As RNAi continues to gain in popularity as a tool for gene silencing and studying gene function as well as biochemical pathways, qPCR has played an important role in quantifying RNA transcripts to validate gene knockdown.
While qPCR is an invaluable assest for assessing changes in RNA levels, understanding the full scope of the effects of gene silencing requires a multidisciplinary approach that combines qPCR, 2-D gel electrophoresis, and Western blotting, according to Hilary K. Srere, Ph.D., marketing manager for amplification in the gene expression division at Bio-Rad Laboratories (www.bio-rad.com).
Bio-Rad will be one of the companies presenting at Intelligent Enterprise Solutions’ “qPCR Symposium USA” to be held later this month in Palo Alto, CA.
Dr. Srere recently published research describing the changes in both mRNA and protein that the R&D team at Bio-Rad found when using RNAi to knock down the ß-actin gene. Using 2-D electrophoresis, the group identified five proteins that were either down- or up-regulated as a result of ß-actin gene silencing. qPCR studies to measure the mRNA levels for these proteins before and after ß-actin knock-down showed that some of the RNA levels changed while others did not.
Subsequent Western blot experiments demonstrated that some of the changes in protein expression could be attributed to post-translational modifications such as phosphorylation rather than to changes in gene expression.
Without a multidisciplinary approach designed to correlate RNA and protein changes “you won’t see the whole story,” said Dr. Srere. “The power of qPCR is that it gives an answer the same day and can then help guide decisions on what to look at next. You can also get a lot of data from a small amount of starting material.”
Bio-Rad’s multiplex real time qPCR (RT-qPCR) technology allows researchers to look at five targets at one time. To simplify data analysis, iQ™5 and MyiQ™ real-time PCR detection systems come with analysis software that contains multiple options for data analysis and presentation to yield a comprehensive view of assay results.
The software permits normalization to a standardized input amount, to a single reference gene, or to the geometric mean of multiple reference genes. Additionally, the software can take individual assay efficiencies into consideration, as well as combine multiple data sets to generate a complete gene study.
When asked to identify the lessons learned from advances in PCR technology and the main challenges for PCR applications at present, Russell Higuchi, Ph.D., associate director of human genetics at Roche Molecular Diagnostics (molecular.roche.com), and keynote speaker at “qPCR Symposium USA,” emphasized two key points. The most important lesson learned, he said, is that PCR is capable of providing reproducible quantification—putting to rest any question of whether DNA and RNA can be quantified using an amplification strategy. The most difficult aspect of PCR, however, remains sample preparation.
As an example of industry-wide advances in making sample prep more reliable and reproducible through automation technology, he points to Roche’s combined COBAS® AmpliPrep/COBAS TaqMan® real-time PCR instrument system, an automated system that has been validated for diagnostic applications. The system can accommodate 72 samples at first, with continuous loading thereafter, and has the ability to run four different assays (three assays plus internal controls). Manual handling is limited to loading sealed, barcoded reagent cassettes.
Sample prep is a challenge across a variety of research and diagnostic applications. “One of the most challenging but necessary applications of quantitative PCR is viral load testing, for example, measuring the amount of HIV or hepatitis virus in a standard blood sample,” said Dr. Higuchi.
In the research arena, the broad spectrum of samples that serve as the starting point for PCR applications and the variability in DNA and RNA sample size, down to the smallest microRNAs, also pose challenges for standardizing and automating sample prep. Roche Applied Sciences’ MagNA Pure LC instrument purifies nucleic acid samples and can set up downstream RT-PCR reactions for research applications, Dr. Higuchi added.
As an enabling tool, PCR is playing a critical role in genetic analysis, DNA- and RNA-based diagnostics, and mRNA profiling and gene expression studies. Enhanced sensitivity makes qPCR a valuable tool to complement and validate microarray studies. Whereas microarrays offer the advantage of being able to look at a large set of genes, the greater sensitivity of qPCR allows for surveying many more samples against a defined gene set of interest.
“In the research arena, people would like to broaden the net,” said Dr. Higuchi, and be able to use qPCR to look at more targets with the same high sensitivity.
Even experienced scientists using qPCR for gene expression studies may make unwise assumptions regarding the quality and performance of the RNA template, and the amplification protocol that can lead to inaccurate or wrongly interpreted results.
Tania Nolan, Ph.D., business development manager at Sigma-Genosys (www.sigma.com), emphasizes the importance of performing quality control and optimization experiments, especially for real-time qPCR.
The company’s assay development work stemmed from the growing interest in profiling mRNA from archived biological samples, typically formalin-fixed, paraffin-embedded (FFPE) samples, and correlating the gene expression data with established clinical data sets.
“The RNA isolated from FFPE-archived material is highly degraded, and it was unclear how such degradation would affect data from such samples,” said Dr. Nolan. She set out to devise a high-throughput method for evaluating the integrity of the RNA templates. An additional aim was to produce a technique that could be used when only small amounts of sample are available, such as samples from laser-capture microdissected biopsies. A detailed analysis of these samples would ensure that RT-qPCR is performed on samples of equivalent integrity. Using the 3´:5´ assay, she demonstrated that the state of the RNA template can affect the outcome of RT-qPCR and the perceived results of gene expression studies.
The method begins with a target RNA transcript and reverse transcription using oligo-dT priming. The reverse transcription then starts from the polyA tail and moves from 3´ to 5´. Two sets of primers target the 3´ and 5´ areas of the specific cDNA template, which are amplified either in separate reactions or in a duplex assay using amplicon-specific probes.
Target quantification is measured using SYBR Green I dye. If the RNA is intact, then quantifying the 5´ and 3´ ends of the cDNA generated from the same target will yield the same quantity of target. In contrast, if the RNA is degraded somewhere between the 5´ and 3´ assay sites, then the reverse transcriptase will stall at the break point and the assay will yield more 3´ cDNA.
Dr. Nolan has observed that not all transcripts in a sample degrade at the same rate. In fact, transcripts appear to degrade at different rates in different tissues. Ongoing work at Queen Mary University of London, together with Sigma-Genosys, aims to determine which targets, and how many, need to be studied before it would be safe to assume whether or not a particular RNA sample is intact.
Another quality control issue relates to the risk of contaminants in the sample that can inhibit the enzymatic reactions required for RT-qPCR. Environmental samples or crude biological preparations, for example, may contain contaminants that inhibit PCR, resulting in false negative results. It is not safe to assume, though, that if a sample contains an inhibitor it will always inhibit all qPCR assays to the same degree. Therefore, noted Dr. Nolan, it is not sufficient to correct for inhibitors by quantifying a reference gene.
To identify whether a sample contains factors that may inhibit PCR, Dr. Nolan and colleagues developed the SPUD assay. This involves running a control PCR using an artificial amplicon (from the potato genome) in parallel with an identical PCR reaction that contains both the artificial amplicon and the sample. If the sample contains an inhibitor, it will take more cycles for the fluorescence signal to rise above the threshold background fluorescence (a parameter known as Ct, or threshold cycle). Therefore, in the presence of inhibiting factors, the Ct will shift higher.
Interestingly, an inhibitory factor may inhibit the 3´ PCR assay and the 5´ PCR assay to different degrees. While the SPUD assay can identify the presence of an inhibitor, the results of the 3´:5´ assay may also reflect the variable effects of the inhibitor, resulting in either more 5´ sequences or more 3´ sequences. Sigma-Genosys is designing a set of reference assays that will allow for a comparison of the amount of 5´ and 3´ sequences compared to a standard curve.
“You cannot use normalization to get around the problem of RNA degradation” or as an alternative to evaluating the quality and integrity of an RNA sample, concluded Dr. Nolan. She recommends running both the 3´:5´ and the SPUD assay on every RNA sample as a quality control measure.
“The small size of microRNAs—on average 22 nucleotides—make them challenging targets to analyze by qPCR,” the gold standard method for quantifying RNA species, said Christopher Adams, Ph.D., research area manager at Invitrogen (www.invitrogen.com). Dr. Adams explained that unlike methods that rely on the use of predesigned miRNA target-specific primers for reverse transcriptase, Invitrogen’s universal primer approach adds a polyA tail to all miRNA targets and introduces a universal RT primer that is then capable of priming cDNA synthesis off of any miRNA species.
NCode™ miRNA RT-qPCR analysis utilizes a polyadenylation reaction, a reverse transcription reaction with SuperScript™ III RT, SYBR® Green detection reagent, a primer designed for each miRNA sequence, and a universal qPCR primer. The sequence of the miRNA of interest is used as the target-specific PCR primer.
“The use of a universal RT primer approach provides a number of advantages. For example, each cDNA reaction can be assayed for multiple miRNAs or archived for assay at a later date as our knowledge of interesting miRNA increases,” said Dr. Adams.
To validate the robustness of its qPCR assay, Invitrogen has tested it with more than 400 miRNA targets. The company recommends using the mature miRNA sequence for conversion into a primer for the PCR reaction. As some primer sequences will fall outside the optimal melting temperature range for qPCR—for example, highly GC-rich sequences have a higher melting temperature and AT-rich regions will have a lower melting temperature—the company is developing a set of guidelines to help customers design appropriate primers.
Dr. Adams described how the company is applying qPCR of miRNAs to study the molecular mechanisms involved in stem cell differentiation in collaboration with researchers in academia. The results support a dynamic miRNA environment and have identified specific miRNAs as markers of totipotency, pluripotency, and other characteristics of human embryonic stem cell (hESC) populations.
Invitrogen recently collaborated with researchers at Rutgers University on comparing miRNA expression patterns of undifferentiated and differentiated hESCs. Using a combination of microarray and qPCR data, they identified a signature microRNA profile in pluripotent cells and clusters of microRNAs grouped with specific mRNAs. They also described “patterns of expression in the progression from hESC to differentiated cells that suggest a role for selected microRNAs in maintenance of the undifferentiated, pluripotent state.”
Invitrogen scientists are also working with Mark Mercola, Ph.D.’s group at the Burnham Institute to link miRNAs to the differentiation of cardiomyocytes from hESCs. Dr. Mercola’s research is directed at discovering molecules that promote differentiation of cardiomyocyte progenitors that will ultimately be useful for regeneration of muscle cells lost as a result of heart disease.
Diagnostic and Prognostic Applications
Oncotype Dx™ is Genomic Health’s (www.genomichealth.com) marketed prognostic RT-qPCR-based gene expression assay used to guide therapeutic decision-making for patients with node-negative, estrogen-receptor positive breast cancer.
Designed for use with FFPE tissue samples, the test involves extracting RNA from a patient sample and looking for associations between specific biomarkers that correlate with predicted clinical outcomes. “The result is a recurrence score,” explained Maureen Cronin, Ph.D., vp of technology research, “which represents the patient’s risk of breast cancer recurrence and the amount of benefit the patient is likely to get from chemotherapy.”
The multigene expression test also predicts the likelihood of patient survival within 10 years of diagnosis. The company has studied and validated the qPCR-based assay in randomized clinical studies involving more than 3,000 breast cancer patients.
Genomic Health chose a RT-qPCR-based assay over a microarray-based test primarily because of the small size of the RNAs that can be isolated from FFPE tissue samples. Whereas the typical size range of RNA extracted from fresh tissue is 1–10 kilobases, due to degradation the FFPE tissue RNAs are usually in the 100–200 base range.
“Using optimization strategies around RT-PCR, selection of a primer/probe assay design that is optimized for the average short length of the RNA, we found we could get robust and reliable assays,” said Dr. Cronin. “We focus on very efficient priming and initiation of the reverse transcription.”
After applying the assay to biomarker discovery in large sets of patients and identifying a small biomarker set associated with the targeted breast cancer cohort, the company incorporated the same assay into a diagnostic test for commercialization. A colon cancer diagnostic is entering the final stages of commercial development, and other cancer biomarker assays are in the pipeline, including work on an assay for node-positive breast cancer.
“The quantitative nature of the RT-PCR assay is the hallmark of this test,” said Dr. Cronin. “With RT-qPCR, you can discriminate more subtle differences between patients than you can with a hybridization-based assay. The quantitative outputs feed into the prognostic model derived from clinical data to yield a percentage risk of recurrence from as low as 4% to as high as 37% based on a continuous curve of recurrence scores from 0 to 100%.”
Advances in RT-qPCR technology are facilitating the use of these assays in clinical medicine. Dr. Cronin pointed to the Roche LightCycler® 480 “as an example of a PCR instrument that introduces the robustness we would like to see in a clinical laboratory application.”
Emerging trends in breast cancer diagnosis and prognosis such as analysis of biopsy samples rather than tissue obtained from surgical tumor resection and detection of tumors earlier (often based on mammography) are resulting in smaller tissue samples and less RNA for analysis. Genomic Health is also working on assay miniaturization and is experimenting with strategies to increase the sensitivity of qPCR.