High-Resolution Melting (HRM) analysis of DNA methylation using semiconductor chip-based digital PCR.

BACKGROUND: Digital PCR (dPCR) technology allows absolute quantification and detection of disease-associated rare variants, and thus the use of dPCR technology has been increasing in clinical research and diagnostics. The high-resolution melting curve analysis (HRM) of qPCR is widely used to distinguish true positives from false positives and detect rare variants. In particular, qPCR-HRM is commonly used for methylation assessment in research and diagnostics due to its simplicity and high reproducibility. Most dPCR instruments have limited fluorescence channels available and separate heating and imaging systems. Therefore, it is difficult to perform HRM analysis using dPCR instruments. OBJECTIVE: A new digital real-time PCR instrument (LOAA) has been recently developed to integrate partitioning, thermocycling, and imaging in a single dPCR instrument. In addition, a new technique to perform HRM analysis is utilized in LOAA. The aim of the present study is to evaluate the efficiency and accuracy of LOAA dPCR on HRM analysis for the detection of methylation. METHODS: In this study, comprehensive comparison with Bio-Rad qRT-PCR and droplet-based dPCR equipment was performed to verify the HRM analysis-based methylation detection efficiency of the LOAA digital PCR equipment. Here, sodium bisulfite modification method was applied to detect methylated DNA sequences by each PCR method. RESULTS: Melting curve analysis detected four different Tm values using LOAA and qPCR, and found that LOAA, unlike qPCR, successfully distinguished between different Tm values when the Tm values were very similar. In addition, melting temperatures increased by each methylation were about 0.5℃ for qPCR and about 0.2 ~ 0.6℃ for LOAA. The melting temperature analyses of methylated and unmethylated DNA samples were conducted using LOAA dPCR with TaqMan probes and EvaGreen, and the result found that Tm values of methylated DNA samples are higher than those of unmethylated DNA samples. CONCLUSION: The present study shows that LOAA dPCR could detect different melting temperatures according to methylation status of target sequences, indicating that LOAA dPCR would be useful for diagnostic applications that require the accurate quantification and assessment of DNA methylation.

High-resolution melting (HRM)-based detection of polymorphisms in the malic enzyme and glucose-6-phosphate isomerase genes for Leishmania infantum genotyping.

BACKGROUND: Leishmaniasis is a zoonotic disease endemic in the Mediterranean region where Leishmania infantum is the causative agent of human and canine infection. Characterization of this parasite at the subspecies level can be useful in epidemiological studies, to evaluate the clinical course of the disease (e.g. resistant strains, visceral and cutaneous forms of leishmaniasis) as well as to identify infection reservoirs. Multilocus enzyme electrophoresis (MLEE), a method currently recognized as the reference method for characterizing and identifying strains of Leishmania, is cumbersome and time-consuming and requires cultured parasites. These disadvantages have led to the development of other methods, such as multilocus microsatellite typing (MLMT) and multilocus sequence typing (MLST), for typing Leishmania parasites; however, these methods have not yet been applied for routine use. In this study, we first used MLST to identify informative polymorphisms on single-copy genes coding for metabolic enzymes, following which we developed two rapid genotyping assays based on high-resolution melting (HRM) analysis to explore these polymorphisms in L. infantum parasites. METHODS: A customized sequencing panel targeting 14 housekeeping genes was designed and MLST analysis was performed on nine L. infantum canine and human strains/isolates. Two quantitative real-time PCR-HRM assays were designed to analyze two informative polymorphisms on malic enzyme (ME) and glucose-6-phosphate isomerase (GPI) genes (390T/G and 1831A/G, respectively). The two assays were applied to 73 clinical samples/isolates from central/southern Italy and Pantelleria island, and the results were confirmed by DNA sequencing in a subset of samples. RESULTS: The MLST analysis, together with sequences available in the Genbank database, enabled the identification of two informative polymorphisms on the genes coding for ME and GPI. The fast screening of these polymorphisms using two HRM-based assays in 73 clinical samples/isolates resulted in the identification of seven genotypes. Overall, genotype 1 (sequence type 390T/1831G) was the most highly represented (45.2%) in the overall sample and correlated with the most common L. infantum zymodemes (MON-1, MON-72). Interestingly, in Pantelleria island, the most prevalent genotype (70.6%) was genotype 6 (sequence type 390T/1831A). CONCLUSIONS: Applying our HRM assays on clinical samples allowed us to identify seven different genotypes without the need for parasite isolation and cultivation. We have demonstrated that these assays could be used as fast, routine and inexpensive tools for epidemiological surveillance of L. infantum or for the identification of new infection reservoirs.

Modified High-Resolution Melting (HRM) Marker Systems Increasing Discriminability Between Homozygous Alleles.

Targeted single-nucleotide polymorphism (SNP) genotyping, especially for functional nucleotide polymorphism, is widely used for current breeding programs in crops. One of the cost- and time-effective approaches for genotyping is high-resolution melting (HRM) analysis for polymerase chain reaction (PCR) amplicons, including target SNP. The reliability of a genotype obtained from an HRM marker depends on the difference in Tm values between two amplicons. Increasing the reliability of HRM marker genotypes could be archived with the selection of the best nearest neighboring nucleotide substitution (NNNs) in primer sequences surrounding SNPs. This chapter provides an easy-way protocol to design primer sequences for NNNs-HRM markers with table and web service, as well as several tips to develop HRM markers that distinguish between homozygous alleles (e.g., between A/A and C/C).

Multiple region high resolution melting-based method for accurate differentiation of food-derived yeasts at species level resolution.

Yeasts comprise a divergent group of microorganisms playing an important role in foods production. To monitor the production processes, validate authenticity and safety of foods, reliable methods of yeast identification and differentiation are needed. Nowadays, traditional PCR/sequencing-based methods are replaced by rapid techniques not requiring post-PCR processing. In the present study, we developed a three region-based qPCR-HRM protocol, for rapid differentiation of yeast species isolated from food products. The three targeted fragments (26S rDNA, 18S rDNA, ITS) were carefully analyzed to dock the primers at inter-species conservative regions, flanking polymorphic regions of ∼200 bp. Thirty eight yeast strains were used as a training material. The collection of yeast spanned Pichia, Clavispora, Candida, Yarrowia, Kluyveromyces, Saccharomyces, and Wickerhamomyces genera. MALDI-TOF mass spectrometry and conventional rDNA sequencing were used for validation. Conducted studies demonstrated that when used individually, each of the three regions analyzed by qPCR-HRM possessed its own yeast species-specific limitations, sometimes leading to inaccurate taxonomic classification. On the other hand, simultaneous analysis of the three proposed regions resulted in rapid and adequate differentiation of all the yeast strains at species-level resolution.

A novel real-time PCR coupled with high resolution melting analysis as a simple and fast tool for the entomological authentication of honey by targeting Apis mellifera mitochondrial DNA.

Honey is one of the foods easily adulterated worldwide. Recently, the analysis of honeybee DNA has been proposed as a useful tool to authenticate the entomological origin of honey. However, the methods proposed so far require more than one polymerase chain reaction (PCR) and the use of agarose gels, making the authentication process laborious and lengthy. In this work, a novel real-time PCR coupled with high-resolution melting (HRM) analysis of a 150 bp fragment of the cytochrome c oxidase I (COI) gene is proposed as a fast and simple tool to assess honey's entomological origin by discriminating the mitochondrial DNA lineages of European honey bees (A, M and C lineages). In addition, the new tool allowed the differentiation of honeys produced by different mitotypes of C-lineage ancestry. The method showed high analytical performance and was able to successfully identify the entomological origin of honeys of known origin obtained from research apiaries/beekeepers. Therefore, it was applied to 44 commercial honeys from different countries. It confirmed the entomological authenticity of French PDO honeys that should be produced by the Corse ecotype A. m. mellifera. For the remaining honeys, the results were also in good agreement with the declared geographical origin. However, three honeys from Slovenia did not cluster with C2 mitotype A. m. carnica as expected, suggesting the mixture of honeys produced by honeybees of different mitotypes.

Bacillus anthracis strain differentiation based on SNP and VNTR loci.

Bacillus anthracis is the anthrax causative agent. For its epidemiology, it is important not only to identify the etiological agent but also to determine the patterns of its evolution and spread. Modern methods of molecular biology make it possible to detect a number of genetic markers suitable for indicating and differentiating the strains of B. anthracis, including the loci arranged as variable number tandem repeats (VNTRs) and SNPs, one nucleotide-sized differences in the DNA sequence of the loci being compared. The objective of the present study was to examine the effectiveness of SNP analysis and PCR amplif ication of VNTR loci combined with the high-resolution amplicon melting analysis for identif ication and differentiation of the anthrax agent strains. In the study, seven strains of B. anthracis obtained from soil samples and animal carcasses were investigated using vaccine strain STI-1 as a reference. For molecular genetic characterization of these bacteria, analysis of 12 SNPs and variability analysis of eight VNTR loci were carried out. To detect the differences between the strains, their PCR product melting points were measured in the presence of the EvaGreen (Sintol, Russia) intercalating dye. For SNP detection, a PCR assay with double TaqMan probes was applied. It was found that the studied virulent strains, except for B. anthracis No. 1 and 3, could not be attributed to any phylogenetic subgroup of the anthrax agents. The proposed method made it possible to differentiate four out of the seven investigated strains. Strains No. 5-7 had identical SNP and HRM prof iles and, as a result, formed a single cluster. Our investigation has conf irmed that the proposed method can be successfully used for preliminary analysis of an epizootic situation in the case of anthrax.

Specific Detection of Pseudomonas savastanoi Pathovars: From End-Point PCR to Real-Time PCR and HRMA.

Pseudomonas savastanoi is a phytopathogenic bacterium causing severe disease on olive, oleander, ash, and other Oleaceae. Three main pathovars belong to this species: P. savastanoi pv. savastanoi, pv. nerii, and pv. fraxini. Detection methods are mostly based on the visual inspection of the typical symptoms (i.e., knots and galls). However, this bacterium can survive on the host plant also as an epiphyte without giving any symptom. To avoid the spread of P. savastanoi to areas where it is absent, it is necessary to develop efficient and sensitive detection methods. Here, we reported three different PCR-based techniques, able to discriminate the three P. savastanoi pathovars attacking woody plants.

High-resolution melting analysis to discriminate between the SARS-CoV-2 Omicron variants BA.1 and BA.2.

High-resolution melting (HRM) analysis was conducted to discriminate between SARS-CoV-2 Omicron variant BA.1 (B.1.1.529.1) and subvariant BA.2 (B.1.1.529.2). We performed two-step PCR consisting of the first PCR and the second nested PCR to prepare the amplicon for HRM analysis, which detected G339D, N440K, G446S and D796Y variations in the SARS-CoV-2 spike protein. The melting temperatures (Tms) of the amplicons from the cDNA of the Omicron variant BA.1 and subvariant BA.2 receptor binding domain (RBD) in spike protein were the same: 75.2 °C (G339D variation) and 73.4 °C (D796Y variation). These Tms were distinct from those of SARS-CoV-2 isolate Wuhan-Hu-1, and were specific to the Omicron variant. In HRM analyses that detected the N440K and G446S variations, the Tms of amplicons from the cDNA of the Omicron variant BA.1 and subvariant BA.2 RBDs were 73.0 °C (N440K and G446S variations) and 73.5 °C (G446S variation). This difference indicates that the SARS-CoV-2 Omicron variants BA.1 and BA.2 can be clearly discriminated. Our study demonstrates the usefulness of HRM analysis after two-step PCR for the discrimination of SARS-CoV-2 variants.

High-resolution melting analysis after nested PCR for the detection of SARS-CoV-2 spike protein G339D and D796Y variations.

High-resolution melting (HRM) analysis was performed to detect G339D and D796Y variations in the SARS-CoV-2 Omicron variant spike protein. We employed two-step PCR consisting of the first RT-PCR and the second nested PCR to prepare the amplicon for HRM analysis. The melting temperatures (Tm) of the amplicon from the cDNA of the Omicron variant receptor binding domain (RBD) were 73.1 °C (G339D variation) and 75.1 °C (D796Y variation), respectively. These Tm values were clearly distinct from those of SARS-CoV-2 isolate Wuhan-Hu-1. HRM analysis after the two-step PCR was conducted on Omicron variant-positive specimens. The HRM curve and Tm value obtained with the Omicron variant-positive specimen were coincident with those of the amplicon from cDNA of the Omicron variant RBD. Our study demonstrates the utility of HRM analysis after two-step PCR for the detection of mutations in SARS-CoV-2 gene.

Combining Protein Expression and Molecular Data Improves Mutation Characterization of Dystrophinopathies.

Duchenne and Becker muscular dystrophy are X-linked recessive inherited disorders characterized by progressive weakness due to skeletal muscle degeneration. Different mutations in the DMD gene, which encodes for dystrophin protein, are responsible for these disorders. The aim of our study was to investigate the relationship between type, size, and location of the mutation that occurs in the DMD gene and their effect on dystrophin protein expression in a cohort of 40 male dystrophinopathy patients and nine females, possible carriers. We evaluated the expression of dystrophin by immunofluorescence and immunoblotting. The mutational spectrum of the DMD gene was established by MLPA for large copy number variants, followed by HRM analysis for point mutations and sequencing of samples with an abnormal melting profile. MLPA revealed 30 deletions (75%) and three duplications (7.5%). HRM analysis accounted for seven-point mutations (17.5%). We also report four novel small mutations (c. 8507G>T, c.3021delG, c.9563_9563+1insAGCATGTTTATGATACAGCA, c.7661-60T>A) in DMD gene. Our work shows that the DNA translational open reading frame and the location of the mutation both influence the expression of dystrophin and disease severity phenotype. The proposed algorithm used in this study demonstrates its accuracy for the characterization of dystrophinopathy patients.

Detection of SARS-CoV-2 spike protein D614G mutation by qPCR-HRM analysis.

OBJECTIVES: Monitoring the spread of the G614 in specific locations is critical as this variant is highly transmissible and can trigger the emergence of other mutations. Therefore, a rapid and accurate method that can reliably detect the D614G mutation will be beneficial. This study aims to analyze the potential use of the two-step Reverse Transcriptase quantitative polymerase chain reaction - high resolution melting analysis (RT-qPCR-HRM) to detect a specific mutation in the SARS-CoV-2 genome. METHODS: Six SARS-CoV-2 RNA samples were synthesized into cDNA and analyzed with the qPCR-HRM method in order to detect the D614G mutation in Spike protein of SARS-CoV-2. The primers are designed to target the specific Spike region containing the D614G mutation. The qPCR-HRM analysis was conducted simultaneously, and the identification of the SARS-CoV-2 variant was confirmed by conventional PCR and Sanger sequencing methods. RESULTS: The results showed that the melting temperature (Tm) of the D614 variant was 79.39 ± 0.03 °C, which was slightly lower than the Tm of the G614 variant (79.62 ± 0.015 °C). The results of the HRM analysis, visualized by the normalized melting curve and the difference curve were able to discriminate the D614 and G614 variant samples. All samples were identified as G614 variants by qPCR-HRM assay, which was subsequently confirmed by Sanger sequencing. CONCLUSIONS: This study demonstrated a sensitive method that can identify the D614G mutation by a simple two-step RT-qPCR-HRM assay procedure analysis, which can be useful for active surveillance of the transmission of a specific mutation.

Gene Editing in Potato Using CRISPR-Cas9 Technology.

Genome editing in the cultivated potato (Solanum tuberosum), a vegetatively propagated and highly heterozygous species, constitutes a promising trail to directly improve traits into elite cultivars. With the recent and successful development of the clustered regularly interspaced short palindromic repeat (CRISPR)-Cas9 system in eukaryotic cells, the plant science community has gained access to a powerful, inexpensive, and easy-to-use toolbox to target and inactivate/modify specific genes. The specificity and versatility of the CRISPR-Cas9 system rely on a variable 20 bp spacer sequence at the 5' end of a single-guide RNA (sgRNA), which directs the SpCas9 (Streptococcus pyogenes) nuclease to cut the target DNA at a precise locus with no or low off-target events. Using this system, we and other teams were able to knock out specific genes in potato through the error-prone non-homologous end-joining (NHEJ) DNA repair mechanism. In this chapter, we describe strategies to design and clone spacer sequences into CRISPR-SpCas9 plasmids. We show how these constructs can be used for Agrobacterium-mediated stable transformation or transient transfection of protoplasts, and we describe the optimization of these two delivery methods, as well as of the plant regeneration processes. Finally, the molecular screening and characterization of edited potato plants are also described, mainly relying on PCR-based methods such as high-resolution melt (HRM) analysis.

Semi-quantitative evaluation of Babesia bovis and B. bigemina infection levels estimated by HRM analysis.

Bovine babesiosis is economically the most important arthropod-borne disease of cattle worldwide. The most significant damage caused by bovine babesiosis is attributed to Babesia bovis due to its higher pathogenicity. This study aimed to develop a real-time PCR method followed by HRM (high-resolution melting) analysis for the simultaneous detection of B. bovis and B. bigemina, enabling a semi-quantitative analysis of Babesia levels using a single-tube reaction. The HRM was compared with real-time PCR using species-specific hydrolysis probes. The HRM analysis allowed to differentiate both Babesia species and was sensitive in the detection and differentiation of 10% for each Babesia species in the sample. Our results suggest the use of this method to estimate the prevalence of infections by B. bovis or B. bigemina as an alternative to the methods of absolute quantification by real-time PCR since it neither requires precise estimates of the number of DNA loads nor the construction of calibration curves. The simultaneous detection of the two Babesia species can be used to characterise the infection levels in cattle populations from different geographical regions, allowing a better control of these diseases.

Convolutional neural network analysis of recurrence plots for high resolution melting classification.

BACKGROUND AND OBJECTIVE: High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, bacteria, yeast, virus, etc. HRM data are produced using real-time polymerase chain reaction (PCR) and unique for each species. Analysis of the HRM data is important for several applications, such as, for detection of diseases (e.g., influenza, zika virus, SARS-Cov-2 and Covid-19 diseases) in health, for identification of spoiled foods in food industry, for analysis of crime scene evidence in forensic investigation, etc. However, the characteristics of the HRM data can change due to the experimental conditions or instrumental settings. In addition, it becomes laborious and time-consuming process as the number of samples increases. Because of these reasons, the analysis and classification of the HRM data become challenging for species which have similar characteristics. METHODS: To improve the classification accuracy of HRM data, we propose to use image (visual) representation of HRM data, which we call HRM images, that are generated using recurrence plots, and propose convolutional neural network (CNN) based models for classifying HRM images. In this study, two different types of recurrence plots are generated, which are black-white recurrence plots (BW-RP) and gray scale recurrence plots (GS-RP) and four different CNN models are proposed for classifying HRM data. RESULTS: The classification performance of the proposed methods are evaluated based on average classification accuracy and F1 score, specificity, recall, and precision values for each yeast species. When BW-RP representation of HRM data is used as input to the CNN models, the best classification accuracy of 95.2% is obtained. The classification accuracies of CNN models for melting curve and GS-RP data representations of HRM data are 90.13% and 86.13%, respectively. The classification accuracy of support vector machines (SVM) model that take melting curve representation of HRM data is 86.53%. Moreover, when BW-RP representation of HRM data is used as input to the CNN models, the F1 score, specificity, recall and precision values are the highest for almost all of species. CONCLUSIONS: Experimental results show that using BW-RP representation of HRM data improved the classification accuracy of HRM data and CNN models that take these images as input outperformed CNN models that take melting curve and GS-RP representations of HRM data as inputs and SVM model that take melting curve representation of HRM data as input.

Evaluation of the High Resolution Melting Approach for Detection of ß-Thalassemia Gene Mutations.

ß-Thalassemia (ß-thal), an autosomal recessive hemoglobinopathy, is one of the most common genetic disorders in Pakistan. Awareness of this disease, genetic counseling, extended family carrier screening and prenatal diagnosis (PND) are helpful in prevention and control. Currently, direct DNA sequencing and multiple amplification refractory mutation system-polymerase chain reaction (MARMS-PCR) are the methods used to detect ß-thal mutations, the latter being the most widely used. This study aimed to evaluate PCR-high resolution melting (PCR-HRM) analysis for the detection of most common ß-thal mutations that are found in Pakistan. This study was designed to identify the ß-thal mutations using PCR-HRM analysis in a total of 90 samples [blood and chorionic villus sampling (CVS)]. These samples were first screened for routine mutations by MARMS-PCR and then evaluated by PCR-HRM analysis. The results of PCR-HRM analyses were further confirmed by direct DNA sequencing and all analyses interpreted the same results in all 90 samples. Eleven cases (36.6%) were detected to carry IVS-I-5 (G>C) (HBB: c0.92 + 5G>C), six cases (20.0%) with frameshift codons (FSC) 41/42 (-TTCT) (HBB: c.126_129delCTTT), five cases (16.0%) were diagnosed with codon 15 (G>A) (HBB: c.47G>A), three cases (10.0%) were found with codon 30 (G>C) (HBB: c.93G>C), one case was diagnosed with FSC 16 (-C) (HBB: c.51delC), one with IVS-I-1 (G>T) (HBB: c0.92 + 1G>T) and one with codon 5 (-CT) (HBB: c.17_18delCT). The PCR-HRM analysis represents a less tedious and more useful method for the detection of ß-globin gene mutations.

Multiplex Quantitative Real-Time Polymerase Chain Reaction and High-Resolution Melting Analysis for Identification of a Couple At-Risk of Having a Newborn with Severe Thalassemia.

Many polymerase chain reaction (PCR)-based techniques have been used for routine diagnosis of α- and ß-thalassemias. However, most require a multi step of post-PCR processes that are time-consuming and labor-intensive procedures. This study reported the successful use of multiplex quantitative real-time PCR (qPCR), with high-resolution melting (HRM) analysis for diagnosis of two common deletional α0-thalassemia (α0-thal) and 15 common ß-thalassemia (ß-thal) mutations, in order to identify a couple at-risk of having a newborn with severe thalassemia in the northern region of Thailand. With this approach, 22 (7.2%) of 306 couples were diagnosed as being at-risk for having a child with severe thalassemia, including three homozygous α0-thal, five homozygous ß-thal and 14 Hb E (HBB: c.79G>A)/ß0-thal disease. Our findings indicated that multiplex qPCR with HRM is applicable for routine molecular diagnosis in order to identify a couple at-risk of having a newborn with severe thalassemia, especially in an endemic region.

Rapid Molecular Detection for Differentiation of Homozygous HbE and ß0-Thalassemia/HbE in Samples Related With HbE >80% and Variable HbF Levels.

OBJECTIVE: To validate a novel rapid molecular testing method for differentiation of homozygous hemoglobin (Hb)E and HbE/ß 0-thalassemia genotypes using multiplex melt curve combined with high-resolution melt (HRM) analysis in a single test tube. METHODS: All 10 genotypes contained (ß N/ß N; n = 95), (ß N/ß 3.5-kb; n = 71), (ß N/ß 45-kb; n = 28), (ß N/ß E; n = 10), (ß E/ß 3.5-kb; n = 6), (ß E/ß 45-kb; n = 4), (ß E/ß 41/42; n = 28), (ß E/ß 17; n = 9), (ß E/ß IVSI#1; n = 6), and (ß E/ß E; n = 76) were recruited for validation. A proposed strategy for rapid differentiation of ß 0-thalassemia/HbE disease and homozygous Hb E in specimens with HbE greater than 80% and variable HbF levels was demonstrated. RESULTS: In the validation method, all genotypes showed 100% concordance, compared with the conventional reverse dot blot (RDB) and gap-polymerase chain reaction (PCR) methods. CONCLUSIONS: Our newly developed method could be useful in routine laboratory settings. The method is rapid, simple, and cost effective; does not require a post-PCR step; and can be applied in routine settings.

Development of novel methodology for the molecular differentiation of Cryptosporidium parvum gp60 subtypes via high resolution melting analysis.

Cryptosporidium species subtypes are generally identified via DNA sequencing of the gp60 gene tandem repeat motif region. Due to the immunogenic nature of its glycoprotein products, gp60 is subject to host selective pressures, genetic recombination and evolutionary processes that drive extensive polymorphism at this locus. The elucidation of the polymorphic nature of this gene has led to the current mainstay in Cryptosporidium subtyping nomenclature. This study aimed to develop a real-time polymerase chain reaction based method utilising a post-PCR application, high resolution melting (HRM) analysis, in conjunction with the abovementioned gp60 nomenclature system, in order to differentiate between Cryptosporidium parvum gp60 subtypes. Subtype differentiation is based on the difference between the melting temperatures of individual subtypes conferred by variations in the polymorphic region of gp60. • Nested gp60 primers were designed to amplify a target region of <200 base pairs for effective HRM analysis • This method presents a rapid, sensitive, cost effective alternative to conventional sequencing. • This method is highly flexible and may be applied to other loci in order to facilitate multi-locus analysis and improve the discriminative abilities of the method.

Methylation of the PKD1 Promoter Inversely Correlates with its Expression in Autosomal Dominant Polycystic Kidney Disease.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD), a multisystem disorder, is the most prevalent type of hereditary kidney disease. Here, we aimed to evaluate methylation of the PKD1 gene (PKD1) promoter and its correlation with PKD1 expression in peripheral blood. METHODS: In this case-control study methylation of the PKD1 promoter was evaluated using methylation-sensitive high-resolution melt (MS-HRM) analysis. PKD1 expression was assessed by quantitative real-time PCR. The correlation was evaluated using the Pearson correlation test. RESULTS: Twenty subjects from both the patient and control groups (n= 40 for each) were methylated at the PKD1 promoter to various levels (18.9% in patients and 62.5% in controls). This difference was statistically significant (p< 0.0001). PKD1 expression in blood samples was significantly greater in ADPKD patients than in controls (p= 0.0081). Significant correlation was seen between PKD1 expression and its promoter methylation status in peripheral blood (r case= -0.5300, p= 0.0162, and r control = -0.6265, p= 0.0031). CONCLUSION: Methylation of the PKD1 promoter in ADPKD patients was inversely correlated with PKD1 expression.

Identification of novel FUS and TARDBP gene mutations in Chinese amyotrophic lateral sclerosis patients with HRM analysis.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterized by progressive loss of motor neurons. More than 30 genes have been linked to ALS to date, including FUS and TARDBP, which exhibit similar roles in RNA metabolism. This study explored the use of high-resolution melting (HRM) analysis to screen for FUS and TARDBP mutation hotspot regions in 146 Chinese ALS patients, which achieved 100% detection. Two FUS mutations were observed in two different familial ALS probands, a missense mutation (p.R521H) and a novel splicing mutation (c.1541+1G>A). Five TARDBP mutations were identified in six ALS patients, including a novel 3'UTR mutation (c.*731A>G) and four missense mutations (p.G294V, p.M337V, p.G348V, and p.I383V). We found that FUS mutations were present in 1.4% of Chinese ALS patients, whereas TARDBP mutations were responsible for 4.1% of Chinese ALS cases. Here, we describe the accuracy of using highly sensitive HRM analysis to identify two novel FUS and TARDBP mutations in Chinese sporadic and familial ALS cases. Our study contributes to the further understanding of the genetic and phenotypic diversity of ALS.