Functional evolution of the p53 regulatory network through its target response elements Anil G. Jegga*†, Alberto Inga‡, Daniel Menendez§, Bruce J. Aronow*†, and Michael A. Resnick§¶ *Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229-3039; †Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH 45267; ‡Molecular Mutagenesis Unit, National Institute for Cancer Research, 16132 Genoa, Italy; and §Laboratory Molecular Genetics, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC 27709 Edited by Eviatar Nevo, University of Haifa, Haifa, Israel, and approved December 5, 2007 (received for review May 18, 2007) Transcriptional network evolution is central to the development of tive functional consequences of diverged REs on promoter complex biological systems. Networks can evolve through varia- outputs. tion of master regulators and/or by changes in regulation of genes We have addressed evolution of REs that provide direct tran- within networks. To gain insight into meaningful evolutionary scriptional control by the sequence-specific TF p53, a tumor differences in large networks, it is essential to address the func- suppressor gene and master regulator of cellular stress responses. tional consequences of sequence differences in response elements The study focuses on functional evolution of p53 REs along with (REs) targeted by transcription factors. Using a combination of sequence evolution and draws on earlier investigations of p53 custom bioinformatics and multispecies alignment of promoter transactivation capacity and the effects of subtle variations in RE regions, we investigated the functional evolution of REs in terms sequences, such as single nucleotide polymorphisms (SNPs) (9, 10). of responsiveness to the sequence-specific transcription factor p53, Limited to human and mouse species, the work also utilizes a tumor suppressor and master regulator of stress responses. We previous analyses of transactivation potentials by the orthologous identified REs orthologous to known p53 targets in human and p53 proteins (11). We combined a customized bioinformatics rodent cells or alternatively REs related to the established p53 approach for phylogenetic footprinting and motif scanning with consensus. The orthologous REs were assigned p53 transactivation predictions of functionality (i.e., transactivation potential in terms capabilities based on rules determined from model systems, and a of ‘‘on’’ or ‘‘off’’ and level of response) for p53 REs based on a set functional heat map was developed to visually summarize conser- of described RE rules (11). This led to a new functional heat map vation of sequence and relative level of responsiveness to p53 for representation of RE functionality and sequence variation within 47 REs in 14 species. Individual REs exhibited marked differences in and across species. There is widespread evolutionary turnover of transactivation potentials and widespread evolutionary turnover. p53 TF binding sites (TFBS) that is not fully predicted by simple Functional differences were often not predicted from consensus sequence analysis. Importantly, the p53 target genes involved in sequence evaluations. Of the established human p53 REs analyzed, DNA-associated metabolic activities in primates appear to have 91% had sequence conservation in at least one nonprimate species been incorporated into the p53 network after branching the rodent compared with 67.5% for functional conservation. Surprisingly, and primate evolutionary paths. there was almost no conservation of functional REs for genes Results involved in DNA metabolism or repair between humans and Functional and Sequence Conservation of p53 REs Between Species. rodents, suggesting important differences in p53 stress responses We addressed evolution of the p53 master regulatory network and cancer development. through an analysis of 47 previously validated human and mouse p53 target REs. Specifically, we investigated the extent to which ene expression largely depends on combinatorial interac- functional variation tracks with sequence variation. In fact, the Gtions of transcription machineries with regulatory modules consensus p53 RE is degenerate, and our previous studies revealed and is influenced by changes in chromatin structure (1–3). that RE function was weakly predicted by position weight matrix Sequence-specific transcription factors (TFs) can modulate ex- (PWM) sequence evaluation (12). Functionality in the present pression of networks of target genes through dynamic interac- study was evaluated from a combination of sequence inspection, tions with unique cis-regulatory response elements (REs). Tran- RE rules [Methods and supporting information (SI) Table 1], and scription network evolution is an important genetic component direct determination of p53-mediated transactivation capacity in in phenotypic diversification between species. Transcriptional yeast and mouse cells. networks can transevolve through variation of master regulators Conservation was examined in up to 14 species, depending on or their targets or they can cis-evolve by changes in regulation of retrievable information. Borrowing microarray expression data target genes. Cis-regulatory evolution, which can arise from representations, the functional and sequence conservation are point mutations, small deletions and additions, or large rear- presented together in a heat map format that presents levels of rangements of promoter regions, may be a major driver of functionality (predicted and/or measured) of the REs, as de- species phenotypic differences (4). However, sequence-based scribed in Fig. 1. Sequence conservation of REs is indicated by analysis of phylogenetic conservation within regulatory regions symbols (see SI Tables 1 and 2 for supporting data). The has limitations because of an overall promoter organization that is less conserved compared with coding sequences. Although conservation of cis-regulatory sequence motifs may indicate Author contributions: A.G.J., A.I., and D.M. contributed equally to this work; A.G.J., A.I., D.M., B.J.A., and M.A.R. designed research; A.G.J., A.I., and D.M. performed research; preserved function within transcriptional networks, there are A.G.J., A.I., D.M., B.J.A., and M.A.R. analyzed data; and A.G.J., A.I., D.M., B.J.A., and M.A.R. few comparative studies that address quantitatively the evolution wrote the paper. of these regulatory interactions and examine the actual func- The authors declare no conflict of interest. tionality of diverged REs in terms of ability to recruit TFs and This article is a PNAS Direct Submission. mediate changes in transcription rates of associated genes (5–8). ¶To whom correspondence should be addressed. E-mail: [email protected]. The commonly observed large variability in individual REs for This article contains supporting information online at www.pnas.org/cgi/content/full/ a given TF within an organism, as exemplified by degenerate 0704694105/DC1. consensus sequences, challenges the ability to predict quantita- © 2008 by The National Academy of Sciences of the USA 944–949 ͉ PNAS ͉ January 22, 2008 ͉ vol. 105 ͉ no. 3 www.pnas.org͞cgi͞doi͞10.1073͞pnas.0704694105 Downloaded by guest on September 28, 2021 Fig. 1. Functional heat map depiction of p53 RE conservation, where relative function is conveyed in a heat map format, and sequence conservation is described by symbols. A modified microarray heat map graphic style was used to represent the predicted transactivation potentials of p53 REs. The estimated strength is relative to the strongly transactivated human p21 RE-5Ј, where red is comparable, and yellow, green, and gray correspond to decreasing transactivation capabilities. Using human or mouse (red gene symbols) p53 REs as reference sequences/seeds (filled triangle), the orthologous sequences from 13 other species (depending on retrievable sequence) were extracted and sequence conservation based on number of mismatches (MM) relative to seed RE was determined (see SI Table 2). * indicates extent of ‘‘sequence conservation relative to the reference sequence’’ as depicted by the size of the 0; X indicates no conservation. A black box indicates no sequence information was available in the corresponding region of the examined species. For each RE, functionality was assigned based on a set of rules derived from yeast-based assays summarized in the text and in SI Table 1 (# indicates reference sequences not experimentally tested in yeast). Species are ordered according to the evolutionary tree, and percentage of conservation of the DNA binding domain of p53 proteins is indicated (hedgehog p53 sequence information is currently not available currently). The color code values for functionality and symbol codes for sequence conservation are indicated in the lower part of the figure. EVOLUTION reference/seed human or mouse sequences for cross-species predicted for only 67.5% (27 of 40) of the human REs. Com- comparisons are shown as filled triangles. Most of these REs parisons were not possible for three seed REs considered have been measured directly for transactivation. Predictions of ‘‘nonresponsive to p53.’’ Conservation of RE functionality was RE functionalities (‘‘nonresponsive’’ to ‘‘high’’) are based on clearly less than sequence conservation (high to poor range) previous findings (10–15) (J. Jordan, D.M., A.I., M. Nourredine, (P ϭ 0.013, Fisher’s exact test). Within primates, a significant