bioRxivBiochemistryPreprint
Basal p53 maintains a distinct transcriptional program from irradiated p53 in tissue, including tumor suppressors
Royce W. ZhouiD, James J. ManfrediiD, Lois Silverman, Ramon E. ParsonsiD
Abstract
The significance of p53s primary and secondary tumor suppressor programs cannot be overstated. A context- and stress-dependent transcription factor, p53 accumulates to mount its most well-characterized programs in response to a variety of stressors, most notably DNA damage. As cells and tissues never exist in a complete absence of stress, a small amount of p53 exists in cells under physiologic stress, detectable by chromatin immunoprecipitation and sequencing, termed basal p53. Recently, we and others have shown that basal p53 is sufficient to regulate tumor suppressor function. Furthermore, others have suggested the possibility that p53 accumulation in response to experimental stress may be dispensable for its tumor suppression. We previously showed basal p53 occupancy and regulation of known tumor suppressor genes, including PTEN and PHLDA3, in non-transformed breast cells, but this study was limited by experimental stress inherent to cell culture. Given the lack of global characterization of the basal p53 landscape under non-malignant physiologic stress in vivo, we utilized a multi-omics approach to define the murine basal p53 epigenome and its transcriptional program in various normal murine tissues. In this study, we observed basal p53 binding to cis regions of multiple tumor suppressor genes in different tissues, of which some showed p53-dependent regulation of their expression, including Phlda3, Bbc3, Xaf1, and itself. Furthermore, the vast majority of basal p53 target genes were not induced upon irradiation, suggesting basal p53 operates a transcriptional program that is largely distinct from its DNA damage response. Similarly, the basal p53 target gene repertoire is unique to each tissue type.
- organism: mouse
- assay: ChIP-seq
- research focus: chromatin & epigenetic regulation
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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