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MECP2: A Multifunctional Protein Supporting Brain Complexity

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Mathematical Models in Biology

Abstract

After more than 20 years from its discovery, MECP2 roles are far from the fully understanding. MeCP2 binds the genome globally, with the need of a single, methylated CG and is enriched in heterochromatic foci. Early hypothesis proposed it as a generalized repressor and modulator of genome architecture that keeps down the transcriptional noise. Its modulation of L1 retrotransposition and the regulation of pericentric heterochromatin condensation might be conceivably associated with this function. Interestingly, MECP2 is mutated in the paradigmatic chromatin disease Rett syndrome, an X linked neurodevelopmental disease affecting females. This highlighted a different function of MECP2, as repressor of downstream genes and the identification of few downstream genes corroborated this hypothesis. Rather recently, however, with the help of high throughput technologies and a number of appropriate mouse models finely dissecting MECP2 functional domains, new and somehow unexpected roles for MECP2 have been highlighted. Expression profiling studies of specific brain areas support a role of MeCP2 not only as a transcriptional silencer but also as activator of gene expression. Beyond its binding to DNA, MeCP2 is also able to influence alternative splicing, promoting inclusion of hypermethylated exons in alternatively spliced transcripts. MeCP2 has been also found to bind non CG methylated residues in brain. Overall, MECP2 appears to be a multifunctional protein, exquisitely adapted to support the functional complexity of the brain.

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Acknowledgements

The authors gratefully acknowledge Epigenomics Flagship Project EPIGEN MIUR-CNR and Associazione Italiana Sindrome di Rett. FS is recipient of a Neuromed fellowship.

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Correspondence to Maurizio D’Esposito .

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Vacca, M., Ragione, F.D., Tripathi, K.P., Scalabrì, F., D’Esposito, M. (2015). MECP2: A Multifunctional Protein Supporting Brain Complexity. In: Zazzu, V., Ferraro, M., Guarracino, M. (eds) Mathematical Models in Biology. Springer, Cham. https://doi.org/10.1007/978-3-319-23497-7_8

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