Dataset Information

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing.

ABSTRACT: RNA editing increases the diversity of the transcriptome and proteome. Adenosine-to-inosine (A-to-I) editing is the predominant type of RNA editing in mammals and it is catalyzed by the adenosine deaminases acting on RNA (ADARs) family. Here, we used a largescale computational analysis of transcriptomic data from brain, heart, colon, lung, spleen, kidney, testes, skeletal muscle and liver, from three adult animals in order to identify RNA editing sites in bovine. We developed a computational pipeline and used a rigorous strategy to identify novel editing sites from RNA-Seq data in the absence of corresponding DNA sequence information. Our methods take into account sequencing errors, mapping bias, as well as biological replication to reduce the probability of obtaining a false-positive result. We conducted a detailed characterization of sequence and structural features related to novel candidate sites and found 1,600 novel canonical A-to-I editing sites in the nine bovine tissues analyzed. Results show that these sites 1) occur frequently in clusters and short interspersed nuclear elements (SINE) repeats, 2) have a preference for guanines depletion/enrichment in the flanking 5'/3' nucleotide, 3) occur less often in coding sequences than other regions of the genome, and 4) have low evolutionary conservation. Further, we found that a positive correlation exists between expression of ADAR family members and tissue-specific RNA editing. Most of the genes with predicted A-to-I editing in each tissue were significantly enriched in biological terms relevant to the function of the corresponding tissue. Lastly, the results highlight the importance of the RNA editome in nervous system regulation. The present study extends the list of RNA editing sites in bovine and provides pipelines that may be used to investigate the editome in other organisms.

SUBMITTER: Bakhtiarizadeh MR

PROVIDER: S-EPMC5823453 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing.

Bakhtiarizadeh Mohammad Reza MR Salehi Abdolreza A Rivera Rocío Melissa RM

PloS one 20180222 2

RNA editing increases the diversity of the transcriptome and proteome. Adenosine-to-inosine (A-to-I) editing is the predominant type of RNA editing in mammals and it is catalyzed by the adenosine deaminases acting on RNA (ADARs) family. Here, we used a largescale computational analysis of transcriptomic data from brain, heart, colon, lung, spleen, kidney, testes, skeletal muscle and liver, from three adult animals in order to identify RNA editing sites in bovine. We developed a computational pip ...[more]

PMID: 29470549

Similar Datasets

Project description:BackgroundRNA 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.ResultsWe 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.ConclusionOur 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.

Dataset Information

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing.

Publications

Genome-wide identification and analysis of A-to-I RNA editing events in bovine by transcriptome sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets