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Predictive modeling of long non-coding RNA chromatin (dis-)association

Evgenia Ntini, Stefan Budach, Ulf A Vang Ørom, Annalisa Marsico
doi: https://doi.org/10.1101/2020.12.15.422063
Evgenia Ntini
1Max-Planck Institute for Molecular Genetics, 14195 Berlin
2Freie Universität Berlin, 14195 Berlin
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  • For correspondence: ntini@molgen.mpg.de annalisa.marsico@helmholtz-muenchen.de
Stefan Budach
1Max-Planck Institute for Molecular Genetics, 14195 Berlin
2Freie Universität Berlin, 14195 Berlin
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Ulf A Vang Ørom
3Aarhus University, Department of Molecular Biology and Genetics, 8000 Aarhus, Denmark
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Annalisa Marsico
1Max-Planck Institute for Molecular Genetics, 14195 Berlin
2Freie Universität Berlin, 14195 Berlin
4Institute of Computational Biology, Helmholtz Zentrum Muenchen, Munich, Germany
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  • For correspondence: ntini@molgen.mpg.de annalisa.marsico@helmholtz-muenchen.de
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Summary

Long non-coding RNAs (lncRNAs) are involved in gene expression regulation in cis and trans. Although enriched in the chromatin cell fraction, to what degree this defines their broad range of functions remains unclear. In addition, the factors that contribute to lncRNA chromatin tethering, as well as the molecular basis of efficient lncRNA chromatin dissociation and its functional impact on enhancer activity and target gene expression, remain to be resolved. Here, we combine pulse-chase metabolic labeling of nascent RNA with chromatin fractionation and transient transcriptome sequencing to follow nascent RNA transcripts from their co-transcriptional state to their release into the nucleoplasm. By incorporating functional and physical characteristics in machine learning models, we find that parameters like co-transcriptional splicing contributes to efficient lncRNA chromatin dissociation. Intriguingly, lncRNAs transcribed from enhancer-like regions display reduced chromatin retention, suggesting that, in addition to splicing, lncRNA chromatin dissociation may contribute to enhancer activity and target gene expression.

Highlights

  • Chromatin (dis-)association of lncRNAs can be modeled using nascent RNA sequencing from pulse-chase chromatin fractionation

  • Distinct physical and functional characteristics contribute to lncRNA chromatin (dis-)association

  • lncRNAs transcribed from enhancers display increased degree of chromatin dissociation

  • lncRNAs of distinct degrees of chromatin association display differential binding probabilities for RNA-binding proteins (RBPs)

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 17, 2020.
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Predictive modeling of long non-coding RNA chromatin (dis-)association
Evgenia Ntini, Stefan Budach, Ulf A Vang Ørom, Annalisa Marsico
bioRxiv 2020.12.15.422063; doi: https://doi.org/10.1101/2020.12.15.422063
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Predictive modeling of long non-coding RNA chromatin (dis-)association
Evgenia Ntini, Stefan Budach, Ulf A Vang Ørom, Annalisa Marsico
bioRxiv 2020.12.15.422063; doi: https://doi.org/10.1101/2020.12.15.422063

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