PolyASite v3.0: a multi-species atlas of polyadenylation sites inferred from single-cell RNA-sequencing data
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Le résumé fourni par la source
The broadly used 10X Genomics technology for single-cell RNA sequencing (scRNA-seq) captures RNA 3' ends. Thus, some reads contain part of the non-templated polyadenosine tails, providing direct evidence for the sites of 3' end cleavage and polyadenylation on the respective RNAs. Taking advantage of this property, we recently developed the SCINPAS workflow to infer polyadenylation sites (PASs) from scRNA-seq data. Here, we used this workflow to construct version 3.0 (v3.0, https://polyasite.unibas.ch/) of the PolyASite Atlas from a big compendium of publicly available human, mouse and worm scRNA-seq datasets obtained from healthy tissues. As the resolution of scRNA-seq was too low for robust detection of cell-level differences in PAS usage, we aggregated samples based on their tissue-of-origin to construct tissue-level catalogs of PASs. These provide qualitatively new information about PAS usage, in comparison to the previous PAS catalogs that were based on bulk 3' end sequencing experiments primarily in cell lines. In the new version, we document stringency levels associated with each PAS so that users can balance sensitivity and specificity in their analysis. We also upgraded the integration with the UCSC Genome Browser and developed track hubs conveniently displaying pooled and tissue-specific expression of PASs.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- PolyASite v3.0: a multi-species atlas of polyadenylation sites inferred from single-cell RNA-sequencing data
- Date Crossref
- 12/11/2024
- Éditeur
- Oxford University Press (OUP)
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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SIB Swiss Institute of Bioinformatics pays non établi dans la noticeOrganisation à but non lucratif
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University of Basel Computational and Systems Biology pays non établi dans la noticeUniversité ou école supérieure
SIB Swiss Institute of Bioinformatics et Computational and Systems Biology — University of Basel.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.