High-Resolution Melting (HRM) of Hypervariable Mitochondrial DNA Regions for Forensic Science

Statistical methods for discrimination of STR genotypes using high resolution melt curve data

Despite the improvements in forensic DNA quantification methods that allow for the early detection of low template/challenged DNA samples, complicating stochastic effects are not revealed until the final stage of the DNA analysis workflow. An assay that would provide genotyping information at the earlier stage of quantification would allow examiners to make critical adjustments prior to STR amplification allowing for potentially exclusionary information to be immediately reported. Specifically, qPCR instruments often have dissociation curve and/or high-resolution melt curve (HRM) capabilities; this, coupled with statistical prediction analysis, could provide additional information regarding STR genotypes present. Thus, this study aimed to evaluate Qiagen's principal component analysis (PCA)-based ScreenClust® HRM® software and a linear discriminant analysis (LDA)-based technique for their abilities to accurately predict genotypes and similar groups of genotypes from HRM data. Melt curves from single source samples were generated from STR D5S818 and D18S51 amplicons using a Rotor-Gene® Q qPCR instrument and EvaGreen® intercalating dye. When used to predict D5S818 genotypes for unknown samples, LDA analysis outperformed the PCA-based method whether predictions were for individual genotypes (58.92% accuracy) or for geno-groups (81.00% accuracy). However, when a locus with increased heterogeneity was tested (D18S51), PCA-based prediction accuracy rates improved to rates similar to those obtained using LDA (45.10% and 63.46%, respectively). This study provides foundational data documenting the performance of prediction modeling for STR genotyping based on qPCR-HRM data. In order to expand the forensic applicability of this HRM assay, the method could be tested with a more commonly utilized qPCR platform.

Improving the efficiency of Y-chromosome detection and the quality of STR typing in forensic casework with an in-house made qPCR and HRM system based on SYTO™ 9 chemistry

DNA quantification prior to STR amplification is a crucial step in forensic casework. Obtaining good-quality genetic STR profiles depends mainly on the amount and integrity of the DNA input in the PCR. In addition, the detection of male trace DNA provides key information for forensic investigation.

AIM

To evaluate the correlation between the quantification results obtained with the previously developed Amel-Y system, and its ability to detect Y-chromosome DNA by HRM, with the resulting STR profiles, and to ultimately show that Amel-Y can be routinely used in forensic casework to improve STR and Y-STR results.

MATERIAL & METHODS

Biological samples derived from forensic casework (85 reference and 391 evidence samples) were quantified by the Amel-Y system (a duplex qPCR/HRM based on SYTO™ 9 chemistry) using Rotor-Gene 6000. STRs were amplified and analyzed with GeneAmp™ PCR System 9700 or Veriti™ Thermal Cyclers and ABI 3500 Genetic Analyzer, respectively.

RESULTS

After DNA normalization, a total of 386 STR profiles were obtained (305 full and 81 partial). Sex typing by HRM was 100% successful in reference samples. Male DNA was detected by HRM in 210 evidence samples. 80/201 were mixed with an excess of female DNA. In addition, Amel-Y was able to detect Y-chromosome DNA in mixed samples that did not amplify the Y-variant of Amelogenin marker with commercial STR kits. The reproducibility and precision of the Amel-Y system were demonstrated (CVCt% ≤ 9.55) within the dynamic range analyzed (0.016-50 ng/µL; 41 independent runs). Amel-Y also proved to be compatible with other real-time PCR platforms.

CONCLUSION

We demonstrated that Amel-Y is a robust quantification system that can be routinely used in forensic casework to obtain reliable autosomal STR profiles and can be suitable as a predictor for Y-STR typing success when male DNA is detected. HRM can be used as a rapid screening tool for male DNA detection in mixed samples. Alternative designs like Amel-Y offer independence from commercial quantification kits in forensic labs.

Epidemiology of Δ8THC-Related Carcinogenesis in USA: A Panel Regression and Causal Inferential Study

The use of Δ8THC is increasing at present across the USA in association with widespread cannabis legalization and the common notion that it is "legal weed". As genotoxic actions have been described for many cannabinoids, we studied the cancer epidemiology of Δ8THC. Data on 34 cancer types was from the Centers for Disease Control Atlanta Georgia, substance abuse data from the Substance Abuse and Mental Health Services Administration, ethnicity and income data from the U.S. Census Bureau, and cannabinoid concentration data from the Drug Enforcement Agency, were combined and processed in R. Eight cancers (corpus uteri, liver, gastric cardia, breast and post-menopausal breast, anorectum, pancreas, and thyroid) were related to Δ8THC exposure on bivariate testing, and 18 (additionally, stomach, Hodgkins, and Non-Hodgkins lymphomas, ovary, cervix uteri, gall bladder, oropharynx, bladder, lung, esophagus, colorectal cancer, and all cancers (excluding non-melanoma skin cancer)) demonstrated positive average marginal effects on fully adjusted inverse probability weighted interactive panel regression. Many minimum E-Values (mEVs) were infinite. p-values rose from 8.04 × 10-78. Marginal effect calculations revealed that 18 Δ8THC-related cancers are predicted to lead to a further 8.58 cases/100,000 compared to 7.93 for alcoholism and -8.48 for tobacco. Results indicate that between 8 and 20/34 cancer types were associated with Δ8THC exposure, with very high effect sizes (mEVs) and marginal effects after adjustment exceeding tobacco and alcohol, fulfilling the epidemiological criteria of causality and suggesting a cannabinoid class effect. The inclusion of pediatric leukemias and testicular cancer herein demonstrates heritable malignant teratogenesis.

On the Identification of Body Fluids and Tissues: A Crucial Link in the Investigation and Solution of Crime

Body fluid and body tissue identification are important in forensic science as they can provide key evidence in a criminal investigation and may assist the court in reaching conclusions. Establishing a link between identifying the fluid or tissue and the DNA profile adds further weight to this evidence. Many forensic laboratories retain techniques for the identification of biological fluids that have been widely used for some time. More recently, many different biomarkers and technologies have been proposed for identification of body fluids and tissues of forensic relevance some of which are now used in forensic casework. Here, we summarize the role of body fluid/ tissue identification in the evaluation of forensic evidence, describe how such evidence is detected at the crime scene and in the laboratory, elaborate different technologies available to do this, and reflect real life experiences. We explain how, by including this information, crucial links can be made to aid in the investigation and solution of crime.

High-Resolution Melting Analysis for Rapid Detection of Mutations in Patients with FGFR3-Related Skeletal Dysplasias

Background: Mutations in the fibroblast growth factor receptor 3 (FGFR3) gene are related to skeletal dysplasias (SDs): acondroplasia (ACH), hypochodroplasia (HCH) and type I (TDI) and II (TDII) tanatophoric dysplasias. This study was designed to standardize and implement a high-resolution melting (HRM) technique to identify mutations in patients with these phenotypes. Methods: Initially, FGFR3 gene segments from 84 patients were PCR amplified and subjected to Sanger sequencing. Samples from 29 patients positive for mutations were analyzed by HRM. Results: Twelve of the patients FGFR3 mutations had ACH (six g.16081 G > A, three g.16081 G > C and three g.16081 G > A + g.16002 C > T); thirteen of patients with HCH had FGFR3 mutations (eight g.17333 C > A, five g.17333 C > G and five were negative); and four patients with DTI had FGFR3 mutations (three g.13526 C > T and one g.16051G > T and two patients with DTII (presented mutation g.17852 A > G). When analyzing the four SDs altogether, an overlap of the dissociation curves was observed, making genotyping difficult. When analyzed separately, however, the HRM analysis method proved to be efficient for discriminating among the mutations for each SD type, except for those patients carrying additional polymorphism concomitant to the recurrent mutation. Conclusion: We conclude that for recurrent mutations in the FGFR3 gene, that the HRM technique can be used as a faster, reliable and less expensive genotyping routine for the diagnosis of these pathologies than Sanger sequencing.

Ion torrent high throughput mitochondrial genome sequencing (HTMGS)

The implementation and popularity of next generation sequencing (NGS) has led to the development of various rapid whole mitochondrial genome sequencing techniques. We summarise an efficient and cost-effective NGS approach for mitochondrial genomic DNA in humans using the Ion Torrent platform, and further discuss our bioinformatics pipeline for streamlined variant calling. Ion 316 chips were utilised with the Ion Torrent semi-conductor platform Personal Genome Machine (PGM) to perform tandem sequencing of mitochondrial genomes from the core pedigree (n = 315) of the Norfolk Island Health Study. Key improvements from commercial methods focus on the initial PCR step, which currently requires extensive optimisation to ensure the accurate and reproducible elongation of each section of the complete mitochondrial genome. Dual-platform barcodes were incorporated into our protocol thereby extending its potential application onto Illumina-based systems. Our bioinformatics pipeline consists of a modified version of GATK best practices tailored for mitochondrial genomic data. When compared with current commercial methods, our method, termed high throughput mitochondrial genome sequencing (HTMGS), allows high multiplexing of samples and the use of alternate library preparation reagents at a lower cost per sample (~1.7 times) when compared to current commercial methodologies. Our HTMGS methodology also provides robust mitochondrial sequencing data (>450X average coverage) that can be applied and modified to suit various study designs. On average, we were able to identify ~30 variants per sample with 572 variants observed across 315 samples. We have developed a high throughput sequencing and analysis method targeting complete mitochondrial genomes; with the potential to be platform agnostic with analysis options that adhere to current best practices.