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© 2017, © 2017 Australian Academy of Forensic Sciences. Species identification is an important facet of forensic investigation. In this study, human and non-human species (cow, chicken, pig, sheep, cat, dog, rabbit, fox, kangaroo and wombat) were assayed on the ViiA 7 Real-Time PCR System (Thermo Fisher Scientific) to rapidly screen for their species of origin using the high resolution melt (HRM) analysis targeting the 16S rRNA gene. Classification of HRM difference profiles using the onboard ViiA 7 software resulted in a classification accuracy of <20%. Derivative profiles (temperature versus negative first derivative of fluorescence, –dF/dT) were classified using random forest algorithms supplemented by bagging and boosting, with either a randomly partitioned test set or a variety of folds of cross-classification, in addition to a range of trees and variables. Random forest classification with bagging conditions (constructed over 500 trees) was found to considerably outperform the ViiA 7 software for species differentiation with 100% classification accuracy for biological material from humans, domestic pets (cat and dog) and consumable meats (chicken and sheep) with an average classification accuracy of 70% across all species.

© 2017, © 2017 Australian Academy of Forensic Sciences. Species identification is an important facet of forensic investigation. In this study, human and non-human species (cow, chicken, pig, sheep, cat, dog, rabbit, fox, kangaroo and wombat) were assayed on the ViiA 7 Real-Time PCR System (Thermo Fisher Scientific) to rapidly screen for their species of origin using the high resolution melt (HRM) analysis targeting the 16S rRNA gene. Classification of HRM difference profiles using the onboard ViiA 7 software resulted in a classification accuracy of <20%. Derivative profiles (temperature versus negative first derivative of fluorescence, –dF/dT) were classified using random forest algorithms supplemented by bagging and boosting, with either a randomly partitioned test set or a variety of folds of cross-classification, in addition to a range of trees and variables. Random forest classification with bagging conditions (constructed over 500 trees) was found to considerably outperform the ViiA 7 software for species differentiation with 100% classification accuracy for biological material from humans, domestic pets (cat and dog) and consumable meats (chicken and sheep) with an average classification accuracy of 70% across all species.

Evolutionary and cultural history can affect the genetic characteristics of a population and influences the frequency of different variants at a particular genetic marker (allele frequency). These characteristics directly influence the strength of forensic DNA evidence and make the availability of suitable allele frequency information for every discrete country or jurisdiction highly relevant. Population sub-structure within Indonesia has not been well characterised but should be expected given the complex geographical, linguistic and cultural architecture of the Indonesian population. Here we use forensic short tandem repeat (STR) markers to identify a number of distinct genetic subpopulations within Indonesia and calculate appropriate population sub-structure correction factors. This data represents the most comprehensive investigation of population sub-structure within Indonesia to date using these markers. The results demonstrate that significant sub-structure is present within the Indonesian population and must be accounted for using island specific allele frequencies and corresponding sub-structure correction factors in the calculation of forensic DNA match statistics.

Evolutionary and cultural history can affect the genetic characteristics of a population and influences the frequency of different variants at a particular genetic marker (allele frequency). These characteristics directly influence the strength of forensic DNA evidence and make the availability of suitable allele frequency information for every discrete country or jurisdiction highly relevant. Population sub-structure within Indonesia has not been well characterised but should be expected given the complex geographical, linguistic and cultural architecture of the Indonesian population. Here we use forensic short tandem repeat (STR) markers to identify a number of distinct genetic subpopulations within Indonesia and calculate appropriate population sub-structure correction factors. This data represents the most comprehensive investigation of population sub-structure within Indonesia to date using these markers. The results demonstrate that significant sub-structure is present within the Indonesian population and must be accounted for using island specific allele frequencies and corresponding sub-structure correction factors in the calculation of forensic DNA match statistics.

High resolution melting (HRM) analysis is a simple, cost effective, closed tube SNP genotyping technique with high throughput potential. The effectiveness of HRM for forensic SNP genotyping was assessed with five commercially available HRM kits evaluated on the ViiA™ 7 Real Time PCR instrument. Four kits performed satisfactorily against forensically relevant criteria. One was further assessed to determine the sensitivity, reproducibility, and accuracy of HRM SNP genotyping. The manufacturer's protocol using 0.5 ng input DNA and 45 PCR cycles produced accurate and reproducible results for 17 of the 19 SNPs examined. Problematic SNPs had GC rich flanking regions which introduced additional melting domains into the melting curve (rs1800407) or included homozygotes that were difficult to distinguish reliably (rs16891982; a G to C SNP). A proof of concept multiplexing experiment revealed that multiplexing a small number of SNPs may be possible after further investigation. HRM enables genotyping of a number of SNPs in a large number of samples without extensive optimization. However, it requires more genomic DNA as template in comparison to SNaPshot®. Furthermore, suitably modifying pre-existing forensic intelligence SNP panels for HRM analysis may pose difficulties due to the properties of some SNPs.

High resolution melting (HRM) analysis is a simple, cost effective, closed tube SNP genotyping technique with high throughput potential. The effectiveness of HRM for forensic SNP genotyping was assessed with five commercially available HRM kits evaluated on the ViiA™ 7 Real Time PCR instrument. Four kits performed satisfactorily against forensically relevant criteria. One was further assessed to determine the sensitivity, reproducibility, and accuracy of HRM SNP genotyping. The manufacturer's protocol using 0.5 ng input DNA and 45 PCR cycles produced accurate and reproducible results for 17 of the 19 SNPs examined. Problematic SNPs had GC rich flanking regions which introduced additional melting domains into the melting curve (rs1800407) or included homozygotes that were difficult to distinguish reliably (rs16891982; a G to C SNP). A proof of concept multiplexing experiment revealed that multiplexing a small number of SNPs may be possible after further investigation. HRM enables genotyping of a number of SNPs in a large number of samples without extensive optimization. However, it requires more genomic DNA as template in comparison to SNaPshot®. Furthermore, suitably modifying pre-existing forensic intelligence SNP panels for HRM analysis may pose difficulties due to the properties of some SNPs.