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Zipper plot : visualizing transcriptional activity of genomic regions

Francisco Avila Cobos (UGent) , Jasper Anckaert (UGent) , Pieter-Jan Volders (UGent) , Celine Everaert (UGent) , Dries Rombaut (UGent) , Jo Vandesompele (UGent) , Katleen De Preter (UGent) and Pieter Mestdagh (UGent)
Author
Organization
Project
Bioinformatics: from nucleotids to networks (N2N)
Abstract
Background: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs. Results: To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIP-sequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot. Conclusion: Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Using publicly available RNA-seq data, we found more than one hundred cases where junction reads connected protein-coding gene exons with a downstream mono-exonic lncRNA, revealing the need for a careful evaluation of lncRNA 5′-boundaries. Our method is implemented using the statistical programming language R and is freely available as a webtool.
Keywords
LONG NONCODING RNAS, INTEGRATIVE ANALYSIS, EVOLUTION, LANDSCAPE, UPDATE

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Citation

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Chicago
Avila Cobos, Francisco, Jasper Anckaert, Pieter-Jan Volders, Celine Everaert, Dries Rombaut, Jo Vandesompele, Katleen De Preter, and Pieter Mestdagh. 2017. “Zipper Plot : Visualizing Transcriptional Activity of Genomic Regions.” Bmc Bioinformatics 18.
APA
Avila Cobos, F., Anckaert, J., Volders, P.-J., Everaert, C., Rombaut, D., Vandesompele, J., De Preter, K., et al. (2017). Zipper plot : visualizing transcriptional activity of genomic regions. BMC BIOINFORMATICS, 18.
Vancouver
1.
Avila Cobos F, Anckaert J, Volders P-J, Everaert C, Rombaut D, Vandesompele J, et al. Zipper plot : visualizing transcriptional activity of genomic regions. BMC BIOINFORMATICS. 2017;18.
MLA
Avila Cobos, Francisco, Jasper Anckaert, Pieter-Jan Volders, et al. “Zipper Plot : Visualizing Transcriptional Activity of Genomic Regions.” BMC BIOINFORMATICS 18 (2017): n. pag. Print.
@article{8519686,
  abstract     = {Background: Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA (lncRNA) annotation are mainly based on evolutionary constraints, which may result in false negatives due to the overall limited conservation of lncRNAs.
Results: To tackle this problem we have developed the Zipper plot, a novel visualization and analysis method that enables users to simultaneously interrogate thousands of human putative transcription start sites (TSSs) in relation to various features that are indicative for transcriptional activity. These include publicly available CAGE-sequencing, ChIP-sequencing and DNase-sequencing datasets. Our method only requires three tab-separated fields (chromosome, genomic coordinate of the TSS and strand) as input and generates a report that includes a detailed summary table, a Zipper plot and several statistics derived from this plot.
Conclusion: Using the Zipper plot, we found evidence of transcription for a set of well-characterized lncRNAs and observed that fewer mono-exonic lncRNAs have CAGE peaks overlapping with their TSSs compared to multi-exonic lncRNAs. Using publicly available RNA-seq data, we found more than one hundred cases where junction reads connected protein-coding gene exons with a downstream mono-exonic lncRNA, revealing the need for a careful evaluation of lncRNA 5{\textquotesingle}-boundaries. Our method is implemented using the statistical programming language R and is freely available as a webtool.},
  articleno    = {231},
  author       = {Avila Cobos, Francisco and Anckaert, Jasper and Volders, Pieter-Jan and Everaert, Celine and Rombaut, Dries and Vandesompele, Jo and De Preter, Katleen and Mestdagh, Pieter},
  issn         = {1471-2105},
  journal      = {BMC BIOINFORMATICS},
  keyword      = {LONG NONCODING RNAS,INTEGRATIVE ANALYSIS,EVOLUTION,LANDSCAPE,UPDATE},
  language     = {eng},
  pages        = {9},
  title        = {Zipper plot : visualizing transcriptional activity of genomic regions},
  url          = {http://dx.doi.org/10.1186/s12859-017-1651-7},
  volume       = {18},
  year         = {2017},
}

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