Faculty Bibliography

MOTIVATION/BACKGROUND:Current methodologies for the selection of putative transcription factor binding sites (TFBS) rely on various assumptions such as over-representation of motifs occurring on gene promoters, and the use of motif descriptions such as consensus or position-specific scoring matrices (PSSMs). In order to avoid bias introduced by such assumptions, we apply an unsupervised motif extraction (MEX) algorithm to sequences of promoters. The extracted motifs are assessed for their likely cis-regulatory function by calculating the expression coherence (EC) of the corresponding genes, across a set of biological conditions. RESULTS:Applying MEX to all Saccharomyces cerevisiae promoters, followed by EC analysis across 40 biological conditions, we obtained a high percentage of putative cis-regulatory motifs. We clustered motifs that obtained highly significant EC scores, based on both their sequence similarity and similarity in the biological conditions these motifs appear to regulate. We describe 20 clusters, some of which regroup known TFBS. The clusters display different mRNA expression profiles, correlated with typical changes in the nucleotide composition of their relevant motifs. In several cases, a variation of a single nucleotide is shown to lead to distinct differences in expression patterns. These results are confronted with additional information, such as binding of transcription factors to groups of genes. Detailed analysis is presented for clusters related to MCB/SCB, STRE and PAC. In the first two cases, we provide evidence for different binding mechanisms of different clusters of motifs. For PAC-related motifs we uncover a new cluster that has so far been overshadowed by the stronger effects of known PAC motifs. SUPPLEMENTARY INFORMATION/BACKGROUND:Supplementary data are available at http://adios.tau.ac.il/regmotifs and at Bioinformatics online.

microRNAs (miRs) are small RNAs that regulate gene expression at the posttranscriptional level. It is anticipated that, in combination with transcription factors (TFs), they span a regulatory network that controls thousands of mammalian genes. Here we set out to uncover local and global architectural features of the mammalian miR regulatory network. Using evolutionarily conserved potential binding sites of miRs in human targets, and conserved binding sites of TFs in promoters, we uncovered two regulation networks. The first depicts combinatorial interactions between pairs of miRs with many shared targets. The network reveals several levels of hierarchy, whereby a few miRs interact with many other lowly connected miR partners. We revealed hundreds of "target hubs" genes, each potentially subject to massive regulation by dozens of miRs. Interestingly, many of these target hub genes are transcription regulators and they are often related to various developmental processes. The second network consists of miR-TF pairs that coregulate large sets of common targets. We discovered that the network consists of several recurring motifs. Most notably, in a significant fraction of the miR-TF coregulators the TF appears to regulate the miR, or to be regulated by the miR, forming a diversity of feed-forward loops. Together these findings provide new insights on the architecture of the combined transcriptional-post transcriptional regulatory network.

A major challenge in comparative genomics is to understand how phenotypic differences between species are encoded in their genomes. Phenotypic divergence may result from differential transcription of orthologous genes, yet less is known about the involvement of differential translation regulation in species phenotypic divergence. In order to assess translation effects on divergence, we analyzed approximately 2,800 orthologous genes in nine yeast genomes. For each gene in each species, we predicted translation efficiency, using a measure of the adaptation of its codons to the organism's tRNA pool. Mining this data set, we found hundreds of genes and gene modules with correlated patterns of translational efficiency across the species. One signal encompassed entire modules that are either needed for oxidative respiration or fermentation and are efficiently translated in aerobic or anaerobic species, respectively. In addition, the efficiency of translation of the mRNA splicing machinery strongly correlates with the number of introns in the various genomes. Altogether, we found extensive selection on synonymous codon usage that modulates translation according to gene function and organism phenotype. We conclude that, like factors such as transcription regulation, translation efficiency affects and is affected by the process of species divergence.

Many genomic loci contain transcription units on both strands, therefore two oppositely oriented transcripts can overlap. Often, one strand codes for a protein, whereas the transcript from the other strand is non-encoding. Such natural antisense transcripts (NATs) can negatively regulate the conjugated sense transcript. NATs are highly prevalent in a wide range of species--for example, around 15% of human protein-encoding genes have an associated NAT. The regulatory mechanisms by which NATs act are diverse, as are the means to control their expression. Here, we review the current understanding of NAT function and its mechanistic basis, which has been gathered from both individual gene cases and genome-wide studies. In parallel, we survey findings about the regulation of NAT transcription. Finally, we hypothesize that the regulation of antisense transcription might be tailored to its mode of action. According to this model, the observed relationship between the expression patterns of NATs and their targets might indicate the regulatory mechanism that is in action.

Functional redundancies, generated by gene duplications, are highly widespread throughout all known genomes. One consequence of these redundancies is a tremendous increase to the robustness of organisms to mutations and other stresses. Yet, this very robustness also renders redundancy evolutionarily unstable, and it is, thus, predicted to have only a transient lifetime. In contrast, numerous reports describe instances of functional overlaps that have been conserved throughout extended evolutionary periods. More interestingly, many such backed-up genes were shown to be transcriptionally responsive to the intactness of their redundant partner and are up-regulated if the latter is mutationally inactivated. By manual inspection of the literature, we have compiled a list of such "responsive backup circuits" in a diverse list of species. Reviewing these responsive backup circuits, we extract recurring principles characterizing their regulation. We then apply modeling approaches to explore further their dynamic properties. Our results demonstrate that responsive backup circuits may function as ideal devices for filtering nongenetic noise from transcriptional pathways and obtaining regulatory precision. We thus challenge the view that such redundancies are simply leftovers of ancient duplications and suggest they are an additional component to the sophisticated machinery of cellular regulation. In this respect, we suggest that compensation for gene loss is merely a side effect of sophisticated design principles using functional redundancy.

Noise in gene expression is generated at multiple levels, such as transcription and translation, chromatin remodeling and pathway-specific regulation. Studies of individual promoters have suggested different dominating noise sources, raising the question of whether a general trend exists across a large number of genes and conditions. We examined the variation in the expression levels of 43 Saccharomyces cerevisiae proteins, in cells grown under 11 experimental conditions. For all classes of genes and under all conditions, the expression variance was approximately proportional to the mean; the same scaling was observed at steady state and during the transient responses to the perturbations. Theoretical analysis suggests that this scaling behavior reflects variability in mRNA copy number, resulting from random 'birth and death' of mRNA molecules or from promoter fluctuations. Deviation of coexpressed genes from this general trend, including high noise in stress-related genes and low noise in proteasomal genes, may indicate fluctuations in pathway-specific regulators or a differential activation pattern of the underlying gene promoters.

PURPOSE/OBJECTIVE:The aim of this study was to investigate the role of p53 in regulating micro-RNA (miRNA) expression due to its function as a transcription factor. In addition, p53 may also affect other cellular mRNA gene expression at the translational level either via its mediated miRNAs or due to its RNA-binding function. EXPERIMENTAL DESIGN/METHODS:The possible interaction between p53 and miRNAs in regulating gene expression was investigated using human colon cancer HCT-116 (wt-p53) and HCT-116 (null-p53) cell lines. The effect of p53 on the expression of miRNAs was investigated using miRNA expression array and real-time quantitative reverse transcription-PCR analysis. RESULTS:Our investigation indicated that the expression levels of a number of miRNAs were affected by wt-p53. Down-regulation of wt-p53 via small interfering RNA abolished the effect of wt-p53 in regulating miRNAs in HCT-116 (wt-p53) cells. Global sequence analysis revealed that over 46% of the 326 miRNA putative promoters contain potential p53-binding sites, suggesting that some of these miRNAs were potentially regulated directly by wt-p53. In addition, the expression levels of steady-state total mRNAs and actively translated mRNA transcripts were quantified by high-density microarray gene expression analysis. The results indicated that nearly 200 cellular mRNA transcripts were regulated at the posttranscriptional level, and sequence analysis revealed that some of these mRNAs may be potential targets of miRNAs, including translation initiation factor eIF-5A, eIF-4A, and protein phosphatase 1. CONCLUSION/CONCLUSIONS:To the best of our knowledge, this is the first report demonstrating that wt-p53 and miRNAs interact in influencing gene expression and providing insights of how p53 regulates genes at multiple levels via unique mechanisms.