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      Broad-Scale Genetic Diversity of Cannabis for Forensic Applications

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          Abstract

          Cannabis (hemp and marijuana) is an iconic yet controversial crop. On the one hand, it represents a growing market for pharmaceutical and agricultural sectors. On the other hand, plants synthesizing the psychoactive THC produce the most widespread illicit drug in the world. Yet, the difficulty to reliably distinguish between Cannabis varieties based on morphological or biochemical criteria impedes the development of promising industrial programs and hinders the fight against narcotrafficking. Genetics offers an appropriate alternative to characterize drug vs. non-drug Cannabis. However, forensic applications require rapid and affordable genotyping of informative and reliable molecular markers for which a broad-scale reference database, representing both intra- and inter-variety variation, is available. Here we provide such a resource for Cannabis, by genotyping 13 microsatellite loci (STRs) in 1 324 samples selected specifically for fibre (24 hemp varieties) and drug (15 marijuana varieties) production. We showed that these loci are sufficient to capture most of the genome-wide diversity patterns recently revealed by NGS data. We recovered strong genetic structure between marijuana and hemp and demonstrated that anonymous samples can be confidently assigned to either plant types. Fibres appear genetically homogeneous whereas drugs show low (often clonal) diversity within varieties, but very high genetic differentiation between them, likely resulting from breeding practices. Based on an additional test dataset including samples from 41 local police seizures, we showed that the genetic signature of marijuana cultivars could be used to trace crime scene evidence. To date, our study provides the most comprehensive genetic resource for Cannabis forensics worldwide.

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          Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power.

          Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.
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            Detecting immigration by using multilocus genotypes.

            Immigration is an important force shaping the social structure, evolution, and genetics of populations. A statistical method is presented that uses multilocus genotypes to identify individuals who are immigrants, or have recent immigrant ancestry. The method is appropriate for use with allozymes, microsatellites, or restriction fragment length polymorphisms (RFLPs) and assumes linkage equilibrium among loci. Potential applications include studies of dispersal among natural populations of animals and plants, human evolutionary studies, and typing zoo animals of unknown origin (for use in captive breeding programs). The method is illustrated by analyzing RFLP genotypes in samples of humans from Australian, Japanese, New Guinean, and Senegalese populations. The test has power to detect immigrant ancestors, for these data, up to two generations in the past even though the overall differentiation of allele frequencies among populations is low.
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              The draft genome and transcriptome of Cannabis sativa

              Background Cannabis sativa has been cultivated throughout human history as a source of fiber, oil and food, and for its medicinal and intoxicating properties. Selective breeding has produced cannabis plants for specific uses, including high-potency marijuana strains and hemp cultivars for fiber and seed production. The molecular biology underlying cannabinoid biosynthesis and other traits of interest is largely unexplored. Results We sequenced genomic DNA and RNA from the marijuana strain Purple Kush using shortread approaches. We report a draft haploid genome sequence of 534 Mb and a transcriptome of 30,000 genes. Comparison of the transcriptome of Purple Kush with that of the hemp cultivar 'Finola' revealed that many genes encoding proteins involved in cannabinoid and precursor pathways are more highly expressed in Purple Kush than in 'Finola'. The exclusive occurrence of Δ9-tetrahydrocannabinolic acid synthase in the Purple Kush transcriptome, and its replacement by cannabidiolic acid synthase in 'Finola', may explain why the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) is produced in marijuana but not in hemp. Resequencing the hemp cultivars 'Finola' and 'USO-31' showed little difference in gene copy numbers of cannabinoid pathway enzymes. However, single nucleotide variant analysis uncovered a relatively high level of variation among four cannabis types, and supported a separation of marijuana and hemp. Conclusions The availability of the Cannabis sativa genome enables the study of a multifunctional plant that occupies a unique role in human culture. Its availability will aid the development of therapeutic marijuana strains with tailored cannabinoid profiles and provide a basis for the breeding of hemp with improved agronomic characteristics.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                20 January 2017
                2017
                : 12
                : 1
                : e0170522
                Affiliations
                [1 ]Laboratory for Conservation Biology, Department of Ecology and Evolution, Biophore Building, University of Lausanne, Lausanne, Switzerland
                [2 ]Centre Universitaire Romand de Médecine Légale, Chemin de la Vuillette 4, Lausanne, Switzerland
                [3 ]Department of Ecology and Evolution, Biophore Building, University of Lausanne, Lausanne, Switzerland
                Universita degli Studi di Siena, ITALY
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                • Conceptualization: JG LF.

                • Formal analysis: CD FB JG LF.

                • Funding acquisition: LF.

                • Investigation: CJ LF.

                • Methodology: CJ LF.

                • Project administration: LF.

                • Supervision: LF.

                • Validation: CJ LF.

                • Visualization: CD LF.

                • Writing – original draft: CD LF.

                • Writing – review & editing: CD CJ FB JG LF.

                Article
                PONE-D-16-39870
                10.1371/journal.pone.0170522
                5249207
                28107530
                4c2646a9-5b27-44d0-934e-d0d397f8b055
                © 2017 Dufresnes et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 6 October 2016
                : 5 January 2017
                Page count
                Figures: 2, Tables: 2, Pages: 13
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100001711, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung;
                Award ID: 31003A_130234
                Award Recipient :
                This work was supported by Swiss National Science Foundation (SNSF). Grant number 31003A_130234 to LF. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Medicine and Health Sciences
                Pharmacology
                Behavioral Pharmacology
                Recreational Drug Use
                Cannabis
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Fiber Crops
                Hemp
                Medicine and Health Sciences
                Diagnostic Medicine
                Clinical Laboratory Sciences
                Forensics
                Social Sciences
                Law and Legal Sciences
                Forensics
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Fiber Crops
                Social Sciences
                Sociology
                Criminology
                Police
                People and Places
                Population Groupings
                Professions
                Police
                Medicine and Health Sciences
                Pharmacology
                Drug Research and Development
                Drug Licensing
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Multivariate Analysis
                Principal Component Analysis
                Medicine and Health Sciences
                Pharmacology
                Drugs
                Cannabinoids
                Custom metadata
                Microsatellite genotypes are available from the Dryad Digital Repository (doi: 10.5061/dryad.p2d8h).

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                Uncategorized

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