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Temporal gene regulation by p53 is associated with the rotational setting of its binding sites in nucleosomes.

ABSTRACT: The tumor suppressor protein p53 is a DNA-binding transcription factor (TF) that, once activated, coordinates the expression of thousands of target genes. Increased p53 binding to gene promoters occurs shortly after p53 activation. Intriguingly, gene transcription exhibits differential kinetics with some genes being induced early (early genes) and others being induced late (late genes). To understand pre-binding factors contributing to the temporal gene regulation by p53, we performed time-course RNA sequencing experiments in human colon cancer cell line HCT116 treated with fluorouracil to identify early and late genes. Published p53 ChIP fragments co-localized with the early or late genes were used to uncover p53 binding sites (BS). We demonstrate that the BS associated with early genes are clustered around gene starts with decreased nucleosome occupancy. DNA analysis shows that these BS are likely exposed on nucleosomal surface if wrapped into nucleosomes, thereby facilitating stable interactions with and fast induction by p53. By contrast, p53 BS associated with late genes are distributed uniformly across the genes with increased nucleosome occupancy. Predicted rotational settings of these BS show limited accessibility. We therefore propose a hypothetical model in which the BS are fully, partially or not accessible to p53 in the nucleosomal context. The partial accessibility of the BS allows subunits of a p53 tetramer to bind, but the resulting p53-DNA complex may not be stable enough to recruit cofactors, which leads to delayed induction. Our work highlights the importance of DNA conformations of p53 BS in gene expression dynamics.

SUBMITTER: Freewoman JM

PROVIDER: S-EPMC8098069 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:In computational methods, position weight matrices (PWMs) are commonly applied for transcription factor binding site (TFBS) prediction. Although these matrices are more accurate than simple consensus sequences to predict actual binding sites, they usually produce a large number of false positive (FP) predictions and so are impoverished sources of information. Several studies have employed additional sources of information such as sequence conservation or the vicinity to transcription start sites to distinguish true binding regions from random ones. Recently, the spatial distribution of modified nucleosomes has been shown to be associated with different promoter architectures. These aligned patterns can facilitate DNA accessibility for transcription factors. We hypothesize that using data from these aligned and periodic patterns can improve the performance of binding region prediction. In this study, we propose two effective features, "modified nucleosomes neighboring" and "modified nucleosomes occupancy", to decrease FP in binding site discovery. Based on these features, we designed a logistic regression classifier which estimates the probability of a region as a TFBS. Our model learned each feature based on Sp1 binding sites on Chromosome 1 and was tested on the other chromosomes in human CD4+T cells. In this work, we investigated 21 histone modifications and found that only 8 out of 21 marks are strongly correlated with transcription factor binding regions. To prove that these features are not specific to Sp1, we combined the logistic regression classifier with the PWM, and created a new model to search TFBSs on the genome. We tested the model using transcription factors MAZ, PU.1 and ELF1 and compared the results to those using only the PWM. The results show that our model can predict Transcription factor binding regions more successfully. The relative simplicity of the model and capability of integrating other features make it a superior method for TFBS prediction.

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Temporal gene regulation by p53 is associated with the rotational setting of its binding sites in nucleosomes.

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