bioRxivCell Biology
Chromatin activity of IκBα mediates the exit from naïve pluripotency
L. G. Palma, D. Alvarez-Villanueva, M. Maqueda, M. Barrero, A. IGLESIAS, j. Bertran, D. ALVAREZ, C. GARCIA-PRIETO, C. BALLARE, V. RODRIGUEZ-CORTEZ, C. BUENO, A. VIDAL, A. Villanueva, P. Menendez, G. Stik, L. Di Croce, B. Payer, M. Esteller, L. Espinosa, A. Bigas
Abstract
Maintenance of pluripotency is a multifactorial process in which NF-{kappa}B is a negative regulator. Our previous work identified a chromatin role for I{kappa}B, the master regulator of NF-{kappa}B signaling, that is critical for the proper regulation of various tissue stem cells. Here, we found that I{kappa}B accumulates specifically in the chromatin fraction of pluripotent embryonic stem cells. I{kappa}B depletion does not affect NF-kB-dependent transcription, but causes a profound epigenetic rewiring in pluripotent stem cells, including alterations in H3K27me3, a histone mark catalyzed by Polycomb repression complex 2. Chromatin changes induced by I{kappa}B depletion affect a subset of pluripotency genes and are associated with altered gene transcription. At the cellular level, I{kappa}B-deficient embryonic stem cells are arrested in a naive pluripotency state when cultured in serum/LIF conditions and fail to exit pluripotency under differentiation conditions. By constructing separation-of-function mutants, we show that the effects of I{kappa}B in regulating stem cell pluripotency are NF-{kappa}B-independent, but mainly rely on its chromatin-related function. Taken together, our results reveal a novel mechanism by which I{kappa}B participates in the regulation of the pluripotent state of embryonic stem cells and shed light on the interplay between inflammatory signals and the regulation of pluripotency.
- organism: mouse
- assay: ChIP-seq
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: chromatin & epigenetic regulation
- research focus: development & morphogenesis
- approach: experimental assay
- approach: genetic perturbation / CRISPR
- approach: statistical model
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