Editing of hnRNP K protein mRNA in colorectal adenocarcinoma and surrounding mucosa

Klimek-Tomczak, Karolina; Mikula, Michał; Dzwonek, Artur; Paziewska, Agnieszka; Karczmarski, Jakub; Hennig, Ewa E.; Bujnicki, Janusz; Brągoszewski, Piotr; Denisenko, Oleg; Bomsztyk, Karol; Ostrowski, Jerzy

doi:10.1038/sj.bjc.6602938

Cited by 47 publications

(39 citation statements)

References 35 publications

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“…Among them, C-to-T and G-to-A were the most frequent (25.3% and 22.5%, respectively), followed by T-to-C (11.6%). Individual examples of C-to-T, G-to-A, and T-to-C editing were reported previously (16)(17)(18). The distributions of the non-A-to-G editing types were similar between the nucleus and the cytosol and between Alu and non-Alu sites (Fig.…”

Section: Resultsmentioning

confidence: 59%

Characterization and comparison of human nuclear and cytosolic editomes

Chen

2013

Proc. Natl. Acad. Sci. U.S.A.

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We developed a robust computational statistical framework to identify RNA editing events from RNA-Seq data with high specificity. Our approach handles several outstanding challenges of genome-wide editing analyses, including the effect of editing on read alignment and the utilization of redundant reads. By applying this framework, we characterized the nuclear and cytosolic editomes of seven human cell lines. We found that 93.8-99.2% of the editing events are A-to-G (or A-to-I). Nuclear transcriptomes contain many more editing events than cytosolic transcriptomes. Most of the sites exhibiting nucleus-specific editing are in introns or novel intergenic transcripts that are preferentially localized in the nucleus regardless of their editing status, arguing against the role of editing in nuclear retention. In contrast, many sites that exhibit cytosol-specific editing show comparable nuclear and cytosolic expression, suggesting the differential subcellular compartmentalization of the edited and the unedited alleles. We found that RNA editing is globally associated with the modification of microRNA regulation in 3′ untranslated regions, whereas editing events in coding regions are rare and tend to be synonymous. Interestingly, A-to-G editing at derived alleles in the human lineage tends to result in reversion back to the ancestral forms at the RNA level. This suggests that editing can mediate RNA memory on evolutionary time-scales to maintain ancestral genetic information.high-throughput sequencing | nucleo-cytoplasmic localization A lthough high-throughput sequencing has facilitated the identification of genetic DNA variants, the identification of RNA editing is much more challenging owing to the uneven read distribution in RNA sequencing and the varied RNA editing rates. Errors in base calling and read alignment, the handling of redundant reads, and other systematic sequencing errors all hinder the single-nucleotide-level analysis of RNA editing. Early analyses of high-throughput sequencing data reported more than 10,000 exonic editing events, many of which were non-A-to-G (1). However, recent studies argued that many of these non-A-to-G editing events were false positives resulting from inappropriate bioinformatic analyses (2-4). To deal with multiple sources of potential errors, the existing tools for editing discovery (5-7) usually involve comprehensive pipelines packed with multiple read aligners, read simulations, and various filters. Meanwhile, many critical issues in editing discovery remain to be addressed more properly. For example, the existing methods remove a large number of redundant reads starting from the same positions, although in deep sequencing many redundant reads can result from true expression and are useful for estimating editing levels. Moreover, the effect of editing on read alignment has been commonly overlooked.Herein, we developed an efficient and robust computational statistical framework for RNA editing discovery. This framework considers the effect of editing on read alignment and hand...

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Section: Resultsmentioning

confidence: 59%

Characterization and comparison of human nuclear and cytosolic editomes

Chen

2013

Proc. Natl. Acad. Sci. U.S.A.

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“…In addition, A-to-I editing can play important roles in regulating gene expression , such as by altering alternative splicing (Rueter et al 1999;Laurencikiene et al 2006;Schoft et al 2007), miRNA sequences (Kawahara et al 2007(Kawahara et al , 2008Reid et al 2008;Dupuis and Maas 2010), or miRNA target sites in the mRNA (Liang and Landweber 2007;Borchert et al 2009). Other types of putative RNA editing events are also known, for example, C-to-U editing and U-to-C and G-to-A conversions (Nutt et al 1994;Sharma et al 1994;Villegas et al 2002;Klimek-Tomczak et al 2006), but with much less prevalence.…”

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confidence: 99%

Accurate identification of A-to-I RNA editing in human by transcriptome sequencing

Bahn¹,

Lee²,

Li³

et al. 2011

Genome Res.

315

355

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RNA editing enhances the diversity of gene products at the post-transcriptional level. Approaches for genome-wide identification of RNA editing face two main challenges: separating true editing sites from false discoveries and accurate estimation of editing levels. We developed an approach to analyze transcriptome sequencing data (RNA-seq) for global identification of RNA editing in cells for which whole-genome sequencing data are available. We applied the method to analyze RNA-seq data of a human glioblastoma cell line, U87MG. Around 10,000 DNA-RNA differences were identified, the majority being putative A-to-I editing sites. These predicted A-to-I events were associated with a low false-discovery rate (~5%). Moreover, the estimated editing levels from RNA-seq correlated well with those based on traditional clonal sequencing. Our results further facilitated unbiased characterization of the sequence and evolutionary features flanking predicted A-to-I editing sites and discovery of a conserved RNA structural motif that may be functionally relevant to editing. Genes with predicted A-to-I editing were significantly enriched with those known to be involved in cancer, supporting the potential importance of cancer-specific RNA editing. A similar profile of DNA-RNA differences as in U87MG was predicted for another RNA-seq data set obtained from primary breast cancer samples. Remarkably, significant overlap exists between the putative editing sites of the two transcriptomes despite their difference in cell type, cancer type, and genomic backgrounds. Our approach enabled de novo identification of the RNA editome, which sets the stage for further mechanistic studies of this important step of post-transcriptional regulation.

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“…Furthermore, we and others have found that there are other types of RNA-DNA sequence differences (RDDs) that are unlikely to be mediated by these deaminases (Li et al 2011;Bahn et al 2012;Bar-Yaacov et al 2013;Rubio et al 2013;Turner et al 2015). These events are found in normal cells, and altered patterns of RDDs were found in neurologic diseases (van Leeuwen et al 1998;Silberberg et al 2012;Krestel et al 2013;Wang et al 2014) and in cancers (Klimek-Tomczak et al 2006;Martinez et al 2008;Lee et al 2013;Avesson and Barry 2014;Han et al 2014;Niavarani et al 2015). Although differences between RNA and their corresponding DNA templates were known for many years, their discoveries in human beyond the editing events mediated by ADAR and APOBEC families of deaminases were debated.…”

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confidence: 99%

RNA–DNA sequence differences in Saccharomyces cerevisiae

et al. 2016

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Alterations of RNA sequences and structures, such as those from editing and alternative splicing, result in two or more RNA transcripts from a DNA template. It was thought that in yeast, RNA editing only occurs in tRNAs. Here, we found that Saccharomyces cerevisiae have all 12 types of RNA-DNA sequence differences (RDDs) in the mRNA. We showed these sequence differences are propagated to proteins, as we identified peptides encoded by the RNA sequences in addition to those by the DNA sequences at RDD sites. RDDs are significantly enriched at regions with R-loops. A screen of yeast mutants showed that RDD formation is affected by mutations in genes regulating R-loops. Loss-of-function mutations in ribonuclease H, senataxin, and topoisomerase I that resolve RNA-DNA hybrids lead to increases in RDD frequency. Our results demonstrate that RDD is a conserved process that diversifies transcriptomes and proteomes and provide a mechanistic link between R-loops and RDDs.

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Editing of hnRNP K protein mRNA in colorectal adenocarcinoma and surrounding mucosa

Cited by 47 publications

References 35 publications

Characterization and comparison of human nuclear and cytosolic editomes

Characterization and comparison of human nuclear and cytosolic editomes

Accurate identification of A-to-I RNA editing in human by transcriptome sequencing

RNA–DNA sequence differences in Saccharomyces cerevisiae

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