Dataset Information

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

ABSTRACT: The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less than 5 h with an accuracy of 99.4%. An integrative analysis of small RNAs from 1836 data sets (20 billion reads) indicated that context-specific miRNAs (e.g. miRNAs present only in one or few different tissues / cell types) still remain to be discovered while broadly expressed miRNAs appear to be largely known. In total, our analysis of known and novel miRNAs indicated nearly 22 000 candidates of precursors with one or two mature forms. Based on these, we designed a custom microarray comprising 11 872 potential mature miRNAs to assess the quality of our prediction. MiRMaster is a convenient-to-use tool for the comprehensive and fast analysis of miRNA NGS data. In addition, our predicted miRNA candidates provided as custom array will allow researchers to perform in depth validation of candidates interesting to them.

SUBMITTER: Fehlmann T

PROVIDER: S-EPMC5587802 | biostudies-literature | 2017 Sep

REPOSITORIES: biostudies-literature

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Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

Fehlmann Tobias T Backes Christina C Kahraman Mustafa M Haas Jan J Ludwig Nicole N Posch Andreas E AE Würstle Maximilian L ML Hübenthal Matthias M Franke Andre A Meder Benjamin B Meese Eckart E Keller Andreas A

Nucleic acids research 20170901 15

The analysis of small RNA NGS data together with the discovery of new small RNAs is among the foremost challenges in life science. For the analysis of raw high-throughput sequencing data we implemented the fast, accurate and comprehensive web-based tool miRMaster. Our toolbox provides a wide range of modules for quantification of miRNAs and other non-coding RNAs, discovering new miRNAs, isomiRs, mutations, exogenous RNAs and motifs. Use-cases comprising hundreds of samples are processed in less ...[more]

PMID: 28911107

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Project description:The three prime untranslated region (3'-UTR) is known to play a pivotal role in modulating gene expression by determining the fate of mRNA. Many crucial developmental events, such as mammalian spermatogenesis, tissue patterning, sex determination and neurogenesis, rely heavily on post-transcriptional regulation by the 3'-UTR. However, 3'-UTR biology seems to be a relatively untapped field, with only limited tools and 3'-UTR resources available. To elucidate the regulatory mechanisms of the 3'-UTR on gene expression, firstly the 3'-UTR sequences must be identified. Current 3'-UTR mining tools, such as GETUTR, 3USS and UTRscan, all depend on a well-annotated reference genome or curated 3'-UTR sequences, which hinders their application on a myriad of non-model organisms where the genomes are not available. To address these issues, the establishment of an NGS-based, automated pipeline is urgently needed for genome-wide 3'-UTR prediction in the absence of reference genomes.Here, we propose ExUTR, a novel NGS-based pipeline to predict and retrieve 3'-UTR sequences from RNA-Seq experiments, particularly designed for non-model species lacking well-annotated genomes. This pipeline integrates cutting-edge bioinformatics tools, databases (Uniprot and UTRdb) and novel in-house Perl scripts, implementing a fully automated workflow. By taking transcriptome assemblies as inputs, this pipeline identifies 3'-UTR signals based primarily on the intrinsic features of transcripts, and outputs predicted 3'-UTR candidates together with associated annotations. In addition, ExUTR only requires minimal computational resources, which facilitates its implementation on a standard desktop computer with reasonable runtime, making it affordable to use for most laboratories. We also demonstrate the functionality and extensibility of this pipeline using publically available RNA-Seq data from both model and non-model species, and further validate the accuracy of predicted 3'-UTR using both well-characterized 3'-UTR resources and 3P-Seq data.ExUTR is a practical and powerful workflow that enables rapid genome-wide 3'-UTR discovery from NGS data. The candidates predicted through this pipeline will further advance the study of miRNA target prediction, cis elements in 3'-UTR and the evolution and biology of 3'-UTRs. Being independent of a well-annotated reference genome will dramatically expand its application to much broader research area, encompassing all species for which RNA-Seq is available.

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Dataset Information

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

Publications

Web-based NGS data analysis using miRMaster: a large-scale meta-analysis of human miRNAs.

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