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JACUSA: site-specific identification of RNA editing events from replicate sequencing data

BACKGROUND: RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by th...

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Autores principales: Piechotta, Michael, Wyler, Emanuel, Ohler, Uwe, Landthaler, Markus, Dieterich, Christoph
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210316/
https://www.ncbi.nlm.nih.gov/pubmed/28049429
http://dx.doi.org/10.1186/s12859-016-1432-8
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author Piechotta, Michael
Wyler, Emanuel
Ohler, Uwe
Landthaler, Markus
Dieterich, Christoph
author_facet Piechotta, Michael
Wyler, Emanuel
Ohler, Uwe
Landthaler, Markus
Dieterich, Christoph
author_sort Piechotta, Michael
collection PubMed
description BACKGROUND: RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by the members of the Adenosine deaminases that act on RNA (ADAR) family. Typically, editing sites are identified as RNA-DNA-differences (RDDs) in a comparison of genome and transcriptome data from next-generation sequencing experiments. However, a method for robust detection of site-specific editing events from replicate RNA-seq data has not been published so far. Even more surprising, condition-specific editing events, which would show up as differences in RNA-RNA comparisons (RRDs) and depend on particular cellular states, are rarely discussed in the literature. RESULTS: We present JACUSA, a versatile one-stop solution to detect single nucleotide variant positions from comparing RNA-DNA and/or RNA-RNA sequencing samples. The performance of JACUSA has been carefully evaluated and compared to other variant callers in an in silico benchmark. JACUSA outperforms other algorithms in terms of the F measure, which combines precision and recall, in all benchmark scenarios. This performance margin is highest for the RNA-RNA comparison scenario. We further validated JACUSA’s performance by testing its ability to detect A→I events using sequencing data from a human cell culture experiment and publicly available RNA-seq data from Drosophila melanogaster heads. To this end, we performed whole genome and RNA sequencing of HEK-293 cells on samples with lowered activity of candidate RNA editing enzymes. JACUSA has a higher recall and comparable precision for detecting true editing sites in RDD comparisons of HEK-293 data. Intriguingly, JACUSA captures most A→I events from RRD comparisons of RNA sequencing data derived from Drosophila and HEK-293 data sets. CONCLUSION: Our software JACUSA detects single nucleotide variants by comparing data from next-generation sequencing experiments (RNA-DNA or RNA-RNA). In practice, JACUSA shows higher recall and comparable precision in detecting A→I sites from RNA-DNA comparisons, while showing higher precision and recall in RNA-RNA comparisons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1432-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-52103162017-01-06 JACUSA: site-specific identification of RNA editing events from replicate sequencing data Piechotta, Michael Wyler, Emanuel Ohler, Uwe Landthaler, Markus Dieterich, Christoph BMC Bioinformatics Software BACKGROUND: RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by the members of the Adenosine deaminases that act on RNA (ADAR) family. Typically, editing sites are identified as RNA-DNA-differences (RDDs) in a comparison of genome and transcriptome data from next-generation sequencing experiments. However, a method for robust detection of site-specific editing events from replicate RNA-seq data has not been published so far. Even more surprising, condition-specific editing events, which would show up as differences in RNA-RNA comparisons (RRDs) and depend on particular cellular states, are rarely discussed in the literature. RESULTS: We present JACUSA, a versatile one-stop solution to detect single nucleotide variant positions from comparing RNA-DNA and/or RNA-RNA sequencing samples. The performance of JACUSA has been carefully evaluated and compared to other variant callers in an in silico benchmark. JACUSA outperforms other algorithms in terms of the F measure, which combines precision and recall, in all benchmark scenarios. This performance margin is highest for the RNA-RNA comparison scenario. We further validated JACUSA’s performance by testing its ability to detect A→I events using sequencing data from a human cell culture experiment and publicly available RNA-seq data from Drosophila melanogaster heads. To this end, we performed whole genome and RNA sequencing of HEK-293 cells on samples with lowered activity of candidate RNA editing enzymes. JACUSA has a higher recall and comparable precision for detecting true editing sites in RDD comparisons of HEK-293 data. Intriguingly, JACUSA captures most A→I events from RRD comparisons of RNA sequencing data derived from Drosophila and HEK-293 data sets. CONCLUSION: Our software JACUSA detects single nucleotide variants by comparing data from next-generation sequencing experiments (RNA-DNA or RNA-RNA). In practice, JACUSA shows higher recall and comparable precision in detecting A→I sites from RNA-DNA comparisons, while showing higher precision and recall in RNA-RNA comparisons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-016-1432-8) contains supplementary material, which is available to authorized users. BioMed Central 2017-01-03 /pmc/articles/PMC5210316/ /pubmed/28049429 http://dx.doi.org/10.1186/s12859-016-1432-8 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Piechotta, Michael
Wyler, Emanuel
Ohler, Uwe
Landthaler, Markus
Dieterich, Christoph
JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title_full JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title_fullStr JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title_full_unstemmed JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title_short JACUSA: site-specific identification of RNA editing events from replicate sequencing data
title_sort jacusa: site-specific identification of rna editing events from replicate sequencing data
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5210316/
https://www.ncbi.nlm.nih.gov/pubmed/28049429
http://dx.doi.org/10.1186/s12859-016-1432-8
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