Large-scale prediction of ADAR-mediated effective human A-to-I RNA editing

AbstractBackgroundAs the number of RNA-seq datasets that become available to explore transcriptome diversity increases, so does the need for easy-to-use comprehensive computational workflows. Many available tools facilitate analyses of one of the two major mechanisms of transcriptome diversity, namely, differential expression of isoforms due to alternative splicing, while the second major mechanism - RNA editing due to post-transcriptional changes of individual nucleotides – remains under-appreciated. Both these mechanisms play an essential role in physiological and diseases processes, including cancer and neurological disorders. However, elucidation of RNA editing events at transcriptome-wide level requires increasingly complex computational tools, in turn resulting in a steep entrance barrier for labs who are interested in high-throughput variant calling applications on a large scale but lack the manpower and/or computational expertise.ResultsHere we present an easy-to-use, fully automated, computational pipeline (Automated Isoform Diversity Detector, AIDD) that contains open source tools for various tasks needed to map transcriptome diversity, including RNA editing events. To facilitate reproducibility and avoid system dependencies, the pipeline is contained within a pre-configured VirtualBox environment. The analytical tasks and format conversions are accomplished via a set of automated scripts that enable the user to go from a set of raw data, such as fastq files, to publication-ready results and figures in one step. A publicly available dataset of Zika virus-infected neural progenitor cells is used to illustrate AIDD’s capabilities.ConclusionsAIDD pipeline offers a user-friendly interface for comprehensive and reproducible RNA-seq analyses. Among unique features of AIDD are its ability to infer RNA editing patterns, including ADAR editing, and inclusion of Guttman scale patterns for time series analysis of such editing landscapes. AIDD-based results show importance of diversity of ADAR isoforms, key RNA editing enzymes linked with the innate immune system and viral infections. These findings offer insights into the potential role of ADAR editing dysregulation in the disease mechanisms, including those of congenital Zika syndrome. Because of its automated all-inclusive features, AIDD pipeline enables even a novice user to easily explore common mechanisms of transcriptome diversity, including RNA editing landscapes.

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Large-scale detection and analysis of RNA editing in grape mtDNA by RNA deep-sequencing

Nucleic Acids Research ◽

10.1093/nar/gkq202 ◽

2010 ◽

Vol 38 (14) ◽

pp. 4755-4767 ◽

Cited By ~ 101

Author(s):

Ernesto Picardi ◽

David S. Horner ◽

Matteo Chiara ◽

Riccardo Schiavon ◽

Giorgio Valle ◽

...

Keyword(s):

Rna Editing ◽

Deep Sequencing ◽

Large Scale ◽

Rna Deep Sequencing ◽

Scale Detection

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Large‐scale potential RNA editing profiling in different adult chicken tissues

Animal Genetics ◽

10.1111/age.12818 ◽

2019 ◽

Vol 50 (5) ◽

pp. 460-474 ◽

Cited By ~ 2

Author(s):

H. Shafiei ◽

M. R. Bakhtiarizadeh ◽

A. Salehi

Keyword(s):

Rna Editing ◽

Large Scale ◽

Adult Chicken ◽

Chicken Tissues

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Automated Isoform Diversity Detector (AIDD): a pipeline for investigating transcriptome diversity of RNA-seq data

BMC Bioinformatics ◽

10.1186/s12859-020-03888-6 ◽

2020 ◽

Vol 21 (S18) ◽

Author(s):

Noel-Marie Plonski ◽

Emily Johnson ◽

Madeline Frederick ◽

Heather Mercer ◽

Gail Fraizer ◽

...

Keyword(s):

Rna Editing ◽

Large Scale ◽

Neural Progenitor Cells ◽

Viral Infections ◽

Variant Calling ◽

Rna Seq ◽

Major Mechanism ◽

Isoform Diversity ◽

Adar Editing ◽

Transcriptome Diversity

Abstract Background As the number of RNA-seq datasets that become available to explore transcriptome diversity increases, so does the need for easy-to-use comprehensive computational workflows. Many available tools facilitate analyses of one of the two major mechanisms of transcriptome diversity, namely, differential expression of isoforms due to alternative splicing, while the second major mechanism—RNA editing due to post-transcriptional changes of individual nucleotides—remains under-appreciated. Both these mechanisms play an essential role in physiological and diseases processes, including cancer and neurological disorders. However, elucidation of RNA editing events at transcriptome-wide level requires increasingly complex computational tools, in turn resulting in a steep entrance barrier for labs who are interested in high-throughput variant calling applications on a large scale but lack the manpower and/or computational expertise. Results Here we present an easy-to-use, fully automated, computational pipeline (Automated Isoform Diversity Detector, AIDD) that contains open source tools for various tasks needed to map transcriptome diversity, including RNA editing events. To facilitate reproducibility and avoid system dependencies, the pipeline is contained within a pre-configured VirtualBox environment. The analytical tasks and format conversions are accomplished via a set of automated scripts that enable the user to go from a set of raw data, such as fastq files, to publication-ready results and figures in one step. A publicly available dataset of Zika virus-infected neural progenitor cells is used to illustrate AIDD’s capabilities. Conclusions AIDD pipeline offers a user-friendly interface for comprehensive and reproducible RNA-seq analyses. Among unique features of AIDD are its ability to infer RNA editing patterns, including ADAR editing, and inclusion of Guttman scale patterns for time series analysis of such editing landscapes. AIDD-based results show importance of diversity of ADAR isoforms, key RNA editing enzymes linked with the innate immune system and viral infections. These findings offer insights into the potential role of ADAR editing dysregulation in the disease mechanisms, including those of congenital Zika syndrome. Because of its automated all-inclusive features, AIDD pipeline enables even a novice user to easily explore common mechanisms of transcriptome diversity, including RNA editing landscapes.

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Large-scale RNA editing profiling in different adult chicken tissues

10.1101/319871 ◽

2018 ◽

Cited By ~ 1

Author(s):

Hamid Shafiei ◽

Mohammad Reza Bakhtiarizadeh ◽

Abdolreza Salehi

Keyword(s):

Rna Editing ◽

Large Scale ◽

Critical Role ◽

Sequencing Data ◽

Adult Chicken ◽

Chicken Tissues ◽

Sequencing Technologies ◽

Synonymous Sites ◽

Interspersed Repeats ◽

The Brain

AbstractRNA editing is a post-transcription maturation process that diversifies genomically encoded information and can lead to diversity and complexity of transcriptome, especially in the brain. Thanks to next-generation sequencing technologies, a large number of editing sites have been identified in different species, especially in human, mouse and rat. While this mechanism is well described in mammals, only a few studies have been performed in the chicken. Here, we developed a rigorous computational strategy to identify RNA editing sites in eight different tissues of the chicken (brain, spleen, colon, lung, kidney, heart, testes and liver), based on RNA sequencing data alone. We identified 68 A-to-G editing sites in 46 genes. Only two of these were previously reported in chicken. We found no C-to-U sites, attesting the lack of this type of editing mechanism in the chicken. Similar to mammals, the editing sites were enriched in non-coding regions, rarely resulted in change of amino acids, showed a critical role in nervous system and had a low guanosine level upstream of the editing site and some enrichment downstream from the site. Moreover, in contrast to mammals, editing sites were weakly enriched in interspersed repeats and the frequency and editing ratio of non-synonymous sites were higher than those of synonymous sites.Interestingly, we found several tissue-specific edited genes including GABRA3, SORL1 and HTR1D in brain and RYR2 and FHOD3 in heart that were associated with functional processes relevant to the corresponding tissue. This finding highlighted the importance of the RNA editing in several chicken tissues, especially the brain. This study extends our understanding of RNA editing in chicken tissues and establish a foundation for further exploration of this process.

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