Browse
Submit Data
Databases
API
Help

Dataset Information

37 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Genetic mapping uncovers cis-regulatory landscape of RNA editing.

ABSTRACT: Adenosine-to-inosine (A-to-I) RNA editing, catalysed by ADAR enzymes conserved in metazoans, plays an important role in neurological functions. Although the fine-tuning mechanism provided by A-to-I RNA editing is important, the underlying rules governing ADAR substrate recognition are not well understood. We apply a quantitative trait loci (QTL) mapping approach to identify genetic variants associated with variability in RNA editing. With very accurate measurement of RNA editing levels at 789 sites in 131 Drosophila melanogaster strains, here we identify 545 editing QTLs (edQTLs) associated with differences in RNA editing. We demonstrate that many edQTLs can act through changes in the local secondary structure for edited dsRNAs. Furthermore, we find that edQTLs located outside of the edited dsRNA duplex are enriched in secondary structure, suggesting that distal dsRNA structure beyond the editing site duplex affects RNA editing efficiency. Our work will facilitate the understanding of the cis-regulatory code of RNA editing.

SUBMITTER: Ramaswami G

PROVIDER: S-EPMC4573499 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

RNA editing affects cis-regulatory elements and predicts adverse cancer survival.

Project description:BackgroundRNA editing exerts critical impacts on numerous biological processes and thus are implicated in crucial human phenotypes, including tumorigenesis and prognosis. While previous studies have analyzed aggregate RNA editing activity at the sample level and associated it with overall cancer survival, there is not yet a large-scale disease-specific survival study to examine genome-wide RNA editing sites' prognostic value taking into account the host gene expression and clinical variables.MethodsIn this study, we solved comprehensive Cox proportional models of disease-specific survival on individual RNA-editing sites plus host gene expression and critical demographic covariates. This allowed us to interrogate the prognostic value of a large number of RNA-editing sites at single-nucleotide resolution.ResultsAs a result, we identified 402 gene-proximal RNA-editing sites that generally predict adverse cancer survival. For example, an RNA-editing site residing in ZNF264 indicates poor survival of uterine corpus endometrial carcinoma, with a hazard ratio of 2.13 and an adjusted p-value of 4.07 × 10-7 . Some of these prognostic RNA-editing sites mediate the binding of RNA binding proteins and microRNAs, thus propagating their impacts to extensive regulatory targets.ConclusionsIn conclusion, RNA editing affects cis-regulatory elements and predicts adverse cancer survival.

| S-EPMC8419749 | biostudies-literature

Cis regulatory effects on A-to-I RNA editing in related Drosophila species.

Project description:Adenosine-to-inosine RNA editing modifies maturing mRNAs through the binding of adenosine deaminase acting on RNA (Adar) proteins to double-stranded RNA structures in a process critical for neuronal function. Editing levels at individual editing sites span a broad range and are mediated by both cis-acting elements (surrounding RNA sequence and secondary structure) and trans-acting factors. Here, we aim to determine the roles that cis-acting elements and trans-acting factors play in regulating editing levels. Using two closely related Drosophila species, D. melanogaster and D. sechellia, and their F1 hybrids, we dissect the effects of cis sequences from trans regulators on editing levels by comparing species-specific editing in parents and their hybrids. We report that cis sequence differences are largely responsible for editing level differences between these two Drosophila species. This study presents evidence for cis sequence and structure changes as the dominant evolutionary force that modulates RNA editing levels between these Drosophila species.

| S-EPMC4418222 | biostudies-literature

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

Project description:Adenosine-to-inosine (A-to-I) RNA editing catalyzed by ADAR enzymes occurs in double-stranded RNAs. Despite a compelling need towards predictive understanding of natural and engineered editing events, how the RNA sequence and structure determine the editing efficiency and specificity (i.e., cis-regulation) is poorly understood. We apply a CRISPR/Cas9-mediated saturation mutagenesis approach to generate libraries of mutations near three natural editing substrates at their endogenous genomic loci. We use machine learning to integrate diverse RNA sequence and structure features to model editing levels measured by deep sequencing. We confirm known features and identify new features important for RNA editing. Training and testing XGBoost algorithm within the same substrate yield models that explain 68 to 86 percent of substrate-specific variation in editing levels. However, the models do not generalize across substrates, suggesting complex and context-dependent regulation patterns. Our integrative approach can be applied to larger scale experiments towards deciphering the RNA editing code.

| S-EPMC8041805 | biostudies-literature

Evolutionary analysis reveals regulatory and functional landscape of coding and non-coding RNA editing.

Project description:Adenosine-to-inosine RNA editing diversifies the transcriptome and promotes functional diversity, particularly in the brain. A plethora of editing sites has been recently identified; however, how they are selected and regulated and which are functionally important are largely unknown. Here we show the cis-regulation and stepwise selection of RNA editing during Drosophila evolution and pinpoint a large number of functional editing sites. We found that the establishment of editing and variation in editing levels across Drosophila species are largely explained and predicted by cis-regulatory elements. Furthermore, editing events that arose early in the species tree tend to be more highly edited in clusters and enriched in slowly-evolved neuronal genes, thus suggesting that the main role of RNA editing is for fine-tuning neurological functions. While nonsynonymous editing events have been long recognized as playing a functional role, in addition to nonsynonymous editing sites, a large fraction of 3'UTR editing sites is evolutionarily constrained, highly edited, and thus likely functional. We find that these 3'UTR editing events can alter mRNA stability and affect miRNA binding and thus highlight the functional roles of noncoding RNA editing. Our work, through evolutionary analyses of RNA editing in Drosophila, uncovers novel insights of RNA editing regulation as well as its functions in both coding and non-coding regions.

| S-EPMC5319793 | biostudies-literature

L-GIREMI uncovers RNA editing sites in long-read RNA-seq.

Project description:Although long-read RNA-seq is increasingly applied to characterize full-length transcripts it can also enable detection of nucleotide variants, such as genetic mutations or RNA editing sites, which is significantly under-explored. Here, we present an in-depth study to detect and analyze RNA editing sites in long-read RNA-seq. Our new method, L-GIREMI, effectively handles sequencing errors and read biases. Applied to PacBio RNA-seq data, L-GIREMI affords a high accuracy in RNA editing identification. Additionally, our analysis uncovered novel insights about RNA editing occurrences in single molecules and double-stranded RNA structures. L-GIREMI provides a valuable means to study nucleotide variants in long-read RNA-seq.

| S-EPMC10360234 | biostudies-literature

Genetic validation of whole-transcriptome sequencing for mapping expression affected by cis-regulatory variation.

Project description:Identifying associations between genotypes and gene expression levels using microarrays has enabled systematic interrogation of regulatory variation underlying complex phenotypes. This approach has vast potential for functional characterization of disease states, but its prohibitive cost, given hundreds to thousands of individual samples from populations have to be genotyped and expression profiled, has limited its widespread application.Here we demonstrate that genomic regions with allele-specific expression (ASE) detected by sequencing cDNA are highly enriched for cis-acting expression quantitative trait loci (cis-eQTL) identified by profiling of 500 animals in parallel, with up to 90% agreement on the allele that is preferentially expressed. We also observed widespread noncoding and antisense ASE and identified several allele-specific alternative splicing variants.Monitoring ASE by sequencing cDNA from as little as one sample is a practical alternative to expression genetics for mapping cis-acting variation that regulates RNA transcription and processing.

| S-EPMC3091669 | biostudies-literature

cis Recognition elements in plant mitochondrion RNA editing.

Project description:RNA editing in higher plant mitochondria modifies mRNA sequences by means of C-to-U conversions at highly specific sites. To determine the cis elements involved in recognition of an editing site in plant mitochondria, deletion and site-directed mutation constructs containing the cognate cox II mitochondrial gene were introduced into purified mitochondria by electroporation. The RNA editing status was analyzed for precursor and spliced transcripts from the test construct. We found that only a restricted number of nucleotides in the vicinity of the target C residue were necessary for recognition by the editing machinery and that the nearest neighbor 3' residues were crucial for the editing process. We provide evidence that two functionally distinguishable sequences can be defined: the 16-nucleotide 5' region, which can be replaced with the same region from another editing site, and a 6-nucleotide 3' region specific to the editing site. The latter region may play a role in positioning the actual editing residue.

| S-EPMC99851 | biostudies-literature

Mapping the cis-regulatory architecture of the human retina reveals noncoding genetic variation in disease.

Project description:The interplay of transcription factors and cis-regulatory elements (CREs) orchestrates the dynamic and diverse genetic programs that assemble the human central nervous system (CNS) during development and maintain its function throughout life. Genetic variation within CREs plays a central role in phenotypic variation in complex traits including the risk of developing disease. We took advantage of the retina, a well-characterized region of the CNS known to be affected by pathogenic variants in CREs, to establish a roadmap for characterizing regulatory variation in the human CNS. This comprehensive analysis of tissue-specific regulatory elements, transcription factor binding, and gene expression programs in three regions of the human visual system (retina, macula, and retinal pigment epithelium/choroid) reveals features of regulatory element evolution that shape tissue-specific gene expression programs and defines regulatory elements with the potential to contribute to Mendelian and complex disorders of human vision.

| S-EPMC7183164 | biostudies-literature

GPEdit: the genetic and pharmacogenomic landscape of A-to-I RNA editing in cancers.

Project description:Altered A-to-I RNA editing has been widely observed in many human cancers and some editing sites are associated with drug sensitivity, implicating its therapeutic potential. Increasing evidence has demonstrated that a quantitative trait loci mapping approach is effective to understanding the genetic basis of RNA editing. We systematically performed RNA editing quantitative trait loci (edQTL) analysis in 33 human cancer types for >10 000 cancer samples and identified 320 029 edQTLs. We also identified 1688 ed-QTLs associated with patient overall survival and 4672 ed-QTLs associated with GWAS risk loci. Furthermore, we demonstrated the associations between RNA editing and >1000 anti-cancer drug response with ∼3.5 million significant associations. We developed GPEdit (https://hanlab.uth.edu/GPEdit/) to facilitate a global map of the genetic and pharmacogenomic landscape of RNA editing. GPEdit is a user-friendly and comprehensive database that provides an opportunity for a better understanding of the genetic impact and the effects on drug response of RNA editing in cancers.

| S-EPMC8728115 | biostudies-literature

A porcine brain-wide RNA editing landscape.

Project description:Adenosine-to-inosine (A-to-I) RNA editing, catalyzed by ADAR enzymes, is an essential post-transcriptional modification. Although hundreds of thousands of RNA editing sites have been reported in mammals, brain-wide analysis of the RNA editing in the mammalian brain remains rare. Here, a genome-wide RNA-editing investigation is performed in 119 samples, representing 30 anatomically defined subregions in the pig brain. We identify a total of 682,037 A-to-I RNA editing sites of which 97% are not identified before. Within the pig brain, cerebellum and olfactory bulb are regions with most edited transcripts. The editing level of sites residing in protein-coding regions are similar across brain regions, whereas region-distinct editing is observed in repetitive sequences. Highly edited conserved recoding events in pig and human brain are found in neurotransmitter receptors, demonstrating the evolutionary importance of RNA editing in neurotransmission functions. Although potential data biases caused by age, sex or health status are not considered, this study provides a rich resource to better understand the evolutionary importance of post-transcriptional RNA editing.

| S-EPMC8192503 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data