HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis

Flati, Tiziano; Gioiosa, Silvia; Spallanzani, Nicola; Tagliaferri, Ilario; Diroma, Maria Angela; Pesole, Graziano; Chillemi, Giovanni; Picardi, Ernesto; Castrignanò, Tiziana

doi:10.1186/s12859-020-03562-x

Cited by 38 publications

(35 citation statements)

References 18 publications

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“…The de novo detection of RNA editing events was performed at the CINECA HPC Data Center (Italy) consuming ∼30 millions of CPU hours running an optimized version of our REDItools package whose algorithm scales almost linearly with the number of available cores ( 25 ). Indeed, the editing identification in massive transcriptome sequencing data is computationally intensive and time consuming, requiring the screening of the entire human genome, position by position, in order to look at nucleotide differences between RNA reads and the corresponding reference genomic site.…”

Section: Data Collection and Processingmentioning

confidence: 99%

“…To speed up the browsing and traversing of aligned RNAseq reads, the editing detection was distributed over multiple computing nodes, each working on a given genomic interval. Moreover, the editing identification at nucleotide level was improved by a novel routine developed to increase the data loading efficiency, raising the algorithm performances of 8–10 times ( 25 ).…”

Section: Data Collection and Processingmentioning

confidence: 99%

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REDIportal: millions of novel A-to-I RNA editing events from thousands of RNAseq experiments

Mansi

Tangaro

Giudice

et al. 2020

Nucleic Acids Research

Self Cite

110

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RNA editing is a relevant epitranscriptome phenomenon able to increase the transcriptome and proteome diversity of eukaryotic organisms. ADAR mediated RNA editing is widespread in humans in which millions of A-to-I changes modify thousands of primary transcripts. RNA editing has pivotal roles in the regulation of gene expression or modulation of the innate immune response or functioning of several neurotransmitter receptors. Massive transcriptome sequencing has fostered the research in this field. Nonetheless, different aspects of the RNA editing biology are still unknown and need to be elucidated. To support the study of A-to-I RNA editing we have updated our REDIportal catalogue raising its content to about 16 millions of events detected in 9642 human RNAseq samples from the GTEx project by using a dedicated pipeline based on the HPC version of the REDItools software. REDIportal now allows searches at sample level, provides overviews of RNA editing profiles per each RNAseq experiment, implements a Gene View module to look at individual events in their genic context and hosts the CLAIRE database. Starting from this novel version, REDIportal will start collecting non-human RNA editing changes for comparative genomics investigations. The database is freely available at http://srv00.recas.ba.infn.it/atlas/index.html.

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Section: Data Collection and Processingmentioning

confidence: 99%

Section: Data Collection and Processingmentioning

confidence: 99%

REDIportal: millions of novel A-to-I RNA editing events from thousands of RNAseq experiments

Mansi

Tangaro

Giudice

et al. 2020

Nucleic Acids Research

Self Cite

110

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show abstract

“…Taking Huntington disease (HD) as an example, it also introduces how to compare the differences in RNA editing levels in different tissues. Moreover, they also developed high-performance HPC-REDItools for large-scale samples, which greatly improves the speed of operation ( 100 ). For the identification of RNA editing in tumor samples with only RNA-seq, we recommend HISAT2 to handle RNA-seq data and REDITools to conduct RNA editing calling.…”

Section: Rna Editing Site Identificationmentioning

confidence: 99%

A-to-I RNA Editing in Cancer: From Evaluating the Editing Level to Exploring the Editing Effects

et al. 2021

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As an important regulatory mechanism at the posttranscriptional level in metazoans, adenosine deaminase acting on RNA (ADAR)-induced A-to-I RNA editing modification of double-stranded RNA has been widely detected and reported. Editing may lead to non-synonymous amino acid mutations, RNA secondary structure alterations, pre-mRNA processing changes, and microRNA-mRNA redirection, thereby affecting multiple cellular processes and functions. In recent years, researchers have successfully developed several bioinformatics software tools and pipelines to identify RNA editing sites. However, there are still no widely accepted editing site standards due to the variety of parallel optimization and RNA high-seq protocols and programs. It is also challenging to identify RNA editing by normal protocols in tumor samples due to the high DNA mutation rate. Numerous RNA editing sites have been reported to be located in non-coding regions and can affect the biosynthesis of ncRNAs, including miRNAs and circular RNAs. Predicting the function of RNA editing sites located in non-coding regions and ncRNAs is significantly difficult. In this review, we aim to provide a better understanding of bioinformatics strategies for human cancer A-to-I RNA editing identification and briefly discuss recent advances in related areas, such as the oncogenic and tumor suppressive effects of RNA editing.

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“…REDItools 2[19, 20] and JACUSA[21] were used together to call the SNVs in the transcriptome of SARS-CoV-2. With REDItools 2, all SNVs within 15 nucleotides from the beginning or the end of the reads were removed to avoid artifacts due to misalignments.…”

Section: Methodsmentioning

confidence: 99%

Emerging SARS-CoV-2 mutation hotspots associated with clinical outcomes

Pang

Li²,

Zhang

et al. 2021

Preprint

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Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes and related factors is critical for treatment and prevention. Here, we analyzed 209,551 high-coverage complete virus sequences and 321 RNA-seq samples to mine the mutations associated with clinical outcome in the SARS-CoV-2 genome. Several important hotspot variants were found to be associated with severe clinical outcomes. Q57H variant in ORF3a protein were found to be associated with higher mortality rate, and was high proportion in severe cases (39.36%) and 501Y.V2 strains (100%) but poorly proportional to asymptomatic cases (10.04%). T265I could change nsp2 structure and mitochondrial permeability, and evidently higher in severe cases (20.12%) and 501Y.V2 strains (100%) but lower in asymptomatic cases (1.43%). Additionally, R203K and G204R could decrease the flexibility and immunogenic property of N protein with high frequency among severe cases, VUI 202012/01 and 484K.V2 strains. Interestingly, the SARS-CoV-2 genome was more susceptible to mutation because of the high frequency of nt14408 mutation (which located in RNA polymerase) and the high expression levels of ADAR and APOBEC in severe clinical outcomes. In conclusion, several important mutation hotspots in the SARS-CoV-2 genome associated with clinical outcomes was found in our study, and that might correlate with different SARS-CoV-2 mortality rates.

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HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis

Cited by 38 publications

References 18 publications

REDIportal: millions of novel A-to-I RNA editing events from thousands of RNAseq experiments

REDIportal: millions of novel A-to-I RNA editing events from thousands of RNAseq experiments

A-to-I RNA Editing in Cancer: From Evaluating the Editing Level to Exploring the Editing Effects

Emerging SARS-CoV-2 mutation hotspots associated with clinical outcomes

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