High resolution melting analysis for a rapid identification of heterozygous and homozygous sequence changes in the MUTYH gene

Evaluation of Two Multiplex PCR-High-Resolution Melt Curve Analysis Methods for Differentiation of Campylobacter jejuni and Campylobacter coli Intraspecies

Campylobacter infection is a common cause of bacterial gastroenteritis in humans and remains a significant global public health issue. The capability of two multiplex PCR (mPCR)-high-resolution melt (HRM) curve analysis methods (i.e., mPCR1-HRM and mPCR2-HRM) to detect and differentiate 24 poultry isolates and three reference strains of Campylobacter jejuni and Campylobacter coli was investigated. Campylobacter jejuni and C. coli were successfully differentiated in both assays, but the differentiation power of mPCR2-HRM targeting the cadF gene was found superior to that of mPCR1-HRM targeting the gpsA gene or a hypothetical protein gene. However, higher intraspecies variation within C. coli and C. jejuni isolates was detected in mPCR1-HRM when compared with mPCR2-HRM. Both assays were rapid and required minimum interpretation skills for discrimination between and within Campylobacter species when using HRM curve analysis software.

High resolution melting curve analysis targeting the HBB gene mutational hot-spot offers a reliable screening approach for all common as well as most of the rare beta-globin gene mutations in Bangladesh

BACKGROUND

Bangladesh lies in the global thalassemia belt, which has a defined mutational hot-spot in the beta-globin gene. The high carrier frequencies of beta-thalassemia trait and hemoglobin E-trait in Bangladesh necessitate a reliable DNA-based carrier screening approach that could supplement the use of hematological and electrophoretic indices to overcome the barriers of carrier screening. With this view in mind, the study aimed to establish a high resolution melting (HRM) curve-based rapid and reliable mutation screening method targeting the mutational hot-spot of South Asian and Southeast Asian countries that encompasses exon-1 (c.1 - c.92), intron-1 (c.92 + 1 - c.92 + 130) and a portion of exon-2 (c.93 - c.217) of the HBB gene which harbors more than 95% of mutant alleles responsible for beta-thalassemia in Bangladesh.

RESULTS

Our HRM approach could successfully differentiate ten beta-globin gene mutations, namely c.79G > A, c.92 + 5G > C, c.126_129delCTTT, c.27_28insG, c.46delT, c.47G > A, c.92G > C, c.92 + 130G > C, c.126delC and c.135delC in heterozygous states from the wild type alleles, implying the significance of the approach for carrier screening as the first three of these mutations account for ~85% of total mutant alleles in Bangladesh. Moreover, different combinations of compound heterozygous mutations were found to generate melt curves that were distinct from the wild type alleles and from one another. Based on the findings, sixteen reference samples were run in parallel to 41 unknown specimens to perform direct genotyping of the beta-thalassemia specimens using HRM. The HRM-based genotyping of the unknown specimens showed 100% consistency with the sequencing result.

CONCLUSIONS

Targeting the mutational hot-spot, the HRM approach could be successfully applied for screening of beta-thalassemia carriers in Bangladesh as well as in other countries of South Asia and Southeast Asia. The approach could be a useful supplement of hematological and electrophortic indices in order to avoid false positive and false negative results.

High-resolution melting (HRM) assay for the detection of recurrent BRCA1/BRCA2 germline mutations in Tunisian breast/ovarian cancer families

Germline deleterious mutations in the BRCA1/BRCA2 genes are associated with an increased risk for the development of breast and ovarian cancer. Given the large size of these genes the detection of such mutations represents a considerable technical challenge. Therefore, the development of cost-effective and rapid methods to identify these mutations became a necessity. High resolution melting analysis (HRM) is a rapid and efficient technique extensively employed as high-throughput mutation scanning method. The purpose of our study was to assess the specificity and sensitivity of HRM for BRCA1 and BRCA2 genes scanning. As a first step we estimate the ability of HRM for detection mutations in a set of 21 heterozygous samples harboring 8 different known BRCA1/BRCA2 variations, all samples had been preliminarily investigated by direct sequencing, and then we performed a blinded analysis by HRM in a set of 68 further sporadic samples of unknown genotype. All tested heterozygous BRCA1/BRCA2 variants were easily identified. However the HRM assay revealed further alteration that we initially had not searched (one unclassified variant). Furthermore, sequencing confirmed all the HRM detected mutations in the set of unknown samples, including homozygous changes, indicating that in this cohort, with the optimized assays, the mutations detections sensitivity and specificity were 100 %. HRM is a simple, rapid and efficient scanning method for known and unknown BRCA1/BRCA2 germline mutations. Consequently the method will allow for the economical screening of recurrent mutations in Tunisian population.

Trainable high resolution melt curve machine learning classifier for large-scale reliable genotyping of sequence variants

High resolution melt (HRM) is gaining considerable popularity as a simple and robust method for genotyping sequence variants. However, accurate genotyping of an unknown sample for which a large number of possible variants may exist will require an automated HRM curve identification method capable of comparing unknowns against a large cohort of known sequence variants. Herein, we describe a new method for automated HRM curve classification based on machine learning methods and learned tolerance for reaction condition deviations. We tested this method in silico through multiple cross-validations using curves generated from 9 different simulated experimental conditions to classify 92 known serotypes of Streptococcus pneumoniae and demonstrated over 99% accuracy with 8 training curves per serotype. In vitro verification of the algorithm was tested using sequence variants of a cancer-related gene and demonstrated 100% accuracy with 3 training curves per sequence variant. The machine learning algorithm enabled reliable, scalable, and automated HRM genotyping analysis with broad potential clinical and epidemiological applications.

Point mutation frequency in the FMR1 gene as revealed by fragile X syndrome screening

Fragile X syndrome (FXS) is a common cause of intellectual disability, developmental delay and autism spectrum disorders. This syndrome is due to a functional loss of the FMR1 gene product FMRP, and, in most cases, it is caused by CGG repeat expansion in the FMR1 promoter. Yet, also other FMR1 mutations may cause a FXS-like phenotype. Since standard molecular testing does not include the analysis of the FMR1 coding region, the prevalence of point mutations causing FXS is not well known. Here, high resolution melting (HRM) was used to screen for FMR1 gene mutations in 508 males with clinical signs of mental retardation and developmental delay, but without CGG and GCC repeat expansions in the FMR1 gene and AFF2 genes, respectively. Sequence variations were identified by HRM analysis and verified by direct DNA sequencing. Two novel missense mutations (p.Gly482Ser in one patient and p.Arg534His in two unrelated patients), one intronic and two 3'-untranslated region (UTR) variations were identified in the FMR1 gene. Missense mutations in the FMR1 gene might account for a considerable proportion of cases in male patients with FXS-related symptoms, such as those linked to mental retardation and developmental delay.

Enhanced primer selection and synthetic amplicon templates optimize high-resolution melting analysis of single-nucleotide polymorphisms in a large population

AIMS

High-resolution melting (HRM) screening and scanning for single-nucleotide polymorphisms (SNPs) afford the advantages of a quicker, less expensive, and less demanding option compared to other methods for sequence analysis. The evaluation of large populations of patients for multiple SNPs in a high-throughput manner is the next phase in individualized medicine.

RESULTS

We demonstrated that Tm profiles can be generated from gDNA samples that clearly differentiate homozygous ancestral, homozygous SNP, and heterozygous genotypes, while identifying samples of unique outcome without the cumbersome processes of normalization, temperature shifting, and difference plot generation.

CONCLUSIONS

Through expanded primer selection criterion and inclusion of a cloning fragment length double-stranded DNA sequence-specific control template, we are now able to generate additional data via HRM melt domains that are greatly simplified, while considering both the peak melt temperature and profile.