Advancing Genomics Assisted Breeding in Apple and Cannabis

Abstract

Apple and cannabis are two economically and culturally important crops grown around the world for a diversity of end uses. Both apple and cannabis stand to benefit immensely from genomics assisted breeding. Discovering the genetic control of key traits is necessary to advance genomics assisted breeding of both apple and cannabis. The objective of this thesis was to characterize genomic and phenotypic diversity across apple and cannabis and leverage insights from genotype-phenotype associations to uncover the genetic control of key traits. To accomplish the outlined objectives, I first undertook a phenomic characterization of Canada’s Apple Biodiversity Collection (ABC) to quantify apple phenotypic diversity across 39 fruit quality and phenology traits from over 20,000 individual apples sampled from 1,000 accessions. I measured a wide range of phenotypic variation that can be leveraged for future apple improvement. For example, apples varied 61-fold in weight, 18-fold in acidity, and 100-fold in phenolic content. I measured dramatic changes to apple physiology that occurred during 3 months of cold storage: on average, apples lost 39% of their firmness, 31% of their acidity, and 9% of their weight, but gained 7% in soluble solids. Next, I paired the apple phenotype data with over 260,000 genetic markers sequenced across the ABC and conducted genome-wide association studies (GWAS) to uncover genetic markers associated with fruit quality and phenology traits. I identified novel associations for phenolic content and an association for softening that overlapped with a previously reported locus. In addition, I identified that allelic variation at the NAC18.1 transcription factor was associated with numerous ripening related traits including harvest date, firmness at harvest, and firmness after storage. Next, I used over 100,000 genetic markers across more than 137 Cannabis samples to conduct GWAS for 40 chemical compounds. In addition, I examined the genetic and chemical basis for cannabis labelling. I found that overall Indica/Sativa labelled samples were genetically and chemically indistinct. However, I identified variation in the content of three sesquiterpenes that was associated with Indica/Sativa labels and was also controlled by genetic variation at tandem arrays of terpene synthase genes. Finally, in Chapter 5, I use apple as a case study to outline a pathway for how putatively causal genetic variants identified from GWAS can be leveraged to develop new cultivars through gene editing. While cannabis and apple each face unique challenges in their cultivation and breeding, the research presented here provides a solid foundation for the genomics-assisted improvement of new cultivars in both crops.