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RNAome sequencing delineates the complete RNA landscape

Standard RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species. For example, small and large RNAs from the same sample cannot be sequenced in a single sequence run. We designed RNAome sequencing, which is a strand-specific method to...

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Detalles Bibliográficos
Autores principales: Derks, Kasper W.J., Pothof, Joris
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4583693/
https://www.ncbi.nlm.nih.gov/pubmed/26484291
http://dx.doi.org/10.1016/j.gdata.2015.07.002
Descripción
Sumario:Standard RNA expression profiling methods rely on enrichment steps for specific RNA classes, thereby not detecting all RNA species. For example, small and large RNAs from the same sample cannot be sequenced in a single sequence run. We designed RNAome sequencing, which is a strand-specific method to determine the expression of small and large RNAs from ribosomal RNA-depleted total RNA in a single sequence run. RNAome sequencing quantitatively preserves all RNA classes. This characteristic allows comparisons between RNA classes, thereby facilitating relationships between different RNA classes. Here, we describe in detail the experimental procedure associated with RNAome sequencing published by Derks and colleagues in RNA Biology (2015) [1]. We also provide the R code for the developed Total Rna Analysis Pipeline (TRAP), an algorithm to analyze RNAome sequencing datasets (deposited at the Gene Expression Omnibus data repository, accession number GSE48084).