Expanded Instrument Comparison of Amplicon DNA Melting Analysis for Mutation Scanning and Genotyping

DNA melting analysis

Melting is a fundamental property of DNA that can be monitored by absorbance or fluorescence. PCR conveniently produces enough DNA to be directly monitored on real-time instruments with fluorescently labeled probes or dyes. Dyes monitor the entire PCR product, while probes focus on a specific locus within the amplicon. Advances in amplicon melting include high resolution instruments, saturating DNA dyes that better reveal multiple products, prediction programs for domain melting, barcode taxonomic identification, high speed microfluidic melting, and highly parallel digital melting. Most single base variants and small insertions or deletions can be genotyped by high resolution amplicon melting. High resolution melting also enables heterozygote scanning for any variant within a PCR product. A web application (uMelt, http://www.dna-utah.org) predicts amplicon melting curves with multiple domains, a useful tool for verifying intended products. Additional applications include methylation assessment, copy number determination and verification of sequence identity. When amplicon melting does not provide sufficient detail, unlabeled probes or snapback primers can be used instead of covalently labeled probes. DNA melting is a simple, inexpensive, and powerful tool with many research applications that is beginning to make its mark in clinical diagnostics.

A novel high-resolution melting analysis strategy for detecting cystic fibrosis-causing variants

Cystic fibrosis (CF), an autosomal recessive disease, is caused by variants in both alleles of the CF transmembrane conductance regulator (CFTR) gene. A new assay based on allele-specific polymerase chain reaction and high-resolution melting analysis was developed for the detection of 18 CF-causing CFTR variants previously identified in Cuba and Latin America. The assay is also useful for zygosity determination of mutated alleles and includes internal controls. The reaction mixtures were normalized and evaluated using blood samples collected on filter paper. The evaluation of analytical parameters demonstrated the specificity and sensitivity of the method to detect the included CFTR variants. Internal and external validations yielded a 100% agreement between the new assay and the used reference tests. This assay can complement CF newborn screening not only in Cuba but also in Latin America.

An update on current and novel molecular diagnostics for the diagnosis of invasive fungal infections

BACKGROUND

Invasive fungal infections cause millions of infections annually, but diagnosis remains challenging. There is an increased need for low-cost, easy to use, highly sensitive and specific molecular assays that can differentiate between colonized and pathogenic organisms from different clinical specimens.

AREAS COVERED

We reviewed the literature evaluating the current state of molecular diagnostics for invasive fungal infections, focusing on current and novel molecular tests such as polymerase chain reaction (PCR), digital PCR, high-resolution melt (HRM), and metagenomics/next generation sequencing (mNGS).

EXPERT OPINION

PCR is highly sensitive and specific, although performance can be impacted by prior/concurrent antifungal use. PCR assays can identify mutations associated with antifungal resistance, non-Aspergillus mold infections, and infections from endemic fungi. HRM is a rapid and highly sensitive diagnostic modality that can identify a wide range of fungal pathogens, including down to the species level, but multiplex assays are limited and HRM is currently unavailable in most healthcare settings, although universal HRM is working to overcome this limitation. mNGS offers a promising approach for rapid and hypothesis-free diagnosis of a wide range of fungal pathogens, although some drawbacks include limited access, variable performance across platforms, the expertise and costs associated with this method, and long turnaround times in real-world settings.

The Arabidopsis HY2 Gene Acts as a Positive Regulator of NaCl Signaling during Seed Germination

Phytochromobilin (PΦB) participates in the regulation of plant growth and development as an important synthetase of photoreceptor phytochromes (phy). In addition, Arabidopsis long hypocotyl 2 (HY2) appropriately works as a key PΦB synthetase. However, whether HY2 takes part in the plant stress response signal network remains unknown. Here, we described the function of HY2 in NaCl signaling. The hy2 mutant was NaCl-insensitive, whereas HY2-overexpressing lines showed NaCl-hypersensitive phenotypes during seed germination. The exogenous NaCl induced the transcription and the protein level of HY2, which positively mediated the expression of downstream stress-related genes of RD29A, RD29B, and DREB2A. Further quantitative proteomics showed the patterns of 7391 proteins under salt stress. HY2 was then found to specifically mediate 215 differentially regulated proteins (DRPs), which, according to GO enrichment analysis, were mainly involved in ion homeostasis, flavonoid biosynthetic and metabolic pathways, hormone response (SA, JA, ABA, ethylene), the reactive oxygen species (ROS) metabolic pathway, photosynthesis, and detoxification pathways to respond to salt stress. More importantly, ANNAT1–ANNAT2–ANNAT3–ANNAT4 and GSTU19–GSTF10–RPL5A–RPL5B–AT2G32060, two protein interaction networks specifically regulated by HY2, jointly participated in the salt stress response. These results direct the pathway of HY2 participating in salt stress, and provide new insights for the plant to resist salt stress.

Improving Quantitative Power in Digital PCR through Digital High-Resolution Melting

Applying digital PCR (dPCR) technology to challenging clinical and industrial detection tasks has become more prevalent because of its capability for absolute quantification and rare target detection. However, practices learned from quantitative PCR (qPCR) that promote assay robustness and wide-ranging utility are not readily applied in dPCR. These include internal amplification controls to account for false-negative reactions and amplicon high-resolution melt (HRM) analysis to distinguish true positives from false positives. Incorporation of internal amplification controls in dPCR is challenging because of the limited fluorescence channels available on most machines, and the application of HRM analysis is hindered by the separation of heating and imaging functions on most dPCR systems. We use a custom digital HRM platform to assess the utility of HRM-based approaches for mitigation of false positives and false negatives in dPCR. We show that detection of an exogenous internal control using dHRM analysis reduces the inclusion of false-negative partitions, changing the calculated DNA concentration up to 52%. The integration of dHRM analysis enables classification of partitions that would otherwise be considered ambiguous "rain," which accounts for up to ∼3% and ∼10% of partitions in intercalating dye and hydrolysis probe dPCR, respectively. We focused on developing an internal control method that would be compatible with broad-based microbial detection in dPCR-dHRM. Our approach can be applied to a number of DNA detection methods including microbial profiling and may advance the utility of dPCR in clinical applications where accurate quantification is imperative.

Use of Machine Learning with Temporal Photoluminescence Signals from CdTe Quantum Dots for Temperature Measurement in Microfluidic Devices

Because of the vital role of temperature in many biological processes studied in microfluidic devices, there is a need to develop improved temperature sensors and data analysis algorithms. The photoluminescence (PL) of nanocrystals (quantum dots) has been successfully used in microfluidic temperature devices, but the accuracy of the reconstructed temperature has been limited to about 1 K over a temperature range of tens of degrees. A machine learning algorithm consisting of a fully-connected network of seven layers with decreasing numbers of nodes was developed and applied to a combination of normalized spectral and time-resolved PL data of CdTe quantum dot emission in a microfluidic device. The data used by the algorithm was collected over two temperature ranges: 10 K to 300 K, and 298 K to 319 K. The accuracy of each neural network was assessed via mean absolute error of a holdout set of data. For the low temperature regime, the accuracy was 7.7 K, or 0.4 K when the holdout set is restricted to temperatures above 100 K. For the high temperature regime, the accuracy was 0.1 K. This method provides demonstrates a potential machine learning approach to accurately sense temperature in microfluidic (and potentially nanofluidic) devices when the data analysis is based on normalized PL data when it is stable over time.

Implementation of high-resolution melting analysis of the porcupine (PORCN) gene for molecular diagnosis of focal dermal hypoplasia: Identification of a novel mutation

BACKGROUND

Focal dermal hypoplasia (FDH) is rare X-linked dominant disease characterized by atrophy and linear pigmentation of the skin, split hand/foot deformities and ocular anomalies. FDH is caused by mutations of the Porcupine (PORCN) gene, which encodes an enzyme that catalyzes the palmitoylation of Wnt ligands required for their secretion. High resolution melting analysis (HRM) is a technique that allows rapid, labor-efficient, low-cost detection of genomic variants. In the present study, we report the successful implementation of HRM in the molecular diagnosis of FDH.

METHODS

Polymerase chain reaction and HRM assays were designed and optimized for each of the coding exons of the PORCN gene, processing genomic DNA samples form a non-affected control and a patient complying with the FDH diagnostic criteria. The causal mutation was characterized by Sanger sequencing from an amplicon showing a HRM trace suggesting heterozygous variation and was validated using an amplification-refractory mutation system (ARMS) assay.

RESULTS

The melting profiles suggested the presence of a variant in the patient within exon 1. Sanger sequencing revealed a previously unknown C to T transition replacing a glutamine codon for a premature stop codon at position 28, which was validated using ARMS.

CONCLUSIONS

Next-generation sequencing facilitates the molecular diagnosis of monogenic disorders; however, its cost-benefit ratio is not optimal when a single, small or medium size causal gene is already identified and the clinical diagnostic presumption is strong. Under those conditions, as it is the case for FDH, HRM represents a cost- and labor-effective approach.

Genotyping DNA Variants with High-Resolution Melting Analysis

High-resolution melting analysis (HRMA) is a simple, quick, and effective method to scan and screen PCR amplicons for sequence variants. HRMA is a nondestructive closed tube assay; after PCR, DNA melting can directly be performed on the amplified samples without any purification or separation steps. For single SNP genotyping, HRMA is an attractive alternative to Sanger sequencing, restriction enzyme analysis, and hydrolysis probes.

Simple and efficient screening of patients with Fabry disease with high resolution melting

BACKGROUND

Fabry disease (FD [MIM: 301500]) is a disorder caused by mutations in the alpha-galactosidase gene (GLA), which presents great allelic heterogeneity. The development of fast screening methods may reduce costs and length of diagnosis, being particularly important for screening programs of high-risk female patients. Therefore, the purpose of this study was to develop a pre-sequencing genetic screening method based on high resolution melting (HRM) analysis.

METHODS

We performed HRM analysis in one hundred and three individuals, 79 females and 24 males, with a total of 27 different variants in 30 different genotypes. We standardized a protocol using EvaGreen, a release-on-demand dye specific for HRM, added to the PCR reaction. Amplification was performed in a conventional real-time system with HRM capability.

RESULTS

All genotypes in all amplicons were distinguishable from wild type. In most amplicons it was even possible to differentiate each genotype from the others.

CONCLUSION

We developed a simple, fast and highly sensitive HRM based protocol that may facilitate genetic screening of FD.

High Resolution Melting (HRM) for High-Throughput Genotyping-Limitations and Caveats in Practical Case Studies

High resolution melting (HRM) is a convenient method for gene scanning as well as genotyping of individual and multiple single nucleotide polymorphisms (SNPs). This rapid, simple, closed-tube, homogenous, and cost-efficient approach has the capacity for high specificity and sensitivity, while allowing easy transition to high-throughput scale. In this paper, we provide examples from our laboratory practice of some problematic issues which can affect the performance and data analysis of HRM results, especially with regard to reference curve-based targeted genotyping. We present those examples in order of the typical experimental workflow, and discuss the crucial significance of the respective experimental errors and limitations for the quality and analysis of results. The experimental details which have a decisive impact on correct execution of a HRM genotyping experiment include type and quality of DNA source material, reproducibility of isolation method and template DNA preparation, primer and amplicon design, automation-derived preparation and pipetting inconsistencies, as well as physical limitations in melting curve distinction for alternative variants and careful selection of samples for validation by sequencing. We provide a case-by-case analysis and discussion of actual problems we encountered and solutions that should be taken into account by researchers newly attempting HRM genotyping, especially in a high-throughput setup.

Differentiation of minute virus of mice and mouse parvovirus by high resolution melting curve analysis

Murine parvovirus is one of the most prevalent infectious pathogens in mouse colonies. A specific primer pair targeting the VP2 gene of minute virus of mice (MVM) and mouse parvovirus (MPV) was utilized for high resolution melting (HRM) analysis. The resulting melting curves could distinguish these two virus strains and there was no detectable amplification of the other mouse pathogens which included rat parvovirus (KRV), ectromelia virus (ECT), mouse adenovirus (MAD), mouse cytomegalovirus (MCMV), polyoma virus (Poly), Helicobactor hepaticus (H. hepaticus) and Salmonella typhimurium (S. typhimurium). The detection limit of the standard was 10 copies/μL. This study showed that the PCR-HRM assay could be an alternative useful method with high specificity and sensitivity for differentiating murine parvovirus strains MVM and MPV.

Comparison of traditional and new generation DNA markers declares high genetic diversity and differentiated population structure of wild almond species

Wild almond species as sources of genetic variation may have crucial importance in breeding. A total of 389 accessions of 18 species have been analysed using inter-retrotransposon amplified polymorphism (IRAP), retrotransposon-microsatellite amplified polymorphism (REMAP), sequence-specific amplification polymorphism (S-SAP), amplified fragment length polymorphism (AFLP), inter simple sequence repeat (ISSR) and simple sequence repeats (SSR). Retrotransposon markers indicated the presence and movement of some Ty3-gypsy and Ty1-copia-elements in almond genome. Since transposable elements are associated with large-scale genome alterations, REMAP produced more reliable phylogenetic inferences than AFLP where homoplasy may affect clustering. In addition, high resolution melting (HRM) analysis was developed to detect SNPs. HRM analysis revealed 1:189 bp frequency of SNPs in exon positions, and the transition-to-transversion proportion was 1.84:1. The low transition bias suggests low methylation levels in almond genome. The polymorphic information content (PIC) was the highest for SSR markers, while SNPs had an average PIC of 0.59, which is close to the values of the rest of the markers. Huge genetic diversity, fragmented population structure and footprints of human selection was confirmed by merging information from all marker strategies. Considering time, cost and performance HRM can be a marker of choice in future studies of Prunus diversity.

Rapid Detection of Common HIV-1 Drug Resistance Mutations by Use of High-Resolution Melting Analysis and Unlabeled Probes

HIV rapidly accumulates resistance mutations following exposure to subtherapeutic concentrations of antiretroviral drugs that reduces treatment efficacy. High-resolution melting analysis (HRMA) has been used to successfully identify single nucleotide polymorphisms (SNPs) and to genotype viral and bacterial species. Here, we tested the ability of HRMA incorporating short unlabeled probes to accurately assign drug susceptibilities at the 103, 181, and 184 codons of the HIV-1 reverse transcriptase gene. The analytical sensitivities of the HRMA assays were 5% of mixed species for K103N and Y181C and 20% for M184V. When applied to 153 HIV-1 patient specimens previously genotyped by Sanger population sequencing, HRMA correctly assigned drug sensitivity or resistance profiles to 80% of the samples at codon 103 (K103K/N) (Cohen's kappa coefficient [κ] > 0.6; P < 0.05), 90% at 181 (Y181Y/C) (κ > 0.74, P < 0.05), and 80% at 184 (M184M/V) (κ > 0.62; P < 0.05). The frequency of incorrect genotypes was very low (≤1 to 2%) for each assay, which in most cases was due to the higher sensitivity of the HRMA assay. Specimens for which drug resistance profiles could not be assigned (9 to 20%) often had polymorphisms in probe binding regions. Thus, HRMA is a rapid, inexpensive, and sensitive method for the determination of drug sensitivities caused by major HIV-1 drug resistance mutations and, after further development to minimize the melting effects of nontargeted polymorphisms, may be suitable for surveillance purposes.

System-specific periodicity in quantitative real-time polymerase chain reaction data questions threshold-based quantitation

Real-time quantitative polymerase chain reaction (qPCR) data are found to display periodic patterns in the fluorescence intensity as a function of sample number for fixed cycle number. This behavior is seen for technical replicate datasets recorded on several different commercial instruments; it occurs in the baseline region and typically increases with increasing cycle number in the growth and plateau regions. Autocorrelation analysis reveals periodicities of 12 for 96-well systems and 24 for a 384-well system, indicating a correlation with block architecture. Passive dye experiments show that the effect may be from optical detector bias. Importantly, the signal periodicity manifests as periodicity in quantification cycle (C_q) values when these are estimated by the widely applied fixed threshold approach, but not when scale-insensitive markers like first- and second-derivative maxima are used. Accordingly, any scale variability in the growth curves will lead to bias in constant-threshold-based C_qs, making it mandatory that workers should either use scale-insensitive C_qs or normalize their growth curves to constant amplitude before applying the constant threshold method.

Wide genetic variations at 18S ribosomal RNA locus of Cyclospora cayetanensis isolated from Egyptian patients using high resolution melting curve

A variable clinical picture of cyclosporiasis including gastrointestinal tract (GIT) symptomatic or asymptomatic beside extraintestinal consequences suggests a possibility of heterogenicity of Cyclospora cayetanensis. The present work aimed to explore the possibility of genetic variation of C. cayetanensis using high-resolution melting (HRM) curve of polymerase chain reaction (PCR) amplified 18S rRNA genes. DNAs extracted from the stool samples of 70 cyclosporiasis patients were amplified and scanned by PCR/HRM curve. The results showed that there are four different genotypic profiles of C. cayetanensis with presence of mixed ones. Although Tm of all profiles was within the same range, they were discerned by plotting of the temperature-shifted florescence difference between normalized melting curves (dF/dT). Genotypic profile I was found alone in 40 % of patients and mixed with genotypic profile II and/or III in 25.7 % of patients, followed by genotypic profile II in 14.3 % then genotypic profile III and IV (10 % each). A significant relation was found between genotypic profiles and GIT symptomatic status as profile I and profile II were mostly detected in patients with acute GIT symptoms without or with chronic illness, respectively, while profile IV cases only were GIT asymptomatic. Statistical significance relations between genotypic profiles and age, gender, residence and oocyst shape index were determined. In conclusion, PCR/HRM proved a wide variation on C. cayetanensis genes that could be reflected on its pathogenic effects and explaining the variability of the clinical manifestations presented by cyclosporiasis patients.

Automated Classification and Cluster Visualization of Genotypes Derived from High Resolution Melt Curves

Introduction

High Resolution Melting (HRM) following PCR has been used to identify DNA genotypes. Fluorescent dyes bounded to double strand DNA lose their fluorescence with increasing temperature, yielding different signatures for different genotypes. Recent software tools have been made available to aid in the distinction of different genotypes, but they are not fully automated, used only for research purposes, or require some level of interaction or confirmation from an analyst.

Materials and Methods

We describe a fully automated machine learning software algorithm that classifies unknown genotypes. Dynamic melt curves are transformed to multidimensional clusters of points whereby a training set is used to establish the distribution of genotype clusters. Subsequently, probabilistic and statistical methods were used to classify the genotypes of unknown DNA samples on 4 different assays (40 VKORC1, CYP2C9*2, CYP2C9*3 samples in triplicate, and 49 MTHFR c.665C>T samples in triplicate) run on the Roche LC480. Melt curves of each of the triplicates were genotyped separately.

Results

Automated genotyping called 100% of VKORC1, CYP2C9*3 and MTHFR c.665C>T samples correctly. 97.5% of CYP2C9*2 melt curves were genotyped correctly with the remaining 2.5% given a no call due to the inability to decipher 3 melt curves in close proximity as either homozygous mutant or wild-type with greater than 99.5% posterior probability.

Conclusions

We demonstrate the ability to fully automate DNA genotyping from HRM curves systematically and accurately without requiring any user interpretation or interaction with the data. Visualization of genotype clusters and quantification of the expected misclassification rate is also available to provide feedback to assay scientists and engineers as changes are made to the assay or instrument.

Rapid detection of human torque teno viruses using high-resolution melting analysis

Torque teno viruses (TTVs) are recently discovered DNA viruses, with heterogeneous genomes, highly prevalent in populations worldwide. The species that infect humans are Torque teno virus (TTV), Torque teno midi virus (TTMDV) and Torque teno mini virus (TTMV). High-resolution melting analysis (HRMA) is a sensitive and effective method for genotyping and mutation scanning. Up to now, HRMA has not been utilized for detection of TTVs. The aim of this study was to asses if HRMA is suitable for detecting TTVs variants. DNA was extracted from the blood and saliva of 13 healthy subjects for method optimization. Additionally, saliva samples from 100 healthy individuals were collected for estimating the TTVs' prevalence. Viral DNA was amplified by heminested polymerase chain reaction (PCR). Second round amplicons were used for the HRMA. The samples were analyzed using two fluorescent dyes, SYBR (®) Green I and EvaGreen®. The prevalence values for TTV, TTMDV and TTMV were 71.0, 31.0 and 54.0%, respectively. The three major melting curve patterns corresponding to TTV, TTMDV and TTMV on HRMA can be easily distinguished regardless of kit used. Our results showed that HRMA is a rapid and efficient method of detecting human TTVs.

Duplex High-Resolution Melting Assay for the Simultaneous Genotyping of IL28B rs12979860 and PNPLA3 rs738409 Polymorphisms in Chronic Hepatitis C Patients

Chronic hepatitis C (CHC) is a major burden for public health worldwide. Although newer direct-acting antivirals show good efficacy, their cost precludes their wide adoption in resource-limited regions. Thus, strategies are being developed to help identify patients with high susceptibility to response to classic PEG-interferon + ribavirin therapy. IL28B polymorphism rs12979860 C/T is an important predictor for an efficient response to interferon-based therapy. A genetic variant in adiponutrin (PNPLA3) gene, rs738409 C/G, is associated with steatosis, severity, and progression of liver fibrosis in CHC patients, and predicts treatment outcome in difficult-to-cure HCV-infected patients with advanced fibrosis. We developed a rapid and inexpensive assay based on duplex high-resolution melting (HRM) for the simultaneous genotyping of these two polymorphisms. The assay validation was performed on synthetic DNA templates and 132 clinical samples from CHC patients. When compared with allele-specific PCR and sequencing, our assay showed 100% (95% CI: 0.9724-1) accuracy, with 100% sensitivity and specificity. Our assay was robust against concentration and quality of DNA samples, melting curve normalization intervals, HRM analysis algorithm, and sequence variations near the targeted SNPs (single nucleotide polymorphism). This duplex assay should provide useful information for patient-oriented management and clinical decision-making in CHC.

PanGen-Fam: Spanish registry of hereditary pancreatic cancer

PURPOSE

To describe the organisation of the registry and the preliminary results in terms of characteristics of high-risk pancreatic ductal adenocarcinoma (PDAC) families recruited to date and findings of the screening programme. To compare early onset sporadic cases (⩽50 years), sporadic cases (>50 years) and cases with family history of cancer, for PDAC possible risk factors.

METHODS/PATIENTS

Families with hereditary cancer syndromes predisposing to PDAC were recruited from two main sources: Spanish hospitals participating in PanGenEU, a pan-European multicentre case-control study, and their genetic counseling unit. Individuals at high-risk of PDAC were enrolled into a screening programme, consisting of Endoscopic ultrasound, computerised tomography, magnetic resonance imaging. Genetic testing of candidate genes was offered according to each patient's risk.

RESULTS

Among 577 consecutive PDAC cases, recruited via PanGenEU, 36 (6%) had ⩾2 first-degree relative with PDAC: Familial pancreatic cancer (FPC). So far PanGen-Fam has recruited 42 high-risk PDAC families; 25 (60%) had FPC. Five index cases with cancer were positive for BRCA2 and one for BRCA1 germline mutations. In the second year of prospective PDAC screening, one neuroendocrine tumour and a high-grade dysplasia lesion suspicious of carcinoma were diagnosed among 41 high-risk individuals. Furthermore EUS detected chronic-pancreatitis-like parenchymal changes in 15 patients.

CONCLUDING STATEMENT

The identification and recruitment of PDAC high-risk families into the PanGen-Fam registry provides an opportunity to detect early onset cancer and precursor pancreatic cancer lesions at a potentially curative stage and to increase the knowledge of the natural history of the disease.

Improving qPCR telomere length assays: Controlling for well position effects increases statistical power

OBJECTIVES

Telomere length (TL) is commonly measured using quantitative PCR (qPCR). Although, easier than the southern blot of terminal restriction fragments (TRF) TL measurement method, one drawback of qPCR is that it introduces greater measurement error and thus reduces the statistical power of analyses. To address a potential source of measurement error, we consider the effect of well position on qPCR TL measurements.

METHODS

qPCR TL data from 3,638 people run on a Bio-Rad iCycler iQ are reanalyzed here. To evaluate measurement validity, correspondence with TRF, age, and between mother and offspring are examined.

RESULTS

First, we present evidence for systematic variation in qPCR TL measurements in relation to thermocycler well position. Controlling for these well-position effects consistently improves measurement validity and yields estimated improvements in statistical power equivalent to increasing sample sizes by 16%. We additionally evaluated the linearity of the relationships between telomere and single copy gene control amplicons and between qPCR and TRF measures. We find that, unlike some previous reports, our data exhibit linear relationships. We introduce the standard error in percent, a superior method for quantifying measurement error as compared to the commonly used coefficient of variation. Using this measure, we find that excluding samples with high measurement error does not improve measurement validity in our study.

CONCLUSIONS

Future studies using block-based thermocyclers should consider well position effects. Since additional information can be gleaned from well position corrections, rerunning analyses of previous results with well position correction could serve as an independent test of the validity of these results.

A handheld flow genetic analysis system (FGAS): towards rapid, sensitive, quantitative and multiplex molecular diagnosis at the point-of-care level

A handheld flow genetic analysis system (FGAS) is proposed for rapid, sensitive, multiplex and real-time quantification of nucleic acids at the point-of-care (POC) level. The FGAS includes a helical thermal-gradient microreactor and a microflow actuator, as well as control circuitry for temperature, fluid and power management, and smartphone fluorescence imaging. All of these features are integrated into a field-portable and easy-to-use molecular diagnostic platform powered by lithium batteries. Due to the unique design of the microreactor, not only steady temperatures for denaturation and annealing/extension but also a linear thermal gradient for spatial high-resolution melting can be achieved through simply maintaining a single heater at constant temperature. The smartphone fluorescence imaging system has a wide field of view that captures all PCR channels of the microreactor in a single snapshot without the need for any mechanical scanning. By these designs, the FGAS enables real-time monitoring of the temporal and spatial fluorescence signatures of amplicons during continuous-flow amplification. On the current FGAS, visual detection of as little as 10 copies per μL of genomic DNA of Salmonella enterica was achieved in 15 min, with real-time quantitative detection of the DNA over 6 orders of magnitude concentration from 10(6) to 10(1) copies per μL also completed in 7.5-15 min. In addition, multiple pathogenic DNA targets could be simultaneously discriminated with direct bar-chart readout or multiplex spatial melting in serial flow. We anticipate that the FGAS has great potential to become a next-generation gene analyzer for POC molecular diagnostics.

Cancer mutation screening: Comparison of high-resolution melt analysis between two platforms

High-resolution melt analysis (HRMA) is a cheap and reliable post-polymerase chain reaction (PCR) cancer mutation screening technique, which is fast gaining clinical relevance. The HRMA capabilities of the LightScanner (Idaho Technology) have been severally studied. However, the ABI 7500 HRM has not been tested against the purpose-built HRM instrument such as the LightScanner.

DNA from formalin-fixed, paraffin-embedded gastric cancer, colorectal cancer, and normal tissue as well as from colorectal cancer cell lines were amplified at exons 2, 3, and 4 of KRAS, and at exons 11 and 15 of BRAF in the ABI 7500 fast real-time PCR machine and subjected to melting both on the ABI and on the LightScanner. HRMA data were analysed with the ABI HRM software v2.0.1 and the LightScanner Call-IT 2.5. We tested the ABI 7500 HRM for internal precision, accuracy, sensitivity, and specificity at mutation screening relative to the LightScanner, using crude percentage concordance, kappa statistics, and the area under the receiver operator characteristics (AUROC) curve on SPSS version 19.

The results show that the ABI 7500 HRMA has a high internal precision, and excellent concordance, sensitivity, and specificity at mutation screening compared with the LightScanner. However, in contrast to the LightScanner HRM software analysis, the ABI HRM software v.2.0.1, cannot distinguish real from certain pseudovariations in PCR amplicons that are sometimes brought about by the artefacts of the melting process.

In conclusion, the ABI HRM has a comparable performance level with the LightScanner, although in certain respects mentioned previously, the LightScanner has an edge over the ABI.

Comparison of different DNA binding fluorescent dyes for applications of high-resolution melting analysis

OBJECTIVES

Different applications of high-resolution melting (HRM) analysis have been adopted for a wide range of research and clinical applications. This study compares the performance of selected DNA binding fluorescent dyes for their possible application in HRM.

DESIGN AND METHODS

We compared twelve dyes with basic properties considered relevant for PCR amplification and melting curve analysis. These included PCR inhibition, fluorescence intensity, the ability to generate melting curves and their effect on melting temperature (Tm). Seven of these dyes with promising properties were then evaluated for possible use in basic HRM applications; such as small amplicon genotyping, genotyping of a 1 kb insertion/deletion polymorphism, probe-based genotyping and mutation screening.

RESULTS

Five dyes failed to exhibit promising properties during the first part of the study, and these were excluded from further testing. Of the remaining dyes, SYTO11, SYTO13 and SYTO16 showed better PCR inhibitory and Tm affecting properties compared to commercial HRM dyes LCGreen Plus, EvaGreen and ResoLight. Although the SYTO dyes generally exhibited good discrimination powers in HRM applications, SYTO11 and SYTO14 gave low signal intensity and lower quality results.

CONCLUSIONS

Our results suggest that the best performing dyes for HRM are those commercially offered for HRM analyses. However, the performance of SYTO16 and SYTO13 was comparable to the HRM dyes in the majority of our assays, thus demonstrating that they are also quite suitable for both real-time PCR and HRM applications.

High-resolution melt analysis for rapid comparison of bacterial community compositions

In the study of bacterial community composition, 16S rRNA gene amplicon sequencing is today among the preferred methods of analysis. The cost of nucleotide sequence analysis, including requisite computational and bioinformatic steps, however, takes up a large part of many research budgets. High-resolution melt (HRM) analysis is the study of the melt behavior of specific PCR products. Here we describe a novel high-throughput approach in which we used HRM analysis targeting the 16S rRNA gene to rapidly screen multiple complex samples for differences in bacterial community composition. We hypothesized that HRM analysis of amplified 16S rRNA genes from a soil ecosystem could be used as a screening tool to identify changes in bacterial community structure. This hypothesis was tested using a soil microcosm setup exposed to a total of six treatments representing different combinations of pesticide and fertilization treatments. The HRM analysis identified a shift in the bacterial community composition in two of the treatments, both including the soil fumigant Basamid GR. These results were confirmed with both denaturing gradient gel electrophoresis (DGGE) analysis and 454-based 16S rRNA gene amplicon sequencing. HRM analysis was shown to be a fast, high-throughput technique that can serve as an effective alternative to gel-based screening methods to monitor microbial community composition.

From genes to markers: exploiting gene sequence information to develop tools for plant breeding

Once the sequence is known for a gene of interest, it is usually possible to design markers to detect polymorphisms within the gene. Such markers can be particularly useful in plant breeding, especially if they detect the causal polymorphism within the gene and are diagnostic of the phenotype. In this chapter, we (1) discuss how gene sequences are obtained and aligned and how polymorphic sites can be identified or predicted; (2) explain the principles of PCR primer design and PCR amplification and provide guidelines for their application in the design and testing of markers; (3) discuss detection methods for presence/absence (dominant) polymorphisms, length polymorphisms and single nucleotide polymorphisms (SNPs); and (4) outline some of the factors that affect the utility of markers in plant breeding and explain how markers can be evaluated (validated) for use in plant breeding.

Telomere length measurement on the Roche LightCycler 480 Platform

BACKGROUND

The average length of telomeres as measured in genomic DNA from human peripheral blood leukocytes is proving to be a potential biomarker of great interest, particularly with respect to studies of aging, specific diseases, and the effects of various stresses on overall health.

AIMS

The aim of this study was to establish an effective real-time quantitative polymerase chain reaction (qPCR) method for telomere length measurement on the Roche LightCycler® 480 (LC480) real-time PCR platform.

METHODS

Measurement of relative average telomere length was achieved by comparing products amplified from telomere-specific primers and single copy reference gene primers in a ratio (T/S).

RESULTS

Extensive testing led us to conclude that a modification of the original two-plate T/S assay was more compatible with this platform than the recently developed single-plate assay, and that choice of hot-start Taq polymerase and intercalating dye were critical factors.

CONCLUSIONS

This modified assay generates reliable measurements as judged by correlation with data derived by the telomeric restriction fragment Southern blot-based method.

Microfluidic Genotyping by Rapid Serial PCR and High-Speed Melting Analysis

BACKGROUND

Clinical molecular testing typically batches samples to minimize costs or uses multiplex lab-on-a-chip disposables to analyze a few targets. In genetics, multiple variants need to be analyzed, and different work flows that rapidly analyze multiple loci in a few targets are attractive.

METHODS

We used a microfluidic platform tailored to rapid serial PCR and high-speed melting (HSM) to genotype 4 single nucleotide variants. A contiguous stream of master mix with sample DNA was pulsed with each primer pair for serial PCR and melting. Two study sites each analyzed 100 samples for F2 (c.*97G&gt;A), F5 (c.1601G&gt;A), and MTHFR (c.665C&gt;T and c.1286A&gt;C) after blinding for genotype and genotype proportions. Internal temperature controls improved melting curve precision. The platform's liquid-handling system automated PCR and HSM.

RESULTS

PCR and HSM were completed in a total of 12.5 min. Melting was performed at 0.5 °C/s. As expected, homozygous variants were separated by melting temperature, and heterozygotes were identified by curve shape. All samples were correctly genotyped by the instrument. Follow-up testing was required on 1.38% of the assays for a definitive genotype.

CONCLUSIONS

We demonstrate genotyping accuracy on a novel microfluidic platform with rapid serial PCR and HSM. The platform targets short turnaround times for multiple genetic variants in up to 8 samples. It is also designed to allow automatic and immediate reflexive or repeat testing depending on results from the streaming DNA. Rapid serial PCR provides a flexible genetic work flow and is nicely matched to HSM analysis.

A comparison of two measures of HIV diversity in multi-assay algorithms for HIV incidence estimation

BACKGROUND

Multi-assay algorithms (MAAs) can be used to estimate HIV incidence in cross-sectional surveys. We compared the performance of two MAAs that use HIV diversity as one of four biomarkers for analysis of HIV incidence.

METHODS

Both MAAs included two serologic assays (LAg-Avidity assay and BioRad-Avidity assay), HIV viral load, and an HIV diversity assay. HIV diversity was quantified using either a high resolution melting (HRM) diversity assay that does not require HIV sequencing (HRM score for a 239 base pair env region) or sequence ambiguity (the percentage of ambiguous bases in a 1,302 base pair pol region). Samples were classified as MAA positive (likely from individuals with recent HIV infection) if they met the criteria for all of the assays in the MAA. The following performance characteristics were assessed: (1) the proportion of samples classified as MAA positive as a function of duration of infection, (2) the mean window period, (3) the shadow (the time period before sample collection that is being assessed by the MAA), and (4) the accuracy of cross-sectional incidence estimates for three cohort studies.

RESULTS

The proportion of samples classified as MAA positive as a function of duration of infection was nearly identical for the two MAAs. The mean window period was 141 days for the HRM-based MAA and 131 days for the sequence ambiguity-based MAA. The shadows for both MAAs were <1 year. Both MAAs provided cross-sectional HIV incidence estimates that were very similar to longitudinal incidence estimates based on HIV seroconversion.

CONCLUSIONS

MAAs that include the LAg-Avidity assay, the BioRad-Avidity assay, HIV viral load, and HIV diversity can provide accurate HIV incidence estimates. Sequence ambiguity measures obtained using a commercially-available HIV genotyping system can be used as an alternative to HRM scores in MAAs for cross-sectional HIV incidence estimation.

Genotyping Accuracy of High-Resolution DNA Melting Instruments

BACKGROUND

High-resolution DNA melting is a closed-tube method for genotyping and variant scanning that depends on the thermal stability of PCR-generated products. Instruments vary in thermal precision, sample format, melting rates, acquisition, and software. Instrument genotyping accuracy has not been assessed.

METHODS

Each genotype of the single nucleotide variant (SNV) (c.3405–29A&gt;T) of CPS1 (carbamoyl-phosphate synthase 1, mitochondrial) was amplified by PCR in the presence of LCGreen Plus with 4 PCR product lengths. After blinding and genotype randomization, samples were melted in 10 instrument configurations under conditions recommended by the manufacturer. For each configuration and PCR product length, we analyzed 32–96 samples (depending on batch size) with both commercial and custom software. We assessed the accuracy of heterozygote detection and homozygote differentiation of a difficult, nearest-neighbor symmetric, class 4 variant with predicted ΔTm of 0.00 °C.

RESULTS

Overall, the heterozygote accuracy was 99.7% (n = 2141), whereas homozygote accuracy was 70.3% (n = 4441). Instruments with single sample detection as opposed to full-plate imaging better distinguished homozygotes (78.1% and 61.8%, respectively, χ2P &lt; 0.0005). Custom software improved accuracy over commercial software (P &lt; 0.002), although melting protocols recommended by manufacturers were better than a constant ramp rate of 0.1 °C with an oil overlay. PCR products of 51, 100, 272, and 547 bp had accuracies of 72.3%, 83.1%, 59.8%, and 65.9%, respectively (P &lt; 0.0005).

CONCLUSIONS

High-resolution melting detects heterozygotes with excellent accuracy, but homozygote accuracy is dependent on detection mode, analysis software, and PCR product size, as well as melting temperature differences between, and variation within, homozygotes.

Process evaluation of an open architecture real-time molecular laboratory platform

The needs of molecular diagnostic laboratories that perform both Food and Drug Administration-cleared as well as laboratory-developed tests are usually not met on a single analytical platform. Furthermore, little information is available about the direct impact of molecular automation on labor costs and efficiency in clinical laboratories. We performed a process impact analysis from time and motion studies of a novel molecular diagnostic robotic system designed to automate sample preparation, extraction, and analysis. All 27 preanalytical tasks were quantified for the amount of time spent preparing 24 specimens for analysis. These steps were completed in 899 s (14 min, 59 s) followed by 7887 s (131 min, 27 s) of instrument operation independent of operator control (walk-away time). Postanalytical results evaluation required 1 min per specimen. The instrument automatically extracted the nucleic acid from the specimen, added the eluted DNA to the amplification reagents, and performed the analysis. Only 12% of the total instrument operations required relatively unskilled human labor. Thus, the availability of automated molecular diagnostic instruments will facilitate the expansion of molecular testing in the clinical laboratory because they reduce operator costs with respect to time and complexity of the tasks they are asked to perform.

Rapid and efficient zebrafish genotyping using PCR with high-resolution melt analysis

Zebrafish is a powerful vertebrate model system for studying development, modeling disease, and performing drug screening. Recently a variety of genetic tools have been introduced, including multiple strategies for inducing mutations and generating transgenic lines. However, large-scale screening is limited by traditional genotyping methods, which are time-consuming and labor-intensive. Here we describe a technique to analyze zebrafish genotypes by PCR combined with high-resolution melting analysis (HRMA). This approach is rapid, sensitive, and inexpensive, with lower risk of contamination artifacts. Genotyping by PCR with HRMA can be used for embryos or adult fish, including in high-throughput screening protocols.

HIV diversity as a biomarker for HIV incidence estimation: including a high-resolution melting diversity assay in a multiassay algorithm

Multiassay algorithms (MAAs) can be used to estimate cross-sectional HIV incidence. We previously identified a robust MAA that includes the BED capture enzyme immunoassay (BED-CEIA), the Bio-Rad Avidity assay, viral load, and CD4 cell count. In this report, we evaluated MAAs that include a high-resolution melting (HRM) diversity assay that does not require sequencing. HRM scores were determined for eight regions of the HIV genome (2 in gag, 1 in pol, and 5 in env). The MAAs that were evaluated included the BED-CEIA, the Bio-Rad Avidity assay, viral load, and the HRM diversity assay, using HRM scores from different regions and a range of region-specific HRM diversity assay cutoffs. The performance characteristics based on the proportion of samples that were classified as MAA positive by duration of infection were determined for each MAA, including the mean window period. The cross-sectional incidence estimates obtained using optimized MAAs were compared to longitudinal incidence estimates for three cohorts in the United States. The performance of the HRM-based MAA was nearly identical to that of the MAA that included CD4 cell count. The HRM-based MAA had a mean window period of 154 days and provided cross-sectional incidence estimates that were similar to those based on cohort follow-up. HIV diversity is a useful biomarker for estimating HIV incidence. MAAs that include the HRM diversity assay can provide accurate HIV incidence estimates using stored blood plasma or serum samples without a requirement for CD4 cell count data.

Conserved synteny-based anchoring of the barley genome physical map

Gene order is largely collinear in the small-grained cereals, a feature which has proved helpful in both marker development and positional cloning. The accuracy of a virtual gene order map ("genome zipper") for barley (Hordeum vulgare), developed by combining a genetic map of this species with a large number of gene locations obtained from the maps constructed in other grass species, was evaluated here both at the genome-wide level and at the fine scale in a representative segment of the genome. Comparing the whole genome "genome zipper" maps with a genetic map developed by using transcript-derived markers, yielded an accuracy of >94 %. The fine-scale comparison involved a 14 cM segment of chromosome arm 2HL. One hundred twenty-eight genes of the "genome zipper" interval were analysed. Over 95 % (45/47) of the polymorphic markers were genetically mapped and allocated to the expected region of 2HL, following the predicted order. A further 80 of the 128 genes were assigned to the correct chromosome arm 2HL by analysis of wheat-barley addition lines. All 128 gene-based markers developed were used to probe a barley bacterial artificial chromosome (BAC) library, delivering 26 BAC contigs from which all except two were anchored to the targeted zipper interval. The results demonstrate that the gene order predicted by the "genome zipper" is remarkably accurate and that the "genome zipper" represents a highly efficient informational resource for the systematic identification of gene-based markers and subsequent physical map anchoring of the barley genome.

Conserved synteny-based anchoring of the barley genome physical map

Gene order is largely collinear in the small-grained cereals, a feature which has proved helpful in both marker development and positional cloning. The accuracy of a virtual gene order map ("genome zipper") for barley (Hordeum vulgare), developed by combining a genetic map of this species with a large number of gene locations obtained from the maps constructed in other grass species, was evaluated here both at the genome-wide level and at the fine scale in a representative segment of the genome. Comparing the whole genome "genome zipper" maps with a genetic map developed by using transcript-derived markers, yielded an accuracy of >94 %. The fine-scale comparison involved a 14 cM segment of chromosome arm 2HL. One hundred twenty-eight genes of the "genome zipper" interval were analysed. Over 95 % (45/47) of the polymorphic markers were genetically mapped and allocated to the expected region of 2HL, following the predicted order. A further 80 of the 128 genes were assigned to the correct chromosome arm 2HL by analysis of wheat-barley addition lines. All 128 gene-based markers developed were used to probe a barley bacterial artificial chromosome (BAC) library, delivering 26 BAC contigs from which all except two were anchored to the targeted zipper interval. The results demonstrate that the gene order predicted by the "genome zipper" is remarkably accurate and that the "genome zipper" represents a highly efficient informational resource for the systematic identification of gene-based markers and subsequent physical map anchoring of the barley genome.

Usefulness of PCR-HRMA in identification of non-fermentative Gram-negative rods recovered from patients suffering from cystic fibrosis or chronic obstructive pulmonary disease

Adequate treatment of microbial infections requires rapid and accurate identification of the etiological agent. In routine diagnostics, identification of bacteria conventionally relies on phenotypic testing, which can be hindered by phenotypic variations. Therefore, genotyping techniques should perform faster and more accurately. Recently, the technique of high-resolution melting analysis (HRMA) of PCR amplicons promises to provide a convenient and economic tool of genotypic identification. In our study, we performed prospective routine testing of a PCR-HRMA system that was recently published in a proof-of-the-principle study. The system was evaluated by analysing 275 clinical isolates of bacteria acquired from 65 patients suffering from cystic fibrosis or chronic obstructive pulmonary disease. Our results show that its routine use may result in partial worsening of its discriminatory power; however, it still outmatched conventional phenotyping in the group of non-fermentative Gram-negative rods. Moreover, when supplemented by rapid, simple and economic oxidase test, it can be even simplified for more economic performance.

High resolution melting analysis is a more sensitive and effective alternative to gel-based platforms in analysis of SSR--an example in citrus

High resolution melting curve analysis (HRM) has been used as an efficient, accurate and cost-effective tool to detect single nucleotide polymorphisms (SNPs) or insertions or deletions (INDELs). However, its efficiency, accuracy and applicability to discriminate microsatellite polymorphism have not been extensively assessed. The traditional protocols used for SSR genotyping include PCR amplification of the DNA fragment and the separation of the fragments on electrophoresis-based platform. However, post-PCR handling processes are laborious and costly. Furthermore, SNPs present in the sequences flanking repeat motif cannot be detected by polyacrylamide-gel-electrophoresis based methods. In the present study, we compared the discriminating power of HRM with the traditional electrophoresis-based methods and provided a panel of primers for HRM genotyping in Citrus. The results showed that sixteen SSR markers produced distinct polymorphic melting curves among the Citrus spp investigated through HRM analysis. Among those, 10 showed more genotypes by HRM analysis than capillary electrophoresis owing to the presence of SNPs in the amplicons. For the SSR markers without SNPs present in the flanking region, HRM also gave distinct melting curves which detected same genotypes as were shown in capillary electrophoresis (CE) analysis. Moreover, HRM analysis allowed the discrimination of most of the 15 citrus genotypes and the resulting genetic distance analysis clustered them into three main branches. In conclusion, it has been approved that HRM is not only an efficient and cost-effective alternative of electrophoresis-based method for SSR markers, but also a method to uncover more polymorphisms contributed by SNPs present in SSRs. It was therefore suggested that the panel of SSR markers could be used in a variety of applications in the citrus biodiversity and breeding programs using HRM analysis. Furthermore, we speculate that the HRM analysis can be employed to analyse SSR markers in a wide range of applications in all other species.

High-resolution melting analysis: a genotyping tool for population studies on Daphnia

Determining genetic variation at the DNA level within and between natural populations is important for understanding the role of natural selection on phenotypic traits, but many techniques of screening for genetic variation are either cost intensive, not sensitive enough or too labour- and time-consuming. Here, we demonstrate high-resolution melting analysis (HRMA) as a cost-effective and powerful tool for screening variable target genes in natural populations. HRMA is based on monitoring the melting of PCR amplicons. Owing to saturating concentrations of a dye that binds at high concentrations to double-stranded DNA, it is possible to genotype high numbers of samples rapidly and accurately. We analysed digestive trypsins of two Daphnia magna populations as an application example for HRMA. One population originated from a pond containing toxic cyanobacteria that possibly produce protease inhibitors and the other from a pond without such cyanobacteria. The hypothesis was that D. magna clones from ponds with cyanobacteria have undergone selection by these inhibitors, which has led to different trypsin alleles. We first sequenced pooled genomic PCR products of trypsins from both populations to identify variable DNA sequences of active trypsins. Second, we screened variable DNA sequences of each D. magna clone from both populations for single nucleotide polymorphisms via HRMA. The HRMA results revealed that both populations exhibited phenotypic differences in the analysed trypsins. Our results indicate that HRMA is a powerful genotyping tool for studying the variation of target genes in response to selection within and between natural Daphnia populations.