Evolution of Transcription Factor Binding Sites in Mammalian Gene Regulatory Regions: Handling Counterintuitive Results

A transgenic reporter mouse model for in vivo assessment of retinoic acid receptor transcriptional activation

Background: Vitamin A is essential for a wide range of life processes throughout embryogenesis to adult life. With the aim of developing an in vivo model to monitor retinoic acid receptor (RAR) transactivation real-time in intact animals, we generated transgenic mice carrying a luciferase (luc) reporter gene under the control of retinoic acid response elements (RAREs) consisting of three copies of a direct repeat with five spacing nucleotides (DR5). Methods: Transgenic mice carrying a RARE dependent luciferase reporter flanked with insulator sequence were generated by pronuclear injection. RARE dependent luciferase activity was detected by in vivo imaging or in tissue extracts following manipulations with RAR/retinoid X receptor (RXR) agonists, RAR antagonists or in vitamin A deficient mice. Results: We found a strong induction of luciferase activity in a time and dose dependent manner by retinoic acid as well as RAR agonists, but not by the RXR agonist (using n=4-6 per group; 94 mice). In addition, luciferase activity was strongly reduced in vitamin A-deficient mice (n=6-9; 30 mice). These observations confirm that luciferase activity was controlled by RAR activation in the RARE-luc mouse. Luciferase activity was detectable in various organs, with high activity especially in brain and testis, indicating strong retinoid signalling in these tissues. Conclusion: The RARE-luc transgenic mice, which enabled real-time in vivo assessment of RAR activation, will be useful in understanding the normal physiology of vitamin A, the role of retinoid signalling in pathologies as well as to evaluate pharmacological ligands for RARs.

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.

Evolutionary rewiring of regulatory networks contributes to phenotypic differences between human and mouse orthologous genes

Mouse models have been engineered to reveal the biological mechanisms of human diseases based on an assumption. The assumption is that orthologous genes underlie conserved phenotypes across species. However, genetically modified mouse orthologs of human genes do not often recapitulate human disease phenotypes which might be due to the molecular evolution of phenotypic differences across species from the time of the last common ancestor. Here, we systematically investigated the evolutionary divergence of regulatory relationships between transcription factors (TFs) and target genes in functional modules, and found that the rewiring of gene regulatory networks (GRNs) contributes to the phenotypic discrepancies that occur between humans and mice. We confirmed that the rewired regulatory networks of orthologous genes contain a higher proportion of species-specific regulatory elements. Additionally, we verified that the divergence of target gene expression levels, which was triggered by network rewiring, could lead to phenotypic differences. Taken together, a careful consideration of evolutionary divergence in regulatory networks could be a novel strategy to understand the failure or success of mouse models to mimic human diseases. To help interpret mouse phenotypes in human disease studies, we provide quantitative comparisons of gene expression profiles on our website (http://sbi.postech.ac.kr/w/RN).

Contextual data integration in drug discovery

INTRODUCTION

The interpretation of high-throughput profiling data depends on the pathway analysis database. Currently, pathway analysis often has to rely on a set of interactions and pathways measured in every possible human tissue, due to insufficient knowledge about interactions and pathways in the context of the profiling experiment. However, a recent global scale analysis of human tissue proteomes and interactomes reveals significant differences among tissues, suggesting that interaction and pathway data that are used out of biological context are the major source of inaccuracies and noise in the analysis of profiling data.

AREAS COVERED

In this review, the major classes of biological context used for experimental detection of molecular interactions and pathways in molecular biology are described. Furthermore, the author reviews methods for predicting biological interactions in order to evaluate the applicability of various contextual interaction data in pathway analysis. Using the results from recent publications that study large-scale tissue composition, the article provides an estimation of the gain in pathway analysis accuracy if only the interactions predicted for the context of a molecular profiling experiment are used, relative to the analysis performed with a context-independent knowledge base.

EXPERT OPINION

It is of the author's opinion that the major source of inaccuracy in pathway analysis is the lack of knowledge about tissue-specific transcriptional regulation. It is therefore suggested that the accuracy of the analysis can be substantially improved if only context-specific interactions and pathways are used for interpretation.

The transposon-driven evolutionary origin and basis of histone deacetylase functions and limitations in disease prevention

Histone deacetylases (HDACs) are homologous to prokaryotic enzymes that removed acetyl groups from non-histone proteins before the evolution of eukaryotic histones. Enzymes inherited from prokaryotes or from a common ancestor were adapted for histone deacetylation, while useful deacetylation of non-histone proteins was selectively retained. Histone deacetylation served to prevent transcriptions with pathological consequences, including the expression of viral DNA and the deletion or dysregulation of vital genes by random transposon insertions. Viruses are believed to have evolved from transposons, with transposons providing the earliest impetus of HDAC evolution. Because of the wide range of genes potentially affected by transposon insertions, the range of diseases that can be prevented by HDACs is vast and inclusive. Repressive chromatin modifications that may prevent transcription also include methylation of selective lysine residues of histones H3 and H4 and the methylation of selective DNA cytosines following specific histone lysine methylation. Methylation and acetylation of individual histone residues are mutually exclusive. While transposons were sources of disease to be prevented by HDAC evolution, they were also the source of numerous and valuable coding and regulatory sequences recruited by “molecular domestication.” Those sequences contribute to evolved complex transcription regulation in which components with contradictory effects, such as HDACs and HATs, may be coordinated and complementary. Within complex transcription regulation, however, HDACs remain ineffective as defense against some critical infectious and non-infectious diseases because evolutionary compromises have rendered their activity transient.