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Cited by 196RNA Research and SplicingGenomics and Phylogenetic StudiesRNA regulation and disease

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PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3′ end sequencing

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Herrmann, Christina J, Schmidt, Ralf, Kanitz, Alexander, Artimo, Panu, Gruber, Andreas J, Zavolan, Mihaela·2019·Nucleic Acids Research
DOI 10.1093/nar/gkz918PMC PMC7145510
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Abstract

Generated by 3' end cleavage and polyadenylation at alternative polyadenylation (poly(A)) sites, alternative terminal exons account for much of the variation between human transcript isoforms. More than a dozen protocols have been developed so far for capturing and sequencing RNA 3' ends from a variety of cell types and species. In previous studies, we have used these data to uncover novel regulatory signals and cell type-specific isoforms. Here we present an update of the PolyASite (https://polyasite.unibas.ch) resource of poly(A) sites, constructed from publicly available human, mouse and worm 3' end sequencing datasets by enforcing uniform quality measures, including the flagging of putative internal priming sites. Through integrated processing of all data, we identified and clustered sites that are closely spaced and share polyadenylation signals, as these are likely the result of stochastic variations in processing. For each cluster, we identified the representative - most frequently processed - site and estimated the relative use in the transcriptome across all samples. We have established a modern web portal for efficient finding, exploration and export of data. Database generation is fully automated, greatly facilitating incorporation of new datasets and the updating of underlying genome resources.

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Crossref · 10.1093/nar/gkz918

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Figure 1. Schematic representation of the data processing underlying PolyASite. An integrated pipeline is used to process all input samples, regardless of 3′ end sequencing technique used for their generation, cell or tissue as well as species from which they originated. Data processing is done in three main parts. The first part of the pipeline consists of protocol specific modules, which cater to the different processing requirements of different 3′ end sequencing techniques in terms of adapter- and poly(A) tail removal, reverse complementation, etc. The second part consists of quality control, alignment and filtering of reads likely originating from internal priming sites, using uniform criteria for all samples, to ensure comparability. Finally, in the third part of the pipeline samples are pooled by species and the poly(A) site clusters are computed, annotated and quantified. The resulting species atlases are accessible through the PolyASite 2.0 web resource (https://polyasite.unibas.ch).
Figure 1. Schematic representation of the data processing underlying PolyASite. An integrated pipeline is used to process all input samples, regardless of 3′ end sequencing technique used for their generation, cell or tissue as well as species from which they originated. Data processing is done in three main parts. The first part of the pipeline consists of protocol specific modules, which cater to the different processing requirements of different 3′ end sequencing techniques in terms of adapter- and poly(A) tail removal, reverse complementation, etc. The second part consists of quality control, alignment and filtering of reads likely originating from internal priming sites, using uniform criteria for all samples, to ensure comparability. Finally, in the third part of the pipeline samples are pooled by species and the poly(A) site clusters are computed, annotated and quantified. The resulting species atlases are accessible through the PolyASite 2.0 web resource (https://polyasite.unibas.ch).CC BY-NC · PubMed Central
Figure 2. Use case: Search for poly(A) sites in a genomic region. Shown is an example search from PolyASite 2.0 and its results, including a screenshot from the UCSC genome browser. After a genomic region was entered into the search field (1) and the organism of interest was selected (2), the search was triggered (3). The figure shows the first rows of the retrieved table of poly(A) site clusters, which has been customized by toggling specific columns via the ‘Column visibility’ button and by sorting the results according to the ‘Usage’ and ‘Protocols’ columns (by clicking/tapping the respective column headers). The arrow on the black background to the left of a row leads to an expanded table, which contains information on the expression/usage of the respective cluster in individual samples (not shown). Selecting ‘Explore region in UCSC browser’ (4) yielded the genome view depicted on top, with distinct browser tracks for atlas sites on the plus and minus strands. The location of the most abundant cluster in the results table and in the browser view is indicated by the curved arrow. Descriptions of the visible columns are indicated at the bottom.
Figure 2. Use case: Search for poly(A) sites in a genomic region. Shown is an example search from PolyASite 2.0 and its results, including a screenshot from the UCSC genome browser. After a genomic region was entered into the search field (1) and the organism of interest was selected (2), the search was triggered (3). The figure shows the first rows of the retrieved table of poly(A) site clusters, which has been customized by toggling specific columns via the ‘Column visibility’ button and by sorting the results according to the ‘Usage’ and ‘Protocols’ columns (by clicking/tapping the respective column headers). The arrow on the black background to the left of a row leads to an expanded table, which contains information on the expression/usage of the respective cluster in individual samples (not shown). Selecting ‘Explore region in UCSC browser’ (4) yielded the genome view depicted on top, with distinct browser tracks for atlas sites on the plus and minus strands. The location of the most abundant cluster in the results table and in the browser view is indicated by the curved arrow. Descriptions of the visible columns are indicated at the bottom.CC BY-NC · PubMed Central

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Metadata

Authors
Herrmann, C. J., Schmidt, R., Kanitz, A., Artimo, P., Gruber, A. J., & Zavolan, M.
Affiliations
  • University of Basel (CH)
  • SIB Swiss Institute of Bioinformatics (CH)
  • University of Oxford (GB)
Corresponding author
Zavolan, Mihaela
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2019-10-16
Volume
48
Issue
D1
Pages
D174-D179
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkz918
PMC
PMC7145510
OpenAlex
W2980708325
Cited by
196
References
32
Citations by year
2026: 18 · 2025: 21 · 2024: 33 · 2023: 36 · 2022: 37 · 2021: 40 · 2020: 10 · 2019: 1
FWCI
7.28
Type
journal article
Language
en
Open access
Licence
Locations
  • Nucleic Acids Research (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • KOPS (University of Konstanz) (submittedVersion, cc-by-nc)
  • edoc (University of Basel) (submittedVersion)
Funders
Swiss National Science Foundation (31003A_170216, 51NF40_141735)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
Keywords
polyadenylation sites, alternative polyadenylation, 3' end sequencing, mRNA isoforms, site clustering, web portal
MeSH terms
Animals, Humans, Poly A, Caenorhabditis elegans, Sequence Analysis, RNA, Polyadenylation, Databases, Nucleic Acid, Mice

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