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Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of single-stranded (SS) spike-in piRNA-like molecules in smallRNA-seq

ABSTRACT: Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of single-stranded (SS) spike-in piRNA-like molecules in smallRNA-seq

PROVIDER: PRJEB41397 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR4845106.fastq.gz	Fastqsanger.gz
	ERR4845107.fastq.gz	Fastqsanger.gz
	ERR4845108.fastq.gz	Fastqsanger.gz

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Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of single-stranded (SS) spike-in piRNA-like molecules in smallRNA-seq

Project description:For the evaluation of \\"WIND: A Workflow for pIRNAs aNd beyonD\\" performance and the transcriptomic approach on small-RNA identification, and particularly on piRNAs, a synthetic set of 4 piRNA-like molecules was used. Two non-methylated (SS-22 and SS-28) and two methylated (mSS-22 and mSS-28) of two different lengths (22 nt and 28 nt) were included. Spike-ins were chemically synthesised at Exiqon, the pool of 4 molecules was used at three different concentrations, with a final amount of 0.3 x 10^9 (dil_A), 0.3 x 10^10 (dil_B) and 0.3 x 10^11 (dil_C) molecules/ug of RNA. Library preparation and sequencing were done as previously described in Sellitto et al 2019 (doi: https://doi.org/10.3390/cells8111390)

2020-11-25 | E-MTAB-9772 | biostudies-arrayexpress

Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of piRNA in mouse samples

Project description:For the evaluation of "WIND: A Workflow for pIRNAs aNd beyonD" performance and the transcriptomic approach on small-RNA identification, and particularly on piRNAs, two mouse Adult Cardiomyocytes (aCMs) were used.

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Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of piRNA molecules in small RNA-seq

Project description:WIND: A Workflow for pIRNAs aNd beyonD, for the evaluation of the performance in piRNAs high expression and low expression conditions, we used Human Testis RNAs (BioChain Institute Inc, Newark, CA, USA) and COLO 205 cell line RNAs (samples are available on ArrayExpress (E-MTAB-8115: Non_treated_Testis_1 and Non_treated_COLO205_1, Non_treated_COLO205_2, Non_treated_COLO205_3).

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Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of piRNA in mouse samples

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Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of piRNA molecules in small RNA-seq

Project description:Monitor the efficiency of "WIND: A Workflow for pIRNAs aNd beyonD" for the identification of piRNA molecules in small RNA-seq

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

Project description: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 p IRNAs a Nd beyon D), 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.

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