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Custom PCR Array

Custom PCR Arrays Tailored to Your Research

Custom Profiler RT² PCR Arrays for gene expression analysis are made with RT² Primer Assays, which are all wet-bench laboratory verified (with a performance guarantee).

Pathways available for other species         

To order a custom RT² Profiler PCR Array, please use this excel file.

If you like the content for any of our pathways, but are working on a different species than those mentioned above, please contact us at Support@SABiosciences.com to inquire about a Species Conversion for this pathway to support your species of interest.

 
Plate Layouts QA/QC Parameters Performance Controls & Data Analysis
 

Click for layout options
Options for Customizing PCR Arrays
  1. Modify Catalogued PCR Arrays: Add Your Favorite Genes (Up to 4) to Existing PCR Array Gene Lists


  2. Build Your Own Custom PCR Arrays: Provide Your Own List of Genes

PCR Array Plate Format

How to Order:

  1. Select a plate layout to match the gene number and the number of samples you would like to analyze.
    • Please have the type of RT-PCR instrument available when placing the order.
  2. Determine the number and types of plates required.
  3. Use the following Excel file to enter your gene list.
  4. Contact SABiosciences Technical Support at 1-888-503-3187 to submit your gene list and obtain a quote.
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Plate Layouts QA/QC Parameters Performance Controls & Data Analysis
  Quality Assurance / Quality Control (QA/QC) Parameters

Primer Quality Control (QC)
Any algorithm's primer design must also be experimentally validated for high-performance with wet bench quality control protocols starting with two major success criteria.

  • First, a melt curve analysis must verify that a single gene-specific product is produced. Following the melt curve, an agarose gel can also be run to further verify a single product of the predicted size, based on the amplicon design, without primer dimers or off-target amplifications.
  • Second, the amplification efficiency must be greater than 90 percent for accurate and reliable results. If a real-time RT-PCR assay does not meet all of the above requirements, then the quality control fails, and the assay must be re-designed.

QA/QC Specificity

All real-time PCR assays must generate a single band of the correct size for the results to accurately represent the expression of the queried gene. Secondary products confound the analysis. If using SYBR Green-based detection, you can tell if your real-time PCR assays are specific enough by simply running the default melting program on your instrument immediately after the completion of the cycling program. A single peak indicates a single melting event, and therefore a single product.

 

Figure 1: Human XpressRef Universal Total RNA was characterized on the Human Common Cytokines (B) RT² Profiler™ PCR Arrays, followed by dissociation (melt) curve and gel electrophoretic analyses. The RT² qPCR™ Assay specifically detects an individual gene, in particular for the displayed cytokine genes, whose specific assays tend to be notoriously difficult to design.

Efficiency

Of the various methods of determining amplification efficiency, the most rigorous and classical method examines the slope of a calibration curve, much like those used to assess dynamic range. An assay with 100 percent efficiency yields a -3.33 calibration curve slope, a relatively narrow standard deviation about that mean.

Figure 2: A representative set of assays for 4,000 genes used in the RT² PCR Arrays demonstrate their average amplification efficiency of 99% and their 95% confidence interval about the mean from 90-110%. Consistently high amplification efficiencies enable PCR Arrays to accurately analyze multiple genes simultaneously using the ΔΔCt method.

Primer Design Algorithm

Primer design algorithm is key to effective qPCR based gene expression analysis. Designs must meet several important thermodynamic and sequence criteria. Primers are designed such that they must detect every alternative transcript and splicing variant of the queried gene so as not to miss any genes.

To do so, all known entries in the public databases should be found and aligned to reveal a common gene-specific region for primer design.

  • By controlling the GC content, primer length, and the primer melting temperature range, each assay can use a standard set of PCR cycling conditions.

  • Uniform cycling conditions, in turn, allow researchers to scale up from a single assay, to multiple assays on an entire 96- or even 384-well plate.

  • Single Nucleotide Polymorphism (SNP) analysis can eliminate repetitive sequences so that any individual source of total RNA may be analyzed with the same assay.

  • BLAST analysis further insures that the chosen primer sequences are sufficiently different from the rest of the transcriptome in the species of interest.

  • Stability at the 3'-end of the primers controls the start position for the DNA polymerase, further enhancing specificity.

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Plate Layouts QA/QC Parameters Performance Controls & Data Analysis
  System Performance

Sensitivity and Dynamic Range

Sensitivity may also be judged by how many copies of cDNA can be detected. When analyzing the expression of multiple genes at once in the same cycling run, some genes may be expressed at very low copy numbers while other may be expressed at much higher copy numbers. Real-time PCR assays, in general, have the unique potential capability of detecting transcripts down to one individual copy and up to several orders of magnitude more. Researchers have come to expect or even assume that real-time PCR assays indeed detect a wide variety of transcripts expressed at very different levels.

Reproducibility

Researchers are also understandably concerned about the reproducibility of their real-time PCR assay results, if only to help make sure that reviewers will let their results be published. In addition, profiling multiple genes in the same sample also requires a high degree of reproducibility. When looking at enough genes to fill an entire 96-well
or even 384-well plate, the assays must be reproducible enough so that the data can be legitimately compared between separate and individual runs, plates, and samples

The MAQC brain reference RNA sample4,5 was reverse transcribed and run on four replicate Human Drug Metabolism PCR Arrays three months apart by two different investigators each using a different production lot. The raw data from each end-user's four replicates with all four of the other enduser's replicates in a scatter plot, and fit to a straight line with a slope of one. The average Ct value correlation coefficient between the replicate runs by the respective end-users was 0.995 +0.001 and 0.998 +0.000.

 

Plate Layouts QA/QC Parameters Performance Controls & Data Analysis
 
How PCR Array Control Elements Work
Many factors are known to influence real-time PCR assay analyses, even if the performance of the assay itself is validated and optimized-from input RNA quality, RT condition, the PCR cycling conditions, and to the performance of real-time PCR instruments. For data normalization purposes, we recommend our customers include a set of control elements into each custom-made PCR array for Biomarker Validation array.

As a company which provides the reagents and pre-validated assays to researchers, we have come across many things that could go astray in a qRT-PCR assay. Problems in the quality of RNA encompasses the majority (>90%) of the cases. In addition, instrument-related problems such as suboptimal performance of the real-time PCR instrument, high background contamination on the thermal block, or incorrect PCR program setup, which will greatly affect the success of PCR, often go unnoticed or ignored. Hence, the possibility of many unforeseen variables that could occur during the qRT-PCR processes necessitates the inclusion of controls that can monitor the outcomes of each step of qRT-PCR.

To have reliable and reproducible qRT-PCR assays, three requirements have to be met. These include:

  1. Minimal genomic DNA contamination.
  2. Intact RNA free of any impurities that inhibit reverse transcription or PCR
  3. Correct PCR cycling conditions

To serve these purposes, we have developed a proprietary panel of controls which would give researchers confidence in their qRT-PCR results. Furthermore, these controls would greatly facilitate researchers and save their time in the troubleshooting processes, should a problem arise in their qRT-PCR assays.

  1. Genomic DNA Contamination (GDC) control: detects a specific genomic DNA sequence within an ORF-free intergenic region
  2. Reverse Transcription Control (RTC): detects an artificial External RNA Control sequence spiked into the first strand cDNA synthesis reaction
  3. Positive PCR Control (PPC): Detects a pre-dispensed external DNA template of known copies to produce a defined Ct value under proper PCR conditions

Minimal genomic DNA contamination

So why do we care about genomic DNA contamination? This is because genomic DNA found in RNA preparations can act as an effective template during PCR, resulting in undesirable false positive signals unrelated to mRNA. Strategies such as cross-intron primer design may still not be able to avoid amplification from the contaminating genomic DNA due to presence of large number of processed pseudogenes in the mammalian genomes.

The GDC assay can be used to evaluate how effective genomic DNA contamination is removed from RNA samples by DNAse treatment. Traditionally, researchers perform qPCR of RT-minus assays (also known as no reverse transcription (NRT) assays) to monitor the level of genomic DNA contamination in their samples. However, this would mean performing an additional first strand synthesis reaction and PCR assay for each targeted gene.

Figure 6: RNA from HEK 293T cells, mouse spinal tissue, mouse brain tissue, or rat brain tissue was characterized on PCR Arrays before (purple bars) and after (yellow bars) treatment with gDNA Elimination Buffer from the RT² First Strand Kit (330401). Successful removal of genomic DNA contamination is indicated by GDC Ct values greater than 35.

Intact RNA free of any impurities that inhibit reverse transcription or PCR

Figure 7: Tissue contaminants and lysis or wash reagent impurities inadvertently co-purifying with RNA during isolation adversely affect RNA integrity or inhibit reverse transcriptase activity. Human universal RNA was characterized without or with a small amount of TRIZOL® reagent or treatment with a magnesium salt to simulate RNA degradation. Contaminated or degraded RNA resulted in higher threshold cycle (Ct) values for both the genes of interest and the RTC, and increased the Ct difference between the RTC and PPC controls above the pass/fail threshold of five (5) cycles, indicating that reverse transcription was impaired.

Correct PCR cycling conditions

Real-time PCR instruments, especially in core facilities, are often heavily used and their performance will deteriorate over time. If these instruments are not properly maintained, data generated from them may not be reliable. The PPC can be used to assess the performance of real-time PCR instruments and to determine if they need to be serviced.

Figure 8: Incorrect setup of PCR cycling conditions or the presence of PCR inhibitors adversely affects qRT-PCR results. Universal RNA was characterized on PCR Arrays with or without the ten-minute 95 ºC heat activation step required to begin the cycling program. The correct program yielded the predicted PPC Ct value of 20, while the wrong program failed to adequately amplify the PPC template (Ct = 36).

Data Analysis
A technical support representative will email you customized data analysis template to suit your gene set after your order is placed. Your system tool will be ready to go when your custom arrays arrive at your lab. Please visit the RT² PCR Array Data Analysis page to learn more.

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