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. Researchers at Erasmus University Medical Center 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.


Schematic of the Total RNA Analysis Pipeline, TRAP for analysis of sequencing datasets. (A) Modules for long RNA analysis, script 1 (green) for RefSeq annotated exonic transcripts and script 2 (red) for RefSeq annotated non-exonic regions. (B) Modules for small RNA analysis, script 3 (blue) to sequentially align trimmed reads to rRNA, tRNA fragments and the microRNA database (miRBase version 21).

Availability – The R code for the developed Total Rna Analysis Pipeline (TRAP), an algorithm to analyze RNAome sequencing datasets is available at: http://rna-ome.erasmusmc.nl/ Note that TRAP can also be used for standard poly(A)+-sequencing, standard small RNA sequencing.

Derks KW, Pothof J. (2015) RNAome sequencing delineates the complete RNA landscape. Genom Data 5:381-4. [article]

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