicted binding sites can indeed account for about half of the observed expression differences. The remaining unexplained differences are correlated with the increased divergence of the sequences that flank the binding sites and an apparent modulation of chromatin structure. Our analysis emphasizes the flexibility of promoter structure, and highlights the interplay between specific binding sites and general chromatin structure in the control of gene expression