Whole Transcriptome Profiling
Overabundant ribosomal RNA dominates sequencing reads
Whole-transcriptome RNA sequencing has traditionally been used in next-generation sequencing. However, the high percentage of ribosomal sequences in samples often results in more background noise than usable data. Detecting novel transcripts or low-expressing transcripts is a time-consuming challenge, where the biologically relevant data you need is often lost in the ribosomal RNA clutter.
Traditional methods exist to remove ribosomal RNA, but these methods tend to be expensive and time consuming. They also usually require large amounts of RNA input because depletion must be done before NGS library construction begins. CRISPRclean differs from traditional methods in that depletion happens after library adapters are ligated. This allows for a more complex library with clearer results - and significantly less RNA input.
CRISPRclean removes more than 99% of ribosomal RNA sequences, revealing high-value, elusive data.
The samples and method
Human brain RNA samples
Human brain RNA samples were prepared with NEB Ultra II Directional RNA Library Prep Kits to create NGS libraries. The CRISPRclean Human rRNA Depletion Kit was applied to the samples, removing all the noisy human rRNA sequences. The libraries were sequenced on a short-read sequencing instrument, and the Jumpcode proprietary software measured the alignment and depletion rates.
Find more of the data you're looking for.
Removing more than 99% of the ribosomal RNA noise with CRISPRclean technology increased the visibility and detection sensitivity of the non-ribosomal RNA transcripts in the prepared samples.
Increase in alignment rates to coding and non-coding regions.
Samples treated with CRISPRclean depletion show minimal to no alignment to ribosomal RNA - and a significant increase in alignment rates to exon, intron, and intergenic regions.
Transcript representation is maintained with reduced inputs.
The number of genes detected at 10x and 30x coverage remains consistent - even with decreasing total RNA inputs. Applying depletion after library construction allows samples with limited amounts to be sequenced thoroughly and successfully.