Mouse let-7 miRNA populations exhibit RNA editing that is constrained in the 5′-seed/ cleavage/anchor regions and stabilize predicted mmu-let-7a:mRNA duplexes

Reid, Jeffrey G.; Nagaraja, Ankur K.; Lynn, Francis C.; Drabek, Rafal; Muzny, Donna M.; Shaw, Chad A.; Weiss, Michelle K.; Naghavi, A.O.; Khan, Mahjabeen F.; Zhu, Huaqing; Tennakoon, Jayantha B.; Gunaratne, Gemunu H.; Corry, David B.; Miller, Jonathan; McManus, Michael T.; German, Michael S.; Gibbs, Richard A.; Matzuk, Martin M.; Gunaratne, Preethi H.

doi:10.1101/gr.078246.108

Cited by 90 publications

(98 citation statements)

References 46 publications

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“…Several recent reports have shown that in both animals (humans, mice, D. melanogaster, and Caenorhabditis elegans) and plants (Arabidopsis thaliana, Oryza sativa, and Populus trichocarpa) miRNAs exhibit heterogeneous 59 and 39 ends, and post-transcriptional nontemplate 39 end additions of uridines or adenosines (Li et al 2005;Landgraf et al 2007;Ruby et al 2007;Azuma-Mukai et al 2008;Morin et al 2008;Reid et al 2008;Seitz et al 2008;Ebhardt et al 2009;Lu et al 2009). Although the biological relevance of these miRNA isoforms, or isomiRs, has been questioned, there is evidence in A. thaliana that terminal nucleotide additions occur after Dicer processing of the miRNA precursor (Li et al 2005), and that some variants are differentially loaded into Argonautes (Seitz et al 2008;Ebhardt et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Dynamic isomiR regulation in Drosophila development

Fernandez-Valverde¹,

Taft²,

Mattick³

2010

RNA

194

171

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Several recent reports have demonstrated that microRNAs (miRNAs) can exhibit heterogeneous ends and post-transcriptional nontemplate 39 end additions of uridines or adenosines. Using two small RNA deep-sequencing data sets, we show here that these miRNA isoforms (isomiRs) are differentially expressed across Drosophila melanogaster development and tissues. Specifically, we demonstrate that: (1) nontemplate nucleotide additions of adenosines to miRNA 39 ends are highly abundant in early development; (2) a subset of miRNAs with nontemplate 39 Us are expressed in adult tissues; and (3) the size of at least eight ''mature'' (unmodified) miRNAs varies in a life-cycle or tissue-specific manner. These results suggest that subtle variability in isomiR expression, which is widely thought to be the result of inexact Dicer processing, is regulated and biologically meaningful. Indeed, a subset of the miRNAs enriched for 39 adenosine additions during early embryonic development, including miR-282 and miR-312, show enrichment for target sites in developmental genes that are expressed during late embryogenesis, suggesting that nontemplate additions increase miRNA stability or strengthen miRNA:target interactions. This work suggests that isomiR expression is an important aspect of miRNA biology, which warrants further investigation.

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Section: Introductionmentioning

confidence: 99%

Dynamic isomiR regulation in Drosophila development

Fernandez-Valverde¹,

Taft²,

Mattick³

2010

RNA

194

171

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“…Global and unequivocal identification of RNA editing targets represents a critical first step in further understanding this post-transcriptional modification. This calls for complete information on whole-genome and transcriptome sequences from the same individual, so as to exclude polymorphisms and mutations among populations, as well as experimental approaches with the necessary high-throughput sequencing and base resolution 13,14 . Whole-transcriptome deep-sequencing technologies (e.g., RNASeq) [15][16][17] , with their capacity to simultaneously assay the entire transcriptome, represent an excellent choice of tool in this regard.…”

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confidence: 99%

Comprehensive analysis of RNA-Seq data reveals extensive RNA editing in a human transcriptome

et al. 2012

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A n A ly s i s RNA editing is a post-transcriptional event that recodes hereditary information. Here we describe a comprehensive profile of the RNA editome of a male Han Chinese individual based on analysis of ~767 million sequencing reads from poly(A) + , poly(A) − and small RNA samples. We developed a computational pipeline that carefully controls for false positives while calling RNA editing events from genome and whole-transcriptome data of the same individual. We identified 22,688 RNA editing events in noncoding genes and introns, untranslated regions and coding sequences of protein-coding genes. Most changes (~93%) converted A to I(G), consistent with known editing mechanisms based on adenosine deaminase acting on RNA (ADAR). We also found evidence of other types of nucleotide changes; however, these were validated at lower rates. We found 44 editing sites in microRNAs (miRNAs), suggesting a potential link between RNA editing and miRNAmediated regulation. Our approach facilitates large-scale studies to profile and compare editomes across a wide range of samples.RNA editing is an integral step in generating the diversity and plasticity of cellular RNA signatures. Most editing events convert A to I(G) (adenosine to inosine, which is translated as guanosine), and are catalyzed by the double-stranded RNA-specific ADAR family of proteins. On the basis of its overabundance in repetitive Alu elements and the brain transcriptome 1-3 , RNA editing has been viewed as a key determinant in primate evolution and the development of higher brain functions 4 . Many outstanding questions on the extent and consequences of RNA editing in humans remain unanswered, despite extensive documentation of edited sites through bioinformatics approaches 5-9 and the reported roles of editing in altering genetic messages and other post-transcriptional events such as RNA splicing and miRNA regulation 2,10-12 . Global and unequivocal identification of RNA editing targets represents a critical first step in further understanding this post-transcriptional modification. This calls for complete information on whole-genome and transcriptome sequences from the same individual, so as to exclude polymorphisms and mutations among populations, as well as experimental approaches with the necessary high-throughput sequencing and base resolution 13,14 . Whole-transcriptome deep-sequencing technologies (e.g., RNASeq) [15][16][17] , with their capacity to simultaneously assay the entire transcriptome, represent an excellent choice of tool in this regard. Recent studies reporting the use of target-specific RNA-Seq 4,18 , the combination of DNA capture and parallel sequencing 19 , and mRNA-Seq 20,21 to find human RNA editing sites attest to the notion that this strategy is advantageous in addressing many outstanding questions of the editing phenomenon and its implications on the transcriptome.In this study, we used RNA-Seq to identify post-transcriptional editing events. Our unbiased and in-depth approach revealed many editing sites in transcripts corresp...

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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.…”

mentioning

confidence: 99%

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

Bahn¹,

Lee²,

Li³

et al. 2011

Genome Res.

309

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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Mouse let-7 miRNA populations exhibit RNA editing that is constrained in the 5′-seed/ cleavage/anchor regions and stabilize predicted mmu-let-7a:mRNA duplexes

Cited by 90 publications

References 46 publications

Dynamic isomiR regulation in Drosophila development

Dynamic isomiR regulation in Drosophila development

Comprehensive analysis of RNA-Seq data reveals extensive RNA editing in a human transcriptome

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

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