Co-evolution of transcription factors and their targets depends on mode of regulation

BACKGROUND: Differences in the transcription regulation network are at the root of much of the phenotypic variation observed among organisms. These differences may be achieved either by changing the repertoire of regulators and/or their targets, or by rewiring the network. Following these changes and studying their logic is crucial for understanding the evolution of regulatory networks. RESULTS: We use the well characterized transcription regulatory network of Escherichia coli K12 and follow the evolutionary changes in the repertoire of regulators and their targets across a large number of fully sequenced γ-proteobacteria. By focusing on close relatives of E. coli K12, we study the dynamics of the evolution of transcription regulation across a relatively short evolutionary timescale. We show significant differences in the evolution of repressors and activators. Repressors are only lost from a genome once their targets have themselves been lost, or once the network has significantly rewired. In contrast, activators are often lost even when their targets remain in the genome. As a result, E. coli K12 repressors that regulate many targets are rarely absent from organisms that are closely related to E. coli K12, while activators with a similar number of targets are often absent in these organisms. CONCLUSION: We demonstrate that the mode of regulation exerted by transcription factors has a strong effect on their evolution. Repressors co-evolve tightly with their target genes. In contrast, activators can be lost independently of their targets. In fact, loss of an activator can lead to efficient shutdown of an unnecessary pathway

Relative predicted protein levels of functionally associated proteins are conserved across organisms

We show that the predicted protein levels of functionally related proteins change in a coordinated fashion over many unicellular organisms. For each protein, we created a profile containing a protein abundance measure in each of a set of organisms. We show that for functionally related proteins these profiles tend to be correlated. Using the Codon Adaptation Index as a predictor of protein abundance in 48 unicellular organisms, we demonstrated this phenomenon for two types of functional relations: for proteins that physically interact and for proteins involved in consecutive steps within a metabolic pathway. Our results suggest that the protein abundance levels of functionally related proteins co-evolve

Reduced Polymorphism in Domains Involved in Protein-Protein Interactions

Genome sequencing of various individuals or isolates of the same species allows studying the polymorphism level of specific proteins and protein domains. Here we ask whether domains that are known to be involved in mediating protein-protein interactions show lower polymorphism than other domains. To this end we take advantage of a recent genome sequence dataset of 39 Saccahromyces cerevisiae strains and the experimentally determined protein interaction network of the laboratory strain. We analyze the polymorphism in domain residues involved in interactions at various levels of resolution, depending on their likelihood to be interaction mediators. We find that domains involved in interactions are less polymorphic than other domains. Furthermore, as the likelihood of a residue to be involved in interaction increases, its polymorphism decreases. Our results suggest that purifying selection operates on domains capable of mediating protein interactions to maintain their function

Evolutionary conservation of domain-domain interactions

BACKGROUND: Recently, there has been much interest in relating domain-domain interactions (DDIs) to protein-protein interactions (PPIs) and vice versa, in an attempt to understand the molecular basis of PPIs. RESULTS: Here we map structurally derived DDIs onto the cellular PPI networks of different organisms and demonstrate that there is a catalog of domain pairs that is used to mediate various interactions in the cell. We show that these DDIs occur frequently in protein complexes and that homotypic interactions (of a domain with itself) are abundant. A comparison of the repertoires of DDIs in the networks of Escherichia coli, Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens shows that many DDIs are evolutionarily conserved. CONCLUSION: Our results indicate that different organisms use the same 'building blocks' for PPIs, suggesting that the functionality of many domain pairs in mediating protein interactions is maintained in evolution

Ab Initio Prediction of Transcription Factor Targets Using Structural Knowledge

Current approaches for identification and detection of transcription factor binding sites rely on an extensive set of known target genes. Here we describe a novel structure-based approach applicable to transcription factors with no prior binding data. Our approach combines sequence data and structural information to infer context-specific amino acid–nucleotide recognition preferences. These are used to predict binding sites for novel transcription factors from the same structural family. We demonstrate our approach on the Cys(2)His(2) Zinc Finger protein family, and show that the learned DNA-recognition preferences are compatible with experimental results. We use these preferences to perform a genome-wide scan for direct targets of Drosophila melanogaster Cys(2)His(2) transcription factors. By analyzing the predicted targets along with gene annotation and expression data we infer the function and activity of these proteins

Assigning functions to genes: identification of S-phase expressed genes in Leishmania major based on post-transcriptional control elements

Assigning functions to genes is one of the major challenges of the post-genomic era. Usually, functions are assigned based on similarity of the coding sequences to sequences of known genes, or by identification of transcriptional cis-regulatory elements that are known to be associated with specific pathways or conditions. In trypanosomatids, where regulation of gene expression takes place mainly at the post-transcriptional level, new approaches for function assignment are needed. Here we demonstrate the identification of novel S-phase expressed genes in Leishmania major, based on a post-transcriptional control element that was recognized in Crithidia fasciculata as involved in the cell cycle-dependent expression of several nuclear and mitochondrial S-phase expressed genes. Hypothesizing that a similar regulatory mechanism is manifested in L.major, we have applied a computational search for similar control elements in the genome of L.major. Our computational scan yielded 132 genes, of which 33% are homologues of known DNA metabolism genes and 63% lack any annotation. Experimental testing of seven of these genes revealed that their mRNAs cycle throughout the cell cycle, reaching a maximum level during S-phase or just prior to it. It is suggested that screening for post-transcriptional control elements associated with a specific function provides an efficient method for assigning functions to trypanosomatid genes

A Functional Selection Model Explains Evolutionary Robustness Despite Plasticity in Regulatory Networks

Evolutionary rewiring of regulatory networks is an important source of diversity among species. Previous evidence suggested substantial divergence of regulatory networks across species. However, systematically assessing the extent of this plasticity and its functional implications has been challenging due to limited experimental data and the noisy nature of computational predictions. Here, we introduce a novel approach to study cis-regulatory evolution, and use it to trace the regulatory history of 88 DNA motifs of transcription factors across 23 Ascomycota fungi. While motifs are conserved, we find a pervasive gain and loss in the regulation of their target genes. Despite this turnover, the biological processes associated with a motif are generally conserved. We explain these trends using a model with a strong selection to conserve the overall function of a transcription factor, and a much weaker selection over the specific genes it targets. The model also accounts for the turnover of bound targets measured experimentally across species in yeasts and mammals. Thus, selective pressures on regulatory networks mostly tolerate local rewiring, and may allow for subtle fine-tuning of gene regulation during evolution

Clustering and conservation patterns of human microRNAs

MicroRNAs (miRNAs) are ∼22 nt-long non-coding RNA molecules, believed to play important roles in gene regulation. We present a comprehensive analysis of the conservation and clustering patterns of known miRNAs in human. We show that human miRNA gene clustering is significantly higher than expected at random. A total of 37% of the known human miRNA genes analyzed in this study appear in clusters of two or more with pairwise chromosomal distances of at most 3000 nt. Comparison of the miRNA sequences with their homologs in four other organisms reveals a typical conservation pattern, persistent throughout the clusters. Furthermore, we show enrichment in the typical conservation patterns and other miRNA-like properties in the vicinity of known miRNA genes, compared with random genomic regions. This may imply that additional, yet unknown, miRNAs reside in these regions, consistent with the current recognition that there are overlooked miRNAs. Indeed, by comparing our predictions with cloning results and with identified miRNA genes in other mammals, we corroborate the predictions of 18 additional human miRNA genes in the vicinity of the previously known ones. Our study raises the proportion of clustered human miRNAs that are <3000 nt apart to 42%. This suggests that the clustering of miRNA genes is higher than currently acknowledged, alluding to its evolutionary and functional implications