DNA microarrays have traditionally dominated applications involving transcriptome analysis, profiling of protein-DNA interactions, and small-scale and large scale genetic variation. However, the processing speed, knowledge requirement for sequences being interrogated, problematic cross-hybridization, and the analog nature of the microarray signal has made it difficult to detect and quantify low-abundance RNA species. These low abundance species include non-polyA+ tailed mRNA, preprocessed RNA, potentially regulatory RNA, and other RNA transcripts of unknown function in assessing the true whole transcriptome. The transcriptome is defined as the complete collection of transcribed elements of the genome and contains mRNA transcripts and non-mRNA transcripts. Since large rRNA constitutes 90–95% RNA species in total RNA, whole transcriptome analysis without any contamination from rRNA is very difficult using existing RNA isolation methods including microarray.



Figure 1.
The RNA-Seq workflow
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A unique testing segment of next generation sequencing technology termed RNA-Seq has been developed to alleviate a majority of these inherent problems and allow for better quantification with exceptional detail. RNA-Seq (Figure 1) is a method which uses a digital interrogation of the transcriptome by next generation sequencing technology and provides detailed, high throughput view of the transcriptome Unlike array-based approaches, RNA-Seq gives a potentially comprehensive view of the transcriptome providing information on transcripts that are expressed at very low levels, limited only by the total number of reads that are generated.

The Ribominus™ Eukaryote Kit for RNA-Seq was developed to provide a superior method for true whole transcriptome isolation through the selective depletion of ribosomal RNA (rRNA). The unique and patented Locked Nucleic Acid (LNA) probe based RiboMinus™ system selectively depletes up to 99.9% of rRNA, including the 5S, 5.8S, 18S and 28S rRNA components in order to increase specificity across multiple organisms (Figure 2, 3).

Unbiased depletion of rRNA is achieved with no effect from the differing expression levels of multiple genes (figure 4).The remaining transcriptome RNA can then be used for digital interrogation of the transcriptome using next generation sequencing technology (ex. ABI SOLiD, Illumina Solexa). Compared to traditional polyA selection methods RiboMinus™ depleted samples provide superior depth and breadth of coverage across long genes thereby increasing the amount and accuracy of the sequencing information obtained (figure 5). This same effect has been demonstrated across multiple genes (figure 6).  The RiboMinus™ method is not dependent on the polyadenylation status or presence of a 5′-cap structure on the RNA as with existing methods that only offer a partial isolation of the transcriptome.


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Figure 2. 18S rRNA Detected by qRT-PCR. Whole transcriptome RNA was isolated from 10µg of total RNA from mouse liver using the RiboMinusTM Eukaryote kit for RNA-Seq. qRT-PCR was performed using a LUX primer set, which  detects the 18S rRNA transcripts. The Ct difference between total RNA and RiboMinusTM  depleted samples is 9.84 corresponding to 99.9% depletion of 18s rRNA.



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Figure 3. RiboMinus™ depleted RNA Samples Analyzed Using the 2100 Bioanalyzer. 10 µg of total RNA sample from mouse liver was purified using the RiboMinusTM Eukaryote Kit for RNA-Seq. Probes specific for 5S, 5.8S, 18S, and 28S were used individually (Panels A-D) or as a mix as included in the kit (Panel E). 1µl of each depleted product  was analyzed using an Agilent RNA 6000 Nano LabChip. The 5S, 5.8S, 18S, and 28S transcripts from the RiboMinusTM  depleted RNA samples are nearly absent (blue ) as compared to control total RNA  ( red ). Greater than 99.1% of rRNA (by peak area) from mouse liver total RNA was depleted.



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Figure 4. Unbiased depletion of rRNAs leaves biologically relevant levels of other transcripts. To investigate the effects of rRNA depletion on specific genes, six mouse house keeping genes with a range of expression levels were detected by qRT-PCR. RNA without RT and without template was used as negative controls (Ct = undetectable/40, data not shown). The Ct difference between total RNA and RiboMinus™ -depleted samples is less than one cycle for all six genes. The depletion of rRNA using the RiboMinusTM Eukaryote kit for RNA-Seq does not negatively effect the detection of expression levels for specific genes.



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Figure 5. mRNA-SEQ Transcriptome Sequencing demonstrating removal of 3’ bias using the RiboMinus™ Kit for RNA-Seq across a single gene. A representative example of the increased breadth and depth of sequencing coverage of a long gene analyzed from enriched mRNA following RiboMinus™ for RNA-Seq preparation of initial total RNA, as compared to coverage obtained with standard polyA mRNA selection from total RNA. *



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Figure 6. mRNA-SEQ Transcriptome Sequencing demonstrating removal of 3’ bias using the RiboMinus™ Kit for RNA-Seq across multiple genes. Note the overall shallower coverage of the transcriptome obtained with polyA selected mRNA (left panel), as compared to the more complete coverage of the enriched whole transcriptome obtained from Ribominus prepared RNA (right panel). Of special interest, the enhanced coverage of the whole transcriptome following RiboMinus™ for RNA-Seq preparation reveals a characteristic fall-off of  5’ and 3’ sequences on an individual gene basis, which – speculatively - may reflect the global variation in 5’ promoter and transcription start site usage as well as 3’ alternative polyadenylation signal usage. *


*Data provided by Ryan Lister, Salk Institute for Biological Studies