DNA metabarcoding provides great potential for species identification in complex samples such as food supplements and traditional medicines. Such a method would aid Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for forensic wildlife species identification and to evaluate the applicability and reproducibility of this approach across different laboratories. A DNA metabarcoding method was developed that makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa and that facilitate the identification of species in samples containing degraded DNA. The DNA metabarcoding method was developed based on Illumina MiSeq amplicon sequencing of well-defined experimental mixtures, for which a bioinformatics pipeline with user-friendly web-interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. The advanced multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES-listed species. The method can provide improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to an enhanced quality assurance.

No abstract

Marijuana (Cannabis sativa) is the most commonly used illicit substance in the USA. The development of a validated method using Cannabis short tandem repeats (STRs) could aid in the individualization of samples as well as serve as an intelligence tool to link multiple cases. For this purpose, a modified 13-loci STR multiplex method was optimized and evaluated according to ISFG and SWGDAM guidelines. A real-time PCR quantification method for C. sativa was developed and validated, and a sequenced allelic ladder was also designed to accurately genotype 199 C. sativa samples from 11 U.S. Customs and Border Protection seizures. Distinguishable DNA profiles were generated from 127 samples that yielded full STR profiles. Four duplicate genotypes within seizures were found. The combined power of discrimination of this multilocus system is 1 in 70 million. The sensitivity of the multiplex STR system is 0.25 ng of template DNA. None of the 13 STR markers cross-reacted with any of the studied species, except for Humulus lupulus (hops) which generated unspecific peaks. Phylogenetic analysis and case-to-case pairwise comparison of 11 cases using F st as genetic distance revealed the genetic association of four groups of cases. Moreover, due to their genetic similarity, a subset of samples (N = 97) was found to form a homogeneous population in Hardy-Weinberg and linkage equilibrium. The results of this research demonstrate the applicability of this 13-loci STR system in associating Cannabis cases for intelligence purposes.

As Cannabis sativa (marijuana) is a controlled substance in many parts of the world, the ability to track biogeographical origin of cannabis could provide law enforcement with investigative leads regarding its trade and distribution. Population substructure and inbreeding may cause cannabis plants to become more genetically related. This genetic relatedness can be helpful for intelligence purposes. Analysis of autosomal, chloroplast, and mitochondrial DNA allows for not only prediction of biogeographical origin of a plant but also discrimination between individual plants. A previously validated, 13-autosomal STR multiplex was used to genotype 510 samples. Samples were analyzed from four different sites: 21 seizures at the US-Mexico border, Northeastern Brazil, hemp seeds purchased in the US, and the Araucania area of Chile. In addition, a previously reported multi-loci system was modified and optimized to genotype five chloroplast and two mitochondrial markers. For this purpose, two methods were designed: a homopolymeric STR pentaplex and a SNP triplex with one chloroplast (Cscp001) marker shared by both methods for quality control. For successful mitochondrial and chloroplast typing, a novel real-time PCR quantitation method was developed and validated to accurately estimate the quantity of the chloroplast DNA (cpDNA) using a synthetic DNA standard. Moreover, a sequenced allelic ladder was also designed for accurate genotyping of the homopolymeric STR pentaplex. For autosomal typing, 356 unique profiles were generated from the 425 samples that yielded full STR profiles and 25 identical genotypes within seizures were observed. Phylogenetic analysis and case-to-case pairwise comparisons of 21 seizures at the US-Mexico border, using the Fixation Index (F ) as genetic distance, revealed the genetic association of nine seizures that formed a reference population. For mitochondrial and chloroplast typing, subsampling was performed, and 134 samples were genotyped. Complete haplotypes (STRs and SNPs) were observed for 127 samples. As expected, extensive haplotype sharing was observed; five distinguishable haplotypes were detected. In the reference population, the same haplotype was observed 39 times and two unique haplotypes were also detected. Haplotype sharing was observed between the US border seizures, Brazil, and Chile, while the hemp samples generated a distinct haplotype. Phylogenetic analysis of the four populations was performed, and results revealed that both autosomal and lineage markers could discern population substructure.

No abstract