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BMC Bioinformatics. 2017 Jan 3;18(1):7. doi: 10.1186/s12859-016-1432-8.

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

Author information

1
Max Planck Institute for Biology of Ageing, Joseph-Stelzmann Str. 9b, Cologne, 50931, Germany.
2
Berlin Institute for Medical Systems Biology, Max-Delbrück-Center for Molecular Medicine, Robert-Rössle-Strasse 10, Berlin, 13125, Germany.
3
Section of Bioinformatics and Systems Cardiology, Klaus Tschira Institute for Integrative Computational Cardiology at the Department of Internal Medicine III, University Hospital Heidelberg, Im Neuenheimer Feld 669, Heidelberg, 69120, Germany. christoph.dieterich@uni-heidelberg.de.
4
German Center for Cardiovascular Research (DZHK) - Partner site Heidelberg/Mannheim, Im Neuenheimer Feld 669, Heidelberg, 69120, Germany. christoph.dieterich@uni-heidelberg.de.

Abstract

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.

KEYWORDS:

ADAR; APOBEC3; RNA editing; SNV; Variant calling

PMID:
28049429
PMCID:
PMC5210316
DOI:
10.1186/s12859-016-1432-8
[Indexed for MEDLINE]
Free PMC Article

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