Analyzing gene expression is an integral part of many, if not most, life sciences studies from basic biology to drug discovery and clinical research. Investigators need to know the underlying molecular basis for a phenotypic distinction, for example, or how a given treatment affects transcription.
Scientists use different methods, such as RNA sequencing (RNA-seq), quantitative-PCR (qPCR), microarrays, and the NanoString nCounter® platform, to query mRNA, with a variety of factors determining their choice. Among these are numbers of genes to be queried, quality of experimental samples, available equipment and budget, and workflow considerations including hands-on time and time-to-result, expertise in programming and bioinformatics, as well as throughput and reproducibility.
When little is known about the gene transcription in a sample, it’s hard to beat sequencing to discover patterns and profiles. With enough sequencing depth, RNA-seq gives gene expression information for every gene in the transcriptome. But it comes at a cost. RNA-seq requires a substantial amount of starting material, and has a long, involved workflow. The library preparation typically involves enzymatic steps such as reverse transcription and amplification, conferring potential biases and making it tricky to deal with suboptimal samples such as formalin-fixed paraffin-embedded (FFPE) tissue or liquid biopsies. Higher sensitivity requires more sequencing, which means a greater expense. In addition, translation to clinical practice involving a CLIA lab is more difficult because of the more complex workflow and long turnaround time.
If the expression of only a few genes is in order, qPCR is often the go-to workflow. Thermocyclers are abundant, the workflow is fast, the results are easy to analyze, and protocols are relatively easy to translate to CLIA facilities. But qPCR is low plex and requires a substantial amount of starting material, especially as more genes are queried. Normalization is not as robust, requiring multiple replicates and therefore more resources. Like RNA-seq, qPCR relies on enzymatic steps that make it less reliable in dealing with suboptimal samples.
Oligonucleotide microarrays offer a consistent method to query a large number of genes in a relatively few samples. They are especially attractive for comparing samples across different laboratories as well as in longitudinal studies, but suffer from some of the same pitfalls included in enzymatically based sample preparations as well as complex data analysis. Their usage has suffered a sharp decline in recent years as other techniques—especially next-generation sequencing (NGS)—have become more affordable and reliable.
The nCounter platform threads the needle of gene expression analysis when compared with the aforementioned techniques. Its non-enzymatic, direct detection protocol demands little hands-on time and offers a simple workflow with a quick turnaround time and easy analysis. It is reliable, robust, and easily translatable, allowing for multiplexed analysis of more than 800 targets directly from a cell lysate.
In a traditional gene expression protocol, RNA is enriched or purified, enzymatically converted to cDNA, often amplified, and quantitated as a proxy for the original RNA. These steps can introduce variability, potentially leading to bias and loss of reproducibility.
In the direct detection approach used by nCounter, each RNA species in a sample is directly tagged by a sequence-specific, optically unique barcode, obviating the need for enzymatically-created proxies. RNA purification is optional, with the 100 base pair homology between probes and target allowing for robust detection even from degraded samples.
The RNA target/probe complexes are counted by fluorescent imaging of the barcodes. The raw counts of each barcode directly represent individual RNA molecules, eliminating approximation and interpolation and helping to simplify data analysis.
The nCounter Pro platform offers comprehensive curated probe panels across a variety of research areas and pathways with which to interrogate samples. Scientists can also customize existing panels with their own probes, or design their own panels.
The nCounter workflow begins with four pipetting steps which combine the reagent, contiguous biotinylated capture probe and barcoded reporter probe—each with a 50 base pair homology to the target—and the sample to be interrogated. These are the only manual pipetting steps in the assay, helping to minimize human error. The next day the assay is moved to the automated platform where any unbound probes are washed away and the hybridized complexes are adhered to a slide where they are imaged and the barcodes counted. Data is then analyzed and can be formatted for presentation, all with a total turn-around time of ~24 hours.
Each method of capturing, exploring and analyzing gene expression has its advantages and disadvantages. It behooves the researchers to weigh these to determine the best fit for their own particular needs.