Cull Alex, Joly David L
Cannabis Innovation and Research Center, Université de Moncton, Moncton, New-Brunswick, Canada.
BMC Genomics. 2025 Jan 28;26(1):83. doi: 10.1186/s12864-025-11263-z.
Due to its previously illicit nature, Cannabis sativa had not fully reaped the benefits of recent innovations in genomics and plant sciences. However, Canada's legalization of C. sativa and products derived from its flower in 2018 triggered significant new demand for robust genotyping tools to assist breeders in meeting consumer demands. Early molecular marker-based research on C. sativa focused on screening for plant sex and chemotype, and more recent research has sought to use molecular markers to target traits of agronomic interest, to study populations and to differentiate between C. sativa cultivars.
In this study, we have conducted whole genome sequencing of 32 cultivars, mined the sequencing data for SNPs, developed a reduced SNP genotyping panel to discriminate between sequenced cultivars, then validated the 20-SNP panel using DNA from the sequenced cultivars and tested the assays on commercially available dried flower. The assay conversion rate was higher in DNA extracted from fresh plant material than in DNA extracted from dried flower samples. However, called genotypes were internally consistent, highlighting discrepancies between genotypes detected using sequencing data and observed using genotyping assays. The primary contributions of this work are to clearly document the process used to develop minimal SNP genotyping panels, the feasibility of using such panels to differentiate between C. sativa cultivars, and outline improvements and goals for future iterations of PCR-based, minimal SNP panels to enable efficient development genotyping tools to identify and screen C. sativa cultivars.
Our key recommendations are to increase sampling density to account for intra-cultivar variability; leverage higher read length paired-end short-read technology; conduct in-depth pre- and post-processing of reads, mapping, and variant calling data; integrate trait-associated loci to develop multi-purpose panels; and use iterative approaches for in vitro validation to ensure that only the most discriminant and performant SNPs are retained.
由于大麻曾经的非法性质,其尚未充分受益于基因组学和植物科学领域的最新创新成果。然而,2018年加拿大将大麻及其花衍生产品合法化,引发了对强大基因分型工具的大量新需求,以帮助育种者满足消费者需求。早期基于分子标记的大麻研究主要集中在筛选植物性别和化学型,而最近的研究则试图利用分子标记来靶向农艺学上感兴趣的性状、研究种群并区分大麻品种。
在本研究中,我们对32个品种进行了全基因组测序,挖掘测序数据中的单核苷酸多态性(SNP),开发了一个简化的SNP基因分型面板以区分已测序的品种,然后使用已测序品种的DNA对20-SNP面板进行验证,并在市售干花上测试了这些检测方法。从新鲜植物材料中提取的DNA的检测转化率高于从干花样品中提取的DNA。然而,所调用的基因型在内部是一致的,突出了使用测序数据检测到的基因型与使用基因分型检测观察到的基因型之间的差异。这项工作的主要贡献在于清晰记录了开发最小SNP基因分型面板所使用的过程、使用此类面板区分大麻品种的可行性,并概述了基于PCR的最小SNP面板未来迭代的改进和目标,以实现高效开发用于鉴定和筛选大麻品种的基因分型工具。
我们的主要建议是增加采样密度以考虑品种内的变异性;利用更长读长的双端短读技术;对读数、映射和变异调用数据进行深入的预处理和后处理;整合与性状相关的位点以开发多用途面板;并使用迭代方法进行体外验证,以确保仅保留最具区分性和性能最佳的SNP。