Dataset Information

The RNA-binding protein QKI5 is a direct target of C/EBP? and delays macrophage differentiation.

ABSTRACT: Differentiated macrophages are essential for the innate immune system; however, the molecular mechanisms underlying the generation of macrophages remain largely unknown. Here we show that the RNA-binding protein QKI, mainly QKI-5, is transcriptionally activated in the early differentiated monocytic progenitors when CCAAT/enhancer-binding protein (C/EBP) ? is expressed. The forced expression of C/EBP? increases the endogenous expression of QKI. Chromatin immunoprecipitation analysis and reporter assays further confirm that C/EBP? activates the transcription of QKI, primarily by binding to the distal C/EBP?-binding site. Blocking the induction of QKI using RNA interference enhances the expression of endogenous CSF1R and facilitates macrophage differentiation. Further study of the mechanism reveals that QKI-5 facilitates the degradation of CSF1R mRNA by interacting with the distal QRE in the 3' untranslated region. In summary, we show that in committed macrophage progenitors, C/EBP?-activated QKI-5 negatively regulates macrophage differentiation by down-regulating CSF1R expression, forming a negative feedback loop during macrophage differentiation.

SUBMITTER: Fu H

PROVIDER: S-EPMC3338430 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

The RNA-binding protein QKI5 is a direct target of C/EBPα and delays macrophage differentiation.

Fu Haiyan H Yang Guodong G Wei Mengying M Liu Li L Jin Liang L Lu Xiaozhao X Wang Li L Shen Lan L Zhang Jing J Lu Huanyu H Yao Libo L Lu Zifan Z

Molecular biology of the cell 20120307 9

Differentiated macrophages are essential for the innate immune system; however, the molecular mechanisms underlying the generation of macrophages remain largely unknown. Here we show that the RNA-binding protein QKI, mainly QKI-5, is transcriptionally activated in the early differentiated monocytic progenitors when CCAAT/enhancer-binding protein (C/EBP) α is expressed. The forced expression of C/EBPα increases the endogenous expression of QKI. Chromatin immunoprecipitation analysis and reporter ...[more]

PMID: 22398723

Similar Datasets

Project description:Precise identification of target sites of RNA-binding proteins (RBP) is important to understand their biochemical and cellular functions. A large amount of experimental data is generated by in vivo and in vitro approaches. The binding preferences determined from these platforms share similar patterns but there are discernable differences between these datasets. Computational methods trained on one dataset do not always work well on another dataset. To address this problem which resembles the classic "domain shift" in deep learning, we adopted the adversarial domain adaptation (ADDA) technique and developed a framework (RBP-ADDA) that can extract RBP binding preferences from an integration of in vivo and vitro datasets. Compared with conventional methods, ADDA has the advantage of working with two input datasets, as it trains the initial neural network for each dataset individually, projects the two datasets onto a feature space, and uses an adversarial framework to derive an optimal network that achieves an optimal discriminative predictive power. In the first step, for each RBP, we include only the in vitro data to pre-train a source network and a task predictor. Next, for the same RBP, we initiate the target network by using the source network and use adversarial domain adaptation to update the target network using both in vitro and in vivo data. These two steps help leverage the in vitro data to improve the prediction on in vivo data, which is typically challenging with a lower signal-to-noise ratio. Finally, to further take the advantage of the fused source and target data, we fine-tune the task predictor using both data. We showed that RBP-ADDA achieved better performance in modeling in vivo RBP binding data than other existing methods as judged by Pearson correlations. It also improved predictive performance on in vitro datasets. We further applied augmentation operations on RBPs with less in vivo data to expand the input data and showed that it can improve prediction performances. Lastly, we explored the predictive interpretability of RBP-ADDA, where we quantified the contribution of the input features by Integrated Gradients and identified nucleotide positions that are important for RBP recognition.

Dataset Information

The RNA-binding protein QKI5 is a direct target of C/EBP? and delays macrophage differentiation.

Publications

The RNA-binding protein QKI5 is a direct target of C/EBPα and delays macrophage differentiation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets