Evolution Of Transcription Factor Binding Sites Research Articles

Prediction and analysis of cis-regulatory elements in Dorsal and Ventral patterning genes of Tribolium castaneum and its comparison with Drosophila melanogaster.

Insect embryonic development and morphology are characterized by their anterior-posterior and dorsal-ventral (DV) patterning. In Drosophila embryos, DV patterning is mediated by a dorsal protein gradient which activates twist and snail proteins, the important regulators of DV patterning. To activate or repress gene expression, some regulatory proteins bind in clusters to their target gene at sites known as cis-regulatory elements or enhancers. To understand how variations in gene expression in different lineages might lead to different phenotypes, it is necessary to understand enhancers and their evolution. Drosophila melanogaster has been widely studied to understand the interactions between transcription factors and the transcription factor binding sites. Tribolium castaneum is an upcoming model animal which is catching the interest of biologists and the research on the enhancer mechanisms in the insect's axes patterning is still in infancy. Therefore, the current study was designed to compare the enhancers of DV patterning in the two insect species. The sequences of ten proteins involved in DV patterning of D. melanogaster were obtained from Flybase. The protein sequences of T. castaneum orthologous to those obtained from D. melanogaster were acquired from NCBI BLAST, and these were then converted to DNA sequences which were modified by adding 20kb sequences both upstream and downstream to the gene. These modified sequences were used for further analysis. Bioinformatics tools (Cluster-Buster and MCAST) were used to search for clusters of binding sites (enhancers) in the modified DV genes. The results obtained showed that the transcription factors in Drosophila melanogaster and Tribolium castaneum are nearly identical; however, the number of binding sites varies between the two species, indicating transcription factor binding site evolution, as predicted by two different computational tools. It was observed that dorsal, twist, snail, zelda, and Supressor of Hairless are the transcriptionfactorsresponsible for the regulation of DV patterning in the two insect species.

Evolution of transcription factor binding through sequence variations and turnover of binding sites.

Variations in noncoding regulatory sequences play a central role in evolution. Interpreting such variations, however, remains difficult even in the context of defined attributes such as transcription factor (TF) binding sites. Here, we systematically link variations in cis-regulatory sequences to TF binding by profiling the allele-specific binding of 27 TFs expressed in a yeast hybrid, in which two related genomes are present within the same nucleus. TFs localize preferentially to sites containing their known consensus motifs but occupy only a small fraction of the motif-containing sites available within the genomes. Differential binding of TFs to the orthologous alleles was well explained by variations that alter motif sequence, whereas differences in chromatin accessibility between alleles were of little apparent effect. Motif variations that abolished binding when present in only one allele were still bound when present in both alleles, suggesting evolutionary compensation, with a potential role for sequence conservation at the motif's vicinity. At the level of the full promoter, we identify cases of binding-site turnover, in which binding sites are reciprocally gained and lost, yet most interspecific differences remained uncompensated. Our results show the flexibility of TFs to bind imprecise motifs and the fast evolution of TF binding sites between related species.

MotifStack for the analysis of transcription factor binding site evolution.

motifStack for the analysis of transcription factor binding site evolution.

Analysis of transcription-factor binding-site evolution by using the Hamilton-Jacobi equations

We investigate a quasi-species mutation-selection model of transcription-factor binding-site evolution. By considering the mesa and the crater fitness landscapes designed to describe these binding sites and point mutations, we derive an evolution equation for the population distribution of binding sequences. In the long-length limit, the evolution equation is replaced by a Hamilton-Jacobi equation which we solve for the stationary state solution. From the stationary solution, we derive the population distributions and find that an error threshold, separating populations in which the binding site does or does not evolve, only exists for certain values of the fitness parameters. A phase diagram in this parameter space is derived and shows a critical line below which no error threshold exists. We also investigate the evolution of multiple binding sites for the same transcription factor. For two binding sites, we perform an analysis similar to that for a single site and determine a phase diagram showing different phases with both, one, or no binding sites selected. In the phase diagram, the phase boundary between the one-or-two selected site phases is qualitatively different for the mesa and the crater fitness landscapes. As fitness benefits for a second bound transcription factor tend to zero, the minimum mutation rate at which the two-site phase occurs diverges in the mesa landscape whereas the mutation rate at the phase boundary tends to a finite value for the crater landscape.

Imogene: identification of motifs and cis-regulatory modules underlying gene co-regulation

Cis-regulatory modules (CRMs) and motifs play a central role in tissue and condition-specific gene expression. Here we present Imogene, an ensemble of statistical tools that we have developed to facilitate their identification and implemented in a publicly available software. Starting from a small training set of mammalian or fly CRMs that drive similar gene expression profiles, Imogene determines de novo cis-regulatory motifs that underlie this co-expression. It can then predict on a genome-wide scale other CRMs with a regulatory potential similar to the training set. Imogene bypasses the need of large datasets for statistical analyses by making central use of the information provided by the sequenced genomes of multiple species, based on the developed statistical tools and explicit models for transcription factor binding site evolution. We test Imogene on characterized tissue-specific mouse developmental CRMs. Its ability to identify CRMs with the same specificity based on its de novo created motifs is comparable to that of previously evaluated ‘motif-blind’ methods. We further show, both in flies and in mammals, that Imogene de novo generated motifs are sufficient to discriminate CRMs related to different developmental programs. Notably, purely relying on sequence data, Imogene performs as well in this discrimination task as a previously reported learning algorithm based on Chromatin Immunoprecipitation (ChIP) data for multiple transcription factors at multiple developmental stages.

Diversification at Transcription Factor Binding Sites within a Species and the Implications for Environmental Adaptation

Evolution of new cellular functions can be achieved both by changes in protein coding sequences and by alteration of expression patterns. Variation of expression may lead to changes in cellular function with relatively little change in genomic sequence. We therefore hypothesize that one of the first signals of functional divergence should be evolution of transcription factor-binding sites (TFBSs). This adaptation should be detectable as substantial variation in the TFBSs of alleles. New data sets allow the first analyses of intraspecies variation from large number of whole-genome sequences. Using data from the Saccharomyces Genome Resequencing Project, we have analyzed variation in TFBSs. We find a large degree of variation both between these closely related strains and between pairs of duplicated genes. There is a correlation between changes in promoter regions and changes in coding sequences, indicating a coupling of changes in expression and function. We show that 1) the types genes with diverged promoters vary between strains from different environments and 2) that patterns of divergence in promoters consistent with positive selection are detectable in alleles between strains and on duplicate promoters. This variation is likely to reflect adaptation to each strain's natural environment. We conclude that, even within a species, we detect signs of selection acting on promoter regions that may act to alter expression patterns. These changes may indicate functional innovation in multiple genes and across the whole genome. Change in function could represent adaptation to the environment and be a precursor to speciation.

Evidence of association between Nucleosome Occupancy and the Evolution of Transcription Factor Binding Sites in Yeast

BackgroundDivergence of transcription factor binding sites is considered to be an important source of regulatory evolution. The associations between transcription factor binding sites and phenotypic diversity have been investigated in many model organisms. However, the understanding of other factors that contribute to it is still limited. Recent studies have elucidated the effect of chromatin structure on molecular evolution of genomic DNA. Though the profound impact of nucleosome positions on gene regulation has been reported, their influence on transcriptional evolution is still less explored. With the availability of genome-wide nucleosome map in yeast species, it is thus desirable to investigate their impact on transcription factor binding site evolution. Here, we present a comprehensive analysis of the role of nucleosome positioning in the evolution of transcription factor binding sites.ResultsWe compared the transcription factor binding site frequency in nucleosome occupied regions and nucleosome depleted regions in promoters of old (orthologs among Saccharomycetaceae) and young (Saccharomyces specific) genes; and in duplicate gene pairs. We demonstrated that nucleosome occupied regions accommodate greater binding site variations than nucleosome depleted regions in young genes and in duplicate genes. This finding was confirmed by measuring the difference in evolutionary rates of binding sites in sensu stricto yeasts at nucleosome occupied regions and nucleosome depleted regions. The binding sites at nucleosome occupied regions exhibited a consistently higher evolution rate than those at nucleosome depleted regions, corroborating the difference in the selection constraints at the two regions. Finally, through site-directed mutagenesis experiment, we found that binding site gain or loss events at nucleosome depleted regions may cause more expression differences than those in nucleosome occupied regions.ConclusionsOur study indicates the existence of different selection constraint on binding sites at nucleosome occupied regions than at the nucleosome depleted regions. We found that the binding sites have a different rate of evolution at nucleosome occupied and depleted regions. Finally, using transcription factor binding site-directed mutagenesis experiment, we confirmed the difference in the impact of binding site changes on expression at these regions. Thus, our work demonstrates the importance of composite analysis of chromatin and transcriptional evolution.

The Consequences of Base Pair Composition Biases for Regulatory Network Organization in Prokaryotes

Given the dramatic variation in guanine-cytosine (GC) content observed in prokaryotes, from approximately 20% to approximately 75% GC, one wonders if these extreme biases in base pair composition affect the evolution of transcription factor-binding sites (BS). This letter shows that, along the wide range of GC content variation in bacteria, bacterial BS keep a high frequency of AT bases, roughly independently of the background (BG) base pair composition of intergenic regions. As a result, the equilibrium base pair frequencies of BS depart the most from those of BS DNA in GC-rich genomes. This not only implies a higher specificity but also a higher coding barrier for BS in GC-rich genomes. In accordance, we observe that the average percentage of divergently transcribed regions increases with the GC content of the genome, suggesting the use of a more efficient coding strategy.

Evolutionary population genetics of promoters: Predicting binding sites and functional phylogenies

We study the evolution of transcription factor-binding sites in prokaryotes, using an empirically grounded model with point mutations and genetic drift. Selection acts on the site sequence via its binding affinity to the corresponding transcription factor. Calibrating the model with populations of functional binding sites, we verify this form of selection and show that typical sites are under substantial selection pressure for functionality: for cAMP response protein sites in Escherichia coli, the product of fitness difference and effective population size takes values 2NDeltaF of order 10. We apply this model to cross-species comparisons of binding sites in bacteria and obtain a prediction method for binding sites that uses evolutionary information in a quantitative way. At the same time, this method predicts the functional histories of orthologous sites in a phylogeny, evaluating the likelihood for conservation or loss or gain of function during evolution. We have performed, as an example, a cross-species analysis of E. coli, Salmonella typhimurium, and Yersinia pseudotuberculosis. Detailed lists of predicted sites and their functional phylogenies are available.