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TREND-DB – A Transcriptome-wide Atlas of the Dynamic Landscape of Alternative Polyadenylation

View ORCID ProfileFederico Marini, Denise Scherzinger, View ORCID ProfileSven Danckwardt
doi: https://doi.org/10.1101/2020.08.04.235804
Federico Marini
1Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Germany
2Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Germany
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  • For correspondence: marinif@uni-mainz.de Sven.Danckwardt@unimedizin-mainz.de
Denise Scherzinger
1Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Germany
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Sven Danckwardt
2Center for Thrombosis and Hemostasis (CTH), University Medical Center of the Johannes Gutenberg-University Mainz, Germany
3Posttranscriptional Gene Regulation, Cancer Research and Experimental Hemostasis, University Medical Center Mainz, Germany
4Institute for Clinical Chemistry and Laboratory Medicine, University Medical Center Mainz, Germany
5German Center for Cardiovascular Research (DZHK), Germany
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  • For correspondence: marinif@uni-mainz.de Sven.Danckwardt@unimedizin-mainz.de
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Abstract

Alternative polyadenylation (APA) profoundly expands the transcriptome complexity. Perturbations of APA can disrupt biological processes, ultimately resulting in devastating disorders. A major challenge in identifying mechanisms and consequences of APA (and its perturbations) lies in the complexity of RNA 3’end processing, involving poorly conserved RNA motifs and multi-component complexes consisting of far more than 50 proteins. This is further complicated in that RNA 3’end maturation is closely linked to transcription, RNA processing, and even epigenetic (histone/DNA/RNA) modifications. Here we present TREND-DB (http://shiny.imbei.uni-mainz.de:3838/trend-db), a resource cataloging the dynamic landscape of APA after depletion of >170 proteins involved in various facets of transcriptional, co- and posttranscriptional gene regulation, epigenetic modifications, and further processes. TREND-DB visualizes the dynamics of transcriptome 3’end diversification (TREND) in a highly interactive manner; it provides a global APA network map and allows interrogating genes affected by specific APA-regulators, and vice versa. It also permits condition-specific functional enrichment analyses of APA-affected genes, which suggest wide biological and clinical relevance across all RNAi conditions. The implementation of the UCSC Genome Browser provides additional customizable layers of gene regulation accounting for individual transcript isoforms (e.g. epigenetics, miRNA binding sites, RNA-binding proteins). TREND-DB thereby fosters disentangling the role of APA for various biological programs, including potential disease mechanisms, and helps to identify their diagnostic and therapeutic potential.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • The revised manuscript also includes Supplementary Methods, and the latest edits after feedback of the reviewers.

  • http://shiny.imbei.uni-mainz.de:3838/trend-db/

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 August 18, 2020.
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TREND-DB – A Transcriptome-wide Atlas of the Dynamic Landscape of Alternative Polyadenylation
Federico Marini, Denise Scherzinger, Sven Danckwardt
bioRxiv 2020.08.04.235804; doi: https://doi.org/10.1101/2020.08.04.235804
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TREND-DB – A Transcriptome-wide Atlas of the Dynamic Landscape of Alternative Polyadenylation
Federico Marini, Denise Scherzinger, Sven Danckwardt
bioRxiv 2020.08.04.235804; doi: https://doi.org/10.1101/2020.08.04.235804

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