WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data

Abstract

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND (Workflow for pIRNAs aNd beyonD), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

Increased serum piwi-interacting RNAs as a novel potential diagnostic tool for brucellosis

“…These need to be further verified by bioinformatics tools or experimental verification. Moreover, these lines of new evidence may also counsel us to pay more attention to future research on circulating piRNAs, and targeting piRNAs cannot be identified by simply mapping small RNA-seq data to piRNA databases ( Geles et al., 2021 ).…”

Combined Noncoding RNA-mRNA Regulomics Signature in Reprogramming and Pluripotency in iPSCs

“…Following the principles detailed in the WiND workflow [ 21 ], the RNA sequencing data were analyzed for piRNA and other sncRNAs. RNASeq was aligned to the GRCh38 genome using STAR, followed by FeatureCounts from the Rsubread package, and, simultaneously, de Novo transcriptome counts with Salmon.…”

“…The expression of sncRNAs was assessed using WIND (Workflow for PIRNAs and Beyond D) [ 21 ], a bioinformatics workflow that addresses the crucial issue of small RNA annotation, allowing for reliable identification of piRNAs and other sncRNAs that have been misclassified as piRNAs in the past.…”

A Review of Discovery Profiling of PIWI-Interacting RNAs and Their Diverse Functions in Metazoans

“…miRanda [ 17 ], pirnaPre [ 67 ], and pirScan [ 18 ] have been used for piRNA target prediction, and three algorithms have been proposed for predicting piRNA clusters from sRNA-seq data: proTRAC [ 54 ], piClust [ 68 ], and PILFER [ 69 ]. In addition, multiple integrated platforms, such as sRNAtools [ 70 ] and Workflow for piRNAs and Beyond (WIND) [ 71 ], have been recently developed for piRNA annotation and downstream analysis from raw data to plots and statistics by sRNA-seq. The performances of most of these piRNA prediction tools have been reviewed by Liu et al [ 46 ].…”