An Investigation into the Genetic Diversity of Cannabis in New Zealand

Abstract

Repeat markers have previously been developed for the analysis of Cannabis in a forensic setting. STRs are useful for providing genetic information about individuals within and among populations. It is this characteristic, which proves to be very useful when identifying the origins and relationships of seized Cannabis within a forensic setting. Diversity studies using repeat markers have previously been carried out by groups in the USA and Australia. This study aimed to extract and amplify DNA from Cannabis seized from different parts of NZ using an 11 STR multiplex and to find any regional variation in order to determine if it is possible to differentiate between Cannabis plants grown in different parts of New Zealand because of their multi-locus genotype. 193 samples were successfully analysed to help determine the genetic diversity of Cannabis in New Zealand. 15 samples showed unusual tri-allelic profiles and were not included in the statistical analysis. The remaining 171 were used to statistically investigate how the diversity is spread throughout the country and how the dataset behaves within a number of classical population genetics principles. The results showed that there were 81 unique and 16 shared multi-locus genotypes within the dataset and a number of new alleles were identified. The shared multi-locus genotypes were found across the length of New Zealand and each group contained samples from all four regional datasets, indicating that the genotypes present in the New Zealand populations overlap considerably. The dataset was tested for departure from Hardy-Weinberg equilibrium and the results showed that the dataset did depart significant from Hardy-Weinberg equilibrium. It was also shown to have significant levels of linkage disequilibrium present between loci. The results indicated that the genotypes present in the New Zealand population overlap significantly and there is no regional separation present within the dataset. Another important result was the identification of a number of clonal samples and samples with shared genotypes in the dataset. The presence of clonal samples indicated that these samples might be used to trace samples with shared genotypes across New Zealand. The conclusions of this study were that it is not possible to assign a sample to a specific geographic location in New Zealand based on its genotype and that the dataset does not behave within the bounds of classical population genetic principles.