Evidence map›Paper›PMID 33375933›Full record

ArticleBMC bioinformatics2020

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

Noel-Marie Plonski, Emily Johnson, Madeline Frederick, Heather Mercer, Gail Fraizer, Richard Meindl, Gemma Casadesus, Helen Piontkivska

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In one paragraph

Article in BMC bioinformatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Noel-Marie PlonskiDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.ORCID http://orcid.org/0000-0003-0747-7664
Emily JohnsonDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.ORCID http://orcid.org/0000-0002-7582-0068
Madeline FrederickDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.
Heather MercerDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.ORCID http://orcid.org/0000-0003-1658-5923
Gail FraizerDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.
Richard MeindlSchool of Biomedical Sciences, Kent State University, PO Box 5190, Kent, OH, 44242, USA.
Gemma CasadesusDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA.ORCID http://orcid.org/0000-0002-5206-5637
Helen PiontkivskaDepartment of Biological Sciences, Kent State University, 256 Cunningham Hall, Kent, OH, 44242, USA. opiontki@kent.edu.ORCID http://orcid.org/0000-0003-1844-864X

Funding

Characterization of transcriptome changes in diet-induced progression to METS/T2D to identify earliest and sex-specific neurodegenerative foci for AD developmentR21AG064479 · NIA · UNIVERSITY OF FLORIDA · PI CASADESUS, GEMMA · 2019 to 2020
$598k
ADAR-editing landscape dysregulation in neuropsychiatric disordersF31MH123131 · NIMH · KENT STATE UNIVERSITY · PI PLONSKI, NOEL-MARIE · 2020 to 2021
$56k
NIA NIH HHS R21 AG064479NIA NIH HHS R21AG064479-01NIMH NIH HHS F31 MH123131
6 · The paper itself

Abstract

backgroundAs 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.

Indexed as

SoftwareTranscriptomeAdenosine DeaminaseGene ExpressionGene OntologyHumansPrincipal Component AnalysisProtein IsoformsRNA EditingRNA-SeqStem CellsZika VirusAdenosine DeaminaseProtein IsoformsAdenosine deaminases acting on RNA (ADAR)Analysis of RNA-seqDifferential expressionEditomeHigh-throughput sequencingIsoformRNA editingSequencing variantsTranscriptome

Identifiers

PMID33375933
PMCPMC7772930

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.