Abstract
The current versions of the microRNA databases MiRgeneDB, miRBase, and PmiREN contain annotations for a total of 358 different species. Public repositories, however, host small RNA sequencing data for over 800 species. This discrepancy implies that microRNA research is also very active in species that neither have an available high-quality genome assembly nor annotations for microRNAs or other types of noncoding genes. These cases are particularly challenging to analyze because reference sequences need to be collected from different sources and processed and formatted appropriately so that the dedicated small RNA analysis tools can make use of them. In this protocol we describe how small RNA sequencing data can be easily analyzed by means of a dockerized version of the well-established sRNAtoolbox/sRNAbench small RNA tools. We outline the analysis of two publicly available datasets to demonstrate basic aspects like the preparation of the local database, expression profiling, or differential expression analysis as well as more advanced features such as quantification of exogenous RNA content and data analysis in non-model species.
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References
Leinonen R, Sugawara H, Shumway M, on behalf of the International Nucleotide Sequence Database Collaboration et al (2011) The sequence read archive. Nucleic Acids Res 39:D19–D21
Aparicio-Puerta E, Gómez-Martín C, Giannoukakos S, Medina JM, Scheepbouwer C, García-Moreno A, Carmona-Saez P, Fromm B, Pegtel M, Keller A, Marchal JA, Hackenberg M (2022) sRNAbench and sRNAtoolbox 2022 update: accurate miRNA and sncRNA profiling for model and non-model organisms. Nucleic Acids Res. Accepted
Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N (2012) miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res 40:37–52
Fehlmann T, Kern F, Laham O et al (2021) miRMaster 2.0: multi-species non-coding RNA sequencing analyses at scale. Nucleic Acids Res 49:W397–W408
Patil AH, Halushka MK (2021) miRge3.0: a comprehensive microRNA and tRF sequencing analysis pipeline. NAR Genomics Bioinform 3:lqab068
Pantano L, Estivill X, Martí E (2010) SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells. Nucleic Acids Res 38:e34
Aparicio-Puerta E, Lebron R, Rueda A et al (2019) sRNAbench and sRNAtoolbox 2019: intuitive fast small RNA profiling and differential expression. Nucleic Acids Res 47:W530–W535
Barturen G, Ruead A, Hamberg M et al (2014) sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments. Methods Gener Seq 1
Hackenberg M, Sturm M, Langenberger D, Falcón-Pérez JM, Aransay AM (2009) miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments. Nucleic Acids Res 37:W68–W76
Howe KL, Achuthan P, Allen J et al (2021) Ensembl 2021. Nucleic Acids Res 49:D884–D891
Gómez-Martín C, Lebrón R, Rueda A, Oliver JL, Hackenberg M (2017) sRNAtoolboxVM: small RNA analysis in a virtual machine. In: Dalmay T (ed) MicroRNA detection and target identification: methods and protocols. Springer, pp 149–174. https://doi.org/10.1007/978-1-4939-6866-4_12
Huang Y, Chen C, Yuan J et al (2019) Sputum exosomal microRNAs profiling reveals critical pathways modulated by pseudomonas aeruginosa colonization in bronchiectasis. Int J Chron Obstruct Pulmon Dis 14:2563–2573
Kozomara A, Birgaoanu M, Griffiths-Jones S (2019) miRBase: from microRNA sequences to function. Nucleic Acids Res 47:D155–D162
Fromm B, Hoye E, Domanska D et al (2022) MirGeneDB 2.1: toward a complete sampling of all major animal phyla. Nucleic Acids Res 50:D204–D210
Guo Z, Kuang Z, Wang Y et al (2020) PmiREN: a comprehensive encyclopedia of plant miRNAs. Nucleic Acids Res 48:D1114–D1121
Fromm B, Zhong X, Tarbier M, Friedlander MR, Hackenberg M (2022) The limits of human microRNA annotation have been met. RNA. rna.079098.122
Anders S, Huber W (2010) Differential expression analysis for sequence count data. Genome Biol 11:R106
Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15:550
Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26:139–140
Tarazona S, Furiotari P, Turra D et al (2015) Data quality aware analysis of differential expression in RNA-seq with NOISeq R/bioc package. Nucleic Acids Res 43:e140
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Gómez-Martín, C., Aparicio-Puerta, E., Hackenberg, M. (2023). sRNAtoolbox: Dockerized Analysis of Small RNA Sequencing Data in Model and Non-model Species. In: Dalmay, T. (eds) MicroRNA Detection and Target Identification. Methods in Molecular Biology, vol 2630. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2982-6_13
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DOI: https://doi.org/10.1007/978-1-0716-2982-6_13
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