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  Kinetics of Xist-induced gene silencing can be predicted from combinations of epigenetic and genomic features

Barros de Andrade e Sousa, L., Jonkers, I., Syx, L., Dunkel, I., Chaumeil, J., Picard, C., et al. (2019). Kinetics of Xist-induced gene silencing can be predicted from combinations of epigenetic and genomic features. Genome Research, 29(7), 1087-1099. doi:10.1101/gr.245027.118.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0004-C660-0 Version Permalink: http://hdl.handle.net/21.11116/0000-0004-C661-F
Genre: Journal Article

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© 2019 Barros de Andrade e Sousa et al

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 Creators:
Barros de Andrade e Sousa, Lisa1, Author              
Jonkers, Iris , Author
Syx, Laurène , Author
Dunkel, Ilona1, Author              
Chaumeil, Julie , Author
Picard, Christel , Author
Foret, Benjamin , Author
Chen, Chong-Jian , Author
Lis, John T. , Author
Heard, Edith , Author
Schulz, Edda G.1, Author              
Marsico, Annalisa2, Author
Affiliations:
1Regulatory Networks in Stem Cells (Edda G. Schulz), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2117286              
2Department of Mathematics and Informatics, Free University of Berlin, 14195 Berlin, Germany, ou_persistent22              

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 Abstract: To initiate X-Chromosome inactivation (XCI), the long noncoding RNA Xist mediates chromosome-wide gene silencing of one X Chromosome in female mammals to equalize gene dosage between the sexes. The efficiency of gene silencing is highly variable across genes, with some genes even escaping XCI in somatic cells. A gene's susceptibility to Xist-mediated silencing appears to be determined by a complex interplay of epigenetic and genomic features; however, the underlying rules remain poorly understood. We have quantified chromosome-wide gene silencing kinetics at the level of the nascent transcriptome using allele-specific Precision nuclear Run-On sequencing (PRO-seq). We have developed a Random Forest machine-learning model that can predict the measured silencing dynamics based on a large set of epigenetic and genomic features and tested its predictive power experimentally. The genomic distance to the Xist locus, followed by gene density and distance to LINE elements, are the prime determinants of the speed of gene silencing. Moreover, we find two distinct gene classes associated with different silencing pathways: a class that requires Xist-repeat A for silencing, which is known to activate the SPEN pathway, and a second class in which genes are premarked by Polycomb complexes and tend to rely on the B repeat in Xist for silencing, known to recruit Polycomb complexes during XCI. Moreover, a series of features associated with active transcriptional elongation and chromatin 3D structure are enriched at rapidly silenced genes. Our machine-learning approach can thus uncover the complex combinatorial rules underlying gene silencing during X inactivation.

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Language(s): eng - English
 Dates: 2019-06-072019-07
 Publication Status: Published in print
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 Rev. Method: -
 Identifiers: DOI: 10.1101/gr.245027.118
PMID: 31175153
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Title: Genome Research
Source Genre: Journal
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Publ. Info: Cold Spring Harbor, N.Y. : Cold Spring Harbor Laboratory Press
Pages: 13 Volume / Issue: 29 (7) Sequence Number: - Start / End Page: 1087 - 1099 Identifier: ISSN: 1088-9051
CoNE: https://pure.mpg.de/cone/journals/resource/954926997202