ADAR1 deaminase contributes to scheduled skeletal myogenesis progression via stage-specific functions

Hsieh, Chia‐Ling; Liu, Hsuan; Huang, Yun‐Ching; Kang, Lin; Chen, H. W.; Chen, Y. T.; Wee, Y. R.; Chen, S. J.; Tan, Bertrand Chin‐Ming

doi:10.1038/cdd.2013.197

Cited by 29 publications

(33 citation statements)

References 53 publications

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“…4j). Hence, our analysis suggests that AIMP2 functions in myoblasts, at least in part, by blocking ADAR1-mediated RNA editing, which has recently been shown to be important for the myoblast-to-myotube transition 31 .…”

mentioning

confidence: 73%

Dynamic landscape and regulation of RNA editing in mammals

Tan

Shanmugam

et al. 2017

Nature

520

628

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Adenosine-to-inosine (A-to-I) RNA editing is a conserved post-transcriptional mechanism mediated by ADAR enzymes that diversifies the transcriptome by altering selected nucleotides in RNA molecules1. Although many editing sites have recently been discovered2–7, the extent to which most sites are edited and how the editing is regulated in different biological contexts are not fully understood8–10. Here we report dynamic spatiotemporal patterns and new regulators of RNA editing, discovered through an extensive profiling of A-to-I RNA editing in 8,551 human samples (representing 53 body sites from 552 individuals) from the Genotype-Tissue Expression (GTEx) project and in hundreds of other primate and mouse samples. We show that editing levels in non-repetitive coding regions vary more between tissues than editing levels in repetitive regions. Globally, ADAR1 is the primary editor of repetitive sites and ADAR2 is the primary editor of non-repetitive coding sites, whereas the catalytically inactive ADAR3 predominantly acts as an inhibitor of editing. Cross-species analysis of RNA editing in several tissues revealed that species, rather than tissue type, is the primary determinant of editing levels, suggesting stronger cis-directed regulation of RNA editing for most sites, although the small set of conserved coding sites is under stronger trans-regulation. In addition, we curated an extensive set of ADAR1 and ADAR2 targets and showed that many editing sites display distinct tissue-specific regulation by the ADAR enzymes in vivo. Further analysis of the GTEx data revealed several potential regulators of editing, such as AIMP2, which reduces editing in muscles by enhancing the degradation of the ADAR proteins. Collectively, our work provides insights into the complex cis- and trans-regulation of A-to-I editing.

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mentioning

confidence: 73%

Dynamic landscape and regulation of RNA editing in mammals

Tan

Shanmugam

et al. 2017

Nature

520

628

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“…To detect potential candidate regulators among the 206 common genes that were identified in our study, we performed in silico identification of enriched TF binding motifs and TF with the iRegulon Cytoscape plugin [ 25 ]. We detected different enriched motifs that can bind directly to candidate TF (see Additional file 9 : Table S7) such as the interferon regulatory factor 1 ( IRF1 ) TF (enriched motif ID = transfac_pro-M00747; NES = 3.860; Targets = 57), which was previously identified as a master regulator in the bovine skeletal muscle of two beef cattle breeds (Piedmontese x Hereford and Wagyu x Hereford) [ 46 ]; the nuclear factor of activated T - cells, cytoplasmic, calcineurin - dependent 4 ( NFATC4 ) TF (enriched motif ID = transfac_pro-M01734; NES = 3.717, Targets = 50), which encodes a member of the nuclear factor of activated T cells (NFAT) DNA-binding transcription complex protein family that plays an important role in skeletal muscle development and growth [ 47 ] and in glucose and insulin homeostasis [ 48 ]; the core - binding factor, beta subunit ( CBFB ) TF (enriched motif ID = hdpi-CBFB; NES = 3.339; Targets = 43), which encodes a beta subunit of a heterodimeric PEBP2/CBF TF family that regulates genes involved in osteogenesis [ 49 ]; the serum response factor ( SRF ) (enriched motif ID = yetfasco-145; NES = 3.295; Targets = 23), the adenosine deaminase, RNA - specific, B1 ( ADARB1 ) (enriched motif ID = hdpi-ADARB1; NES = 3.231; Targets = 63) and the mex - 3 RNA binding family member C ( MEX3C ) (enriched motif ID = hdpi-RKHD2; NES = 3.339; Targets = 43), which play a crucial role in skeletal muscle growth and maturation [ 50 ], skeletal myogenesis [ 51 ], and postnatal growth and energy balance regulation [ 52 , 53 ], respectively. Finally, iRegulon identified the GATA binding protein 2 ( GATA2 ) (NES = 4.887) as an enriched TF that can bind 73 of the 206 analyzed genes.…”

Section: Resultsmentioning

confidence: 99%

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds

Ramayo-Caldas¹,

Renand²,

Ballester³

et al. 2016

Genet Sel Evol

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BackgroundStudies to identify markers associated with beef tenderness have focused on Warner–Bratzler shear force (WBSF) but the interplay between the genes associated with WBSF has not been explored. We used the association weight matrix (AWM), a systems biology approach, to identify a set of interacting genes that are co-associated with tenderness and other meat quality traits, and shared across the Charolaise, Limousine and Blonde d’Aquitaine beef cattle breeds.ResultsGenome-wide association studies were performed using ~500K single nucleotide polymorphisms (SNPs) and 17 phenotypes measured on more than 1000 animals for each breed. First, this multi-trait approach was applied separately for each breed across 17 phenotypes and second, between- and across-breed comparisons at the AWM and functional levels were performed. Genetic heterogeneity was observed, and most of the variants that were associated with WBSF segregated within rather than across breeds. We identified 206 common candidate genes associated with WBSF across the three breeds. SNPs in these common genes explained between 28 and 30 % of the phenotypic variance for WBSF. A reduced number of common SNPs mapping to the 206 common genes were identified, suggesting that different mutations may target the same genes in a breed-specific manner. Therefore, it is likely that, depending on allele frequencies and linkage disequilibrium patterns, a SNP that is identified for one breed may not be informative for another unrelated breed. Well-known candidate genes affecting beef tenderness were identified. In addition, some of the 206 common genes are located within previously reported quantitative trait loci for WBSF in several cattle breeds. Moreover, the multi-breed co-association analysis detected new candidate genes, regulators and metabolic pathways that are likely involved in the determination of meat tenderness and other meat quality traits in beef cattle.ConclusionsOur results suggest that systems biology approaches that explore associations of correlated traits increase statistical power to identify candidate genes beyond the one-dimensional approach. Further studies on the 206 common genes, their pathways, regulators and interactions will expand our knowledge on the molecular basis of meat tenderness and could lead to the discovery of functional mutations useful for genomic selection in a multi-breed beef cattle context.Electronic supplementary materialThe online version of this article (doi:10.1186/s12711-016-0216-y) contains supplementary material, which is available to authorized users.

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“…RNA-IP was performed according to a previous report (47). Briefly, cells were washed once with PBS, and lysed by Polysomal Lysis Buffer (100 mM KCl, 5 mM MgCl 2 , 10 mM HEPES (pH 7.0), 0.5% Nonidet P-40, 1 mM DTT, 50 units/ml of RNase-OUT, and protease inhibitor (Roche)).…”

Section: Rna-ip Experimentsmentioning

confidence: 99%

Tumor-associated intronic editing of HNRPLL generates a novel splicing variant linked to cell proliferation

Chen¹,

Chang²,

Liu

et al. 2018

Journal of Biological Chemistry

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Processing of the eukaryotic transcriptome is a dynamic regulatory mechanism that confers genetic diversity, and splicing and adenosine to inosine (A-to-I) RNA editing are well-characterized examples of such processing. Growing evidence reveals the cross-talk between the splicing and RNA editing, but there is a paucity of substantial evidence for its mechanistic details and contribution in a physiological context. Here, our findings demonstrate that tumor-associated differential RNA editing, in conjunction with splicing machinery, regulates the expression of variants of , a gene encoding splicing factor. We discovered an transcript variant containing an additional exon 12A (), which is a substrate of ADAR1 and ADAR2. denosineeaminases cting onNA (ADAR) direct deaminase-dependent expression of the transcript, and ADAR-mediated regulation of is largely splicing-based, and does not affect the stability or nucleocytoplasmic distribution of the transcript. Furthermore, ADAR-mediated modification of exon 12A generates an enhancer for the oncogenic splicing factor SRSF1 and consequently promotes the frequency of alternative splicing. Gene expression profiling by RNA-seq revealed that acts distinctly from HNRPLL and regulates a set of growth-related genes, such as cyclin and growth factor receptor Accordingly, silencing expression leads to impaired clonogenic ability and enhanced sensitivity to doxorubicin, thus highlighting the significance of this alternative isoform in tumor cell survival. In summary, we present the interplay of RNA editing and splicing as a regulatory mechanism of gene expression and also its physiological relevance. These findings extend our understanding of transcriptional dynamics and provide a mechanistic explanation to the link of RNA editors to tumorigenesis.

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ADAR1 deaminase contributes to scheduled skeletal myogenesis progression via stage-specific functions

Cited by 29 publications

References 53 publications

Dynamic landscape and regulation of RNA editing in mammals

Dynamic landscape and regulation of RNA editing in mammals

Multi-breed and multi-trait co-association analysis of meat tenderness and other meat quality traits in three French beef cattle breeds

Tumor-associated intronic editing of HNRPLL generates a novel splicing variant linked to cell proliferation

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