Targeted RNA Expression Profiling
RNA expression profiling of biological models to identify which genes are expressed and which pathways are active in biological systems under different conditions is central to unraveling how genes control biology. For years, qRT-PCR has provided a reliable and robust approach to assess transcript levels for any gene. However, the qRT-PCR assay is limited to just a few gene targets. Approaches using arrayed oligonucleotide probes developed to address this throughput limitation, but RNA expression analysis using microarrays does not provide the robust measurements of expression levels over a wide dynamic range that qRT-PCR does. In addition, indirect detection by fluorescence of hybridized transcripts to arrayed oligonucleotides suffers from noise and background signals caused by cross-hybridization.
With the advent of affordable and accessible next generation sequencing (NGS) technology, complete sequencing of cDNA made from RNA isolated from biological models of interest became much more feasible. RNA-seq approaches have overtaken microarrays as the method of choice for genome-wide expression analysis.
While RNA-seq provides an accurate reading of the transcripts present in biological samples, it can be a challenging assay to run for large numbers of samples. In addition RNA, sample preparation, especially for groups interested mainly in protein expression genes, requires mRNA enrichment. For blood samples, additional work is required to deplete beta-globin gene levels. Even after this preparative work on the RNA is completed the assay involves cDNA synthesis of the total transcriptome, followed by generation of NGS libraries from the total complement of fragmented cDNA. NGS analysis of these complex samples requires significant sequencing depth—typically 25-50M reads—as well as involved deconvolution and bioinformatic processing to estimate the copy number of each gene from large numbers of variable gene fragment reads.
Genome-Wide Targeted RNA Sequencing for Expression Profiling
An alternative to sequencing the entire transcriptome is to use a targeted RNA sequencing approach. This is the basis of the DriverMap Targeted RNA Expression Assay developed by Cellecta. Rather than reverse-transcribing the whole transcriptome, the DriverMap method combines multiplex RT-PCR amplification to amplify a defined and conserved 80- to 250- base segment of the transcript of each targeted gene, and then uses next-generation sequencing (NGS) to quantitatively assess abundance levels of each of these transcript amplicons (Fig. 1).
The DriverMap RT-PCR targeted approach also greatly simplifies the cDNA library that needs to be sequenced. A multiplex assay that targets all 19,000 human protein-coding genes produces, at most, only 19,000 amplicons for sequencing. The NGS read depth required to reliably read several thousand targeted amplicons is much less than the depth required for the whole transcriptome. As a result, the targeted approach detects lower level expressed transcripts more consistently and reliably than other RNA-seq approaches and with much less sequencing. (Fig. 2)
Developing the DriverMap Targeted RNA Profiling Primer Sets
Key to the DriverMap Targeted RNA approach is the efficiency and specificity of the multiplex PCR target amplification step. Numerous factors which may be tolerated in simple PCR reactions–including secondary structure, non-specific binding, primer binding inefficiency and primer-primer interactions–can cause significant problems in a multiplex PCR environment that amplifies many thousands of templates in the same reaction.
Development of the DriverMap assay required sophisticated primer design work and an iterative empirical testing process. For this, we developed a bioinformatics primer design pipeline and carried out experimental validation of thousands of PCR primers in a highly complex multiplex reaction (see Fig. 3). This approach enabled us to generated an optimized genome-wide, multiplex PCR assay for all 19,000 human protein-coding genes.
In addition to the bioinformatics selection, each primer set also had to be experimentally tested. For each target mRNA, we synthesized the best 5–20 PCR primers then ran them in a several multiplex RT-PCR reactions using a set of universal control human tissue/cell line RNAs (Fig. 4), mouse negative control RNAs and positive control DNA as templates. For the genome-wide DriverMap Targeted RNA Expression Assay one set of primers targeting the conservative portions of different mRNA isoforms with the highest efficiency, sensitivity, and specificity was selected for each mRNA. Furthermore, for highly abundant transcripts, we selected primers with low specific efficacy, which allowed us to solve the problem of over-sequencing highly expressed target transcripts.
Generally, the DriverMap Targeted RNA Expression Profiling Assay provides a convenient and effective method to identify which pathways are active in your biological samples of interest. As a PCR assay, it is particularly effective when samples are limiting with very small amounts of RNA. In addition, due to the ability to target selected sets of genes, it can be especially useful to quantify cell or biomarkers expressed at very low levels. Custom assays can also be designed to target specifically target low-level genes of interest. Particularly for investigators interested in measuring transcript levels of specific cell fractions in heterogeneous samples, such as immune cells in tumor samples, this ability to pick up low expressed genes can be crucial.
Cellecta offers researchers access to the DriverMap assay as a kit to enable you to run the assay in your lab, and as a service, if you prefer to send us your samples for targeted expression profiling.