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ACValidator: A novel assembly-based approach for in silico verification of circular RNAs
Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons “back-splice” to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415914/ https://www.ncbi.nlm.nih.gov/pubmed/32793805 http://dx.doi.org/10.1093/biomethods/bpaa010 |
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author | Sekar, Shobana Geiger, Philipp Adkins, Jonathan Tassone, Erica Serrano, Geidy Beach, Thomas G Liang, Winnie S |
author_facet | Sekar, Shobana Geiger, Philipp Adkins, Jonathan Tassone, Erica Serrano, Geidy Beach, Thomas G Liang, Winnie S |
author_sort | Sekar, Shobana |
collection | PubMed |
description | Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons “back-splice” to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs. To this end, we developed Assembly based CircRNA Validator (ACValidator) for in silico verification of circRNAs. ACValidator extracts reads from a user-defined window on either side of a circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the back-spliced junction. When evaluated on simulated datasets, ACValidator achieved over ∼80% sensitivity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher verification percentages for samples treated with ribonuclease R compared to nontreated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for prioritizing experimental validations. All workflow scripts are freely accessible on our GitHub page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator. |
format | Online Article Text |
id | pubmed-7415914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-74159142020-08-12 ACValidator: A novel assembly-based approach for in silico verification of circular RNAs Sekar, Shobana Geiger, Philipp Adkins, Jonathan Tassone, Erica Serrano, Geidy Beach, Thomas G Liang, Winnie S Biol Methods Protoc Methods Manuscript Circular RNAs (circRNAs) are evolutionarily conserved RNA species that are formed when exons “back-splice” to each other. Current computational algorithms to detect these back-splicing junctions produce divergent results, and hence there is a need for a method to distinguish true-positive circRNAs. To this end, we developed Assembly based CircRNA Validator (ACValidator) for in silico verification of circRNAs. ACValidator extracts reads from a user-defined window on either side of a circRNA junction and assembles them to generate contigs. These contigs are aligned against the circRNA sequence to find contigs spanning the back-spliced junction. When evaluated on simulated datasets, ACValidator achieved over ∼80% sensitivity on datasets with an average of 10 circRNA-supporting reads and with read lengths of at least 100 bp. In experimental datasets, ACValidator produced higher verification percentages for samples treated with ribonuclease R compared to nontreated samples. Our workflow is applicable to non-polyA-selected RNAseq datasets and can also be used as a candidate selection strategy for prioritizing experimental validations. All workflow scripts are freely accessible on our GitHub page https://github.com/tgen/ACValidator along with detailed instructions to set up and run ACValidator. Oxford University Press 2020-08-10 /pmc/articles/PMC7415914/ /pubmed/32793805 http://dx.doi.org/10.1093/biomethods/bpaa010 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Manuscript Sekar, Shobana Geiger, Philipp Adkins, Jonathan Tassone, Erica Serrano, Geidy Beach, Thomas G Liang, Winnie S ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title | ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title_full | ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title_fullStr | ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title_full_unstemmed | ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title_short | ACValidator: A novel assembly-based approach for in silico verification of circular RNAs |
title_sort | acvalidator: a novel assembly-based approach for in silico verification of circular rnas |
topic | Methods Manuscript |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415914/ https://www.ncbi.nlm.nih.gov/pubmed/32793805 http://dx.doi.org/10.1093/biomethods/bpaa010 |
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