The application was developed in Actionscript and can be found online at http://www.dna.utah.edu/umelt/umelt.html. Adobe Flash is required to run in all browsers.

uAnalyze(SM) is a web-based tool for analyzing high-resolution melting data of PCR products. PCR product sequence is input by the user and recursive nearest neighbor thermodynamic calculations used to predict a melting curve similar to uMELT(http://www.dna.utah.edu/umelt/umelt.html). Unprocessed melting data are input directly from LightScanner-96, LS32, or HR-1 data files or via a generic format for other instruments. A fluorescence discriminator identifies low intensity samples to prevent analysis of data that cannot be adequately normalized. Temperature regions that define fluorescence background are initialized by prediction and optionally adjusted by the user. Background is removed either as an exponential or by linear baseline extrapolation. The precision or, “curve spread,” of experimental melting curves is quantified as the average of the maximum helicity difference of all curve pairs. Melting curve accuracy is quantified as the area or “2D offset” between the average experimental and predicted melting curves. Optional temperature overlay (temperature shifting) is provided to focus on curve shape. Using 14 amplicons of CYBB, the mean + / - standard deviation of the difference between experimental and predicted fluorescence at 50 percent helicity was 0:04 + / - 0:48°C. uAnalyze requires Flash, is not browser specific and can be accessed at http://www.dna.utah.edu/uv/uanalyze.html.

BACKGROUND Extreme PCR in <30 s and high-speed melting of PCR products in <5 s are recent advances in the turnaround time of DNA analysis. Previously, these steps had been performed on different specialized instruments. Integration of both extreme PCR and high-speed melting with real-time fluorescence monitoring for detection and genotyping is presented here. METHODS A microfluidic platform was enhanced for speed using cycle times as fast as 1.05 s between 66.4 °C and 93.7 °C, with end point melting rates of 8 °C/s. Primer and polymerase concentrations were increased to allow short cycle times. Synthetic sequences were used to amplify fragments of hepatitis B virus (70 bp) and Clostridium difficile (83 bp) by real-time PCR and high-speed melting on the same instrument. A blinded genotyping study of 30 human genomic samples at F2 c.*97, F5 c.1601, MTHFR c.665, and MTHFR c.1286 was also performed. RESULTS Standard rapid-cycle PCR chemistry did not produce any product when total cycling times were reduced to <1 min. However, efficient amplification was possible with increased primer (5 μmol/L) and polymerase (0.45 U/μL) concentrations. Infectious targets were amplified and identified in 52 to 71 s. Real-time PCR and genotyping of single-nucleotide variants from human DNA was achieved in 75 to 87 s and was 100% concordant to known genotypes. CONCLUSIONS Extreme PCR with high-speed melting can be performed in about 1 min. The integration of extreme PCR and high-speed melting shows that future molecular assays at the point of care for identification, quantification, and variant typing are feasible.

Melting curve prediction of PCR products is limited to perfectly complementary strands. Multiple domains are calculated by recursive nearest neighbor thermodynamics. However, the melting curve of an amplicon containing a heterozygous single-nucleotide variant (SNV) after PCR is the composite of four duplexes: two matched homoduplexes and two mismatched heteroduplexes. To better predict the shape of composite heterozygote melting curves, 52 experimental curves were compared with brute force in silico predictions varying two parameters simultaneously: the relative contribution of heteroduplex products and an ionic scaling factor for mismatched tetrads. Heteroduplex products contributed 25.7 ± 6.7% to the composite melting curve, varying from 23%-28% for different SNV classes. The effect of ions on mismatch tetrads scaled to 76%-96% of normal (depending on SNV class) and averaged 88 ± 16.4%. Based on uMelt (www.dna.utah.edu/umelt/umelt.html) with an expanded nearest neighbor thermodynamic set that includes mismatched base pairs, uMelt HETS calculates helicity as a function of temperature for homoduplex and heteroduplex products, as well as the composite curve expected from heterozygotes. It is an interactive Web tool for efficient genotyping design, heterozygote melting curve prediction, and quality control of melting curve experiments. The application was developed in Actionscript and can be found online at http://www.dna.utah.edu/hets/.

Rare variant enrichment and quantification was achieved by allele-specific, competitive blocker, digital PCR for aiming to provide a noninvasive method for detecting rare DNA variants from circulating cells. The allele-specific blocking chemistry improves sensitivity and lowers assay cost over previously described digital PCR methods while the instrumentation allowed for rapid thermal cycling for faster turnaround time. Because the digital counting of the amplified variants occurs in the presence of many wild-type templates in each well, the method is called "quasi-digital PCR". A spinning disk was used to separate samples into 1000 wells, followed by rapid-cycle, allele-specific amplification in the presence of a molecular beacon that serves as both a blocker and digital indicator. Monte Carlo simulations gave similar results to Poisson distribution statistics for mean number of template molecules and provided an upper and lower bound at a specified confidence level and accounted for input DNA concentration variation. A 111 bp genomic DNA fragment including the BRAF p.V600E mutation (c.T1799A) was amplified with quasi-digital PCR using cycle times of 23 s. Dilution series confirmed that wild-type amplification was suppressed and that the sensitivity for the mutant allele was<0.01 % (43 mutant alleles amongst 500,000 wild-type alleles). The Monte Carlo method presented here is publically available on the internet and can calculate target concentration given digital data or predict digital data given target concentration.