Limits...
Genome-wide identification and characterization of tissue-specific RNA editing events in D. melanogaster and their potential role in regulating alternative splicing.

Mazloomian A, Meyer IM - RNA Biol (2015)

Bottom Line: The majority of these editing events, however, cannot be associated with regulatory mechanisms.Furthermore, we identify 244 edited regions where RNA editing and alternative splicing are likely to influence each other.For 96 out of these 244 regions, we find evolutionary evidence for conserved RNA secondary-structures near splice sites suggesting a potential regulatory mechanism where RNA editing may alter splicing patterns via changes in local RNA structure.

View Article: PubMed Central - PubMed

Affiliation: a Centre for High-Throughput Biology; Department of Computer Science and Department of Medical Genetics ; University of British Columbia ; Vancouver ; BC , Canada.

ABSTRACT
RNA editing is a widespread mechanism that plays a crucial role in diversifying gene products. Its abundance and importance in regulating cellular processes were revealed using new sequencing technologies. The majority of these editing events, however, cannot be associated with regulatory mechanisms. We use tissue-specific high-throughput libraries of D. melanogaster to study RNA editing. We introduce an analysis pipeline that utilises large input data and explicitly captures ADAR's requirement for double-stranded regions. It combines probabilistic and deterministic filters and can identify RNA editing events with a low estimated false positive rate. Analyzing ten different tissue types, we predict 2879 editing sites and provide their detailed characterization. Our analysis pipeline accurately distinguishes genuine editing sites from SNPs and sequencing and mapping artifacts. Our editing sites are 3 times more likely to occur in exons with multiple splicing acceptor/donor sites than in exons with unique splice sites (p-value < 2.10(-15)). Furthermore, we identify 244 edited regions where RNA editing and alternative splicing are likely to influence each other. For 96 out of these 244 regions, we find evolutionary evidence for conserved RNA secondary-structures near splice sites suggesting a potential regulatory mechanism where RNA editing may alter splicing patterns via changes in local RNA structure.

No MeSH data available.


There is a positive correlation between genes that are targets of RNA editing and genes that are alternatively spliced. (A) The number of annotated isoforms vs. the number of predicted sites in our study. The number of detected sites is found to be greater in genes that express more annotated isoforms. (B) We group genes based on their length and compare the average number of annotated isoforms for genes of similar length between those that are edited and those that are un-edited genes. For genes with similar length, edited genes have a higher chance of being alternatively spliced.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4829317&req=5

f0003: There is a positive correlation between genes that are targets of RNA editing and genes that are alternatively spliced. (A) The number of annotated isoforms vs. the number of predicted sites in our study. The number of detected sites is found to be greater in genes that express more annotated isoforms. (B) We group genes based on their length and compare the average number of annotated isoforms for genes of similar length between those that are edited and those that are un-edited genes. For genes with similar length, edited genes have a higher chance of being alternatively spliced.

Mentions: We find that a gene with a greater number of known isoforms has a higher chance of being edited. Figure 3A illustrates the positive correlation (Rpearson = 0.33, p-value 2.10-15) between the number of annotated isoforms and the number of predicted RNA editing sites in our study. One would expect longer genes to have a higher probability of being edited and to also have more splice variants (based on the larger number of exons). In order to test if the correlation observed in our data can be explained by gene length alone, we grouped genes according to their lengths and calculated the average number of known isoforms per group, once for the sub-group of edited and once for the complementary sub-group of un-edited genes (Fig. 3B). Although we find that longer genes tend to contain more editing sites, edited genes have a significantly greater number of known isoforms than un-edited genes.Figure 3.


Genome-wide identification and characterization of tissue-specific RNA editing events in D. melanogaster and their potential role in regulating alternative splicing.

Mazloomian A, Meyer IM - RNA Biol (2015)

There is a positive correlation between genes that are targets of RNA editing and genes that are alternatively spliced. (A) The number of annotated isoforms vs. the number of predicted sites in our study. The number of detected sites is found to be greater in genes that express more annotated isoforms. (B) We group genes based on their length and compare the average number of annotated isoforms for genes of similar length between those that are edited and those that are un-edited genes. For genes with similar length, edited genes have a higher chance of being alternatively spliced.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4829317&req=5

f0003: There is a positive correlation between genes that are targets of RNA editing and genes that are alternatively spliced. (A) The number of annotated isoforms vs. the number of predicted sites in our study. The number of detected sites is found to be greater in genes that express more annotated isoforms. (B) We group genes based on their length and compare the average number of annotated isoforms for genes of similar length between those that are edited and those that are un-edited genes. For genes with similar length, edited genes have a higher chance of being alternatively spliced.
Mentions: We find that a gene with a greater number of known isoforms has a higher chance of being edited. Figure 3A illustrates the positive correlation (Rpearson = 0.33, p-value 2.10-15) between the number of annotated isoforms and the number of predicted RNA editing sites in our study. One would expect longer genes to have a higher probability of being edited and to also have more splice variants (based on the larger number of exons). In order to test if the correlation observed in our data can be explained by gene length alone, we grouped genes according to their lengths and calculated the average number of known isoforms per group, once for the sub-group of edited and once for the complementary sub-group of un-edited genes (Fig. 3B). Although we find that longer genes tend to contain more editing sites, edited genes have a significantly greater number of known isoforms than un-edited genes.Figure 3.

Bottom Line: The majority of these editing events, however, cannot be associated with regulatory mechanisms.Furthermore, we identify 244 edited regions where RNA editing and alternative splicing are likely to influence each other.For 96 out of these 244 regions, we find evolutionary evidence for conserved RNA secondary-structures near splice sites suggesting a potential regulatory mechanism where RNA editing may alter splicing patterns via changes in local RNA structure.

View Article: PubMed Central - PubMed

Affiliation: a Centre for High-Throughput Biology; Department of Computer Science and Department of Medical Genetics ; University of British Columbia ; Vancouver ; BC , Canada.

ABSTRACT
RNA editing is a widespread mechanism that plays a crucial role in diversifying gene products. Its abundance and importance in regulating cellular processes were revealed using new sequencing technologies. The majority of these editing events, however, cannot be associated with regulatory mechanisms. We use tissue-specific high-throughput libraries of D. melanogaster to study RNA editing. We introduce an analysis pipeline that utilises large input data and explicitly captures ADAR's requirement for double-stranded regions. It combines probabilistic and deterministic filters and can identify RNA editing events with a low estimated false positive rate. Analyzing ten different tissue types, we predict 2879 editing sites and provide their detailed characterization. Our analysis pipeline accurately distinguishes genuine editing sites from SNPs and sequencing and mapping artifacts. Our editing sites are 3 times more likely to occur in exons with multiple splicing acceptor/donor sites than in exons with unique splice sites (p-value < 2.10(-15)). Furthermore, we identify 244 edited regions where RNA editing and alternative splicing are likely to influence each other. For 96 out of these 244 regions, we find evolutionary evidence for conserved RNA secondary-structures near splice sites suggesting a potential regulatory mechanism where RNA editing may alter splicing patterns via changes in local RNA structure.

No MeSH data available.