A major hurdle to transcriptome profiling by deep-sequencing technologies is that abundant transcripts, such as rRNAs, can overwhelm the libraries, severely reducing transcriptome-wide coverage. Methods for depletion of such unwanted sequences typically require treatment of RNA samples prior to library preparation, are costly and not suited to unusual species and applications. Here researchers from the Australian National University describe Probe-Directed Degradation (PDD), an approach that employs hybridisation to DNA oligonucleotides at the single-stranded cDNA library stage and digestion with Duplex-Specific Nuclease (DSN).
Targeting Saccharomyces cerevisiae rRNA sequences in Illumina HiSeq libraries generated by the split adapter method, the researchers show that PDD results in efficient removal of rRNA. The probes generate extended zones of depletion as a function of library insert size and the requirements for DSN cleavage. Using intact total RNA as starting material, probes can be spaced at the minimum anticipated library size minus 20 nucleotides to achieve continuous depletion. No off-target bias is detectable when comparing PDD-treated with untreated libraries. They further provide a bioinformatics tool to design suitable PDD probe sets.
They find that PDD is a rapid procedure that results in effective and specific depletion of unwanted sequences from deep-sequencing libraries. Because PDD acts at the cDNA stage, handling of fragile RNA samples can be minimised and it should further be feasible to remediate existing libraries. Importantly, PDD preserves the original RNA fragment boundaries as is required for nucleotide-resolution footprinting or base-cleavage studies. Finally, as PDD utilises unmodified DNA oligonucleotides it can provide a low-cost option for large-scale projects, or be flexibly customised to suit different depletion targets, sample types and organisms.