Non-coding regulatory SNPs in transcription factor binding sites can have significant biological consequences (1
). We carried out a comprehensive genome-wide bioinformatics search using a unique prediction model (BPWM), to identify human SNPs in validated and putative p53-targeted sequences that were predicted to alter p53 binding following exposure to DNA-damaging agents. The selected SNPs were evaluated using the MAPD binding assay and gene expression analysis to determine the functional impact of each variant. We employed ChIP-Seq analysis to confirm p53 sequence-specific binding in cultured human cells in response to doxorubicin, a DNA-damaging agent. To our knowledge, this represents the first study that examines properties of SNPs that co-locate with ChIP-seq peaks. The allele-specific differences observed for p53 target genes following exposure to doxorubicin support the hypothesis that genetic variation in non-coding regulatory sequences may impact risk in environmentally induced diseases such as cancer (1
). Our findings also demonstrate that this bioinformatics strategy can identify SNPs in gene regulatory regions that alter p53–DNA binding and gene expression. In addition, we believe regulatory SNPs that affect other transcription factors or DNA binding proteins can be identified and evaluated using a similar approach.
Many of the sequences we identified have not been experimentally validated as p53REs. Our results, using MAPD, gene expression and ChIP-seq methods, demonstrate that p53 binds putative polymorphic REs near ADARB1, HMOX1, PSMA6
in cultured human cells, which suggests that these genes are novel, previously unidentified components of the p53 transcriptional network. Several polymorphic sequences that were tested are associated with genes that have tumor suppressive activity, play roles in cell cycle regulation, or function in other cellular processes associated with p53-mediated signaling pathways. ADARB1
is a member of the adenosine deaminase family, which plays important roles during developmental processes. This RNA-editing enzyme is suggested to have negative effects on the development and progression of brain cancer (36
is a member of the peptidase T1A family and a subunit of the proteasome 20S catalytic core. The core is involved in cell-cycle regulation and differentiation and is expressed in malignant cells (37
is involved in the development of hepatocellular carcinoma (39
) and breast cancer (38
is a ligand for a member of the tumor necrosis factor receptor superfamily, which stimulates the proliferation of T cells and triggers apoptosis of various tumor cells (40
is an interferon-inducible protein and is a p53 target gene. TRIM22
has antiproliferative effects in leukemic cells (42
) and is suggested to play lineage-specific roles during hematopoietic differentiation (43
is the catalytic subunit of the NEDD8
-activing enzyme. NEDD8
is involved in the regulation of cell division and cell signaling. UBA3
is essential for the antiproliferative activity of an antiestrogen drug that is targeted against estrogen receptor alpha positive breast cancer cells (44
In this work, we have used de novo approaches to identify and test polymorphic REs that alter p53–DNA binding. These SNPs may also alter cellular stress responses and increase disease susceptibility in vivo. Our results further illustrate the significance of the conserved C and G in the p53-DNA binding motif. We demonstrate that this observation is apparent in both moderate (ADARB1 and TLR8) and low (PMAIP1 and RRM1) affinity p53 binding sites, which suggests that sequence variations involving these nucleotides will have the most significant biological consequences. In contrast, SNPs that alter nucleotides outside of the conserved C and G may have little impact and produce no obvious phenotypic effects.
In this study, we identified SNPs that alter p53-RE binding and impact gene expression; however, the functional, evolutionary and risk implications of these effects are not always obvious. For example, we observe occasionally that the less common, minor allele is the predicted strong allele, displaying both stronger binding (e.g. rs1077667, TNFSF14
; rs1048990, PSMA6
) and stronger transactivation while the common (i.e. ancestral allele, shared with other primates) allele displays weaker binding. This suggests that the recently created, stronger allele may have some selective advantage in human lineages that have it. However, selective advantage (positive selection) or disadvantage (purifying selection) is related to reproductive success, while cancer risk is related to somatic processes that impact a post-reproductive disease outcome. Although it is unclear whether the creation of these specific strong-binding alleles in the human population affects physiology, survival or risk, transcriptional pathways can evolve in this way (45–47
). Menendez et al
) have suggested that an SNP may create novel binding sites and connect transcriptional pathways. The impact of RE polymorphisms is further complicated by the possibility that specific p53RE ‘WW’ dinucleotide combinations can influence whether p53 activates or represses gene expression (48
). Thus, an SNP that occurs in a RE from which p53 represses transcription could decrease p53 binding and thereby increase gene expression. This scenario may explain the increased expression of PMAIP1 in cell lines homozygous for the weak allele. Evaluating SNPs in p53REs that are predicted to repress transactivation would be of great interest.
The p53 protein plays key roles during the cellular stress response (12
), which can be influenced by cell type (30
). A number of reports have demonstrated that different stress-inducing agents trigger a variety of p53 post-translational modifications (49
) and differential transactivation of target genes (51
). Two recent publications disagree with regard to whether different agents produce different p53 occupancy profiles at native binding sites in cells. Shaked et al
), using ChIP-on-chip, observed that global patterns of p53 occupancy differed very little among gamma irradiated, DOXO, 5-FU or UV treated HCT116 and U2OS cell lines. Millau et al
) using a more sensitive technique, observed unique p53 occupancy patterns over time at different p21 response elements following treatment with 5-FU, Nutlin-3, UV and gamma radiation. The MAPD assay evaluates the p53 binding step and provides high resolution and discrimination of small binding differences. The present findings using DOXO and IR in lymphoblastoid and U2OS osteosarcoma cells clearly demonstrate that very similar p53 binding patterns are produced from p53 activated under all experimental conditions tested. Thus, it is likely that other features in the transcription process, such as the chromatin environment or stress-specific cofactors, may contribute to cell type- and treatment-specific p53 binding and subsequent transactivation in cells (51
). In addition, we demonstrate for the first time that individual SNPs produced similar effects on p53–DNA binding regardless of the cell type or stimulus used for activation.
The present study suggests that sequence variation in p53 binding sites can impact binding and potentially modify p53-mediated responses to DNA-damaging agents. The MAPD binding assay is a useful way to estimate the functional impact of nucleotide changes in target binding sites and could be applied to other transcription factors. Developing quantitative binding data for many regulatory elements may allow us to elucidate the impact of polymorphic variation on transcriptional networks.