Kinetics of Xist-induced gene silencing can be predicted from combinations of epigenetic and genomic features
Autor: | Annalisa Marsico, Edda G. Schulz, John T. Lis, Chong-Jian Chen, Iris Jonkers, Edith Heard, Benjamin Foret, Ilona Dunkel, Christel Picard, Lisa Barros de Andrade e Sousa, Julie Chaumeil, Laurène Syx |
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Přispěvatelé: | Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI) |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
DOMAINS
Heterochromatin REGULATORY ELEMENTS PROTEINS Locus (genetics) Biology ESCAPE Gene dosage X-inactivation HETEROCHROMATIN 03 medical and health sciences 0302 clinical medicine X-CHROMOSOME INACTIVATION MAPS Genetics Gene silencing Epigenetics Gene Genetics (clinical) 030304 developmental biology 0303 health sciences IDENTIFICATION METHYLATION RNA XIST 030217 neurology & neurosurgery |
Zdroj: | Genome Research Genome Research, 29(7), 1087-1099. COLD SPRING HARBOR LAB PRESS, PUBLICATIONS DEPT |
ISSN: | 1088-9051 |
Popis: | 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. |
Databáze: | OpenAIRE |
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