Population and allelic variation of A-to-I RNA editing in human transcriptomes

Park, Eddie; Guo, Jianqiang; Shen, Shihao; Demirdjian, Levon; Wu, Ying; Lin, Lan; Xing, Yi

doi:10.1186/s13059-017-1270-7

Cited by 44 publications

(50 citation statements)

References 78 publications

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“…To provide a quantitative assessment of editing in a larger population of animals, the base composition of candidate sites identified in the nine 'discovery' animals was assessed in 355 additional animals for which RNAseq data was available. The proportion of reads edited in these 'quantification' animals was defined as phi (Φ; (Park et al, 2017)). Phi values varied widely across sites: from 0.03% to 90.04% for A-to-I reads (median 12.81, mean 17.89).…”

Section: Proportions Of Reads Editedmentioning

confidence: 99%

“…Since numerous regulatory effects have been attributed to RNA editing, genetic regulation of editing poses another potential mechanism to explain impacts on physiological traits. In three recent studies conducted in Drosophila (Ramaswami et al, 2015), mice (Gu et al, 2016), and humans (Park et al, 2017), researchers demonstrated the application of QTL mapping approaches to reveal widespread genetic modulation of RNA-editing. In the current study, we aimed to build on these studies by characterising the genetic landscape of RNA-editing in cattle, and more specifically, use these data to investigate potential regulatory effects of identified loci on gene expression and complex quantitative traits.…”

Section: Introductionmentioning

confidence: 99%

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Widespread cis-regulation of RNA-editing in a large mammal

Lopdell

Couldrey

Tiplady

et al. 2018

Preprint

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Post-transcriptional RNA editing may regulate transcript expression and diversity in cells, with potential impacts on various aspects of physiology and environmental adaptation. A small number of recent genome-wide studies in Drosophila, mouse, and human have shown that RNA editing can be genetically modulated, highlighting loci that quantitatively impact editing of transcripts. The potential gene expression and physiological consequences of these RNA editing quantitative trait loci (edQTL), however, are almost entirely unknown. Here, we present analyses of RNA editing in a large domestic mammal (Bos taurus), where we use whole genome and high depth RNA sequencing to discover, characterise, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply-sequenced cows, we identify 2,001 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (97.4%). Most sites are predicted to reside in double-stranded secondary structures (85.7%), and quantification of the rates of editing in an additional 355 cows reveals editing is negatively correlated with gene expression in the majority of cases. Genetic analyses of RNA editing and gene expression highlights 67 cis-regulated edQTL, of which seven appear to co-segregate with expression QTL effects. Trait association analyses in a separate population of 9,988 lactating cows also shows nine of the cis-edQTL coincide with at least one co-segregating lactation QTL. Together, these results enhance our understanding of RNA editing dynamics in mammals, and suggest mechanistic links by which loci may impact phenotype through RNA-editing mediated processes.

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Section: Proportions Of Reads Editedmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Widespread cis-regulation of RNA-editing in a large mammal

Lopdell

Couldrey

Tiplady

et al. 2018

Preprint

View full text Add to dashboard Cite

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“…The threshold for minimum RNA-sequencing reads is necessary for distinguishing SNV positions with monoallelic reference signal from non-expressed SNV positions and is critical for the estimation of VAFRNA. In the presented results, we have selected a threshold of 10 RNA-sequencing reads covering each SNV position of interest, based on considerations for sequencing depth and confidence of the VAFRNA assessment, and also following trends in the assessment of RNA editing from RNA-sequencing data (Park et al, 2017). Our experiments with various minimum thresholds show that higher thresholds increase the accuracy of the VAFRNA estimation, naturally retaining a lower number of variants for analysis (Movassagh et al, 2016).…”

Section: Reqtl Usagementioning

confidence: 99%

ReQTL – an allele-level measure of variation-expression genomic relationships

Alomran

Słowiński

et al. 2018

Preprint

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Motivation:By testing for association of DNA genotypes with gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation can be measured at expressed genome regions, and differs from the DNA genotype in sites subjected to regulatory forces. Therefore, assessment of correlation between RNA genetic variation and gene expression can reveal regulatory genomic relationships in addition to eQTLs. Results:We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele frequency (VAF) at expressed SNV loci in the transcriptome. We exemplify the method on sets of RNA-sequencing data from human tissues obtained though the Genotype-Tissue Expression Project (GTEx) and demonstrate that ReQTL analyses show consistently high performance and sufficient power to identify both previously known and novel molecular associations. The majority of the SNVs implicated in significant cis-ReQTLs identified by our analysis were previously reported as significant cis-eQTL loci. Notably, trans ReQTL loci in our data were substantially enriched in RNA-editing sites. In summary, ReQTL analyses are computationally feasible and do not require matched DNA data, hence they have a high potential to facilitate the discovery of novel molecular interactions through exploration of the increasingly accessible RNA-sequencing datasets.Availability and implementation: Sample scripts used in our ReQTL analyses are available with the Supplementary Material (ReQTL_sample_code).

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“…Editing can be enhanced or suppressed by deviations from perfect base-pairing (i.e., mismatches, bulges and loops), suggesting complex structural contributions to editing specificity [14][15][16] . The quantitative trait loci (QTL) mapping approach has been used to identify genetic variants associated with variability in RNA editing in Drosophila and humans, demonstrating that many editing QTLs (edQTL) can act through changes in the local and distal secondary structure for edited dsRNAs, consistent with importance of RNA structure 20,21 . Nevertheless, few general properties have emerged across different substrates, suggesting complex structural contributions to editing specificity 22 .…”

Section: Introductionmentioning

confidence: 99%

Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis

Liu

Sun

Shcherbina

et al. 2019

Preprint

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Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs (dsRNAs). How the RNA sequence and structure (i.e., the cis-regulation) determine the editing efficiency and specificity is poorly understood, despite a compelling need towards functional understanding of known editing events and transcriptome engineering of desired adenosines. We developed a CRISPR/Cas9-mediated saturation mutagenesis approach to generate comprehensive libraries of point mutations near an editing site and its editing complementary sequence (ECS) at the endogenous genomic locus. We used machine learning to integrate diverse RNA sequence features and computationally predicted structures to model editing levels measured by deep sequencing and identified cis-regulatory features of RNA editing. As proof-of-concept, we applied this integrative approach to three editing substrates. Our models explained over 70% of variation in editing levels. The models indicate that RNA sequence and structure features synergistically determine the editing levels.Our integrative approach can be broadly applied to any editing site towards the goal of deciphering the RNA editing code. It also provides guidance for designing and screening of antisense RNA sequences that form dsRNA duplex with the target transcript for ADAR-mediated transcriptome engineering.

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Population and allelic variation of A-to-I RNA editing in human transcriptomes

Cited by 44 publications

References 78 publications

Widespread cis-regulation of RNA-editing in a large mammal

Widespread cis-regulation of RNA-editing in a large mammal

ReQTL – an allele-level measure of variation-expression genomic relationships

Learning cis-regulatory principles of ADAR-based RNA editing from CRISPR-mediated mutagenesis

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