Genome-wide analyses reveal clustering in Cannabis cultivars: the ancient trilogy of a panacea

Science and Management, University of Northern British Columbia, Prince George, British Columbia, Canada
DOI
10.7287/peerj.preprints.1553v1
Subject Areas
Agricultural Science, Evolutionary Studies, Genomics, Plant Science, Taxonomy
Keywords
Cannabis Genetics, SNP, Cannabis, sativa, indica, ruderalis
Copyright
© 2015 Henry
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Henry P. 2015. Genome-wide analyses reveal clustering in Cannabis cultivars: the ancient trilogy of a panacea. PeerJ PrePrints 3:e1553v1

Abstract

In the present research, I used an open access data set (Medicinal Genomics) consisting of nearly 200'000 genome-wide single nucleotide polymorphisms (SNPs) typed in 28 cannabis accessions to shed light on the plant's underlying genetic structure. Genome-wide loadings were used to sequentially cull less informative markers. The process involved reducing the number of SNPs to 100K, 10K, 1K, 100 until I identified a set of 42 highly informative SNPs that I present here. The two first principal components, encompass over 3/4 of the genetic variation present in the dataset (PCA1 = 48.6%, PCA2= 26.3%). This set of diagnostic SNPs is then used to identify clusters into which cannabis accession segregate. I identified three clear and consistent clusters; reflective of the ancient trilogy of the genus Cannabis.

Author Comment

The present research demonstrates the use of 42 highly informative single nucleotide polymorphism that can be used to determine the phylogenetic position of a given Cannabis cultivar.

Supplemental Information

Information on the 42 highly informative SNPs

DOI: 10.7287/peerj.preprints.1553v1/supp-1