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

Abstract

13Background: As the number of RNA-seq datasets that become available to explore transcriptome 14 diversity increases, so does the need for easy-to-use comprehensive computational workflows. 15Many available tools facilitate analyses of one of the two major mechanisms of transcriptome 16 diversity, namely, differential expression of isoforms due to alternative splicing, while the second 17 major mechanism -RNA editing due to post-transcriptional changes of individual nucleotides -18 remains under-appreciated. Both these mechanisms play an essential role in physiological and 19 diseases processes, including cancer and neurological disorders. However, elucidation of RNA 20 editing events at transcriptome-wide level requires increasingly complex computational tools, in 21 turn resulting in a steep entrance barrier for labs who are interested in high-throughput variant 22 calling applications on a large scale but lack the manpower and/or computational expertise. 23 24 Results: Here we present an easy-to-use, fully automated, computational pipeline (Automated 25 Isoform Diversity Detector, AIDD) that contains open source tools for various tasks needed to map 26 transcriptome diversity, including RNA editing events. To facilitate reproducibility and avoid 27 system dependencies, the pipeline is contained within a pre-configured VirtualBox environment. 28 . The analytical tasks and format conversions are accomplished via a set of automated scripts that 29 enable the user to go from a set of raw data, such as fastq files, to publication-ready results and 30 figures in one step. A publicly available dataset of Zika virus-infected neural progenitor cells is 31 used to illustrate AIDD's capabilities. 32 33 Conclusions: AIDD pipeline offers a user-friendly interface for comprehensive and reproducible 34 RNA-seq analyses. Among unique features of AIDD are its ability to infer RNA editing patterns, 35 including ADAR editing, and inclusion of Guttman scale patterns for time series analysis of such 36 editing landscapes. AIDD-based results show importance of diversity of ADAR isoforms, key RNA 37 editing enzymes linked with the innate immune system and viral infections. These findings offer 38 insights into the potential role of ADAR editing dysregulation in the disease mechanisms, including 39 those of congenital Zika syndrome. Because of its automated all-inclusive features, AIDD pipeline 40 enables even a novice user to easily explore common mechanisms of transcriptome diversity, 41 including RNA editing landscapes. 42 43Keywords: high-throughput sequencing, analysis of RNA-seq, transcriptome, editome, RNA editing, isoform, 44 differential expression, sequencing variants, adenosine deaminases acting on RNA (ADAR) 45Background: 47Transcriptome complexity and diversity, including patterns of differential isoform

Alterations in RNA editing in skeletal muscle following exercise training in individuals with Parkinson’s disease

“…Ultimately, while mutations in specific candidate genes have been suggested as culprits in PD pathogenesis, no monogenic targets have been definitively identified, making it more likely that a variety of genetic and environmental influences are at play in the manifestation of the neuroinflammation indicative of PD. ADAR editing, a known factor in the pathology of multiple neurodegenerative and psychiatric disorders (28,64,80), must be acknowledged as a potential role-player in PD pathology.…”

“…The Automated Isoform Diversity Detector (AIDD) pipeline (64) was used to infer ADAR editing events. Briefly, fastq files of individual patients were trimmed and aligned to the chosen human reference (GRCh37) using HISAT2 (65).…”

“…Once aligned, the transcriptome was assembled using Stringtie (66), to estimate levels of individual gene expression as Transcripts Per Kilobase Million (TPM). ADAR editing events were inferred using GATK haplotype caller (67) following the best practices, as described in Plonski et al (64). VCF files are available at https://doi.org/10.5281/zenodo.7971793.…”

Differential ADAR editing landscapes in major depressive disorder and suicide

“…Our computational pipeline, Automated Isoform Diversity Detector (AIDD) (Plonski et al, 2020) was used to map, assemble and perform variant calling on RNA-seq datasets using HISAT2 (Kim et al, 2019;Pertea et al, 2015) for alignment to GRCh37 (human reference Ensembl build release 75) annotated with both splice site and genomic single nucleotide polymorphisms (SNPs). In total, between 90-95% of reads for each of the used 303 RNA-seq samples were accurately aligned to the genome (Supplemental Table 2).…”

“…However, this increases the chance that some true editing sites are being removed because some editing events have been reported as polymorphisms in dbSNP. Thus, in addition to global analysis we also used a manually curated list of excitome editing sites (Supplementary Table 1 in (Plonski et al, 2020)).…”