REDItools: high-throughput RNA editing detection made easy

Picardi, Ernesto; Pesole, Graziano

doi:10.1093/bioinformatics/btt287

Cited by 264 publications

(237 citation statements)

References 14 publications

Supporting

Mentioning

227

Contrasting

Order By: Relevance

“…In all cases, the consensus sequence deriving from deep sequencing coincided with the one determined by Sanger sequencing, confirming the cosegregation of newly identified variants with the known EBNA2 alleles. We also found one or more variable positions in all HDs (1-17) and individuals with MS (3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19). For all couples of variants lying on the same read (coverage $50), the hypothesis of independent segregation, indicative of random sequencing errors, was rejected through a x 2 test (p , 0.05), thus supporting the coexistence of different genotypes.…”

Section: Resultsmentioning

confidence: 67%

See 1 more Smart Citation

Epstein-Barr virus genetic variants are associated with multiple sclerosis

et al. 2015

View full text Add to dashboard Cite

Objective: We analyzed the Epstein-Barr nuclear antigen 2 (EBNA2) gene, which contains the most variable region of the viral genome, in persons with multiple sclerosis (MS) and control subjects to verify whether virus genetic variants are involved in disease development. 84-14.32; p 5 0.016) and underrepresentation of 1.3B allele (OR 5 0.23; 95% CI 0.08-0.51; p 5 0.0006). We identified new genetic variants, mostly 1.2 allele-and MS-associated (especially amino acid variation at position 245; OR 5 9.4; 95% CI 1.19-78.72; p 5 0.0123). In all cases, the consensus sequence from deep sequencing confirmed Sanger sequencing (including the cosegregation of newly identified variants with known EBNA2 alleles) and showed that the extent of genotype intraindividual variability was higher than expected: rare EBNA2 variants were detected in all HDs and patients with MS (range 1-17 and 3-19, respectively). EBNA2 variants did not seem to correlate with human leucocyte antigen typing or clinical/MRI features. MethodsConclusions: Our study unveils a strong association between Epstein-Barr virus genomic variants and MS, reinforcing the idea that Epstein-Barr virus contributes to disease development. Despite converging evidence supporting an etiologic role for Epstein-Barr virus (EBV) in multiple sclerosis (MS), we still do not know through which mechanisms the virus may contribute to disease development. 1 The potential pathogenic role of EBV genetic variants in MS may be in keeping with epidemiologic observations, in particular the geographic gradient of MS and the change in MS risk in migrants, 2 and with the reported association between virus genetic variants and EBV-related malignancies with different geographic distribution.3-5 Also, the discrepancy between the global diffusion of EBV infection and the low prevalence of MS could be at least in part explained by EBV genomic diversity that differently affects MS development.Major methodologic difficulties hinder the study of EBV variants through sequencing of the whole viral genome. To date, only 8 complete genome sequences have been described: 5 from patients with EBV-related diseases and 3 from healthy individuals.6 This is mainly attributable

show abstract

Section: Resultsmentioning

confidence: 67%

“…18 The viral allele assignment of both amplicon and Sanger EBNA2 sequences was performed using a methodology implemented in a python script (available on request). Further details on the EBNA2 amplicon deep sequencing and analysis can be found in appendix e-1 on the Neurology ® Web site at Neurology.org.…”

mentioning

confidence: 99%

Epstein-Barr virus genetic variants are associated with multiple sclerosis

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Next, we excluded cells with fewer than 1 million uniquely aligned reads and a mapping rate <70%, reducing the starting data set to 268 cells. On average, we analyzed 2.3 million reads per cell (Supplemental Table 1), calling RNA editing events using REDItools (Picardi and Pesole 2013) and retaining only sites supported by at least 10 independent reads.…”

Section: Resultsmentioning

confidence: 99%

Single-cell transcriptomics reveals specific RNA editing signatures in the human brain

Picardi

Horner

Pesole

2017

RNA

Self Cite

View full text Add to dashboard Cite

While RNA editing by A-to-I deamination is a requisite for neuronal function in humans, it is under-investigated in single cells. Here we fill this gap by analyzing RNA editing profiles of single cells from the brain cortex of living human subjects. We show that RNA editing levels per cell are bimodally distributed and distinguish between major brain cell types, thus providing new insights into neuronal dynamics.

show abstract

“…Consequently, improved methods to robustly characterize genome-wide RE events (Danecek et al 2012;Ramaswami et al 2012;Picardi and Pesole 2013) have enabled genome-wide characterization of RE in several, mostly nondiseased, tissues (Danecek et al 2012;Park et al 2012;Lagarrigue et al 2013;Bazak et al 2014;Blanc et al 2014;Han et al 2015). To date, however, only a few studies have reported RE events at a genome-wide scale in disease tissues; for example, Han et al (2015) showed that in various cancer types RE events are associated with survival and drug resistance.…”

Section: Discussionmentioning

confidence: 99%

“…After removal of known single nucleotide variants (SNVs) and using stringent filters for base (quality score > 25) and mapping quality (quality score > 20) (see Methods), we identified 201,322 unique mRNA sites with an alternate allele significantly different from its corresponding DNA sequence in at least one sample (BH-corrected P-value < 0.05, using REDItools) (Supplemental Fig. S1; Picardi and Pesole 2013). This set of candidate RE sites was further analyzed to minimize other potential sources of systematic bias, including variant distance bias (VDB; i.e., to account for false variants that tend to occur at a fixed distance from the end of reads), removal of read sequences with very high similarity (>95%) with other genomic regions, and strand bias (i.e., to account for variants observed only in either the forward or reverse strand of mapped reads) (see Figure 1. (A) Summary of study design for detecting significant differential RNA editing events associated with epilepsy.…”

Section: Methodsmentioning

confidence: 99%

Genome-wide analysis of differential RNA editing in epilepsy

et al. 2017

View full text Add to dashboard Cite

The recoding of genetic information through RNA editing contributes to proteomic diversity, but the extent and significance of RNA editing in disease is poorly understood. In particular, few studies have investigated the relationship between RNA editing and disease at a genome-wide level. Here, we developed a framework for the genome-wide detection of RNA sites that are differentially edited in disease. Using RNA-sequencing data from 100 hippocampi from mice with epilepsy (pilocarpine-temporal lobe epilepsy model) and 100 healthy control hippocampi, we identified 256 RNA sites (overlapping with 87 genes) that were significantly differentially edited between epileptic cases and controls. The degree of differential RNA editing in epileptic mice correlated with frequency of seizures, and the set of genes differentially RNA-edited between case and control mice were enriched for functional terms highly relevant to epilepsy, including "neuron projection" and "seizures." Genes with differential RNA editing were preferentially enriched for genes with a genetic association to epilepsy. Indeed, we found that they are significantly enriched for genes that harbor nonsynonymous de novo mutations in patients with epileptic encephalopathy and for common susceptibility variants associated with generalized epilepsy. These analyses reveal a functional convergence between genes that are differentially RNA-edited in acquired symptomatic epilepsy and those that contribute risk for genetic epilepsy. Taken together, our results suggest a potential role for RNA editing in the epileptic hippocampus in the occurrence and severity of epileptic seizures.

show abstract

REDItools: high-throughput RNA editing detection made easy

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 264 publications

References 14 publications

Epstein-Barr virus genetic variants are associated with multiple sclerosis

Epstein-Barr virus genetic variants are associated with multiple sclerosis

Single-cell transcriptomics reveals specific RNA editing signatures in the human brain

Genome-wide analysis of differential RNA editing in epilepsy

Contact Info

Product

Resources

About